Abdollahi, A, Pradhan, B & Alamri, A 2020, 'VNet: An End-to-End Fully Convolutional Neural Network for Road Extraction From High-Resolution Remote Sensing Data', IEEE Access, vol. 8, pp. 179424-179436.
View/Download from: Publisher's site
Abdollahi, A, Pradhan, B, Gite, S & Alamri, A 2020, 'Building Footprint Extraction from High Resolution Aerial Images Using Generative Adversarial Network (GAN) Architecture', IEEE Access, vol. 8, pp. 209517-209527.
View/Download from: Publisher's site
Abdollahi, A, Pradhan, B, Shukla, N, Chakraborty, S & Alamri, A 2020, 'Deep Learning Approaches Applied to Remote Sensing Datasets for Road Extraction: A State-Of-The-Art Review', Remote Sensing, vol. 12, no. 9, pp. 1444-1444.
View/Download from: Publisher's site
View description>>
One of the most challenging research subjects in remote sensing is feature extraction, such as road features, from remote sensing images. Such an extraction influences multiple scenes, including map updating, traffic management, emergency tasks, road monitoring, and others. Therefore, a systematic review of deep learning techniques applied to common remote sensing benchmarks for road extraction is conducted in this study. The research is conducted based on four main types of deep learning methods, namely, the GANs model, deconvolutional networks, FCNs, and patch-based CNNs models. We also compare these various deep learning models applied to remote sensing datasets to show which method performs well in extracting road parts from high-resolution remote sensing images. Moreover, we describe future research directions and research gaps. Results indicate that the largest reported performance record is related to the deconvolutional nets applied to remote sensing images, and the F1 score metric of the generative adversarial network model, DenseNet method, and FCN-32 applied to UAV and Google Earth images are high: 96.08%, 95.72%, and 94.59%, respectively.
Abraham, MT, Satyam, N, Bulzinetti, MA, Pradhan, B, Pham, BT & Segoni, S 2020, 'Using Field-Based Monitoring to Enhance the Performance of Rainfall Thresholds for Landslide Warning', Water, vol. 12, no. 12, pp. 3453-3453.
View/Download from: Publisher's site
View description>>
Landslides are natural disasters which can create major setbacks to the socioeconomic of a region. Destructive landslides may happen in a quick time, resulting in severe loss of lives and properties. Landslide Early Warning Systems (LEWS) can reduce the risk associated with landslides by providing enough time for the authorities and the public to take necessary decisions and actions. LEWS are usually based on statistical rainfall thresholds, but this approach is often associated to high false alarms rates. This manuscript discusses the development of an integrated approach, considering both rainfall thresholds and field monitoring data. The method was implemented in Kalimpong, a town in the Darjeeling Himalayas, India. In this work, a decisional algorithm is proposed using rainfall and real-time field monitoring data as inputs. The tilting angles measured using MicroElectroMechanical Systems (MEMS) tilt sensors were used to reduce the false alarms issued by the empirical rainfall thresholds. When critical conditions are exceeded for both components of the systems (rainfall thresholds and tiltmeters), authorities can issue an alert to the public regarding a possible slope failure. This approach was found effective in improving the performance of the conventional rainfall thresholds. We improved the efficiency of the model from 84% (model based solely on rainfall thresholds) to 92% (model with the integration of field monitoring data). This conceptual improvement in the rainfall thresholds enhances the performance of the system significantly and makes it a potential tool that can be used in LEWS for the study area.
Abraham, MT, Satyam, N, Kushal, S, Rosi, A, Pradhan, B & Segoni, S 2020, 'Rainfall Threshold Estimation and Landslide Forecasting for Kalimpong, India Using SIGMA Model', Water, vol. 12, no. 4, pp. 1195-1195.
View/Download from: Publisher's site
View description>>
Rainfall-induced landslides are among the most devastating natural disasters in hilly terrains and the reduction of the related risk has become paramount for public authorities. Between the several possible approaches, one of the most used is the development of early warning systems, so as the population can be rapidly warned, and the loss related to landslide can be reduced. Early warning systems which can forecast such disasters must hence be developed for zones which are susceptible to landslides, and have to be based on reliable scientific bases such as the SIGMA (sistema integrato gestione monitoraggio allerta—integrated system for management, monitoring and alerting) model, which is used in the regional landslide warning system developed for Emilia Romagna in Italy. The model uses statistical distribution of cumulative rainfall values as input and rainfall thresholds are defined as multiples of standard deviation. In this paper, the SIGMA model has been applied to the Kalimpong town in the Darjeeling Himalayas, which is among the regions most affected by landslides. The objectives of the study is twofold: (i) the definition of local rainfall thresholds for landslide occurrences in the Kalimpong region; (ii) testing the applicability of the SIGMA model in a physical setting completely different from one of the areas where it was first conceived and developed. To achieve these purposes, a calibration dataset of daily rainfall and landslides from 2010 to 2015 has been used; the results have then been validated using 2016 and 2017 data, which represent an independent dataset from the calibration one. The validation showed that the model correctly predicted all the reported landslide events in the region. Statistically, the SIGMA model for Kalimpong town is found to have 92% efficiency with a likelihood ratio of 11.28. This performance was deemed satisfactory, thus SIGMA can be integrated with rainfall forecasting and can be used to develop a l...
Abraham, MT, Satyam, N, Pradhan, B & Alamri, AM 2020, 'Forecasting of Landslides Using Rainfall Severity and Soil Wetness: A Probabilistic Approach for Darjeeling Himalayas', Water, vol. 12, no. 3, pp. 804-804.
