Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 145-162.
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This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC–HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07–0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.
Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Review of studies on hydrological modelling in Malaysia', Modeling Earth Systems and Environment, vol. 4, no. 4, pp. 1577-1605.
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Hydrological models are vital component and essential tools for water resources and environmental planning and management. In recent times, several studies have been conducted with a view of examining the compatibility of model results with streamflow measurements. Some modelers are of the view that even the use of complex modeling techniques does not give better assessment due to soil heterogeneity and climatic changes that plays vital roles in the behavior of streamflow. In Malaysia, several public domain hydrologic models that range from physically-based models, empirical models and conceptual models are in use. These include hydrologic modeling system (HEC-HMS), soil water assessment tool (SWAT), MIKE-SHE, artificial neural network (ANN). In view of this, a study was conducted to evaluate the hydrological models used in Malaysia, determine the coverage of the hydrological models in major river basins and to identify the methodologies used (specifically model performance and evaluation). The results of the review showed that 65% of the studies conducted used physical-based models, 37% used empirical models while 6% used conceptual models. Of the 65% of physical-based modelling studies, 60% utilized HEC-HMS an open source models, 20% used SWAT (public domain model), 9% used MIKE-SHE, MIKE 11 and MIKE 22, Infoworks RS occupied 7% while TREX and IFAS occupy 2% each. Thus, indicating preference for open access models in Malaysia. In the case of empirical models, 46% from the total of empirical researches in Malaysia used ANN, 13% used Logistic Regression (LR), while Fuzzy logic, Unit Hydrograph, Auto-regressive integrated moving average (ARIMA) model and support vector machine (SVM) contributed 8% each. Whereas the remaining proportion is occupied by Numerical weather prediction (NWP), land surface model (LSM), frequency ratio (FR), decision tree (DT) and weight of evidence (WoE). Majority of the hydrological modelling studies utilized one or more statis...
Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 67-84.
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The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant...
Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Relationship between design floods and land use land cover (LULC) changes in a tropical complex catchment', Arabian Journal of Geosciences, vol. 11, no. 14.
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© 2018, Saudi Society for Geosciences. Rainfall characteristics are directly related to the climate of a basin, but this can only be noticed after a long period. Human activities, such as deforestation, tend to play a major role in transforming the land use land cover (LULC). Knowledge of the relationship between design floods and LULC is important in modeling and designing watershed management strategies. A study was conducted in the Kelantan River basin, Malaysia, to determine the impact of past and present LULC changes on peak discharge and runoff volumes. To achieve this, the basin was delineated into four catchments (Galas, Pergau, Nenggiri, and Lebir) due to its size and increased precision. Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was calibrated based on December 20–30th, 2014, flood in Kelantan. Flood hydrographs corresponding to 1984, 2002, and 2013 LULC conditions were simulated, and relative changes in peak discharge and runoff volume were determined for different return periods (2, 5, 10, 20, 50, 100 years). Results of LULC analysis showed that Galas recorded highest deforestation (54.35%). When the four catchments were compared with respect to highest contribution of outlet peak discharge, Lebir under 2013 LULC condition was the highest with 2847.70 m3/s. This was followed by Nenggiri (2196.90 m3/s), Galas (1252.7 m3/s), and Pergau (328.7 m3/s), all under the 2013 LULC condition. Results of unit response approach applied based on 50-year return period to the catchments for ranking their sub-basins revealed that the novel fa index developed in this study provides a better way of ranking sub-basins with respect to their contribution to the outlet and therefore is recommended for use. Methodologies developed in this study may be useful to land use planners from around the world which when applied can provide alternatives that will minimize the adverse effects of floods.
Abdullahi, S & Pradhan, B 2018, 'Land use change modeling and the effect of compact city paradigms: integration of GIS-based cellular automata and weights-of-evidence techniques', Environmental Earth Sciences, vol. 77, no. 6.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. In recent decades, attaining urban sustainability is the primary goal for urban planners and decision makers. Among various aspects of urban sustainability, environmental protection such as agricultural and forest conservations is very important in tropical countries like Malaysia. In this regard, compact urban development due to high density, rural development containment is known as the most sustainable urban forms. This paper attempts to propose an integrated modeling approach to predict the future land use changes by considering city compactness paradigms. First, the cellular automata (CA) were applied for calculating land use conversion. Next, weights-of-evidence (WoE) which is based on Bayes theory was utilized to calibrate CA model and to support the transitional rule assessment. Several urban-related parameters as well as compact city indicators were utilized to estimate the future land use maps. The results showed how compact development parameters and site characteristics can be combined using the WoE model to predict the probability of land use changes. The modeling approach supports the essential logic of probabilistic methods and indicates that spatial autocorrelation of various land use types and accessibility is the main drivers of urban land use changes.
Abdullahi, S, Pradhan, B & Mojaddadi, H 2018, 'City Compactness: Assessing the Influence of the Growth of Residential Land Use', Journal of Urban Technology, vol. 25, no. 1, pp. 21-46.
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© 2017 The Society of Urban Technology. In the urban sprawl paradigm, residential land use exhibits a more significant growth than other categories. Consequently, large proportions of the natural environment are converted to residential areas, particularly in tropical countries. Compact urban development is one of the most sustainable urban forms with environmental perspectives, such as rural development containment and natural environment preservation. However, no proper investigation of the relationship and influence of residential growth and city compactness is available. This study evaluated and forecasted the residential development of Kajang City in Malaysia based on compact development. First, the relationship between residential land use change and city compactness was evaluated. Second, residential growth was projected by utilizing the land transformation model (LTM) and the statistical-based weight of evidence (WoE) using various spatial parameters. Both models were evaluated with respect to observed land use and compactness maps. Results indicated that most of the newly developed residential areas were in zones where the degrees of compactness increase during certain periods. In addition, LTM performed better and provided a more accurate modeling of residential growth than the WoE. However, WoE provided clearer and more informative results than LTM in terms of functional relationships between dependent and independent variables related to city compactness.
Abolhasan, M, Abdollahi, M, Ni, W, Jamalipour, A, Shariati, N & Lipman, J 2018, 'A Routing Framework for Offloading Traffic From Cellular Networks to SDN-Based Multi-Hop Device-to-Device Networks', IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1516-1531.
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© 2004-2012 IEEE. Device-to-device (D2D) communications are set to form an integral part of future 5G wireless networks. D2D communications have a number of benefits such as improving energy efficiency and spectrum utilization. Until now much of the D2D research in LTE and 5G-type network scenarios have focused on direct (one-hop) communications between two adjacent mobile devices. In this paper, we propose a new routing framework called virtual ad hoc routing protocol (VARP). This framework introduces significant advantages such as better security, lower routing overheads, and higher scalability, when compared to conventional ad hoc routing protocols. It also reduces traffic overhead in LTE networks using multi-hop D2D communications under management of a software defined networking (SDN)-controller. Further, it enables the development of various types of routing protocols for different networking scenarios. To this end, a source-routing based protocol was developed on top of VARP, referred to as VARP-S. We present a detailed analytical study of routing overhead in the VARP-S protocol, as compared to overhead analysis of our previous proposed hybrid SDN architecture for wireless distributed networks (HSAW) Our results show that VARP-S, compared to HSAW, achieves higher network scalability and lower power consumption for mobile nodes.
Ahmadirouhani, R, Karimpour, M-H, Rahimi, B, Malekzadeh-Shafaroudi, A, Pour, AB & Pradhan, B 2018, 'Integration of SPOT-5 and ASTER satellite data for structural tracing and hydrothermal alteration mineral mapping: implications for Cu–Au prospecting', International Journal of Image and Data Fusion, vol. 9, no. 3, pp. 237-262.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The integration of information extracted from the Syste`m Pour l’Observation de la Terre (SPOT) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, comprehensive field and mineralogy studies demonstrates that phyllic alteration zone associated with northwestern (NW)–southeastern (SE) structural fractures is a high potential zone for Cu–Fe–Au vein-type mineralisation in the Bajestan region, the Lut block, east Iran. The fractal pattern was calculated for fractures map using the Box-Counting algorithm to the SPOT-5 data. Statistical parameters of fractures, such as density, intensity and fractures’ intersection were also determined. Band composition, specialised band ratio and Spectral Angle Mapper (SAM) classification methods were implemented to the ASTER dataset for detecting hydrothermal alteration zones, such as propylitic, phyllic, argillic and gossan. Results indicate that the maximum value of the fractal dimension, intensity, density and the intersection of the fractures are concentrated in the NW and SE parts of SPOT image maps. In the other hand, phyllic alteration zone containing sericite, alunite, kaolinite and jarosite mineral assemblages was also identified in several zones of the NW and SE parts of the ASTER image maps. Integration of the results indicates the high potential zones for the occurrence of Cu–Fe–Au mineralisation in the Bajestan region.
Ahmed, AA, Pradhan, B, Sameen, MI & Makky, AM 2018, 'An optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data', Arabian Journal of Geosciences, vol. 11, no. 11.
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© 2018, Saudi Society for Geosciences. This study proposed a workflow for an optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data. The method is validated on a set of data captured over a part of Selangor located in the Peninsular Malaysia. The method comprised four components including image segmentation, Taguchi optimization, attribute selection using random forest, and rule-based feature extraction. Results indicated the robustness of the proposed approach as the area under curve of forest; grassland, old oil palm, rubber, urban tree, and young oil palm were calculated as 0.90, 0.89, 0.87, 0.87, 0.80, and 0.77, respectively. In addition, results showed that SAR data is very useful for extracting rubber and young oil palm trees (given by random forest importance values). Finally, further research is suggested to improve segmentation results and extract more features from the scene.
Ahmed, JB & Pradhan, B 2018, 'Termite mounds as bio-indicators of groundwater: Prospects and constraints', Pertanika Journal of Science and Technology, vol. 26, no. 2, pp. 479-498.
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Reliance on modern sophisticated equipment for making ‘discoveries’ has limited the human power of observing subtle clues in the environment that are capable of saving cost and labour that come with researching new resources and methods to improve life for all. Due to the growing scarcity of potable water, especially in African and Asian countries, newer, cheaper and reliable methods of investigating groundwater resources are becoming critical. One such potentially promising method is mapping the distribution of termite mounds in the environment. Termite mounds are conspicuous landscape features in tropical and sub-tropical regions of the world. Built from surrounding soils by several species of termite, the properties of mound soil are relatively different from the surrounding soil in most cases, indicating improved hydraulic properties. In this paper, the aim is to review the possibility of employing termite mounds as prospecting tools for groundwater search from three spatial scales of observation. From assessing the smallest to the highest scale of observation, it can be concluded that termite mounds’ prospect as surface indicators of groundwater is apparent. Review findings indicate increased surface water infiltration, presence of riparian tree vegetation and other trees with tap-root system around termite mounds, linear assemblage of termite mounds along aquiferous dykes and seep-lines as well as the dependence of termites on water but avoidance of places with risk of inundation. Whether they indicate permanent groundwater reserves in all cases or whether all species depend largely on water for their metabolism is a subject for further research.
Ait Lamqadem, A, Pradhan, B, Saber, H & Rahimi, A 2018, 'Desertification Sensitivity Analysis Using MEDALUS Model and GIS: A Case Study of the Oases of Middle Draa Valley, Morocco', Sensors, vol. 18, no. 7, pp. 2230-2230.
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Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas.
Alazigha, DP, Indraratna, B, Vinod, JS & Heitor, A 2018, 'Mechanisms of stabilization of expansive soil with lignosulfonate admixture', Transportation Geotechnics, vol. 14, pp. 81-92.
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Alizadeh, M, Hashim, M, Alizadeh, E, Shahabi, H, Karami, M, Beiranvand Pour, A, Pradhan, B & Zabihi, H 2018, 'Multi-Criteria Decision Making (MCDM) Model for Seismic Vulnerability Assessment (SVA) of Urban Residential Buildings', ISPRS International Journal of Geo-Information, vol. 7, no. 11, pp. 444-444.
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Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world.
Alizadeh, M, Ngah, I, Hashim, M, Pradhan, B & Pour, A 2018, 'A Hybrid Analytic Network Process and Artificial Neural Network (ANP-ANN) Model for Urban Earthquake Vulnerability Assessment', Remote Sensing, vol. 10, no. 6, pp. 975-975.
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© 2018 by the authors. Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to aMultilayer Perceptron (MLP) neural network for producing an Earthquake VulnerabilityMap (EVM). Finally, an EVMwas produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are usefu...
Anaissi, A, Khoa, NLD & Wang, Y 2018, 'Automated parameter tuning in one-class support vector machine: an application for damage detection', International Journal of Data Science and Analytics, vol. 6, no. 4, pp. 311-325.
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Arabameri, A, Pradhan, B, Pourghasemi, HR & Rezaei, K 2018, 'Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 1129-1155.
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Arabameri, A, Pradhan, B, Pourghasemi, HR, Rezaei, K & Kerle, N 2018, 'Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms', Applied Sciences, vol. 8, no. 8, pp. 1369-1369.
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Gully erosion triggers land degradation and restricts the use of land. This study assesses the spatial relationship between gully erosion (GE) and geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, and then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT), and multivariate adaptive regression spline (MARS)—for gully erosion susceptibility mapping (GESM) in the Shahroud watershed, Iran. Gully locations were identified by extensive field surveys, and a total of 172 GE locations were mapped. Twelve gully-related GEVs: Elevation, slope degree, slope aspect, plan curvature, convergence index, topographic wetness index (TWI), lithology, land use/land cover (LU/LC), distance from rivers, distance from roads, drainage density, and NDVI were selected to model GE. The results of variables importance by RF and BRT models indicated that distance from road, elevation, and lithology had the highest effect on GE occurrence. The area under the curve (AUC) and seed cell area index (SCAI) methods were used to validate the three GE maps. The results showed that AUC for the three models varies from 0.911 to 0.927, whereas the RF model had a prediction accuracy of 0.927 as per SCAI values, when compared to the other models. The findings will be of help for planning and developing the studied region.
Arabameri, A, Pradhan, B, Rezaei, K, Yamani, M, Pourghasemi, HR & Lombardo, L 2018, 'Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm', Land Degradation & Development, vol. 29, no. 11, pp. 4035-4049.
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AbstractThis study aims to assess gully erosion susceptibility and delineate gully erosion‐prone areas in Toroud Watershed, Semnan Province, Iran. Two different methods, namely, logistic regression (LR) and evidential belief function (EBF), were evaluated, and a new ensemble method was proposed using the combination of both methods. We initially created a gully erosion inventory map using different resources, including early reports, Google Earth images, and Global Positioning System‐aided field surveys. We subsequently split this information randomly and selected 70% (90) of the gullies for calibration and 30% (38) for validation. The method was constructed using a combination of morphometric and thematic predictors that include 16 conditioning parameters. We also assessed the following: (a) potential multicollinearity issues using tolerance and variance inflation factor indices and (b) covariate effects using LR coefficients and EBF class weights. Results show that land use/land cover, lithology, and distance to roads dominate the method with the greatest effect on gully occurrences. We produced three susceptibility maps and evaluated their predictive power through area under the curve (AUC) and seed cell area index analyses. AUC results revealed that the ensemble method presented a considerably higher performance (AUC = 0.909) than did the individual LR (0.802) and EBF (0.821) methods. Similarly, seed cell area index displayed a constant decrease from the ensemble to single methods. The resulted gully erosion‐susceptibility map could be used by decision makers and local managers for soil conservation, and for minimising damages in development activities including construction of infrastructures such as roads and the route of gas and electricity transmission lines.
Askari, G, Pour, A, Pradhan, B, Sarfi, M & Nazemnejad, F 2018, 'Band Ratios Matrix Transformation (BRMT): A Sedimentary Lithology Mapping Approach Using ASTER Satellite Sensor', Sensors, vol. 18, no. 10, pp. 3213-3213.
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Remote sensing imagery has become an operative and applicable tool for the preparation of geological maps by reducing the costs and increasing the precision. In this study, ASTER satellite remote sensing data were used to extract lithological information of Deh-Molla sedimentary succession, which is located in the southwest of Shahrood city, Semnan Province, North Iran. A robust and effective approach named Band Ratio Matrix Transformation (BRMT) was developed to characterize and discriminate the boundary of sedimentary rock formations in Deh-Molla region. The analysis was based on the forward and continuous division of the visible-near infrared (VNIR) and the shortwave infrared (SWIR) spectral bands of ASTER with subsequent application of principal component analysis (PCA) for producing new transform datasets. The approach was implemented to ASTER spectral band ratios for mapping dominated mineral assemblages in the study area. Quartz, carbonate, and Al, Fe, Mg –OH bearing-altered minerals such as kaolinite, alunite, chlorite and mica were appropriately mapped using the BRMT approach. The results match well with geology map of the study area, fieldwork data and laboratory analysis. Accuracy assessment of the mapping result represents a reasonable kappa coefficient (0.70%) and appropriate overall accuracy (74.64%), which verified the robustness of the BRMT approach. This approach has great potential and capability for mapping sedimentary succession with diverse local–geological–physical characteristics around the world.
Azeez, O, Pradhan, B & Shafri, H 2018, 'Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS', Sustainability, vol. 10, no. 10, pp. 3434-3434.
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Transportation infrastructures play a significant role in the economy as they provide accessibility services to people. Infrastructures such as highways, road networks, and toll plazas are rapidly growing based on changes in transportation modes, which consequently create congestions near toll plaza areas and intersections. These congestions exert negative impacts on human health and the environment because vehicular emissions are considered as the main source of air pollution in urban areas and can cause respiratory and cardiovascular diseases and cancer. In this study, we developed a hybrid model based on the integration of three models, correlation-based feature selection (CFS), support vector regression (SVR), and GIS, to predict vehicular emissions at specific times and locations on roads at microscale levels in an urban areas of Kuala Lumpur, Malaysia. The proposed model comprises three simulation steps: first, the selection of the best predictors based on CFS; second, the prediction of vehicular carbon monoxide (CO) emissions using SVR; and third, the spatial simulation based on maps by using GIS. The proposed model was developed with seven road traffic CO predictors selected via CFS (sum of vehicles, sum of heavy vehicles, heavy vehicle ratio, sum of motorbikes, temperature, wind speed, and elevation). Spatial prediction was conducted based on GIS modelling. The vehicular CO emissions were measured continuously at 15 min intervals (recording 15 min averages) during weekends and weekdays twice per day (daytime, evening-time). The model’s results achieved a validation accuracy of 80.6%, correlation coefficient of 0.9734, mean absolute error of 1.3172 ppm and root mean square error of 2.156 ppm. In addition, the most appropriate parameters of the prediction model were selected based on the CFS model. Overall, the proposed model is a promising tool for traffic CO assessment on roads.
Aziz, N, Rasekh, H, Mirzaghorbanali, A, Yang, G, Khaleghparast, S & Nemcik, J 2018, 'An Experimental Study on the Shear Performance of Fully Encapsulated Cable Bolts in Single Shear Test', Rock Mechanics and Rock Engineering, vol. 51, no. 7, pp. 2207-2221.
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A set of single shear tests on fully encapsulated cable bolts was carried out using a newly developed and integrated Megabolt single shear apparatus. The instrument is designed to determine the pure shear strength of cable bolts where there is no contact between the host body faces during the shearing process. Eight different types of cable bolt were encapsulated in 40 MPa concrete cylinders, using Stratabinder HS grout. Prior to encapsulation, cable bolts were pretensioned at the desired value using a manual pretensioner. Effects of surface profile, pretension value and debonding on shear strength of cable bolts were investigated. It was found that the shear strength of spiral/indented cable bolts was lower than that of plain cable bolts. Increasing the pretension load decreased the peak shear load of cable bolts. In general, no debonding was observed for spiral/indented cable bolts during shear testing; however, all tested plain cable bolts were debonded.
Baral, P, Rujikiatkamjorn, C, Indraratna, B & Kelly, R 2018, 'Radial consolidation characteristics of soft undisturbed clay based on large specimens', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1037-1045.
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Basack, S & Nimbalkar, S 2018, 'Measured and Predicted Response of Pile Groups in Soft Clay Subjected to Cyclic Lateral Loading', International Journal of Geomechanics, vol. 18, no. 7, pp. 04018073-04018073.
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© 2018 American Society of Civil Engineers. Major offshore and onshore structures, including transport corridors and high-rise buildings, resting on soft compressible clays are often supported by pile foundations. Apart from the usual vertical loading from the superstructures, these piles are usually subjected to large cyclic loads arising from the actions of waves, ship impacts, or moving vehicles. Under such circumstances, vertical and lateral modes of cyclic loading are predominant and affect overall stability. Such repetitive loading on piles leads to reversal of axial stresses in the adjacent soft clay, initiating progressive degradation in soil strength and stiffness that deteriorates the pile capacity with unacceptable displacements. Although several studies have been carried out to investigate the response of a single pile, a detailed investigation on a pile group in soft soil subjected to cyclic lateral loading, which is of immense practical interest to field engineers, had yet to be conducted. In this paper, extensive laboratory model tests with steel-pipe-pile groups in soft cohesive soil were conducted followed by the development of a numerical model that was based on a two-dimensional (2D) dynamic finite-element (FE) approach. The degradation of both axial and lateral capacities of the pile group and the pattern of the degradation with variations in the cyclic-loading parameters were studied. Comparisons of the experimental data with the computed results validated the numerical analysis. The study indicates that both the axial and lateral pile capacities and displacements were significantly influenced by the cyclic-loading parameters (number of cycles, frequency, and amplitude). Relevant design recommendations are presented.
Basack, S, Indraratna, B & Rujikiatkamjorn, C 2018, 'Effectiveness of stone column reinforcement for stabilizing soft ground with reference to transport infrastructure', Geotechnical Engineering, vol. 49, no. 1, pp. 8-14.
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The use of stone columns for soft soil stabilization has numerous advantages compared to other methods. There are many factors controlling performance of stone columns including column geometry and particle morphology. The reinforced soft ground supporting transport infrastructure like the railways and highways is subjected to cyclic loading, usually initiating a partially drained condition. The study reveals that the stone columns are more effective in mitigating the built up of cyclic excess pore water pressure compared to conventional vertical drains. This paper presents a brief overview on the rigorous theoretical and experimental studies carried out by the Authors to investigate the effectiveness of stone column reinforcement for stabilizing soft ground with particular reference to transport infrastructure.
Basack, S, Indraratna, B, Rujikiatkamjorn, C & Siahaan, F 2018, 'Closure to “Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation” by Sudip Basack, Buddhima Indraratna, Cholachat Rujikiatkamjorn, and Firman Siahaan', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 5, pp. 07018008-07018008.
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Basack, S, Siahaan, F, Indraratna, B & Rujikiatkamjorn, C 2018, 'Stone Column–Stabilized Soft-Soil Performance Influenced by Clogging and Lateral Deformation: Laboratory and Numerical Evaluation', International Journal of Geomechanics, vol. 18, no. 6, pp. 04018058-04018058.
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Beiranvand Pour, A, Park, T-Y, Park, Y, Hong, J, Zoheir, B, Pradhan, B, Ayoobi, I & Hashim, M 2018, 'Application of Multi-Sensor Satellite Data for Exploration of Zn–Pb Sulfide Mineralization in the Franklinian Basin, North Greenland', Remote Sensing, vol. 10, no. 8, pp. 1186-1186.
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Geological mapping and mineral exploration programs in the High Arctic have been naturally hindered by its remoteness and hostile climate conditions. The Franklinian Basin in North Greenland has a unique potential for exploration of world-class zinc deposits. In this research, multi-sensor remote sensing satellite data (e.g., Landsat-8, Phased Array L-band Synthetic Aperture Radar (PALSAR) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) were used for exploring zinc in the trough sequences and shelf-platform carbonate of the Franklinian Basin. A series of robust image processing algorithms was implemented for detecting spatial distribution of pixels/sub-pixels related to key alteration mineral assemblages and structural features that may represent potential undiscovered Zn–Pb deposits. Fusion of Directed Principal Component Analysis (DPCA) and Independent Component Analysis (ICA) was applied to some selected Landsat-8 mineral indices for mapping gossan, clay-rich zones and dolomitization. Major lineaments, intersections, curvilinear structures and sedimentary formations were traced by the application of Feature-oriented Principal Components Selection (FPCS) to cross-polarized backscatter PALSAR ratio images. Mixture Tuned Matched Filtering (MTMF) algorithm was applied to ASTER VNIR/SWIR bands for sub-pixel detection and classification of hematite, goethite, jarosite, alunite, gypsum, chalcedony, kaolinite, muscovite, chlorite, epidote, calcite and dolomite in the prospective targets. Using the remote sensing data and approaches, several high potential zones characterized by distinct alteration mineral assemblages and structural fabrics were identified that could represent undiscovered Zn–Pb sulfide deposits in the study area. This research establishes a straightforward/cost-effective multi-sensor satellite-based remote sensing approach for reconnaissance stages of mineral exploration in hardly accessible parts of the H...
Cai, Q, Turner, BD, Sheng, D & Sloan, S 2018, 'Application of kinetic models to the design of a calcite permeable reactive barrier (PRB) for fluoride remediation', Water Research, vol. 130, pp. 300-311.
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Chen, W, Peng, J, Hong, H, Shahabi, H, Pradhan, B, Liu, J, Zhu, A-X, Pei, X & Duan, Z 2018, 'Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China', Science of The Total Environment, vol. 626, pp. 1121-1135.
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© 2018 Elsevier B.V. The preparation of a landslide susceptibility map is considered to be the first step for landslide hazard mitigation and risk assessment. However, these maps are accepted as end products that can be used for land use planning. The main goal of this study is to assess and compare four advanced machine learning techniques, namely the Bayes’ net (BN), radical basis function (RBF) classifier, logistic model tree (LMT), and random forest (RF) models, for landslide susceptibility modelling in Chongren County, China. A total of 222 landslide locations were identified in the study area using historical reports, interpretation of aerial photographs, and extensive field surveys. The landslide inventory data was randomly split into two groups with a ratio of 70/30 for training and validation purposes. Fifteen landslide conditioning factors were prepared for landslide susceptibility modelling. The spatial correlation between landslides and conditioning factors was analyzed using the information gain (IG) method. The BN, RBF classifier, LMT, and RF models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) and statistical measures, including sensitivity, specificity, and accuracy, were employed to validate and compare the predictive capabilities of the models. Out of the tested models, the RF model had the highest sensitivity, specificity, and accuracy values of 0.787, 0.716, and 0.752, respectively, for the training dataset. Overall, the RF model produced an optimized balance for the training and validation datasets in terms of AUC values and statistical measures. The results of this study also demonstrate the benefit of selecting optimal machine learning techniques with proper conditioning selection methods for landslide susceptibility modelling.
Chen, X, Li, Y, Li, J & Gu, X 2018, 'A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices', Smart Materials and Structures, vol. 27, no. 1, pp. 015005-015005.
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© 2017 IOP Publishing Ltd. Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov's direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.
Chenari, RJ, Fatahi, B, Ghorbani, A & Alamoti, MN 2018, 'Evaluation of strength properties of cement stabilized sand mixed with EPS beads and fly ash', Geomechanics and Engineering, vol. 14, no. 6, pp. 533-544.
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The importance of using materials cost effectively to enhance the strength and reduce the cost, and weight of earth fill materials in geotechnical engineering led researchers to seek for modifying the soil properties by adding proper additives. Lightweight fill materials made of soil, binder, water, and Expanded polystyrene (EPS) beads are increasingly being used in geotechnical practices. This paper primarily investigates the behavior of sandy soil, modified by EPS particles. Besides, the mechanical properties of blending sand, EPS and the binder material such as fly ash and cement were examined in different mixing ratios using a number of various laboratory studies including the Modified Standard Proctor (MSP) test, the Unconfined Compressive Strength (UCS) test, the California Bearing Ratio (CBR) test and the Direct Shear test (DST). According to the results, an increase of 0.1% of EPS results in a reduction of the density of the mixture for 10%, as well as making the mixture more ductile rather than brittle. Moreover, the compressive strength, CBR value and shear strength parameters of the mixture decreases by an increase of the EPS beads, a trend on the contrary to the increase of cement and fly ash content.
Chou, K-P, Prasad, M, Wu, D, Sharma, N, Li, D-L, Lin, Y-F, Blumenstein, M, Lin, W-C & Lin, C-T 2018, 'Robust Feature-Based Automated Multi-View Human Action Recognition System', IEEE Access, vol. 6, pp. 15283-15296.
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© 2013 IEEE. Automated human action recognition has the potential to play an important role in public security, for example, in relation to the multiview surveillance videos taken in public places, such as train stations or airports. This paper compares three practical, reliable, and generic systems for multiview video-based human action recognition, namely, the nearest neighbor classifier, Gaussian mixture model classifier, and the nearest mean classifier. To describe the different actions performed in different views, view-invariant features are proposed to address multiview action recognition. These features are obtained by extracting the holistic features from different temporal scales which are modeled as points of interest which represent the global spatial-temporal distribution. Experiments and cross-data testing are conducted on the KTH, WEIZMANN, and MuHAVi datasets. The system does not need to be retrained when scenarios are changed which means the trained database can be applied in a wide variety of environments, such as view angle or background changes. The experiment results show that the proposed approach outperforms the existing methods on the KTH and WEIZMANN datasets.
Das, A, Suwanwiwat, H, Ferrer, MA, Pal, U & Blumenstein, M 2018, 'Thai Automatic signature verification System Employing Textural Features', IET Biometrics, vol. 7, no. 6, pp. 615-627.
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© The Institution of Engineering and Technology 2018. This study focuses on a comprehensive study of Automatic Signature Verification (ASV) for off-line Thai signatures; an investigation was carried out to characterise the challenges in Thai ASV and to baseline the performance of Thai ASV employing baseline features, being Local Binary Pattern, Local Directional Pattern, Local Binary and Directional Patterns combined (LBDP), and the baseline shape/feature-based hidden Markov model. As there was no publicly available Thai signature database found in the literature, the authors have developed and proposed a database considering real-world signatures from Thailand. The authors have also identified their latent challenges and characterised Thai signature-based ASV. The database consists of 5,400 signatures from 100 signers. Thai signatures could be bi-script in nature, considering the fact that a single signature can contain only Thai or Roman characters or contain both Roman and Thai, which poses an interesting challenge for script-independent SV. Therefore, along with the baseline experiments, the investigation on the influence and nature of bi-script ASV was also conducted. From the equal error rates and Bhattacharyya distance, the score achieved in the experiments indicate that the Thai SV scenario is a script-independent problem. The open research area on this subject of research has also been addressed.
