Abdulwahid, WM & Pradhan, B 2017, 'Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)', Landslides, vol. 14, no. 3, pp. 1057-1076.
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Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the de...
Adak, C, Chaudhuri, BB & Blumenstein, M 2017, 'An Empirical Study on Writer Identification & Verification from Intra-variable Individual Handwriting', IEEE Access, vol. 7, pp. 24738-24758.
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The handwriting of an individual may vary substantially with factors such asmood, time, space, writing speed, writing medium and tool, writing topic, etc.It becomes challenging to perform automated writer verification/identificationon a particular set of handwritten patterns (e.g., speedy handwriting) of aperson, especially when the system is trained using a different set of writingpatterns (e.g., normal speed) of that same person. However, it would beinteresting to experimentally analyze if there exists any implicitcharacteristic of individuality which is insensitive to high intra-variablehandwriting. In this paper, we study some handcrafted features and auto-derivedfeatures extracted from intra-variable writing. Here, we work on writeridentification/verification from offline Bengali handwriting of highintra-variability. To this end, we use various models mainly based onhandcrafted features with SVM (Support Vector Machine) and featuresauto-derived by the convolutional network. For experimentation, we havegenerated two handwritten databases from two different sets of 100 writers andenlarged the dataset by a data-augmentation technique. We have obtained someinteresting results.
Aghdam, IN, Pradhan, B & Panahi, M 2017, 'Landslide susceptibility assessment using a novel hybrid model of statistical bivariate methods (FR and WOE) and adaptive neuro-fuzzy inference system (ANFIS) at southern Zagros Mountains in Iran', Environmental Earth Sciences, vol. 76, no. 6, pp. 1-22.
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The aim of landslide susceptibility mapping (LSM) is to produce the most important and basic information required for overall landslide disaster planning and mitigation. Different statistical bivariate methods such as frequency ratio (FR) and weights-of-evidence (WOE) have been widely used for LSM. Although results of these aforementioned statistical methods are generally acceptable, however, they can be improved further by fine tuning the conditioning factor’s classes. The purpose of this paper is to overcome some drawbacks of the bivariate models by developing a novel hybrid method using adaptive neuro-fuzzy inference system (ANFIS) and statistical bivariate methods (FR and WOE) in geographical information system. The provinces of southern Zagros Mountains (Iran) are chosen as a case study to implement the proposed method. First, landslide inventory map was produced using various data source such as historical landslides locations, remote sensing images and land surveying techniques. Second, the inventory data were divided into a ratio 70:30 for training and testing the models. Third, twelve landslide conditioning and triggering factors (such as altitude, slope, aspect, plan and profile curvatures, distance to roads, distance to streams, distance to faults, rainfall, seismicity, land use and lithology) were selected and categorized in two groups consisting of numerical and nominal values. Then, each conditioning factor was classified and the weight of each class was determined by using FR and WOE models. The outputs of individual statistical and hybrid methods were applied to determine nominal and continuous numerical data, respectively. In the hybrid approach, the calculated weights of each class were allocated to the center of each class, and the rest of the weights were determined by ANFIS. Landslide locations which were not used in training the models were used for validation. The produced susceptibility maps were validated and compared using area under the...
Ajaj, QM, Pradhan, B, Noori, AM & Jebur, MN 2017, 'Spatial Monitoring of Desertification Extent in Western Iraq using Landsat Images and GIS', Land Degradation & Development, vol. 28, no. 8, pp. 2418-2431.
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AbstractDesertification refers to land degradation in arid, semi‐arid, and dry sub‐humid areas caused by various factors, including climatic variations and human activities. In recent decades, sandstorms have increased significantly in Western Iraq, which primarily increased desert lands. Proper management is required to control and to monitor the phenomena, as well as to calculate the desertified areas caused by desertification. The study area covered 50,861.854 km2 in Western Iraq. Landsat‐5 TM, Landsat‐7 ETM+, and Landsat‐8 OLI data for 1990, 2002, and 2014 were used. Maximum likelihood algorithm was used to classify the images. Change detection results were discussed in two terms: short‐term (1990–2002) and (2002–2014) and long‐term (1990–2014) analysis. Change detection analysis from 1990 to 2014 showed that desert area increased to 2286.7308 km2, becoming a new source of dust storms. Hazard occurrence probability was studied on September and October 2014. The desertification amount decreased from 1990 to 2002 and increased significantly from 2002 to 2014. Sandstorms have recently been considered a hazardous phenomenon affecting the human population, the vegetation, and the ecosystem in Iraq. Copyright © 2017 John Wiley & Sons, Ltd.
Alaei, A, Pal, S, Pal, U & Blumenstein, M 2017, 'An Efficient Signature Verification Method Based on an Interval Symbolic Representation and a Fuzzy Similarity Measure', IEEE Transactions on Information Forensics and Security, vol. 12, no. 10, pp. 2360-2372.
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© 2017 IEEE. In this paper, an efficient offline signature verification method based on an interval symbolic representation and a fuzzy similarity measure is proposed. In the feature extraction step, a set of local binary pattern-based features is computed from both the signature image and its under-sampled bitmap. Interval-valued symbolic data is then created for each feature in every signature class. As a result, a signature model composed of a set of interval values (corresponding to the number of features) is obtained for each individual's handwritten signature class. A novel fuzzy similarity measure is further proposed to compute the similarity between a test sample signature and the corresponding interval-valued symbolic model for the verification of the test sample. To evaluate the proposed verification approach, a benchmark offline English signature data set (GPDS-300) and a large data set (BHSig260) composed of Bangla and Hindi offline signatures were used. A comparison of our results with some recent signature verification methods available in the literature was provided in terms of average error rate and we noted that the proposed method always outperforms when the number of training samples is eight or more.
Althuwaynee, OF & Pradhan, B 2017, 'Semi-quantitative landslide risk assessment using GIS-based exposure analysis in Kuala Lumpur City', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 706-732.
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Amiri, M, Tofigh, F, Ghafoorzadeh Yazdi, A & Abolhasan, M 2017, 'Exponential Antipodal Vivaldi Antenna With Exponential Dielectric Lens', IEEE Antennas and Wireless Propagation Letters, vol. 16, pp. 1-1.
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Basack, S & Nimbalkar, S 2017, 'Free strain analysis of the performance of vertical drains for soft soil improvement', Geomechanics and Engineering, vol. 13, no. 6, pp. 963-975.
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Improvement of soft clay deposit by preloading with vertical drains is one of the most popular techniques followed worldwide. These drains accelerate the rate of consolidation by shortening the drainage path. Although the analytical and numerical solutions available are mostly based on equal strain hypothesis, the adoption of free strain analysis is more realistic because of the flexible nature of the imposed surcharge loading, especially for the embankment loading used for transport infrastructure. In this paper, a numerical model has been developed based on free strain hypothesis for understanding the behaviour of soft ground improvement by vertical drain with preloading. The unit cell analogy is used and the effect of smear has been incorporated. The model has been validated by comparing with available field test results and thereafter, a hypothetical case study is done using the available field data for soft clay deposit existing in the eastern part of Australia and important conclusions are drawn therefrom.
Basack, S & Nimbalkar, S 2017, 'Numerical Solution of Single Pile Subjected to Torsional Cyclic Load', International Journal of Geomechanics, vol. 17, no. 8, pp. 04017016-04017016.
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© 2017 American Society of Civil Engineers. Large structures, such as offshore platforms, wind turbine foundations, wide buildings, bridges, and railway granular embankments, are often supported by pile foundations. These structures are usually subjected to large cyclic loads (in axial, lateral, and torsional modes) arising from actions of waves, ship impacts, or moving trains. Significant torsional cyclic forces can be transferred to the foundation piles due to the eccentricity of the lateral loads. In the past, several theoretical and experimental investigations were carried out on piles under axial and lateral cyclic loads; however, study of the influence of torsional cyclic loads on pile foundations is rather limited. This paper presents a novel numerical model based on the boundary element approach to analyze the response of a single, vertical, floating pile subjected to torsional cyclic load. The nonlinear stress-strain response of soil is incorporated, and the pile material was idealized as elastic-perfectly plastic. The effect of progressive degradation of soil strength and stiffness under cyclic stress reversal is incorporated in the numerical method. Apart from predicting the degradation of torsional pile-soil interactive performance, the profiles for shear stress and angle of twist are also captured by the proposed solution. Validation of the model indicates the suitability and accuracy of the proposed solutions. The frequency, amplitude, and number of cycles play significant roles in torsional cyclic response of piles. The proposed model is also applied successfully to selected case studies on single piles under torsional cyclic loading, and important conclusions are drawn from there.
Basack, S, Indraratna, B, Rujikiatkamjorn, C & Siahaan, F 2017, 'Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 6, pp. 04017016-04017016.
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Burton, GJ, Pineda, JA, Sheng, D, Airey, DW, Zhang, F, Rawat, A, Al-Badran, YM & Schanz, T 2017, 'Exploring one-dimensional compression of compacted clay under constant degree of saturation paths', Géotechnique, vol. 67, no. 1, pp. 86-90.
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Cai, Q, Turner, BD, Sheng, D & Sloan, S 2017, 'Impact of Barium and Cadmium on Defluoridation by Calcite: Batch Reactor and Column Tests', Environmental Engineering Science, vol. 34, no. 11, pp. 792-804.
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Cai, Y, Chen, Q, Zhou, Y, Nimbalkar, S & Yu, J 2017, 'Estimation of Passive Earth Pressure against Rigid Retaining Wall Considering Arching Effect in Cohesive-Frictional Backfill under Translation Mode', International Journal of Geomechanics, vol. 17, no. 4, pp. 04016093-04016093.
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n this study, a novel analytical approach is proposed to calculate the passive earth pressure against a rigid retaining wall subjected to the translation mode. Effects of arching in cohesive backfill soils as well as friction mobilized along the wall–soil interface are considered. Analytical expressions of the earth pressure, passive resistance, and its height of application on the backface of the retaining wall were derived based on static equilibrium of forces under passive conditions acting on the failure wedge. A parametric study was undertaken to assess effects of internal friction angle of backfill, wall–soil interface friction angle, surcharge pressure, cohesion, unit weight, and inclination angle of the slip surface on the active earth pressure as well as on the slip-surface angle. The results of the proposed method were then verified against the existing test data as well as the predictions by Coulomb theory and Rankine theory. The results show that the proposed method yields satisfactory results
Chen, W, Xie, X, Wang, J, Pradhan, B, Hong, H, Bui, DT, Duan, Z & Ma, J 2017, 'A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility', CATENA, vol. 151, pp. 147-160.
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© 2016 Elsevier B.V. The main purpose of the present study is to use three state-of-the-art data mining techniques, namely, logistic model tree (LMT), random forest (RF), and classification and regression tree (CART) models, to map landslide susceptibility. Long County was selected as the study area. First, a landslide inventory map was constructed using history reports, interpretation of aerial photographs, and extensive field surveys. A total of 171 landslide locations were identified in the study area. Twelve landslide-related parameters were considered for landslide susceptibility mapping, including slope angle, slope aspect, plan curvature, profile curvature, altitude, NDVI, land use, distance to faults, distance to roads, distance to rivers, lithology, and rainfall. The 171 landslides were randomly separated into two groups with a 70/30 ratio for training and validation purposes, and different ratios of non-landslides to landslides grid cells were used to obtain the highest classification accuracy. The linear support vector machine algorithm (LSVM) was used to evaluate the predictive capability of the 12 landslide conditioning factors. Second, LMT, RF, and CART models were constructed using training data. Finally, the applied models were validated and compared using receiver operating characteristics (ROC), and predictive accuracy (ACC) methods. Overall, all three models exhibit reasonably good performances; the RF model exhibits the highest predictive capability compared with the LMT and CART models. The RF model, with a success rate of 0.837 and a prediction rate of 0.781, is a promising technique for landslide susceptibility mapping. Therefore, these three models are useful tools for spatial prediction of landslide susceptibility.
Cheng, S, Yu, L, Zhang, D & Ji, J 2017, 'Consensus of multiple Euler-Lagrange systems using one Euler-Lagrange System’s velocity measurements', International Journal of Control, Automation and Systems, vol. 15, no. 1, pp. 450-456.
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© 2016, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg. This brief paper studies the stationary consensus of multiple Euler-Lagrange systems with nonlinear protocols. Two consensus protocols are given to guarantee that positions and velocities of multiple Euler-Lagrange systems reach consensus. Proposed protocols need only the relative position measurements and the velocity measurements of one Euler-Lagrange system. Finally, numerical simulations are given to illustrate the theoretical results.
Cooper, CS, Franklin, DR, Ros, M, Safaei, F & Abolhasan, M 2017, 'A Comparative Survey of VANET Clustering Techniques.', IEEE Commun. Surv. Tutorials, vol. 19, no. 1, pp. 657-681.
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A vehicular ad hoc network (VANET) is a mobile ad hoc network (MANET) in which network nodes are vehicles – most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organised nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, inforomation dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming – the lack of realistic vehicular channel modelling – is identified. The importance of a rigorous and standardised performance evaluation regime utilising realistic vehicular channel models is demonstrated.
Dackermann, U, Yu, Y, Niederleithinger, E, Li, J & Wiggenhauser, H 2017, 'Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines', Sensors, vol. 17, no. 12, pp. 2938-2938.
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This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%.
Dantas Neto, SA, Indraratna, B, Oliveira, DAF & de Assis, AP 2017, 'Modelling the Shear Behaviour of Clean Rock Discontinuities Using Artificial Neural Networks', Rock Mechanics and Rock Engineering, vol. 50, no. 7, pp. 1817-1831.
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Deng, Y, Kan, ME, Indraratna, B & Zhong, R 2017, 'Finite Element Analysis of Vacuum Consolidation With Modified Compressibility and Permeability Parameters', International Journal of Geosynthetics and Ground Engineering, vol. 3, no. 2.
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© 2017, Springer International Publishing Switzerland. Laboratory tests and case history studies indicate that soil subjected to vacuum preloading may not behave the same as ground treated by traditional surcharge preloading. In detail, soil compression under vacuum pressure is smaller than or equal to that induced by positive pressure with the same magnitude; soil rebound after stopping the vacuum is not as high as after removing the surcharge; and the consolidation rate is usually faster under vacuum pressure than with surcharge preloading. Analysis of vacuum consolidation with existing methods cannot gain all these differences. Thus, in this study, three factors for adjusting compressibility and permeability are proposed based on past laboratory and field results which are used in a finite element analysis of soft soil foundation under vacuum-assisted preloading. This proposed method can be incorporated in existing computer programs associated with classical soil models (e.g., the modified Cam-Clay model and the Soft-Soil model); it is then examined via three distinct simulation scenarios including a laboratory model test and two prototype field cases. The improved accuracy in relation to consolidation by the proposed method is demonstrated and practical ranges for the adjustment factors are discussed.
Deng, Y-B, Liu, G-B, Indraratna, B, Rujikiatkamjorn, C & Xie, K-H 2017, 'Model Test and Theoretical Analysis for Soft Soil Foundations Improved by Prefabricated Vertical Drains', International Journal of Geomechanics, vol. 17, no. 1, pp. 04016045-04016045.
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Ghosh, B, Fatahi, B & Khabbaz, H 2017, 'Analytical Solution to Analyze LTP on Column-Improved Soft Soil Considering Soil Nonlinearity', International Journal of Geomechanics, vol. 17, no. 3, pp. 04016082-04016082.
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© 2016 American Society of Civil Engineers. In this paper, a mechanical model to idealize the load-settlement response of the load transfer platform (LTP) on column-improved soft soil is proposed. This model simultaneously considers the nonlinear and time-dependent stress-strain behavior of soft soil and the negligible tensile strength of the granular material in LTP. The reinforced Timoshenko beam is adopted to model LTP to consider the shear and flexural deformations. Soft soil is idealized by a spring-dashpot system that includes nonlinear and time-dependent behaviors. The columns and geosynthetics are modeled with linear Winkler springs in the applied range of stresses and rough elastic membrane, respectively. The response function of LTP has been derived for distributed pressure loading in the plane strain condition. The principle of superposition is used to solve the fourth-order differential equations. Parametric studies indicate that the spacing of columns, thickness of LTP, degree of consolidation of the soft soil, and tensile stiffness of the geosynthetics significantly affect the behavior of LTP. This study also evaluates the accuracy of using reinforced Timoshenko theory by comparing the results with Pasternak and Euler-Bernoulli theories.
Ghosh, B, Fatahi, B, Khabbaz, H & Yin, J-H 2017, 'Analytical study for double-layer geosynthetic reinforced load transfer platform on column improved soft soil', Geotextiles and Geomembranes, vol. 45, no. 5, pp. 508-536.
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© 2017 The objective of this study is to propose a reasonably accurate mechanical model for double-layer geosynthetic reinforced load transfer platform (LTP) on column reinforced soft soil which can be used by practicing engineers. The developed model is very useful to study the behaviour of LTP resting on soft soil improved with conventional columns such as concrete columns, piles, and deep soil mixing columns. The negligible tensile strength of granular material in LTP, bending and shear deformations of LTP, compressibility and shearing of soft soil have been incorporated in the model. Furthermore, the results from the proposed model simulating the soft soil as Kerr foundation model are compared to the corresponding solutions when the soft soil is idealised by Winkler and Pasternak foundation models. It is observed from the comparison that the presented model can be used as a tool for a better prediction of the LTP behaviour with multi layers of geosynthetics, in comparison with the situation that soft soil is modelled by Winkler and Pasternak foundations. Furthermore, parametric studies show that as the column spacing increases, the maximum deflection of LTP and normalised tension in the geosynthetics also increase. Whereas, the maximum deflection of LTP and normalised tension in the geosynthetics decrease with increasing LTP thickness, stiffness of subsoil, and stiffness of geosynthetic reinforcement. In addition, it is observed that the use of one stronger geosynthetic layer (e.g. 1 × 2000 kN/m) with the equivalent stiffness of two geosynthetic layers (e.g. 2 × 1000 kN/m) does not result in the same settlement of LTP and the tension of the geosynthetic reinforcement when compared to two weaker geosynthetic layers.
Gibril, MBA, Bakar, SA, Yao, K, Idrees, MO & Pradhan, B 2017, 'Fusion of RADARSAT-2 and multispectral optical remote sensing data for LULC extraction in a tropical agricultural area', Geocarto International, vol. 32, no. 7, pp. 735-748.
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In this study, we investigated the performance of different fusion and classification techniques for land cover mapping in Hilir Perak, Peninsula Malaysia using RADAR and Landsat-8 images in a predominantly agricultural area. The fusion methods used are Brovey Transform, Wavelet Transform, Ehlers and Layer Stacking and their results classified into seven different land cover classes which include (1) pixel-based classifiers (spectral angle mapper (SAM), maximum likelihood (ML), support vector machine (SVM)) and (2) Object-based (rule-based and standard nearest neighbour (NN)) classifiers. The result shows that pixel-based classification achieved maximum accuracy of the optical data classification using SVM in Landsat-8 with 74.96% accuracy compared to SAM and ML. For multisource data classification, the highest overall accuracy recorded for layer stacking (SVM) was 79.78%, Ehlers fusion (SVM) with 45.57%, Brovey fusion (SVM) with 63.70% and Wavelet fusion (SVM) 61.16%. And for object-based classifiers, the overall classification accuracy is 95.35% for rule-based and 76.33% for NN classifier, respectively. Based on the analysis of their performances, object-based and the rule-based classifiers produced the best classification accuracy from the fused images.
Gu, X, Yu, Y, Li, J & Li, Y 2017, 'Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model', Journal of Sound and Vibration, vol. 406, pp. 346-362.
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© 2017 Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.
Halkon, BJ & Rothberg, SJ 2017, 'Reprint of: Taking laser Doppler vibrometry off the tripod: correction of measurements affected by instrument vibration', Optics and Lasers in Engineering, vol. 99, pp. 3-10.
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© 2017. Laser Doppler vibrometers (LDVs) are now well-established as an effective non-contact alternative to traditional contacting transducers. Despite 30 years of successful applications, however, very little attention has been given to sensitivity to vibration of the instrument itself. In this paper, the sensitivity to instrument vibration is confirmed before development theoretically and experimentally of a practical scheme to enable correction of measurements for arbitrary instrument vibration. The scheme requires a pair of correction sensors with appropriate orientation and relative location, while using frequency domain processing to accommodate inter-channel time delay and signal integrations. Error reductions in excess of 30. dB are delivered in laboratory tests with simultaneous instrument and target vibration over a broad frequency range. Ultimately, application to measurement on a vehicle simulator experiencing high levels of vibration demonstrates the practical nature of the correction technique and its robustness in a challenging measurement environment.
Halkon, BJ & Rothberg, SJ 2017, 'Restoring high accuracy to laser Doppler vibrometry measurements affected by vibration of beam steering optics', Journal of Sound and Vibration, vol. 405, pp. 144-157.
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© 2017 Elsevier Ltd Laser Doppler vibrometers are now well-established as an effective non-contact alternative to traditional contacting transducers. Wide-ranging applications include those where beam steering optics are required to reach locations that are difficult to access but no attention has yet been given to measurement sensitivity to the vibration of those optics. In this paper, a thorough mathematical treatment of this sensitivity to steering optic vibration and its correction is set out. A very practical scheme requiring a single correction measurement, from the back-surface of the mirror at the incidence point and aligned with the mirror normal, delivers an error reduction typically in excess of 30 dB. After validation in the laboratory, the scheme is then applied to a genuinely challenging measurement scenario on a single cylinder racing motorcycle. Correction is theoretically perfect for translational mirror vibrations but angular mirror vibrations require an adapted scheme using a triplet of accelerometers arranged around a circular path on the mirror back-surface and this is set out theoretically.
Halkon, BJ & Rothberg, SJ 2017, 'Taking laser Doppler vibrometry off the tripod: correction of measurements affected by instrument vibration', Optics and Lasers in Engineering, vol. 91, pp. 16-23.
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© 2016 Elsevier Ltd Laser Doppler vibrometers (LDVs) are now well-established as an effective non-contact alternative to traditional contacting transducers. Despite 30 years of successful applications, however, very little attention has been given to sensitivity to vibration of the instrument itself. In this paper, the sensitivity to instrument vibration is confirmed before development theoretically and experimentally of a practical scheme to enable correction of measurements for arbitrary instrument vibration. The scheme requires a pair of correction sensors with appropriate orientation and relative location, while using frequency domain processing to accommodate inter-channel time delay and signal integrations. Error reductions in excess of 30 dB are delivered in laboratory tests with simultaneous instrument and target vibration over a broad frequency range. Ultimately, application to measurement on a vehicle simulator experiencing high levels of vibration demonstrates the practical nature of the correction technique and its robustness in a challenging measurement environment.
He, X, Cai, G, Zhao, C & Sheng, D 2017, 'On the stress-force-fabric equation in triaxial compressions: Some insights into the triaxial strength', Computers and Geotechnics, vol. 85, pp. 71-83.
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The strength of granular materials during triaxial compression is investigated via a grain scale analysis in this paper. A 3D Discrete Element Method (DEM) program provides the triaxial strength data and helps to validate the micromechanical analysis. Some standard methods in statistics are employed first to quantitatively examine the assumptions made when deriving the stress-force-fabric (SFF) equation. After careful validation, a more concise format for the SFF equation is proposed for triaxial compressions. With this SFF equation, the strength is found to be jointly contributed by the magnitudes of the contact force anisotropy and fabric anisotropy. The influence of the initial void ratio, confining pressure and loading direction on the development of contact force anisotropy and fabric anisotropy is examined and presented. With similar techniques, the “force” term in the SFF equation is further decoupled, and an equation is obtained such that it explicitly links the contact force term with the friction coefficient between grains, a tensor defined as a statistic of the normal contact forces and a tensor defined as a statistic of the mobilisation status of contacts. Based on this equation, another equation regarding the stress ratio of granular assembly is obtained, and it clearly indicates two sources that contribute to the phenomenological friction nature of granular assembly. These two sources are caused by the contact force at the grain scale. The first is the anisotropy of the average normal contact forces, and the second is the mobilisation of contacts.
Ho, L & Fatahi, B 2017, 'Axisymmetric Consolidation in Unsaturated Soil Deposit Subjected to Time-Dependent Loadings', International Journal of Geomechanics, vol. 17, no. 2, pp. 04016046-04016046.
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© 2016 American Society of Civil Engineers. This paper presents an analytical solution to predict the axisymmetric consolidation in unsaturated soil deposits subjected to different time-dependent loadings. The mathematical procedure uses the separation of variables and Laplace transformation methods to obtain the final solution. A set of polar governing equations of flow are obtained and presented under the partial differential equations (PDEs), and then the variable separation technique is used to alter the PDEs to ordinary differential equations (ODEs) consisting of distinctive variables. Fourier Bessel and sine series are used to present functions of radial and vertical flows, respectively, and the Laplace transformation is used to obtain a function of time. Four primary time-dependent loading functions, including ramping, asymptotic, sinusoid, and damped sine wave, are mathematically simulated and incorporated into the proposed solutions. This study investigates changes in excess pore-air and pore-water pressures as well as consolidation settlement against the air-to-water permeability ratio and various loading parameters. Moreover, changes in suction and net stress induced by ramped and asymptotic loadings are also presented in the worked examples.