View/Download from: Publisher's site
View description>>
Rainfall induced landslides are creating havoc in hilly areas and have become an important concern for the stakeholders and public. Many approaches have been proposed to derive rainfall thresholds to identify the critical conditions that can initiate landslides. Most of the empirical methods are defined in such a way that it does not depend upon any of the in situ conditions. Soil moisture plays a key role in the initiation of landslides as the pore pressure increase and loss in shear strength of soil result in sliding of soil mass, which in turn are termed as landslides. Hence this study focuses on a Bayesian analysis, to calculate the probability of occurrence of landslides, based on different combinations of severity of rainfall and antecedent soil moisture content. A hydrological model, called Système Hydrologique Européen Transport (SHETRAN) is used for the simulation of soil moisture during the study period and event rainfall-duration (ED) thresholds of various exceedance probabilities were used to characterize the severity of a rainfall event. The approach was used to define two-dimensional Bayesian probabilities for occurrence of landslides in Kalimpong (India), which is a highly landslide susceptible zone in the Darjeeling Himalayas. The study proves the applicability of SHETRAN model for simulating moisture conditions for the study area and delivers an effective approach to enhance the prediction capability of empirical thresholds defined for the region.
Abraham, MT, Satyam, N, Pradhan, B & Alamri, AM 2020, 'IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas', Sensors, vol. 20, no. 9, pp. 2611-2611.
View/Download from: Publisher's site
View description>>
In hilly areas across the world, landslides have been an increasing menace, causing loss of lives and properties. The damages instigated by landslides in the recent past call for attention from authorities for disaster risk reduction measures. Development of an effective landslide early warning system (LEWS) is an important risk reduction approach by which the authorities and public in general can be presaged about future landslide events. The Indian Himalayas are among the most landslide-prone areas in the world, and attempts have been made to determine the rainfall thresholds for possible occurrence of landslides in the region. The established thresholds proved to be effective in predicting most of the landslide events and the major drawback observed is the increased number of false alarms. For an LEWS to be successfully operational, it is obligatory to reduce the number of false alarms using physical monitoring. Therefore, to improve the efficiency of the LEWS and to make the thresholds serviceable, the slopes are monitored using a sensor network. In this study, micro-electro-mechanical systems (MEMS)-based tilt sensors and volumetric water content sensors were used to monitor the active slopes in Chibo, in the Darjeeling Himalayas. The Internet of Things (IoT)-based network uses wireless modules for communication between individual sensors to the data logger and from the data logger to an internet database. The slopes are on the banks of mountain rivulets (jhoras) known as the sinking zones of Kalimpong. The locality is highly affected by surface displacements in the monsoon season due to incessant rains and improper drainage. Real-time field monitoring for the study area is being conducted for the first time to evaluate the applicability of tilt sensors in the region. The sensors are embedded within the soil to measure the tilting angles and moisture content at shallow depths. The slopes were monitored continuously during three monsoon seas...
Abraham, MT, Satyam, N, Rosi, A, Pradhan, B & Segoni, S 2020, 'The Selection of Rain Gauges and Rainfall Parameters in Estimating Intensity-Duration Thresholds for Landslide Occurrence: Case Study from Wayanad (India)', Water, vol. 12, no. 4, pp. 1000-1000.
View/Download from: Publisher's site
View description>>
Recurring landslides in the Western Ghats have become an important concern for authorities, considering the recent disasters that occurred during the 2018 and 2019 monsoons. Wayanad is one of the highly affected districts in Kerala State (India), where landslides have become a threat to lives and properties. Rainfall is the major factor which triggers landslides in this region, and hence, an early warning system could be developed based on empirical rainfall thresholds considering the relationship between rainfall events and their potential to initiate landslides. As an initial step in achieving this goal, a detailed study was conducted to develop a regional scale rainfall threshold for the area using intensity and duration conditions, using the landslides that occurred during the years from 2010 to 2018. Detailed analyses were conducted in order to select the most effective method for choosing a reference rain gauge and rainfall event associated with the occurrence of landslides. The study ponders the effect of the selection of rainfall parameters for this data-sparse region by considering four different approaches. First, a regional scale threshold was defined using the nearest rain gauge. The second approach was achieved by selecting the most extreme rainfall event recorded in the area, irrespective of the location of landslide and rain gauge. Third, the classical definition of intensity was modified from average intensity to peak daily intensity measured by the nearest rain gauge. In the last approach, four different local scale thresholds were defined, exploring the possibility of developing a threshold for a uniform meteo-hydro-geological condition instead of merging the data and developing a regional scale threshold. All developed thresholds were then validated and empirically compared to find the best suited approach for the study area. From the analysis, it was observed that the approach selecting the rain gauge based on the most extrem...
Afshar, A, Jahandari, S, Rasekh, H, Shariati, M, Afshar, A & Shokrgozar, A 2020, 'Corrosion resistance evaluation of rebars with various primers and coatings in concrete modified with different additives', Construction and Building Materials, vol. 262, pp. 120034-120034.
View/Download from: Publisher's site
View description>>
Corrosion of steel rebars in concrete can reduce the durability of concrete structures in coastal environments. The corrosion rate of these concrete structures can be reduced by using suitable concrete additives and coating on rebars. This paper investigates the corrosion resistance of steel rebars by the addition of pozzolanic materials including fly ash, silica fume, polypropylene fibers, and industrial 2-dimethylaminoethanol (FerroGard 901) inhibitors to the concrete mixture. Three different types of rebars including mild steel rebar st37, and two stainless steel reinforcements, AISI 304 and AISI 316, were used. Various types of primer and coating including alkyd based primer, hot-dip galvanized coatings, alkyd top coating, zinc-rich epoxy primer, polyamide epoxy primer, polyamide epoxy top coating, polyurethane coatings, double layer of epoxy primer and alkyd top coating, and double layer of alkyd primer and alkyd top coating were applied on steel rebars to investigate the effect of coating type on the corrosion resistance of steel rebars in concrete. Polarization tests, electrochemical impedance spectroscopy, compressive strength and color adhesion tests were conducted. The best reinforced concrete mix design for corrosion resistance was the one including the rebar with zinc-rich epoxy primer and 25% fly ash, 10% silica fume, and 3% FerroGard 901 inhibitors by cementitious material weight. Polyurethane was the best coating due to the highest strength and the lowest corrosion rate. Alkyd primer was the weakest coating, although it was the most economical coating system.