Dong, Y, Fatahi, B, Khabbaz, H & Zhang, H 2018, 'Influence of particle contact models on soil response of poorly graded sand during cavity expansion in discrete element simulation', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1154-1170.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The discrete element method (DEM) has been extensively adopted to investigate many complex geotechnical related problems due to its capability to incorporate the discontinuous nature of granular materials. In particular, when simulating large deformations or distortion of soil (e.g. cavity expansion), DEM can be very effective as other numerical solutions may experience convergence problems. Cavity expansion theory has widespread applications in geotechnical engineering, particularly to the problems concerning in situ testing, pile installation and so forth. In addition, the behaviour of geomaterials in a macro-level is utterly determined by microscopic properties, highlighting the importance of contact models. Despite the fact that there are numerous contact models proposed to mimic the realistic behaviour of granular materials, there are lack of studies on the effects of these contact models on the soil response. Hence, in this study, a series of three-dimensional numerical simulations with different contact constitutive models was conducted to simulate the response of sandy soils during cylindrical cavity expansion. In this numerical investigation, three contact models, i.e. linear contact model, rolling resistance contact model, and Hertz contact model, are considered. It should be noted that the former two models are linear based models, providing linearly elastic and frictional plasticity behaviours, whereas the latter one consists of nonlinear formulation based on an approximation of the theory of Mindlin and Deresiewicz. To examine the effects of these contact models, several cylindrical cavities were created and expanded gradually from an initial radius of 0.055 m to a final radius of 0.1 m. The numerical predictions confirm that the calibrated contact models produced similar results regarding the variations of cavity pressure, radial stress, deviatoric stress, volumetric ...
Fanos, AM & Pradhan, B 2018, 'Laser Scanning Systems and Techniques in Rockfall Source Identification and Risk Assessment: A Critical Review', Earth Systems and Environment, vol. 2, no. 2, pp. 163-182.
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Rockfall poses risk to people, their properties and to transportation ways in mountainous and hilly regions. This catastrophe shows various characteristics such as vast distribution, sudden occurrence, variable magnitude, strong fatalness and randomicity. Therefore, prediction of rockfall phenomenon both spatially and temporally is a challenging task. Digital Terrain model (DTM) is one of the most significant elements in rockfall source identification and risk assessment. Light detection and ranging (LiDAR) is the most advanced effective technique to derive high-resolution and accurate DTM. This paper presents a critical overview of rockfall phenomenon (definition, triggering factors, motion modes and modeling) and LiDAR technique in terms of data pre-processing, DTM generation and the factors that can be obtained from this technique for rockfall source identification and risk assessment. It also reviews the existing methods that are utilized for the evaluation of the rockfall trajectories and their characteristics (frequency, velocity, bouncing height and kinetic energy), probability, susceptibility, hazard and risk. Detail consideration is given on quantitative methodologies in addition to the qualitative ones. Various methods are demonstrated with respect to their application scales (local and regional). Additionally, attention is given to the latest improvement, particularly including the consideration of the intensity of the phenomena and the magnitude of the events at chosen sites.
Fanos, AM, Pradhan, B, Mansor, S, Yusoff, ZM & Abdullah, AFB 2018, 'A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data', Landslides, vol. 15, no. 9, pp. 1833-1850.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.
Fatahi, B, Van Nguyen, Q, Xu, R & Sun, W-J 2018, 'Three-Dimensional Response of Neighboring Buildings Sitting on Pile Foundations to Seismic Pounding', International Journal of Geomechanics, vol. 18, no. 4, pp. 04018007-04018007.
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© 2018 American Society of Civil Engineers. Seismic pounding occurs when the separation gap between buildings and structures is not wide enough, particularly during major earthquake events; this can cause them to collide, causing local damage or, in extreme cases, collapse. This study investigated the impact that this separation gap has on the seismic response of midrise buildings supported on piles while considering seismic soil-pile-structure interaction (SSPSI). To achieve this aim, three 15-story reinforced concrete buildings sitting on pile foundations and with five different separation gaps under excitations from the 1994 Northridge and 1995 Kobe earthquakes were numerically simulated. This study used three-dimensional numerical modeling to simultaneously capture the effects of seismic pounding and SSPSI. Because the considered structure, pile foundation, and soil deposit are three-dimensional in nature, the adopted three-dimensional numerical modeling can provide a more realistic simulation to capture the seismic behavior of the system. The nonlinear behavior of structural elements was included, and the dynamic soil properties were obtained from field data and backbone curves. A contact pair interface with small-sliding surface-to-surface formulation between buildings was used to capture possible seismic pounding, and contact interfaces with a finite-sliding formulation were used to simulate the interaction between the piles and the soil. The results, including lateral building deflections, interstory drifts, structural shear forces, foundation rocking, lateral pile deflections, and the distributions of bending moments and shear forces of the piles, are presented and discussed. The findings of this study will give engineers a better insight into the possible effects of seismic pounding on the seismic performance of buildings, and the response of endbearing piles in soft soils.
Ghasemi, K, Pradhan, B & Jena, R 2018, 'Spatial Identification of Key Alteration Minerals Using ASTER and Landsat 8 Data in a Heavily Vegetated Tropical Area', Journal of the Indian Society of Remote Sensing, vol. 46, no. 7, pp. 1061-1073.
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© 2018, Indian Society of Remote Sensing. The Central Gold Belt (CGB) of Malaysia is a major host to gold deposits. Penjom, Raub, Selising and Buffalo reef are major gold mines in CGB. The study area, Selinsing gold mine, is located at the northwest of Pahang province on the lineament known as the Raub Bentong Suture. Presence of dense vegetation and cloud cover in tropical regions are main obstacles in alteration mapping using satellite imageries. In this study, Landsat 8 and ASTER level 1B images were used to map clay minerals and quartz rich zones at Selinsing gold mine and surrounding areas. Direct principal component analysis (DPCA), matched filtering (MF) and band ratio were the effective methods used in this study. High concentration of clay minerals was detected using band ratio 6/7, DPC2 and MF and ratio 14/12 was carried out to highlight quartz rich zones. The results of image processing methods were verified by in situ inspection and X-ray diffraction analyses. The results show that, in spite of limited bedrock exposure, the known gold prospects and potential areas of mineralization can be recognized by the methods employed in this study.
Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 2018, 'A review of neural networks in plant disease detection using hyperspectral data', Information Processing in Agriculture, vol. 5, no. 3, pp. 354-371.
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© 2018 China Agricultural University This paper reviews advanced Neural Network (NN) techniques available to process hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a review on NN mechanism, types, models, and classifiers that use different algorithms to process hyperspectral data. Then we highlight the current state of imaging and non-imaging hyperspectral data for early disease detection. The hybridization of NN-hyperspectral approach has emerged as a powerful tool for disease detection and diagnosis. Spectral Disease Index (SDI) is the ratio of different spectral bands of pure disease spectra. Subsequently, we introduce NN techniques for rapid development of SDI. We also highlight current challenges and future trends of hyperspectral data.
Golkarian, A, Naghibi, SA, Kalantar, B & Pradhan, B 2018, 'Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS', Environmental Monitoring and Assessment, vol. 190, no. 3.
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© 2018, Springer International Publishing AG, part of Springer Nature. Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.
Gong, B, Wang, S, Sloan, SW, Sheng, D & Tang, C 2018, 'Modelling Coastal Cliff Recession Based on the GIM–DDD Method', Rock Mechanics and Rock Engineering, vol. 51, no. 4, pp. 1077-1095.
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He, X, Liang, D & Bolton, MD 2018, 'Run-out of cut-slope landslides: mesh-free simulations', Géotechnique, vol. 68, no. 1, pp. 50-63.
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This study uses an incompressible smoothed-particle hydrodynamics (ISPH) model to investigate the run-out and deposit morphology of granular materials flowing down cut slopes. The primary aim is to study the influence of various factors on the run-out and to summarise a quantitative relationship for direct use in landslide hazard management. In the model, the granular materials are modelled as a rigid perfectly plastic material with a Coulomb yield surface. The coupled continuity equation and momentum equation are solved by a semi-implicit algorithm. The model is first validated and its results are carefully compared with various controlled experiments regarding granular flows. The model reproduces the flows and correctly predicts the deposition profiles under various conditions. Then, the computational results are used to study the run-out and mobility of landslides. For granular columns collapsing onto a flat surface, a normalised run-out and a new scaling relationship are proposed, which are supported by numerous measured and numerical results. A similar relationship for the run-out of granular rectangles on steep slopes has also been explored. It is found that the normalised run-out is mainly determined by the slope angle and the normalised drop height. Furthermore, three types of idealised cut-slope landslides are simulated to study the influence of the initial landslide shape on the run-out. It is found that the normalised run-out of these idealised cut-slope landslides is smaller than that of granular rectangles on slopes of the same angles and drop heights. The difference between the run-outs is found to be mainly determined by the proportion of the whole mass that initially lies above a predictable discontinuity plane.
He, X, Liang, D, Wu, W, Cai, G, Zhao, C & Wang, S 2018, 'Study of the interaction between dry granular flows and rigid barriers with an SPH model', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 11, pp. 1217-1234.
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SummaryThis study uses an incompressible smoothed‐particle hydrodynamics model to investigate the interaction between dry granular material flows and rigid barriers. The primary aim is to summarise some practical guidelines for the design of debris‐resisting barriers. The granular materials are modelled as a rigid‐perfectly plastic material where the plastic flow corresponds to the critical state. The coupled continuity equation and momentum equation are solved by a semi‐implicit algorithm. Compared with flows in controlled flume experiments, the model adequately reproduces both the kinetic of the flows and the impact force under various conditions. Then the numerical simulations are used to study the detailed interaction process. It is illustrated quantitatively that the interaction force consists of two parts, ie, the earth pressure force caused by the weight of the soil and a dynamic force caused by the internal deformation (flowing mass on top of a dead zone). For the estimation of impact load, this study suggests that an increased earth pressure coefficient depending on the Froude number should be incorporated into the hydrostatic model.
He, Z, Zhang, S, Teng, J, Yao, Y & Sheng, D 2018, 'A coupled model for liquid water-vapor-heat migration in freezing soils', Cold Regions Science and Technology, vol. 148, pp. 22-28.
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Ho, L & Fatahi, B 2018, 'Analytical solution to axisymmetric consolidation of unsaturated soil stratum under equal strain condition incorporating smear effects', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 15, pp. 1890-1913.
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SummaryThis paper proposes closed‐form analytical solutions to the axisymmetric consolidation of an unsaturated soil stratum using the equal strain hypothesis. Following the 1‐dimensional (1D) consolidation theory for unsaturated soil mechanics, polar governing equations describing the air and water flows are first presented on the basis of Fick's law and Darcy's law, respectively. The current study takes into account the peripheral smear caused by an installation of vertical drain. Separation of variables and Laplace transformation are mainly adopted in the analytical derivation to obtain final solutions. Then, the hydraulic conductivity ratio, the radius of influence zone and smear parameters influencing time‐dependent excess pore pressures, and the average degree of consolidation are graphically interpreted. In this study, a comparison made between the proposed equal strain results and the existing free strain results suggests that both hypotheses would deliver similar predictions. Moreover, it is found that the smear zone resulting from vertical drain installations would hinder the consolidation rate considerably.
Ho, L, Fatahi, B & Khabbaz, H 2018, 'Analytical Solution to One-Dimensional Consolidation in Unsaturated Soil Deposit Incorporating Time-Dependent Diurnal Temperature Variation', International Journal of Geomechanics, vol. 18, no. 5, pp. 04018029-04018029.
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© 2018 American Society of Civil Engineers. Several experimental studies have demonstrated that temperature changes may significantly influence the deformation of unsaturated soils. Thus, there is an essential need to develop a predictive framework for unsaturated consolidation capturing the nonisothermal effect. This paper presents an analytical solution to the one-dimensional (1D) consolidation of unsaturated soil deposit in response to temperature variation. A set of governing equations of flow incorporating the nonisothermal condition were first obtained. Then, Fourier sine series and the Laplace transformation were used to derive solutions based on these governing equations. This study highlighted the effect of diurnal temperature variation on pore pressures and soil deformation at different depths while considering two conditions of interest: (1) no external applied load, and (2) application of step loading to the ground surface. In addition, the thermal diffusivity characterizing the consolidation behavior of unsaturated soils was also investigated and is discussed in this paper. It is predicted that a decrease in thermal diffusivity would attenuate the effects of diurnal temperature on the unsaturated consolidation.
Hong, H, Liu, J, Bui, DT, Pradhan, B, Acharya, TD, Pham, BT, Zhu, A-X, Chen, W & Ahmad, BB 2018, 'Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)', CATENA, vol. 163, pp. 399-413.
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© 2018 Elsevier B.V. Landslides are a manifestation of slope instability causing different kinds of damage affecting life and property. Therefore, high-performance-based landslide prediction models are useful to government institutions for developing strategies for landslide hazard prevention and mitigation. Development of data mining based algorithms shows that high-performance models can be obtained using ensemble frameworks. The primary objective of this study is to investigate and compare the use of current state-of-the-art ensemble techniques, such as AdaBoost, Bagging, and Rotation Forest, for landslide susceptibility assessment with the base classifier of J48 Decision Tree (JDT). The Guangchang district (Jiangxi province, China) was selected as the case study. Firstly, a landslide inventory map with 237 landslide locations was constructed; the landslide locations were then randomly divided into a ratio of 70/30 for the training and validating models. Secondly, fifteen landslide conditioning factors were prepared, such as slope, aspect, altitude, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), plan curvature, profile curvature, lithology, distance to faults, distance to rivers, distance to roads, land use, normalized difference vegetation index (NDVI), and rainfall. Relief-F with the 10-fold cross-validation method was applied to quantify the predictive ability of the conditioning factors and for feature selection. Using the JDT and its three ensemble techniques, a total of four landslide susceptibility models were constructed. Finally, the overall performance of the resulting models was assessed and compared using area under the receiver operating characteristic (ROC) curve (AUC) and statistical indexes. The result showed that all landslide models have high performance (AUC > 0.8). However, the JDT with the Rotation Forest model presents the highest prediction capability (AUC = 0.855), followed by the JD...
Hong, H, Pradhan, B, Sameen, MI, Kalantar, B, Zhu, A & Chen, W 2018, 'Improving the accuracy of landslide susceptibility model using a novel region-partitioning approach', Landslides, vol. 15, no. 4, pp. 753-772.
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© 2017, Springer-Verlag GmbH Germany. Landslide is a natural disaster that threatens human lives and properties worldwide. Numerous have been conducted on landslide susceptibility mapping (LSM), in which each has attempted to improve the accuracy of final outputs. This study presents a novel region-partitioning approach for LSM to understand the effects of partitioning a focused region into smaller areas on the prediction accuracy of common regression models. Results showed that the partitioning of the study area into two regions using the proposed method improved the prediction rate from 0.77 to 0.85 when support vector machine was used, and from 0.87 to 0.88 when logistic regression model was utilized. The spatial agreements of the models were also improved after partitioning the area into two regions based on Shannon entropy equations. Our comparative study indicated that the proposed method outperformed the geographically weighted regression model that considered the spatial variations in landslide samples. Overall, the main advantages of the proposed method are improved accuracy and the reduction of the effects of spatial variations exhibited in landslide-conditioning factors.
Hussaini, SKK, Indraratna, B & Vinod, JS 2018, 'A critical review of the performance of geosynthetic-reinforced railroad ballast', Geotechnical Engineering, vol. 49, no. 4, pp. 31-41.
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In the recent times, railway organizations across the world have resorted to the use of geosynthetics as a low-cost solution to stabilize ballast. In this view, extensive studies have been conducted worldwide to assess the performance of geosynthetic-reinforced ballast under various loading conditions. This paper evaluates the various benefits the rail industry could attain because of the geosynthetic reinforcement. A review of literature reveals that geogrid arrests the lateral spreading of ballast, reduces the extent of permanent vertical settlement and minimizes the particle breakage. The geogrid was also found to reduce the extent of volumetric compressions in ballast. The overall performance improvement due to geogrid was observed to be a function of the interface efficiency factor (φ). Moreover, studies also established the additional role of geogrids in reducing the differential track settlements and diminishing the stresses at the subgrade level. The geosynthetics were found to be more beneficial in case of tracks resting on soft subgrades. Furthermore, the benefits of geosynthetics in stabilizing ballast were found to be significantly higher when placed within the ballast. The optimum placement location of geosynthetics has been reported by several researchers to be about 200-250 mm below the sleeper soffit for a conventional ballast depth of 300-350 mm. A number of field investigations and track rehabilitation schemes also confirmed the role of geosynthetics/geogrids in stabilizing the tracks thereby helping in removing the stringent speed restrictions that were imposed earlier, and enhancing the time interval between maintenance operations.
Idrees, MO & Pradhan, B 2018, 'Geostructural stability assessment of cave using rock surface discontinuity extracted from terrestrial laser scanning point cloud', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 3, pp. 534-544.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The use of terrestrial laser scanning (TLS) in the caves has been growing drastically over the last decade. However, TLS application to cave stability assessment has not received much attention of researchers. This study attempted to utilize rock surface orientations obtained from TLS point cloud collected along cave passages to (1) investigate the influence of rock geostructure on cave passage development, and (2) assess cave stability by determining areas susceptible to different failure types. The TLS point cloud was divided into six parts (Entry hall, Chamber, Main hall, Shaft 1, Shaft 2 and Shaft 3), each representing different segments of the cave passages. Furthermore, the surface orientation information was extracted and grouped into surface discontinuity joint sets. The computed global mean and best–fit planes of the entire cave show that the outcrop dips 290° with a major north-south strike. But at individual level, the passages with dip angle between 26° and 80° are featured with dip direction of 75°–322°. Kinematic tests reveal the potential for various failure modes of rock slope. Our findings show that toppling is the dominant failure type accounting for high-risk rockfall in the cave, with probabilities of 75.26%, 43.07% and 24.82% in the Entry hall, Main hall and Shaft 2, respectively. Unlike Shaft 2 characterized by high risk of the three failure types (32.49%, 24.82% and 50%), the chamber and Shaft 3 passages are not suffering from slope failure. The results also show that the characteristics of rock geostructure considerably influence the development of the cave passages, and four sections of the cave are susceptible to different slope failure types, at varying degrees of risk.
Inan, DI, Beydoun, G & Pradhan, B 2018, 'Developing a decision support system for Disaster Management: Case study of an Indonesia volcano eruption', International Journal of Disaster Risk Reduction, vol. 31, pp. 711-721.
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© 2018 Elsevier Ltd Disaster Management activities often focus on specific tasks (e.g. evacuation, logistic or coordination) and are confined to one specific DM phase (e.g. Preparedness or Response). New awareness about an external change, be it environmental or organisational, typically act as a trigger for such focussed activities. A variety of views or stakeholders are also involved in those activities, and their various concerns get often intertwined. This work advocates the use of a Decision Support System (DSS) that can be deployed as a single access point. Such a system requires a sufficient amount of representative knowledge, and facilities to avail the knowledge to the appropriate stakeholders in an appropriate form. With the multitude of stakeholders and their varying knowledge requirements, the system will need to present the knowledge differently according to the stakeholders needs in their decision making process. Such processes can vary, e.g. whether for policy making or for operational real time responses. This paper presents a hybrid of knowledge elicitation and retrieval mechanisms, some are top down and others are bottom up. The mechanisms make use of the Meta Object Facility (MOF) to structure and present the knowledge appropriately according to different interests and roles. A case study of the recent Mt. Agung volcano eruption in Bali Indonesia is successfully used to demonstrate the efficacy of the mechanisms proposed and the resultant DSS.
Indraratna, B, Baral, P, Rujikiatkamjorn, C & Perera, D 2018, 'Class A and C predictions for Ballina trial embankment with vertical drains using standard test data from industry and large diameter test specimens', Computers and Geotechnics, vol. 93, pp. 232-246.
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Indraratna, B, Ferreira, FB, Qi, Y & Ngo, TN 2018, 'Application of geoinclusions for sustainable rail infrastructure under increased axle loads and higher speeds', Innovative Infrastructure Solutions, vol. 3, no. 1, p. 69.
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Given the ongoing demand for faster trains for carrying heavier loads, conventional ballasted railroads require considerable upgrading in order to cope with the increasing traffic-induced stresses. During train operations, ballast deteriorates due to progressive breakage and fouling caused by the infiltration of fine particles from the surface or mud-pumping from the underneath layers (e.g. sub-ballast, sub-grade), which decreases the load bearing capacity, impedes drainage and increases the deformation of ballasted tracks. Suitable ground improvement techniques involving geosynthetics and resilient rubber sheets are commonly employed to enhance the stability and longevity of rail tracks. This keynote paper focuses mainly on research projects undertaken at the University of Wollongong to improve track performance by emphasising the main research outcomes and their practical implications. Results from laboratory tests, computational modelling and field trials have shown that track behaviour can be significantly improved by the use of geosynthetics, energy-absorbing rubber mats, rubber crumbs and infilled-recycled tyres. Full-scale monitoring of instrumented track sections supported by rail industry (ARTC) has been performed, and the obtained field data for in situ stresses and deformations could verify the track performance, apart from validating the numerical simulations. The research outcomes provide promising approaches that can be incorporated into current track design practices to cater for high-speed freight trains carrying heavier loads.
Indraratna, B, Israr, J & Li, M 2018, 'Inception of geohydraulic failures in granular soils – an experimental and theoretical treatment', Géotechnique, vol. 68, no. 3, pp. 233-248.
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This paper outlines an experimental investigation into seepage-induced failures in soils subjected to static and cyclic loading. Internally stable, marginal and unstable soils are characterised by heave, composite heave–piping and suffusion that develops immediately upon instability. In this study, the stable specimens exhibited heave at larger hydraulic gradients than the unstable specimens failing by suffusion at relatively smaller hydraulic gradients. Under no external load (i.e. self-weight only), the relative density (Rd) and particle size distribution (PSD) in tandem controlled the internal stability of soils, although the effective stress magnitude (σ′vt) also had a role to play under both static and cyclic loading conditions. Instability in soils was governed by specific combinations of their geo-hydro-mechanical characteristics such as PSD, Rd, stress reduction factor, critical hydraulic gradients and associated effective stress levels. These factors are combined to model the development and inception of instability, and the paper offers visual guides as a practical tool for practitioners. Each soil has a unique critical envelope related to its PSD and Rd, and a critical path with its inclination that depends on the hydro-mechanical conditions. The current results of internal erosion tests conducted by the authors plus those adopted from published literature are used to verify the proposed model.
Indraratna, B, Qi, Y & Heitor, A 2018, 'Evaluating the Properties of Mixtures of Steel Furnace Slag, Coal Wash, and Rubber Crumbs Used as Subballast', Journal of Materials in Civil Engineering, vol. 30, no. 1, pp. 04017251-04017251.
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Indraratna, B, Sun, Q, Heitor, A & Grant, J 2018, 'Performance of Rubber Tire-Confined Capping Layer under Cyclic Loading for Railroad Conditions', Journal of Materials in Civil Engineering, vol. 30, no. 3, pp. 06017021-06017021.
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Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR & Jamalipour, A 2018, 'Analysis of Effective Capacity and Throughput of Polling-Based Device-To-Device Networks.', IEEE Trans. Veh. Technol., vol. 67, no. 9, pp. 8656-8666.
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© 1967-2012 IEEE. Next-generation wireless networks will give rise to heterogeneous networks by integrating multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. Device-to-device (D2D) communication has proven to be a promising technology that can increase the capacity and coverage of wireless networks. The D2D communication was first introduced in long-term evolution advanced (LTE-A) and has gained immense popularity for the offloading traffic using the licensed and unlicensed band. Challenges arise from resource allocation, provision of quality-of-service (QoS), and the quantification of capacity in an unlicensed band due to the distributed nature of Wi-Fi. In this paper, we propose an analytical performance model for the scalable MAC protocol (SC-MP) in which a resource allocation mechanism is based on the IEEE 802.11 point coordinated function to access the Wi-Fi channel for voice and video/multimedia traffic. In the SC-MP, D2D communication is applied to further offload the video/multimedia traffic. In particular, this paper establishes a three-state semi-Markovian model to derive a closed-form expression of effective capacity in terms of transmission rate and quality-of-service. Further, the SC-MP is analytically modeled using the four-state traditional Markov model to derive the saturation throughput. The analytical results are validated through simulations, hence, proving the appropriateness of the model.
Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR, Dutkiewicz, E, Krunz, M & Jamalipour, A 2018, 'PCF-Based LTE Wi-Fi Aggregation for Coordinating and Offloading the Cellular Traffic to D2D Network.', IEEE Trans. Veh. Technol., vol. 67, no. 12, pp. 12193-12203.
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© 2018 IEEE. Device-to-device (D2D) communication is a promising technology towards 5G networks. D2D communication can offload traffic using licensed/unlicensed band by establishing a direct communication between two users without traversing the base station or core network. However, one of the major challenges of D2D communication is resource allocation and guaranteeing quality-of-service (QoS). In this paper, we establish an optimal queuing scheduling and resource allocation problem for three-tier heterogeneous network based on LTE Wi-Fi aggregation, to offload voice/multimedia traffic from licensed band to unlicensed band using scalable MAC protocol (SC-MP) under various static delay constraints. The access mechanism used for Wi-Fi in SC-MP is point coordination function, which further offloads the multimedia traffic using D2D communication in unlicensed band. Resource allocation and optimal joint queuing scheduling problems are formulated with diverse QoS guarantee between licensed and unlicensed band to minimize the bandwidth of licensed band. Furthermore, an iterative algorithm is proposed to express the nonconvex problem as a series of subproblems based on block coordinate descent and difference of two convex functions (D.C) program. We have simulated the proposed scheme using two scenarios: Voice traffic using licensed band and voice traffic using both licensed and unlicensed band, whereas multimedia traffic uses unlicensed band for both the scenarios. The simulation results show that both the schemes perform better than the existing scheme and scenario 2 outperforms scenario 1.
Israr, J & Indraratna, B 2018, 'Assessment of internal stability of filters under static and cyclic loading: An experimental and theoretical treatment', Australian Geomechanics Journal, vol. 53, no. 4, pp. 103-116.
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The occurrence of internal instability may significantly affect geo-mechanical characteristics of granular filters such as permeability and particle size distribution, consequently rendering them ineffective in retaining the protected base soils and thereby endangering the structural stability. This paper presents the results of 65 hydraulic tests performed on ten different granular soils compacted at varying relative densities between 0 and 100% and subjected to an upward hydraulic flow under both static and cyclic conditions. It was observed that the internal stability is a function of particle gradation and relative density in tandem, i.e. constriction size distribution, under static conditions. However, the agitation and pore pressure development under cyclic loading triggered excessively premature internal erosion in filters. Based on the analysis, new constriction-based criteria proposed for both static and cyclic conditions that showed remarkable accuracy in correctly assessing the potential of instability of filters compared to many existing criteria. Moreover, a new hydromechanical model is presented that could accurately capture the correct potential of instability of filters, thereby contributing toward increased confidence level for practical design of filters. Two practical design examples presented to demonstrate the implications of this research study in practice to conclude this paper.
Israr, J & Indraratna, B 2018, 'Closure to “Internal Stability of Granular Filters under Static and Cyclic Loading” by Jahanzaib Israr and Buddhima Indraratna', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 12, pp. 07018033-07018033.
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Israr, J & Indraratna, B 2018, 'Mechanical response and pore pressure generation in granular filters subjected to uniaxial cyclic loading', Canadian Geotechnical Journal, vol. 55, no. 12, pp. 1756-1768.
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This paper presents results from a series of piping tests carried out on a selected range of granular filters under static and cyclic loading conditions. The mechanical response of filters subjected to cyclic loading could be characterized in three distinct phases; namely, (I) pre-shakedown, (II) post-shakedown, and (III) post-critical (i.e., the occurrence of internal erosion). All the permanent geomechanical changes such, as erosion, permeability variations, and axial strain developments, took place during phases I and III, while the specimen response remained purely elastic during phase II. The post-critical occurrence of erosion incurred significant settlement that may not be tolerable for high-speed railway substructures. The analysis revealed that a cyclic load would induce excess pore-water pressure, which, in corroboration with steady seepage forces and agitation due to dynamic loading, could then cause internal erosion of fines from the specimens. The resulting excess pore pressure is a direct function of the axial strain due to cyclic densification, as well as the loading frequency and reduction in permeability. A model based on strain energy is proposed to quantify the excess pore-water pressure, and subsequently validated using current and existing test results from published studies.
Jayamali, KVSD, Nawagamuwa, UP & Indraratna, B 2018, 'Estimation of four-day soaked CBR using index properties', Australian Geomechanics Journal, vol. 53, no. 4, pp. 149-158.
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California Bearing Ratio (CBR) is an important parameter used to evaluate the strength of subgrade and sub-base soils for design of flexible pavements and hence it plays a significant role in road and highway constructions. Obtaining CBR is heavily time consuming and it is difficult to acquire a representative CBR value. Therefore, many correlations have been developed by various researchers worldwide to predict the CBR. Due to differences in soil formations in the tropical environment, these existing global correlations found to be not satisfactory with local soils in Sri Lanka. Hence, this study was carried out to develop empirical correlations between CBR and index properties those best suit for local soils, using the data obtained from Atterberg limits and sieve analysis tests together with compaction tests. The new correlations were established using the method of regression analysis in the form of empirical equations representing the role of index properties. Robust regression by the method of least absolute residuals using MATLAB was considered in the analysis to reduce the impact of outliers along with traditional multiple regression using Microsoft Excel. As a final verification, several laboratory tests were conducted to compare the results with proposed regression equations.
Jordaan, J, Punzet, S, Melnikov, A, Sanches, A, Oberst, S, Marburg, S & Powell, DA 2018, 'Measuring monopole and dipole polarizability of acoustic meta-atoms', Applied Physics Letters, vol. 113, no. 22, pp. 224102-224102.