Hong, H, Chen, W, Xu, C, Youssef, AM, Pradhan, B & Tien Bui, D 2017, 'Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy', Geocarto International, vol. 32, no. 2, pp. 1-16.
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© 2016 Taylor & Francis. The main objective of the study was to evaluate and compare the overall performance of three methods, frequency ratio (FR), certainty factor (CF) and index of entropy (IOE), for rainfall-induced landslide susceptibility mapping at the Chongren area (China) using geographic information system and remote sensing. First, a landslide inventory map for the study area was constructed from field surveys and interpretations of aerial photographs. Second, 15 landslide-related factors such as elevation, slope, aspect, plan curvature, profile curvature, stream power index, sediment transport index, topographic wetness index, distance to faults, distance to rivers, distance to roads, landuse, NDVI, lithology and rainfall were prepared for the landslide susceptibility modelling. Using these data, three landslide susceptibility models were constructed using FR, CF and IOE. Finally, these models were validated and compared using known landslide locations and the receiver operating characteristics curve. The result shows that all the models perform well on both the training and validation data. The area under the curve showed that the goodness-of-fit with the training data is 79.12, 80.34 and 80.42% for FR, CF and IOE whereas the prediction power is 80.14, 81.58 and 81.73%, for FR, CF and IOE, respectively. The result of this study may be useful for local government management and land use planning.
Hong, H, Liu, J, Zhu, A-X, Shahabi, H, Pham, BT, Chen, W, Pradhan, B & Bui, DT 2017, 'A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)', Environmental Earth Sciences, vol. 76, no. 19, pp. 1-19.
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This study proposed a hybrid modeling approach using two methods, support vector machines and random subspace, to create a novel model named random subspace-based support vector machines (RSSVM) for assessing landslide susceptibility. The newly developed model was then tested in the Wuning area, China, to produce a landslide susceptibility map. With the purpose of achieving the objective of the study, a spatial dataset was initially constructed that includes a landslide inventory map consisting of 445 landslide regions. Then, various landslide-influencing factors were defined, including slope angle, aspect, altitude, topographic wetness index, stream power index, sediment transport index, soil, lithology, normalized difference vegetation index, land use, rainfall, distance to roads, distance to rivers, and distance to faults. Next, the result of the RSSVM model was validated using statistical index-based evaluations and the receiver operating characteristic curve approach. Then, to evaluate the performance of the suggested RSSVM model, a comparison analysis was performed to other existing approaches such as artificial neural network, Naïve Bayes (NB) and support vector machine (SVM). In general, the performance of the RSSVM model was better than the other models for spatial prediction of landslide susceptibility. The AUC results of the applied models are as follows: RSSVM (AUC = 0.857), followed by MLP (AUC = 0.823), SVM (AUC = 0.814) and NB (AUC = 0.783). The present study indicates that RSSVM can be used for landslide susceptibility evaluation, and the results are very useful for local governments and people living in the Wuning area.
Hong, H, Pradhan, B, Bui, DT, Xu, C, Youssef, AM & Chen, W 2017, 'Comparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China)', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 544-569.
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Suichuan is a mountainous area at the Jiangxi province in Central China, where rainfall-induced landslides occur frequently. The purpose of this study is to assess landslide susceptibility of this region using support vector machine (SVM) with four kernel functions: polynomial (PL), radial basis function (RBF), sigmoid (SIG), and linear (LN). A total of 178 landslides were used to accomplish this approach, of which, 125 (70%) landslides were randomly selected for training the landslide susceptibility models, whereas the remaining 53 (30%) were used for the model validation. Fifteen landslide conditioning factors were considered including slope-angle, altitude, slope-aspect, topographic wetness index (TWI), sediment transport index (STI), stream power index (SPI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, precipitation, landuse, normalized difference vegetation index (NDVI), and lithology. Using the training dataset, nine landslide susceptibility models for the Suichuan area were constructed with the four kernel functions. To evaluate the performance of these models, the receiver-operating characteristic curve (ROC) and area under the curve (AUC) were used. Using the training dataset, AUC values for the SVM-PL models with six degrees PL function (1–6) are 0.715, 0.801, 0.856, 0.891, 0.919, 0.953, respectively, and for the SVM-RBF model, the SVM-SIG model, and the SVM-LN model are 0.716, 0.741, and 0.740, respectively. Using the validation dataset, AUC values for the SVM-PL models with six degrees PL function (1–6) are 0.738, 0.730, 0.683, 0.648, 0.608, and 0.598, respectively, and for the SVM-RBF model, the SVM-SIG model, and the SVM-LN model are 0.716, 0.741, and 0.740, respectively. Our results suggested that the SVM-RBF model is the most suitable for landslide susceptibility assessment for the study area.
Hong, H, Pradhan, B, Sameen, MI, Chen, W & Xu, C 2017, 'Spatial prediction of rotational landslide using geographically weighted regression, logistic regression, and support vector machine models in Xing Guo area (China)', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 1997-2022.
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Indraratna, B & Sun, Y 2017, 'Closure to “Laboratory Assessment of the Role of Particle Size Distribution on the Deformation and Degradation of Ballast under Cyclic Loading” by Buddhima Indraratna, Yifei Sun, and Sanjay Nimbalkar', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 9, pp. 07017023-07017023.
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Indraratna, B, Baral, P, Ameratunga, J & Kendaragama, B 2017, 'Potential biological and chemical clogging of piezometer filters in acid sulphate soil', Australian Geomechanics Journal, vol. 52, no. 2, pp. 79-85.
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Instrumentation for performance monitoring of an embankment built on soft soils is vital for assessing the progress of consolidation and confirming (or refuting) soil parameters used in design when there are significant design uncertainties and the monitoring data can be used to calibrate the design soil parameters. A suite of instruments including settlement plates, extensometers, piezometers, inclinometers is often employed for this purpose. In the first Author's experience, erroneous readings interpretations of pore water pressure (PWP) readings have been reported in various case studies involving transport infrastructure development and reclamations works both in Australia and South East Asia, especially in low-lying acid sulphate soil floodplains. It has been observed that in spite of the presence of vertical drains (PVDs), excess pore water pressure readings from vibrating wire piezometers (VWPs) do not always dissipate as fast as expected especially after a certain period of time, typically a year. The article discusses the potential factors affecting the reliability of VWPs including filter tip clogging, extreme smearing of soil adjoining the filter, gas generation or cavitation, chemical alteration or corrosion of the filter, electro-osmotic effects and cavitation due to bacterial activity. Based on this, the response of VWPs may be divided into a distinct trilinear trend, observed for much of the Australian northern and eastern coastal belt that is predominantly affected by Acid sulphate soil (ASS) conditions where oxidisable pyrite layers are present within relatively shallow depths of the upper Holocene clay.
Indraratna, B, Ngo, NT & Rujikiatkamjorn, C 2017, 'Improved Performance of Ballasted Rail Tracks Using Plastics and Rubber Inclusions', Procedia Engineering, vol. 189, pp. 207-214.
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Current railroads require significant upgrading to meet the challenges of heavier loads at higher speeds. Due to excessive track degradation, the Australian rail industry spends large amounts on frequent track repair and maintenance, as well as ground improvement prior to track construction where soft and saturated subgrade soils pose considerable difficulties in design and construction. Moreover, the degradation of ballast particles under impact loading seriously hampers the safety and efficiency of rail tracks, which leads to speed restrictions and more frequent track upgrading. Hence, there is a need for innovative design solutions that can extend the service life of tracks to cater for faster and heavier train traffic. The use of planar geosynthetics and recycled rubber mats placed at the interface of ballast and subballast layer has proven an effective approach to mitigate ballast degradation and improve track longevity. This paper presents the current state-of-the-art knowledge of rail track geomechanics conducted at the University of Wollongong (UOW) including topics relating to laboratory testing and computational modeling approaches. The load-deformation responses of rubber mat/geogrid-stabilised ballast are studied in the laboratory using a large-scale drop weight impact testing facility, and Track Process Simulation Apparatus (TPSA). Numerical modelling using discrete element methods (DEM) are used to model geogrid-reinforced ballasted tracks, capturing both the discrete nature of ballast subject to various types of loading and boundary conditions. These results provide promising approaches to incorporate into the existing track design routines catering for future high speed and heavy haul trains.
Indraratna, B, Pathirage, PU & Banasiak, LJ 2017, 'Remediation of acidic groundwater by way of permeable reactive barrier', Environmental Geotechnics, vol. 4, no. 4, pp. 284-298.
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A permeable reactive barrier (PRB) was installed in the Shoalhaven Floodplain about 100 km south of Sydney (Australia), where acidic groundwater generation from pyritic soil poses a severe environmental and socioeconomic problem. Recycled concrete aggregates were a promising source of alkalinity-generating material and adopted as the reactive media for this PRB. The current study simulates the performance of the PRB through coupling geochemical reactions involved with recycled concrete and acidic groundwater with geohydraulics (transient groundwater flows). This is the first such attempt made for time-dependent modelling and performance verification of a PRB located in acid sulfate soil (ASS) terrain. The developed model describes the chemical clogging due to mineral precipitates and the associated reductions in porosity and hydraulic conductivity of the reactive medium. The governing equations of the model were incorporated into commercial software, MODFLOW and RT3D. The field results are in favourable agreement with the model predictions, confirming that the reduction in hydraulic conductivity due to mineral precipitation occurs predominantly at the entrance zone of the PRB and insignificantly in the middle and exit zones after 7 years of operation. Mineralogical analysis undertaken on sample specimens from the PRB also confirms that clogging is minimal at the entrance zone.
Indraratna, B, Sun, Q & Grant, J 2017, 'Behaviour of subballast reinforced with used tyre and potential application in rail tracks', Transportation Geotechnics, vol. 12, pp. 26-36.
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Rubber tyres have a three dimensional cylindrical structure, and as such could be used to stabilise foundations by increasing the bearing capacity and reducing settlement for transport infrastructure. It is therefore expected that in railroad engineering, a capping layer reinforced with rubber tyres could help to reduce the thickness of the granular layer (i.e. ballast), improve the track bearing capacity, and reduce the frequency of maintenance. However, there is a notable gap between the conceptual theories and real-life applications pertaining to the mechanisms of rubber tyre-reinforced foundations. In pavement engineering, the bearing capacity is closely linked to plate load tests. In this study, plate load tests were carried out on a single tyre filled with subballast material and subjected to a vertical load. This testing process was then modelled using the Finite Element software ABAQUS to study and quantify the interaction between the tyre and the granular medium. The experimental and numerical results reveal that the rubber tyre can significantly increase the modulus and ultimate bearing capacity of the granular layer. The numerical process was further extended to a finite element track model to demonstrate the expected response of a ballasted railway track with and without tyre reinforcement.
Indraratna, B, Sun, Q, Ngo, NT & Rujikiatkamjorn, C 2017, 'Current research into ballasted rail tracks: model tests and their practical implications', Australian Journal of Structural Engineering, vol. 18, no. 3, pp. 204-220.
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Ballasted rail tracks are the most important mode of transportation in terms of traffic tonnage serving the needs of bulk freight and passenger movement, but under train loads, the particles degrade due to breakage and the progressive accumulation of external fines or mud-pumping under the subgrade, all of which reduce its shear strength and increase track instability. These actions adversely affect the safety, passenger comfort and efficiency of tracks, as well as enforcing speed restrictions and more frequent track maintenance. In spite of advances in rail track geotechnology, the optimum choice of ballast for track design is still considered critical because ballast degradation is influenced by the amplitude and number of load cycles, particle gradation, track confining pressure and the angularity and fracture strength of individual grains. One of the most effective methods of enhancing track stability and reducing the stresses transmitted to a soft subgrade layer is to increase the stiffness of the overlying granular media. This paper presents our current knowledge of rail track geomechanics, including important concepts/topics related to laboratory testing and computational modelling approaches used to study the load–deformation behaviour of ballast improved with waste tyres, synthetic geogrids and geocells.
Indraratna, B, Zhong, R, Fox, PJ & Rujikiatkamjorn, C 2017, 'Large-Strain Vacuum-Assisted Consolidation with Non-Darcian Radial Flow Incorporating Varying Permeability and Compressibility', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 1, pp. 04016088-04016088.
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Israr, J & Indraratna, B 2017, 'Internal Stability of Granular Filters under Static and Cyclic Loading', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 6, pp. 04017012-04017012.
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Jaber, HS, Mansor, S, Pradhan, B & Ahmad, N 2017, 'Rainfall–runoff modelling and water balance analysis for Al-Hindiyah barrage, Iraq using remote sensing and GIS', Geocarto International, vol. 32, no. 12, pp. 1407-1420.
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Jamshidi Chenari, R, Fatahi, B, Akhavan Maroufi, MA & Alaie, R 2017, 'An Experimental and Numerical Investigation into the Compressibility and Settlement of Sand Mixed with TDA', Geotechnical and Geological Engineering, vol. 35, no. 5, pp. 2401-2420.
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A series of large scale oedometer experiments were carried out to investigate the settlement of sand reinforced with tire derived aggregates (TDA). The parameters studied were five different amounts of TDAs, three aspect ratios and relative skeletal densities, and seven overburden pressures. The volume compressibility coefficient was calculated against different input parameters, and the constraint condition used enabled Poisson’s ratio to be calculated from an “at-rest” coefficient of earth pressure. The triaxial modulus was calculated indirectly and then adopted in subsequent numerical analyses. Finite element analysis and Monte Carlo simulations were used to investigate the settlement of this mixture and to study how the different parameters affected the settlement mixtures of sand and TDAs. The experimental and numerical results reveal that the amount of TDAs is the major parameter which affects settlement, although the overburden pressure and relative skeletal density are also important. The aspect ratio of the shred has almost no effect on volume compressibility parameters as long as constraint compression condition governs. Two index parameters were defined to discuss the type of shred distribution and how it affects settlement of the mixture.
Ji, J 2017, 'Stability of the coupled vibrations of work roll and strip in cold rolling process', Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 231, no. 7, pp. 1169-1181.
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Undesirable vibrations that occurred in cold rolling mills, widely known as chatter, are studied in this article by considering the interaction of three types of vibrations, namely, the longitudinal vibration of the rolled strip and the torsional and vertical vibrations of the upper work roll. The dynamic component of rolling force is determined using the quasi-static model under the assumption that the changes in roll gap and strip tension produce the variation of rolling force. The coupled vibrations of the work roll and rolled strip are mathematically governed by a set of 3-degree-of-freedom non-linear equations. Under chatter conditions, a new variable is introduced to represent the motion of the quasi-neutral point. A stability criterion for the motion of the quasi-neutral point is developed by studying the eigenvalues of the corresponding characteristic equation of the linearized parts of the non-linear equations. The chatter stability can then be examined by evaluating the determinants of five matrices. Numerical examples are given to show the stable and unstable vibrations in the cold rolling process. The unstable vibration would lead to skidding phenomenon and even break the rolled strip. The results presented in this article provide new insights into the dynamic interaction of the coupled vibrations and the dynamics of the rolling process.
Ji, JC & Brown, T 2017, 'Periodic and Chaotic Motion of a Time-Delayed Nonlinear System Under Two Coexisting Families of Additive Resonances', International Journal of Bifurcation and Chaos, vol. 27, no. 05, pp. 1750066-1750066.
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A time-delayed quadratic nonlinear mechanical system can exhibit two coexisting stable bifurcating solutions (SBSs) after two-to-one resonant Hopf bifurcations occur in the corresponding autonomous time-delayed system. One SBS is of small-amplitude and has the Hopf bifurcation frequencies (HBFs), while the other is of large-amplitude and contains the shifted Hopf bifurcation frequencies (the shifted HBFs). When the forcing frequency is tuned to be the sum of two HBFs or the sum of two shifted HBFs, two families of additive resonances can be induced in the forced response. The forced response under the additive resonance related to the HBFs can demonstrate periodic, quasi-periodic and chaotic motion. On the contrary, the forced response under the additive resonance associated with the shifted HBFs may exhibit period-three periodic motion and quasi-periodic motion. Bifurcation diagrams, time trajectories, frequency spectra, phase portraits and Poincaré sections are presented to show periodic, quasi-periodic, and chaotic motion of the time-delayed nonlinear system under the two families of additive resonances.
Ji, JC & Zhou, J 2017, 'Coexistence of two families of sub-harmonic resonances in a time-delayed nonlinear system at different forcing frequencies', Mechanical Systems and Signal Processing, vol. 93, pp. 151-163.
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© 2017 Elsevier Ltd Two coexisting families of sub-harmonic resonances can be induced at different forcing frequencies in a time-delayed nonlinear system having quadratic nonlinearities. They occur in the region where two stable bifurcating periodic solutions coexist in the corresponding autonomous system following two-to-one resonant Hopf bifurcations of the trivial equilibrium. The forced response is found to demonstrate small- and large-amplitude quasi-periodic motion under the family of sub-harmonic resonances related to Hopf bifurcation frequencies, and large-amplitude periodic and quasi-periodic motion under the family of sub-harmonic resonances associated with the shifted Hopf bifurcation frequencies. The family of sub-harmonic resonances related to Hopf bifurcation frequencies may cease to exist with the loss of the initially established frequency relationship of sub-harmonic resonances when the magnitude of periodic excitation is beyond a certain value. This will lead to a jump phenomenon from small- to large-amplitude quasi-periodic motion. Bifurcation diagrams, time trajectories and frequency spectra are numerically obtained to characterize the sub-harmonic resonances of the time-delayed nonlinear system around the critical point of the resonant Hopf bifurcations.
Jiang, YB, He, N, Xu, BH, Zhou, YZ & Zhang, ZL 2017, 'Model tests on negative pressure distribution in vacuum preloading', Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering, vol. 39, no. 10, pp. 1874-1883.
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The rule of negative pressure distribution is an important subject in the studies on vacuum preloading mechanism. By discussing the spatial distribution characteristics of vacuum preloading and the associated concepts, the negative pressure is defined in a broad sense, and the methods and influencing factors for the negative pressure measurement are analyzed. The tests are carried out, with a well-designed large scale indoor model 15 m in vertical height, to study the negative pressure distribution in vacuum preloading. The test results show that there is hysteresis effect in vacuum measurement in saturated clay soil, and the limit depth where vacuum exists is 8.9 m. The pore water pressure and vacuum degree in drain board exhibit a symmetrical linear distribution above zero pressure plane at the vacuum stable stage, and the slope is similar to hydrostatic pressure gradient. The negative pressure distribution along the depth is of piecewise linear type, due to the energy consumption in water lifting, attenuation is found in the unsaturated soil above the underground water level, and the average attenuation value is 21.4 kPa in the stable period. The negative pressure is uniform with no attenuation under the average water level, and the corresponding average negative pressure is -67.0 kPa within the depth scope of drainage board in the stable period. Based on the experimental results and the flow pattern distribution of gas-liquid two-phase flow in the equivalent drainage tube, the piecewise linear negative pressure boundary of the vertical drainage board in the stable period of vacuum preloading is put forward.
Jozi, B, Braun, R, Samali, B, Li, J & Dackermann, U 2017, 'Limitation of the Lateral Angled Broadband Low Frequency Impact Excitation on the Non-Destructive Condition Assessment of the Timber Utility Poles', International Journal of Advancements in Technology, vol. 08, no. 04, pp. 1-8.
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Timber utility poles play a significant role in the infrastructure of Australia as well as many other countries for power distribution and communication networks. Due to the advanced age of Australia’s timber pole infrastructure, substantial efforts are undertaken on maintenance and asset management to avoid any failures of the utility lines. Nevertheless, the lack of reliable tools for assessing the condition of in-service poles seriously jeopardizes the maintenance and asset management. For instance, each year approximately 300,000 poles are replaced in the Eastern States of Australia with up to 80% of them still being in a very good condition, resulting in major waste of natural resources and money. Non-destructive testing (NDT) methods based on stress wave propagation can potentially offer simple and cost-effective tools for identifying the in-service condition of timber poles. Nonetheless, most of the currently available methods are not appropriate for condition assessment of timber poles in-service due to presence of uncertainties such as complicated material properties, environmental conditions, interaction of soil and structure, and an impact excitation type. In order to address these complexities, advanced digital signal processing methodologies are needed to be employed. Deterministic signal separation, blind signal separation, and frequency-wavenumber velocity filtering are the three groups of methodologies, which could most probably provide solutions. In this paper applicability and effectiveness of the blind signal separation methods is investigated through a numerical data obtained from of a timber pole modelled with both isotropic and orthotropic material properties. Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and K-means clustering algorithms are the blind signal separation methodologies that are employed in this research work.
Kalantar, B, Mansor, S, Khuzaimah, Z, Ibrahim Sameen, M & Pradhan, B 2017, 'MODELLING MEAN ALBEDO OF INDIVIDUAL ROOFS IN COMPLEX URBAN AREASUSING SATELLITE IMAGES AND AIRBORNE LASER SCANNING POINT CLOUDS', The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W7, no. 2W7, pp. 237-240.
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Abstract. Knowledge of surface albedo at individual roof scale is important for mitigating urban heat islands and understanding urban climate change. This study presents a method for quantifying surface albedo of individual roofs in a complex urban area using the integration of Landsat 8 and airborne LiDAR data. First, individual roofs were extracted from airborne LiDAR data and orthophotos using optimized segmentation and supervised object based image analysis (OBIA). Support vector machine (SVM) was used as a classifier in OBIA process for extracting individual roofs. The user-defined parameters required in SVM classifier were selected using v-fold cross validation method. After that, surface albedo was calculated for each individual roof from Landsat images. Finally, thematic maps of mean surface albedo of individual roofs were generated in GIS and the results were discussed. Results showed that the study area is covered by 35% of buildings varying in roofing material types and conditions. The calculated surface albedo of buildings ranged from 0.16 to 0.65 in the study area. More importantly, the results indicated that the types and conditions of roofing materials significantly effect on the mean value of surface albedo. Mean albedo of new concrete, old concrete, new steel, and old steel were found to be equal to 0.38, 0.26, 0.51, and 0.44 respectively. Replacing old roofing materials with new ones should highly prioritized.
Kalantar, B, Mansor, SB, Sameen, MI, Pradhan, B & Shafri, HZM 2017, 'Drone-based land-cover mapping using a fuzzy unordered rule induction algorithm integrated into object-based image analysis', International Journal of Remote Sensing, vol. 38, no. 8-10, pp. 2535-2556.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. Land-cover maps provide essential data for a wide range of practical and small-scale applications. A number of data sources appropriate for land-cover extraction are available. Among these, images captured using unmanned aerial vehicles (UAVs) are low cost, have very high resolution, and can be acquired at any time with few restrictions. Over the past two decades, various classification techniques have been developed to extract land-cover features from UAV images, and object-based image analysis (OBIA) is the preferred technique based on the recent literature. This study presents a novel method that integrates the fuzzy unordered rule induction algorithm (FURIA) into OBIA to achieve accurate land-cover extraction from UAV images. The images were segmented using a multiresolution segmentation algorithm with an optimized scale parameter. The scale parameter was optimized using a novel approach that integrated feature space optimization into the plateau objective function. During the classification stage, significant features were selected via random forest, and rule sets were developed using FURIA. For comparison, result of the proposed approach was compared with those of decision tree (DT) rules and the Support Vector Machine (SVM) classification method. The results of this study indicate that the proposed method outperforms DT and SVM with an overall accuracy of 91.23%. A transferability evaluation showed that FURIA achieved accurate classification results on different UAV image subsets captured at different times. The findings suggest that fuzzy rules are more appropriate than conventional crisp rules for land-cover extraction from UAV images.
Khare, V, Shivakumara, P, Paramesran, R & Blumenstein, M 2017, 'Arbitrarily-oriented multi-lingual text detection in video', Multimedia Tools and Applications, vol. 76, no. 15, pp. 16625-16655.
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© 2016 Springer Science+Business Media New YorkText detection in arbitrarily-oriented multi-lingual video is an emerging area of research because it plays a vital role for developing real-time indexing and retrieval systems. In this paper, we propose to explore moments for identifying text candidates. We introduce a novel idea for determining automatic windows to extract moments for tackling multi-font and multi-sized text in video based on stroke width information. The temporal information is explored to find deviations between moving and non-moving pixels in successive frames iteratively, which results in static clusters containing caption text and dynamic clusters containing scene text, as well as background pixels. The gradient directions of pixels in static and dynamic clusters are analyzed to identify the potential text candidates. Furthermore, boundary growing is proposed that expands the boundary of potential text candidates until it finds neighbor components based on the nearest neighbor criterion. This process outputs text lines appearing in the video. Experimental results on standard video data, namely, ICDAR 2013, ICDAR 2015, YVT videos and on our own English and Multi-lingual videos demonstrate that the proposed method outperforms the state-of-the-art methods.