Aghayarzadeh, M, Khabbaz, H, Fatahi, B & Terzaghi, S 2020, 'Interpretation of Dynamic Pile Load Testing for Open-Ended Tubular Piles Using Finite-Element Method', International Journal of Geomechanics, vol. 20, no. 2, pp. 04019169-04019169.
View/Download from: Publisher's site
View description>>
© 2019 American Society of Civil Engineers. For a foundation to perform safely, the ultimate strength of each pile must satisfy the structural and geotechnical requirements. Pile load testing is considered to be a direct method for determining the ultimate geotechnical capacity of piles. In this paper the dynamic and static response of a driven steel pipe pile monitored as part of a highway bridge construction project in New South Wales, Australia, has been simulated and then numerically analyzed using the finite-element method. A continuum numerical model has been established to simulate the dynamic load testing of steel pipe piles with unplugged behavior in which adopting measured soil properties resulted in a reasonable match between the measured and predicted results and without needing random signal matching in an iterative process. Settlement at the head and toe of the pile was then calculated when a static load represented by a dead load plus a heavy platform load of a bridge was applied over the pile head. During the dynamic and static load testing simulation, a hardening soil model with small strain stiffness was used to obtain the best correlation between the large and small strains, which occurred while the pile was under static load and being driven. The numerical predictions obtained using continuum finite-element simulations were then compared with the corresponding predictions obtained from the Case Western Reserve University (CASE) method and CASE Pile Wave Analysis Program (CAPWAP) to evaluate the predictions. The results show that the hardening soil model with small strain stiffness exhibits a reasonable correlation with the field measurements during static and dynamic loading. Moreover, parametric studies have been carried out in the established continuum numerical model to evaluate how the interface properties between the pile and soil and the reference shear strain define the backbone on the velocity at the head of the pile and trac...
Ahmed, JB, Salisu, A, Pradhan, B & Alamri, AM 2020, 'Do Termitaria Indicate the Presence of Groundwater? A Case Study of Hydrogeophysical Investigation on a Land Parcel with Termite Activity', Insects, vol. 11, no. 11, pp. 728-728.
View/Download from: Publisher's site
View description>>
Termite nests have long been suggested to be good indicators of groundwater but only a few studies are available to demonstrate the relationship between the two. This study therefore aims at investigating the most favourable spots for locating groundwater structures on a small parcel of land with conspicuous termite activity. To achieve this, geophysical soundings using the renowned vertical electrical sounding (VES) technique was carried out on the gridded study area. A total of nine VESs with one at the foot of a termitarium were conducted. The VES results were interpreted and assessed via two different techniques: (1) physical evaluation as performed by drillers in the field and (2) integration of primary and secondary geoelectrical parameters in a geographic information system (GIS). The result of the physical evaluation indicated a clear case of subjectivity in the interpretation but was consistent with the choice of VES points 1 and 6 (termitarium location) as being the most prospective points to be considered for drilling. Similarly, the integration of the geoelectrical parameters led to the mapping of the most prospective groundwater portion of the study area with the termitarium chiefly in the center of the most suitable region. This shows that termitaria are valuable landscape features that can be employed as biomarkers in the search of groundwater.
Al-Abadi, AM & Pradhan, B 2020, 'In flood susceptibility assessment, is it scientifically correct to represent flood events as a point vector format and create flood inventory map?', Journal of Hydrology, vol. 590, pp. 125475-125475.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. In this discussion article, we try to highlight and discuss the wrong way for representing an areal phenomenon “flood” as a point vector format in GIS-based flood susceptibility studies and creating what is called “flood inventory map”. Two examples from the literature were taken to show that a flood event cannot be represented by point except with very small map scales (1: 10000000) and this flood event should be with other flood events to form the “flood inventory map”. With the help of the other two examples from the previous studies, this article showed the wrong used way for representing flood worldwide and suggested an appropriate method for mapping flood susceptibility.
Alfouneh, M, Ji, J & Luo, Q 2020, 'Optimal design of multi-cellular cores for sandwich panels under harmonic excitation', Composite Structures, vol. 248, pp. 112507-112507.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Sandwich panels with cellular cores are increasingly used in engineering due to their superb dynamic performance. In this type of structure, core design significantly affects its mechanical property. This article is to study optimal design of a multi-cellular core to minimize dynamic response of the sandwich panel under harmonic excitation by use of topology optimization. In this study, structural dynamic responses to harmonic excitation are discussed and formulations of the dynamic response in terms of strain and kinetic energy densities are derived. Topology optimization with multi-fractional volume constraint is conducted for multi-cellular core design to minimize the dynamic response of the sandwich panel under harmonic excitation. The optimization to minimize or maximize the dynamic responses are discussed in optimal core designs of sandwich panels. A multi-objective optimisation problem is also considered to optimally suppress harmonic vibrations with a range of several frequencies. Numerical examples are presented to validate the derived formulations and to optimally design multi-cellular cores for sandwich panels to achieve better dynamic performance.
Amiri, M, Tofigh, F, Shariati, N, Lipman, J & Abolhasan, M 2020, 'Wide-angle metamaterial absorber with highly insensitive absorption for TE and TM modes', Scientific Reports, vol. 10, no. 1.
View/Download from: Publisher's site
View description>>
AbstractBeing incident and polarization angle insensitive are crucial characteristics of metamaterial perfect absorbers due to the variety of incident signals. In the case of incident angles insensitivity, facing transverse electric (TE) and transverse magnetic (TM) waves affect the absorption ratio significantly. In this scientific report, a crescent shape resonator has been introduced that provides over 99% absorption ratio for all polarization angles, as well as 70% and 93% efficiencies for different incident angles up to $$\theta =80^{\circ }$$θ=80∘ for TE and TM polarized waves, respectively. Moreover, the insensitivity for TE and TM modes can be adjusted due to the semi-symmetric structure. By adjusting the structure parameters, the absorption ratio for TE and TM waves at $$\theta =80^{\circ }$$θ=80∘ has been increased to 83% and 97%, respectively. This structure has been designed to operate at 5 GHz spectrum to absorb undesired signals generated due to the growing adoption of Wi-Fi networks. Finally, the proposed absorber has been fabricated in a $$20 \times 20$$20×20 arr...