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We present a method to extract monopole and dipole polarizability from experimental measurements of two-dimensional acoustic meta-atoms. In contrast to extraction from numerical results, this enables all second-order effects and uncertainties in material properties to be accounted for. We apply the technique to 3D-printed labyrinthine meta-atoms of a variety of geometries. We show that the polarizability of structures with a shorter acoustic path length agrees well with numerical results. However, those with longer path lengths suffer strong additional damping, which we attribute to the strong viscous and thermal losses in narrow channels.
Jumaah, HJ, Mansor, S, Pradhan, B & Adam, SN 2018, 'UAV-based PM2.5 monitoring for small-scale urban areas', International Journal of Geoinformatics, vol. 14, no. 4, pp. 61-69.
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Air quality data such as Particulate Matter PM2.5 collection near the ground is difficult, particularly in small complex regions. This study aims to introduce a PM2.5 prediction algorithm based on measurements from Unmanned Arial Vehicle (UAV)-based sensing system and validate the model at a specified low altitude. Observations were applied around 1.6 km2 area in University Putra Malaysia. This study uses an empirical method via applying amassed records of PM2.5 and meteorological parameters to produce a predictive Geographically Weighted Regression (GWR) model. An accuracy value is computed from the probability value given by the regression analysis model. To validate this approach, we have utilized training and testing data. To evaluate and validate the suggested model, we applied the model to the training set. The obtained result indicated that there is a good statistical correlation, and demonstrated that the characteristics obtained by analysis are able to predict the concentration of PM2.5.
Kalantar, B, Pradhan, B, Naghibi, SA, Motevalli, A & Mansor, S 2018, 'Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 49-69.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs. However, few studies have been published on the training data selection effects on the LSM. Thus, this study assesses the training landslides random selection effects on support vector machine (SVM) accuracy, logistic regression (LR) and artificial neural networks (ANN) models for LSM in a catchment at the Dodangeh watershed, Mazandaran province, Iran. A 160 landslide locations inventory was collected by Geological Survey of Iran for this investigation. Different methods were implemented to define the landslide locations, such as inventory reports, satellite images and field survey. Moreover, 14 landslide conditioning factors were considered in the analysis of landslide susceptibility. These factors include curvature, plan curvature, profile curvature, altitude, slope angle, slope aspect, distance to faults, distance to stream, topographic wetness index, stream power index, terrain roughness index, sediment transport index, lithology and land use. The results show that the random landslide training data selection affected the parameter estimations of the SVM, LR and ANN algorithms. The results also show that the training samples selection had an effect on the accuracy of the susceptibility model because landslide conditioning factors vary according to the geographic locations in the study area. The LR model was found to be less sensitive than the SVM and ANN models to the training samples selection. Validation results showed that SVM and LR models outperformed the ANN model for all scenarios. The average overall accuracy of LR, SVM and ANN models are 81.42%, 79.82% and 70.2%, respectively.
Keshavarzi, A, Shrestha, CK, Melville, B, Khabbaz, H, Ranjbar-Zahedani, M & Ball, J 2018, 'Estimation of maximum scour depths at upstream of front and rear piers for two in-line circular columns', Environmental Fluid Mechanics, vol. 18, no. 2, pp. 537-550.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Previous investigations indicate that scour around bridge piers is one of the most important factors for the failure of waterway bridges. Hence, it is essential to determine the accurate scour depth around the bridge piers. Most of the previous studies were based on scour around a single pier; however, in practice, new bridges are usually wide and then piers comprise two circular piers aligned in the flow direction that together support the loading of the structure. In this study, the effect on maximum scour depth of the spacing between two piers aligned in the flow direction was investigated experimentally under clear water scour conditions. The results show that the maximum scour depth at upstream of the front pier occurs when the spacing between the two piers is 2.5 times the diameter of the pier. Two semi empirical equations have been developed to predict the maximum scour depth at upstream of both front and rear piers as a function of the spacing between the piers, in terms of a pier-spacing factor. If the new equations for the pier-spacing factor are used with some of the existing equations for scour at a single pier, the predicted scouring depths are in good agreement with observed results. The S/M equation exhibited the best performance among the various equations tested and was recommended for use in prediction of the equilibrium scour depth. The findings of this study can be used to facilitate the positioning of piers when scouring is a design concern.
Keshavarzi, A, Shrestha, CK, Zahedani, MR, Ball, J & Khabbaz, H 2018, 'Experimental study of flow structure around two in-line bridge piers', Proceedings of the Institution of Civil Engineers - Water Management, vol. 171, no. 6, pp. 311-327.
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Previous investigations indicate that local scouring is one of the most common causes of waterway bridge failure. The scour mechanism around bridge piers is complicated by the interaction of flow and structure. To explore the local scouring process, it is therefore essential to study the flow–structure interaction around bridge piers. Most previous studies have been based on this interaction around a single pier; however, in practice, many bridges are wide and comprise a number of piers aligned in the flow direction that together support the loading. In this study, a particle image velocimetry technique was used to investigate two-dimensional flow–structure interaction around two in-line bridge piers with different spacings. Various influencing flow characteristics including turbulence intensity, turbulent kinetic energy and Reynolds stresses were calculated in different vertical planes around the bridge piers. Results indicated that the flow characteristics around two in-line bridge piers are very different than for a single pier and the spacing between two in-line piers significantly influences the flow characteristics, particularly in the rear of the piers. Furthermore, for spacing in the range of 2 ≤ L/D ≤ 3, stronger turbulence structures occurred behind pier 1 and, as a result, a higher scour depth can be expected around pier 1.
Khan, AA, Abolhasan, M & Ni, W 2018, 'An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs', IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 4501-4513.
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© 1967-2012 IEEE. Discovering and maintaining efficient routes for data dissemination in vehicular ad hoc networks (VANETs) has proven to be a very challenging problem. Clustering is one of the control protocols used to provide efficient and stable routes for data dissemination. However, the rapid changes in network topology in VANETs creates frequent cluster reformation, which can seriously affect route stability. We propose a novel evolutionary game theoretic (EGT) framework to automate the clustering of nodes and nominations of cluster heads, to achieve cluster stability in VANETs. The equilibrium point is proven analytically and the stability is also tested using Lyapunov function. The performance of the proposed evolutionary game is empirically investigated with different cost functions using static and mobile scenarios. The simulation results demonstrate the effectiveness and robustness of our proposed EGT approach for different populations and speeds, thus reducing the overhead of frequent cluster reformation in VANETs.
Khosrokhani, M, Khairunniza-Bejo, S & Pradhan, B 2018, 'Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques', Geocarto International, vol. 33, no. 3, pp. 260-276.
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Lake, C & Sheng, D 2018, 'Note of appreciation / Note de reconnaissance', Canadian Geotechnical Journal, vol. 55, no. 12, pp. v-vii.
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Lamqadem, A, Saber, H & Pradhan, B 2018, 'Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques', Remote Sensing, vol. 10, no. 12, pp. 1862-1862.
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Desertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part of the country. This study aims to map the degree of desertification in middle Draa Valley in 2017 using a Sentinel-2 MSI (multispectral instrument) image. Firstly, three indices, namely, tasselled cap brightness (TCB), greenness (TCG) and wetness (TCW) were extracted using the tasselled cap transformation method. Secondly, other indices, such as normalized difference vegetation index (NDVI) and albedo, were retrieved. Thirdly, a linear regression analysis was performed on NDVI–albedo, TCG–TCB and TCW–TCB combinations. Results showed a higher correlation between TCW and TCB (r = −0.812) than with that of the NDVI–albedo (r = −0.50). On the basis of this analysis, a desertification degree index was developed using the TCW–TCB feature space classification. A map of desertification grades was elaborated and divided into five classes, namely, nondesertification, low, moderate, severe and extreme levels. Results indicated that only 6.20% of the study area falls under the nondesertification grade, whereas 26.92% and 32.85% fall under the severe and extreme grades, respectively. The employed method was useful for the quantitative assessment of desertification with an overall accuracy of 93.07%. This method is simple, robust, powerful, and easy to use for the management and protection of the fragile arid and semiarid lands.
Lee, J-H, Sameen, MI, Pradhan, B & Park, H-J 2018, 'Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods', Geomorphology, vol. 303, pp. 284-298.
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Li, K, Ni, W, Duan, L, Abolhasan, M & Niu, J 2018, 'Wireless Power Transfer and Data Collection in Wireless Sensor Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 3, pp. 2686-2697.
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© 1967-2012 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, whereas the other nodes 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 EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semidecentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.
Li, L, Nimbalkar, S & Zhong, R 2018, 'Finite element model of ballasted railway with infinite boundaries considering effects of moving train loads and Rayleigh waves', Soil Dynamics and Earthquake Engineering, vol. 114, pp. 147-153.
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© 2018 Elsevier Ltd This paper proposes a three-dimensional model incorporating finite element (FE) meshes with infinite element (IE) boundaries for ballasted railways. Moving train loads are simulated with sliding motions of moving elements which have hard contact feature at the interface with supporting rails. Dynamic responses of ballasted railway under different train speeds are investigated in time domain and frequency domain to identify the predominant frequency and critical speed. Rayleigh wave (R-Wave) propagation is simulated using the combined FE-IE model to determine the velocity of R-Wave in the layered embankment model and its relationship with the critical speed of the ballasted railway. The proposed model is successfully validated against the results of Euler-Bernoulli Elastic Beam (E-BEB) model.
Llano-Serna, MA, Farias, MM, Pedroso, DM, Williams, DJ & Sheng, D 2018, 'An assessment of statistically based relationships between critical state parameters', Géotechnique, vol. 68, no. 6, pp. 556-560.
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Reliability-based design (RBD) has been proved effective in the application of probability theory to research and practice in geotechnical engineering. However, the limited field and laboratory information makes it difficult to build robust predictions. This note shows some statistical relationships that may help with additional information in this area. Descriptive statistics are performed in the note followed by demonstrations of the close relationship between deformabilty parameters. The strong correlation between the slope of the critical state line and the earth pressure coefficient at rest is found. The applicability of the statistical relationships is also examined using RBD. Numerical analysis of oedometer tests demonstrates how RBD can consider the influence of the uncertainty of the critical state parameters.
Llano-Serna, MA, Farias, MM, Pedroso, DM, Williams, DJ & Sheng, D 2018, 'Considerations on the Experimental Calibration of the Fall Cone Test', Geotechnical Testing Journal, vol. 41, no. 6, pp. 1131-1138.
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Abstract The fall cone test is widely used in soil mechanics to determine the liquid limit of fine-grained soils as an aid to soil classification. The test can also be used to obtain the undrained shear strength of a fine-grained soil, based on the “cone factor,” K. Reports from different authors show K values ranging from 0.4–1.33. Differences are mostly attributed to the cone surface roughness. This article presents a reinterpretation of several experimental observations available in the literature. It is observed that besides the cone roughness, testing methods have a clear influence when calibrating the fall cone for determining the undrained shear strength of materials with low and very low consistency. The results show that existing K reports should be extrapolated with care. Finally, we propose a series of recommendations and good practices for future calibrations.
Lloret-Cabot, M, Wheeler, SJ, Pineda, JA, Romero, E & Sheng, D 2018, 'From saturated to unsaturated conditions and vice versa', Acta Geotechnica, vol. 13, no. 1, pp. 15-37.
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Lloret-Cabot, M, Wheeler, SJ, Pineda, JA, Romero, E & Sheng, D 2018, 'Reply to “Discussion of “From saturated to unsaturated conditions and vice versa” by M. Lloret-Cabot et al. (DOI 10.1007/s11440-017-0577-6)” by S. Qi et al. (DOI 10.1007/s11440-017-0625-2)', Acta Geotechnica, vol. 13, no. 2, pp. 493-495.
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Masoudi, M, Jokar, P & Pradhan, B 2018, 'A new approach for land degradation and desertification assessment using geospatial techniques', Natural Hazards and Earth System Sciences, vol. 18, no. 4, pp. 1133-1140.
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Abstract. Land degradation reduces the production of biomass and vegetation cover for all forms of land use. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of the current state of land degradation or desertification is very difficult because this phenomenon includes several complex processes. For that reason, no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment, based on its current state by modifying of Food and Agriculture Organization (FAO)–United Nations Environment Programme (UNEP) index and the normalized difference vegetation index (NDVI) index in Khuzestan province, southwestern Iran. Using the proposed evaluation method it is easy to understand the degree of destruction caused by the pursuit of low costs and in order to save time. Results showed that based on the percent of hazard classes in the current condition of land degradation, the most and least widespread areas of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. Results in the desert component of the study area showed that the severe class is much more widespread than the other hazard classes, which could indicate an environmentally dangerous situation. Statistical results indicated that degradation is highest in deserts and rangeland areas compared to dry cultivated areas and forests. Statistical tests also showed that the average degradation amount in the arid region is higher than in other climates. It is hoped that this study's use of geospatial techniques will be found to be applicable in other regions of the world and can also contribute to better planning and management of land.
Meng, J, Huang, J, Sheng, D & Sloan, SW 2018, 'Closure to “Quasi-Static Rheology of Granular Media Using the Static DEM” by J. Meng, J. Huang, D. Sheng, and S. W. Sloan', International Journal of Geomechanics, vol. 18, no. 12, pp. 07018016-07018016.
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Meng, J, Huang, J, Sloan, SW & Sheng, D 2018, 'Discrete modelling jointed rock slopes using mathematical programming methods', Computers and Geotechnics, vol. 96, pp. 189-202.
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Meng, J, Huang, J, Yao, C & Sheng, D 2018, 'A discrete numerical method for brittle rocks using mathematical programming', Acta Geotechnica, vol. 13, no. 2, pp. 283-302.
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Mezaal, M, Pradhan, B & Rizeei, H 2018, 'Improving Landslide Detection from Airborne Laser Scanning Data Using Optimized Dempster–Shafer', Remote Sensing, vol. 10, no. 7, pp. 1029-1029.
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© 2018 by the authors. A detailed and state-of-the-art landslide inventory map including precise landslide location is greatly required for landslide susceptibility, hazard, and risk assessments. Traditional techniques employed for landslide detection in tropical regions include field surveys, synthetic aperture radar techniques, and optical remote sensing. However, these techniques are time consuming and costly. Furthermore, complications arise for the generation of accurate landslide location maps in these regions due to dense vegetation in tropical forests. Given its ability to penetrate vegetation cover, high-resolution airborne light detection and ranging (LiDAR) is typically employed to generate accurate landslide maps. The object-based technique generally consists of many homogeneous pixels grouped together in a meaningful way through image segmentation. In this paper, in order to address the limitations of this approach, the final decision is executed using Dempster-Shafer theory (DST) rule combination based on probabilistic output from object-based support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN) classifiers. Therefore, this research proposes an efficient framework by combining three object-based classifiers using the DST method. Consequently, an existing supervised approach (i.e., fuzzy-based segmentation parameter optimizer) was adopted to optimize multiresolution segmentation parameters such as scale, shape, and compactness. Subsequently, a correlation-based feature selection (CFS) algorithm was employed to select the relevant features. Two study sites were selected to implement the method of landslide detection and evaluation of the proposed method (subset 'A' for implementation and subset 'B' for the transferrable). The DST method performed well in detecting landslide locations in tropical regions such as Malaysia, with potential applications in other similarly vegetated regions.
Mezaal, MR & Pradhan, B 2018, 'An improved algorithm for identifying shallow and deep-seated landslides in dense tropical forest from airborne laser scanning data', CATENA, vol. 167, pp. 147-159.
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© 2018 Landslides are natural disasters that cause environmental and infrastructure damage worldwide. They are difficult to be recognized, particularly in densely vegetated regions of the tropical forest areas. Consequently, an accurate inventory map is required to analyze landslides susceptibility, hazard, and risk. Several studies were done to differentiate between different types of landslide (i.e. shallow and deep-seated); however, none of them utilized any feature selection techniques. Thus, in this study, three feature selection techniques were used (i.e. correlation-based feature selection (CFS), random forest (RF), and ant colony optimization (ACO)). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Random forest (RF) was used to evaluate the performance of each feature selection algorithms. The overall accuracies of the RF classifier revealed that CFS algorithm exhibited higher ranks in differentiation landslide types. Moreover, the results of the transferability showed that this method is easy, accurate, and highly suitable for differentiating between types of landslides (shallow and deep-seated). In summary, the study recommends that the outlined approaches are significant to improve in distinguishing between shallow and deep-seated landslide in the tropical areas, such as; Malaysia.
Mezaal, MR & Pradhan, B 2018, 'Data Mining-Aided Automatic Landslide Detection Using Airborne Laser Scanning Data in Densely Forested Tropical Areas', KOREAN JOURNAL OF REMOTE SENSING, vol. 34, no. 1, pp. 45-74.
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Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.
Mirzababaei, M, Arulrajah, A, Haque, A, Nimbalkar, S & Mohajerani, A 2018, 'Effect of fiber reinforcement on shear strength and void ratio of soft clay', Geosynthetics International, vol. 25, no. 4, pp. 471-480.
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In this study, a series of multi-stage drained reverse direct shear tests were carried out on soft clay samples reinforced with 0.25% and 0.50% polypropylene fibers of 6 mm, 10 mm and 19 mm in length. Tests were carried out at different normal effective stresses and cumulative horizontal shear displacement of 1.17 times of the sample width. Results showed an increase of the shear strength with the increase of fiber content and length. However, the rate of improvement was capped with the normal effective stress applied during the shearing stage. At a high normal effective stress, the shear strength of the fiber-reinforced soft clay approached that of the unreinforced clay regardless of the amount of fiber inclusion. The rate of shear strength improvement decayed with the number of shear cycles. Fiber reinforcement also resulted in a reduction of the compressibility of the soft clay at consecutive consolidation and shear stages. Although the effective internal friction angle of the soft clay was not altered significantly with the fiber reinforcement, the effective cohesion of the soft clay improved significantly as much as 6.4 and 8.5 times with the inclusion of 0.25% and 0.50% of 10 mm long fibers, respectively.
Mohammadi-Moghaddam, T, Razavi, SMA, Taghizadeh, M, Pradhan, B, Sazgarnia, A & Shaker-Ardekani, A 2018, 'Hyperspectral imaging as an effective tool for prediction the moisture content and textural characteristics of roasted pistachio kernels', Journal of Food Measurement and Characterization, vol. 12, no. 3, pp. 1493-1502.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The objective of this study was to develop calibration models for prediction of moisture content and textural characteristics (fracture force, hardness, apparent modulus of elasticity and compressive energy) of pistachio kernels roasted in different conditions (temperatures 90, 120 and 150 °C; times 20, 35 and 50 min and air velocities 0.5, 1.5 and 2.5 m/s) using Vis/NIR hyperspectral imaging and multivariate analysis. The effects of different pre-processing methods and spectral treatments such as normalization [multiplicative scatter correction (MSC), standard normal variate transformation (SNV)], smoothing (median filter, Savitzky–Golay and Wavelet) and differentiation (first derivative, D1 and second derivative, D2) on the obtained data were investigated. The prediction models were developed by partial least square regression (PLSR) and artificial neural network (ANN). The results indicated that ANN models have higher potential to predict moisture content and textural characteristics of roasted pistachio kernels comparing to PLSR models. High correlation was observed between reflectance data and fracture force (R2 = 0.957 and RMSEP = 3.386) using MSC, Savitzky–Golay and D1, compressive energy (R2 = 0.907 and RMSEP = 15.757) using the combination of MSC, Wavelet and D1, moisture content (R2 = 0.907 and RMSEP = 0.179) and apparent modulus of elasticity (R2 = 0.921 and RMSEP = 2.366) employing combination of SNV, Wavelet and D1, respectively. Moreover, Vis–NIR data correlated well with hardness (R2 = 0.876 and RMSEP = 5.216) using SNV, Wavelet and D2. These results showed the capability of Vis/NIR hyperspectral imaging and the central role of multivariate analysis in developing accurate models for prediction of moisture content and textural properties of roasted pistachio kernels.
Mokhtar, ES, Pradhan, B, Ghazali, AH & Shafri, HZM 2018, 'Assessing flood inundation mapping through estimated discharge using GIS and HEC-RAS model', Arabian Journal of Geosciences, vol. 11, no. 21.
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© 2018, Saudi Society for Geosciences. Water discharge is the main parameter in hydraulic modeling for flood hazard assessment. However, the unavailability of data on discharge and observed river morphologies resulted in erroneous calculations and irregularities in flood inundation mapping. The objectives of this study are (i) to investigate uncertainties of hydraulic parameters (width, cross-sectional depth, and channel slope) used in discharge equation and (ii) to examine the influence of estimate discharge on water extent and flood depth with different boundary conditions on interferometric synthetic aperture radar (IFSAR) and modified IFSAR DEMs. Sensitivity analysis was conducted with the Monte Carlo simulation method to generate random data combinations. Bjerklie’s equation was used to calculate discharge based on the three variables, and Manning’s n was substituted into the Hydrologic Engineering Center River Analysis System (HEC-RAS) model. TerraSAR-X was used to distinguish existing flood water bodies and normal water extent. The uncertainty of the combined variables was assessed with the likelihood measures such as F-statistic, mean absolute error, root mean square error, and Nash–Sutcliffe efficiency which compares observed and predicted inundated area as well as flood water depth simulated using the HEC-RAS model.
Movassaghi, S, Smith, DB, Abolhasan, M & Jamalipour, A 2018, 'Opportunistic Spectrum Allocation for Interference Mitigation Amongst Coexisting Wireless Body Area Networks', ACM Transactions on Sensor Networks, vol. 14, no. 2, pp. 1-22.
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Wireless Body Area Networks (WBANs) are seen as the enabling technology for developing new generations of medical applications, such as remote health monitoring. As such it is expected that WBANs will predominantly transport mission-critical and delay sensitive data. A key strategy towards building a reliable WBAN is to ensure such networks are highly immune to interference. To achieve this, new and intelligent wireless spectrum allocation strategies are required not only to avoid interference, but also to make best-use of the limited available spectrum. This article presents a new spectrum allocation scheme referred to as Smart Channel Assignment (SCA), which maximizes the resource usage and transmission speed by deploying a partially-orthogonal channel assignment scheme between coexisting WBANs as well as offering a convenient tradeoff among spectral reuse efficiency, transmission rate, and outage. Detailed analytical studies verify that the proposed SCA strategy is robust to variations in channel conditions, increase in sensor node-density within each WBAN, and an increase in number of coexisting WBANs.
Naghibi, S, Vafakhah, M, Hashemi, H, Pradhan, B & Alavi, S 2018, 'Groundwater Augmentation through the Site Selection of Floodwater Spreading Using a Data Mining Approach (Case study: Mashhad Plain, Iran)', Water, vol. 10, no. 10, pp. 1405-1405.
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It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions.
Nahhas, FH, Shafri, HZM, Sameen, MI, Pradhan, B & Mansor, S 2018, 'Deep Learning Approach for Building Detection Using LiDAR–Orthophoto Fusion', Journal of Sensors, vol. 2018, pp. 1-12.
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This paper reports on a building detection approach based on deep learning (DL) using the fusion of Light Detection and Ranging (LiDAR) data and orthophotos. The proposed method utilized object-based analysis to create objects, a feature-level fusion, an autoencoder-based dimensionality reduction to transform low-level features into compressed features, and a convolutional neural network (CNN) to transform compressed features into high-level features, which were used to classify objects into buildings and background. The proposed architecture was optimized for the grid search method, and its sensitivity to hyperparameters was analyzed and discussed. The proposed model was evaluated on two datasets selected from an urban area with different building types. Results show that the dimensionality reduction by the autoencoder approach from 21 features to 10 features can improve detection accuracy from 86.06% to 86.19% in the working area and from 77.92% to 78.26% in the testing area. The sensitivity analysis also shows that the selection of the hyperparameter values of the model significantly affects detection accuracy. The best hyperparameters of the model are 128 filters in the CNN model, the Adamax optimizer, 10 units in the fully connected layer of the CNN model, a batch size of 8, and a dropout of 0.2. These hyperparameters are critical to improving the generalization capacity of the model. Furthermore, comparison experiments with the support vector machine (SVM) show that the proposed model with or without dimensionality reduction outperforms the SVM models in the working area. However, the SVM model achieves better accuracy in the testing area than the proposed model without dimensionality reduction. This study generally shows that the use of an autoencoder in DL models can improve the accuracy of building recognition in fused LiDAR–orthophoto data.
Nampak, H, Pradhan, B, Mojaddadi Rizeei, H & Park, H 2018, 'Assessment of land cover and land use change impact on soil loss in a tropical catchment by using multitemporal SPOT‐5 satellite images and Revised Universal Soil Loss Equation model', Land Degradation & Development, vol. 29, no. 10, pp. 3440-3455.
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AbstractSoil erosion is a common land degradation problem and has disastrous impacts on natural ecosystems and human life. Therefore, researchers have focused on detection of land cover–land use changes (LCLUC) with respect to monitoring and mitigating the potential soil erosion. This article aims to appraise the relationship between LCLUC and soil erosion in the Cameron Highlands (Malaysia) by using multitemporal satellite images and ancillary data. Land clearing and heavy rainfall events in the study area has resulted in increased soil loss. Moreover, unsustainable development and agricultural practices, mismanagement, and lack of land use policies increase the soil erosion rate. Hence, the main contribution of this study lies in the application of appropriate land management practices in relation to water erosion through identification and prediction of the impacts of LCLUC on the spatial distribution of potential soil loss in a region susceptible to natural hazards such as landslide. The LCLUC distribution within the study area was mapped for 2005, 2010, and 2015 by using SPOT‐5 temporal satellite imagery and object‐based image classification. A projected land cover–land use map was also produced for 2025 through integration of Markov chain and cellular automata models. An empirical‐based approach (Revised Universal Soil Loss Equation) coupled with geographic information system was applied to measure soil loss and susceptibility to erosion over the study area for four periods (2005, 2010, 2015, and 2025). The model comprises five parameters, namely, rainfall factor, soil erodibility, topographical factor, conservation factor, and support practice factor. Results exhibited that the average amount of soil loss increased by 31.77 t ha−1 yr−1 from 2005 to 2015 and was predicted to dramatically increase in 2025. The results generated from this research recommends that awareness of...
Navaratnarajah, SK & Indraratna, B 2018, 'Closure to “Use of Rubber Mats to Improve the Deformation and Degradation Behavior of Rail Ballast under Cyclic Loading” by Sinniah K. Navaratnarajah and Buddhima Indraratna', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 7, pp. 07018014-07018014.
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Navaratnarajah, SK, Indraratna, B & Ngo, NT 2018, 'Influence of Under Sleeper Pads on Ballast Behavior Under Cyclic Loading: Experimental and Numerical Studies', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 9, pp. 04018068-04018068.
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Railway industries are placing greater emphasis on implementing fast and heavy haul corridors for bulk freight and commuter transport in order to deliver more efficient and cost-effective services. However, increasing dynamic stresses from the passage of trains progressively degrades and fouls the primary load-bearing ballast layer, which inevitably leads to excessive settlement and instability, damage to track elements, and more frequent maintenance. Ballasted tracks are subjected to even greater stresses and faster deterioration in sections where a reduced ballast thickness is used (e.g., bridge decks) or at locations where heavier concrete sleepers are used instead of lightweight timber sleepers. The inclusion of under sleeper pads (USPs) at the base of a concrete sleeper is one measure used to minimize dynamic stresses and subsequent track deterioration. In this study, cyclic loads from fast and heavy haul trains were simulated using a large-scale process simulation prismoidal triaxial apparatus (PSPTA) to investigate the performance of ballast improved by USPs. The laboratory results indicate that the inclusion of an elastic element at the harder interface of the concrete sleeper-ballast reduces the stresses transmitted to the ballast and the underlying layers and minimizes the amount of deformation and degradation of the ballast. A three-dimensional finite-element model was used to predict the behavior of ballast, and the influence of USPs on the stress-strain responses of ballast generally agree with the experimental findings.
Ngo, NT, Indraratna, B, Ferreira, FB & Rujikiatkamjorn, C 2018, 'Improved performance of geosynthetics enhanced ballast: laboratory and numerical studies', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 171, no. 4, pp. 202-222.
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Ballasted rail tracks form one of the most important worldwide transportation modes in terms of traffic tonnage, serving the needs of bulk freight and passenger movement. High impact and cyclic loads can cause a significant deformation leading to poor track geometry. In order to mitigate these problems, the concept of the inclusion of geosynthetics in rail tracks is introduced. This paper presents the current state-of-the-art knowledge of rail track geomechanics, including results obtained from laboratory testing, field investigations and numerical modelling to study the load–deformation behaviour of ballast improved by geosynthetics. The shear stress–strain and deformation behaviour of geosynthetic-reinforced ballast are investigated in the laboratory using a large-scale direct shear test device, a track process simulation apparatus and a drop-weight impact testing equipment. Computational modelling using the discrete-element method is employed to simulate geosynthetic-reinforced ballasted tracks, capturing the discrete nature of ballast aggregates when subjected to various types of loading and boundary conditions. Discrete-element modelling is also used to conduct micromechanical analysis at the interface between ballast and geogrid, providing further insight into the behaviour of ballast subjected to cyclic loadings. These results provide promising approaches to incorporate into existing track design routines catering for future high-speed trains and heavier heavy hauls.
Ngo, P-T, Hoang, N-D, Pradhan, B, Nguyen, Q, Tran, X, Nguyen, Q, Nguyen, V, Samui, P & Tien Bui, D 2018, 'A Novel Hybrid Swarm Optimized Multilayer Neural Network for Spatial Prediction of Flash Floods in Tropical Areas Using Sentinel-1 SAR Imagery and Geospatial Data', Sensors, vol. 18, no. 11, pp. 3704-3704.
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Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg–Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility.
Nguyen, TT, Indraratna, B & Carter, J 2018, 'Laboratory Investigation into Biodegradation of Jute Drains with Implications for Field Behavior', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 6, pp. 04018026-04018026.