Kumara, C & Indraratna, B 2017, 'Normal Deformation and Formation of Contacts in Rough Rock Fractures and Their Influence on Fluid Flow', International Journal of Geomechanics, vol. 17, no. 1, pp. 04016022-04016022.
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Le, TM, Fatahi, B, Khabbaz, H & Sun, W 2017, 'Numerical optimization applying trust-region reflective least squares algorithm with constraints to optimize the non-linear creep parameters of soft soil', Applied Mathematical Modelling, vol. 41, pp. 236-256.
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© 2016 Determination of the creep model parameters is a challenging task particularly when a non-linear elastic visco-plastic (EVP) model is adopted, mainly due to the limited test duration as well as the assumption of the reference time. Therefore, this paper presents an innovative numerical solution to find the EVP model parameters applying the trust-region reflective least square optimization algorithm. The developed approach involves several available laboratory consolidation test results in the optimization procedure with the adopted commencing time to creep as a unit of time. In this paper, the laboratory results of Ottawa clay were employed to demonstrate the limitation of the recent method to obtain model parameters. Furthermore, the developed method is verified against Skå-Edeby clay in the laboratory conditions. The EVP model parameters are obtained by applying the developed method to the available laboratory consolidation results of clay samples. The analysis results of vertical strains and excess pore water pressures demonstrate that the developed method can be a feasible tool to estimate the settlement properties of clays.
Li, Y & Li, J 2017, 'On rate-dependent mechanical model for adaptive magnetorheological elastomer base isolator', Smart Materials and Structures, vol. 26, no. 4, pp. 045001-045001.
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© 2017 IOP Publishing Ltd. This paper presents research on the phenomenological model of an adaptive base isolator. The adaptive base isolator is made of field-dependent magnetorheological elastomer (MRE) which can alter its physical property under application of magnetic field. Experimental testing demonstrated that the developed MRE base isolator possesses an amazing ability to vary its stiffness under applied magnetic field. However, several challenges have been encountered when it comes modeling such novel device. For example, under a large deformation, the MRE base isolator exhibits a clear strain stiffening effect and this behavior escalates with the increasing of applied current. In addition, the MRE base isolator has also shown typical rate-dependent behavior. Following a review on mechanical models for viscos-elastic rubber devices, a novel rate-dependent model is proposed in this paper to capture the behavior of the new MRE base isolator. To develop a generalized model, the proposed model was evaluated using its performance under random displacement input and a seismic input. It shows that the proposed rate-dependent model can successfully describe the complex behavior of the device.
Liang, D, He, X & Zhang, J-X 2017, 'An ISPH model for flow-like landslides and interaction with structures', Journal of Hydrodynamics, vol. 29, no. 5, pp. 894-897.
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Liu, J, Miao, Z, Ji, J & Zhou, J 2017, 'Group Regional Consensus of Networked Lagrangian Systems With Input Disturbances', Journal of Dynamic Systems, Measurement, and Control, vol. 139, no. 9.
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Networked multirobot systems under the coordinated control can perform tasks more effectively than a group of individually operating robots. This paper studies the group regional consensus of networked multirobot systems (formulated by second-order Lagrangian dynamics) having input disturbances under directed acyclic topology. An adaptive control protocol is designed to achieve group regional consensus of the networked Lagrangian systems with parametric uncertainties for both leader and leaderless cases. Sufficient conditions are established to guarantee group regional consensus for any prior given desired consensus errors. Compared with the existing work, a distinctive feature of the proposed control algorithm is that the stability analysis indicates the global validity of the obtained consensus results. Numerical examples are provided to demonstrate the effectiveness of the proposed scheme.
Liu, MD & Indraratna, B 2017, 'Strength Criterion for Intact Rock', Indian Geotechnical Journal, vol. 47, no. 3, pp. 261-264.
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© 2016, Indian Geotechnical Society. Based on studies of the peak strength for soil by the authors, a simple strength criterion for intact rock is obtained in the general principal stress space. There are two material parameters in the equation. One is the uniaxial compression strength of the rock; the other describes the influence of stress level, and similar parameters are well studied in soil mechanics. It is seen that the proposed general strength criterion represents well the strength of various rocks and can provide a useful tool for geotechnical engineering practice.
Makki Alamdari, M, Samali, B, Li, J, Lu, Y & Mustapha, S 2017, 'Structural condition assessment using entropy-based time series analysis', Journal of Intelligent Material Systems and Structures, vol. 28, no. 14, pp. 1941-1956.
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We present a time-series-based algorithm to identify structural damage in the structure. The method is in the context of non-model-based approaches; hence, it eliminates the need of any representative numerical model of the structure to be built. The method starts by partitioning the state space into a finite number of subsets which are mutually exclusive and exhaustive and each subset is identified by a distinct symbol. Partitioning is performed based on a maximum entropy approach which takes into account the sparsity and distribution of information in the time series. After constructing the symbol space, the time series data are uniquely transformed from the state space into the constructed symbol space to create the symbol sequences. Symbol sequences are the simplified abstractions of the complex system and describe the evolution of the system. Each symbol sequence is statistically characterized by its entropy which is obtained based on the probability of occurrence of the symbols in the sequence. As a consequence of damage occurrence, the entropy of the symbol sequences changes; this change is implemented to define a damage indicative feature. The method shows promising results using data from two experimental case studies subject to varying excitation. The first specimen is a reinforced concrete jack arch which replicates one of the major structural components of the Sydney Harbor Bridge and the second specimen is a three-story frame structure model which has been tested at Los Alamos National Laboratory. The method not only could successfully identify the presence of damage but also has potential to localize it.
Meng, J, Huang, J, Sheng, D & Sloan, SW 2017, 'Granular contact dynamics with elastic bond model', Acta Geotechnica, vol. 12, no. 3, pp. 479-493.
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Meng, J, Huang, J, Sheng, D & Sloan, SW 2017, 'Quasi-Static Rheology of Granular Media Using the Static DEM', International Journal of Geomechanics, vol. 17, no. 11, pp. 04017094-04017094.
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Mezaal, MR, Pradhan, B, Sameen, MI, Mohd Shafri, HZ & Yusoff, ZM 2017, 'Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data', Applied Sciences, vol. 7, no. 7, pp. 730-730.
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An accurate inventory map is a prerequisite for the analysis of landslide susceptibility, hazard, and risk. Field survey, optical remote sensing, and synthetic aperture radar techniques are traditional techniques for landslide detection in tropical regions. However, such techniques are time consuming and costly. In addition, the dense vegetation of tropical forests complicates the generation of an accurate landslide inventory map for these regions. Given its ability to penetrate vegetation cover, high-resolution airborne light detection and ranging (LiDAR) has been used to generate accurate landslide maps. This study proposes the use of recurrent neural networks (RNN) and multi-layer perceptron neural networks (MLP-NN) in landscape detection. These efficient neural architectures require little or no prior knowledge compared with traditional classification methods. The proposed methods were tested in the Cameron Highlands, Malaysia. Segmentation parameters and feature selection were respectively optimized using a supervised approach and correlation-based feature selection. The hyper-parameters of network architecture were defined based on a systematic grid search. The accuracies of the RNN and MLP-NN models in the analysis area were 83.33% and 78.38%, respectively. The accuracies of the RNN and MLP-NN models in the test area were 81.11%, and 74.56%, respectively. These results indicated that the proposed models with optimized hyper-parameters produced the most accurate classification results. LiDAR-derived data, orthophotos, and textural features significantly affected the classification results. Therefore, the results indicated that the proposed methods have the potential to produce accurate and appropriate landslide inventory in tropical regions such as Malaysia.
Mezaal, MR, Pradhan, B, Shafri, HZM & Yusoff, ZM 2017, 'Automatic landslide detection using Dempster–Shafer theory from LiDAR-derived data and orthophotos', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 1935-1954.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. A good landslide inventory map is a prerequisite for landslide hazard and risk analysis. In tropical countries, such as Malaysia, preparation of the landslide inventory is a challenging task because of the rapid growth of vegetation. Thus, it is crucial to use rapid and accurate technique and effective parameters. For this purpose, Dempster Shafer theory (DST) was applied in fusing high resolution LiDAR derived data products and Greenness index derived from orthophoto imagery. Two sites were selected, for the implementation and evaluation of the DST model; site “A” for DST implementation and site “B” for the comparison. For model implementation, vegetation index, slope and height were used as effective parameters for identifying automatic landslide detection. Two type of DST based fusions were evaluated; (greenness and height) and (greenness and slope). Furthermore, validation techniques were used to validate the accuracy are confusion matrix and area under the curve. The overall accuracy of the first and second evaluated fusions were (73.4% and 84.33%), and area under the curve were (0.76 and 0.81) respectively. Additionally, the result was compa red with Random Forest (RF) based detection approach. The results showed that DST does not require a priori knowledge.
Mirzaghorbanali, A, Rasekh, H, Aziz, N, Yang, G, Khaleghparast, S & Nemcik, J 2017, 'Shear strength properties of cable bolts using a new double shear instrument, experimental study, and numerical simulation', Tunnelling and Underground Space Technology, vol. 70, pp. 240-253.
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© 2017 Elsevier Ltd A newly developed double shear apparatus without contact between concrete blocks was developed to conduct a series of double shear tests. This new double shear apparatus is capable of determining the pure shear strength of pre-tensioned fully grouted cable bolt without friction between sheared concrete blocks. Five different types of cable bolt, with various pretension loads, were tested to investigate the influence of surface profile type and pretension load on the shear strength of cable bolt. Concrete blocks of 40 MPa strength and the Stratabinder HS grout were used for consistency across the entire tests. The results showed that the plain cable bolts had higher peak shear load compared with the indented and spiral strand cable bolts. The shear displacement and peak shear load decreased by increasing the pretension load. A numerical analysis was carried out, based on the Fast Lagrangian Analysis of Continua (FLAC 2D) and the result was compared with the experimental data. It was observed that FLAC 2D is capable of simulating the performance of cable bolt satisfactorily.
Mojaddadi, H, Pradhan, B, Nampak, H, Ahmad, N & Ghazali, AHB 2017, 'Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 1080-1102.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. In this paper, an ensemble method, which demonstrated efficiency in GIS based flood modeling, was used to create flood probability indices for the Damansara River catchment in Malaysia. To estimate flood probability, the frequency ratio (FR) approach was combined with support vector machine (SVM) using a radial basis function kernel. Thirteen flood conditioning parameters, namely, altitude, aspect, slope, curvature, stream power index, topographic wetness index, sediment transport index, topographic roughness index, distance from river, geology, soil, surface runoff, and land use/cover (LULC), were selected. Each class of conditioning factor was weighted using the FR approach and entered as input for SVM modeling to optimize all the parameters. The flood hazard map was produced by combining the flood probability map with flood-triggering factors such as; averaged daily rainfall and flood inundation depth. Subsequently, the hydraulic 2D high-resolution sub-grid model (HRS) was applied to estimate the flood inundation depth. Furthermore, vulnerability weights were assigned to each element at risk based on their importance. Finally flood risk map was generated. The results of this research demonstrated that the proposed approach would be effective for flood risk management in the study area along the expressway and could be easily replicated in other areas.
Mokhtar, ES, Pradhan, B, Ghazali, AH & Shafri, HZM 2017, 'Comparative assessment of water surface level using different discharge prediction models', Natural Hazards, vol. 87, no. 2, pp. 1125-1146.
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Discharge is traditionally measured at gauge stations located at discrete positions along the river course. When the volume of water discharge is higher than the river bank, inundation to adjacent land occurs. Flood inundation mapping has largely relied on in situ discharge data. However, it cannot be accessed at ungauged sites. In recent literature, no comparative study on the impact of water level using different discharge models has been carried out. This paper evaluates the performance of three empirical formulas for discharge measurement to model flood inundation along Padang Terap River in Kedah, Malaysia, between October 31, 2010 and November 4, 2010. Water discharge was computed using three models, and the Manning-n values were assigned to the types of land use. Further, the rainfall obtained from gauge stations was interpolated using the Kriging interpolation method. Relative error and RMSE methods were used to evaluate the measured and predicted water surface elevation. The impact of predicted water surface elevation (WSE) from different land use types and terrain information was assessed. Dingman and Sharma’s model significantly presented good agreement between measured and predicted WSE with R 2 = 0.8034, followed by Manning and Bjerklie equations with 0.8024 and 0.7997, respectively. Moreover, Dingman and Sharma’s model produced less RE and RMSE with 13.09% and 2.27 m compared with the others. Therefore, the estimated discharge can be used in ungauged sites for flood inundation modeling. Manning-n, elevation, and slope affected the WSE.
Naghibi, SA, Moghaddam, DD, Kalantar, B, Pradhan, B & Kisi, O 2017, 'A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping', Journal of Hydrology, vol. 548, pp. 471-483.
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In recent years, application of ensemble models has been increased tremendously in various types of natural hazard assessment such as landslides and floods. However, application of this kind of robust models in groundwater potential mapping is relatively new. This study applied four data mining algorithms including AdaBoost, Bagging, generalized additive model (GAM), and Naive Bayes (NB) models to map groundwater potential. Then, a novel frequency ratio data mining ensemble model (FREM) was introduced and evaluated. For this purpose, eleven groundwater conditioning factors (GCFs), including altitude, slope aspect, slope angle, plan curvature, stream power index (SPI), river density, distance from rivers, topographic wetness index (TWI), land use, normalized difference vegetation index (NDVI), and lithology were mapped. About 281 well locations with high potential were selected. Wells were randomly partitioned into two classes for training the models (70% or 197) and validating them (30% or 84). AdaBoost, Bagging, GAM, and NB algorithms were employed to get groundwater potential maps (GPMs). The GPMs were categorized into potential classes using natural break method of classification scheme. In the next stage, frequency ratio (FR) value was calculated for the output of the four aforementioned models and were summed, and finally a GPM was produced using FREM. For validating the models, area under receiver operating characteristics (ROC) curve was calculated. The ROC curve for prediction dataset was 94.8, 93.5, 92.6, 92.0, and 84.4% for FREM, Bagging, AdaBoost, GAM, and NB models, respectively. The results indicated that FREM had the best performance among all the models. The better performance of the FREM model could be related to reduction of over fitting and possible errors. Other models such as AdaBoost, Bagging, GAM, and NB also produced acceptable performance in groundwater modelling. The GPMs produced in the current study may facilitate groundwater exploitati...
Navaratnarajah, SK & Indraratna, B 2017, 'Use of Rubber Mats to Improve the Deformation and Degradation Behavior of Rail Ballast under Cyclic Loading', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 6, pp. 04017015-04017015.
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Neshat, A & Pradhan, B 2017, 'Evaluation of groundwater vulnerability to pollution using DRASTIC framework and GIS', Arabian Journal of Geosciences, vol. 10, no. 22, pp. 1-8.
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© 2017, Saudi Society for Geosciences. Groundwater management has a prominent role in the world especially in arid and semi-arid areas which have a shortage of water, and due to this serious problem, many researchers work on that for prevention and managing the water recourses to conserve and monitor sources. DRASTIC index can be put forward for estimating of groundwater vulnerability to such pollution. The main purpose of using the groundwater vulnerability model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, disregarding the effects of pollution type and characteristics. Thus, this technique must be standardized and approved for Kerman plain. Vulnerability evaluation to explain areas that are more vulnerable to contamination from anthropogenic sources has become a prominent element for land use planning and tangible resource management. This contribution aims at evaluating groundwater vulnerability by applying the DRASTIC index as well as employ sensitivity analyses to evaluate the comparative prominent of the model parameters for groundwater vulnerability in Kerman plain in the southeastern part of Iran. Moreover, the potential of vulnerability to pollution is more accurately assessed by optimizing the weights of the DRASTIC parameters with the single-parameter sensitivity analysis (SPSA). The new weights were calculated. The result of the study revealed that the DRASTIC-Sensitivity analysis exhibit more efficiently than the traditional method for a nonpoint source pollution. Observation of ultimate nitrate showed the result of DRASTIC-SPSA has more accuracy. The GIS method offers an efficient environment for carrying out assessments and greater capabilities for dealing with a huge quantity of spatial data.
Ngo, NT 2017, 'DEM MODELLING OF GEOCELL-STABILISED SUB-BALLAST UNDER CYCLIC LOADING', International Journal of GEOMATE, vol. 12, no. 31, pp. 23-29.
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Upon repeated train loading, sub-ballast aggregates, placed underneath a ballast layer in rail track, become degraded and fouled by the progressive accumulation of external fine particles such as mud-pumping of soft subgrade, seriously decreasing the shear strength and drainage capacity of the track. This paper presents a study of the load-deformation response of geocell-reinforced sub-ballast under cyclic loads using laboratory tests and discrete element method (DEM). A series of large-scale cubical triaxial tests with and without geocell inclusions are conducted in the laboratory and simulated in DEM to investigate the beneficial effect of the geocells in decreasing the lateral and vertical deformations of railway subballast. Irregularly-shaped particles of sub-ballast are modelled by connecting and bonding of many circular balls together at appropriate sizes and positions. The geogcell was simulated by bonding many small spheres together to build a desired geometry and structure. The load-deformation behaviour of the geocell-stabilised sub-ballast specimen at varied load cycles predicted from the DEM modelling agrees well with those measured experimentally, showing that the proposed DEM model in this study is able to capture the deformation behaviour of the sub-ballast stabilised by the geocell. Additionally, the DEM modelling also provides insight into the distribution of contact forces, average contact normal and shear forces, which cannot be determined experimentally. These observations clearly prove the reinforcement effect of the geocell in eliminating the deformation of sub-ballast from a micromechanical perspective.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'A study of the geogrid–subballast interface via experimental evaluation and discrete element modelling', Granular Matter, vol. 19, no. 3, pp. 1-16.
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This paper presents a study of the interface of geogrid reinforced subballast through a series of large-scale direct shear tests and discrete element modelling. Direct shear tests were carried out for subballast with and without geogrid inclusions under varying normal stresses of σn= 6.7 to 45kPa. Numerical modelling with three-dimensional discrete element method (DEM) was used to study the shear behaviour of the interface of subballast reinforced by geogrids. In this study, groups of 25–50 spherical balls are clumped together in appropriate sizes to simulate angular subballast grains, while the geogrid is modelled by bonding small spheres together to form the desired grid geometry and apertures. The calculated results of the shear stress ratio versus shear strain show a good agreement with the experimental data, indicating that the DEM model can capture the interface behaviour of subballast reinforced by geogrids. A micromechanical analysis has also been carried out to examine how the contact force distributions and fabric anisotropy evolve during shearing. This study shows that the shear strength of the interface is governed by the geogrid characteristics (i.e. their geometry and opening apertures). Of the three types of geogrid tested, triaxial geogrid (triangular apertures) exhibits higher interface shear strength than the biaxial geogrids; and this is believed due to multi-directional load distribution of the triaxial geogrid.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'Micromechanics-Based Investigation of Fouled Ballast Using Large-Scale Triaxial Tests and Discrete Element Modeling', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 2, pp. 04016089-04016089.
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Railway ballast comprises unbounded discrete grains that are often used to form a load-bearing platform for tracks. Ballast degradation as trains pass over the tracks and infiltration of external fines including slurried (pumped) fine subgrade soils are two of the main reasons for ballast fouling. Fouling causes tracks to settle and also reduces the load-bearing capacity, which is associated with a reduction in internal friction and increased lateral spreading of the ballast layer. This paper presents a study of mobilized friction angle, volumetric behavior, and associated evolutions of contact and fabric anisotropy of fouled ballast subjected to monotonic triaxial loading using a series of large-scale triaxial tests and discrete element modeling. Monotonically loaded and drained triaxial tests were carried out on ballast with levels of clay fouling that varied from 10 to 50% void contamination index (VCI) subjected to three confining pressures of 10, 30, and 60 kPa. The results showed that an increase in the level of fouling decreased the mobilized friction angle and increased the ballast dilation. The discrete element method (DEM) was used to study the mobilized friction angle and fabric anisotropy of fresh and fouled ballast by simulating actual large-scale triaxial tests. Irregular shaped grains of ballast were simulated by clumping bonded circular balls with appropriate sizes and positions together. Ballast fouling was approximately simulated in DEM by adding 1-mm particles into the pore spaces of the fresh ballast. The predicted mobilized friction angles and volumetric changes obtained from the DEM simulations agreed well with those measured in the laboratory, indicating that the peak friction angle of fouled ballast and dilation decreased as the degree of fouling increased. The DEM simulations provided an insight into the distribution of contact force chains, contact orientations, and evolution of fabric anisotropy of fresh and fouled ballast tha...
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'Simulation Ballasted Track Behavior: Numerical Treatment and Field Application', International Journal of Geomechanics, vol. 17, no. 6, pp. 1-12.
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The load deformation of ballasted rail tracks subjected to cyclic loading is investigated experimentally using a large-scale track process simulation apparatus and numerically through a combined discrete element-finite-difference approach. Laboratory tests were performed to examine the deformation and degradation of ballast subjected to cyclic loading at 15 Hz and a lateral confinement of 10 kPa. The laboratory results reveal that ballast undergoes significant deformation during the initial load cycles, followed by gradually increasing deformation attaining a steady value toward the end of testing. A numerical model based on a combined discrete element method (DEM) and finite-difference method (FDM) is introduced to study the load-deformation response of the ballast assembly while considering interaction between the ballast aggregates and the subgrade layer. In this coupled model, the discrete ballast grains are modeled by DEM, and the subgrade domain is modeled as a continuum by FDM. Interface elements are introduced to transmit the interacting forces and displacements between adjoining material domains in which the DEM transfers contact forces to the FDM, and then the FDM updates the displacements, which provides subsequent input into the DEM. This computational cycle continues with the increasing number of loading cycles. The numerical model is validated by comparing the predicted cyclic load-deformation response with the laboratory measurements. Contact force distributions and stress contours in the assembly are analyzed and presented graphically to interpret the behavior of the model track, and the effects that subgrade stiffness have on the axial strain and bond breakage of the ballast are investigated. This combined DEM-FDM analysis is also used to analyze the load deformation of an instrumented track in the town of Singleton, Australia, and the numerical predictions are compared with the field data.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 2017, 'Stabilization of track substructure with geo-inclusions—experimental evidence and DEM simulation', International Journal of Rail Transportation, vol. 5, no. 2, pp. 63-86.
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This article reviews on current knowledge of rail track geomechanics, including several important concepts and topics related to laboratory testing and computational modelling, to study the shear stress-strain and deformation of ballast improved by geosynthetics and recycled rubber mats. The effect that impact loads have on ballast degradation and its mitigation due to resilient synthetic mats (i.e. rubber mats) between the ballast and the subballast is investigated using large-scale impact-testing apparatus. Computational modelling with finite element and discrete element methods are increasingly being used to model ballasted tracks reinforced with geosynthetics to capture the continuum media of formation soils and the discrete nature of ballast aggregates. The article focuses on reviewing previous studies by the University of Wollongong on ballasted track substructure and highlights some practical implications whereby innovation progresses from theory to practice.
Nguyen, L, Fatahi, B & Khabbaz, H 2017, 'Development of a Constitutive Model to Predict the Behavior of Cement-Treated Clay during Cementation Degradation: C3 Model', International Journal of Geomechanics, vol. 17, no. 7, pp. 04017010-04017010.
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© 2017 American Society of Civil Engineers. Many researchers have indicated how cementation allows treated soft clays to sustain a higher yield mean effective stress at the same void ratio as its reconstituted state, and thus, the strength of clay treated with cement increases because the cement and clay particles bond together. However, the void ratio of cement-treated clay decreases significantly in isotropic consolidation and triaxial conditions when subjected to a high mean effective stress, particularly beyond the initial yield stress. Laboratory experiments have shown that the cementation of clay gradually diminishes as the mean effective stress increases as a result of the degradation of cementation bonds. Thus, the failure envelope of cement-treated clay gradually merges with the reconstituted clay-cement mixture at high mean effective stresses. Furthermore, the shear strength of cement-treated clay is influenced by the shear degradation induced by shear deformation. In this study, by combining the mean effective stress and shear degradation, a constitutive model, referred to as the C3 model, based on the critical state framework, was developed to simulate the behavior of cement-treated clay. The proposed model includes a modified mean effective stress, a nonlinear failure envelope, a nonassociated plastic potential function, and a general stress-strain relationship to simulate the prepeak and postpeak deviatoric stress states, including the softening behavior of cement-treated clay. In this study, triaxial tests (drained and undrained) were conducted on Ballina clay treated with 10 and 12% cement and Kaolin clay treated with 5 and 10% cement, and the results are reported and discussed. The proposed model was evaluated by comparing its predictions with the triaxial test results reported on the cement-treated Ballina clay and Kaolin clay. The proposed constitutive model gave reliable predictions that agreed with the experimental results and captu...