Arabameri, A, Asadi Nalivan, O, Chandra Pal, S, Chakrabortty, R, Saha, A, Lee, S, Pradhan, B & Tien Bui, D 2020, 'Novel Machine Learning Approaches for Modelling the Gully Erosion Susceptibility', Remote Sensing, vol. 12, no. 17, pp. 2833-2833.
View/Download from: Publisher's site
View description>>
The extreme form of land degradation caused by the formation of gullies is a major challenge for the sustainability of land resources. This problem is more vulnerable in the arid and semi-arid environment and associated damage to agriculture and allied economic activities. Appropriate modeling of such erosion is therefore needed with optimum accuracy for estimating vulnerable regions and taking appropriate initiatives. The Golestan Dam has faced an acute problem of gully erosion over the last decade and has adversely affected society. Here, the artificial neural network (ANN), general linear model (GLM), maximum entropy (MaxEnt), and support vector machine (SVM) machine learning algorithm with 90/10, 80/20, 70/30, 60/40, and 50/50 random partitioning of training and validation samples was selected purposively for estimating the gully erosion susceptibility. The main objective of this work was to predict the susceptible zone with the maximum possible accuracy. For this purpose, random partitioning approaches were implemented. For this purpose, 20 gully erosion conditioning factors were considered for predicting the susceptible areas by considering the multi-collinearity test. The variance inflation factor (VIF) and tolerance (TOL) limit were considered for multi-collinearity assessment for reducing the error of the models and increase the efficiency of the outcome. The ANN with 50/50 random partitioning of the sample is the most optimal model in this analysis. The area under curve (AUC) values of receiver operating characteristics (ROC) in ANN (50/50) for the training and validation data are 0.918 and 0.868, respectively. The importance of the causative factors was estimated with the help of the Jackknife test, which reveals that the most important factor is the topography position index (TPI). Apart from this, the prioritization of all predicted models was estimated taking into account the training and validation data set, which should help futu...
Arabameri, A, Asadi Nalivan, O, Saha, S, Roy, J, Pradhan, B, Tiefenbacher, JP & Thi Ngo, PT 2020, 'Novel Ensemble Approaches of Machine Learning Techniques in Modeling the Gully Erosion Susceptibility', Remote Sensing, vol. 12, no. 11, pp. 1890-1890.
View/Download from: Publisher's site
View description>>
Gully erosion has become one of the major environmental issues, due to the severity of its impact in many parts of the world. Gully erosion directly and indirectly affects agriculture and infrastructural development. The Golestan Dam basin, where soil erosion and degradation are very severe problems, was selected as the study area. This research maps gully erosion susceptibility (GES) by integrating four models: maximum entropy (MaxEnt), artificial neural network (ANN), support vector machine (SVM), and general linear model (GLM). Of 1042 gully locations, 729 (70%) and 313 (30%) gully locations were used for modeling and validation purposes, respectively. Fourteen effective gully erosion conditioning factors (GECFs) were selected for spatial gully erosion modeling. Tolerance and variance inflation factors (VIFs) were used to examine the collinearity among the GECFs. The random forest (RF) model was used to assess factors’ effectiveness and significance in gully erosion modeling. An ensemble of techniques can provide more accurate results than can single, standalone models. Therefore, we compared two-, three-, and four-model ensembles (ANN-SVM, GLM-ANN, GLM-MaxEnt, GLM-SVM, MaxEnt-ANN, MaxEnt-SVM, ANN-SVM-GLM, GLM-MaxEnt-ANN, GLM-MaxEnt-SVM, MaxEnt-ANN-SVM and GLM-ANN-SVM-MaxEnt) for GES modeling. The susceptibility zones of the GESMs were classified as very-low, low, medium, high, and very-high using Jenks’ natural break classification method (NBM). Subsequently, the receiver operating characteristics (ROC) curve and the seed cell area index (SCAI) methods measured the reliability of the models. The success rate curve (SRC) and predication rate curve (PRC) and their area under the curve (AUC) values were obtained from the GES maps. The results show that the ANN model combined with two and three models are more accurate than the other combinations, but the ANN-SVM model had the highest accuracy. The rank of the others from best to worst accuracy ...
Arabameri, A, Blaschke, T, Pradhan, B, Pourghasemi, HR, Tiefenbacher, JP & Bui, DT 2020, 'Evaluation of Recent Advanced Soft Computing Techniques for Gully Erosion Susceptibility Mapping: A Comparative Study', Sensors, vol. 20, no. 2, pp. 335-335.
View/Download from: Publisher's site
View description>>
Gully erosion is a problem; therefore, it must be predicted using highly accurate predictive models to avoid losses caused by gully development and to guarantee sustainable development. This research investigates the predictive performance of seven multiple-criteria decision-making (MCDM), statistical, and machine learning (ML)-based models and their ensembles for gully erosion susceptibility mapping (GESM). A case study of the Dasjard River watershed, Iran uses a database of 306 gully head cuts and 15 conditioning factors. The database was divided 70:30 to train and verify the models. Their performance was assessed with the area under prediction rate curve (AUPRC), the area under success rate curve (AUSRC), accuracy, and kappa. Results show that slope is key to gully formation. The maximum entropy (ME) ML model has the best performance (AUSRC = 0.947, AUPRC = 0.948, accuracy = 0.849 and kappa = 0.699). The second best is the random forest (RF) model (AUSRC = 0.965, AUPRC = 0.932, accuracy = 0.812 and kappa = 0.624). By contrast, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model was the least effective (AUSRC = 0.871, AUPRC = 0.867, accuracy = 0.758 and kappa = 0.516). RF increased the performance of statistical index (SI) and frequency ratio (FR) statistical models. Furthermore, the combination of a generalized linear model (GLM), and functional data analysis (FDA) improved their performances. The results demonstrate that a combination of geographic information systems (GIS) with remote sensing (RS)-based ML models can successfully map gully erosion susceptibility, particularly in low-income and developing regions. This method can aid the analyses and decisions of natural resources managers and local planners to reduce damages by focusing attention and resources on areas prone to the worst and most damaging gully erosion.