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Naturally occurring materials such as jute and coir have some favorable engineering characteristics and also degrade over time, so they have increasingly been used in engineering applications in recent years. The efficient way that naturally prefabricated vertical drains made from those materials help accelerate soil consolidation has been shown in previous studies, but they also tend to decompose rapidly in adverse environments, where cellulose-degrading bacteria cause a serious deterioration of their favorable drainage properties. This study presents a laboratory investigation into the biodegradation of prefabricated vertical jute drains in saturated soft soils, where the tensile strength of jute and coir fibers and the discharge capacity of drains decrease in response to different environments. Micro-observation also shows a transformation of the jute fibers and destruction of the drain structure due to biodegradation. DNA extraction and sequencing techniques to determine the microbial properties of these decayed fibers indicate that bacteria such as species of the genera Clostridium and Bacillus can cause rapid decomposition of cellulose-based material (i.e., jute), whereas other organic matter-consuming microbes such as sulfate-reducing bacteria do not directly contribute to the biodegradation of jute. In response, an analytical approach that incorporates various forms of drain discharge capacity over time is proposed to predict soil consolidation. The results indicate there is considerable deviation in dissipating the excess pore pressure when the drain degrades in different ways.
Nguyen, TT, Indraratna, B & Rujikiatkamjorn, C 2018, 'Challenges and solutions towards natural prefabricated vertical drains', Australian Geomechanics Journal, vol. 53, no. 4, pp. 89-100.
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In recent years, natural fibres such as jute and coir are emerging as a reasonable alternative to synthetic materials because they do not only have favourable engineering characteristics but also degrade biologically over time. Of promising applications of those environmentally friendly materials, natural prefabricated vertical drains (NPVDs) have received considerable attention, however their application is still limited. This paper summarises existing issues which are hampering these novel drains from a wider application, followed by studies carried out by the authors to overcome those limitations. Particularly this includes: (1) hydraulic properties of NPVDs considering macro and micro features; (2) modelling NPVDS including analytical method and a novel numerical approach to capture micro-hydraulic behavior of fibre drains considering fluid-fibre interaction; (3) bioderadable characteristics of NPVDs exposed to saturated soft soils; (4) analytical and numerical solutions to incorporate biodegradation of NPVDs into consolidation of soil.
Nguyen, VV, Li, J, Erkmen, E, Alamdari, MM & Dackermann, U 2018, 'FRF Sensitivity-Based Damage Identification Using Linkage Modeling for Limited Sensor Arrays', International Journal of Structural Stability and Dynamics, vol. 18, no. 08, pp. 1840002-1840002.
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This paper presents a novel method to localize and quantify damage in a jack arch structure by introducing a linkage modeling technique to overcome issues caused by having limited sensors. The main strategy in the proposed Frequency Response Function (FRF)-based sensitivity model updating approach is to divide the specimen into partitions. The Young’s modulus of each partition is then updated to detect stiffness reduction caused by damage. System Equivalent Reduction Expansion Process (SEREP) is used to reduce the full finite element (FE) model to a linkage model. The number of measured degrees of freedom (DOFs) is then expanded to the linkage model using the mass and stiffness matrices of the linkage model for the synthesis of interpolated FRFs. The FRF sensitivities are then formulated using the linkage model along with the interpolated FRFs to iteratively calculate the values of the updating parameters until convergence is achieved. The methodology and theory behind this procedure are discussed and verified using a numerical and experimental study. The successful implementation of this method has the potential to detect the location and severity of damage where sensor placement is limited.
Ni, W, Zhang, JA, Fang, Z, Abolhasan, M, Liu, RP & Guo, YJ 2018, 'Analysis of Finite Buffer in Two-Way Relay: A Queueing Theoretic Point of View', IEEE Transactions on Vehicular Technology, vol. 67, no. 4, pp. 3690-3694.
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© 1967-2012 IEEE. The impact of a finite relay buffer on the throughput of two-way relay is analyzed from a new queueing theoretic point of view. Distinctively from recent Markov model based analyses, the proposed queueing theoretic analysis is able to infer closed-form asymptotic upper bounds for the throughput, shed valuable insights, and point out limitations in the recent analyses. Validated by simulations, our queueing theoretic analysis reveals that the throughput is increasingly insusceptible to the size of the relay buffer, as the buffer enlarges. Moreover, locking the relay in transmitting xored packets can hardly improve the throughput, especially under balanced channel conditions. This is due to the fact that the relay queues stabilize nonempty, and hence, xored packets are forwarded in most cases.
Nimbalkar, S, Annapareddy, VSR & Pain, A 2018, 'A simplified approach to assess seismic stability of tailings dams', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1082-1090.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences In the zones of high seismic activity, tailings dam should be assessed for the stability against earthquake forces. In the present paper, a simplified method is proposed to compute the factor of safety of tailings dams. The strain-dependent dynamic properties are used to assess the stability of tailings dams under seismic conditions. The effect of foundation soil properties on the seismic stability of tailings dams is studied using the proposed method. For the given input parameters, the factor of safety for low-frequency input motions is nearly 26% lower than that for high-frequency input excitations. The impedance ratio and the depth of foundation have significant effect on the seismic factor of safety of tailings dams. The results from the proposed method are well compared with the existing pseudo-static method of analysis. Tailings dams are vulnerable to damage for low-frequency input motions.
Nimbalkar, S, Dash, SK & Indraratna, B 2018, 'Performance of ballasted track under impact loading and applications of recycled rubber inclusion', Geotechnical Engineering, vol. 49, no. 4, pp. 79-91.
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In this paper a review of the sources of impact loads and their effect on the performance of ballasted track is presented. The typical characteristics and implications of impact loading on track deterioration, particularly ballast degradation, are discussed. None of the procedures so far developed to design rail track incorporate the impact that dynamic loading has on the breakage of ballast and therefore it can be said to be incomplete. An intensive study on the impact of induced ballast breakage is needed in order to understand this phenomenon and then use the knowledge gained to further advance the design methodology. A stiff track structure can create severe dynamic loading under operating conditions which causes large scale component failure and increases maintenance requirements. Installing resilient mats such as rubber pads (ballast mat, soffit pad) in rail tracks can attenuate the dynamic force and improve overall performance. The efficacy of ballast mats to reduce structural noise and ground vibration has been studied extensively, but a few recent studies has reported how ballast mats and soffit pads reduce ballast degradation, thus obviating the necessity of a comprehensive study in this direction.
Oberst, S & Tuttle, S 2018, 'Nonlinear dynamics of thin-walled elastic structures for applications in space', Mechanical Systems and Signal Processing, vol. 110, pp. 469-484.
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© 2018 Elsevier Ltd Driven by the need for multi-functionality and increasing demands for low mass and compact-stowing, unfolding, self-deploying or –morphing smart mechanical structures have become popular space engineering designs for flexible appendages. Extensive research has been conducted on the use of tape springs as hinge deployment mechanisms for space booms, solar sails, or optical membranes or directly for used as antennas. However, the vibrational behaviour of tape springs and its related dynamics have rarely been addressed in detail, even though missions are underway with similarly flexible appendages installed. By conducting quasi-static bending tests on a tape spring antenna, we evidence hysteresis behaviours in both the opposite- and equal sense bending directions. Apart from the well-known snap-through buckling, the structure exhibits torsional buckling in the equal sense bending direction before collapsing. Micro-vibrational excitation triggers nonlinear jump phenomena and the period-doubling route to chaos. Using a computational tape spring model and simplified environmental loads similar to those encountered in near-Earth orbits, coupling between the first bending and torsional modes generates a dynamic instability which is predicted by a complex eigenvalue analysis step. The current study highlights that high perturbation sensitivity and system-inherent nonlinearities can lead to stability issues. In the course of designing a spacecraft with thin-walled appendages, system-level trade-offs are routinely performed. Since it is unclear how severely the vibrations of flexible appendages might affect their proper functioning or the control of the spacecraft, it is of paramount importance to validate experimentally thin-walled structures thoroughly for their dynamic and stability behaviours.
Oberst, S, Baetz, J, Campbell, G, Lampe, F, Lai, JCS, Hoffmann, N & Morlock, M 2018, 'Vibro-acoustic and nonlinear analysis of cadavric femoral bone impaction in cavity preparations', International Journal of Mechanical Sciences, vol. 144, pp. 739-745.
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© 2018 Elsevier Ltd Owing to an ageing population, the impact of unhealthy lifestyle, or simply congenital or gender specific issues (dysplasia), degenerative bone and joint disease (osteoarthritis) at the hip pose an increasing problem in many countries. Osteoarthritis is painful and causes mobility restrictions; amelioration is often only achieved by replacing the complete hip joint in a total hip arthroplasty (THA). Despite significant orthopaedic progress related to THA, the success of the surgical process relies heavily on the judgement, experience, skills and techniques used of the surgeon. One common way of implanting the stem into the femur is press fitting uncemented stem designs into a prepared cavity. By using a range of compaction broaches, which are impacted into the femur, the cavity for the implant is formed. However, the surgeon decides whether to change the size of the broach, how hard and fast it is impacted or when to stop the excavation process, merely based on acoustic, haptic or visual cues which are subjective. It is known that non-ideal cavity preparations increase the risk of peri-prosthetic fractures especially in elderly people. This study reports on a simulated hip replacement surgery on a cadaver and the analysis of impaction forces and the microphone signals during compaction. The recorded transient signals of impaction forces and acoustic pressures (≈ 80 µs–2 ms) are statistically analysed for their trend, which shows increasing heteroscedasticity in the force-pressure relationship between broach sizes. TIKHONOV regularisation, as inverse deconvolution technique, is applied to calculate the acoustic transfer functions from the acoustic responses and their mechanical impacts. The extracted spectra highlight that system characteristics altered during the cavity preparation process: in the high-frequency range the number of resonances increased with impacts and broach size. By applying nonlinear time series analysis the syste...
Oberst, S, Lai, JCS & Evans, TA 2018, 'Key physical wood properties in termite foraging decisions', Journal of The Royal Society Interface, vol. 15, no. 149, pp. 20180505-20180505.
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As eusocial and wood-dwelling insects, termites have been shown to use vibrations to assess their food, to eavesdrop on competitors and predators and to warn nest-mates. Bioassay choice experiments used to determine food preferences in animals often consider single factors only but foraging decisions can be influenced by multiple factors such as the quantity and quality of the food and the wood as a medium for communication. A statistical analysis framework is developed here to design a single bioassay experiment to study multifactorial foraging choice (Pinus radiata) in the basal Australian termite speciesCoptotermes(C.)acinaciformis(Isoptera: Rhinotermitidae). By employing a correlation analysis, 17 measured physical properties of 1417Pinus radiataveneer discs were reduced to five key material properties: density, moisture absorption, early wood content, first resonance frequency and damping. By applying a fuzzyc-means clustering technique, these veneer discs were optimally paired for treatment and control trials to study food preference by termites based on these five key material properties. A multifactorial analysis of variance was compared to a permutation analysis of the results indicating for the first time thatC. acinaciformistakes into account multiple factors when making foraging decisions.C. acinaciformisprefer denser wood with large early wood content, preferably humid and highly damped. Results presented here have practical implications for food choice experiments and for studies concerned with communication in termites as well as their ecology and coevolution with trees as their major food source.
Oberst, S, Niven, RK, Lester, DR, Ord, A, Hobbs, B & Hoffmann, N 2018, 'Detection of unstable periodic orbits in mineralising geological systems', Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 28, no. 8, pp. 085711-085711.
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Worldwide, mineral exploration is suffering from rising capital costs, due to the depletion of readily recoverable reserves and the need to discover and assess more inaccessible or geologically complex deposits. For gold exploration, this problem is particularly acute. We propose an innovative approach to mineral exploration and orebody characterisation, based on the analysis of geological core data as a spatial dynamical system, using the mathematical tools of dynamical system analysis. This approach is highly relevant for orogenic gold deposits, which—in contrast to systems formed at chemical equilibrium—exhibit many features of nonlinear dynamical systems, including episodic fluctuations on various length and time scales. Feedback relationships between thermo-chemical and deformation processes produce recurrent fluid temperatures and pressures and the deposition of vein-filling minerals such as pyrite and gold. We therefore relax the typical assumption of chemical equilibrium and analyse the underlying processes as aseismic, non-adiabatic, and inherent to a hydrothermal, nonlinear dynamical open-flow chemical reactor. These processes are approximated using the Gray-Scott model of reaction-diffusion as a complex toy system, which captures some of the features of the underlying mineralisation processes, including the spatiotemporal Turing patterns of unsteady chemical reactions. By use of this analysis, we demonstrate the capability of recurrence plots, recurrence power spectra, and recurrence time probabilities to detect underlying unstable periodic orbits as one sign of deterministic dynamics and their robustness for the analysis of data contaminated by noise. Recurrence plot based quantification is then applied to three mineral concentrations in the core data from the Sunrise Dam gold deposit in the Yilgarn region of Western Australia. Using a moving window, we reveal the episodic recurring low-dimensional dynamic structures and the period d...
Oberst, S, Tuttle, SL, Griffin, D, Lambert, A & Boyce, RR 2018, 'Experimental validation of tape springs to be used as thin-walled space structures', Journal of Sound and Vibration, vol. 419, pp. 558-570.
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© 2018 Elsevier Ltd With the advent of standardised launch geometries and off-the-shelf payloads, space programs utilising nano-satellite platforms are growing worldwide. Thin-walled, flexible and self-deployable structures are commonly used for antennae, instrument booms or solar panels owing to their lightweight, ideal packaging characteristics and near zero energy consumption. However their behaviour in space, in particular in Low Earth Orbits with continually changing environmental conditions, raises many questions. Accurate numerical models, which are often not available due to the difficulty of experimental testing under 1g-conditions, are needed to answer these questions. In this study, we present on-earth experimental validations, as a starting point to study the response of a tape spring as a representative of thin-walled flexible structures under static and vibrational loading. Material parameters of tape springs in a singly (straight, open cylinder) and a doubly curved design, are compared to each other by combining finite element calculations, with experimental laser vibrometry within a single and multi-stage model updating approach. While the determination of the Young's modulus is unproblematic, the damping is found to be inversely proportional to deployment length. With updated material properties the buckling instability margin is calculated using different slenderness ratios. Results indicate a high sensitivity of thin-walled structures to miniscule perturbations, which makes proper experimental testing a key requirement for stability prediction on thin-elastic space structures. The doubly curved tape spring provides closer agreement with experimental results than a straight tape spring design.
Oweis, IS 2018, 'Discussion of “Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation” by Sudip Basack, Buddhima Indraratna, Cholachat Rujikiatkamjorn, and Firman Siahaan', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 5, pp. 07018007-07018007.
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Pain, A, Ramakrishna Annapareddy, VS & Nimbalkar, S 2018, 'Seismic Active Thrust on Rigid Retaining Wall Using Strain Dependent Dynamic Properties', International Journal of Geomechanics, vol. 18, no. 12, pp. 06018034-06018034.
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Peng, H, Zheng, Y, Blumenstein, M, Tao, D & Li, J 2018, 'CRISPR/Cas9 cleavage efficiency regression through boosting algorithms and Markov sequence profiling', Bioinformatics, vol. 34, no. 18, pp. 3069-3077.
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AbstractMotivationCRISPR/Cas9 system is a widely used genome editing tool. A prediction problem of great interests for this system is: how to select optimal single-guide RNAs (sgRNAs), such that its cleavage efficiency is high meanwhile the off-target effect is low.ResultsThis work proposed a two-step averaging method (TSAM) for the regression of cleavage efficiencies of a set of sgRNAs by averaging the predicted efficiency scores of a boosting algorithm and those by a support vector machine (SVM). We also proposed to use profiled Markov properties as novel features to capture the global characteristics of sgRNAs. These new features are combined with the outstanding features ranked by the boosting algorithm for the training of the SVM regressor. TSAM improved the mean Spearman correlation coefficiencies comparing with the state-of-the-art performance on benchmark datasets containing thousands of human, mouse and zebrafish sgRNAs. Our method can be also converted to make binary distinctions between efficient and inefficient sgRNAs with superior performance to the existing methods. The analysis reveals that highly efficient sgRNAs have lower melting temperature at the middle of the spacer, cut at 5’-end closer parts of the genome and contain more ‘A’ but less ‘G’ comparing with inefficient ones. Comprehensive further analysis also demonstrates that our tool can predict an sgRNA’s cutting efficiency with consistently good performance no matter it is expressed from an U6 promoter in cells or from a T7 promoter in vitro.Availability and implementationOnline tool is available at http://www.aai-bioinfo.com/CRISPR/. Python and Matlab source codes are freely available at https://github.com/penn-hui/TSAM.Supplementary information
Pourghasemi, HR, Teimoori Yansari, Z, Panagos, P & Pradhan, B 2018, 'Analysis and evaluation of landslide susceptibility: a review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016)', Arabian Journal of Geosciences, vol. 11, no. 9.
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© 2018, Saudi Society for Geosciences. Landslides are one of the most important environmental hazards occur naturally or human-induced with large-scale social, economic, and environmental impacts. Landslide susceptibility zoning, which has been widely performed in the last decades, allows identifying spatial prediction of areas of landslides, which could be used for land use planning and land management. The present study was conducted as a review with the aim of investigating the research background of landslide susceptibility in the world during the period of 2005–2016. The results showed that the publication of papers related to landslide susceptibility during the period of investigation has been on the rise, and China has produced a larger number of papers and authors (13% of total). In addition, this article reviews the most popularly used models and the most frequently used input factors. Among different models, the logistic regression has been used as the most common method for assessing landslide susceptibility in 28.4% of the articles, and the slope gradient is considered as the most important conditioning factor in landslide occurrence in 94.2% of the articles. Finally, it is concluded that the recent technological developments in the field of remote sensing, computing technologies and Geographic Information Systems (GIS), the increased data availability, and the awareness has arisen among media and recent policy developments are important elements for increasing the research interest in landslide susceptibility.
Pradhan, B, Jung, H-S & Beydoun, G 2018, 'Systems and Sensors in Geoscience Applications.', J. Sensors, vol. 2018, pp. 7242495:1-7242495:1.
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Pradhan, B, Moneir, AAA & Jena, R 2018, 'Sand dune risk assessment in Sabha region, Libya using Landsat 8, MODIS, and Google Earth Engine images', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 1280-1305.
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Globally, sand dunes are a major environmental problem that causes damage to urban areas, transportation, and population. The current study proposes a comprehensive investigation on sand dune risk modeling in Sabha located in the southwestern part of Libya. Data from various sources were collected and prepared in a GIS database. Data from 2016 were used to derive several controlling factors, such as altitude, rainfall, soil texture, wind direction and speed, land cover, and population density. Next, sand dune susceptibility, hazard and vulnerability assessments were performed. Finally, a risk map was produced. Results indicate that land use and soil are the most influential factors affecting the sand dunes in the study area, whereas rainfall is the least significant factor. Results indicate that, southern part has a higher chance of sand dune occurrence than the northern part, whereas the highest risk zone is located in the middle part, where the urban and agricultural lands are present. More than 200 km2 of the study area are under high and very high risk zones. Overall, this study provides an effective tool for assessing sand dune risk in Sabha, which can be useful for land management.
Pradhan, B, Rizeei, H & Abdulle, A 2018, 'Quantitative Assessment for Detection and Monitoring of Coastline Dynamics with Temporal RADARSAT Images', Remote Sensing, vol. 10, no. 11, pp. 1705-1705.
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This study aims to detect coastline changes using temporal synthetic aperture radar (SAR) images for the state of Kelantan, Malaysia. Two active images, namely, RADARSAT-1 captured in 2003 and RADARSAT-2 captured in 2014, were used to monitor such changes. We applied noise removal and edge detection filtering on RADARSAT images for preprocessing to remove salt and pepper distortion. Different segmentation analyses were also applied to the filtered images. Firstly, multiresolution segmentation, maximum spectral difference and chessboard segmentation were performed to separate land pixels from ocean ones. Next, the Taguchi method was used to optimise segmentation parameters. Subsequently, a support vector machine algorithm was applied on the optimised segments to classify shorelines with an accuracy of 98% for both temporal images. Results were validated using a thematic map from the Department of Survey and Mapping of Malaysia. The change detection showed an average difference in the shoreline of 12.5 m between 2003 and 2014. The methods developed in this study demonstrate the ability of active SAR sensors to map and detect shoreline changes, especially during low or high tides in tropical regions where passive sensor imagery is often masked by clouds.
Praveena, SM, Pradhan, B & Aris, AZ 2018, 'Assessment of bioavailability and human health exposure risk to heavy metals in surface soils (Klang district, Malaysia)', Toxin Reviews, vol. 37, no. 3, pp. 196-205.
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In urban area surface soil the heavy metal concentrations followed the order: Pb (76.15 mg/kg) > Fe (12.96 mg/kg) > Cu (11.58 mg/kg) > Al (10.3 mg/kg) > Zn (6.42 mg/kg) > Co (0.21 mg/kg) > Cd (0.18 mg/kg) > Cr (0.07 mg/kg). For the industrial area surface soil, heavy metal concentrations followed the sequence: Pb (55.28 mg/kg) > Al (15.5 mg/kg) > Fe (14.73 mg/kg)> Cu (14.68 mg/kg) > Zn (4.48 mg/kg) > Co (0.26 mg/kg) > Cr (0.11 mg/kg) > Cd (0.11 mg/kg). PCA output showed that the first and second principal components are attributed due to the presence of “urban metals” in the urban areas while third principal component reflects the anthropogenic factor in the industrial areas. Total Cancer Risk values are more than the incremental lifetime (1.0E − 05), showing the likelihood of a cancer threat for adults and children. For non-carcinogenic risks, Hazard Index values <1 one indicating no potential risks.
Qi, Y, Indraratna, B & Vinod, JS 2018, 'Behavior of Steel Furnace Slag, Coal Wash, and Rubber Crumb Mixtures with Special Relevance to Stress–Dilatancy Relation', Journal of Materials in Civil Engineering, vol. 30, no. 11, pp. 04018276-04018276.
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Qi, Y, Indraratna, B, Heitor, A & Vinod, J 2018, 'Effect of Rubber Crumbs on the Cyclic Behaviour of Steel Furnace Slag and Coal Wash Mixtures', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 2.
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Qi, Y, Indraratna, B, Heitor, A & Vinod, JS 2018, 'Effect of Rubber Crumbs on the Cyclic Behavior of Steel Furnace Slag and Coal Wash Mixtures', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 2, pp. 04017107-04017107.
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The practical application of waste materials such as steel furnace slag (SFS) and coal wash (CW) is becoming more prevalent in many geotechnical projects. While adding rubber crumbs (RCs) from recycled tires into mixtures of SFS and CW not only solves the problem of large stockpiles of waste tires, it also can provide an energy-absorbing medium that will reduce vibration and prevent track degradation. Thus, the engineering insight into the effect that rubber crumbs have on the dynamic behavior of SFS + CW + RC mixtures is in urgent demand. In this study the influence that RC contents and confining pressures have on the deformation, resilient modulus, damping ratio, and shear modulus was investigated by cyclic triaxial tests. Test results reveal that with the inclusion of RC, the axial strain, volumetric strain, damping ratio, and energy-absorbing capacity of the SFS + CW + RC mixture increase, while its resilient modulus and shear modulus decrease. Based on these properties, an amount of 10% RC is recommended as an optimal blended mix to be used as railway subballast. A three-dimensional (3D) empirical model of the relationship between the maximum axial strain, volumetric strain, and resilient modulus with RC contents and the effective confining pressure was developed, and the energy-absorbing capacity of these waste mixtures has also been analyzed for practical purposes based on their comprehensive parameters.
Rahmati, O, Naghibi, SA, Shahabi, H, Bui, DT, Pradhan, B, Azareh, A, Rafiei-Sardooi, E, Samani, AN & Melesse, AM 2018, 'Groundwater spring potential modelling: Comprising the capability and robustness of three different modeling approaches', Journal of Hydrology, vol. 565, pp. 248-261.
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© 2018 Elsevier B.V. Sustainable water resources management in arid and semi-arid areas needs robust models, which allow accurate and reliable predictive modeling. This issue has motivated the researchers to develop hybrid models that offer solutions on modelling problems and accurate predictions of groundwater potential zonation. For this purpose, this research aims to investigate the capability and robustness of a novel hybrid model, namely the logistic model tree (LMT) and compares it with state-of-the-art models such as the support vector machine and C4.5 models that locate potential zones for groundwater springs. A spring location dataset consisting of 359 springs was provided by field surveys and national reports and from which three different sample data sets (S1–S3) were randomly prepared (70% for training and 30% for validation). Additionally, 16 spring-related factors were analyzed using regression logistic analysis to find which factors play a significant role in spring occurrence. Twelve significant geo-environmental and morphometric factors were identified and applied in all models. The accuracy of models was evaluated by three different threshold-dependent and –Independent methods including efficiency (E), true skill statistic (TSS), and area under the receiver operating characteristics curve (AUC-ROC) methods. Results showed that the LMT model had the highest accuracy performance for all three validation datasets (Emean = 0.860, TSSmean = 0.718, AUC-ROCmean = 0.904); although a slight sensitivity to change in input data was sometimes observed for this model. Furthermore, the findings showed that relative slope position (RSP) was the most important factor followed by distance from faults and lithology.
Ranjbar-Zahedani, M, Keshavarzi, A, Khabbaz, H & Ball, J 2018, 'Protecting bridge piers against local scour using a flow-diversion structure', Proceedings of the Institution of Civil Engineers - Water Management, vol. 171, no. 5, pp. 271-280.
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Previous studies indicate that local scour is a leading cause of most waterway bridge failures during flood events. Using armouring countermeasures such as riprap and gabions is a conventional way of reducing scour around bridge piers, but is very costly and time consuming. As an alternative, a flow-diversion structure is proposed that has a triangular prismatic shape with dimensions much smaller than the actual pier and should be installed upstream of the pier. To assess its performance, experiments were conducted under clear-water scour conditions. After achieving equilibrium bed conditions, the bed profile was measured and the maximum scour depth and volume of the scour hole were determined for each experimental test. The results indicated that the clear distance between the pier and the countermeasure to achieve the maximum reduction in local scour was 1·5 times the pier diameter. For this condition, the proposed countermeasure reduced the maximum scour depth by 38% and the volume of the scour hole was decreased by around 61%. To determine the influence of the countermeasure on flow field around the pier, three-dimensional velocity components were measured at grid points using a micro-acoustic Doppler velocity meter. Analysis of the results indicated that the proposed structure could change both the magnitude and direction of the velocity components upstream of the pier and consequently induce a significant reduction in local scour depth and volume around the pier.
Rao, P, Chen, Q, Nimbalkar, S & Liu, Y 2018, 'Effect of water and salinity on soil behaviour under lightning', Environmental Geotechnics, vol. 5, no. 1, pp. 56-62.
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The east coast of China, in particular Shanghai, is frequently exposed to lightning, and the resulting annual loss approaches US$30 million. All kinds of protection devices transfer the lightning current and the energy into the ground. In this study, the characteristics of the typical soft soil in Shanghai with different values of water content and salinity under the action of lightning shock have been analysed by an impulse current generator and a self-designed test equipment. The test results show that the current waveform from the impact of lightning in soils has a steep rise and a slow fall. At the same lightning intensity, higher water content or salinity leads to (a) shorter peak time, (b) larger peak current waveform, (c) quicker release speed and (d) larger lightning impulse response. The test results are valuable in guiding the design and the reformation of lightning protection and grounding systems.
Rizeei, HM, Azeez, OS, Pradhan, B & Khamees, HH 2018, 'Assessment of groundwater nitrate contamination hazard in a semi-arid region by using integrated parametric IPNOA and data-driven logistic regression models', Environmental Monitoring and Assessment, vol. 190, no. 11.
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Groundwater hazard assessments involve many activities dealing with the impacts of pollution on groundwater, such as human health studies and environment modelling. Nitrate contamination is considered a hazard to human health, environment and ecosystem. In groundwater management, the hazard should be assessed before any action can be taken, particularly for groundwater pollution and water quality. Thus, pollution due to the presence of nitrate poses considerable hazard to drinking water, and excessive nutrient loads deteriorate the ecosystem. The parametric IPNOA model is one of the well-known methods used for evaluating nitrate content. However, it cannot predict the effect of soil and land use/land cover (LULC) types on calculations relying on parametric well samples. Therefore, in this study, the parametric model was trained and integrated with the multivariate data-driven model with different levels of information to assess groundwater nitrate contamination in Saladin, Iraq. The IPNOA model was developed with 185 different well samples and contributing parameters. Then, the IPNOA model was integrated with the logistic regression (LR) model to predict the nitrate contamination levels. Geographic information system techniques were also used to assess the spatial prediction of nitrate contamination. High-resolution SPOT-5 satellite images with 5 m spatial resolution were processed by object-based image analysis and support vector machine algorithm to extract LULC. Mapping of potential areas of nitrate contamination was examined using receiver operating characteristic assessment. Results indicated that the optimised LR-IPNOA model was more accurate in determining and analysing the nitrate hazard concentration than the standalone IPNOA model. This method can be easily replicated in other areas that have similar climatic condition. Therefore, stakeholders in planning and environmental decision makers could benefit immensely from the proposed method of this research...
Rizeei, HM, Pradhan, B & Saharkhiz, MA 2018, 'Surface runoff prediction regarding LULC and climate dynamics using coupled LTM, optimized ARIMA, and GIS-based SCS-CN models in tropical region', Arabian Journal of Geosciences, vol. 11, no. 3.
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© 2018, Saudi Society for Geosciences. The effects of climate and land use/land cover (LULC) dynamics have directly affected the surface runoff and flooding events. Hence, current study proposes a full-packaged model to monitor the changes in surface runoff in addition to forecast of the future surface runoff based on LULC and precipitation variations. On one hand, six different LULC classes were extracted from Spot-5 satellite image. Conjointly, land transformation model (LTM) was used to detect the LULC pixel changes from 2000 to 2010 as well as predict the 2020 ones. On the other hand, the time series-autoregressive integrated moving average (ARIMA) model was applied to forecast the amount of rainfall in 2020. The ARIMA parameters were calibrated and fitted by latest Taguchi method. To simulate the maximum probable surface runoff, distributed soil conservation service-curve number (SCS-CN) model was applied. The comparison results showed that firstly, deforestation and urbanization have been occurred upon the given time, and they are anticipated to increase as well. Secondly, the amount of rainfall has non-stationary declined since 2000 till 2015 and this trend is estimated to continue by 2020. Thirdly, due to damaging changes in LULC, the surface runoff has been also increased till 2010 and it is forecasted to gradually exceed by 2020. Generally, model calibrations and accuracy assessments have been indicated, using distributed-GIS-based SCS-CN model in combination with the LTM and ARIMA models are an efficient and reliable approach for detecting, monitoring, and forecasting surface runoff.