Nguyen, TT & Indraratna, B 2017, 'Experimental and numerical investigations into hydraulic behaviour of coir fibre drain', Canadian Geotechnical Journal, vol. 54, no. 1, pp. 75-87.
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Over many decades, natural fibre bundles have been widely used for drainage and filtration applications because of their favourable hydraulic conductivity and abundance in Asian countries. In recent times, natural (biodegradable) coir and jute drains, which are environmentally friendly, have been considered in lieu of conventional geosynthetic wick drains for soft clay consolidation in Australian coastal regions. However, there is a lack of a computational framework to predict the hydraulic behaviour of fibre drains on the basis of micromechanical (fabric) characteristics. Employing computational fluid dynamics (CFD) coupled with the discrete element method (DEM) to model the hydraulic behaviour of fibrous materials has shown promise in an earlier 2016 study by Nguyen and Indraratna, which considered an idealized parallel arrangement of fibres for simplicity. This paper aims to broaden the application of the coupled CFD–DEM technique to real fibres (coconut coir) considering both nontwisted and twisted fibre bundles that have more complex porous structure. The hydraulic conductivity determined from the numerical approach is validated with the experimental results, and also compared with the analytical prediction based on the conventional Kozeny–Carmen (KC) approach. The current study shows that the CFD–DEM technique can capture well the fluid flow characteristics of a nonuniform fibrous structure, including dense twisted coir bundles.
Nguyen, TT & Indraratna, B 2017, 'The permeability of natural fibre drains, capturing their micro-features', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 170, no. 3, pp. 123-136.
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Natural fibres such as jute and coir are emerging as distinct alternatives to synthetic geomaterials, and in recent years they have been used increasingly for drainage and filtration in field applications. However, these naturally occurring materials are extremely variable in micro-characteristics such as the size, uniformity and shape of their fibres, while there is a lack of studies addressing how these differences can affect the hydraulic behaviour of fibrous media. This paper offers a laboratory study of the influence of micro-features on the hydraulic conductivity of fibre drain. Non-twisted and twisted fibre drains made from jute and coir were subjected to hydraulic conductivity testing and micro-analyses. Experimental results show a considerable contribution of the size characteristics of fibre to the hydraulic behaviour of the drain. A less-rounded shape of fibre and a larger twisting angle of the drain can increase the fluid–fibre contact area and the corresponding tortuosity of flow, which significantly reduces the drain permeability. The way in which the Kozeny–Carmen analytical approach can be adopted to predict the permeability of a fibre drain is discussed based on the experimental results, considering various micro-factors including the size of fibre, uniformity and the associated porosity.
Ni, W, Abolhasan, M, Hagelstein, B, Liu, RP & Wang, X 2017, 'A New Trellis Model for MAC Layer Cooperative Retransmission Protocols', IEEE Transactions on Vehicular Technology, vol. 66, no. 4, pp. 3448-3461.
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© 1967-2012 IEEE. Comparison studies on timer-based distributed cooperative retransmission protocols are challenging, given a variety of backoff techniques. We propose a new unified model, which can characterize a wide range of cooperative retransmission protocols. The key idea is a new trellis diagram that extrapolates the retransmission probabilities in each timeslot to the entire cooperative process. Following the trellis, performance metrics, such as success rate and collision intensity, can be derived in a structured manner. The new trellis model, coupled with Markov techniques, can be also extended to analyze the distributed binary exponential backoff processes of cooperative retransmissions. Confirmed by simulations, the proposed trellis model accurately reveals the impact of the relays' relative locations and density on different protocols. Our model also has the potential to be used as a management tool to adaptively configure protocol parameters.
Nourbakhsh, N, Chen, F, Wang, Y & Calvo, RA 2017, 'Detecting Users’ Cognitive Load by Galvanic Skin Response with Affective Interference', ACM Transactions on Interactive Intelligent Systems, vol. 7, no. 3, pp. 1-20.
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Experiencing high cognitive load during complex and demanding tasks results in performance reduction, stress, and errors. However, these could be prevented by a system capable of constantly monitoring users’ cognitive load fluctuations and adjusting its interactions accordingly. Physiological data and behaviors have been found to be suitable measures of cognitive load and are now available in many consumer devices. An advantage of these measures over subjective and performance-based methods is that they are captured in real time and implicitly while the user interacts with the system, which makes them suitable for real-world applications. On the other hand, emotion interference can change physiological responses and make accurate cognitive load measurement more challenging. In this work, we have studied six galvanic skin response (GSR) features in detection of four cognitive load levels with the interference of emotions. The data was derived from two arithmetic experiments and emotions were induced by displaying pleasant and unpleasant pictures in the background. Two types of classifiers were applied to detect cognitive load levels. Results from both studies indicate that the features explored can detect four and two cognitive load levels with high accuracy even under emotional changes. More specifically, rise duration and accumulative GSR are the common best features in all situations, having the highest accuracy especially in the presence of emotions.
Oberst, S, Bann, G, Lai, JCS & Evans, TA 2017, 'Cryptic termites avoid predatory ants by eavesdropping on vibrational cues from their footsteps', Ecology Letters, vol. 20, no. 2, pp. 212-221.
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AbstractEavesdropping has evolved in many predator–prey relationships. Communication signals of social species may be particularly vulnerable to eavesdropping, such as pheromones produced by ants, which are predators of termites. Termites communicate mostly by way of substrate‐borne vibrations, which suggest they may be able to eavesdrop, using two possible mechanisms: ant chemicals or ant vibrations. We observed termites foraging within millimetres of ants in the field, suggesting the evolution of specialised detection behaviours. We found the termite Coptotermes acinaciformis detected their major predator, the ant Iridomyrmex purpureus, through thin wood using only vibrational cues from walking, and not chemical signals. Comparison of 16 termite and ant species found the ants‐walking signals were up to 100 times higher than those of termites. Eavesdropping on passive walking signals explains the predator detection and foraging behaviours in this ancient relationship, which may be applicable to many other predator–prey relationships.
Oberst, S, Marburg, S & Hoffmann, N 2017, 'Determining periodic orbits via nonlinear filtering and recurrence spectra in the presence of noise', Procedia Engineering, vol. 199, pp. 772-777.
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Pain, A, Chen, Q, Nimbalkar, S & Zhou, Y 2017, 'Evaluation of seismic passive earth pressure of inclined rigid retaining wall considering soil arching effect', Soil Dynamics and Earthquake Engineering, vol. 100, pp. 286-295.
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© 2017 Elsevier Ltd Evaluation of seismic passive earth pressure is an important topic of research in geotechnical engineering. In this study seismic passive pressure on an inclined rigid retaining wall supporting horizontal cohesionless backfill is estimated considering arching effect. A planar failure surface is considered in the present analysis. Seismic forces are considered to be pseudo-static in nature. The effect of different parameters on the seismic passive earth pressure is studied in details. The normal stress distribution along the depth of the backfill is found to be nonlinear in nature. Friction angle between wall and the backfill soil has the most significant effect on the distribution of normal stress along the depth of the backfill. The point of application of seismic passive pressure shifts gradually downward for higher seismic forces. Present method is validated with the experimental results available in the literature for static conditions. Comparison of present method with other theories is also presented showing the merit of the present study. Arching effect in the backfill should be considered for high values of wall inclination angle as the present seismic passive resistance is found to be the lowest as compared to other theoretical solutions.
Peng, H, Lan, C, Liu, Y, Liu, T, Blumenstein, M & Li, J 2017, 'Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes', Oncotarget, vol. 8, no. 45, pp. 78901-78916.
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© Peng et al. Disease-related protein-coding genes have been widely studied, but diseaserelated non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the stateof- the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long noncoding genes.
Perera, D, Indraratna, B, Leroueil, S, Rujikiatkamjorn, C & Kelly, R 2017, 'Analytical model for vacuum consolidation incorporating soil disturbance caused by mandrel-driven drains', Canadian Geotechnical Journal, vol. 54, no. 4, pp. 547-560.
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When vacuum preloading is applied with vertical drains, the rate of consolidation can be increased, and the stability of an embankment is enhanced due to the inward lateral movement. The aim of this study is to develop an analytical solution for vacuum preloading that accurately captures the more realistic variations in compressibility and permeability in actual ground conditions as a result of drain installation. The soil samples were obtained from various locations after drain installation to determine the characteristics of soil surrounding the vertical drain in terms of compressibility and permeability. The main differences between the proposed and conventional models are described by considering the stress history and preloading pressure. The effect of pre-consolidation pressure and the magnitude of applied preloading are examined through the dissipation of average excess pore pressure and associated settlement. The analysis of a selected case history employing the writers’ solution indicates improved accuracy of the predictions in comparison to the field measurements.
Pradhan, B, Mohsen Mousavi, S, Golkarian, A, Amir Naghibi, S & Kalantar, B 2017, 'GIS-based Groundwater Spring Potential Mapping Using Data Mining Boosted Regression Tree and Probabilistic Frequency Ratio Models in Iran', AIMS Geosciences, vol. 3, no. 1, pp. 91-115.
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Pradhan, B, Sameen, MI & Kalantar, B 2017, 'Optimized Rule-Based Flood Mapping Technique Using Multitemporal RADARSAT-2 Images in the Tropical Region', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 7, pp. 3190-3199.
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Flood is one of the most common natural disasters in Malaysia. Preparing an accurate flood inventory map is the basic step in flood risk management. Flood detection is a complex process because of the limitation of methodological approaches and cloud coverage over tropical areas. An efficient approach is proposed to identify flooded areas using multitemporal RADARSAT-2 imageries. First, multispectral Landsat image was used to extract and subtract permanent water bodies, and this image was later utilized to extract the same information from multitemporal RADARSAT-2 imageries. Next, water bodies during a flood event were extracted from RADARSAT-2 images. Permanent water bodies, shadow, and paddy were detected from synthetic aperture radar (SAR) images by analyzing their temporal backscattering values. During feature extraction, rule-based object-oriented technique was applied to classify both SAR and Landsat images. Image segmentation during object-based analysis was performed to distinguish the boundaries of various dimensions and scales of objects. Moreover, a Taguchibased method was employed to optimize the segmentation parameters. After segmentation, the rules were defined and images were classified to produce an accurate flood inventory map for the 2014 Kelantan flood. A confusion matrix was generated to evaluate the performance of the classification method. The overall accuracy of 86.16% was achieved for RADARSAT-2 using rule-based classification and optimization technique. The resulting flood inventory map using the proposed approach supported the efficiency of the proposed methodology.
Rao, P, Chen, Q, Nimbalkar, S & Liu, Y 2017, 'Laboratory study on impulse current characteristics of clay', Environmental Geotechnics, vol. 4, no. 3, pp. 199-208.
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Lightning is recognised as one of the most detrimental natural disasters. While numerous research studies were carried out on the lightning impulse characteristics of the grounding system and the critical breakdown characteristics of soil, little attention was paid to the impulse current characteristics of soils when lightning strikes. In this study, the performance of typical soft soil in Shanghai under the action of lightning is analyzed. Different factors, including the impulse current waveforms, the front time and half peak time of impulse current, the quantity of electric charge and absorption of unit heat, have been studied by performing a series of laboratory tests. The test results show that the variation of impulse current due to lightning strike is time dependent. The higher the soil temperature, the larger the peak impulse current produced during lightning strike. The value of the front time decreases exponentially, while the value of the half peak time decreases linearly with the rise of soil temperature. Novel empirical relationships between the impulse current characteristics of soil and soil temperature are proposed, with the aim of providing useful practical references for the design of a grounding system for lightning strikes.
Rao, P-P, Chen, Q, Li, L, Nimbalkar, S & Cui, J 2017, 'Elastoplastic Solution for Spherical Cavity Expansion in Modified Cam-Clay Soil under Drained Condition', International Journal of Geomechanics, vol. 17, no. 8, pp. 06017005-06017005.
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© 2017 American Society of Civil Engineers. This paper presents an innovative semianalytical solution for the expansion of a drained spherical cavity with finite initial radius. The widely known modified Cam-clay model is adopted to capture the nonlinear elastoplastic behavior of soil. The rigorous definitions for the mean and deviator stresses are adopted. The problem is then formulated as a set of first-order ordinary differential equations in the Lagrangian form. The radial and tangential stress and specific volume distribution around the cavity are determined. Extensive parametric study is undertaken to investigate effects of the overconsolidation ratio and relative positioning of elastoplastic interface, among others. The applicability of the proposed theoretical approach is demonstrated by a comparison with laboratory test results.
Rasekh, H, Mirzaghorbanali, A, Nemcik, J, Aziz, N & Li, X 2017, 'A New Equation for the Shear Strength of Cable Bolts Incorporating the Energy Balance Theory', Geotechnical and Geological Engineering, vol. 35, no. 4, pp. 1529-1548.
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© 2017, Springer International Publishing Switzerland. The application of cable bolts as a secondary support system is an increasing trend in underground coal mines worldwide. The performances of cable bolts have been evaluated under both axial and shear loading conditions. Two methods of testing cables for shear, single and double shear, have been recognised. This paper examines the shear behaviour of a variety of cable bolts under different pre-tension loads by double shear testing. Plain, spiral and the combination of both cable types were used in this study. The initial axial load and the type of cable bolts are the main factors affecting their shear strength. By increasing the axial pre-tension load, the peak shear load occurs at lower shear displacement. The failure angle due to cable bending across the joint at different pre-tension loads varied between 41° and 49°. This demonstrates that the ratio of axial and perpendicular displacements is almost constant and on average the failure occurs at about 45°. A novel analytical model is proposed to evaluate the shear behaviour of pre-tensioned fully grouted cable bolts subjected to double shearing. Energy and Fourier Series methods were incorporated in the model to simulate the shear behaviour of cable bolts. The comparison of the experimental results with the proposed model shows a good agreement.
Rothberg, SJ, Allen, MS, Castellini, P, Di Maio, D, Dirckx, JJJ, Ewins, DJ, Halkon, BJ, Muyshondt, P, Paone, N, Ryan, T, Steger, H, Tomasini, EP, Vanlanduit, S & Vignola, JF 2017, 'An international review of laser Doppler vibrometry: Making light work of vibration measurement', Optics and Lasers in Engineering, vol. 99, pp. 11-22.
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© 2016 In 1964, just a few years after the invention of the laser, a fluid velocity measurement based on the frequency shift of scattered light was made and the laser Doppler technique was born. This comprehensive review paper charts advances in the development and applications of laser Doppler vibrometry (LDV) since those first pioneering experiments. Consideration is first given to the challenges that continue to be posed by laser speckle. Scanning LDV is introduced and its significant influence in the field of experimental modal analysis described. Applications in structural health monitoring and MEMS serve to demonstrate LDV's applicability on structures of all sizes. Rotor vibrations and hearing are explored as examples of the classic applications. Applications in acoustics recognise the versatility of LDV as demonstrated by visualisation of sound fields. The paper concludes with thoughts on future developments, using examples of new multi-component and multi-channel instruments.
Sameen, M & Pradhan, B 2017, 'Severity Prediction of Traffic Accidents with Recurrent Neural Networks', Applied Sciences, vol. 7, no. 6, pp. 476-476.
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In this paper, a deep learning model using a Recurrent Neural Network (RNN) was developed and employed to predict the injury severity of traffic accidents based on 1130 accident records that have occurred on the North-South Expressway (NSE), Malaysia over a six-year period from 2009 to 2015. Compared to traditional Neural Networks (NNs), the RNN method is more effective for sequential data, and is expected to capture temporal correlations among the traffic accident records. Several network architectures and configurations were tested through a systematic grid search to determine an optimal network for predicting the injury severity of traffic accidents. The selected network architecture comprised of a Long-Short Term Memory (LSTM) layer, two fully-connected (dense) layers and a Softmax layer. Next, to avoid over-fitting, the dropout technique with a probability of 0.3 was applied. Further, the network was trained with a Stochastic Gradient Descent (SGD) algorithm (learning rate = 0.01) in the Tensorflow framework. A sensitivity analysis of the RNN model was further conducted to determine these factors’ impact on injury severity outcomes. Also, the proposed RNN model was compared with Multilayer Perceptron (MLP) and Bayesian Logistic Regression (BLR) models to understand its advantages and limitations. The results of the comparative analyses showed that the RNN model outperformed the MLP and BLR models. The validation accuracy of the RNN model was 71.77%, whereas the MLP and BLR models achieved 65.48% and 58.30% respectively. The findings of this study indicate that the RNN model, in deep learning frameworks, can be a promising tool for predicting the injury severity of traffic accidents.
Sameen, MI & Pradhan, B 2017, 'A Novel Road Segmentation Technique from Orthophotos Using Deep Convolutional Autoencoders', KOREAN JOURNAL OF REMOTE SENSING, vol. 33, no. 4, pp. 423-436.
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This paper presents a deep learning-based road segmentation framework from very high resolution orthophotos.The proposed method usesDeep Convolutional Autoencoders for end-to-end mapping
of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the
model outputs GIS-ready data that could be useful for various applications. The optimization of the model’s
parameters is explained whichwas conducted via grid search method.The modelwas trained and implemented
in Keras, a high-level deep learning framework run on top of Tensorflow. The results show thatthe proposed
model with the best-obtained hyperparameters could segment road objects from orthophotos at an average
accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation
function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU),
respectively. In addition,the best numbers of convolutional filters were found to be 8 for the first and second
layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis
on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on
1024 high-resolution images of size 106 × 106 pixels, and segment road objects from similar size and
resolution images in around 14 minutes.The results show that the deep learning models such as Convolutional
Autoencoders could be a best alternative to traditional machine learning models for road segmentation from
aerial photographs.
Sameen, MI & Pradhan, B 2017, 'A Simplified Semi-Automatic Technique for Highway Extraction from High-Resolution Airborne LiDAR Data and Orthophotos', Journal of the Indian Society of Remote Sensing, vol. 45, no. 3, pp. 395-405.
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Information on highways is an essential input for various geospatial applications, including car navigation, forensic analysis on highway geometries, and intelligent transportation systems. Semi-automatic and automatic extractions of highways are critical for the regular updating of municipal databases and for highway maintenance. This study presents a semi-automatic data processing approach for extracting highways from high-resolution airborne LiDAR height information and aerial orthophotos. The method was developed based on two data sets. Experimental results for the first testing site showed that the accuracy of the proposed method for highway extraction was 74.50 % for completeness and 73.13 % for correctness. Meanwhile, the completeness and correctness for the second testing site were 71.20 and 70.72 %, respectively. The proposed method was compared with an object-based approach on a different data set. The accuracy for highway extraction of the object-based approach was 64.29 % for completeness and 63.11 % for correctness, whereas that of the proposed method was 67.14 % for completeness and 65.08 % for correctness. This research aims to promote semi-automatic highway extraction from LiDAR data and orthophotos by proposing a new approach and a multistep post-processing technique. The proposed method provides an accurate final output that is valuable for a wide range of geospatial applications.
Sameen, MI & Pradhan, B 2017, 'A Two-Stage Optimization Strategy for Fuzzy Object-Based Analysis Using Airborne LiDAR and High-Resolution Orthophotos for Urban Road Extraction', Journal of Sensors, vol. 2017, pp. 1-17.
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In the last decade, object-based image analysis (OBIA) has been extensively recognized as an effective classification method for very high spatial resolution images or integrated data from different sources. In this study, a two-stage optimization strategy for fuzzy object-based analysis using airborne LiDAR was proposed for urban road extraction. The method optimizes the two basic steps of OBIA, namely, segmentation and classification, to realize accurate land cover mapping and urban road extraction. This objective was achieved by selecting the optimum scale parameter to maximize class separability and the optimum shape and compactness parameters to optimize the final image segments. Class separability was maximized using the Bhattacharyya distance algorithm, whereas image segmentation was optimized using the Taguchi method. The proposed fuzzy rules were created based on integrated data and expert knowledge. Spectral, spatial, and texture features were used under fuzzy rules by implementing the particle swarm optimization technique. The proposed fuzzy rules were easy to implement and were transferable to other areas. An overall accuracy of 82% and a kappa index of agreement (KIA) of 0.79 were achieved on the studied area when results were compared with reference objects created via manual digitization in a geographic information system. The accuracy of road extraction using the developed fuzzy rules was 0.76 (producer), 0.85 (user), and 0.72 (KIA). Meanwhile, overall accuracy was decreased by approximately 6% when the rules were applied on a test site. A KIA of 0.70 was achieved on the test site using the same rules without any changes. The accuracy of the extracted urban roads from the test site was 0.72 (KIA), which decreased to approximately 0.16. Spatial information (i.e., elongation) and intensity from LiDAR were the most interesting properties for urban road extraction. The proposed method can be applied to a wide range of real applicatio...
Sameen, MI & Pradhan, B 2017, 'Assessment of the effects of expressway geometric design features on the frequency of accident crash rates using high-resolution laser scanning data and GIS', Geomatics, Natural Hazards and Risk, vol. 8, no. 2, pp. 733-747.
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Sameen, MI, Pradhan, B, Shafri, HZM, Mezaal, MR & Hamid, HB 2017, 'Integration of Ant Colony Optimization and Object-Based Analysis for LiDAR Data Classification', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 5, pp. 2055-2066.
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© 2017 IEEE. Light detection and ranging (LiDAR) data classification provides useful thematic maps for numerous geospatial applications. Several methods and algorithms have been proposed recently for LiDAR data classification. Most studies focused on object-based analysis because of its advantages over per-pixel-based methods. However, several issues, such as parameter optimization, attribute selection, and development of transferable rulesets, remain challenging in this topic. This study contributes to LiDAR data classification by developing an approach that integrates ant colony optimization (ACO) and rule-based classification. First, LiDAR-derived digital elevation and digital surface models were integrated with high-resolution orthophotos. Second, the processed raster was segmented with the multiresolution segmentation method. Subsequently, the parameters were optimized with a supervised technique based on fuzzy analysis. A total of 20 attributes were selected based on general knowledge on the study area and LiDAR data; the best subset containing 12 attributes was then selected via ACO. These attributes were utilized to develop rulesets through the use of a decision tree algorithm, and a thematic map was generated for the study area. Results revealed the robustness of the proposed method, which has an overall accuracy of ∼95% and a kappa coefficient of 0.94. The rule-based approach with all attributes and the k nearest neighbor (KNN) classification method were applied to validate the results of the proposed method. The overall accuracy of the rule-based method with all attributes was ∼88% (kappa = 0.82), whereas the KNN method had an overall accuracy of <70% and produced a poor thematic map. The selection of the ACO algorithm was justified through a comparison with three well-known feature selection methods. On the other hand, the transferability of the developed rules was evaluated by using a second LiDAR dataset at another study area. The overall ...
Sathyamoorthy, D, Pradhan, B, Voon Chet, K & Chuah, HT 2017, 'IEEE GRSS Malaysia Chapter [Chapters]', IEEE Geoscience and Remote Sensing Magazine, vol. 5, no. 2, pp. 100-102.
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Shi, W, Chen, Q, Nimbalkar, S & Liu, W 2017, 'A new mixing technique for solidifier and dredged fill in coastal area', Marine Georesources & Geotechnology, vol. 35, no. 1, pp. 52-61.
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2016 Copyright © Taylor & Francis Group, LLCOne of the major drawbacks of the conventional method of land reclamation, which involves mixing cement with the dredged soils at the disposal site, is the high cost associated with its manufacturing and transportation. In this study, a new solidified dredged fill (SDF) technique and a new additive are proposed and their practical applications are discussed. Unlike the conventional approach, the dredged marine soils were mixed with the solidifiers using a newly designed mixing technique prior to its transport to site, which would significantly reduce the cost of site machinery and effectively reclaim land with adequate engineering properties necessary for the construction of infrastructure. To evaluate the performance of the reclaimed land using the proposed technique, a series of laboratory and field tests (namely, static and dynamic cone penetration tests, and plate load tests) were conducted on grounds filled with and without solidified dredged marine soils, respectively. The results showed that the engineering behavior of the reclaimed land with dredged marine soils using SDF technique had significantly improved. The SDF technique combined with the newly designed mixing system improved the performance of ground and has thus proved to be both cost-effective and safe.
Shirvani, Z, Abdi, O, Buchroithner, MF & Pradhan, B 2017, 'Analysing Spatial and Statistical Dependencies of Deforestation Affected by Residential Growth: Gorganrood Basin, Northeast Iran', Land Degradation & Development, vol. 28, no. 7, pp. 2176-2190.