Arabameri, A, Cerda, A, Pradhan, B, Tiefenbacher, JP, Lombardo, L & Bui, DT 2020, 'A methodological comparison of head-cut based gully erosion susceptibility models: Combined use of statistical and artificial intelligence', Geomorphology, vol. 359, pp. 107136-107136.
View/Download from: Publisher's site
Arabameri, A, Chen, W, Loche, M, Zhao, X, Li, Y, Lombardo, L, Cerda, A, Pradhan, B & Bui, DT 2020, 'Comparison of machine learning models for gully erosion susceptibility mapping', Geoscience Frontiers, vol. 11, no. 5, pp. 1609-1620.
View/Download from: Publisher's site
View description>>
© 2019 China University of Geosciences (Beijing) and Peking University Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory, especially in the Northern provinces. A number of studies have been recently undertaken to study this process and to predict it over space and ultimately, in a broader national effort, to limit its negative effects on local communities. We focused on the Bastam watershed where 9.3% of its surface is currently affected by gullying. Machine learning algorithms are currently under the magnifying glass across the geomorphological community for their high predictive ability. However, unlike the bivariate statistical models, their structure does not provide intuitive and quantifiable measures of environmental preconditioning factors. To cope with such weakness, we interpret preconditioning causes on the basis of a bivariate approach namely, Index of Entropy. And, we performed the susceptibility mapping procedure by testing three extensions of a decision tree model namely, Alternating Decision Tree (ADTree), Naïve-Bayes tree (NBTree), and Logistic Model Tree (LMT). We dichotomized the gully information over space into gully presence/absence conditions, which we further explored in their calibration and validation stages. Being the presence/absence information and associated factors identical, the resulting differences are only due to the algorithmic structures of the three models we chose. Such differences are not significant in terms of performances; in fact, the three models produce outstanding predictive AUC measures (ADTree = 0.922; NBTree = 0.939; LMT = 0.944). However, the associated mapping results depict very different patterns where only the LMT is associated with reasonable susceptibility patterns. This is a strong indication of what model combines best performance and mapping for any natural hazard – oriented application.
Arabameri, A, Pradhan, B & Bui, DT 2020, 'Spatial modelling of gully erosion in the Ardib River Watershed using three statistical-based techniques', CATENA, vol. 190, pp. 104545-104545.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. Gully erosion threatens land sustainability. Gullies trigger considerable erosion, damaging agricultural land, infrastructure and urban areas; thus, predicting and modelling gully susceptibility is of utmost concern. In particular, such a model is urgently required in semiarid areas where soil loss from gullies is high. Three predictive models are evaluated to assess gully erosion susceptibility mapping (GESM) in Semnan Province, Iran. The index of entropy (IOE), frequency ratio (FR) and certainty factor (CF) models are combined with remote sensing and geographic information system techniques to predict gully erosion. The collation of data from geographic resources identified 287 gullies in the study area. These areas were then randomly divided into 2 groups for calibration (70% or 201 gullies) and validation (30% or 86 gullies). Pairwise linear dependency amongst geoenvironmental factors was also assessed. A total of 16 factors were screened for modelling. Four performance metrics, namely, true skill statistic (TSS), area under the receiver operating characteristic (AUROC) curve, seed cell area index (SCAI) and modified SCAI (mSCAI), were used to evaluate the prediction accuracy and robustness of each model using validation datasets. Bootstrapped replicates were considered in estimating the accuracy and robustness of each model by varying gully/no-gully samples. The IOE results indicated that elevation, lithology and slope angle promoted favourable conditions for gully erosion in the study area. The results showed that the IOE model performed better than the FR and CF models for all three validation datasets (AUROCmean = 0.874 and TSSmean = 0.855). This finding was also confirmed in terms of stability and robustness (RTSS = 0.024 and RAUROC = 0.023). The SCAI and mSCAI results showed that all the models exhibited acceptable accuracy, but IOE demonstrated superior performance. Accordingly, IOE was used as the reference model for the study are...
Arabameri, A, Pradhan, B, Rezaei, K, Lee, S & Sohrabi, M 2020, 'An ensemble model for landslide susceptibility mapping in a forested area', Geocarto International, vol. 35, no. 15, pp. 1680-1705.
View/Download from: Publisher's site
View description>>
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. This article proposes a new methodological approach using a combination of expert knowledge-based (analytic hierarchy process, AHP), bivariate (statistical index, SI) and multivariate (linear discriminant analysis, LDA) models for landslide susceptibility mapping (LSM) in Mazandran Province, Iran. Tolerance and variance inflation factor indicators were used for assessing multi-collinearity among parameters, and three (i.e. profile curvature, soil type and topography wetness index) of 18 factors were eliminated because of multi-collinearity issues. Fifteen geo-environmental conditioning factors including elevation, slope degree, slope aspect, plan curvature, slope length, convergence index, stream power index, distance from river, drainage density, distance from road, distance from fault, lithology, rainfall, land use/landcover and normalized difference vegetation index and 321 landslide locations (testing data set, 70% of total landslides) were used for modeling. The importance of factors showed that distance to road (AHP = 0.201, LDA = 0.301) was the most important factor in landslide occurrence. The validation results using validation data set (138 landslide locations, 30% of total landslides) and area under the receiver operating characteristic curve (AUROC) showed that the ensemble models AHP-LDR (83%), AHP-SI (95%) and SI-LDR (83%) had higher prediction accuracies than the individual AHP (82%), SI (82%) and LDA (79%) models and combination of AHP and SI models along with ALOS-PALSAR remote sensing data and geographic information system (GIS) technique provide powerful tool in LSM in the study area. The results of proposed novel methodological framework can be used by decision-makers and forest engineers for forest management spatially forest roads conservation that have key importance in sustainable development in local and regional scales.