Rizeei, HM, Shafri, HZM, Mohamoud, MA, Pradhan, B & Kalantar, B 2018, 'Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis', Journal of Sensors, vol. 2018, pp. 1-13.
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The current study proposes a new method for oil palm age estimation and counting from Worldview-3 satellite image and light detection and range (LiDAR) airborne imagery. A support vector machine algorithm (SVM) of object-based image analysis (OBIA) was implemented for oil palm counting. The sensitivity analysis was conducted on four SVM kernel types with associated segmentation parameters to obtain the optimal crown coverage delineation. Extracting tree’s crown was integrated with height model and multiregression methods to accurately estimate the age of trees. The multiregression model with multikernel sizes was examined to achieve the most optimized model for age estimation. Applied models were trained and examined over five different oil palm plantations. The results of oil palm counting had an overall accuracy of 98.80%, while the overall accuracy of age estimation showed 84.91%, over all blocks. The relationship between tree’s height and age was significant which supports the polynomial regression function (PRF) model with a 3×3 kernel size for under 10–12-year-old oil palm trees, while exponential regression function (ERF) is more fitted for older trees (i.e., 22 years old). Overall, recent remote sensing dataset and machine learning techniques are useful in monitoring and detecting oil palm plantation to maximize productivity.
Robson, EN, Wijayaratna, KP & Dixit, VV 2018, 'A review of computable general equilibrium models for transport and their applications in appraisal', Transportation Research Part A: Policy and Practice, vol. 116, pp. 31-53.
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© 2018 Elsevier Ltd 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, where benefits are primarily measured from the change in consumer surplus in the transport market. However, these benefits will only reflect maximum social welfare if markets operate perfectly competitively and without any market failures. 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 impact 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. Aside from their traditional role estimating changes in macroeconomic variables, CGE models can provide a measure of welfare that guarantees no double counting and accounts for nth order effects. This paper reviews the full range of CGE models that have been applied to transport issues and discusses their role in transport appraisal. CGE models for transport have been developed in urban, regional and environmental economics as well as other fields, and each field has applied its own theory, assumptions and practices to represent the relationships between transport and the economy relevant to the field. This paper also discusses the general role of CGE modelling in transport appraisal, as well as theoretical and practical concerns regarding CGE modelling practice.
Saeidian, B, Mesgari, M, Pradhan, B & Ghodousi, M 2018, 'Optimized Location-Allocation of Earthquake Relief Centers Using PSO and ACO, Complemented by GIS, Clustering, and TOPSIS', ISPRS International Journal of Geo-Information, vol. 7, no. 8, pp. 292-292.
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After an earthquake, it is required to establish temporary relief centers in order to help the victims. Selection of proper sites for these centers has a significant effect on the processes of urban disaster management. In this paper, the location and allocation of relief centers in district 1 of Tehran are carried out using Geospatial Information System (GIS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision model, a simple clustering method and the two meta-heuristic algorithms of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). First, using TOPSIS, the proposed clustering method and GIS analysis tools, sites satisfying initial conditions with adequate distribution in the area are chosen. Then, the selection of proper centers and the allocation of parcels to them are modelled as a location/allocation problem, which is solved using the meta-heuristic optimization algorithms. Also, in this research, PSO and ACO are compared using different criteria. The implementation results show the general adequacy of TOPSIS, the clustering method, and the optimization algorithms. This is an appropriate approach to solve such complex site selection and allocation problems. In view of the assessment results, the PSO finds better answers, converges faster, and shows higher consistency than the ACO.
Sajedi-Hosseini, F, Malekian, A, Choubin, B, Rahmati, O, Cipullo, S, Coulon, F & Pradhan, B 2018, 'A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination', Science of The Total Environment, vol. 644, pp. 954-962.
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© 2018 Elsevier B.V. This study aimed to develop a novel framework for risk assessment of nitrate groundwater contamination by integrating chemical and statistical analysis for an arid region. A standard method was applied for assessing the vulnerability of groundwater to nitrate pollution in Lenjanat plain, Iran. Nitrate concentration were collected from 102 wells of the plain and used to provide pollution occurrence and probability maps. Three machine learning models including boosted regression trees (BRT), multivariate discriminant analysis (MDA), and support vector machine (SVM) were used for the probability of groundwater pollution occurrence. Afterwards, an ensemble modeling approach was applied for production of the groundwater pollution occurrence probability map. Validation of the models was carried out using area under the receiver operating characteristic curve method (AUC); values above 80% were selected to contribute in ensembling process. Results indicated that accuracy for the three models ranged from 0.81 to 0.87, therefore all models were considered for ensemble modeling process. The resultant groundwater pollution risk (produced by vulnerability, pollution, and probability maps) indicated that the central regions of the plain have high and very high risk of nitrate pollution further confirmed by the exiting landuse map. The findings may provide very helpful information in decision making for groundwater pollution risk management especially in semi-arid regions.
Sameen, MI, Pradhan, B & Aziz, OS 2018, 'Classification of Very High Resolution Aerial Photos Using Spectral-Spatial Convolutional Neural Networks', Journal of Sensors, vol. 2018, pp. 1-12.
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Classification of aerial photographs relying purely on spectral content is a challenging topic in remote sensing. A convolutional neural network (CNN) was developed to classify aerial photographs into seven land cover classes such as building, grassland, dense vegetation, waterbody, barren land, road, and shadow. The classifier utilized spectral and spatial contents of the data to maximize the accuracy of the classification process. CNN was trained from scratch with manually created ground truth samples. The architecture of the network comprised of a single convolution layer of 32 filters and a kernel size of 3 × 3, pooling size of 2 × 2, batch normalization, dropout, and a dense layer with Softmax activation. The design of the architecture and its hyperparameters were selected via sensitivity analysis and validation accuracy. The results showed that the proposed model could be effective for classifying the aerial photographs. The overall accuracy and Kappa coefficient of the best model were 0.973 and 0.967, respectively. In addition, the sensitivity analysis suggested that the use of dropout and batch normalization technique in CNN is essential to improve the generalization performance of the model. The CNN model without the techniques above achieved the worse performance, with an overall accuracy and Kappa of 0.932 and 0.922, respectively. This research shows that CNN-based models are robust for land cover classification using aerial photographs. However, the architecture and hyperparameters of these models should be carefully selected and optimized.
Shi, X, Zhu, S, Ni, YQ & Li, J 2018, 'Vibration suppression in high-speed trains with negative stiffness dampers', Smart Structures and Systems, vol. 21, no. 5, pp. 653-668.
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This work proposes and investigates re-centering negative stiffness dampers (NSDs) for vibration suppression in high-speed trains. The merit of the negative stiffness feature is demonstrated by active controllers on a high-speed train. This merit inspires the replacement of active controllers with re-centering NSDs, which are more reliable and robust than active controllers. The proposed damper design consists of a passive magnetic negative stiffness spring and a semi-active positioning shaft for re-centering function. The former produces negative stiffness control forces, and the latter prevents the amplification of quasi-static spring deflection. Numerical investigations verify that the proposed re-centering NSD can improve ride comfort significantly without amplifying spring deflection.
Shirzadi, A, Soliamani, K, Habibnejhad, M, Kavian, A, Chapi, K, Shahabi, H, Chen, W, Khosravi, K, Thai Pham, B, Pradhan, B, Ahmad, A, Bin Ahmad, B & Tien Bui, D 2018, 'Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping', Sensors, vol. 18, no. 11, pp. 3777-3777.
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The main objective of this research was to introduce a novel machine learning algorithm of alternating decision tree (ADTree) based on the multiboost (MB), bagging (BA), rotation forest (RF) and random subspace (RS) ensemble algorithms under two scenarios of different sample sizes and raster resolutions for spatial prediction of shallow landslides around Bijar City, Kurdistan Province, Iran. The evaluation of modeling process was checked by some statistical measures and area under the receiver operating characteristic curve (AUROC). Results show that, for combination of sample sizes of 60%/40% and 70%/30% with a raster resolution of 10 m, the RS model, while, for 80%/20% and 90%/10% with a raster resolution of 20 m, the MB model obtained a high goodness-of-fit and prediction accuracy. The RS-ADTree and MB-ADTree ensemble models outperformed the ADTree model in two scenarios. Overall, MB-ADTree in sample size of 80%/20% with a resolution of 20 m (area under the curve (AUC) = 0.942) and sample size of 60%/40% with a resolution of 10 m (AUC = 0.845) had the highest and lowest prediction accuracy, respectively. The findings confirm that the newly proposed models are very promising alternative tools to assist planners and decision makers in the task of managing landslide prone areas.
Siahaan, F, Indraratna, B, Ngo, NT, Rujikiatkamjorn, C & Heitor, A 2018, 'Influence of Particle Gradation and Shape on the Performance of Stone Columns in Soft Clay', Geotechnical Testing Journal, vol. 41, no. 6, pp. 1076-1091.
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Abstract A stone column typically consists of particles whose influence has largely been overlooked in design practice in terms of stress transfer, pattern of deformation, and intrusion of fines (clogging). This article presents an experimental study on the load-deformation behavior of a model stone column installed in soft clay with a particular emphasis on the influence of particle gradation and shape under undrained loading. The results show that particle gradation and shape have a significant influence on the load-deformation behavior and the extent of fines intrusion into the stone columns. Relatively well-graded particle sizes favor the development of higher peak shear stresses accompanied by lateral bulging, whereas more uniform grading results in the development of distinct shear planes and smaller peak shear stresses. Deformed columns were also examined using computed tomography, and the porosity profiles at the end of the test were determined using micrographs. Maximum porosity typically occurred in the zone of extreme lateral deformation, with the results suggesting that the extent of fines intrusion was influenced by particle morphology.
Singh, SK, Taylor, RW, Rahman, MM & Pradhan, B 2018, 'Developing robust arsenic awareness prediction models using machine learning algorithms', Journal of Environmental Management, vol. 211, pp. 125-137.
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© 2018 Elsevier Ltd Arsenic awareness plays a vital role in ensuring the sustainability of arsenic mitigation technologies. Thus far, however, few studies have dealt with the sustainability of such technologies and its associated socioeconomic dimensions. As a result, arsenic awareness prediction has not yet been fully conceptualized. Accordingly, this study evaluated arsenic awareness among arsenic-affected communities in rural India, using a structured questionnaire to record socioeconomic, demographic, and other sociobehavioral factors with an eye to assessing their association with and influence on arsenic awareness. First a logistic regression model was applied and its results compared with those produced by six state-of-the-art machine-learning algorithms (Support Vector Machine [SVM], Kernel-SVM, Decision Tree [DT], k-Nearest Neighbor [k-NN], Naïve Bayes [NB], and Random Forests [RF]) as measured by their accuracy at predicting arsenic awareness. Most (63%) of the surveyed population was found to be arsenic-aware. Significant arsenic awareness predictors were divided into three types: (1) socioeconomic factors: caste, education level, and occupation; (2) water and sanitation behavior factors: number of family members involved in water collection, distance traveled and time spent for water collection, places for defecation, and materials used for handwashing after defecation; and (3) social capital and trust factors: presence of anganwadi and people's trust in other community members, NGOs, and private agencies. Moreover, individuals' having higher social network positively contributed to arsenic awareness in the communities. Results indicated that both the SVM and the RF algorithms outperformed at overall prediction of arsenic awareness—a nonlinear classification problem. Lower-caste, less educated, and unemployed members of the population were found to be the most vulnerable, requiring immediate arsenic mitigation. To this end, local social inst...
Stapelberg, NJC, Pratt, R, Neumann, DL, Shum, DHK, Brandis, S, Muthukkumarasamy, V, Stantic, B, Blumenstein, M & Headrick, JP 2018, 'From feedback loop transitions to biomarkers in the psycho-immune-neuroendocrine network: Detecting the critical transition from health to major depression', Neuroscience & Biobehavioral Reviews, vol. 90, pp. 1-15.
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Stender, M, Tiedemann, M, Hoffmann, N & Oberst, S 2018, 'Impact of an irregular friction formulation on dynamics of a minimal model for brake squeal', Mechanical Systems and Signal Processing, vol. 107, pp. 439-451.
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Friction-induced vibrations are of major concern in the design of reliable, efficient and comfortable technical systems. Well-known examples for systems susceptible to self-excitation can be found in fluid structure interaction, disk brake squeal, rotor dynamics, hip implants noise and many more. While damping elements and amplitude reduction are well-understood in linear systems, nonlinear systems and especially self-excited dynamics still constitute a challenge for damping element design. Additionally, complex dynamical systems exhibit deterministic chaotic cores which add severe sensitivity to initial conditions to the system response. Especially the complex friction interface dynamics remain a challenging task for measurements and modeling. Today, mostly simple and regular friction models are investigated in the field of self-excited brake system vibrations. This work aims at investigating the effect of high-frequency irregular interface dynamics on the nonlinear dynamical response of a self-excited structure. Special focus is put on the characterization of the system response time series.
A low-dimensional minimal model is studied which features self-excitation, gyroscopic effects and friction-induced damping. Additionally, the employed friction formulation exhibits temperature as inner variable and superposed chaotic fluctuations governed by a Lorenz attractor. The time scale of the irregular fluctuations is chosen one order smaller than the overall system dynamics. The influence of those fluctuations on the structural response is studied in various ways, i.e. in time domain and by means of recurrence analysis. The separate time scales are studied in detail and regimes of dynamic interactions are identified. The results of the irregular friction formulation indicate dynamic interactions on multiple time scales, which trigger larger vibration amplitudes as compared to regular friction formulations conventionally studied in the field of friction-induced vibr...
Stewart, RA, Nguyen, K, Beal, C, Zhang, H, Sahin, O, Bertone, E, Vieira, AS, Castelletti, A, Cominola, A, Giuliani, M, Giurco, D, Blumenstein, M, Turner, A, Liu, A, Kenway, S, Savić, DA, Makropoulos, C & Kossieris, P 2018, 'Integrated intelligent water-energy metering systems and informatics: Visioning a digital multi-utility service provider', Environmental Modelling & Software, vol. 105, pp. 94-117.
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© 2018 Elsevier Ltd Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. Providers that can install low-cost integrative systems will reap the benefits of derived operational synergies and access to mass markets not bounded by historical city, state or country limits. This paper provides a vision of the required transformative process and features of an integrated multi-utility service provider covering the system architecture, opportunities and benefits, impediments and strategies, and business opportunities. The heart of the paper is focused on demonstrating data modelling processes and informatics opportunities for contemporaneously collected demand data, through illustrative examples and four informative water-energy nexus case studies. Finally, the paper provides an overview of the transformative R&D priorities to realise the vision.
Sutton, GJ, Zeng, J, Liu, RP, Ni, W, Nguyen, DN, Jayawickrama, BA, Huang, X, Abolhasan, M & Zhang, Z 2018, 'Enabling Ultra-Reliable and Low-Latency Communications through Unlicensed Spectrum', IEEE Network, vol. 32, no. 2, pp. 70-77.
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© 2018 IEEE. In this article, we aim to address the question of how to exploit the unlicensed spectrum to achieve URLLC. Potential URLLC PHY mechanisms are reviewed and then compared via simulations to demonstrate their potential benefits to URLLC. Although a number of important PHY techniques help with URLLC, the PHY layer exhibits an intrinsic trade-off between latency and reliability, posed by limited and unstable wireless channels. We then explore MAC mechanisms and discuss multi-channel strategies for achieving low-latency LTE unlicensed band access. We demonstrate, via simulations, that the periods without access to the unlicensed band can be substantially reduced by maintaining channel access processes on multiple unlicensed channels, choosing the channels intelligently, and implementing RTS/CTS.
Tai, P, Indraratna, B & Rujikiatkamjorn, C 2018, 'Experimental simulation and mathematical modelling of clogging in stone column', Canadian Geotechnical Journal, vol. 55, no. 3, pp. 427-436.
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In this paper, time-dependent clogging is studied considering a unit cell consisting of a single stone column interacting with the surrounding soft clay. Clogging is assessed quantitatively and the corresponding void space of the column is determined using computed tomography. It is observed that the extent of clogging is substantial in the upper part of the column, but diminishes rapidly with depth. The soil properties in the clogged zone are determined indirectly through additional tests of clay–aggregates mixtures with various clay fractions. An equal strain consolidation model based on the principle of unit cell analysis is developed to capture both the initial and time-dependent clogging. The model accounts for a reduction in permeability and an increase in compressibility of the column. This current model, as expected, offers identical results to some previous studies if clogging is ignored, while the comparison with other selected models demonstrates the influence that clogging of the stone column can have on the consolidation of the surrounding soil. Furthermore, load–settlement predictions from the proposed “equal strain” model are also compared with the consolidation response of a previously developed “free strain” model.
Tang, G, Huang, J, Sheng, D & Sloan, SW 2018, 'Stability analysis of unsaturated soil slopes under random rainfall patterns', Engineering Geology, vol. 245, pp. 322-332.
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The significance of rainfall pattern in the assessment of rainfall-induced landslide is widely recognized. However, much work so far is limited to several simplified typical rainfall patterns. In this study, the random rainfall pattern (RRP) is introduced and generated using random cascade model based on the rainfall event characterized by average rainfall intensity and duration. The stability of unsaturated slope considering RRPs is studied from three perspectives: deterministic analysis by means of safety factor under different generated RRPs, probabilistic analysis through conditional failure probability considering the diversity of generated RRPs based on Monte Carlo method and risk assessment analysis by introducing annual failure probability (AFP) considering also the occurrence frequencies of rainfall events. Three typical rainfall patterns are introduced for comparison analysis. The results show that slope stability is sensitive to the RRP and is strongly depend on the temporal distribution of rainfall intensity in RRP. High likelihood of slope failure may occur considering the variety of RRPs even though the slope is in a stable state in terms of deterministic analysis. The AFP considering RRPs increases rapidly with increasing rainfall duration and is significantly different from those under typical rainfall patterns. The findings lead to the conclusion that RRPs should be considered in the estimation of unsaturated slope stability.
Tien Bui, D, Shahabi, H, Shirzadi, A, Chapi, K, Pradhan, B, Chen, W, Khosravi, K, Panahi, M, Bin Ahmad, B & Saro, L 2018, 'Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms', Sensors, vol. 18, no. 8, pp. 2464-2464.
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In this study, land subsidence susceptibility was assessed for a study area in South Korea by using four machine learning models including Bayesian Logistic Regression (BLR), Support Vector Machine (SVM), Logistic Model Tree (LMT) and Alternate Decision Tree (ADTree). Eight conditioning factors were distinguished as the most important affecting factors on land subsidence of Jeong-am area, including slope angle, distance to drift, drift density, geology, distance to lineament, lineament density, land use and rock-mass rating (RMR) were applied to modelling. About 24 previously occurred land subsidence were surveyed and used as training dataset (70% of data) and validation dataset (30% of data) in the modelling process. Each studied model generated a land subsidence susceptibility map (LSSM). The maps were verified using several appropriate tools including statistical indices, the area under the receiver operating characteristic (AUROC) and success rate (SR) and prediction rate (PR) curves. The results of this study indicated that the BLR model produced LSSM with higher acceptable accuracy and reliability compared to the other applied models, even though the other models also had reasonable results.
Tong, C-X, Burton, GJ, Zhang, S & Sheng, D 2018, 'A simple particle-size distribution model for granular materials', Canadian Geotechnical Journal, vol. 55, no. 2, pp. 246-257.
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Particle-size distribution (PSD) is a fundamental soil property that plays an important role in soil classification and soil hydromechanical behaviour. A continuous mathematical model representing the PSD curve facilitates the quantification of particle breakage, which often takes place when granular soils are compressed or sheared. This paper proposes a simple and continuous PSD model for granular soils involving particle breakage. The model has two parameters and is able to represent different types of continuous PSD curves. It is found that one model parameter is closely related to the coefficient of nonuniformity (Cu) and the coefficient of curvature (Cc), while the other represents a characteristic particle diameter. A database of 53 granular soils with 154 varying PSD curves is analyzed to evaluate the performance of the proposed PSD model, as well as that of three other PSD models in the literature. The results show that the proposed model has improved overall performance and captures the typical trends in PSD evolution during particle breakage. In addition, the proposed model is also used for assessing the internal stability of 27 widely graded soils.
Walker, RTR & Indraratna, B 2018, 'Moving Loads on a Viscoelastic Foundation with Special Reference to Railway Transition Zones', International Journal of Geomechanics, vol. 18, no. 11, pp. 04018145-04018145.
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Wang, Q, Ye, X, Wang, S, Sloan, SW & Sheng, D 2018, 'Use of photo-based 3D photogrammetry in analysing the results of laboratory pressure grouting tests', Acta Geotechnica, vol. 13, no. 5, pp. 1129-1140.
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This paper presents a non-destructive, low-cost, photo-based, 3D reconstruction technique for characterizing geo-materials with irregular shapes of a relatively large size. After being validated against two traditional volume measurement methods, namely the vernier caliper method and the fluid displacement method for regular and irregular shapes, respectively, 3D photogrammetry was used to analyse the grout bulbs formed in laboratory pressure grouting tests. The reconstructed 3D mesh model of the sample provides accurate and detailed 3D vertex data, which allowed the volume, densification efficiency and bleeding behaviour of the grout bulbs to be analysed. Comparing the bulb section views at different grouting pressures also offers an intuitive observation of the grout development and propagation process. Moreover, the 3D vertex data and surface area included in the model are of great importance in validating numerical predictions of the pressure grouting process and analysing the interface shear resistance of grouted soil nails or anchors. Compared to existing approaches, the new 3D photogrammetry method possesses several key advantages: (a) it does not require expensive, specialized equipment; (b) samples are not destroyed or modified during testing; (c) it allows to reconstruct objects of various scales and (d) the software is public domain. Therefore, the adoption of this 3D photogrammetry method will facilitate research in the pressure grouting process and can be extended to other problems in geotechnical engineering.
Wang, S, Wu, W, Peng, C, He, X & Cui, D 2018, 'Numerical integration and FE implementation of a hypoplastic constitutive model', Acta Geotechnica, vol. 13, no. 6, pp. 1265-1281.
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Wang, S, Wu, W, Yin, Z, Peng, C & He, X 2018, 'Modelling the time‐dependent behaviour of granular material with hypoplasticity', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 12, pp. 1331-1345.
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SummaryThis paper presents a constitutive model for time‐dependent behaviour of granular material. The model consists of 2 parts representing the inviscid and viscous behaviour of granular materials. The inviscid part is a rate‐independent hypoplastic constitutive model. The viscous part is represented by a rheological model, which contains a high‐order term denoting the strain acceleration. The proposed model is validated by simulating some element tests on granular soils. Our model is able to model not only the non‐isotach behaviour but also the 3 creep stages, namely, primary, secondary, and tertiary creep, in a unified way.
Xu, KJ, Liu, MD, Indraratna, B & Horpibulsuk, S 2018, 'Explicit stress–strain equations for modeling frictional materials', Marine Georesources & Geotechnology, vol. 36, no. 6, pp. 722-734.
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Xu, R & Fatahi, B 2018, 'Geosynthetic-reinforced cushioned piles with controlled rocking for seismic safeguarding', Geosynthetics International, vol. 25, no. 6, pp. 561-581.
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In this study, a cushioned pile foundation reinforced with geosynthetics is proposed to protect buildings and foundations from seismic energy. This composite foundation utilises piles to control foundation settlement while the geosynthetic-reinforced cushion modifies the dynamic structural characteristics and the load transfer mechanism. The seismic performance of this proposed foundation system is evaluated numerically using FLAC3D software. A fully coupled nonlinear dynamic analysis was conducted in the time domain. The variation of shear modulus corresponding to shear strains in the soil is used to simulate the dynamic behaviour of the soil, while the influence of the plasticity index is also captured. The soil-geosynthetic interface utilises the Mohr-Coulomb failure criterion to capture possible sliding and pull-out of the reinforcement layers. 3D numerical predictions of the tensile forces mobilised in the geosynthetic layers, the shear forces, the lateral deformations and maximum and residual inter-storey drifts in the building are presented and discussed in this paper, as well as how the shear forces and bending moments develop in the piles, and the lateral pile displacements. The results indicate that the proposed geosynthetic-reinforced cushioned pile foundation can provide design engineers with an alternative solution for safeguarding buildings constructed on soft soils in earthquake-prone regions.
Xu, R & Fatahi, B 2018, 'Influence of geotextile arrangement on seismic performance of mid-rise buildings subjected to MCE shaking', Geotextiles and Geomembranes, vol. 46, no. 4, pp. 511-528.
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Geotextile layers make it possible to construct mid-rise buildings sitting on shallow foundations in unfavourablesoil conditions; this study investigates how the arrangement of geotextiles affects the seismic performance ofmid-rise buildings under Maximum Considered Earthquake (MCE) shaking. The geotextile arrangement con-sidered here includes the stiffness (5000 kN/m–12000 kN/m), the length with respect to width of the foun-dation (B) (1B–4B), the number of geotextile layers (1–7 layers), and their spacing (250 mm–1000 mm).FLAC3D is used for the numerical simulation and to carry out nonlinear dynamic analysis in the time domain,and an inelastic constitutive model is used to simulate the behaviour of the structure and the geotextile layersunder seismic loads. Variations in the shear modulus of soil and the corresponding damping ratio with cyclicshear strain are considered using a hysteretic damping algorithm to model the reasonable dissipation of energyin the soil. The interface between the foundation and ground surface, including the material and geometricalnonlinearities, are used to capture any possible slide and uplift in the foundations. The results are presented withregard to the geotextile arrangement considered, and include the tensile force mobilised in the geotextile layers,the response spectra at the bedrock and ground surface, the shear force developed in the structure, the maximumrocking angle of the foundation, permanent foundation settlement, maximum lateral displacement and themaximum and residual inter-storey drifts. The results show that the geotextile layers close to the edges of thefoundation sustained most of the stress induced by foundation rocking, and the geotextile arrangement has asignificant influence on the seismic response of mid-rise buildings. Thus, to satisfy the seismic performance ofbuildings and to optimise the design of foundations reinforced with geotextiles, the stiffness, length, number andspacing of the geotextile layers sh...
Ye, K & Ji, J 2018, 'Natural Frequency Analysis of a Spar-Type Offshore Wind Turbine Tower With End Mass Components', Journal of Offshore Mechanics and Arctic Engineering, vol. 140, no. 6, pp. 1-5.
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Abstract Different from the fixed-based wind turbines, the floating type wind turbines are regarded as under a free–free end operating condition. The tower structure of a floating offshore wind turbine is an integrated part connecting the nacelle and support platform. An analytic solution is presented in this technical brief for the free-vibration of the tower structure of a spar-type offshore wind turbine. The tower structure is modeled as a free–free beam based on Euler–Bernoulli beam-column theory. The platform and the nacelle are considered as two large mass components connected by torsion springs at two tower ends with different stiffness. The effects of system parameters on the natural frequencies are investigated under a range of variables, including the tower structure parameters, platform and nacelle parameters, and the connection types. Nonlinear relationships between those variables and the natural frequency of the tower structure are numerically found and some design issues are discussed for the spar-type floating wind turbines.
Ye, K & Ji, J 2018, 'The effect of the rotor adjustment on the vibration behaviour of the drive-train system for a 5 MW direct-drive wind turbine', Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 232, no. 17, pp. 3027-3044.
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Direct-drive wind turbines, different from the standard geared wind turbines, widely use a direct-drive permanent-magnet generator to avoid the gearbox failures. In the absence of a gearbox in the drive-train system, the direct-drive generator operates at low rotating speeds. Thus direct-drive wind turbines require a larger sized generator (higher weight) to transfer the kinetic energy into electrical energy. The inherent unbalanced magnetic pull force of the generator can have impact on the vibration behaviour of the drive-train system. This paper studies the effect of rotor position and weight adjustment on the vibration behaviour of the drive-train system within a 5 MW direct-drive wind turbine by considering the unbalanced magnetic pull force. The adjustment of rotor position and weight changes the location of the centre of gravity of the drive-train system. The drive-train system which consists of the main shaft, rotor, hub and blades is modelled as a four degree-of-freedom nonlinear system. Both rotor displacement and bearing forces are obtained for a wide range of rotor position and weight under different rotating speeds. The obtained results would provide useful information on the optimized rotor position and mass ratio to improve the performance of the drive-train system.
Yin, S, Ji, J, Deng, S & Wen, G 2018, 'Neimark-Sacker Bifurcations Near Degenerate Grazing Point in a Two Degree-of-Freedom Impact Oscillator', Journal of Computational and Nonlinear Dynamics, vol. 13, no. 11.
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Saddle-node or period-doubling bifurcations of the near-grazing impact periodic motions have been extensively studied in the impact oscillators, but the near-grazing Neimark-Sacker bifurcations have not been discussed yet. For the first time, this paper uncovers the novel dynamic behavior of Neimark-Sacker bifurcations, which can appear in a small neighborhood of the degenerate grazing point in a two degree-of-freedom impact oscillator. The higher order discontinuity mapping technique is used to determine the degenerate grazing point. Then, shooting method is applied to obtain the one-parameter continuation of the elementary impact periodic motion near degenerate grazing point and the peculiar phenomena of Neimark-Sacker bifurcations are revealed consequently. A two-parameter continuation is presented to illustrate the relationship between the observed Neimark-Sacker bifurcations and degenerate grazing point. New features that differ from the reported situations in literature can be found. Finally, the observed Neimark-Sacker bifurcation is verified by checking the existence and stability conditions in line with the generic theory of Neimark-Sacker bifurcation. The unstable bifurcating quasi-periodic motion is numerically demonstrated on the Poincaré section.
Yu, J, Ji, J, Miao, Z & Zhou, J 2018, 'Formation control with collision avoidance for uncertain networked Lagrangian systems via adaptive gain techniques', IET Control Theory & Applications, vol. 12, no. 10, pp. 1393-1401.