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AbstractThis study aimed to examine deforestation and residential growth trends and their spatial dependencies from 1972 to 2010 in Northeast of Iran. First, change rates of forests and residential areas were mapped using Landsat satellite images in 1972–1987, 1987–2000 and 2000–2010. Then, the forest change patterns were interpreted using univariate local Moran's I (local univariate spatial autocorrelation), and the spatial autocorrelation between deforestation and residential growth was tested through bivariate local Moran's I (bivariate local spatial autocorrelation). Furthermore, the spatial relationships between deforestation and residential growth rates were quantified by ordinary least squares, spatial lag (SL) and geographically weighted regression. Results indicated that approximately 25% of forests have been converted to other land‐use types in the span of 38 years, since 1972. Local univariate spatial autocorrelation maps showed that significant values of high–high cluster scattered in all locations in the first span, in the east and south aspects in the second duration, and in the eastern part in the third span. Bivariate local spatial autocorrelation indicated a meaningful Moran's I values of −0·12, −0·26 and −0·20 between deforestation and residential growth, chronologically. Analyses of spatial regression models showed that geographically weighted regression performed better than SL and ordinary least squares in the first (R2 = 0·315, AIC = 6,160) and third periods (R2 = 0·27, AIC = 6,351), whereas, the validity of SL was the highest in the second period (R2 = 0·36, AIC = 6,288). However, the overall trends of deforestation and residential growth have decreased, but the rate of deforestation induced by residential growth is still significant. Spatial exploration of...
Shivakumara, P, Wu, L, Lu, T, Tan, CL, Blumenstein, M & Anami, BS 2017, 'Fractals based multi-oriented text detection system for recognition in mobile video images', Pattern Recognition, vol. 68, pp. 158-174.
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© 2017 Elsevier Ltd Text detection in mobile video is challenging due to poor quality, complex background, arbitrary orientation and text movement. In this work, we introduce fractals for text detection in video captured by mobile cameras. We first use fractal properties such as self-similarity in a novel way in the gradient domain for enhancing low resolution mobile video. We then propose to use k-means clustering for separating text components from non-text ones. To make the method font size independent, fractal expansion is further explored in the wavelet domain in a pyramid structure for text components in text cluster to identify text candidates. Next, potential text candidates are obtained by studying the optical flow property of text candidates. Direction guided boundary growing is finally proposed to extract multi-oriented texts. The method is tested on different datasets, which include low resolution video captured by mobile, benchmark ICDAR 2013 video, YouTube Video Text (YVT) data, ICDAR 2013, Microsoft, and MSRA arbitrary orientation natural scene datasets, to evaluate the performance of the proposed method in terms of recall, precision, F-measure and misdetection rate. To show the effectiveness of the proposed method, the results are compared with the state of the art methods.
Stone, BW, Harland, AR, Jones, JA, Mitchell, SR, Sherratt, PJ, Ranson, CA & Halkon, BJ 2017, 'On the dynamic response of an instrumented headform for alternative mounting stiffnesses when subjected to ballistic impacts', Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, vol. 231, no. 4, pp. 324-335.
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The current British Standard for head protectors for cricketers has been recently revised to include a projectile-based battery of tests, the intention being to ensure that a certified helmet will also prevent contact of the ball or grille with the specified headform facial region. The purpose of this study was to characterise the dynamic response of the headform to direct ballistic impacts for alternative headform mounting arrangements. On one hand, and in accordance with the relevant sections of the Standard, what might be described as a ‘Constrained’ setup was evaluated while, on the other hand, an arrangement with significantly reduced stiffness, in line with that previously reported for the passive human neck, was subject to equivalent appraisal. For each mounting scenario, an air cannon was used to project a cricket training ball at three speeds towards the instrumented headform at three locations with five repeats per speed/location combination. High-rate/resolution video and piezoelectric accelerometer data were collected and processed to determine the headform response. While differences between specific ball impact speed and location scenarios are set out in detail later in the article, overall observations are summarised as follows. From a ball/headform contact duration standpoint, video derived results showed ranges of 1.30–1.45 ms (Constrained) versus 1.26–1.41 ms. Maximum ball deformations, the timing of which enabling the event to be subdivided into ‘loading’ and ‘unloading’ phases, were found to be 82.5%–86.2% (Constrained) versus 82.8%–86.4% of original ball diameter; mean peak headform accelerations during loading were found to be 860–1615 m/s2 (Constrained) versus 967–1638 m/s2; and headform speeds at the end of the loading phase were found to be 0.5–0.92 m/s (Constrained) versus 0.54–0.93 m/s. Differences between headform response for the two mounting arrangements were observed to be...
Sun, W-J, Zong, F-Y, Sun, D-A, Wei, Z-F, Schanz, T & Fatahi, B 2017, 'Swelling prediction of bentonite-sand mixtures in the full range of sand content', Engineering Geology, vol. 222, pp. 146-155.
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© 2017 Elsevier B.V. The swelling prediction of bentonite–sand mixtures due to wetting is very important in evaluating the long term performance of the engineered barrier in the high level radioactive waste disposal system and the hydraulic barriers in geoenvironmental constructions. Sun et al. (2015) proposed the swelling prediction model of bentonite-sand mixtures due to full hydration, and predicted the swelling of different types of bentonite-sand mixtures, which was verified, to be consistent with the swelling test results. However, the predicted swelling results of bentonite-sand mixtures with extremely high sand content obtained by the original swelling prediction model have a large deviation from the test results. The reason is that the original model is based on an assumption that all the pores and available water are only associated with bentonite/montmorillonite fraction. However, for mixtures with extremely high sand content, the sand skeleton exists and resists the external stress from the very beginning. At the same time, the bentonite, dispersing in the sand skeleton, in contact with the pore fluid, swells freely to fully saturated state, however, still fails to fill the sand skeleton voids completely. In this research, the original swelling prediction model is extended by introducing the concept of critical filling sand content and critical contact stress. When sand content is more than the critical filling sand content, the deformation of the mixture is mainly due to the sand skeleton deformation. After the stress increases greater than the critical contact stress, the saturated bentonite fills the sand skeleton voids completely, and the swelling can still be predicted by the original swelling prediction model. In the extended model, the swelling prediction can be divided into three zones according to the two limit values of critical sand content and critical filling sand content. In different zones, the distribution ratio of the vertical stress ...
Sun, Y, Chen, C & Nimbalkar, S 2017, 'Identification of ballast grading for rail track', Journal of Rock Mechanics and Geotechnical Engineering, vol. 9, no. 5, pp. 945-954.
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© 2017 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences Grading has long been recognised to critically influence the mechanical behaviour of ballast. To identify the ballast grading for heavy-haul rail track, monotonic and cyclic triaxial tests are conducted to assess the performances of different gradings. Permanent deformations, aggregates degradation, resilience, shear resistance, maximum and minimum densities are recorded and analysed. The grading is found to affect the behaviour of ballast in that coarser gradings exhibit relatively better strength, resilience and therefore less permanent deformation. However, ballast degradation increases with the overall aggregate size. Therefore, to identify the grading for ballast with different performance objectives, a grey relational theory is used to convert the multi-objective into single-objective, i.e. grey relational grade. A relatively optimal grading that provides the highest grey relational grade is thus suggested for the improved ballast performance.
Sun, Y, Indraratna, B, Carter, JP, Marchant, T & Nimbalkar, S 2017, 'Application of fractional calculus in modelling ballast deformation under cyclic loading', Computers and Geotechnics, vol. 82, pp. 16-30.
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Tien Bui, D, Bui, Q-T, Nguyen, Q-P, Pradhan, B, Nampak, H & Trinh, PT 2017, 'A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area', Agricultural and Forest Meteorology, vol. 233, pp. 32-44.
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© 2016 Elsevier B.V. This paper proposes and validates a novel hybrid artificial intelligent approach, named as Particle Swarm Optimized Neural Fuzzy (PSO-NF), for spatial modeling of tropical forest fire susceptibility. In the proposed approach, a Neural Fuzzy inference system (NF) was used to establish the forest fire model whereas Particle Swarm Optimization (PSO) was adopted to investigate the best values for the model parameters. Tropical forest at the province of Lam Dong (Central Highland of Vietnam) was used as a case study. For this purpose, historic forest fires and ten ignition factors (slope, aspect, elevation, land use, Normalized Difference Vegetation Index, distance to road, distance to residence area, temperature, wind speed, and rainfall) were collected from various sources to construct a GIS database, and then, the database was used to develop and validate the proposed model. The performance of the forest model was assessed using the Receiver Operating Characteristic curve, area under the curve (AUC), and several statistical measures. The results showed that the proposed model performs well, both on the training dataset (AUC = 0.932) and the validation dataset (AUC = 0.916). The usability of the proposed model was further assessed through comparisons with those derived from two benchmark state-of-the art machine learning methods, Random Forests (RF) and Support Vector Machine (SVM). Because the performance of the proposed model is better than the two benchmark models, we concluded that the PSO-NF model is a valid alternative tool that should be considered for tropical forest fire susceptibility modeling. The result in this study is useful for forest planning and management in forest fire prone areas.
Tien Bui, D, Tuan, TA, Hoang, N-D, Thanh, NQ, Nguyen, DB, Van Liem, N & Pradhan, B 2017, 'Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization', Landslides, vol. 14, no. 2, pp. 447-458.
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© 2016, Springer-Verlag Berlin Heidelberg. The main objective of this study is to produce a landslide susceptibility map for the Lao Cai area (Vietnam) using a new hybrid intelligent method based on least squares support vector machines (LSSVM) and artificial bee colony (ABC) optimization, namely LSSVM-BC. LSSVM and ABC are state-of-the-art soft computing techniques that have been rarely utilized in landslide susceptibility assessment. LSSVM is adopted to develop landslide prediction model whereas ABC was used to optimize the prediction model by identifying an appropriate set of the LSSVM hyper-parameters. To establish the hybrid intelligent method, a GIS database with ten landslide-influencing factors and 340 landslide locations that occurred mainly during the last 20-years was constructed. These historical landslide locations were collected from the existing inventories that sourced from (i) five landslide projects carried out in this study areas before and (ii) interpretations of SPOT satellite images with resolution of 2.5 m. The study area was geographically split into two different parts, with landslides located in the first part was used for building models whereas the other landslides in the second part was used for the model validation. Performance of the LSSVM-BC model was assessed using the receiver operating characteristic (ROC) curve and area under the curve (AUC). Result shows that the prediction power of the model is good with the area under the curve (AUC) = 0.900. Experiments have pointed out the prediction power of the LSSVM-BC is better than that obtained from the popular support vector machines. Therefore, the proposed model is a promising tool for spatial prediction of landslides at the study area. The landslide susceptibility map is useful for landuse planning for the Lao Cai area.
Trung Ngo, N, Indraratna, B & Rujikiatkamjorn, C 2017, 'Closure to “Micromechanics-Based Investigation of Fouled Ballast Using Large-Scale Triaxial Tests and Discrete Element Modeling” by Ngoc Trung Ngo, Buddhima Indraratna, and Cholachat Rujikiatkamjorn', Journal of Geotechnical and Geoenvironmental Engineering, vol. 143, no. 9, pp. 07017027-07017027.
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Van Nguyen, Q, Fatahi, B & Hokmabadi, AS 2017, 'Influence of Size and Load-Bearing Mechanism of Piles on Seismic Performance of Buildings Considering Soil–Pile–Structure Interaction', International Journal of Geomechanics, vol. 17, no. 7, pp. 04017007-04017007.
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© 2017 American Society of Civil Engineers. Pile foundations are usually used to transmit foundation loads through soil strata of low bearing capacity to deeper soil or rock strata with a higher bearing capacity and stiffness. The type and size of a pile foundation that supports midrise buildings in high-risk seismic zones can alter the dynamic characteristics of the soil-pile-foundation system during an earthquake due to soil-structure interaction. To investigate these phenomena, a 15-story moment-resisting frame sitting on differently sized end-bearing and floating pile foundations was simulated numerically. The present paper describes a numerical modeling technique for the simulation of complex seismic soil-pile-structure interaction phenomena. By adopting a method of direct calculation, the numerical model can perform a fully nonlinear time history dynamic analysis to realistically simulate the dynamic behavior of soil, pile foundations, and structure under seismic excitations. This three-dimensional (3D) numerical model accounts for the nonlinear behavior of the soil medium, the piles, and the structural elements. Results show that the type and size of the pile elements influence the dynamic characteristics and seismic response of the building due to interaction between the soil, pile foundations, and the structure. The findings of this study can help engineers select the correct size and type of pile foundation while considering the seismic performance of buildings sitting on soft soil and aim at optimizing their design.
Wang, J, Yang, G, Liu, H, Shrawan Nimbalkar, S, Tang, X & Xiao, Y 2017, 'Seismic response of concrete-rockfill combination dam using large-scale shaking table tests', Soil Dynamics and Earthquake Engineering, vol. 99, pp. 9-19.
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Wang, Q, Ye, X, Wang, S, Sloan, S & Sheng, D 2017, 'Development of a Model Test System for Studying the Behaviour of a Compaction Grouted Soil Nail under Unsaturated Conditions', Geotechnical Testing Journal, vol. 40, no. 5, pp. 20160229-20160229.
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Wang, Q, Ye, X, Wang, S, Sloan, SW & Sheng, D 2017, 'Experimental investigation of compaction-grouted soil nails', Canadian Geotechnical Journal, vol. 54, no. 12, pp. 1728-1738.
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An innovative compaction-grouted soil nail was designed by injecting grout into a special latex balloon (grouting bag) to avoid bleeding and penetration of grout into the surrounding soil. A series of large-scale model tests was performed to study the surrounding soil responses due to grouting and the subsequent pull-out resistance of the soil nail. The experimental results show that grouting pressure plays an important role in the enhancement of the density and (or) strength of the surrounding soil. In addition, during the pull-out process, the compaction-grouted soil nail exhibits a strain-hardening behaviour without a yield point. This is a significant advantage of this new soil nail, indicating that it can enable soil masses to remain stable against a relatively large deformation before ultimate failure. The main factors behind the improvement of the pull-out resistance of the new soil nail are, first, the compaction–densification of the soil near the grouting bag due to grouting, resulting in the enhancement of the shear strength of the soil, and, second, the enlargement of the grouting bag, causing the increase of the interface shear and end resistance to the pull-out of the soil nail.
Wijayaratna, KP, Dixit, VV, Denant-Boemont, L & Waller, ST 2017, 'An experimental study of the Online Information Paradox: Does en-route information improve road network performance?', PLOS ONE, vol. 12, no. 9, pp. e0184191-e0184191.
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This study investigates the empirical presence of a theoretical transportation paradox, defined as the 'Online Information Paradox' (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.
Xu, S, Wu, C, Liu, Z, Han, K, Su, Y, Zhao, J & Li, J 2017, 'Experimental investigation of seismic behavior of ultra-high performance steel fiber reinforced concrete columns', Engineering Structures, vol. 152, pp. 129-148.
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© 2017 Elsevier Ltd This paper presents an experimental study on seismic behavior of ultra-high performance steel fiber reinforced concrete (UHPSFRC) columns. Based on a series of cyclic loading tests on 14 UHPSFRC specimens subjected to combined static axial loading and cyclic lateral loading, the investigation and analysis have been carried out on crack status, failure modes, hysteretic loops, skeleton curves, strength and stiffness degradation, energy dissipation capacity and ductility of UHPSFRC columns. The influence of stirrup spacing, type of stirrup, axial compression ratio and shear span ratio on the seismic performance of UHPSFRC columns was also investigated in details. The experiment results show that three typical failure modes are observed, i.e., flexural, flexural-shear and shear failure mode. The existence of steel fiber could prevent the cracked concrete from spalling efficiently and delay the bulking of longitudinal reinforcement further. It noteworthy that the limit plastic drift ratio of all columns changes from 0.036 to 0.061, indicating that the UHPSFRC columns represent a good ductility which is obviously different from the conventional high strength concrete columns that exhibit much more brittleness with the increase of strength.
Yao, K, Pradhan, B & Idrees, MO 2017, 'Identification of Rocks and Their Quartz Content in Gua Musang Goldfield Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery', Journal of Sensors, vol. 2017, pp. 1-8.
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Quartz is an important mineral element and the most abundant rock-forming mineral that controls the mineralogy of a reservoir. At the surface, quartz is more stable than most other rock minerals because it is made up of interlocking silica that makes it quite resistant to mechanical weathering. Quartz abundance is an indication of mineralization in many metal deposits; therefore, identification and mapping of quartz in rocks are of great value for exploration and resource potential assessments. In this study, thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery were used to identify quartz contained rocks in Gua Musang. First, the image was corrected for atmospheric effect and the study area subset for further processing. Thereafter, spectral transformation (principal component analysis (PCA)) was implemented on the TIR bands and the resulting principal component (PC) images were analysed. The three optimal PCs were selected using the strength of spectral interaction and the eigenvalues of each band. To discriminate between quartz-rich and quartz-poor rocks, RGB false colour composite and greyscale image of one of the PCs were analysed. The result shows that volcanogenic igneous rock and carbonate sedimentary rocks of Permian formation are quartz-poor while Triassic sedimentary rock made up of organic particles and sandstone is quartz-rich. On the contrary, the quartz content in the metamorphic rock varies across the area but is richer in quartz content than the igneous and carbonate rocks. Classification of the composite image classified using maximum likelihood (ML) supervised classification method produced overall accuracy and Kappa coefficient of 96.53%, and 0.95, respectively.
Yap, HC, Khabbaz, H & Singh, J 2017, 'Numerical analysis of geosynthetics and engineering fill in performance of reconditioned ballasted track', Australian Geomechanics Journal, vol. 52, no. 1, pp. 43-55.
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Over the past few decades, geosynthetics have been used extensively during track reconditioning to improve soil stability as they offer many advantages including cost effectiveness, ease of installation and minimal earthworks. Among the wide range of products in the market, geogrid remains the most commonly used geosynthetics for soil reinforcement. The aims of this paper are to investigate the effect of varying subgrade properties on track performance and to examine the effectiveness of geogrids and engineering fill for track reconditioning purposes. In the current study, numerical analyses were conducted using engineering software OptumG2, a finite element program for geotechnical stability and deformation analysis. The results of the parametric study indicated that geogrid inclusion within track substructure has considerable effect on settlement reduction and, in particular, increases the bearing capacity of railway track. The results also suggested that increase in axial stiffness of geogrids has minimal impact on track deformation. The most effective and practical location for geogrid reinforcement was achieved at interface between ballast and capping layers irrespective of the subgrade strength and stiffness. Sensitivity analyses showed that both total settlement and the bearing capacity of the railway track were most affected by the changes in the friction angle of subgrade, compared with cohesion and elastic modulus of subgrade, with or without geogrid reinforcement. The findings concluded that proper design of geogrid reinforcement can eliminate the need for or significantly reduce the thickness of engineering fill for ground improvement purposes.
Ye, X, Wang, S, Wang, Q, Sloan, SW & Sheng, D 2017, 'Numerical and experimental studies of the mechanical behaviour for compaction grouted soil nails in sandy soil', Computers and Geotechnics, vol. 90, pp. 202-214.
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A model test was conducted for a newly developed soil nail, the result of which was compared to that of a 3D finite element method (FEM) simulation. The shape angle (β) and friction coefficients (μ) contributed to the difference in pull-out force between the model test and the simulation. Further verifications were conducted, during which the pull-out mechanisms of the soil nail for different β and μ were analysed. It was found that both β and μ have a positive influence on the pull-out force; β only affects the increase rate, while μ influences the overall pull-out force level. Three components were found to govern the pull-out force, with the component applied to the expanded cement bulk surface accounting for approximately 80% of the total. This study proves that the optimal approach for increasing pull-out force is to enlarge the diameter of the cement bulk rather than extend the nail length.
Yu, J, Ji, J, Miao, Z & Zhou, J 2017, 'Adaptive formation control of networked Lagrangian systems with a moving leader', Nonlinear Dynamics, vol. 90, no. 4, pp. 2755-2766.
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© 2017, Springer Science+Business Media B.V. This paper investigates the formation control problem of networked Lagrangian systems with a moving leader under the directed network topology. A special form of geometric pattern is introduced to design the desired formation for such systems. Three adaptive control strategies are proposed for the networked Lagrangian systems to achieve the formation for the cases of the absence and presence of time delays. Some simple yet general algebraic criteria are developed to ensure that the networked Lagrangian systems can always achieve desired geometric formation. Furthermore, the effect of communication time delays on the performance of formation control is numerically investigated. Finally, numerical examples are given to illustrate and visualize the effectiveness of the theoretical results.
Zare, M, Mohammady, M & Pradhan, B 2017, 'Modeling the effect of land use and climate change scenarios on future soil loss rate in Kasilian watershed of northern Iran', Environmental Earth Sciences, vol. 76, no. 8, pp. 1-15.
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Accelerated erosion processes caused by global climate and land use changes in many regions of the world constitute a major restrictive factor in their sustainability. This study proposes a method to estimate soil loss rate under changes in future land use and climate in Kasilian watershed of northern Iran within two periods. The first period is related to current climate and land use (1991–2010), and the second concerns climate and land use scenarios (2011–2030). Downscaling global climate model projections of future climate was applied at the regional scale. A statistical downscaling model was then used to downscale precipitation for three scenarios, i.e., 10% increase in rainfall, 10% decrease in rainfall, and unchanged rainfall. Next, cellular automata–Markov model was used for characterization based on two scenarios of land use future that were designed using suitability maps. The soil loss mean for the current period was found to be 6.3 t ha−1year−1 , thereby indicating a low sustainability of soils. The results of simulated soil loss maps indicate a similar pattern in spatial distribution of loss rates compared with those of current periods, but the amount of risk has increased such that simulated erosion mean was 31–58% higher than the current period in all scenarios. Soil loss is thoroughly influenced by climate and land cover patterns in future. In other words, rainfall erosivity has increased by 20 MJ mm ha−1h−1year−1 , based on unchanged rainfall scenario and National Centers for Environmental Prediction data, simulated that cover management factor has increased by 35% compared with the current period. However, simulations indicated that land use changes may potentially induce much larger changes in erosion. The results also showed that soil loss is closely related to land use change and various scenarios of climate change and that revised universal soil loss equation is suitable model to investigate these relationships.
Zhang, X, Sheng, D, Sloan, SW & Bleyer, J 2017, 'Lagrangian modelling of large deformation induced by progressive failure of sensitive clays with elastoviscoplasticity', International Journal for Numerical Methods in Engineering, vol. 112, no. 8, pp. 963-989.
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SummaryThis paper presents a Lagrangian formulation of elastoviscoplasticity, on the basis of the particle finite element method, for progressive failure analysis of sensitive clays. The sensitive clay is represented by an elastoviscoplastic model that is a mixture of the Bingham model, for describing rheological behaviour, and the Tresca model with strain softening for capturing the progressive failure behaviour. The finite element formulation for the incremental elastoviscoplastic analysis is reformulated, through the application of the Hellinger–Reissner variational theorem, as an equivalent optimisation program that can be solved efficiently using modern algorithms such as the interior‐point method. The recast formulation is then incorporated into the framework of the particle finite element method for investigating progressive failure problems related to sensitive clays, such as the collapse of a sensitive clay column and the retrogressive failure of a slope in sensitive clays, where extremely large deformation occurs. Copyright © 2017 John Wiley & Sons, Ltd.
Zhang, X, Sloan, SW, Vignes, C & Sheng, D 2017, 'A modification of the phase-field model for mixed mode crack propagation in rock-like materials', Computer Methods in Applied Mechanics and Engineering, vol. 322, pp. 123-136.
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The critical energy release rates for mode I and II fracture for rock-like materials are usually different. In this paper, a modified phase-field model is proposed for simulating mixed mode crack propagation. The model can distinguish between the critical energy release rates for mode I and mode II cracks. For the purpose of validation, rock-like materials with a single flaw or double flaws under compression are studied. The simulated results are compared to experimental data, both qualitatively and quantitatively. It is shown that the proposed model is able to capture the commonly observed propagation pattern of wing crack emergence followed by secondary cracks. Additionally, the typical types of crack coalescence observed in experimental tests are successfully reproduced, including the critical loads at which crack coalescence occurs.
Zhang, X, Vignes, C, Sloan, SW & Sheng, D 2017, 'Numerical evaluation of the phase-field model for brittle fracture with emphasis on the length scale', Computational Mechanics, vol. 59, no. 5, pp. 737-752.
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© 2017, Springer-Verlag Berlin Heidelberg. The phase-field model has been attracting considerable attention due to its capability of capturing complex crack propagations without mesh dependence. However, its validation studies have primarily focused on the ability to predict reasonable, sharply defined crack paths. Very limited works have so far been contributed to estimate its accuracy in predicting force responses, which is majorly attributed to the difficulty in the determination of the length scale. Indeed, accurate crack path simulation can be achieved by setting the length scale to be sufficiently small, whereas a very small length scale may lead to unrealistic force-displacement responses and overestimate critical structural loads. This paper aims to provide a critical numerical investigation of the accuracy of phase-field modelling of brittle fracture with special emphasis on a possible formula for the length scale estimation. Phase-field simulations of a number of classical fracture experiments for brittle fracture in concretes are performed with simulated results compared with experimental data qualitatively and quantitatively to achieve this goal. Furthermore, discussions are conducted with the aim to provide guidelines for the application of the phase-field model.