Arabameri, A, Saha, S, Chen, W, Roy, J, Pradhan, B & Bui, DT 2020, 'Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques', Journal of Hydrology, vol. 587, pp. 125007-125007.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. The present research aims to assess and judge the capability of flash flood susceptibility (FFS) models considering hybrid machine learning ensemble techniques for the FFS assessment in the Gorgan Basin in Iran. Three novel intelligence approaches, namely, bagging–functional tree (BFT), dagging–functional tree, and rotational forest–functional tree are used for modelling, with consideration to 15 flood conditioning factors (FCFs) as independent variables and 426 flood locations as dependent variables. Three threshold-dependent and -independent approaches are used to evaluate the goodness-of-fit and prediction capability of the ensemble models with a single functional tree (FT). These approaches include the area under the receiver operating characteristic curve of the success rate curve (SRC) and prediction rate curve (PRC), efficiency (E) and true skill statistics (TSS). The random forest model is used to determine the relative importance of FCFs. Elevation, stream distance and normalized difference vegetation index (NDVI) have crucial roles in the study area during flash flood occurrences. According to the results of all threshold-dependent and -independent approaches (AUC of SRC = 0.933, AUC of PRC = 0.959, E = 0.76 and TSS = 0.72), the BFT ensemble model has the greatest accuracy in terms of modelling FFS. Results also show that the performance of the FT model is enhanced by three meta-classifiers. The seed cell area index technique is also used to check model classification accuracy and reliability. Results of this technique show that all the models demonstrate good performance and reliability. However, the FFS maps prepared by machine learning ensemble techniques have excellent accuracy and reliability, as per the results of validation methods. Thus, these FFS maps can be used as a convenient tool to reduce the effect of flood in flash flood-prone areas.
Arabameri, A, Saha, S, Roy, J, Tiefenbacher, JP, Cerda, A, Biggs, T, Pradhan, B, Thi Ngo, PT & Collins, AL 2020, 'A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility', Science of The Total Environment, vol. 726, pp. 138595-138595.
View/Download from: Publisher's site
Arabameri, A, Tiefenbacher, JP, Blaschke, T, Pradhan, B & Tien Bui, D 2020, 'Morphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Model', Remote Sensing, vol. 12, no. 5, pp. 874-874.
View/Download from: Publisher's site
View description>>
The morphometric characteristics of the Kalvārī basin were analyzed to prioritize sub-basins based on their susceptibility to erosion by water using a remote sensing-based data and a GIS. The morphometric parameters (MPs)—linear, relief, and shape—of the drainage network were calculated using data from the Advanced Land-observing Satellite (ALOS) phased-array L-type synthetic-aperture radar (PALSAR) digital elevation model (DEM) with a spatial resolution of 12.5 m. Interferometric synthetic aperture radar (InSAR) was used to generate the DEM. These parameters revealed the network’s texture, morpho-tectonics, geometry, and relief characteristics. A complex proportional assessment of alternatives (COPRAS)-analytical hierarchy process (AHP) novel-ensemble multiple-criteria decision-making (MCDM) model was used to rank sub-basins and to identify the major MPs that significantly influence erosion landforms of the Kalvārī drainage basin. The results show that in evolutionary terms this is a youthful landscape. Rejuvenation has influenced the erosional development of the basin, but lithology and relief, structure, and tectonics have determined the drainage patterns of the catchment. Results of the AHP model indicate that slope and drainage density influence erosion in the study area. The COPRAS-AHP ensemble model results reveal that sub-basin 1 is the most susceptible to soil erosion (SE) and that sub-basin 5 is least susceptible. The ensemble model was compared to the two individual models using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). To evaluate the prediction accuracy of the ensemble model, its results were compared to results generated by the modified Pacific Southwest Inter-Agency Committee (MPSIAC) model in each sub-basin. Based on SCCT and KTCCT, the ensemble model was better at ranking sub-basins than the MPSIAC model, which indicated that sub-basins 1 and 4, with mean sediment ...
Ardalan, RB, Emamzadeh, ZN, Rasekh, H, Joshaghani, A & Samali, B 2020, 'Physical and mechanical properties of polymer modified self-compacting concrete (SCC) using natural and recycled aggregates', Journal of Sustainable Cement-Based Materials, vol. 9, no. 1, pp. 1-16.
View/Download from: Publisher's site
View description>>
The study researched the effectiveness of four polymer admixtures (3%, 5%, 10%, and 15% of water weight) on the fresh and hardened properties of self-compacting concrete (SCC) cast using recycled and natural aggregates. Results show that polymer additives had positive effects on the fresh properties of SCC using recycled aggregates. Incorporating polymer additives increased the filling ability of concrete by more than four times. All polymer modified SCCs had a 100% passing ability compared to the 80% passing ability of the control samples. The compressive strength of materials at similar polymer ratios decreased by about 50% when natural aggregates were replaced with recycled aggregates. The flexural strength of SCC including recycled aggregates with 15% polymer was maintained compared to the control SCC including natural aggregates. The addition of 15% polymer to recycled aggregates concrete could improve workability and maintain flexural strength.
BAHARVAND, S, PARDHAN, B & SOORI, S 2020, 'Evaluation of active tectonics using geomorphic indices in a mountainous basin of Iran', Earth and Environmental Science Transactions of the Royal Society of Edinburgh, vol. 111, no. 2, pp. 109-117.