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© 2018 The Institution of Engineering and Technology. All rights reserved. This study addresses the problem of formation control with collision avoidance for networked Lagrangian systems with uncertain parameters interacting on directed network communication topologies. Two adaptive formation control strategies with collision avoidance are proposed by making use of adaptive gain techniques for both cases of with and without a dynamic leader. The main objective of the proposed control strategies is to dispatch a group of agents to maintain a desired geometric pattern, while still guarantee collision avoidance at any time, and eventually to achieve velocity matching. A distinctive feature of the developed adaptive gain is to adapt itself duly based on both the network communication topology and collision avoidance constraints, so it is feasible to be implemented in practice. Some general criteria are derived to guarantee that the desired formation with collision avoidance for the networked Lagrangian systems can be achieved. Finally, numerical simulations are given to show the performance of the proposed control methodologies.
Yu, Y, Li, Y, Li, J, Gu, X & Royel, S 2018, 'Nonlinear Characterization of the MRE Isolator Using Binary-Coded Discrete CSO and ELM', International Journal of Structural Stability and Dynamics, vol. 18, no. 08, pp. 1840007-1840007.
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Magnetorheological elastomer (MRE) isolator has been proved as a promising semi-active control device for structural vibration control. For its engineering application, developing an accurate and robust model is definitely necessary and also a challenging task. Most of the present models, belonging to parametric models, need to identify various model parameters and sometimes are not capable of perfectly capturing the unique characteristics of the device. In this work, a novel nonparametric model is proposed to characterize the inherent dynamics of the MRE isolator with the features of hysteresis and nonlinearity. Initially, dynamic tests are conducted to evaluate the performance of the isolator under various loading conditions, including harmonic, random, and seismic excitations. Then, on the basis of the captured experimental results, a hybrid learning method is designed to forecast the nonlinear responses of the device with known external inputs. In this method, a type of single hidden layer feed-forward network, called extreme learning machine (ELM), is developed to forecast the nonlinear responses (shear force) of the device with captured velocity, displacement, and current level. To obtain optimal performance of the developed model, an improved binary-coded discrete cat swarm optimization (BCDCSO) method is adopted to select optimal inputs and neuron number in the hidden layer for the network development. The performance of the proposed method is verified through the comparison between experimental results and model predictions. Due to the noise influence in the practical condition, the robustness of the proposed method is also validated via adding noise disturbance into the supplying currents. The results show that the proposed method outperforms the standard ELM in terms of characterization of the MRE isolator, even though the captured responses are polluted with external measurement noises.
Zhang, C-C, Zhu, H-H, Shi, B & Fatahi, B 2018, 'A long term evaluation of circular mat foundations on clay deposits using fractional derivatives', Computers and Geotechnics, vol. 94, pp. 72-82.
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© 2017 Elsevier Ltd This study proposes to use fractional derivatives to evaluate the long term performance of circular mat foundations overlying clays and also predict the associated ground settlement. Closed form solutions for the deflection and bending moment of foundations and the subsequent reaction of subgrade are obtained with the Mittag–Leffler function. Numerical examples are used to determine how the fractional order affects the time dependent properties of the foundation and ground settlement, and to simulate the case history of a large standpipe constructed over Tertiary sediments. New insights into design and prediction of shallow foundations and ground settlement are also discussed.
Zhang, H & Ji, J 2018, 'Group synchronization of coupled harmonic oscillators without velocity measurements', Nonlinear Dynamics, vol. 91, no. 4, pp. 2773-2788.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. This paper investigates the group synchronization of coupled harmonic oscillators over a directed network topology in the absence of velocity measurements. Each harmonic oscillator can only obtain the sampled position states relative to its neighbors at a series of discrete-time instants. Two distributed control protocols are proposed based on the impulsive control and sampled-data control strategies. Theoretical analysis shows that the desired sampling period is determined by the position gain and the eigenvalues of the Laplacian matrix associated with the network topology. Some necessary and sufficient conditions for group synchronization are analytically established in virtue of matrix analysis, graph theory and polynomial Schur stability theory. Different to the synchronization criteria presented in the form of linear matrix inequality or general inequality, which may need to be verified, this paper explicitly gives the ranges for all feasible sampling periods. A significant feature of the synchronization criteria is that certain functional relationships between the feasible sampling period, the largest real part of the eigenvalues of the Laplacian matrix, the largest ratio of the imaginary part to the real part of the eigenvalues of the Laplacian matrix (if there exist complex eigenvalues) and the position gain are analytically established. Some effective iterative methods are then derived to calculate the endpoints of the feasible range of the sampling periods for achieving group synchronization. Finally, numerical experiments further verify the correctness of the theoretical results.
Zhang, H, Ji, J & Wu, Q 2018, 'Sampled‐data control of coupled harmonic oscillators using measured position states only', IET Control Theory & Applications, vol. 12, no. 7, pp. 985-991.
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© The Institution of Engineering and Technology 2018. This brief study investigates the synchronisation of undirected coupled harmonic oscillators by using a sampled-data control strategy. In the absence of measured velocity information, each of the networked oscillators can only obtain the measurements of the position States relative to its neighbours at the sampling moments. A distributed protocol based on the sampled relative position measurements at a series of time instants is proposed for the coupled harmonic oscillators. Necessary and sufficient conditions for achieving synchronisation are analytically established in virtue of the graph theory, matrix analysis theory and Schur stability theory of cubic polynomials. Theoretical results indicate that the explicit range that contains all the desirable sampling periods is uniquely determined by the largest eigenvalue of the Laplacian matrix associated with the network graph and the position gain of the harmonic oscillators. An effective simple iterative method is then developed to calculate the range in which the desirable sampling periods fall. Finally, numerical simulations are performed to illustrate the correctness of the theoretical results and effectiveness of the proposed protocol.
Zhang, H, Wu, Q & Ji, J 2018, 'Synchronization of Discretely Coupled Harmonic Oscillators Using Sampled Position States Only', IEEE Transactions on Automatic Control, vol. 63, no. 11, pp. 3994-3999.
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© 1963-2012 IEEE. This technical note studies the synchronization of discretely coupled harmonic oscillators by using an impulsive control strategy. In the absence of velocity measurements, a distributed protocol for the coupled harmonic oscillators is proposed under the assumption that each oscillator can only obtain the information of its position relative to its neighbors at a series of discrete time moments. Necessary and sufficient conditions are established for the synchronization of the networked system with and without an active leader over an undirected communication topology. The desirable sampling period is analytically found to be dependent on the network topology and position gain. A simple iterative method is developed to calculate the range in which the sampling period falls. Finally, numerical simulations are performed to show the effectiveness of the proposed protocols.
Zhang, L & Ji, JC 2018, 'One-to-three resonant Hopf bifurcations of a maglev system', Nonlinear Dynamics, vol. 93, no. 3, pp. 1277-1286.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. This paper studies the dynamics of a maglev system around 1:3 resonant Hopf–Hopf bifurcations. When two pairs of purely imaginary roots exist for the corresponding characteristic equation, the maglev system has an interaction of Hopf–Hopf bifurcations at the intersection of two bifurcation curves in the feedback control parameter and time delay space. The method of multiple time scales is employed to drive the bifurcation equations for the maglev system by expressing complex amplitudes in a combined polar-Cartesian representation. The dynamics behavior in the vicinity of 1:3 resonant Hopf–Hopf bifurcations is studied in terms of the controller’s parameters (time delay and two feedback control gains). Finally, numerical simulations are presented to support the analytical results and demonstrate some interesting phenomena for the maglev system.
Zhang, X, Xu, J & Ji, J 2018, 'Modelling and tuning for a time-delayed vibration absorber with friction', Journal of Sound and Vibration, vol. 424, pp. 137-157.
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© 2018 Elsevier Ltd This paper presents an integrated analytical and experimental study to the modelling and tuning of a time-delayed vibration absorber (TDVA) with friction. In system modelling, this paper firstly applies the method of averaging to obtain the frequency response function (FRF), and then uses the derived FRF to evaluate the fitness of different friction models. After the determination of the system model, this paper employs the obtained FRF to evaluate the vibration absorption performance with respect to tunable parameters. A significant feature of the TDVA with friction is that its stability is dependent on the excitation parameters. To ensure the stability of the time-delayed control, this paper defines a sufficient condition for stability estimation. Experimental measurements show that the dynamic response of the TDVA with friction can be accurately predicted and the time-delayed control can be precisely achieved by using the modelling and tuning technique provided in this paper.
Zhao, N, Yang, X, Ren, A, Zhang, Z, Zhao, W, Hu, F, Ur Rehman, M, Abbas, H & Abolhasan, M 2018, 'Antenna and Propagation Considerations for Amateur UAV Monitoring', IEEE Access, vol. 6, pp. 28001-28007.
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© 2013 IEEE. The broad application spectrum of unmanned aerial vehicles is making them one of the most promising technologies of Internet of Things era. Proactive prevention for public safety threats is one of the key areas with vast potential of surveillance and monitoring drones. Antennas play a vital role in such applications to establish reliable communication in these scenarios. This paper considers line-of-sight and non-line-of-sight threat scenarios with the perspective of antennas and electromagnetic wave propagation.
Zhou, A, Wu, S, Li, J & Sheng, D 2018, 'Including degree of capillary saturation into constitutive modelling of unsaturated soils', Computers and Geotechnics, vol. 95, pp. 82-98.
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The degree of saturation (S) of soil can be separated into two components: the degree of capillary saturation (S′) that is based on the capillary water and the degree of adsorptive saturation (S″) that is based on the adsorbed water. This paper discusses the role of the degree of capillary saturation (S′) in modelling the coupled hydro-mechanical behaviour of unsaturated soils and proposes a new constitutive model for unsaturated soils by using the degree of capillary saturation (S′) and the effective inter-particle stress (σij′). An enhanced hydraulic model is introduced to describe the hydraulic hysteresis and hydro-mechanical interaction in terms of the degree of capillary saturation (S′). In the proposed constitutive model, the shear strength, yield stress and deformation behaviour of unsaturated soils are governed directly by the above two constitutive variables, namely σij′ and S′. To be in line with the existing finite element frameworks for unsaturated soils, the proposed model is eventually generalised to constitutive functions consisting of only primary variables such as the net stress (σij), suction (s) and degree of saturation (S). The typical performance of the model for simulating the characteristic trends of unsaturated soil behaviour is discussed in several different scenarios. The model is then validated against a variety of experimental data in the literature, and the results show that a reasonable agreement can be obtained using this new constitutive model.
Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'A Study on Idiosyncratic Handwriting with Impact on Writer Identification', 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Niagara Falls, NY, USA, pp. 193-198.
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© 2018 IEEE. In this paper, we study handwriting idiosyncrasy in terms of its structural eccentricity. In this study, our approach is to find idiosyncratic handwritten text components and model the idiosyncrasy analysis task as a machine learning problem supervised by human cognition. We employ the Inception network for this purpose. The experiments are performed on two publicly available databases and an in-house database of Bengali offline handwritten samples. On these samples, subjective opinion scores of handwriting idiosyncrasy are collected from handwriting experts. We have analyzed the handwriting idiosyncrasy on this corpus which comprises the perceptive ground-truth opinion. We also investigate the effect of idiosyncratic text on writer identification by using the SqueezeNet. The performance of our system is promising.
Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'Cognitive Analysis for Reading and Writing of Bengali Conjuncts', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, pp. 1-7.
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© 2018 IEEE. In this paper, we study the difficulties arising in reading and writing of Bengali conjunct characters by human-beings. Such difficulties appear when the human cognitive system faces certain obstructions in effortlessly reading/writing. In our computer-based investigation, we consider the reading/writing difficulty analysis task as a machine learning problem supervised by human perception. To this end, we employ two distinct models: (a) an auto-derived feature-based Inception network and (b) a hand-crafted feature-based SVM (Support Vector Machine). Two commonly used Bengali printed fonts and three contemporary handwritten databases are used for collecting subjective opinion scores from human readers/writers. On this corpus, which contains the perceptive ground-truth opinion of reading/writing complications, we have undertaken to conduct the experiments. The experimental results obtained on various types of conjunct characters are promising.
Adak, C, Marinai, S, Chaudhuri, BB & Blumenstein, M 1970, 'Offline Bengali Writer Verification by PDF-CNN and Siamese Net', 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), IEEE, Vienna, Austria, pp. 381-386.
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© 2018 IEEE. Automated handwriting analysis is a popular area of research owing to the variation of writing patterns. In this research area, writer verification is one of the most challenging branches, having direct impact on biometrics and forensics. In this paper, we deal with offline writer verification on complex handwriting patterns. Therefore, we choose a relatively complex script, i.e., Indic Abugida script Bengali (or, Bangla) containing more than 250 compound characters. From a handwritten sample, the probability distribution functions (PDFs) of some handcrafted features are obtained and input to a convolutional neural network (CNN). For such a CNN architecture, we coin the term 'PDFCNN', where handcrafted feature PDFs are hybridized with auto-derived CNN features. Such hybrid features are then fed into a Siamese neural network for writer verification. The experiments are performed on a Bengali offline handwritten dataset of 100 writers. Our system achieves encouraging results, which sometimes exceed the results of state-of-The-Art techniques on writer verification.
Aghayarzadeh, M, Khabbaz, H & Fatahi, B 1970, 'Numerical analysis of concrete piles driving in saturated dense and loose sand deposits', Numerical methods in geotechnical engineering IX, European Conference on Numerical Methods in Geotechnical Engineering, CRC Press, Porto, Portugal, pp. 1031-1038.
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Many approaches and techniques are used to evaluate pile axial capacity ranging from static methods to dynamic methods, which are based on either the results of pile driving or numerical simulations, which require reliable constitutive models representing the real soil behaviour and the interaction between the pile and soil. In this paper, using PLAXIS software and different constitutive soil models including Mohr-Coulomb, Hardening Soil and Hypoplastic with Intergranular Strain models, the behaviour of concrete piles driven into saturated dense and loose sand deposits under a hammer blow is evaluated. The main objective of this study is to assess the influence of different factors including frequency of loading and Hypoplastic soil model parameters on the recorded velocity and pile head displacement. In addition, the concept of one-dimensional wave propagation induced by pile driving is discussed. It is indicated that using the Intergranular Strain concept, defined in Hypoplastic soil model, small strain behaviour of soil around the pile during driving can directly be captured. The results of this study reveals that considering the Hypoplastic model, incorporating the Intergranular Strain concept, can accumulate much less strains than the corresponding predictions excluding the Intergranular Strain, and hence predict the pile performance during driving more realistically.
Alaei, F, Alaei, A, Pal, U & Blumenstein, M 1970, 'Evaluation of Gist Operator for Document Image Retrieval', 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), IEEE, Vienna, Austria, pp. 369-374.
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© 2018 IEEE. As digitised documents normally contain a large variety of structures, a page segmentation-and layout-free method for document image retrieval is preferable. In this research work, therefore, wavelet transform as a transform-based approach is initially used to provide different under-sampled images from the original image. Then, GIST operator, as a feature extraction technique, is employed to extract a set of global features from the original image as well as the sub-images obtained from the wavelet transform. Moreover, the column-wise variances of the values in each sub-image are computed and they are then concatenated to obtain another set of features. Considering each feature set, locality-sensitive hashing is employed to compute similarity distances between a query and the document images in the database. Finally, a classifier fusion technique using the mean function is taken into account to provide a document image retrieval result. The combination of these features and a clustering score fusion strategy provides higher document image retrieval accuracy. Two different databases of the document image are considered for experimentation. The results obtained from the experimental study are detailed and the results are encouraging.
Amazeeq, MSAB, Kalantar, B, Al-Najjar, HAH, Idrees, MO, Pradhan, B & Mansor, S 1970, 'A geospatial solution using a TOPSIS approach for prioritizing urban projects in Libya', Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018, Asian Conference on Remote Sensing, ACRS, Malaysia, pp. 87-96.
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The world population is growing rapidly; consequently, urbanization has been in an increasing trend in many developing cities around the globe. This rapid growth in population and urbanization have also led to infrastructural development such as transportation systems, sewer, power utilities and many others. One major problem with rapid urbanization in developing/third-world countries is that developments in mega cities are hindered by ineffective planning before construction projects are initiated and mostly developments are random. Libya faces similar problems associated with rapid urbanization. To resolve this, an automating process via effective decision making tools is needed for development in Libyan cities. This study develops a geospatial solution based on GIS and TOPSIS for automating the process of selecting a city or a group of cities for development in Libya. To achieve this goal, fifteen GIS factors were prepared from various data sources including Landsat, MODIS, and ASTER. These factors are categorized into six groups of topography, land use and infrastructure, vegetation, demography, climate, and air quality. The suitability map produced based on the proposed methodology showed that the northern part of the study area, especially the areas surrounding Benghazi city and northern parts of Al Marj and Al Jabal al Akhdar cities, are most suitable. Support Vector Machine (SVM) model accurately classified 1178 samples which is equal to 78.5% of the total samples. The results produced Kappa statistic of 0.67 and average success rate of 0.861. Validation results revealed that the average prediction rate is 0.719. Based on the closeness coefficient statistics, Benghazi, Al Jabal al Akhdar, Al Marj, Darnah, Al Hizam Al Akhdar, and Al Qubbah cities are ranked in that order of suitability. The outputs of this study provide solution to subjective decision making in prioritizing cities for development.
Bhuiyan, MZI, Wang, S, Sloan, SW, Sheng, D & Ming, LK 1970, 'Gravity Grouting and Its Future Alternative for Soil Reinforcement Systems', Springer Series in Geomechanics and Geoengineering, Springer International Publishing, pp. 898-901.
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© Springer Nature Switzerland AG 2018. Gravity grouting technique is commonly used in soil nailing and ground anchorage systems to increase pull out capacity of soil inclusions. Bond strength in between soil-grout interface estimates the pull out capacity of a grouted soil nail/anchor. The bond strength improvement due to gravity grouting and pressure grouting is very limited and grout likely shrinks after setting, resulting in reduction of skin friction between cement grout and surrounding soil of drill hole. One of the major concerns of soil nailing techniques is excessive lateral movement or creep behaviour over the service life and a case study of instrumented ground anchor wall reported that gravity grouted soil reinforcement technique experience excessive creep behaviours. The application of fracture grouting technique in soil nailing is very new and presumably it not only provides drill hole expansion but also provides mechanical interlocking between the penetrating grout and surrounding soil, which could resist the creep behaviour of soil-nails as well as enhance the bond resistance. The application of fracture grouting in soil nailing system could also be a cost-effective method since it likely to increase the pullout resistance of soil-nails, resulting in reduction of the number of soil-nails.
Chemalamarri, VD, Braun, R, Lipman, J & Abolhasan, M 1970, 'A Multi-agent Controller to enable Cognition in Software Defined Networks', 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), IEEE, Sydney, Australia, pp. 52-56.
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© 2018 IEEE. Current SDN controllers are not cognitive. We propose a new architecture for an SDN controller to enable intelligence. The proposed new architecture is based on Multi-agent systems. As a prototype, we have built a MAS-SDN controller using the GOAL agent programming language. We highlight the motivation behind the new architecture, describe the architecture and provide some initial results.
Dang, LC & Khabbaz, MH 1970, 'Assessment of the geotechnical and microstructural characteristics of lime stabilised expansive soil with bagasse ash', the 71st Canadian Geotechnical Conference and the 13th Joint CGS/IAH-CNC Groundwater Conference, the 71st Canadian Geotechnical Conference and the 13th Joint CGS/IAH-CNC Groundwater Conference, Alberta, Canada.
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Bagasse ash is a readily available waste by-product of the sugar-cane refining industry; its improper disposal can cause adverse environmental impacts. Therefore, bagasse ash is considered in this assessment to investigate the possibility of utilising it as an additive for stabilisation of expansive soils. This study aims to assess the improvement in geotechnical properties of expansive soil stabilised with various contents of bagasse ash and lime. The geotechnical characteristics of stabilised soil were examined through a series of unconfined compressive strength (UCS) tests of untreated and treated soil specimens for various curing periods of 3, 7, 28, and 56 days. A preliminary study on the microstructure development of untreated and treated soils was also conducted using scanning electron microscopy (SEM) technique. The results of the UCS tests reveal that the additions of hydrated lime alone, and combined hydrated lime-bagasse ash improved the compressive strength and the stiffness of stabilised soil remarkably. The significant strength development of lime treated soils with bagasse ash was observed not only at the initial stage of 28 days of curing but also at the subsequent 28 days irrespective of additive content. However, for soil samples treated with hydrated lime alone, the predominant strength gain was obtained at the initial stage of 28 days of curing. Subsequently, the compressive strength remained almost constant when curing time exceeded 28 days. The outcomes of the SEM analysis indicate the change in microstructure of the stabilised soils and the formation of new cementitious compounds of Calcium-Silicate-Hydrate (C-S-H). The findings of this study reveal that the application of hydrated lime and bagasse ash combination, as reinforcing construction materials, enhances the geotechnical properties of expansive soil. Using bagasse ash combined with lime can address the coming environmental impacts of bagasse ash disposal, while providing c...
Dang, LC, Khabbaz, H & Fatahi, B 1970, 'Evaluation of Swelling Behaviour and Soil Water Characteristic Curve of Bagasse Fibre and Lime Stabilised Expansive Soil', PanAm Unsaturated Soils 2017, Second Pan-American Conference on Unsaturated Soils, American Society of Civil Engineers, Dallas, Texas, pp. 58-70.
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© 2018 American Society of Civil Engineers (ASCE). All rights reserved. This paper presents an experimental investigation on the enhancement of swelling behaviour and soil water characteristic curve (SWCC) of bagasse fibre and lime stabilised expansive soil. Lime stabilisation is commonly used to improve the engineering properties of expansive soil. Bagasse fibre, an industrial waste by-product left after crushing of sugarcane for juice extraction, was used in this study as reinforcing component in combination of lime for expansive soil stabilisation. The expansive soil used in this investigation was collected from Queensland, Australia. In order to investigate the influences of combination of bagasse fibres and lime on the engineering behaviour of unsaturated expansive soil, a variety of stabilised soil samples were prepared by changing proportions of randomly distributed bagasse fibres combined with different lime contents. An array of experimental tests was performed including free swell potential, swelling pressure, and one-dimensional consolidation tests. Soil suction tests were conducted using the contact filter paper technique on natural and stabilised expansive soil samples. The results revealed that lime-bagasse fibre treatment of expansive clay has a significant effect on swelling behaviour and SWCC response of treated soils. Combination of hydrated lime and bagasse fibre resulted in more improvement on swelling behaviour of soil samples when compared to that treated with lime only. The air entry value of stabilised expansive soil increased with an increase in the stabiliser content.
Das, A, Pal, U, Ferrer, MA, Blumenstein, M, Stepec, D, Rot, P, Emersic, Z, Peer, P & Struc, V 1970, 'SSBC 2018: Sclera Segmentation Benchmarking Competition', 2018 International Conference on Biometrics (ICB), 2018 International Conference on Biometrics (ICB), IEEE, Gold Coast, QLD, Australia, pp. 303-308.
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© 2018 IEEE. This paper summarises the results of the Sclera Segmentation Benchmarking Competition (SSBC 2018). It was organised in the context of the 11th IAPR International Conference on Biometrics (ICB 2018). The aim of this competition was to record the developments on sclera segmentation in the cross-sensor environment (sclera trait captured using multiple acquiring sensors). Additionally, the competition also aimed to gain the attention of researchers on this subject of research. For the purpose of benchmarking, we have developed two datasets of sclera images captured using different sensors. The first dataset was collected using a DSLR camera and the second one was collected using a mobile phone camera. The first dataset is the Multi-Angle Sclera Dataset (MASD version 1), which was used in the context of the previous versions of sclera segmentation competitions. The images in the second dataset were captured using.a mobile phone rear camera of 8-megapixel. As baseline manual segmentation mask of the sclera images from both the datasets were developed. Precision and recall-based statistical measures were employed to evaluate the effectiveness of the submitted segmentation technique and to rank them. Six algorithms were submitted towards the segmentation task. This paper analyses the results produced by these algorithms/system and defines a way forward for this subject of research. Both the datasets along with some of the accompanying ground truth/baseline mask will be freely available for research purposes upon request to authors by email.
Das, A, Sengupta, A, Saqib, M, Pal, U & Blumenstein, M 1970, 'More Realistic and Efficient Face-Based Mobile Authentication using CNNs', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, pp. 1-8.
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© 2018 IEEE. In this work, we propose a more realistic and efficient facebased mobile authentication technique using CNNs. This paper discusses and explores an inevitable problem of using face images for mobile authentication, taken from varying distances with a front/selfie camera of the mobile phone. Incidentally, once an individual comes towards a certain distance from the camera, the face images get large and appear over-sized. Simultaneously sharp features of some portions of the face, such as forehead, cheek, and chin are changed completely. As a result, the face features change and the impact increases exponentially once the individual crosses a certain distance and gradually approaches towards the front camera. This work proposes a solution (achieving better accuracy and facial features, whereby face images were cropped and aligned around its close bounding box) to mitigate the aforementioned identified gap. The work investigated different frontier face detection and recognition techniques to justify the proposed solution. Among all the employed methods evaluated, CNNs worked best. For a quantitative comparison of the proposed method, manually cropped face images/annotations of the face images along with their close boundary were prepared. In turn, we have developed a database considering the above-mentioned scenario for 40 individuals, which will be publicly available for academic research purposes. The experimental results achieved indicate a successful implementation of the proposed method and the performance of the proposed technique is also found to be superior in comparison to the existing state-of-the-art.
Dong, Y, Fatahi, B, Khabbaz, H & Kamruzzaman, AHM 1970, 'Investigating Effects of Particle Scaling for Cavity Expansion Simulation Using Discrete Element Method', PROCEEDINGS OF GEOSHANGHAI 2018 INTERNATIONAL CONFERENCE: FUNDAMENTALS OF SOIL BEHAVIOURS, GeoShanghai International Conference on Fundamentals of Soil Behaviours, Springer Singapore, Tongji Univ, Shanghai, PEOPLES R CHINA, pp. 938-946.
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Ferreira, F & Indraratna, B 1970, 'Deformation and Degradation Response of Railway Ballast under Impact Loading–Effect of Artificial Inclusions', ICRT 2017, First International Conference on Rail Transportation 2017, American Society of Civil Engineers, SW Jiaotong Univ, Chengdu, PEOPLES R CHINA, pp. 1090-1101.
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Gamal, M, Abolhasan, M, Lipman, J, Liu, RP & Ni, W 1970, 'Multi Objective Resource Optimisation for Network Function Virtualisation Requests', 2018 26th International Conference on Systems Engineering (ICSEng), 2018 26th International Conference on Systems Engineering (ICSEng), IEEE, Sydney, Australia.
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© 2018 IEEE. Network function vitalization (NFV) as a new research concept, for both academia and industry, faces many challenges to network operators before it can be accepted into mainstream. One challenge addressed in this paper is to find the optimal placement f or a set of incoming requests with VNF service chains to serve in suitable Virtual Machines (VMs) such that a set of conflicting objectives are met. Mainly, focus is placed on maximizing the total saving cost by increasing the total CPU utilization during the processing time and increasing the processing time for every service request in the cloud network. Moreover, we aim to maximize the admitted traffic simultaneously while considering the system constraints. We formulate the problem as a multi-objective optimization problem and use a Resource Utilization Multi-Objective Evolutionary Algorithm based on Decomposition (RU-MOEA/D) algorithm to solve the problem considering the two objectives simultaneously. Extensive simulations are carried out to evaluate the effects of the different network sizes, genetic parameters and the number of server resources on the acceptable ratio of the arrival chains to serve in the available VMs. The empirical results illustrate that the proposed algorithm can solve the problem efficiently and compute the optimal solution for two objectives together within a reasonable running time.
Gong, S, Wang, X & Oberst, S 1970, 'Non-linear Analysis of Vibrating Flip-flow Screens', MATEC Web of Conferences, International Conference on Design and Manufacturing Engineering, EDP Sciences, Monash University, Melbourne, Australia, pp. 04007-04007.
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Vibrating flip-flow screens provide an effective solution for the screening of highly viscous or fine materials. Apart from other factors, the vibration characteristics of the main and floating screen frames are largely responsible for the flip-flow screen’s sifting performance and its processing capacity. In this paper, the vibration characteristics of a vibrating flip-flow screen with linear and nonlinear springs are compared. Analytical results highlight that increasing the relative amplitude and avoiding undesirable resonances of the main and the floating screen frames can be realised to improve the screen’s performance. The materials on the screen panel have less an effect on the vibration characteristics of the vibrating flip-flow screen with nonlinear springs than using linear springs. Other design parameters which influence the performance of vibrating flip-flow screens are discussed.
Haider, AM & Wijayaratna, K 1970, 'Redesigning roadway infrastructure for mixed autonomous and non-autonomous traffic', ATRF 2018 - Australasian Transport Research Forum 2018, Proceedings, Darwin, Australia.
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© 2018 ATRF, Commonwealth of Australia. All rights reserved. Autonomous vehicles are likely to be one of the major forms of disruptive technology that will be affecting travel behaviour and transport infrastructure development. During the last century, roads have been designed to provide a safe, approachable and efficient environment for the navigation of human drivers in conventional vehicles. The presence of enhanced driving behaviours, such as precise lane guidance and near instantaneous reaction times within autonomous vehicles will transform the planning and design of roadway infrastructure. Acknowledging and leveraging these aspects in coordination with the optimisation of the interaction between conventional and autonomous vehicles will be pivotal for the sustainable adoption of the technology. This study focusses on facilitating mixed autonomous and non-autonomous roadway sharing through two potential redesign options. These are modelled in a microsimulation traffic modelling environment to assess the operational impact of a variety of autonomous vehicle penetration rates, across three demand scenarios. The first option reassigns a single lane as an “autonomous vehicle only” lane on a network consisting of major arterials and motorways. The second redesign consists of reserving entire links of a parallel grid network layout for autonomous vehicles, thus separating general traffic and autonomous vehicle only links. The results from the microsimulation modelling indicate that both proposals present improvements in network performance, evident through increased speeds and reduced delay times. However, improvements are observed only in select scenarios. The analysis highlights that the success of the proposed redesigns are primarily dependent on the level of traffic demand and the technology penetration percentage. Accordingly, the development and redesign of roadway infrastructure must be carefully considered in light of adoption rates to obtain an...