Zhou, J, Sun, J, Wang, Y & Chen, F 2017, 'Wrapping practical problems into a machine learning framework: using water pipe failure prediction as a case study', International Journal of Intelligent Systems Technologies and Applications, vol. 16, no. 3, pp. 191-191.
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Despite the recognised value of machine learning (ML) techniques and high expectation of applying ML techniques within various applications, users often find it difficult to effectively apply ML techniques in practice because of complicated interfaces between ML algorithms and users. This paper presents a work flow of wrapping practical problems into an ML framework. The water pipe failure prediction is used as a case study to show that the applying process can be divided into various steps: obtain domain data, interview with domain experts, clean/pre-process and preview original domain data, extract ML features, set up ML models, explain ML results and make decisions, as well as make feedback to the system based on decision making. In this process, domain experts and ML developers need to collaborate closely in order to make this workflow more effective.
Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'Impact of struck-out text on writer identification', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, AK, USA, pp. 1465-1471.
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© 2017 IEEE. The presence of struck-out text in handwritten manuscripts may affect the accuracy of automated writer identification. This paper presents a study on such effects of struck-out text. Here we consider offline English and Bengali handwritten document images. At first, the struck-out texts are detected using a hybrid classifier of a CNN (Convolutional Neural Network) and an SVM (Support Vector Machine). Then the writer identification process is activated on normal and struck-out text separately, to ascertain the impact of struck-out texts. For writer identification, we use two methods: (a) a hand-crafted feature-based SVM classifier, and (b) CNN-extracted auto-derived features with a recurrent neural model. For the experimental analysis, we have generated a database from 100 English and 100 Bengali writers. The performance of our system is very encouraging.
Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'Legibility and Aesthetic Analysis of Handwriting', 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), IEEE, Kyoto, Japan, pp. 175-182.
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© 2017 IEEE. This paper deals with computer-based cognitive analysis towards legibility and aesthetics of a handwritten document. The legible text creates a human perception that the writing can be read effortlessly because of its orthographic clarity. The aesthetic property relates to the beautiful appearance of a handwritten document. In this study, we deal with these properties on offline Bengali handwriting. We formulate both legibility and aesthetic analysis tasks as machine learning problems supervised by the human cognitive system. We employ automatically derived feature-based recurrent neural networks to investigate writing legibility. For aesthetics evaluation, we employ hand-crafted feature-based support vector machines (SVMs). We have collected contemporary Bengali handwritings, on which the subjective legibility and aesthetic scores are provided by human readers. On this corpus containing legibility and aesthetic ground-Truth information, we executed our experiments. The experimental results obtained on various handwritings are encouraging.
Aghayarzadeh, M, Khabbaz, H, Fatahi, B & Terzaghi, S 1970, 'Continuum Numerical Modelling Of Dynamic Load Test For Steel Pipe Piles', Proceedings of the International Conference On Advancement of Pile Technology and Pile Case Histories, International Conference On Advancement of Pile Technology and Pile Case Histories, Universitas Katolik Parahyangan, Bali, Indonesia, pp. 1-10.
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In order to estimate the static axial capacity of driven piles, one-dimensional wave equationanalysis was proposed in 1960, in which pile is simulated by a number of masses attached to each other usingelastic springs, sliders and linear viscous dampers to simulate the visco-elasto-plastic response of the soil. Later,the signal matching technique program, CAPWAP, employing this model, was proposed to overcome theshortcomings of the conventional model. The main objective of this paper is to assess capabilities of so-calledcontinuum numerical model in analyzing dynamic pile load test. In this paper, the static and dynamic load testsof an open-ended steel pipe pile driven into dense sand have been simulated using PLAXIS 2D finite elementsoftware. After carrying out a number of numerical analyses the results of numerical simulation have beencompared to static load test results. The capabilities and challenges of the continuum numerical analysis tosimulate dynamic pile testing of steel pipe piles are briefly discussed.
Alaei, F, Alaei, A, Pal, U & Blumenstein, M 1970, 'Fast local binary pattern: Application to document image retrieval', 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Christchurch, New Zealand, pp. 1-6.
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© 2017 IEEE. The volume of digitised documents is increasing every day. Thus, designing a fast document image retrieval method for the large volume of document images, especially when the document images are also large in size, is of high demand. As feature extraction is one of the important steps in every document image retrieval system, a feature extraction technique with a low computing time and small feature number has a direct effect on the speed of the retrieval system. In this paper, we propose a non-parametric texture feature extraction method based on summarising the local grey-level structure of the image. To extract the proposed features, the input image is, at first, divided into a set of overlapping patches of equal size. The peripheral pixels of the centre pixel in a patch are used to extract two sets of patterns. The patterns are derived from the vertical & horizontal, and diagonal & off-diagonal pixels of the patch, separately. From each set of pixels, 15 different local binary patterns are extracted in our proposed feature extraction method. Two histograms of the local binary patterns are then created and concatenated to obtain 30 features called fast local binary pattern (F-LBP). To evaluate the efficiency of the proposed feature extraction method, MTDB and ITESOFT databases were considered for experimentation. The proposed F-LBP provided promising results with lower computing time as well as smaller memory space consumption compared to other variation of LBP methods.
Anaissi, A, Khoa, NLD, Mustapha, S, Alamdari, MM, Braytee, A, Wang, Y & Chen, F 1970, 'Adaptive One-Class Support Vector Machine for Damage Detection in Structural Health Monitoring', Advances in Knowledge Discovery and Data Mining (LNAI), Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, Springer International Publishing, Jeju, South Korea, pp. 42-57.
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© 2017, Springer International Publishing AG. Machine learning algorithms have been employed extensively in the area of structural health monitoring to compare new measurements with baselines to detect any structural change. One-class support vector machine (OCSVM) with Gaussian kernel function is a promising machine learning method which can learn only from one class data and then classify any new query samples. However, generalization performance of OCSVM is profoundly influenced by its Gaussian model parameter ϭ. This paper proposes a new algorithm named Appropriate Distance to the Enclosing Surface (ADES) for tuning the Gaussian model parameter. The semantic idea of this algorithm is based on inspecting the spatial locations of the edge and interior samples, and their distances to the enclosing surface of OCSVM. The algorithm selects the optimal value of ϭ which generates a hyperplane that is maximally distant from the interior samples but close to the edge samples. The sets of interior and edge samples are identified using a hard margin linear support vector machine. The algorithm was successfully validated using sensing data collected from the Sydney Harbour Bridge, in addition to five public datasets. The designed ADES algorithm is an appropriate choice to identify the optimal value of ϭ for OCSVM especially in high dimensional datasets.
Anaissi, A, Khoa, NLD, Rakotoarivelo, T, Alamdari, MM & Wang, Y 1970, 'Self-advised Incremental One-Class Support Vector Machines: An Application in Structural Health Monitoring', NEURAL INFORMATION PROCESSING, ICONIP 2017, PT I, 24th International Conference on Neural Information Processing (ICONIP), Springer International Publishing, Guangzhou, PEOPLES R CHINA, pp. 484-496.
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Blumenstein, M, Rokne, J & Srivastava, J 1970, 'IEEE/ACM ASONAM 2017 message from the general chairs', Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, pp. xvi-xvii.
Calderon-Vizcarra, G, Nimbalkar, S, Casagrande, M & Velloso, R 1970, 'Discrete element modelling of compression test on coarse granular aggregates used in railroad', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 821-829.
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This paper demonstrates results of numerical simulations based on discrete element approach. The triaxial compression behaviour of coarse granular particles that represent railroad ballast is simulated. During laboratory testing, the vertical deformation of ballast layer prepared with two different gradations was assessed under vertical loading. One specimen was simulated using particle size distribution (PSD) recommended by Indraratna and co-workers in the past as an improvement to Australian Standard and the other was prepared with PSD in accordance with Brazilian standard. The discrete element method offers a new resource for accurate investigation of response of railway ballast as evident in controlled laboratory environment as well as field conditions. In this paper, the discrete element method of analysis is used to simulate the geotechnical behaviour of ballast observed during compression testing. The numerical analysis captured the evolution of inter-particle forces as a granular material is subjected to compression test. The article showed a procedure to model ballast testing using DEM, where useful features of the micromechanical analyses such as coordination number, velocity vectors of particles are exhibited.
Chehrazad, S, Aghdasi, HS, Shariati, N & Abolhasan, M 1970, 'Addressing coverage problem in wireless sensor networks based on evolutionary algorithms', 2017 23rd Asia-Pacific Conference on Communications (APCC), 2017 23rd Asia-Pacific Conference on Communications (APCC), IEEE, Perth, WA, Australia, pp. 1-5.
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Wireless Sensor Networks (WSNs) are the key part of Internet of Things, as they provide the physical interface between on-field information and backbone analytic engines. An important role of WSNs-when collecting vital information-is to provide a consistent and reliable coverage. To Achieve this, WSNs must implement a highly reliable and efficient coverage recovery algorithm. In this paper, we take a fresh new approach to coverage recovery based on evolutionary algorithms. We propose EMACB-SA, which introduces a new evolutionary algorithm that selects coverage sets using a fitness function that balances energy efficiency and redundancy. The proposed algorithm improves network's coverage and lifetime in areas with heterogeneous event rate in comparison to previous works and hence, it is suitable for using in disaster management.
Cheng, E-J, Prasad, M, Puthal, D, Sharma, N, Prasad, OK, Chin, P-H, Lin, C-T & Blumenstein, M 1970, 'Deep Learning Based Face Recognition with Sparse Representation Classification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 24th International Conference on Neural Information Processing (ICONIP), Springer International Publishing, Guangzhou, PEOPLES R CHINA, pp. 665-674.
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Feature extraction is an essential step in solving real-world pattern recognition and classification problems. The accuracy of face recognition highly depends on the extracted features to represent a face. The traditional algorithms uses geometric techniques, comprising feature values including distance and angle between geometric points (eyes corners, mouth extremities, and nostrils). These features are sensitive to the elements such as illumination, variation of poses, various expressions, to mention a few. Recently, deep learning techniques have been very effective for feature extraction, and deep features have considerable tolerance for various conditions and unconstrained environment. This paper proposes a two layer deep convolutional neural network (CNN) for face feature extraction and applied sparse representation for face identification. The sparsity and selectivity of deep features can strengthen sparseness for the solution of sparse representation, which generally improves the recognition rate. The proposed method outperforms other feature extraction and classification methods in terms of recognition accuracy.
Coluccia, A, Ghenescu, M, Piatrik, T, De Cubber, G, Schumann, A, Sommer, L, Klatte, J, Schuchert, T, Beyerer, J, Farhadi, M, Amandi, R, Aker, C, Kalkan, S, Saqib, M, Sharma, N, Daud, S, Makkah, K & Blumenstein, M 1970, 'Drone-vs-Bird detection challenge at IEEE AVSS2017', 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), IEEE, Lecce, Italy, pp. 1-6.
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© 2017 IEEE. Small drones are a rising threat due to their possible misuse for illegal activities, in particular smuggling and terrorism. The project SafeShore, funded by the European Commission under the Horizon 2020 program, has launched the 'drone-vs-bird detection challenge' to address one of the many technical issues arising in this context. The goal is to detect a drone appearing at some point in a video where birds may be also present: the algorithm should raise an alarm and provide a position estimate only when a drone is present, while not issuing alarms on birds. This paper reports on the challenge proposal, evaluation, and results1.
Dang, LC, Dang, CC & Khabbaz, H 1970, 'Behaviour of columns and fibre reinforced load transfer platform supported embankments built on soft soil', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, the 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, Wuhan, China, pp. 1233-1246.
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This paper presents the findings of a numerical study on the behaviour of fibre reinforced load transfer platform (FRLTP) and cement-soil columns supported (CS) embankment constructed on soft soil. An array of numerical analyses based on finite element method incorporated in PLAXIS was conducted on the full geometry of an embankment reinforced without or with an FRLTP over cement-soil columns for different improvement depth in a two-dimensional plane strain condition to examine the effectiveness of the FRLTP inclusion into the CS embankment system. The beneficial effects of lime-fibre-soil inclusion as a load transfer platform (LTP) and cement-soil columns supported embankment on the total and differential settlements, stress transfer mechanism, and lateral displacement have been analyzed and discussed in detail. Subsequently, a detailed parametric study on the influence of the shear strength parameters of the FRLTP has also been performed and discussed to provide a better understanding of the interaction between FRLTP, cement-soil columns and embankment over soft soil. The findings reveal that the CS embankment with FRLTP inclusion can provide the effective improvement in minimising the total and differential settlements, and the lateral displacement, meanwhile enhance the embankment stability and the stress concentration ratio to a great extent. Moreover, the numerical simulation results display that the increase in the improvement depth of the embankment reinforced with an FRLTP over cement-soil columns accelerate the consolidation progress of soft soils subjected to embankment loads. The numerically predicted results from the parametric study indicate that the cohesion and friction angle of the FRLTP have notable influence on the investigated embankment behaviour in terms of improving stress concentration ratio and differential settlement. However, the cohesion of FRLTP appears to be the most influential factor to be considered in the design procedu...
Dang, LC, Khabbaz, H & Fatahi, B 1970, 'An experimental study on engineering behaviour of lime and bagasse fibre reinforced expansive soils', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, the 19th International Conference on Soil Mechanics and Geotechnical Engineering, ISSMGE, Seoul, Republic of Korea, pp. 2497-2500.
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This investigation exhibits a series of laboratory tests conducted to evaluate the influences of bagasse fibre and hydrated lime addition on the engineering properties and swelling behaviour of stabilised expansive soils. Bagasse fibre is industrial waste byproduct left after crushing of sugar-cane for juice extraction, used in this study as a reinforcing component for expansive soil stabilisation. The expansive soils used in this investigation were collected from Queensland, Australia. Varying proportions of randomly distributed bagasse fibre of 0.5%, 1.0%, and 2.0% were added to expansive soil and lime-treated expansive soil to investigate the influences of bagasse fibre on the engineering characteristics of stabilised soil. Results of California bearing capacity (CBR), swell potential and one-dimensional consolidation tests after various curing time are presented and discussed in detail. The findings of this experimental investigation indicate that expansive soil reinforcement, blended with bagasse fibre and lime leads to a significant increase in the compressive strength and the bearing capacity of expansive soil. Meanwhile, the swell potential and compressibility of stabilised expansive soils decreased with increasing lime and bagasse fibre contents.
Dang, S, Cai, X, Wang, Y, Zhang, J & Chen, F 1970, 'Unsupervised Matrix-valued Kernel Learning For One Class Classification', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM, Singapore, SINGAPORE, pp. 2031-2034.
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Das, A, Mondal, P, Pal, U, Blumenstein, M & Ferrer, MA 1970, 'Sclera Vessel Pattern Synthesis Based on a Non-parametric Texture Synthesis Technique', Advances in Intelligent Systems and Computing, International Conference on Computer Vision and Image Processing, Springer Singapore, pp. 241-250.
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© Springer Science+Business Media Singapore 2017. This work proposes a sclera vessel texture pattern synthesis technique. Sclera texture was synthesized by a non-parametric based texture regeneration technique. A small number of classes from the UBIRIS version: 1 dataset was employed as primitive images. An appreciable result was achieved which solicits the successful synthesis of sclera texture patterns. It is difficult to get a huge collection real sclera data and hence such synthetic data will be useful to the researchers.
Das, A, Pal, U, Ferrer, MA & Blumenstein, M 1970, 'A decision-level fusion strategy for multimodal ocular biometric in visible spectrum based on posterior probability', 2017 IEEE International Joint Conference on Biometrics (IJCB), 2017 IEEE International Joint Conference on Biometrics (IJCB), IEEE, Denver, CO, USA, pp. 794-798.
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© 2017 IEEE. In this work, we propose a posterior probability-based decision-level fusion strategy for multimodal ocular biometric in the visible spectrum employing iris, sclera and peri-ocular trait. To best of our knowledge this is the first attempt to design a multimodal ocular biometrics using all three ocular traits. Employing all these traits in combination can help to increase the reliability and universality of the system. For instance in some scenarios, the sclera and iris can be highly occluded or for completely closed eyes scenario, the peri-ocular trait can be relied on for the decision. The proposed system is constituted of three independent traits and their combinations. The classification output of the trait which produces highest posterior probability is to consider as the final decision. An appreciable reliability and universal applicability of ocular trait are achieved in experiments conducted employing the proposed scheme.
Das, A, Pal, U, Ferrer, MA, Blumenstein, M, Stepec, D, Rot, P, Emersic, Z, Peer, P, Struc, V, Kumar, SVA & Harish, BS 1970, 'SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition', 2017 IEEE International Joint Conference on Biometrics (IJCB), 2017 IEEE International Joint Conference on Biometrics (IJCB), IEEE, Denver, CO, USA, pp. 742-747.
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© 2017 IEEE. This paper summarises the results of the Sclera Segmentation and Eye Recognition Benchmarking Competition (SSERBC 2017). It was organised in the context of the International Joint Conference on Biometrics (IJCB 2017). The aim of this competition was to record the recent developments in sclera segmentation and eye recognition in the visible spectrum (using iris, sclera and peri-ocular, and their fusion), and also to gain the attention of researchers on this subject. In this regard, we have used the Multi-Angle Sclera Dataset (MASD version 1). It is comprised of2624 images taken from both the eyes of 82 identities. Therefore, it consists of images of 164 (82×2) eyes. A manual segmentation mask of these images was created to baseline both tasks. Precision and recall based statistical measures were employed to evaluate the effectiveness of the segmentation and the ranks of the segmentation task. Recognition accuracy measure has been employed to measure the recognition task. Manually segmented sclera, iris and peri-ocular regions were used in the recognition task. Sixteen teams registered for the competition, and among them, six teams submitted their algorithms or systems for the segmentation task and two of them submitted their recognition algorithm or systems. The results produced by these algorithms or systems reflect current developments in the literature of sclera segmentation and eye recognition, employing cutting edge techniques. The MASD version 1 dataset with some of the ground truth will be freely available for research purposes. The success of the competition also demonstrates the recent interests of researchers from academia as well as industry on this subject.
Das, A, Sengupta, A, Ferrer, MA, Pal, U & Blumenstein, M 1970, 'Linking face images captured from the optical phenomenon in the wild for forensic science', 2017 IEEE International Joint Conference on Biometrics (IJCB), 2017 IEEE International Joint Conference on Biometrics (IJCB), IEEE, Denver, CO, USA, pp. 781-786.
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© 2017 IEEE. This paper discusses the possibility of use of some challenging face images scenario captured from optical phenomenon in the wild for forensic purpose towards individual identification. Occluded and under cover face images in surveillance scenario can be collected from its reflection on a surrounding glass or on a smooth wall that is under the coverage of the surveillance camera and such scenario of face images can be linked for forensic purposes. Another similar scenario that can also be used for forensic is the face images of an individual standing behind a transparent glass wall. To investigate the capability of these images for personal identification this study is conducted. This work investigated different types of features employed in the literature to establish individual identification by such degraded face images. Among them, local region based featured worked best. To achieve higher accuracy and better facial features face image were cropped manually along its close bounding box and noise removal was performed (reflection, etc.). In order to experiment we have developed a database considering the above mentioned scenario, which will be publicly available for academic research. Initial investigation substantiates the possibility of using such face images for forensic purpose.
Dibs, H, Mansor, S, Ahmad, N & Pradhan, B 1970, 'Registration model for near-equatorial earth observation satellite images using automatic extraction of control points'.
Dong, Y, Li, D, Fatahi, B, Zhang, X & Khabbaz, H 1970, 'Small-strain shear modulus of soft clay treated with Saccharomyces cerevisiae and cement', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2507-2510.
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Soil stabilisation by means of microorganisms is an emerging and novel technique in geotechnical engineering. On the other hand, cementation, as one of the conventional ground improvement techniques, has been proved to be an effective method to enhance the engineering properties of soils. Hence, it is believed that the combination of these two approaches can be extremely valuable and offer a novel, cost effective, environmentally friendly and practical engineering solution. In this study, the Saccharomyces cerevisiae, a species of yeast, has been selected owing to abundance and production cost to conduct the experiment in order to investigate its influence on the shear wave velocity and the small-strain shear modulus of cement stabilised clays using bender element test. It is observed that an appropriate amount of Saccharomyces cerevisiae can adequately improve the stiffness of soft clays treated with cement and microorganisms in long term.
Ebadi, A & Ji, J 1970, 'Investigation & comparison of the integration of flywheel energy storage in hybrid electric and electric vehicles using bond graphs', 2017 20th International Conference on Electrical Machines and Systems (ICEMS), 2017 20th International Conference on Electrical Machines and Systems (ICEMS), IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. Over the past few years Hybrid Electric and Electric propulsion systems have found significant attention as the most plausible substitute to fossil fuel based engines. Hybrid Electric Vehicles (HEV) have been around for more than a decade and extensive research has been taken out to make these vehicles more efficient. With advances in technology, manufacturers such as Tesla and Chevrolet have successfully launched a number of Electric Vehicles (EV) in the past 5 years. In despite of all this success, HEVs and EVs currently face challenges in energy storage systems (ESS) with regard to a variety of parameters and to overcome these issues research has been done on different types of ESS systems to extend the range of such vehicles. Flywheel Energy Storage Systems (FESS) have regained interest in the last decade and the application of kinetic energy recovery system (KERS) in the Formula 1 has reinforced the case of using FESS in HEV and EV. In this study, the integration of an FESS system within a hybrid electric propulsion and an electric propulsion system is considered and with the help of Bond-Graphs as a multidisciplinary modelling tool the impact of this integration is analyzed and compared with each other.
Farhood, H, He, X, Jia, W, Blumenstein, M & Li, H 1970, 'Counting People Based on Linear, Weighted, and Local Random Forests', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, pp. 1-7.
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© 2017 IEEE. Recently, many works have been published for counting people. However, when being applied to real-world train station videos, they have exposed many limitations due to problems such as low resolution, heavy occlusion, various density levels and perspective distortions. In this paper, following the recent trend of regression-based density estimation, we present a linear regression approach based on local Random Forests for counting either standing or moving people on station platforms. By dividing each frame into sub-windows and extracting features with ground truth densities as well as learned weights, we perform a linear transformation for counting people to overcome the perspective problems of the existing patch-based approaches. We present improvements against several recent baselines on the UCSD dataset and a dataset of CCTV videos taken from a train station. We also show improvements in speed compared with the state-of-the-art models based on detection and Deep Learning.
Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 1970, 'Red-Edge indices to diagnose orange spotting disease of oil palm in Malaysia', 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, Asian Conference on Remote Sensing, New Delhi, India.
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The use of hyperspectral remote sensing techniques for plant disease diagnosis is gaining much prominence due to its non-destructive feature. The steep gradient in reflectance between visible and near-infrared region is known as the red-edge, which is located between 680 and 780 nm. Red-edge is a stress diagnostic indicator that provides for non-destructive diagnosis of plant disease. This paper investigates the potential of two selected red-edge wavebands (680 nm and 754 nm) in diagnosing Orange Spotting (OS) disease of oil palm. OS is a fast emerging disease in Malaysian oil palm plantations. Coconut cadang-cadang viroid (CCCVd) is the causal agent of OS disease. Four well-known red-edge indices namely Ratio Vegetation Index (RVI), Red Edge Position (REP), Normalized Difference Red Edge Index (NDREI) and Chlorophyll Index (CI) were evaluated using selected wavebands. A spectroradiometer (Model: ASD FieldSpec® HandHeld 2), which operates in the spectral range of 325-1075 nm, was deployed to measure leaf reflectance of fifteen inoculated and five healthy oil palm seedlings grown under glasshouse conditions. A highly infective CCCVd variant, OP246, was used to inoculate the seedlings. Reflectance was measured at 15, 30, 45 and 60 days after inoculation. This work was aimed at investigation of variations on red-edge indices within the specific intervals of inoculation. Red-edge indices were calculated from inoculated and healthy seedlings and analyzed using one-way analysis of variance. Mean differences were interpreted at 0.05 significance level using Latin Square design. REP was selected as best red-edge index as multiple comparison of means values for healthy and inoculated seedlings were significantly different at 95% confidence level at all intervals.
Heitor, A, Indraratna, B, Rujikiatkamjorn, C & McIntosh, GW 1970, 'Influence of compaction history on the shear strength behaviour of compacted soil', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 1361-1364.
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The condition under which soil is compacted governs its shear strength, which is why the shear strength parameters of specimens compacted at a given state are usually evaluated and tested for different post-compaction loading conditions. While this enables the behaviour to be predicted in service, the impact of the compaction history is usually ignored. This is an important aspect because how compacted soil behaves during shearing is strongly influenced by its structure and suction, and thus its compaction and loading history. In this paper the aspects related to the compaction history of a silty sand soil prepared by dynamic compaction and then tested with a direct shearing box are examined. To replicate an as-compacted condition, the specimens are tested under constant water content. To investigate the compaction history the specimens were prepared under different levels of compaction energy and then tested under the same vertical stress. The results confirm how important the initial stress state of the soil is in relation to its compaction history, in governing the mechanical response during direct shearing.