View/Download from: Publisher's site
View description>>
ABSTRACTThis study aims to evaluate the tectonic activities of the Vark basin, located in the great basin of Dez River in northwestern Iran, using geomorphologic indices combined with the geographical information system technique. Some geomorphic indices were used to achieve this aim. In this regard, the indices of stream length (SL), drainage asymmetry (Af), hypsometric integral (Hi), valley floor ratio (Vf), basin shape (Bs), and mountain sinuosity (Smf) were estimated to reach an average index of relative tectonics (Iat), indicating the intensity classes of tectonic activity. The mean SL,Hi,Vf, andBsvalues were estimated as 2273, 0.55, 0.45, and 1.75, respectively, regarding the active class of tectonic activity. Therefore, considering theAfandSmfindices with values of 27 and 1.14, the basin was categorised as having semi-active conditions. The overallIat, with a value of 1.33, represented the very high class (1.0 <Iat< 1.5) of tectonic activity. Hence, by calculating the index of relative active tectonics, the study area is observed as the intensive class concerning tectonic movements. Overall, the mean values of theIatfor all sub-basins were calculated as 1.50, 1.17, and 1.83, revealing the very high and high classes of active tectonics in the basin. ...
Balogun, A-L, Yekeen, ST, Pradhan, B & Althuwaynee, OF 2020, 'Spatio-Temporal Analysis of Oil Spill Impact and Recovery Pattern of Coastal Vegetation and Wetland Using Multispectral Satellite Landsat 8-OLI Imagery and Machine Learning Models', Remote Sensing, vol. 12, no. 7, pp. 1225-1225.
View/Download from: Publisher's site
View description>>
Oil spills are a global phenomenon with impacts that cut across socio-economic, health, and environmental dimensions of the coastal ecosystem. However, comprehensive assessment of oil spill impacts and selection of appropriate remediation approaches have been restricted due to reliance on laboratory experiments which offer limited area coverage and classification accuracy. Thus, this study utilizes multispectral Landsat 8-OLI remote sensing imagery and machine learning models to assess the impacts of oil spills on coastal vegetation and wetland and monitor the recovery pattern of polluted vegetation and wetland in a coastal city. The spatial extent of polluted areas was also precisely quantified for effective management of the coastal ecosystem. Using Johor, a coastal city in Malaysia as a case study, a total of 49 oil spill (ground truth) locations, 54 non-oil-spill locations and Landsat 8-OLI data were utilized for the study. The ground truth points were divided into 70% training and 30% validation parts for the classification of polluted vegetation and wetland. Sixteen different indices that have been used to monitor vegetation and wetland stress in literature were adopted for impact and recovery analysis. To eliminate similarities in spectral appearance of oil-spill-affected vegetation, wetland and other elements like burnt and dead vegetation, Support Vector Machine (SVM) and Random Forest (RF) machine learning models were used for the classification of polluted and nonpolluted vegetation and wetlands. Model optimization was performed using a random search method to improve the models’ performance, and accuracy assessments confirmed the effectiveness of the two machine learning models to identify, classify and quantify the area extent of oil pollution on coastal vegetation and wetland. Considering the harmonic mean (F1), overall accuracy (OA), User’s accuracy (UA), and producers’ accuracy (PA), both models have high accuracies. However, the...
Bordbar, M, Neshat, A, Javadi, S, Pradhan, B & Aghamohammadi, H 2020, 'Meta-heuristic algorithms in optimizing GALDIT framework: A comparative study for coastal aquifer vulnerability assessment', Journal of Hydrology, vol. 585, pp. 124768-124768.
View/Download from: Publisher's site
Burton, GJ, Sheng, D & Airey, DW 2020, 'Critical state behaviour of an unsaturated high-plasticity clay', Géotechnique, vol. 70, no. 2, pp. 161-172.
View/Download from: Publisher's site
View description>>
This paper describes a series of tests carried out to examine triaxial compression and shearing of a high-plasticity compacted clay. Reconstituted and compacted samples which were saturated are used as a basis for interpreting the unsaturated test results within a critical state soil mechanics (CSSM) framework. The shear strength behaviour of unsaturated soils have previously been found to be reasonably well captured in a CSSM framework, whereas the volume change behaviour has been more difficult to rationalise. Based on test results presented using the Bishop effective stress, the volume change behaviour during shear suggests that a unique critical state line is approached, independent of the applied suction. The normalised shearing behaviour of the compacted unsaturated soil is interpreted to be analogous to that of saturated-structured soils.
Cai, G, He, X, Dong, L, Liu, S, Xu, Z, Zhao, C & Sheng, D 2020, 'The shear and tensile strength of unsaturated soils by a grain-scale investigation', Granular Matter, vol. 22, no. 1.
View/Download from: Publisher's site
View description>>
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. This paper presents a study of the tensile strength of unsaturated soil by a DEM model in a novel uniaxial tensile test device. For validation and comparison, traditional triaxial shear test of unsaturated soil are also conducted. In the DEM model, the capillary effects and some other cementation effects are modelled by a bond, whose strength is a function of the moisture content and void ratio in uniaxial tensile tests and also the confining pressure in triaxial tests. To compare the DEM simulations with experiments, the bond strength function is calibrated through a quantity measurable in both laboratory and DEM simulations such as the shear strength in triaxial tests or the uniaxial tensile strength in uniaxial tensile tests. The comparison shows that the proposed model is able to capture the phenomena observed in experiments. Most importantly, through investigation of the grain-scale data such as the motion, force chains and development of fractures, it is possible to explain some macroscopic observations such as the form of shear bands in the sample, the influence of the moisture content on the shear and tensile strength, etc.
Cai, G, Li, J, Xu, Z, He, X & Zhao, C 2020, 'Three-dimensional Distinct Element Analysis of Shear Properties of Unsaturated Soils', Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering, vol. 28, no. 6, pp. 1447-1459.