Halkon, B & Chapman, C 1970, 'On the development and characterisation of a synchronised-scanning laser doppler vibrome-ter system', 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling, International Congress on Sound and Vibration, Hiroshima, Japan, pp. 2876-2883.
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Laser Doppler vibrometry (LDV) is now a well-established technique for the non-contact measurement of surface vibration at a point of interest. LDV exhibits numerous benefits over traditional contacting transducers but care must be taken with data interpretation in various scenarios of particular interest. In this paper, the development of a synchronised-scanning LDV system for measurements directly from rotating structures will be described in detail. While still employing the now traditional pair of orthogonally oriented scanning mirrors for laser beam orientation manipulation, this system, for the first time, makes use of hardware-based National Instruments LabVIEW RealTime/FPGA technology to achieve the desired mirror drive signals yielding excellent performance with little loss of flexibility. Characterisation of the performance of the system from a frequency-dependent standpoint will be set-out. Ultimately, manipulation of the generated signals to counter mirror inertia related challenges in maintaining the probe laser beam at the desired position/profile is considered. A number of practically realisable synchronised-scanning profiles will be described on a simplified laboratory set-up with initial interrogation of the resulting measured vibration velocity signals ultimately being made.
Halkon, B & Rothberg, S 1970, 'Taking laser Doppler vibrometry off the tripod', 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling, International Congress on Sound and Vibration, Curran, Hiroshima, Japan, pp. 136-143.
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Laser Doppler vibrometers are now well-established as an effective non-contact alternative to traditional contacting transducers. Despite over 30 years of successful applications, however, very little attention has been given to sensitivity to vibration of the instrument itself. In this paper, sensitivity to instrument vibration and steering optics vibration is confirmed before development theoretically and experimentally of practical schemes to enable correction of measurements. In the case of instrument vibration, the correction scheme requires a pair of sensors with appropriate orientation and relative location. In the case of a beam steering mirror vibration, the correction scheme requires a single measurement from an appropriate location on the back-surface of the mirror in line with the laser beam incidence point. In both cases, frequency domain processing conveniently accommodates inter-channel time delay and signal integrations. Error reductions in excess of 30 dB are delivered in laboratory tests with simultaneous instrument / steering optic and target vibration over a broad frequency range. The practical nature of the correction techniques is demonstrated by successful applications of each. Finally, a previously unreported challenging real-world measurement scenario is described.
Halkon, BJ & Rothberg, SJ 1970, 'Towards laser Doppler vibrometry from unmanned aerial vehicles', Journal of Physics: Conference Series, 13th International Conference on Vibration Measurements by Laser and Noncontact Techniques, IOP Publishing, Ancona, Italy, pp. 012022-012022.
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© 2019 Published under licence by IOP Publishing Ltd. Laser Doppler vibrometers are technically well suited to general application but they offer special benefits in a variety of challenging measurement scenarios which are now well documented and accepted. An interesting and potentially powerful example of such a challenging measurement scenario is one where the laser vibrometer is mounted on/in an unmanned aerial vehicle in order that autonomous measurement campaigns can be undertaken in remote and/or harsh environments. One important challenge to overcome in such a scenario is the measurement sensitivity to vibration of the instrument itself or indeed of any steering optics used to point the probe laser beam toward the target of interest. In this paper, recently reported means by which this measurement sensitivity can be rectified by simultaneously obtained correction measurements will be developed. Specifically, this development is intended to lead towards laser Doppler vibrometry from unmanned aerial vehicles (UAVs) with correction of instrument motion being presented herein for the first time from a single, rather than a pair of, uniaxial accelerometers.
Haque, A & Indraratna, B 1970, 'Experimental and numerical modelling of shear behaviour of rock joints', ISRM International Symposium 2000, IS 2000.
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The shear behaviour of soft rock joints is investigated in laboratory under both Constant Normal Load (CNL) and Constant Normal Stiffness (CNS) conditions. The laboratory behaviour is modelled numerically using the Universal Distinct Element Code (UDEC). The predicted shear stress, normal stress and dilation behaviour with shear displacements are compared with the laboratory results. It is observed that UDEC can predict the peak shear stress of unfilled joints under CNS, however, it overestimates the joint dilation as well as the normal stress. The maximum peak shear stress in UDEC is attained at a greater shear displacement in contrast to the laboratory observations. The UDEC predictions are generally in good agreement with the laboratory data under CNL condition, where the asperity degradation is found to be less significant.
Hasan, H, Khabbaz, H & Fatahi, B 1970, 'Strength Property of Expansive Soils Treated with Bagasse Ash and Lime', ADVANCES IN CHARACTERIZATION AND ANALYSIS OF EXPANSIVE SOILS AND ROCKS, 1st GeoMEast International Congress and Exhibition on Sustainable Civil Infrastructures, Springer International Publishing, EGYPT, pp. 24-35.
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He, X, Wu, W, Zhang, D & Kim, J 1970, 'On Collapse of 2D Granular Columns: A Grain-Scale Investigation', Springer Series in Geomechanics and Geoengineering, Springer International Publishing, pp. 157-160.
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© 2018, Springer Nature Switzerland AG. This study uses the Discrete Element Method (DEM) to investigate the grain-scale mechanisms that give rise to the diverse flow phenomena of granular material, particularly the collapse of granular columns. The small-scale 2D experiments conducted with aluminium rods are used as benchmarks. It is found that the stiffness or the viscous dissipation at the contacts are not important factors to influence the kinetic, but the apparent friction angle is the dominant one, which is contributed by several sources.
He, X, Wu, W, Zhang, D & Kim, J 1970, 'The Hypoplastic Model Expressed by Mean Stress and Deviatoric Stress Ratio', Springer Series in Geomechanics and Geoengineering, Springer International Publishing, pp. 17-20.
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© 2018, Springer Nature Switzerland AG. Over the past several decades, hypoplasticity has been shwon to be a powerful tool to predict the non-linear behaviour of soils. Early hypoplastic models were developed from trial-and-error procedures and these models are usually expressed in a unique tensorial equation regarding the stress tensor. However, most models for fluid-like soil are expressed in the deviatoric stress ratio and the mean stress and these variables are usually modelled differently. This paper presents the hypoplastic model in a new format and written in these two variables. Additionally, parameters of hypoplastic models usually do not have any clear physical meaning and the authors try to investigate the meaning of parameters in the new equations.
Idrees, MO, Kalantar, B, Ueda, N, A. Alnajjar, H, Motevalli, A & Pradhan, B 1970, 'Landslide susceptibility mapping at Dodangeh watershed, Iran using LR and ANN models in GIS', Earth Resources and Environmental Remote Sensing/GIS Applications IX, Earth Resources and Environmental Remote Sensing/GIS Applications, SPIE, Berlin, GERMANY.
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Indraratna, B & Blunden, B 1970, 'Modeling of acid generation in pyritic estuarine soils', ISRM International Symposium 2000, IS 2000.
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The effective management of acid sulfate or pyritic soils is a major issue for many coastal regions in Australia. Drainage and subsequent aeration of potential acid sulfate soils often leads to pyrite oxidation and the acidification of the soil and groundwater. A numerical model has been developed to calculate the rate and magnitude of pyrite oxidation in acid sulfate soils, and the distribution of oxidation products such as H+, SO42- and Fe3+ within the soil profile. The pyrite oxidation model includes vertical diffusion of oxygen from the atmosphere through soil macropores, lateral diffusion of dissolved oxygen from the macropores into the soil matrix, and the consumption of dissolved oxygen in the acid sulfate soil layers by pyrite oxidation. The model developed by the authors is used in conjunction with a commercially available water flow model which is used to simulate the groundwater and soil moisture regime in a three dimensional space. The model can be used to assess the effectiveness of different acid sulfate soils management strategies. The acidity generated by various drain management strategies is demonstrated.
Indraratna, B, Baral, P, Kendaragama, B, Ameratunga, J & Athuraliya, S 1970, 'Potential Biological and Geochemical Clogging of Vibrating Wire Piezometers in Low-lying Acid Sulphate Soil', Australian National Committee on Large Dams Conference 2018, Australian National Committee on Large Dams Conference 2018, Melbourne, Australia.
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Installing a suite of appropriate instruments such as piezometers, settlement plates, extensometers, and inclinometers etc., in strategic locations to monitor the performance of an embankment built on soft soils is vital when there are major design uncertainties; the monitoring data can also be used to calibrate the design parameters. Questionable readings of pore water pressure (PWP) have been reported in various case studies involving the development of dams, embankment foundations and reclamation work in Australia and in South East Asia, especially in low-lying acid sulphate soil (ASS) floodplains. Despite having 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. This paper describes the biological and geo-chemical factors affecting reliability of Vibrating Wire (VW) piezometers, filter-tip clogging, smearing of soil adjoining the filter, gas generation, chemical alteration or corrosion of the filter, as well as electro-osmotic effects and cavitation. To that end, several VW piezometers installed in ASS terrain were extracted after being in place for 1.5 years and the soil surrounding the tips was tested for iron related and sulphate reducing bacteria. It is found that sulphate reducing bacteria has medium to high aggressivity whereas iron related bacteria has very high aggressivity with the bacteria count exceeding 20,000. VWPs with ceramic/stainless steel filter tips installed in acidic ground with organic contents exceeding say 4-5% have shown impeded dissipation of excess pore water pressure after a year or so. Accordingly, it appears that this issue is likely in other types of piezometers fitted with such ceramic or stainless filters when installed in ASS soils. Further Scanning Electron Microscopy (SEM) analysis of the piezometer filter is also ongoing at the University of Wollongong (UOW) lab...
Indraratna, B, Ngo, NT, Nimbalkar, S & Rujikiatkamjorn, C 1970, 'Two Decades of Advancement in Process Simulation Testing of Ballast Strength, Deformation, and Degradation', ASTM Special Technical Publication, Symposium on Railroad Ballast Testing and Properties, ASTM International100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, New Orleans, LA, pp. 11-38.
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This paper describes salient features of a set of large-scale ballast testing equipment developed at the University of Wollongong, Australia, and how the test results and research outcomes have contributed to transforming tracks in the Australian heavy haul and commuter networks, particularly with regards to the strength, deformation, and degradation of ballast. Ideally, ballast assemblies should be tested in prototype scale under actual loading conditions. This is because a reduction in particle sizes for testing in smaller equipment can reduce the internal angle of friction (shearing resistance) of the granular assembly in a macro sense, and the angularity of the particles in a micro sense, and hence the volumetric changes during the shearing process. In response to the worldwide lack of proper test facilities for ballast, the University of Wollongong has, since the early 1990s, designed and built a number of large-scale process simulation triaxial testing rigs. They are all custom made to minimize any boundary effects and also to evaluate the deformation and degradation of ballast, particularly the size, shape, and origin of aggregates used as ballast in Australian tracks. This triaxial process simulation equipment was originally used to characterize the behavior of coarse aggregate used for state railway standards for monotonic loading, but since then it has been fitted with dynamic actuators to simulate actual track conditions involving the true cyclic loading nature while also capturing the wheel-rail dynamics that correspond to high-speed commuter rail and fast heavy-haul operations. These tests invariably demonstrated completely different stress–strain and volumetric characteristics of ballast compared to conventional static or monotonic testing of the same test specimens.
Jena, R & Pradhan, B 1970, 'A novel GIS based seismic hazard assessment in Odisha, India', Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018, Asian Conference On Remote Sensing, ACRS, Kuala Lumpur, Malaysia, pp. 64-71.
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This research was conducted to analyse and estimate the PGA (Peak Ground Acceleration) and seismic amplification of Odisha state in India by using earthquake events recorded by USGS (US geological survey) of the region from the year 1950 to 2015. The analysis also includes for an approximately a range of 300 km from every side of state. Many attempts have been proposed to investigate the PGA in this region during the last decades. Therefore, it was a requirement to implement various methods using some recent viewpoints and methodological approaches. Furthermore, research approaches on seismic hazard analysis need to be updated for currently experienced seismic events. Therefore, the objectives of this research focusing; 1) to ensemble various attributes of seismic events for graphical investigation and, 2) to prepare hazard maps using PGA based on a distinctive GIS approach. Our results clearly showed that the region of Odisha is seismically active and there exists the hazard of ground shaking. It also provides a very accurate evaluation of seismic hazards including the seismic waves that influences surface of the ground based on the amplification map. These findings can be considered for the rapid improvement in earthquake research during recent decades that attempts to study seismic hazards and risks in Odisha.
Jena, R & Pradhan, B 1970, 'Estimating seismic hazard using GIS for the state of Sabah, Malaysia', Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018, Asian Conference on Remote Sensing, ACRS, Kuala Lumpur, Malaysia, pp. 97-104.
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The state of Sabah, Malaysia is not forever immune to seismic risk from global tectonic boundaries but always under risk due to the local active faults. The patches of intersecting active faults can be found in the hilly regions of the Sabah that have resulted more than 65 earthquakes. Till date, researchers have not focused on the intersecting lineaments and faults of Sabah. Therefore, we have proposed the critical triangular analysis on these patches of intersection to find out the zone of risk where most of the earthquakes are happening. To the end, we prepared the PGA map and intensity map based on the historical earthquakes recorded. However, PGA and Intensity maps have been prepared using the Campbell attenuation model. The highest PGA and intensity values resulting from this study are 0.07 and 7, respectively. Our results shows that the critical zone of intersecting faults is the region coming under high intensity and PGA values. It is clearly pinpointing that the intersection of faults and lineaments lead to produce a large number of earthquakes, where the highest magnitude of earthquakes can be found due to the influence of intersecting fault movements.
Jena, R & Pradhan, B 1970, 'Identifying forest loss areas using google earth engine coding system in Keonjhar, Odisha, India', Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018, Asian conference on remote sensing 2018, ACRS, Kuala Lumpur, pp. 856-863.
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Keonjhar district of Odisha is famous for iron and manganese rich minerals according to the directorate of mines, Govt of Odisha. The district is the home to 45.4% of tribal people. However, depletion of forest, increase of wastelands and loss of grazing fields are the major problems for the district. Therefore, the main reason for these changes are mining activity in Keonjhar that is inclusively affecting the tribal livelihood system as well as health. Direct impact of the forest loss is lowering assess of nutrition to the tribal people. Therefore, researchers have not attended any effective research to identifying the areas of forest loss in Keonjhar. Therefore, we have made a reliable attempt by using the google earth engine coding for the identification of forest loss and gain areas in Keonjhar. We have used the Hansen global forest change data of 2014 and 2017 for the analysis. To the end, we identified the regions of forest loss as well as gain. Our results show that there is no forest gain from 2014 to 2017 where the loss is very high. In general, these forest changes were due to mining activity and unusual logging activity.
Jingyang, Z, Jinchen, J, Shan, Y & Van Canh, T 1970, 'The Load Distribution of the Main Shaft Bearing Considering Combined Load and Misalignment in a Floating Direct-Drive Wind Turbine', E3S Web of Conferences, International Conference on Power and Renewable Energy, EDP Sciences, Berlin, Germany, pp. 07009-07009.
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The main shaft tapered double-inner ring bearing (TDIRB) of floating direct-drive wind turbine system (FDDWT) is one of the most critical components in FDDWT, and its failure accounts for a large proportion of wind turbine malfunctions and faults. Over the past decades, a significant number of methods have been proposed to calculate the contact load distribution along the roller length in TDIRB, since the contact load distribution of roller is the key factor of fatigue life of TDIRB. Most of methods, however, neglected the misalignment of inner ring with respect to outer ring and friction force. In this paper, with the help of comprehensive and accurate quasi-static mathematical method, the contact load distribution of internal loads in TDIRB are analysed by considering the effects of combined loads, angular misalignment and friction force at different wind speeds for FDDWT. The simulation results show that the amount of combined load has an apparent effect on the contact load distribution along the TDIRB raceways and flanges in both rows. Furthermore, the slight change of tilted misalignment has a great influence on the contact load distribution. In addition, the slight angular misalignment easily produces noncontact zone for the bearing raceway in both rows, which is significantly disadvantage for the external load uniform transmitting to each roller.
Khan, AA, Abolhasan, M & Ni, W 1970, '5G next generation VANETs using SDN and fog computing framework', 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC), IEEE, Las Vegas, NV, USA, pp. 1-6.
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© 2018 IEEE. The growth of technical revolution towards 5G Next generation networks is expected to meet various communication requirements of future Intelligent Transportation Systems (ITS). Motivated by the consumer needs for variety of ITS applications, bandwidth, high speed and ubiquity, researches are currently exploring different network architectures and techniques, which could be employed in Next generation ITS. To provide flexible network management, control and high resource utilization in Vehicular Ad-hoc Networks (VANETs) on large scale, a new hierarchical 5G Next generation VANET architecture is proposed. The key idea of this holistic architecture is to integrate the centralization and flexibility of Software Defined Networking (SDN) and Cloud-RAN (CRAN), with 5G communication technologies, to effectively allocate resources with a global view. Moreover, a fog computing framework (comprising of zones and clusters) has been proposed at the edge, to avoid frequent handovers between vehicles and RSUs. The transmission delay, throughput and control overhead on controller are analyzed and compared with other architectures. Simulation results indicate reduced transmission delay and minimized control overhead on controllers. Moreover, the throughput of proposed system is also improved.
Lai, JCS, Oberst, S & Evans, TA 1970, 'Termites use vibrations to eavesdrop on predatory ants', INTER-NOISE 2018 - 47th International Congress and Exposition on Noise Control Engineering: Impact of Noise Control Engineering, Internoise 2018, Chicago, Illinois, USA..
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Animals detect many signal types, including light, chemicals, sound and vibrations, some of which come from their environment, some they produce themselves. Signals are used deliberately to communicate and can be detected by predators or parasites. The role of vibrational communication in predator-prey relationships has received limited attention. One such relationship is that between termites and ants, which often live in close proximity with evidence of this evolutionary arms race dating back millions of years ago. Apart from having soldiers to drum alarm signals and to slow down predators' attacks, termites rely on mechanisms to avoid being contacted and detected. However, being cryptic also limits their ability to explore and assess foraging sites. Our previous research shows that despite being blind, (a) termites use vibrations of their feeding to assess food size; and (b) the drywood secundus workers use vibrations to eavesdrop to discriminate their own kin from and avoid their main subterranean competitor, Coptotermes (Co.) acinaciformis. In this paper, we will discuss our recent results that Co. acinaciformis can detect its main predator, the ant Iridomyrmex pupureus, by detecting its footsteps of which the frequency and magnitude are similar to that of the alarm signal of Co. acinaciformis. The application of the engineering noise control principle to develop vibration-based termite control technologies will be discussed.
Liang, B, Li, Z, Wang, Y & Chen, F 1970, 'Long-Term RNN', Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM '18: The 27th ACM International Conference on Information and Knowledge Management, ACM, Torino, ITALY, pp. 1687-1690.
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Lloret-Cabot, M, Pineda, JA & Sheng, D 1970, 'Numerical Implementation of a Critical State Model for Soft Rocks', PanAm Unsaturated Soils 2017, Second Pan-American Conference on Unsaturated Soils, American Society of Civil Engineers, Dallas, TX, pp. 236-246.
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LU, S, Oberst, S, Zhang, G & Luo, Z 1970, 'Comparing complex dynamics using machine learning-reconstructed attracting sets', Colloquium on Irregular Engineering Oscillations and Signal Processing, TUHH, Hamburg, Germany.
LU, S, Oberst, S, Zhang, G & Luo, Z 1970, 'Order patterns recurrence plots and new quantifications to unveil nonlinear dynamics from stochastic systems', International Conference on Time Series and Forecasting 2018, International Conference on Time Series and Forecasting 2018, Granada, Spain.
Makhdoom, I, Abolhasan, M & Ni, W 1970, 'Blockchain for IoT: The Challenges and a Way Forward', Proceedings of the 15th International Joint Conference on e-Business and Telecommunications, International Conference on Security and Cryptography, SCITEPRESS - Science and Technology Publications, Porto, Portugal, pp. 428-439.
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Bitcoin has revolutionized the decentralized payment system by excluding the need for a trusted third party, reducing the transaction (TX) fee and time involved in TX confirmation as compared to a conventional banking system. The underlying technology of Bitcoin is Blockchain, which was initially designed for financial TXs only. However, due to its decentralized architecture, fault tolerance and cryptographic security benefits such as user anonymity, data integrity and authentication, researchers and security analysts around the world are focusing on the Blockchain to resolve security and privacy issues of IoT. But at the same time, default limitations of Blockchain, such as latency in transaction confirmation, scalability concerning Blockchain size and network expansion, lack of IoT-centric transaction validation rules, the absence of IoT-focused consensus protocols and insecure device integration are required to be addressed before it can be used securely and efficiently in an IoT e nvironment. Therefore, in this paper we analyze some of the existing consensus protocols used in various Blockchain-based applications, with a focus on investigating significant limitations in TX (Transaction) validation and consensus mechanism that make them inappropriate to be implemented in Blockchain-based IoT systems. We also propose a way forward to address these issues.
Makhdoom, I, Abolhasan, M & Ni, W 1970, 'Blockchain for IoT: The Challenges and a Way Forward', Proceedings of the 15th International Joint Conference on e-Business and Telecommunications, International Conference on Security and Cryptography, SCITEPRESS - Science and Technology Publications.
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Melnikov, A, Quann, L, Alú, A, Oberst, S, Marburg, S & Powell, D 1970, 'Theory for Willis coupling prediction of acoustic meta-atoms', Symposium on Acoustic Metamaterials, Xatavia, Spain.
Ngo, NT, Indraratna, B & Ferreira, FB 1970, 'Modelling of geogrid-reinforced ballast under direct shear and impact loading', 11th International Conference on Geosynthetics 2018, ICG 2018, pp. 1013-1022.
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Railways provide an efficient and economic transport mode in many parts of the developed countries including Australia, China, South Korea and the USA. Ballast layer is designed as a load bearing layer for rail tracks and to be free draining, but when the ballast voids are wholly or partially impeded due to the intrusion of fine particles or ballast breakage, the ballast can be considered to be fouled. Ballast degradation causes a reduction in the drainage capacity of ballast, thereby reducing the track resiliency and triggering high maintenance costs. Geosynthetics are commonly used in railway construction for reinforcement and stabilisation purposes. When railway ballast becomes degraded, the beneficial effect of geosynthetics could significantly decrease. A series of drop-weight impact tests and direct shear tests for ballast with and without the inclusion of geosynthetics are carried out in the laboratory. Discrete element modelling (DEM) is also carried out on ballast with and without the inclusion of geogrids. Load-deformation and ballast breakage responses obtained from the DEM simulations are in reasonable comparison with those measured experimentally. The research outcomes of this study can provide a fundamental laboratory and computational framework to assist practicing engineers in track design considering the role of geosynthetic inclusions.
Ngo, NT, Indraratna, B & Rujikiatkamjorn, C 1970, 'Load-Deformation Responses of Ballasted Rail Tracks: Laboratory and Discrete-Continuum Modelling', Proceedings of GeoShanghai 2018 International Conference: Transportation Geotechnics and Pavement Engineering, Springer Singapore, pp. 189-198.
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Oberst, S 1970, 'Nonlinear Dynamics: Towards a paradigm change via evidence-based complex dynamics modelling', Noise and Vibrations Emerging Methods, Ibiza, Spain.
Oberst, S, Baetz, J, Campbell, G, Lampe, F, Lai, JCS, Hoffmann, N & Morlock, M 1970, 'Vibro-acoustic and nonlinear analysis of cadavric femoral bone impaction for cavity preparation in hip implants', MATEC Web of Conferences, EDP Sciences.
Oberst, S, Baetz, J, Campbell, G, Lampe, F, Leis, JCS, Hoffmann, N & Morlock, M 1970, 'Vibro-acoustic and nonlinear analysis of cadavric femoral bone impaction in cavity preparations', INTERNATIONAL CONFERENCE ON ENGINEERING VIBRATION (ICOEV 2017), International Conference on Engineering Vibration (ICoEV), E D P SCIENCES, BULGARIA, Sofia, pp. 1-6.
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Owing to an ageing population, the impact of unhealthy lifestyle, or simply congenital or gender
specific issues (dysplasia), degenerative bone and joint disease (osteoarthritis) at the hip pose an increasing
problem in many countries. Osteoarthritis is painful and causes mobility restrictions; amelioration is often only
achieved by replacing the complete hip joint in a total hip arthroplasty (THA). Despite significant orthopaedic
progress related to THA, the success of the surgical process relies heavily on the judgement, experience, skills
and techniques used of the surgeon. One common way of implanting the stem into the femur is press fitting
uncemented stem designs into a prepared cavity. By using a range of compaction broaches, which are impacted
into the femur, the cavity for the implant is formed. However, the surgeon decides whether to change the size of
the broach, how hard and fast it is impacted or when to stop the excavation process, merely based on acoustic,
haptic or visual cues which are subjective. It is known that non-ideal cavity preparations increase the risk of
peri-prosthetic fractures especially in elderly people.
This study reports on a simulated hip replacement surgery on a cadaver and the analysis of impaction forces
and the microphone signals during compaction. The recorded transient signals of impaction forces and acoustic
pressures (≈ 80 µs - 2 ms) are statistically analysed for their trend, which shows increasing heteroscedasticity
in the force-pressure relationship between broach sizes.
TIKHONOV regularisation, as inverse deconvolution technique, is applied to calculate the acoustic transfer
functions from the acoustic responses and their mechanical impacts. The extracted spectra highlight that system
characteristics altered during the cavity preparation process: in the high-frequency range the number of
resonances increased with impacts and broach size. By applying nonlinear time series analysis the system dynamics
increase in compl...
Oberst, S, Lai, JCS & Evans, TA 1970, 'Excitation signal extraction of ant walking pattern under the influence of noise using a biomechanical bipedal mathematical model', 2nd International Symposium on Biotremology, San Michele all’Adige, Italy.
Oberst, S, Lim, S, Romão, AC, Lai, JCS, Stender, M, Hoffmann, NP & Evans, TA 1970, 'A coupled mono-bipedal biomechanical surrogate model to mimic ants walking and running gait analysed using recurrence plot quantification analysis', Colloquium on Irregular Oscillations and Signal Processing,, Hamburg, Germany.
Qi, Y & Indraratna, B 1970, 'The influence of rubber crumbs on the cyclic deformation behavior of waste mixtures', 12th Australia & New Zealand Young Geotechnical Professional Conference, Hobart, Australia.
Qi, Y, Indraratna, B & Vinod, JS 1970, 'Dynamic Properties of Mixtures of Waste Materials', Springer Singapore, pp. 308-317.
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Rahman, JS, Li, J, Xie, J, Fogelman, S & Blumenstein, M 1970, 'Connectivity Based Method for Clustering Microbial Communities from Metagenomics Data of Water and Soil Samples', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, pp. 1-8.
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© 2018 IEEE. Understanding microbial community structure of metagenomics water and soil samples is a key process in discovering functions and impact of microorganisms on human and animal health. Evolution of Next Generation Sequencing (NGS) technology has encouraged researchers to sequence large quantity of microbial data from environmental sources. Clustering marker gene sequences into Operational Taxonomic Units (OTU) is the most significant task in microbial community analysis. Several methods have been developed over the years to improve OTU picking strategies. However, building strongly connected OTUs is a major issue in majority of these methods. Herein we present ConClust, a novel method for clustering OTUs that is based on quantifying connectivity among the sequences. Experimental analysis on two synthetic datasets and two real world datasets from water and soil samples demonstrate that our method can mine robust OTUs. Our method can be highly benelicial to study functions of known and unknown microbes and analyze their positive and negative effect on the environment as well as human and animal health.
Razzak, MI, Saris, RA, Blumenstein, M & Xu, G 1970, 'Robust 2D Joint Sparse Principal Component Analysis With F-Norm Minimization For Sparse Modelling: 2D-RJSPCA', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil.
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Rizeei, HM & Pradhan, B 1970, 'Extraction and accuracy assessment of DTMs derived from remotely sensed and field surveying approaches in GIS framework', IOP Conference Series: Earth and Environmental Science, IOP Publishing, pp. 012009-012009.
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Abstract Generating a high precision continuous surface is a key capability required in most geographic information system (GIS) applications. In fact the most commonly used surface type is a digital elevation model (DEM). Recently, there are some sources of remote sensing data that provide DEM information such as; LiDAR, InSAR and ASTER GDEM which ranged from very high to low spatial resolution. However, new methods of topographic field surveying still highly on demand e.g. Differential GPS and Total station devices. In both method of capturing the terrain elevation the post processing need to be applied to create a continuous surface from point clouds. Geostatistical analysis were used to interpolate the taken sample points from site into continuous surface. In current research, we examined the height accuracy of LiDAR point clouds and total station dataset with three non-adoptive interpolation models including, invers distance weightage (IDW), nearest neighbour (NN) and radial basis function (RBF) based on referenced DGPS points. RMSE and R square regression analysis were conducted to reveal the most accurate approaches in pilot study area. The results showed Lidar surveying (less than 0.5 meter RMSE) has higher height accuracy compared to Total station surveying (above 1 meter in RMSE) to extract DTM in flat area; while consumed less computational processing time. Moreover, IDW was the best and accurate interpolation model in both datasets to generate raster cautious terrain model.
Rizeei, HM, Pradhan, B & Mahlia, TMI 1970, 'GIS-based suitability analysis on hybrid renewal energy site allocation using integrated MODIS and ASTER Satellite imageries in Peninsular Malaysia', Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018, Asian Conference on Remote Sensing, ACRS, Kuala Lumpur, pp. 358-368.