Ho, L, Li, D, Fatahi, B & Khabbaz, H 1970, 'Analytical solution to one-dimensional consolidation in unsaturated soil due to time-dependent exponential temperature and external step loading', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 757-760.
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Recent experimental studies demonstrate that temperature changes may significantly influence the deformation of unsaturated soils. Thus, there is an essential need to develop a predictive framework for the unsaturated consolidation capturing non-isothermal effects. This paper introduces analytical solutions to predict the one-dimensional (1D) consolidation of unsaturated soil deposit while incorporating the time-dependent exponential temperature variation. The one-way drainage boundary system and the uniform initial condition are adopted for the mathematical derivation. In this study, governing equations under the non-isothermal condition are first obtained. Then, Fourier sine series and the Laplace transform technique are used to solve these governing equations and obtain the final solutions. This study highlights the combined effects of time-dependent exponential temperature and an external step loading on the excess pore pressures at various depths. It is predicted that the effects of exponential temperature on the dissipation process would be much attenuated at a lower depth.
Huang, B, Fatahi, B & Khabbaz, H 1970, 'Influence of Underground Opening with Stiff Lining on Seismic Response of Buildings', International Conference on Geomechanics and Geoenvironmental Engineering, International Conference on Geomechanics and Geoenvironmental Engineering, Science, Technology and Management Crest 12 Boyer Pl, Minto, New South Wales 2565, Sydney, Australia, Sydney, pp. 125-131.
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In this study, the influence of an underground opening at different depths on seismic performance of a 15-storey moment resisting building subjected to the 1995 Kobe earthquake is investigated. The numerical model consists of a superstructure, soil medium, and an underground opening, all simulated using finite element method in time domain considering soil nonlinearity and soil-structure interaction. The results are presented in terms of foundation rocking angle, distribution of maximum shear force developed in the structure, maximum lateral deflection as well as inter-storey drifts of the building. The results indicate that the underground opening has a notable influence on seismic response of the building. Particularly, the maximum foundation rocking angle is reduced with the presence of the underground opening with stiff concrete lining and the reduction is more significant when the underground opening is constructed at a lower depth. In addition, for a shallower underground opening, as the foundation rocking decreases, seismic energy dissipation is reduced, which in turn, causes more seismic energy transmitted to the structure and consequently larger shear forces are developed in the structure, which reveals the importance of consideration of underground structure in the seismic design of superstructures. Moreover, according to the results, the building constructed above a shallow underground opening experiences relatively smaller lateral displacement and inter-storey drifts subjected to earthquake excitation.
Indraratna, B 1970, 'Recent advances in vertical drains and vacuum preloading for soft ground stabilisation', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 141-166.
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Much of the world’s essential infrastructure is built along congested coastal belts that are composed of weak and highly compressible soils to significant depths. Soft alluvial and marine clay deposits have very low bearing capacity and excessive settlement characteristics. This has design and maintenance implications for tall structures, large commercial buildings, as well as port and transport infrastructure constructed on such poor soils. Stabilising these very soft deposits is essential before commencing construction of infrastructure. A system of vertical drains combined with vacuum pressure and surcharge preloading has become an efficient and cost effective ground improvement option. This technique accelerates consolidation by promoting rapid radial flow which decreases the excess pore pressure while increasing the effective stress. This 4th Louis Menard lecture presents an overview of the theoretical and practical developments of soft ground improvement via prefabricated vertical drains, PVD (including natural fibre drains) and vacuum preloading, with application to selected case studies in Australia.
Indraratna, B, Heitor, A & Pathirage, P 1970, 'Acidic Groundwater Remediation in the Shoalhaven Floodplain', Geotechnical Frontiers 2017, Geotechnical Frontiers 2017, American Society of Civil Engineers, Orlando, FL, pp. 518-525.
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Indraratna, B, Shahin, MA & Salim, W 1970, 'A study of geotechnical characteristics of particulate media in rail track substructures', Geomechanics and Geotechnics of Particulate Media, International Symposium on Geomechanics and Geotechnics of Particulated Media, CRC Press, Ube, JAPAN, pp. 381-387.
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Ismaiel, B, Abolhasan, M, Smith, DB, Ni, W & Franklin, DR 1970, 'A Survey and Comparison of Device-to-Device Architecture Using LTE Unlicensed Band.', VTC Spring, IEEE Vehicular Technology Conference, IEEE, Sydney, NSW, Australia, pp. 1-5.
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© 2017 IEEE. Due to the rapid increase in data traffic, one of the solutions provided by mobile operators is to operate Long Term Evolution (LTE) in the unlicensed 5GHz band, as the licensed spectrum is becoming scarce. Mobile operators can expand their network capacity by operating LTE in the unlicensed band at lower cost when compared with using other licensed bands. Device to Device (D2D) communication, proven to be another effective way to enhance the capacity of a network, enables direct data exchange of localized traffic of users in proximity. Applying D2D communication to LTE unlicensed 5GHz band will further improve the network performance and user experience. In this article, we will discuss the new type of solutions that have been proposed for LTE operating in an unlicensed 5GHz band that includes; LTE-Unlicensed (LTE-U), LTE-License Assisted Access (LTE-LAA), LTE WiFi Link Aggregation (LWA), and MuLTEfire. We will discuss the important features along with their advantages and disadvantages and compare these technologies as well. We simulate LTE-LAA, LWA and MuLTEfire technologies in the presence of Wi-Fi hotspot and compare their results. Furthermore, we apply D2D communication to these technologies and from the results we conclude that MuLTEfire can increase the throughput drastically but network saturates quickly. Whereas, applying D2D communication with LWA is beneficial for a scalable network as it will not only increase the network throughput but will increase the network capacity as well.
Ismaiel, B, Abolhasan, M, Smith, DB, Ni, W & Franklin, DR 1970, 'Scalable MAC protocol for D2D communication for future 5G networks.', CCNC, 2017 14th IEEE Annual Consumer Communications & Networking Conference, IEEE, Las Vegas, NV, USA, pp. 542-547.
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© 2017 IEEE. Device-to-device communication (D2D) will be an integral part of 5G wireless networks. Device-to-Device (D2D) communication provide the additional resources to the cellular users for spatially reusing licensed/unlicensed spectrum by establishing direct communication. Although, D2D communication is gaining significant attention towards offloading traffic in heterogeneous networks in licensed band, no attention has been given to offload traffic in an unlicensed band in a centralized manner. However, a major challenge of D2D communication is managing resources in an efficient manner in a heterogeneous network. This paper will direct a new approach to D2D Communication and will present a scalable MAC protocol for D2D communications based on Point Coordination Function (PCF) access mechanism. The importance of PCF access mechanism is that it operates in a centralized manner and highly suitable for the dense environment, hence, can create a centralized control in a distributive manner. In this article, we propose an innovative three tier 5G architecture for D2D communication, which will offload cellular traffic from the cellular network to the WLAN in a dense environment. Moreover, we will present a new centralized scalable MAC protocol for D2D communication between WLAN users, based on the IEEE 802.11 Point Coordination Function (PCF) access mechanism. Our simulation results show that the proposed MAC scheme can increase the capacity of the network and perform better relative to the legacy Distributed coordination Function (DCF) defined in IEEE 802.11.
Israr, J, Indraratna, B & Rujikiatkamjorn, C 1970, 'Effect of the Level of Compaction on the Internal Erosion Potential for Granular Soils', Geotechnical Frontiers 2017, Geotechnical Frontiers 2017, American Society of Civil Engineers, Orlando, FL, pp. 1-10.
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Kalantar, B, Moneir, AAA, Mansor, SB & Pradhan, B 1970, 'The use of random forest and object-based image classification for thematic map creation: A case study of Kelantan, Malaysia', 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, 38th Asian Conference on Remote Sensing 2017, New Delhi, India.
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This paper presented results of creation of thematic map for Kelantan city using an integration of object-based analysis and random forest algorithm. The thematic map was generated based on SPOT image with a spatial resolution of 5 m. Object-based analysis was used for its advantages over per-pixel based methods. On the other hand, random forest algorithm was selected because it was suggested in very recent literature and it has advantages ofgood generalization.A thematic map with sixclasses was generated with an overall accuracy and kappa index of 92% and 0.90, respectively using the proposed method. Other details are included in the paper.
Khoa, NLD, Anaissi, A & Wang, Y 1970, 'Smart Infrastructure Maintenance Using Incremental Tensor Analysis', Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17: ACM Conference on Information and Knowledge Management, ACM.
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Li, K, Ni, W, Duan, L, Abolhasan, M & Niu, J 1970, 'SWPT: A Joint-Scheduling Model for Wireless Powered Sensor Networks', GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017 IEEE Global Communications Conference (GLOBECOM 2017), IEEE, Singapore, Singapore, pp. 1-6.
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© 2017 IEEE. In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the others waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called Scheduled WPT (SWPT), aiming to minimize data packet loss from a network of wireless powered sensor nodes by jointly considering the sensor nodes' energy consumption and data queue state information. The scheduling problem is formulated by a MDP model, assuming that the complete states of each sensor node are well known by the base station. This presents the best effort performance of the scheduling that can be collected in a wireless powered sensor network. The simulation results show that, in terms of network throughput and packet loss rate, the proposed scheduling model significantly improves the network performance.
Meng, J, Huang, J, Sheng, D, Sloan, SW, Cao, P & Fan, W 1970, 'Mathematical programming based DEM for geomaterials', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 315-321.
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In this paper, a discrete numerical model using second-order cone programming is presented. The resulting optimisation problem is solved using an off-the-shelf interior-point algorithm. In contrast to the classical DEM, the purely static problem can be formulated directly without using artificial damping. The proposed approach can also be readily extended to dynamics problems. Due to the implicit time integration scheme adopted, large time steps can be employed. Importantly, the proposed approach is more general than the classical DEM because rigid particles and rigid-cementation in geomaterials can also be considered. The capabilities of the proposed method are demonstrated through (1) a biaxial compression test on granular media using circular particles; and (2) the simulation of brittle rock failure using polygonal particles.
Movassaghi, S, Maleki, B, Smith, DB & Abolhasan, M 1970, 'Biologically inspired self-organization and node-level interference mitigation amongst multiple coexisting wireless body area networks', 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, Valencia, Spain, pp. 1221-1226.
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© 2017 IEEE. This paper presents a node-level self-organizing interference avoidance scheme (SIAC) between multiple coexisting wireless body area networks (WBANs) that incorporates self-organization and smart spectrum allocation. It follows a biologically inspired approach based on the theory of pulse-coupled oscillators for self-organization. The proposed scheme makes three major contributions as compared to the current literature. Firstly, it considers node-level interference for internetwork interference mitigation rather than considering each WBAN as a whole. Secondly, it allocates synchronous and parallel transmission intervals for interference avoidance in an optimal manner and dynamically adapts to changes in their coexistence. Finally, it achieves collision-free, self-organized communication with only information of the firing signal of each WBAN and does not require a global coordinator to manage its communications. It operates on a nodes traffic priority, signal strength, and density of sensors in a WBAN. Simulation results show that our proposal achieves a fast convergence time despite the little information it receives. Moreover, SIAC is shown to be robust to variations in signal strength, number of coexisting WBANs and number of sensor nodes within each WBAN.
Mukunthan, A, Cooper, CS, Safaei, F, Franklin, DR & Abolhasan, M 1970, 'Leveraging the Propagation Model to Make Greedy Routing Decisions in Urban Environments.', VTC Spring, IEEE Vehicular Technology Conference, IEEE, Sydney, NSW, Australia, pp. 1-6.
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© 2017 IEEE. The CORNER propagation model, first proposed in 2010, has been previously validated and found to be a reasonably accurate representation of propagation scenarios in urban Vehicular Ad Hoc Networks (VANETs). This paper considers the impact of the propagation environment on routing performance and reveals a pressing need to consider more accurate propagation models when designing urban VANET routing protocols. A greedy routing protocol, which uses CORNER's propagation estimates for neighbour selection, is then presented. The new protocol, named Corner Propagation Stateless Routing (CPSR) is compared to GPSR, a benchmark protocol for VANETs, showing between 87% and 300% improvement in packet delivery ratio at higher network loads.
Ngo, NT, Indraratna, B & Biabani, MM 1970, 'Performance Assessment of Geocell-Reinforced Subballast: Modeling and Design Implications', Geotechnical Frontiers 2017, Geotechnical Frontiers 2017, American Society of Civil Engineers, Orlando, FL, pp. 374-383.
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This paper presents a study of the load-deformation behavior of geocell-stabilised subballast subjected to cyclic loads using a large-scale track process simulation apparatus and numerical modelling. The tests and numerical simulations were conducted to mimic the actual track conditions. Subjected to a given frequency and cyclic loads the predicted load-deformation behavior of the subballast with and without geocell inclusions match reasonably with those measured in the laboratory, and show that geocell could effectively decrease the lateral and axial deformations of the reinforced subballast. The results also provide an insight to design of rail tracks capturing the roles of geocell in decreasing lateral deformation of subballast. Additionally, the numerical modelling carried out in this study can be applied in the preliminary design of track substructure where a wide range of subballast aggregates and geocell mattresses with varying strengths and stiffness can be considered.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 1970, 'Coupled DEM-FEM analysis for simulating ballasted rail tracks', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 528-539.
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Ballasted tracks play an essential role in its economy through transporting freight and bulk commodities between major cities and ports, and carrying passengers, particularly in urban areas. Ballast usually consists of hard and strong angular particles, which are derived from high strength unweathered rocks. Ballast aggregates undergo gradual and continuing degradation under cyclic train loadings. In this study, the load-deformation responses of ballasted rail tracks subjected to cyclic loading are studied experimentally using a large-scale Track Process Simulation Apparatus (TPSA), and numerically through a coupled discrete-continuum approach, namely, coupled DEM-FEM. Laboratory tests are carried out to examine the deformation and degradation responses of ballast subjected to cyclic train loading under a frequency of f=15 Hz and a lateral confinement of σxx=10 kPa. Test results reveal that significant settlements are observed during the initial load cycles, followed by gradually increased deformation, arriving at a steady value towards the end of testing. A rigorous coupling model based on discrete element method (DEM) and finite element method (FEM) is introduced to predict the load-deformation behaviour of the ballast assembly considering the interaction of discrete ballast grains and continuum subgrade. In this coupled model, the discrete ballast grains are modelled by DEM and the subgrade domain is modelled as a continuum by FEM. Interface elements are introduced to transmit the interacting forces and displacements between adjoining material domains (i.e. discrete and continuum) whereby the DEM transfers contact forces to the FEM, and then the FEM updates the displacements back to the DEM. The coupled model is validated by comparing the predicted ballast settlement responses with those obtained experimentally. Contact force distributions, stress contours and a corresponding number of broken bonds are analysed. This combined DEM-FEM model is also us...
Ngo, NT, Indraratna, B, Rujikiatkamjorn, C & Neville, T 1970, 'DEM modelling of geocells reinforced subballast in rail tracks', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 1403-1406.
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This paper presents a study of the load-deformation behaviour of geocell-reinforced subballast under cyclic loads using laboratory tests and discrete element method (DEM). A series of large-scale laboratory tests with and without geocell inclusions are carried out using a track process simulation apparatus to study the beneficial effect of the geocells in decreasing the lateral and vertical deformations of railway subballast. Numerical studies conducted in the DEM can capture the reinforcement effect of geocells, considering micromechanical analysis subjected to a given frequency and load cycles, the predicted load-settlement response of the subballast with and without geocell agrees well with those measured experimentally. This finding indicates that the proposed DEM model is able to capture the deformation behaviour of the subballast reinforced by the geocells. These observations clearly emphasise the beneficial effects of the geocell in decreasing the deformation of subballast from a micromechanical perspective.
Ngoc, TP, Li, D, Fatahi, B & Khabbaz, H 1970, 'A review on the influence of degree of saturation on small strain shear modulus of unsaturated soils', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, International Conference on Soil Mechanics and Geotechnical Engineering, ISSMGE, Seoul, Korea, pp. 1225-1228.
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Small-strain shear modulus (Gmax) is an important parameter in the analysis and design of structures resting on liquefiable soils, particularly under dynamic loads such as earthquakes. In real condition, soil layers near the ground surface consistently undergo variation of degree of saturation (Sr) due to the change of weather or loading-unloading processes that lead to the variation of Gmax. To date, this area has received limited attention and still encounters difficulties in evaluating the influence of Sr on Gmax as well as capturing the effect of hysteresis on water retention behaviour. This study concentrates on the relationship between Sr and Gmax based on available experimental data in literature. The results of the analysis show that Sr plays an important role in the magnitude of Gmax for both cohesionless and cohesive unsaturated soils, while it has a greater influence on the latter. In order to predict Gmax for cohesive soils within the full range of degree of saturation, apart from the influence of Sr on the contribution of matric suction (ym), the influence of Sr on the contribution of plastic fines, salt concentration and van der Waals attraction should be additionally included.
Nguyen, HH, Khabbaz, H, Fatahi, B & Hsi, J 1970, 'Effects of installing controlled modulus columns on previously installed columns', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, the 19th International Conference on Soil Mechanics and Geotechnical Engineering, Seoul, South Korea, pp. 2611-2614.
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Controlled modulus columns (CMC) ground improvement technique is an attractive geotechnical solution for modification of soft soils. This technique uses a displacement auger during column installation, aiming to reduce the construction cost and disposal of excavated materials. However, lateral and vertical soil movement induced by the installation process may pose potential risks to the adjacent previously installed columns. Only a handful of studies have been attempted in quantifying such effects. This paper presents the results of a numerical investigation on the effects of CMC installation sequence on the already installed columns using the three-dimensional finite difference software package FLAC3D. The results indicate that the installation sequence should be taken into account in the design process to minimise any adverse effects of installing new CMCs on the existing columns.
Nguyen, T, Indraratna, B & Rujikiatkamjorn, C 1970, 'Finite element modelling of biodegradable jute drains', In Proceedings of the 15th IACMAG, Wuhan.
Nguyen, TT, Indraratna, B & Rujikiatkamjorn, C 1970, 'A numerical investigation into the transverse permeability of fibrous geomaterials', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 821-824.
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Fibrous geomaterials are widely used in geo-engineering practices for stabilisation, filtration and drainage. Most applications rely on their exceptional hydraulic conductivity despite the current paucity of numerical methods which can simultaneously capture the behaviour of fibre and fluid. In this paper, a coupling numerical approach is proposed where fibres are modelled by Discrete Element Method (DEM) and fluid is simulated by Finite Volume Method (FVM). The Parallel Bond Model incorporated in DEM will reasonably capture the linear stress-strain behaviour of natural fibres such as jute, but unlike previous studies where the fibres are either pre-formed and have an unchanged geometry, the coupling technique provides a good agreement in predicting the hydraulic behaviour of fibrous porous media. The motion of fibres due to fluid flow is also analysed.
Nguyen, VV, Li, J & Erkmen, E 1970, 'Numerical investigation of a linkage modelling technique for damage identification using FRF-based model updating', SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings, International Conference on Structural Health Monitoring of Intelligent Infrastructure, Brisbane, QLD, pp. 1243-1252.
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This paper presents a novel method of identifying the location and severity of damage in a bridge component via model updating where the number of degrees of freedom (DOF) in the finite element (FE) model far exceeds the DOFs measured on a structure. First, the FE model is divided into partitions, each with a predefined Young's modulus. These Young's moduli are used as the updating parameters where the reduction in the Young's moduli is used to indicate damage. The mass and stiffness matrices of the FE model is reduced to a linkage model using the System Equivalent Reduction Expansion Process (SEREP). Then the measured DOFs of the bridge component is expanded to the DOF of the linkage model using the mass and stiffness matrices of the linkage model. Based on the expanded modal data, interpolated FRFs are synthesised and used to form the FRF sensitivity matrix, which is iteratively used to calculate the values of the updating parameters until convergence is achieved. The resulting Young's moduli are used to calculate the damage index for each partition of the FE model. The proposed method is explained and verified using a numerical study. This method has the potential to locate and quantify damage in a structure where sensor instrumentation is otherwise inadequate due to the limitation in sensor availability and access for sensor installation.
Nguyen, VV, Li, J, Yu, Y, Dackermann, U & Alamdari, MM 1970, 'Simulation of various damage scenarios using finite element modelling for structural health monitoring systems', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC Press/Balkema, Australia, pp. 1541-1546.
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Structural Health Monitoring (SHM) is a developing technology for asset management of structures including bridge assets. A crucial benefit of SHM is its ability to monitor the health status of structures using continuous measurements. As a key in SHM, the application of damage detection algorithms to assess the condition of a structure using vibration measurements can be enhanced by providing structural information under various damaged scenarios, which can be obtained from updated numerical models that realistically represent the in-situ structure. However, the dynamic characteristics of a structure are sensitive to uncertainties of various parameters, including material properties and boundary conditions, which require updating in the Finite Element (FE) model to ensure that the model replicates the actual structure. This study focuses on the development of an FE model for the accurate simulation of a jack arch replica structure of the Sydney Harbour Bridge. An experimental jack arch replica is produced to simulate various damage scenarios for laboratory testing. A matching FE model of the jack arch replica is generated and updated using Genetic Algorithm (GA) based on experimental measurements. Damage is simulated in the updated model and the results are validated using the experimental test results. The successful simulation of damage using updated FE models enables the generation of a large number of damage cases that can be trained into an SHM system to improve its damage detection capabilities.
Qi, Y, Indraratna, B, Heitor, A & Vinod, J 1970, 'Developing an Energy Absorbing Layer Using Waste Materials', International Conference of Ground Improvement (ICGI2017), Hangzhou, China.
Rafiei, A, Abolhasan, M, Franklin, DR, Safaei, F, Smith, S & Ni, W 1970, 'Cooperative recovery of coverage holes in WSNs via disjoint spanning trees.', ICSPCS, International Conference on Signal Processing and Communication Systems, IEEE, Gold Coast, QLD, Australia, pp. 1-10.
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© 2017 IEEE. Large scale coverage holes (CHs) resulting from correlated node failures, can significantly degrade quality of service and also jeopardise the integrity of WSNs. In the absence of centralised control, the distributed relocation of deployed nodes becomes a promising solution especially in harsh and hostile environments. In this paper, a distributed method is proposed that enables a network to partially or entirely repair itself through a collection of distributed movements of disjoint spanned trees (DS-Trees) towards the CHs. DS-Trees are spanned based on the nodes distances from the CHs, which are autonomously perceived by the nodes and their one-hop neighbours. DS-Trees around the CHs are spanned in a downstream style outwards from the holes, as nodes select their parents based on the minimum distance to the CH from their neighbours; nodes then decide whether or not to follow the movements of their DS-Trees parents. To examine the efficiency of the proposed model, its performance is compared with two Voronoi-based and one force-based node relocation algorithms. Results show that the proposed DS-Tree model either outperforms or matches the alternative approaches across a wide range of scenarios.
Rafiei, A, Abolhasan, M, Franklin, DR, Safaei, F, Smith, S & Ni, W 1970, 'Effect of the number of participating nodes on recovery of WSN coverage holes.', ITNAC, International Telecommunication Networks and Applications Conference, IEEE Computer Society, Melbourne, VIC, Australia, pp. 1-8.
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© 2017 IEEE. Coverage holes (CHs) due to the correlated node failures, if not appropriately addressed in a timely manner, not only disrupt network's operation but also can compromise its integrity. In the absence of centralised control, distributed node relocation can be an effective solution to recover CHs. Relocation algorithms that mainly applied to all nodes to address networks' coverage and unbalanced deployments problems, are not efficient as participating nodes beyond a certain distance and depth from the CHs do not significantly contribute to recovery of CHs. Here, the effects of the number of participating nodes and movement iterations on recovery of CHs are examined in two Voronoi-based and one force-based node relocation algorithms.
Rasekh, H, Aziz, N, Mirza, A, Nemcik, J, Li, X, Yang, G & Khaleghparast, S 1970, 'Double Shear Testing of Cable Bolts with No Concrete Face Contacts', Procedia Engineering, Elsevier BV, pp. 1169-1177.
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© 2017 Published by Elsevier Ltd. A new series of double shear tests were carried out using a newly modified double shear apparatus which prevented contacts between concrete block surfaces during shearing. 13 double shear tests were carried out using 21 mm diameter 19 (9 × 9 × 1) seal construction wire strand cable (also called Superstrand cable), Plain SUMO, Indented SUMO, Spiral MW9 and Plain MW10 cable bolts. These cables were tested subjected to different pretension loads. Concrete blocks with Uniaxial Compressive Strength (UCS) of 40 MPa and Stratabinder grout were used for all the tests to maintain test consistency. The results show that the peak shear load and the corresponding shear displacement decrease by increasing the pretension load of the tested cable. The Ultimate tensile strength, lay length, number of wires and cable bolt surface profile type (plain and spiral/indented) are important factors in total shear strength of the cable bolt.
Robson, E, Wijayaratna, K & Dixit, VV 1970, 'From CBA to CGE: A review of computable general equilibrium modelling for transport appraisal', ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings.
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In the transport planning process, decision makers require reliable and informative appraisals to facilitate comparisons and determine if a proposal is worthwhile to society. The cost benefit analysis is the most common form of appraisal, but the consumer surplus metric used in cost benefit analyses will only reflect total social welfare if markets operate perfectly. There may be significant uncaptured impacts, known as wider economic impacts, which agencies are beginning to incorporate in appraisals using ad-hoc methods. Computable general equilibrium (CGE) models are an increasingly popular method for assessing the economic impacts of transport, including both direct and wider economic impacts, as they can determine the distribution of impacts among every market and agent in the economy. By simulating the behaviour of households, firms and others from microeconomic first principles, they can provide a measure of welfare that guarantees no double counting and accounts for nth order effects. This paper reviews CGE models that have been applied to transport issues, and discusses the general role of CGE modelling in transport appraisal as well as theoretical and practical concerns regarding CGE modelling practice.
Robson, E, Wijayaratna, K & Dixit, VV 1970, 'From CBA to CGE: A review of computable general equilibrium modelling for transport appraisal', ATRF 2017 - Australasian Transport Research Forum 2017, Proceedings.
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© 2017 ATRF, Commonwealth of Australia. All rights reserved. In the transport planning process, decision makers require reliable and informative appraisals to facilitate comparisons and determine if a proposal is worthwhile to society. The cost benefit analysis is the most common form of appraisal, but the consumer surplus metric used in cost benefit analyses will only reflect total social welfare if markets operate perfectly. There may be significant uncaptured impacts, known as wider economic impacts, which agencies are beginning to incorporate in appraisals using ad-hoc methods. Computable general equilibrium (CGE) models are an increasingly popular method for assessing the economic impacts of transport, including both direct and wider economic impacts, as they can determine the distribution of impacts among every market and agent in the economy. By simulating the behaviour of households, firms and others from microeconomic first principles, they can provide a measure of welfare that guarantees no double counting and accounts for nth order effects. This paper reviews CGE models that have been applied to transport issues, and discusses the general role of CGE modelling in transport appraisal as well as theoretical and practical concerns regarding CGE modelling practice.
Rujikiatkamjorn, C & Indraratna, B 1970, 'An Evaluation of vacuum consolidation performance using observational techniques', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2643-2646.
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Soft clays in coastal areas normally have low shear strength and high compressibility. The construction activities for near shore infrastructure on these deposits often pose geotechnical problems due to large time dependent settlement and lateral movement. Ground improvement techniques are used in this terrain to reduce the water content of soft clays by preloading with vertical drains. Depending on the magnitude of the surcharge, substantial and immediate settlement with lateral movement can occur during preloading, which then causes problems of undrained stability in the loaded areas. Vacuum assisted preloading has now become a popular method of ground improvement in Australia where substantial loads must be applied to meet a desired rate of settlement and mitigate undrained failure. To assist vacuum propagation at significant depths, vertical drains are usually used in conjunction. At the Port of Brisbane and the Ballina Bypass, Australia, vacuum assisted surcharge preloading and conventional surcharge preloading schemes were used to reduce the time required for consolidation and long term settlement in soft Holocene clays. The design of the combined vacuum and surcharge fill system and construction of the embankment are described in this paper. Field monitoring data are presented to demonstrate how the embankment performed during construction. The paper also evaluates the relative performance of the two contrasting preloading systems (i.e. vacuum and non-vacuum system) using a dimensionless analysis. Here the dimensionless parameter can be considered to act as a 'filter' to distinguish the relative performance of the improved foundations for vacuum combined surcharge loading, even if the shape of the time settlement curves and the degree of consolidation are similar.
Sadra, S & Abolhasan, M 1970, 'On improving the saturation performance of IEEE802.15.6-based MAC protocols in Wireless Body Area Networks', 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, Valencia, Spain, pp. 1233-1238.
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© 2017 IEEE. Wireless Body Area Networks (WBANs) were designed to collect and transfer vital physiological parameters within a short distance of the human body by employing low-power, light-weight, small-sized and smart implantable or wearable sensor devices. Lately, WBANs are expected to support various types of applications with data rates from a few Kbps upto 10 Mbps and satisfy the heterogeneous requirements of both medical and consumer electronics applications. Hence, novel communication protocols that consider a unique set of constraints and demands of these networks need to be developed to provide optimum system efficiency and data transmission reliability. As the IEEE 802.15.6 Medium Access Control (MAC) protocol based on the latest WBANs standard, cannot maintain the balance between the strict energy limitation and Quality of Service (QoS) requirements of such networks, this paper focuses on developing MAC protocols to improve the performance of WBANs specifically in the saturation condition. Two IEEE802.15.6-based MAC protocols are proposed to enhance channel access for the highest user priority and the other user priorities in saturated networks. The simulation results show better network performance as well as lower energy consumption in the proposed MAC protocols compared to the IEEE 802.15.6 MAC protocol.
Saqib, M, Daud Khan, S, Sharma, N & Blumenstein, M 1970, 'A study on detecting drones using deep convolutional neural networks', 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), IEEE, Lecce, Italy, pp. 1-5.
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© 2017 IEEE. The object detection is a challenging problem in computer vision with various potential real-world applications. The objective of this study is to evaluate the deep learning based object detection techniques for detecting drones. In this paper, we have conducted experiments with different Convolutional Neural Network (CNN) based network architectures namely Zeiler and Fergus (ZF), Visual Geometry Group (VGG16) etc. Due to sparse data available for training, networks are trained with pre-trained models using transfer learning. The snapshot of trained models is saved at regular interval during training. The best models having high mean Average Precision (mAP) for each network architecture are used for evaluation on the test dataset. The experimental results show that VGG16 with Faster R-CNN perform better than other architectures on the training dataset. Visual analysis of the test dataset is also presented.
Saqib, M, Daud Khan, S, Sharma, N & Blumenstein, M 1970, 'Extracting descriptive motion information from crowd scenes', 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Christchurch, New Zealand, pp. 1-6.
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© 2017 IEEE. An important contribution that automated analysis tools can generate for management of pedestrians and crowd safety is the detection of conflicting large pedestrian flows: this kind of movement pattern, in fact, may lead to dangerous situations and potential threats to pedestrian's safety. For this reason, detecting dominant motion patterns and summarizing motion information from the scene are inevitable for crowd management. In this paper, we develop a framework that extracts motion information from the scene by generating point trajectories using particle advection approach. The trajectories obtained are then clustered by using unsupervised hierarchical clustering algorithm, where the similarity is measured by the Longest Common Sub-sequence (LCS) metric. The achieved motions patterns in the scene are summarized and represented by using color-coded arrows, where speeds of the different flows are encoded with colors, the width of an arrow represents the density (number of people belonging to a particular motion pattern) while the arrowhead represents the direction. This novel representation of crowded scene provides a clutter free visualization which helps the crowd managers in understanding the scene. Experimental results show that our method outperforms state-of-the-art methods.
Saqib, M, Khan, SD & Blumenstein, M 1970, 'Detecting dominant motion patterns in crowds of pedestrians', SPIE Proceedings, Eighth International Conference on Graphic and Image Processing, SPIE, Tokyo, Japan, pp. 102251L-102251L.
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© 2017 SPIE. As the population of the world increases, urbanization generates crowding situations which poses challenges to public safety and security. Manual analysis of crowded situations is a tedious job and usually prone to errors. In this paper, we propose a novel technique of crowd analysis, the aim of which is to detect different dominant motion patterns in real-time videos. A motion field is generated by computing the dense optical flow. The motion field is then divided into blocks. For each block, we adopt an Intra-clustering algorithm for detecting different flows within the block. Later on, we employ Inter-clustering for clustering the flow vectors among different blocks. We evaluate the performance of our approach on different real-time videos. The experimental results show that our proposed method is capable of detecting distinct motion patterns in crowded videos. Moreover, our algorithm outperforms state-of-the-art methods.
Sharbaf, M, Ghafoori, N & Dumitru, N 1970, 'Geogrid in paved and unpaved road systems: A review of mechanisms and design mehods', Bearing Capacity of Roads, Railways and Airfields - Proceedings of the 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields, BCRRA 2017, International Conference on the Bearing Capacity of Roads, Railways and Airfields, CRC Press, Athens, Greece, pp. 1161-1168.
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© 2017 Taylor & Francis Group, London. This study has focused on the effect of using Lime (L) from 1.5% to 6.25%; Bagasse Ash (BA) between 6% and 25% and combination of BA-L reached up to 25% on the consolidation characteristic of expansive after the swelling pressure has been determined. The results indicated that the swelling pressure was reduced with increasing BA or L. Furthermore, the results were improved when BA was added to soil treated with L. The swelling pressure of untreated soil decreased from 80 kPa (untreated soil) to 7 kPa (treated with 25% BA-L). In consolidation tests, the pre-consolidation stress has been developed from 180 kPa with untreated soil to 290 kPa with 6.25% lime and 350 kPa when 18.75% BA was added to soil-6.25% L. Furthermore, better results were ascertained when soft clay stabilized with 25% BA-L in comparison with compacted virgin soft clay samples. In addition, the compression indices, and swelling indices decreased 97% and 56%, respectively.
Sharma, N, Sengupta, A, Sharma, R, Pal, U & Blumenstein, M 1970, 'Pincode detection using deep CNN for postal automation', 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Christchurch, New Zealand, pp. 1-6.
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© 2017 IEEE. Postal automation has been a topic of research over a decade. The challenges and complexity involved in developing a postal automation system for a multi-lingual and multi-script country like India are many-fold. The characteristics of Indian postal documents include: multi-lingual behaviour, unconstrained handwritten addresses, structured/unstructured envelopes and postcards, being among the most challenging aspects. This paper examines the state-of-the-art Deep CNN architectures for detecting pin-code in both structured and unstructured postal envelopes and documents. Region-based Convolutional Neural Networks (RCNN) are used for detecting the various significant regions, namely Pin-code blocks/regions, destination address block, seal and stamp in a postal document. Three network architectures, namely Zeiler and Fergus (ZF), Visual Geometry Group (VGG16), and VGG M were considered for analysis and identifying their potential. A dataset consisting of 2300 multilingual Indian postal documents of three different categories was developed and used for experiments. The VGG-M architecture with Faster-RCNN performed better than others and promising results were obtained.
Sirivivatnanon, V, Khabbaz, H & Ayton, G 1970, '“Performance-based Specification of sand for skid resistance of concrete pavements”, ASCP 4th Concrete Pavement Conference, 2017.', ASCP 4th Concrete Pavement Conference, 2017, ASCP 4th Concrete Pavement Conference, 2017.
Sun, WJ, Liu, C, Wei, G, Sun, DA, Wei, ZF, Liu, SQ & Fatahi, B 1970, 'Effect of sand content on undrained behaviour of GMZ bentonite-sand mixtures', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, pp. 1497-1503.
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The hydro-mechanical behaviour was studied by carrying out the constant water content triaxial tests on Gaomiaozi (GMZ) bentonite-sand mixtures with sand content of 70% and 50%, and the stress-strain relationship, deformation and pore water pressure under undrained shear state were obtained, together with the changes of the initial suction, compressibility, suction and strength with the sand content in mixtures. Moreover, the control mechanism was analyzed in microscopic level. The research provides the experimental basis to establish the hydro-mechanical model for unsaturated expansive soils under undrained state, and can be available for reference in proportional optimization design in bentonite based materials used in deep geological disposal system and waste landfills projects.
Suwanwiwat, H, Das, A, Ferrer, MA, Pal, U & Blumenstein, M 1970, 'An Automatic Student Verification System Utilising Off-Line Thai Name Components', 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Sydney, Australia, pp. 1-6.
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This research proposed an automatic student identification and verification system utilising off-line Thai name components. The Thai name components consist of first and last names. Dense texture-based feature descriptors were able to yield encouraging results when applied to different handwritten text recognition scenarios. As a result, the authors employed such features in investigating their performance on Thai name component verification system. In this research, Dense-Local Binary Pattern, Dense-Local Directional Pattern, and Local Binary Pattern combined with Local Directional Pattern were employed. A base-line shape/feature i.e. Hidden Markov Model (HMM) was also utilised in this study. As there is no dataset on Thai name verification in the literature, a dataset is proposed for a Thai name verification system. The name component samples were collected from high school students. It consists of 8,400 name components (first and last names) from 100 students. Each student provided 60 genuine name components, and each of the name components was forged by 12 other students. An encouraging result was found employing the above-mentioned features on the proposed dataset.
Vizcarra, G, Casagrande, M & Nimbalkar, S 1970, 'DEM Three-dimensional modeling of triaxial testing on railway ballast', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 1443-1446.
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This article presents the results of numerical simulations of cyclic loading tests conducted on particles that simulate railroad ballast. The objective of this study was to evaluate the deformation of ballast under a large number of loading cycles and to study the influence of the two different particle size distributions. One of them was according to particle size distribution recommended by Indraratna and co-workers in the past as an improvement to Australian Standard and the other was prepared in accordance with Brazilian standard. The discrete element method offers a new means of studying the response characteristics of railway ballast. The basic idea of discrete element method (DEM) is that arbitrary discontinuities are divided into a set of rigid elements, making each rigid element satisfy the equations of motion, use time step iteration method for solving the equations of motion of rigid elements, and then obtain the overall movement patterns of arbitrary discontinuities. In this study, the discrete element method of analysis has been used to simulate the geotechnical behaviour of railway ballast observed during the testing.
Wang, B, Gao, Y, Sun, C, Blumenstein, M & La Salle, J 1970, 'Can Walking and Measuring Along Chord Bunches Better Describe Leaf Shapes?', 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, Honolulu, HI, USA, pp. 2047-2056.
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© 2017 IEEE. Effectively describing and recognizing leaf shapes under arbitrary deformations, particularly from a large database, remains an unsolved problem. In this research, we attempted a new strategy of describing shape by walking along a bunch of chords that pass through the shape to measure the regions trespassed. A novel chord bunch walks (CBW) descriptor is developed through the chord walking that effectively integrates the shape image function over the walked chord to reflect the contour features and the inner properties of the shape. For each contour point, the chord bunch groups multiple pairs of chord walks to build a hierarchical framework for a coarse-to-fine description. The proposed CBW descriptor is invariant to rotation, scaling, translation, and mirror transforms. Instead of using the expensive optimal correspondence based matching, an improved Hausdorff distance encoded correspondence information is proposed for efficient yet effective shape matching. In experimental studies, the proposed method obtained substantially higher accuracies with low computational cost over the benchmarks, which indicates the research potential along this direction.
Wang, JJ, Gowripalan, N, Li, J & Nguyen, VV 1970, 'Close-range photogrammetry for accurate deformation distribution measurement', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, Taylor and Francis, Perth, Australia, pp. 793-799.
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This paper introduces a methodology for improving the accuracy of Deformation Distribution Measurement (DDM) using close-range photogrammetry. After reviewing various algorithms for 2D Digital Image Correlation (DIC), Zero-Normalized Cross-Correlation (ZNCC) is selected for deformation measurement. The impact of several other factors on DIC measurement accuracy has been investigated, including the type of imaging sensors, the contrast and pattern of a specimen, and searching window size. Optimal option of these factors is proposed. The technique is utilized in the experiment of applying static loading on a replica of a concrete structural component used for Sydney Harbour Bridge. Test results presented in the paper include DIC measurements and validation data from conventional sensors.
Wang, Z, Shivakumara, P, Lu, T, Basavanna, M, Pal, U & Blumenstein, M 1970, 'Fourier-Residual for Printer Identification', 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), IEEE, Japan, pp. 1114-1119.
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© 2017 IEEE. Printer identification is challenging due to advanced software technologies in the field of forgery detection. This paper presents a new idea of using the Fourier transform residual for the identification of documents printed by different printers. The proposed approach first convolves a Laplacian mask with a Fourier transform in the frequency domain to smoothen the edges. Next, we apply an inverse Fourier transform to reconstruct images from smoothed information (RFL). Similarly, the proposed approach reconstructs images using gray information of the input image (RFG). Then the residual is calculated by subtracting RFG from RFL. The set of statistical features, texture and spatial features are extracted from residual images for printer identification. Experimental results with the existing method on our dataset and a standard dataset show that the proposed approach outperforms the existing approach on both the datasets in terms of classification rate, recall, precision and F-measure.
Wu, D, Sharma, N & Blumenstein, M 1970, 'Recent advances in video-based human action recognition using deep learning: A review', 2017 International Joint Conference on Neural Networks (IJCNN), 2017 International Joint Conference on Neural Networks (IJCNN), IEEE, Anchorage, Alaska, USA, pp. 2865-2872.
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© 2017 IEEE. Video-based human action recognition has become one of the most popular research areas in the field of computer vision and pattern recognition in recent years. It has a wide variety of applications such as surveillance, robotics, health care, video searching and human-computer interaction. There are many challenges involved in human action recognition in videos, such as cluttered backgrounds, occlusions, viewpoint variation, execution rate, and camera motion. A large number of techniques have been proposed to address the challenges over the decades. Three different types of datasets namely, single viewpoint, multiple viewpoint and RGB-depth videos, are used for research. This paper presents a review of various state-of-the-art deep learning-based techniques proposed for human action recognition on the three types of datasets. In light of the growing popularity and the recent developments in video-based human action recognition, this review imparts details of current trends and potential directions for future work to assist researchers.
Xu, R, Fatahi, B & Li, D 1970, 'Effects of Soil Stiffness on Seismic Response of Buildings Considering Soil-Pile-Structure Interaction', The 19th International Conference on Soil Mechanics and Geotechnical Engineering, Seoul, Korea.
Yeganeh, N, Fatahi, B & Terzaghi, S 1970, 'Effects of shear wave velocity profile of soil on seismic response of high rise buildings', Proceedings - IACMAG 2017, 15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, International Conference of the International Association for Computer Methods and Advances in Geomechanics, International Association for Computer Methods and Advances in Geomechanics (IACMAG), Wuhan, China, pp. 920-928.
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There is, nowadays, a conspicuous demand for the high rise buildings in the high-density dwellings of the urban areas; in consequence, harnessing the whiz-bang numerical simulations plus conducting the rigorous experimental studies so as to design and construct such prodigious structures would be essential. Thus, the appropriate parameters for modeling the structure and the soil medium in the Soil-Structure Interaction (SSI) system should be selected. The soil-structure interaction is referred to the process in which the soil response is told on by the structure motion whilst the latter is affected by the soil motion. The current research zeroed in on the soil shear wave velocity and its influence on the superstructure performance. Invoking the weighted average shear wave velocity with the aim of calculating the soil shear modulus, which is closely related to the strength and deformation characteristics of the soil, has been a hotly debated issue since the aforesaid parameter was posited by a plethora of codes and regulations to obtain the soil site classification required for the earthquake design. To that end, the numerical model, having two assorted profiles associated with the shear wave velocity, namely, the in situ non-uniform profile (Case A) and the equivalent uniform profile (Case B), was built by means of FLAC3D, capable of analyzing the complex interaction issues via the direct method whereby the entire system of the structure-foundation-soil is modeled and analyzed in one single step. To put it in a nutshell, employing the weighted average shear wave velocity for the entire soil mass in parsing of the 3D seismic soil-structure interaction problems would be accused for ending up with somewhat unreliable results, e.g., underestimated drift ratio and building deformation, which might be the culprit of the damage to the building and possibly the death of the residents residing in the earthquake-prone zones.
Yu, Y, Li, J, Dackermann, U & Subhani, M 1970, 'Development of a portable NDE system with advanced signal processing and machine learning for health condition diagnosis of in-service timber utility poles', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC Press, Perth, Australia, pp. 1547-1552.
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Aiming at current shortcomings of Non-Destructive Evaluation (NDE) in health condition estimation of timber utility poles, this paper put forward a novel testing method via combination of a portable NDE system, advanced signal processing and machine learning techniques. Primarily, the multi-sensing strategy is employed and incorporated in current NDE technique to capture reflected stress wave signals, avoiding difficult interpretation of complicated wave propagation by only one sensor. Secondly, advanced signal processing methods, such as Ensemble Empirical Mode Decomposition (EEMD) and Principal Component Analysis (PCA), are introduced to extract effective wave patterns that are sensitive to structural damage. Moreover, based on captured signal features, the state-of-the-art machine learning techniques are applied to implement the condition assessment. Finally, field testing results of 26 decommissioned timber poles at Mason Park in Sydney are used to validate the effectiveness of the proposed method.
Yu, Y, Li, Y & Li, J 1970, 'Sigmoid function-based hysteresis modeling of magnetorheological pin joints', 2017 3rd International Conference on Control, Automation and Robotics (ICCAR), 2017 3rd International Conference on Control, Automation and Robotics (ICCAR), IEEE, Nagoya, Japan, pp. 514-517.
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© 2017 IEEE. The magnetorheological (MR) pin joint is a semi-active control device which can be installed in the column-beam structures for structural vibration control. Nevertheless, the nonlinear response of the MR pin joint together with its unique rheological nature makes the device modeling difficult and impedes its engineering application. Although many complicated phenomenal models have been proposed to illustrate the dynamic behaviour of MR devices, a large number of model parameters and differential equations bring the challenges for model identification and controller design. In this study, we try to predict the dynamic response of a MR pin joint using a novel and simple phenomenal model, which is comprised of a rotary spring, a rotary damper and a sigmoid function-based hysteresis component. Then, the model parameters are identified using trust-region-reflective least squares algorithm in MATLAB optimization toolbox. Finally, the experimental results under various loading conditions are used to validate the performance of the proposed model.
Yu, Y, Li, Y, Li, J, Gu, X & Royel, S 1970, 'Dynamic modeling of magnetorheological elastomer base isolator based on extreme learning machine', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC press, Perth, Australia, pp. 703-708.
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This paper presents a novel modeling method to describe the nonlinear and hysteretic characteristics of Magnetorheological Elastomer (MRE) isolator, which is a semi-active control device and used in vibration control of engineering structures such as vehicle suspension system, offshore platform and built infrastructure. In the proposed method, a new single-hidden-layer feed-forward neural network algorithm named Extreme Learning Machine (ELM) is adopted to set up the model, in which the captured responses such as displacement and velocity of the device together with applied current level are employed as model inputs while the model output is the shear force generated according to the external excitation. Finally, the experimental data are utilized to validate the performance of the proposed method.
Zhang, Z, Oberst, S & Lai, JCS 1970, 'Uncertainty analysis for the prediction of disc brake squeal propensity', INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, Internoise 2017, Hong Kong, China.
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ACT Since brake squeal was first investigated in the 1930s, it has been a noise, vibration and harshness (NVH) problem plaguing the automotive industry due to warranty-related claims and customer dissatisfaction. Accelerating research efforts in the last decade, represented by almost 70% of the papers published in the open literature, have improved the understanding of the generation mechanisms of brake squeal, resulting in better analysis of the problem and better development of countermeasures by combining numerical simulations with noise dynamometer tests. However, it is still a challenge to predict brake squeal propensity with any confidence. This is because of modelling difficulties that include the often transient and nonlinear nature of brake squeal, and uncertainties in material properties, operating conditions (brake pad pressure and temperature, speed), contact conditions between pad and disc, and friction. Although the conventional Complex Eigenvalue Analysis (CEA) method, widely used in industry, is a good linear analysis tool for identifying unstable vibration modes to complement noise dynamometer tests, it is not a predictive tool as it may either over-predict or under-predict the number of unstable vibration modes. In addition, there is no correlation between the magnitude of the positive real part of a complex eigenvalue and the likelihood that the unstable vibration mode will squeal. Transient nonlinear simulations are still computationally too expensive to be implemented in industries for even exploratory predictions. In this paper, a stochastic approach, incorporating uncertainties in the surface roughness of the lining, material properties and the friction coefficient, is applied to predict the squeal propensity of a full disc brake system by using CEA on a finite element model updated by experimental modal testing results. Results compared with noise dynamometer squeal tests illustrate the potential of the stochastic CEA approach ov...
Zhong, R, Indraratna, B, Rujikiatkamjorn, C, Kan, M, Vincent, P & Ryan, G 1970, 'A Model for Vacuum-assisted Soft Soil Consolidation with PVDs', ICSMGE 2017 - 19th International Conference on Soil Mechanics and Geotechnical Engineering, pp. 2685-2688.
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To maintain the ground stability and reduce the post-construction settlement, the soft deposits characterised by high water content, high compressibility and low permeability need to be treated by an appropriate ground improvement method prior to the construction of infrastructure. Application of PVD is a well-practiced ground improvement method for consolidating the soft clays. PVD can be used in conjunction with a fill surcharge, vacuum pressure or a combination of the two. An analytical unit cell model was proposed to capture the large strain geometry and the non-linear soil properties during the large settlement. This model showed an advantage over the traditional model in predicting the soft ground consolidation behaviour. In this paper, this model is used to analyse some case histories.