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This study attempts to find the most suitable places to establish hybrid renewable energy sites (e.g. biomass and solar energy) in Malaysia. We used space borne satellite-derived solar irradiance estimation which is useful and accurate approach for solar resource calculation. To do so, MODIS Terra and Aqua satellite were used to extract values of Aerosol Optical Depth (AOD) at 550 nm. Subsequently, other topographic contribution factors were derived from ASTER satellite imagery. MODIS satellite imagery was classified by support vector machine to extract land use/land cover. Additionally, sixteen different metrological stations were utilized to calibrate the solar irradiances achieved from MODIS satellite and provide daily wind data over the entire Peninsular Malaysia. Finally, simple additive weighting method was implemented in geographical information system (GIS) platform to develop the hybrid RE suitability model. MODIS solar radiation result showed a high correlation with field observation. The result of hybrid renewable energy suitability analysis revealed that coastal areas of Hulu Terengganu, have high potential for allocating sites. This country scale research can be used as a guidance/preliminary assessment to narrow down the scope of new potential hybrid RE in regional scale.
Rmezaal, M & Pradhan, B 1970, 'Correlation-based feature optimization and object-based approach for distinguishing shallow and deep-seated landslides using high resolution airborne laser scanning data', IOP Conference Series: Earth and Environmental Science, International Conference and Exhibition on Geospatial & Remote Sensing, IOP Publishing, Kuala Lumpur, Malaysia, pp. 012048-012048.
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Abstract Landslides post great threats to many regions globally, particularly in densely vegetated areas where they are hard to identify. Thus, in order to address this issue, precise inventory mapping methods are required in order to gauge landslide susceptibility in regions, as well as hazards and risk. Obstacles in the development of such mapping methods, however, are optimization techniques to employ, feature selection methods, as well as the development of model transferability. The present study seeks to utilize correlation-based feature selection and object-based approach in conjunction with LiDAR data, whereby LiDAR-DEM derived digital elevation alongside high-resolution orthophotos are employed in tandem. Next, fuzzy-based segmentation parameter optimizer was employed in order to optimize segmentation parameters. Next, support vector machine was employed in order to assess the effectiveness of the proposed method, with results illustrating the algorithm’s robustness with regards to landslide identification. The results of transferability also demonstrated the ease of use for the method, as well as its accuracy and capability to identify landslides as either shallow or deep-seated. To summarize, the study proposes that the developed methods are greatly effective in landslide detection, especially in tropical regions such as in Malaysia.
Saharkhiz, MA, Pradhan, B, Rizeei, HM & Shariff, ARBM 1970, 'Extraction of forest plantation extents using majority voting classification fusion algorithm', Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018, Asian Conference on Remote Sensing, Kuala Lumpur, Malaysia, pp. 1971-1979.
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Satellite Phased Array L-band Synthetic Aperture Radar-2 has great advantages in extracting natural and industrial forest plantation in tropical areas, but it suffers from presence of speckle that create problem to identify the forest body. Optimal fusion of Landsat-8 operational land imager bands with ALOS PALSAR-2 can provide the ideal complementary information for an accurate forest extraction while suppressing unwanted information. The goal of this study is to analyze the potential ability of Landsat-8 OLI and ALOS PALSAR-2 as complementary data resources in order to extract land cover especially forest types. Comprehensive preprocessing analysis (e.g. geometric correction, filtering enhancement and polarization combination) were conducted on ALOS PALSAR-2 dataset in order to make the imagery ready for processing. Principal component index method as one of the most effective Pan-Sharpening fusion approaches was used to synthesize Landsat and ALOS PALSAR-2 images. Three different classifiers methods (support vector machine, k-nearest neighborhood, and random forest) were employed and then fused by majority voting algorithm to generate more robust and precise classification result. Accuracy of the final fused result was assessed on the basis of ground truth points by using confusion matrices and kappa coefficient. This study proves that the accurate and reliable majority voting fusion method can be used to extract large-scale land cover with emphasis on natural and industrial forest plantation from synthetic aperture radar and optical datasets.
Saqib, M, Daud Khan, S, Sharma, N, Scully-Power, P, Butcher, P, Colefax, A & Blumenstein, M 1970, 'Real-Time Drone Surveillance and Population Estimation of Marine Animals from Aerial Imagery', 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Auckland, New Zealand.
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© 2018 IEEE. Video analysis is being rapidly adopted by marine biologists to asses the population and migration of marine animals. Manual analysis of videos by human observers is labor intensive and prone to error. The automatic analysis of videos using state-of-the-art deep learning object detectors provides a cost-effective way for the study of marine animals population and their ecosystem. However, there are many challenges associated with video analysis such as background clutter, illumination, occlusions, and deformation. Due to the high-density of objects in the images and sever occlusion, current state-of-the-art object often results in multiple detections. Therefore, customized Non-Maxima-Suppression is proposed after the detections to suppress false positives which significantly improves the counting and mean average precision of the detections. An end-to-end deep learning framework of Faster-RCNN [1] was adopted for detections with base architectures of VGG16 [2], VGGM [3] and ZF [4].
Saqib, M, Khan, SD, Sharma, N & Blumenstein, M 1970, 'Person Head Detection in Multiple Scales Using Deep Convolutional Neural Networks', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil.
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© 2018 IEEE. Person detection is an important problem in computer vision with many real-world applications. The detection of a person is still a challenging task due to variations in pose, occlusions and lighting conditions. The purpose of this study is to detect human heads in natural scenes acquired from a publicly available dataset of Hollywood movies. In this work, we have used state-of-the-art object detectors based on deep convolutional neural networks. These object detectors include region-based convolutional neural networks using region proposals for detections. Also, object detectors that detect objects in the single-shot by looking at the image only once for detections. We have used transfer learning for fine-tuning the network already trained on a massive amount of data. During the fine-tuning process, the models having high mean Average Precision (mAP) are used for evaluation of the test dataset. Experimental results show that Faster R-CNN [18] and SSD MultiBox [13] with VGG16 [21] perform better than YOLO [17] and also demonstrate significant improvements against several baseline approaches.
Sharma, N, Mandal, R, Sharma, R, Pal, U & Blumenstein, M 1970, 'Signature and Logo Detection using Deep CNN for Document Image Retrieval', 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Niagara Falls, NY, USA, pp. 416-422.
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© 2018 IEEE. Signature and logo as a query are important for content-based document image retrieval from a scanned document repository. This paper deals with signature and logo detection from a repository of scanned documents, which can be used for document retrieval using signature or logo information. A large intra-category variance among signature and logo samples poses challenges to traditional hand-crafted feature extraction-based approaches. Hence, the potential of deep learning-based object detectors namely, Faster R-CNN and YOLOv2 were examined for automatic detection of signatures and logos from scanned administrative documents. Four different network models namely ZF, VGG16, VGG-M, and YOLOv2 were considered for analysis and identifying their potential in document image retrieval. The experiments were conducted on the publicly available 'Tobacco-800' dataset. The proposed approach detects Signatures and Logos simultaneously. The results obtained from the experiments are promising and at par with the existing methods.
Sharma, N, Scully-Power, P & Blumenstein, M 1970, 'Shark Detection from Aerial Imagery Using Region-Based CNN, a Study', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Australasian Joint Conference on Artificial Intelligence, Springer International Publishing, Wellington, New Zealand, pp. 224-236.
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© Springer Nature Switzerland AG 2018. Shark attacks have been a very sensitive issue for Australians and many other countries. Thus, providing safety and security around beaches is very fundamental in the current climate. Safety for both human beings and underwater creatures (sharks, whales, etc.) in general is essential while people continue to visit and use the beaches heavily for recreation and sports. Hence, an efficient, automated and real-time monitoring approach on beaches for detecting various objects (e.g. human activities, large fish, sharks, whales, surfers, etc.) is necessary to avoid unexpected casualties and accidents. The use of technologies such as drones and machine learning techniques are promising directions in such challenging circumstances. This paper investigates the potential of Region-based Convolutional Neural Networks (R-CNN) for detecting various marine objects, and Sharks in particular. 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 3957 video frames were used for experiments. VGG16 architecture with faster-R-CNN performed better than others, with an average precision of 0.904 for detecting Sharks.
Sibaruddin, HI, Shafri, HZM, Pradhan, B & Haron, NA 1970, 'Comparison of pixel-based and object-based image classification techniques in extracting information from UAV imagery data', IOP Conference Series: Earth and Environmental Science, International Conference and Exhibition on Geospatial & Remote Sensing, IOP Publishing, Kuala Lumpur, pp. 012098-012098.
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© Published under licence by IOP Publishing Ltd. As the rapid development is being focused in the urban area, there is a need for the utilisation of a rapid system for updating this profile immediately. One of the current technologies being applied in recent years is the use of unmanned aerial vehicle (UAV) for mapping purposes. The use of UAV is widespread in various fields because it is low cost, has high resolution and is able to fly at low altitude without the constraints of cloudy weather. Typically, the method of data extraction for UAV in Malaysia is still very limited and the traditional methods are still being implemented by some industries. The features from aerial photo orthomosaic are manually detected and digitised from visual interpretation for the mapping purposes. Unfortunately, these methods are tedious, expensive, consume much time, and may involve much fieldwork, to acquire only a limited information. Pixel-based technique is often used to extract low level features where the image is classified according to the spectral information where the pixels in the overlapping region will be misclassified due to the confusion among the classes. The supervised object-based image analysis (OBIA) classification technique is widely used nowadays for automatic data extraction. Therefore, the general objective of this study is to assess the capability of UAV with high resolution data for image classifications. The pixel-based and OBIA classifications were compared using the Support Vector Machine (SVM) classifier. The classifications were assessed using different numbers of sample size. The result shows that OBIA gives a better result of Overall Accuracy (OA) than pixel-based. The consequences of this study accommodate further understanding and additional insight of utilising OBIA technique with different classifiers for the extended study.
Stender, M, Oberst, S & Hoffmann, NP 1970, 'Reconstruction of differential equations from time-series data for feature engineering and model identification', Colloquium on Irregular Oscillations and Signal Processing, Hamburg, Germany.
Suwanwiwat, H, Das, A, Pal, U & Blumenstein, M 1970, 'ICFHR 2018 Competition on Thai Student Signatures and Name Components Recognition and Verification (TSNCRV2018)', 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Niagara Falls, NY, USA, pp. 500-505.
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© 2018 IEEE. This paper summarises the results of the competition on the 1st Thai Student Signature and Name Components Recognition and Verification (TSNCRV 2018). It was organised in the context of the 16th International Conference on Frontiers in Handwriting Recognition (ICFHR 2018). The aim of this competition was to record the development and gain attention on Thai student signatures and name component recognition and verification. Two different types of datasets were used for the competition: The first dataset contains Thai student signatures and the second dataset contains Thai student name components. Signatures and name components from 100 volunteers each were included in the competition datasets. For Thai signature dataset, there are 30 genuine signatures, 12 skilled and 12 simple forgeries for each writer. For Thai name components, there are 30 genuine and 12 skilfully forged name components for each writer. For both the datasets the individuals were asked to write their name/signature in the given space on a white piece of paper for number of time (with a pause between each 10 samples). The skilled forgers were asked practice emitting the original signature for certain number of times till they fill skilled to forge. Five teams from distinguish labs submitted their systems. This paper analysed the results produced by these algorithms/systems using a performance measure and defined a way forward for this subject of research. Both the datasets along with some of the accompanying ground truth/baseline mask will be made freely available for research purposes via the TC10/TC11.
Tang, G, Huang, J, Sheng, D & Sloan, S 1970, 'Stability assessment of the unsaturated slope under rainfall condition considering random rainfall patterns', Numerical Methods in Geotechnical Engineering IX, CRC Press, UK, pp. 507-514.
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Using a typical two-dimensional unsaturated slope, this paper investigates the effects of random rainfall patterns on the stability of unsaturated slope under rainfall condition. Rainfall information is presented in the form of Intensity-Frequency-Duration (IFD) curves. Random Rainfall Patterns (RRPs) are simulated based on Random Cascade Model (RCM) and Monte Carlo Method (MCM). The Conditional Failure Probability (CFP) of the unsaturated slope is investigated by considering the numerous generated RRPs. Meanwhile, the Annual Failure Probability (AFP) of the unsaturated slope is estimated considering also the occurrence frequencies of rainfall events. The results show that the slope stability is sensitive to rainfall patterns, and the RRPs can be considered in the determination of slope reliability.
Tofigh, F, Mao, G, Lipman, J & Abolhasan, M 1970, 'Crowd Density Mapping Based on Wi-Fi Measurements on Train Platforms', 2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS), 2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS), IEEE, Cairns, Australia.
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© 2018 IEEE. Crowd distribution is a challenging issue in the management and design levels. This paper provides a passive method to derive the crowd density distribution using Wi-Fi measurements on a real scenario. Six WiFi access points (AP) are deployed in the platform 2/3 of Redfern station, Sydney to monitor the platform for a week. Based on the probability maps that are built using RSSI measurements and prior knowledge, the crowd distribution is calculated on the platform and its results are compared with distributions acquired from CCTV images. Final density heat maps are in good agreement with the acquired results from CCTV cameras.
Tong, C-X, Zhang, S & Sheng, D 1970, 'A Breakage Matrix Model for Calcareous Sands Subjected to One-Dimensional Compression', Springer Singapore, pp. 17-24.
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Wang, S, Wu, W, He, X, Zhang, D & Kim, JR 1970, 'A Stress Correction Algorithm for a Simple Hypoplastic Model', Springer Series in Geomechanics and Geoengineering, Springer International Publishing, pp. 419-422.
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© 2018, Springer Nature Switzerland AG. In this paper, we consider the numerical integration of a simple hypoplastic constitutive equation. The stress drift away from the failure surface is corrected with a predictor-corrector scheme, which is verified by a boundary value problems, i.e., failure process of a homogeneous slope.
Wang, W, Xu, J, Wang, Y, Cai, C & Chen, F 1970, 'DualBoost', Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM '18: The 27th ACM International Conference on Information and Knowledge Management, ACM, Torino, ITALY, pp. 1543-1546.
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Wijayaratna, K, Jian, S, Jayakumar Nair, D & Waller, T 1970, 'Novel approach to transport project appraisal: Demand weighted multi-modal level of service', Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018, 23rd Conference of Hong Kong Society for Transportation Studies, Hong Kong, Hong Kong, pp. 265-272.
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Traffic management, road network planning and appraisal are highly dependent on effectively assessing the performance of existing and future road infrastructure. In traffic engineering, performance assessment has been underpinned by a grading system known as the “Level of Service” (LoS), which identifies performance criteria that reflects the functionality of the road. This study develops a novel, consistent calculation methodology, the Demand Weighted Level of Service Estimation (DWLE) method, to estimate singular holistic multi-modal LoS metrics, which can be used to compare and contrast the performance of road segments. The generalized approach is independent of the definition and quantification of LoS indicators which offers global application potential. A demonstration of the approach provides evidence for the robustness and consistency of the approach. The value of the DWLE method is that it offers a tool for project prioritization evolving a long-held traffic engineering concept of the Level of Service.
Wu, D, Sharma, N & Blumenstein, M 1970, 'An End-to-End Hierarchical Classification Approach for Similar Gesture Recognition', 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, New Zealand, pp. 73-78.
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© 2018 IEEE. Human action recognition from the RGB video is widely applied on varies real applications. Many works have been done by researchers in computer vision and machine learning area to address the challenges and complexity involved in video-based human action recognition. Deep learning approaches including Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) have been introduced in the human action recognition research area. However, due to the drawbacks of the CNNs, recognizing actions with similar gestures and describing complex actions is still very challenging. Hence, an end-to-end hierarchical classification architecture has been proposed in this paper to resolve the confusion between similar gesture. The proposed approach firstly classifies the whole dataset and generates the accuracy for each class in stage 1. Based on the confusion matrix obtained from stage-1, the approach combines the most confused similar gesture pairs into one class, and classify them along with all other class, in the stage-2. In stage 3, similar gesture pairs will be classified by binary classifiers, which will increase the performance of each class and the overall accuracy. We apply and evaluate the developed models to recognize the similar human actions on the both KTH and UCF101 dataset. The result shows that the proposed approach can boost the classification performance on both the datasets. The proposed architecture is robust and any classification technique can be used in stage 1 and stage 2.
Wu, D, Sharma, N & Blumenstein, M 1970, 'Similar Gesture Recognition using Hierarchical Classification Approach in RGB Videos', 2018 Digital Image Computing: Techniques and Applications (DICTA), 2018 Digital Image Computing: Techniques and Applications (DICTA), IEEE, Canberra, Australia.
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© 2018 IEEE. Recognizing human actions from the video streams has become one of the very popular research areas in computer vision and deep learning in the recent years. Action recognition is wildly used in different scenarios in real life, such as surveillance, robotics, healthcare, video indexing and human-computer interaction. The challenges and complexity involved in developing a video-based human action recognition system are manifold. In particular, recognizing actions with similar gestures and describing complex actions is a very challenging problem. To address these issues, we study the problem of classifying human actions using Convolutional Neural Networks (CNN) and develop a hierarchical 3DCNN architecture for similar gesture recognition. The proposed model firstly combines similar gesture pairs into one class, and classify them along with all other class, as a stage-1 classification. In stage-2, similar gesture pairs are classified individually, which reduces the problem to binary classification. We apply and evaluate the developed models to recognize the similar human actions on the HMDB51 dataset. The result shows that the proposed model can achieve high performance in comparison to the state-of-the-art methods.
Wu, L, Jiang, G, Liu, X, Xiao, H & Sheng, D 1970, 'Performance of geogrid-reinforced pile-supported embankments over decomposed granite soil', Proceedings of the Institution of Civil Engineers: Geotechnical Engineering, ICE PUBLISHING, pp. 37-51.
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This paper presents a full-scale test of high-speed railway embankments over completely decomposed granite soil foundations in order to investigate the performance of geosynthetic-reinforced and pile-supported (GRPS) embankments. The emphasis is placed on the study of the load-transfer mechanisms in those GRPS embankments and on verifying the existing design approaches, taking into account soil arching effects. To do so, four fully instrumented embankment sections were studied, with two sections of geogrid-reinforced and cement-mixing pile-supported embankments and the other two of geogrid reinforcement only. Six commonly used existing design methods for GRPS embankments were tested to show their limitations and applicability. Experimental data from field monitoring for nearly 2 years in these sections were obtained. Results show that all of the six existing design methods tested significantly over-predict the pile efficiency at the end of full embankment, thus leading to a conservative design. BS 8006 and modified BS 8006 yield an overestimation of geogrid strains and thus a conservative estimation. However, all the other methods tested for geogrid strain calculation may lead to an unsafe design. Therefore, it is highly recommended to compare the design results using different approaches in order to optimise the design.
Xiao, X, Wang, S, Sloan, S & Sheng, D 1970, 'Measured and Predicted Response of a Post-grouted Pile in Cohesionless Soil', Springer Series in Geomechanics and Geoengineering, Springer International Publishing, pp. 1051-1054.
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© Springer Nature Switzerland AG 2018. Although compaction grouting beneath the pile tips has been proven to improve the vertically loaded capacity of piles, its design is still largely based on empirical experience and lack of rational design guide. An analytical model that relates the tip resistance to the pressure to expand a spherical cavity for prediction of pile tip bearing capacity is presented. The proposed approach prediction matches quite well with tests results. However, more tests should be done to confirm the correctness of this method. In this paper, a new laboratory setup for investigating the effect of compaction grouting on pile capacity was designed and assembled. This apparatus allows a model pile to be driven into or buried in the sand sample and then a low mobility grout is delivered through a grouting tube inside the model pile into a membrane that is used to prevent grout fracture the sand sample. Then soil stress and pore pressure change are monitored by soil pressure and pore pressure transducer buried in the sample. Pile load test is conducted after the grout have been cured and the pile penetration resistance is measured by the load cell.
Ye, X, Wang, S, Wang, Q, Sloan, SW & Sheng, D 1970, 'The Study of the Compaction Grouted Soil Nail with Multiple Grout Bulks Using Finite Element Method', Springer Singapore, pp. 338-345.
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Yeganeh, N & Fatahi, B 1970, 'Seasonal Effects on Seismic Performance of High Rise Buildings Considering Soil-Structure Interaction', 16th European Conference on Earthquake Engineering, 16th European Conference on Earthquake Engineering, Thessaloniki, Greece.
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The Seismic Soil-Structure Interaction (SSSI), which is a tangled phenomenon, is concerned with the shear waves in preference to the longitudinal waves on account of a prevalent greater energy content in the former. The need for the high rise buildings in the megalopolises results in the paramountcy of the seismic soil-foundation-building interaction analysis in order to achieve the reliable predictions and mayhap curtail the severe damage and probable partial or total collapse of the superstructures. The seasonal effects could influence the soil moisture content particularly in the vadose zone near the surface, exacerbated by the climate change effects, inducing more frequent floods and drought. Wherefore, a soil-structure model was evaluated in this study, subjected to the soil moisture variations in the vadose zone, by utilizing the 3D finite difference modeling technique through the fully nonlinear dynamic analysis in the time domain considering SSSI during the 1994 Northridge earthquake. In particular, the objective was probing the possible effects of the selected degree of saturation (Sr) values, i.e., 5%, 17.5%, 60%, and 100%, for the noncohesive soil, named “Glacier Way Silt”, in conjunction with the small-strain shear moduli on the seismic performance and its corresponding damage of a 20-story reinforced concrete moment-resisting building frame. It is of note that the said values of Sr were employed for the common 4-m zone of influence in Australia, being a sequel of the natural and artificial wetting-drying cycles. Get to the point, it was concluded that the season, in which an earthquake befalls, is stark prominent insomuch as it is potent to impact the extend of the damage in a superstructure.
Yu, J, Xiang, L, Ji, J, Miao, Z & Zhou, J 1970, 'Adaptive Region Tracking Control for Robot Manipulator Systems with Uncertain Kinematics and Dynamics', 2018 37th Chinese Control Conference (CCC), 2018 37th Chinese Control Conference (CCC), IEEE, Wuhan, China, pp. 2909-2914.
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© 2018 Technical Committee on Control Theory, Chinese Association of Automation. This paper studies the region tracking control problem of robot manipulator systems modeled by Lagrangian dynamics with uncertain kinematics and dynamics. By introducing a novel sliding mode, an adaptive controller is constructed to make the robot manipulator reach and track a desired dynamic region. Furthermore, a simple yet generic criterion on the region tracking control problem for robot manipulator systems is derived. It is shown that the robot end-effector can be able to reach in the desired dynamic region with the proposed controller in the presence of the uncertain kinematics and dynamics parameters. Based on the investigation, we revisit the region tracking problem with different control methodologies, to gain a brand-new understanding in the region tracking control problem. Finally, simulation results are presented to demonstrate the effectiveness of the theoretical results.
Zhang, B, Zhang, L, Guo, T, Wang, Y & Chen, F 1970, 'Simultaneous Urban Region Function Discovery and Popularity Estimation via an Infinite Urbanization Process Model', Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, London, ENGLAND, pp. 2692-2700.
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Zhang, J, Li, B, Fan, X, Wang, Y & Chen, F 1970, 'Corrosion Prediction on Sewer Networks with Sparse Monitoring Sites: A Case Study', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, Australia, pp. 223-235.
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© Springer International Publishing AG, part of Springer Nature 2018. Sewer corrosion is a widespread and costly issue for water utilities. Knowing the corrosion status of a sewer network could help the water utility to improve efficiency and save costs in sewer pipe maintenance and rehabilitation. However, inspecting the corrosion status of all sewer pipes is impractical. To prioritize sewer pipes in terms of corrosion risk, the water utility requires a corrosion prediction model built on influential factors that cause sewer corrosion, such as hydrogen sulphide (H 2 S) and temperature. Unfortunately, monitoring sites of influential factors are very sparse on the sewer network such that a reliable prediction has often been hampered by insufficient observations – It is a challenge to predict H 2 S distribution and sewer corrosion levels on the entire sewer network with a limited number of monitoring sites. This work leverages a Bayesian nonparametric method, Gaussian Process, to integrate the physical model developed by domain experts, the sparse H 2 S and temperature monitored records, and the sewer geometry to predict corrosion risk levels on the entire sewer network. A case study has been conducted on a real data set of a water utility in Australia. The evaluation results well demonstrate the effectiveness of the model and admit promising applications for water utilities, including prioritizing high corrosion areas and recommending chemical dosing profiles.
Zhang, M, Gao, Y, Sun, C & Blumenstein, M 1970, 'Matching Pursuit Based on Kernel Non-Second Order Minimization', 2018 25th IEEE International Conference on Image Processing (ICIP), 2018 25th IEEE International Conference on Image Processing (ICIP), IEEE, Athens, Greece, pp. 3858-3862.
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© 2018 IEEE. The orthogonal matching pursuit (OMP) is an important sparse approximation algorithm to recover sparse signals from compressed measurements. However, most MP algorithms are based on the mean square error(MSE) to minimize the recovery error, which is suboptimal when there are outliers. In this paper, we present a new robust OMP algorithm based on kernel non-second order statistics (KNS-OMP), which not only takes advantages of the outlier resistance ability of correntropy but also further extends the second order statistics based correntropy to a non-second order similarity measurement to improve its robustness. The resulted framework is more accurate than the second order ones in reducing the effect of outliers. Experimental results on synthetic and real data show that the proposed method achieves better performances compared with existing methods.
Zhang, X, Fatahi, B & Khabbaz, H 1970, 'Investigating Effects of Fracture Aperture and Orientation on the Behaviour of Weak Rock Using Discrete Element Method', Proceedings of GeoShanghai 2018 International Conference: Rock Mechanics and Rock Engineering, GeoShanghai International Conferences, Springer Singapore, Shanghai, pp. 74-81.
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The effects of the fracture aperture and orientation on the behaviour of weak rock were numerically investigated using discrete element method (DEM). In this study, the mechanical behaviour of the intact and fractured rock specimens was simulated by adopting the discontinuum based software PFC3D. The rock specimens with various fracture apertures and orientations were replicated, and the effects of these two fracture characteristics were studied through triaxial tests. The flat-joint model was employed for simulating the stress-strain behaviour of intact rock and had the ability to reproduce the cementation effect. The smooth-joint contact model was utilised to simulate the sliding effect of the fractures. The effects of five different fracture orientations were investigated in the combination of three different fracture aperture categories, namely very tight, open, and moderately wide. It can be concluded that the strength of the fractured weak rock specimens reduces as the fracture aperture width increases. The amount of alternation in strength and deformability that were contributed by fracture apertures differed with the orientations of the fracture. With the fracture orientation that was parallel to the deviatoric loading, the effect of fracture aperture on the strength and deformability of the specimens was less evident.
Zhang, Z, Oberst, S & Lai, JCS 1970, 'Instability analysis of brake squeal with uncertain contact conditions', 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling, International Congress on Sound and Vibration, Hiroshima, Japan, pp. 4031-4038.
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Brake squeal, as a phenomenon of friction-induced self-excited vibrations, has been a noise, vibration and harshness (NVH) problem for the automotive industry due to warranty-related claims and customer dissatisfaction. Intensive research in the past two decades have provided insight into a number of mechanisms that trigger brake squeal. However, brake squeal is a transient and nonlinear phenomenon and many determining factors are not known precisely such as material properties, operating conditions (brake pad pressure and temperature, speed), contact conditions between pad and disc, and friction. As a result, reliable prediction of brake squeal propensity is difficult to achieve and extensive noise dynamometer testings are still required to identify problematic frequencies for the development and validation of countermeasures. Here, the influence of uncertainties in friction modelling and contact conditions on friction-induced self-excited vibrations of a 3 x 3 coupled friction oscillators model is examined by combining the linear Complex Eigenvalue Analysis (CEA) method widely used in industry with a stochastic approach that incorporates these uncertainties. It has been found that unstable vibration modes with consistently high occurrence of instability independent of the contact area, friction modelling and sliding speed could be identified. Such unstable modes are considered to be robustly unstable and are most likely to produce squeal. An example is given to illustrate how instability countermeasures could be designed by repeating the uncertainty analysis for these robustly unstable modes. These results highlight the potential of reliable prediction of brake squeal propensity in a full brake-system using a stochastic approach with the CEA.
Zhang, Z, Wu, Q, Wang, Y & Chen, F 1970, 'Fine-Grained and Semantic-Guided Visual Attention for Image Captioning', 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, Lake Tahoe, NV, USA, pp. 1709-1717.
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© 2018 IEEE. Soft-attention is regarded as one of the representative methods for image captioning. Based on the end-to-end CNN-LSTM framework, it tries to link the relevant visual information on the image with the semantic representation in the text (i.e. captioning) for the first time. In recent years, there are several state-of-the-art methods published, which are motivated by this approach and include more elegant fine-tune operation. However, due to the constraints of CNN architecture, the given image is only segmented to fixed-resolution grid at a coarse level. The overall visual feature created for each grid cell indiscriminately fuses all inside objects and/or their portions. There is no semantic link among grid cells, although an object may be segmented into different grid cells. In addition, the large-area stuff (e.g. sky and beach) cannot be represented in the current methods. To tackle the problems above, this paper proposes a new model based on the FCN-LSTM framework which can segment the input image into a fine-grained grid. Moreover, the visual feature representing each grid cell is contributed only by the principal object or its portion in the corresponding cell. By adopting the pixel-wise labels (i.e. semantic segmentation), the visual representations of different grid cells are correlated to each other. In this way, a mechanism of fine-grained and semantic-guided visual attention is created, which can better link the relevant visual information with each semantic meaning inside the text through LSTM. Without using the elegant fine-tune, the comprehensive experiments show promising performance consistently across different evaluation metrics.
Zhou, F, Li, Z, Fan, X, Wang, Y, Sowmya, A & Chen, F 1970, 'A Refined MISD Algorithm Based on Gaussian Process Regression', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer International Publishing, pp. 584-596.
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Time series data is a common data type in real life, and modelling of time series data along with its underlying temporal dynamics is always a challenging job. Temporal point process is an outstanding method to model time series data in domains that require temporal continuity, and includes homogeneous Poisson process, inhomogeneous Poisson process and Hawkes process. We focus on Hawkes process which can explain self-exciting phenomena in many real applications. In classical Hawkes process, the triggering kernel is always assumed to be an exponential decay function, which is inappropriate for some scenarios, so nonparametric methods have been used to deal with this problem, such as model independent stochastic de-clustering (MISD) algorithm. However, MISD algorithm has a strong dependence on the number of bins, which leads to underfitting for some bins and overfitting for others, so the choice of bin number is a critical step. In this paper, we innovatively embed a Gaussian process regression into the iterations of MISD to make this algorithm less sensitive to the choice of bin number.