View/Download from: Publisher's site
View description>>
Based on the discrete element theory and the existing laboratory experimental results, a method to determine the corresponding relationship between macro parameters and grain-scale parameters of unsaturated soil is proposed, that is, taking the structural yield stress as the intermediate variable, the corresponding relationship between the bond strength and water content between particles is constructed, and a flexible boundary program is compiled and added to PFC3D(particle flow code in three dimensions).Three dimensional discrete element model of unsaturated soil is established in the program of dimensions.The numerical simulation of triaxial consolidation drained shear test of unsaturated soil with different water content is carried out.The internal grain-scale evolution mechanism of macro mechanical properties such as strength, deformation and failure of unsaturated soil is deeply studied.The feasibility of using discrete element method to study unsaturated materials is also discussed.The results show that: with the increase of water content, the smaller the contact force between particles in the sample is, the less the number of soil particles under stress will be, and the earlier the bond failure point will appear.In addition, the change of bond failure number in the shear process can be divided into three stages: slow growth stage, rapid development stage and residual stage. Compared with the laboratory test results of unsaturated soil, the established DEM model and analysis program show good applicability in the aspects of deviatoric stress-strain relationship and strength characteristics.
Chakrabortty, R, Pradhan, B, Mondal, P & Pal, SC 2020, 'The use of RUSLE and GCMs to predict potential soil erosion associated with climate change in a monsoon-dominated region of eastern India', Arabian Journal of Geosciences, vol. 13, no. 20.
View/Download from: Publisher's site
View description>>
© 2020, Saudi Society for Geosciences. Soil is one of the most important natural resources; therefore, there is an urgent need to estimate soil erosion. The subtropical monsoon-dominated region also faces a comparatively greater problem due to heavy rainfall with high intensity in a very short time and the presence of longer dry seasons and shorter wet seasons. The Arkosa watershed faces the problem of extreme land degradation in the form of soil erosion; therefore, the rate of soil erosion needs to be estimated according to appropriate models. GCM (general circulation model) data such as MIROC5 (Model for Interdisciplinary Climate Research) of CMIP5 (Coupled Model Intercomparison Project Phase 5) have been used to project future storm rainfall and soil erosion rates following the revised universal soil loss equation (RUSLE) in various influential time frames. Apart from that, different satellite data and relevant primary field-based data for future prediction were considered. The average annual soil erosion of Arkosa watershed ranges from < 1 to > 6 t/ha/year. The very high (> 6 t/ha/year) and high (5–6 t/ha/year) soil loss areas are found in the southern, south-eastern, and eastern part of the watershed. Apart from this, low (1–2 t/ha/year) and very low (< 1 t/ha/year) soil loss areas are associated with the western, northern, southern, and major portion of the watershed. Extreme precipitation rates with high kinetic energy due to climate change are favorable to soil erosion susceptibility. The results of this research will help to implement management strategies to minimize soil erosion by keeping authorities and researchers at risk for future erosion and vulnerability.
Chen, M, Ji, J, Liu, H & Yan, F 2020, 'Periodic Oscillations in the Quorum-Sensing System with Time Delay', International Journal of Bifurcation and Chaos, vol. 30, no. 09, pp. 2050127-2050127.
View/Download from: Publisher's site
View description>>
The main aim of this paper is to study the oscillatory behaviors of gene expression networks in quorum-sensing system with time delay. The stability of the unique positive equilibrium and the existence of Hopf bifurcation are investigated by choosing the time delay as the bifurcation parameter and by applying the bifurcation theory. The explicit criteria determining the direction of Hopf bifurcation and the stability of bifurcating periodic solutions are developed based on the normal form theory and the center manifold theorem. Numerical simulations demonstrate good agreements with the theoretical results. Results of this paper indicate that the time delay plays a crucial role in the regulation of the dynamic behaviors of quorum-sensing system.
Chen, W, Li, Y, Xue, W, Shahabi, H, Li, S, Hong, H, Wang, X, Bian, H, Zhang, S, Pradhan, B & Ahmad, BB 2020, 'Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods', Science of The Total Environment, vol. 701, pp. 134979-134979.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier B.V. Floods are one of the most devastating types of disasters that cause loss of lives and property worldwide each year. This study aimed to evaluate and compare the prediction capability of the naïve Bayes tree (NBTree), alternating decision tree (ADTree), and random forest (RF) methods for the spatial prediction of flood occurrence in the Quannan area, China. A flood inventory map with 363 flood locations was produced and partitioned into training and validation datasets through random selection with a ratio of 70/30. The spatial flood database was constructed using thirteen flood explanatory factors. The probability certainty factor (PCF) method was used to analyze the correlation between the factors and flood occurrences. Consequently, three flood susceptibility maps were produced using the NBTree, ADTree, and RF methods. Finally, the area under the curve (AUC) and statistical measures were used to validate the flood susceptibility models. The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rate, sensitivity, specificity, and accuracy for the training (0.951, 0.892, 0.941, 0.945, 0.886, and 0.915, respectively) and validation (0.925, 0.851, 0.938, 0.945, 0.835, and 0.890, respectively) datasets.
Cheshomi, A, Bakhtiyari, E & Khabbaz, H 2020, 'A comparison between undrained shear strength of clayey soils acquired by “PMT” and laboratory tests', Arabian Journal of Geosciences, vol. 13, no. 14, p. 640.
View/Download from: Publisher's site
View description>>
© 2020, Saudi Society for Geosciences. A pressuremeter test (PMT) is one of the in situ tests, which is used to evaluate deformation and strength parameters of soils for various projects, including subway projects. The limit pressure (PL) and undrained shear strength (Su) are the key parameters that are obtained directly and indirectly from the pressuremeter testing results. This research was carried out using geotechnical information obtained from a subway project in Qom city, Iran. Based on 44 PMT and uniaxial tests on very stiff to hard saturated clayey soils, a linear empirical equation between Su − PL and Su − PL* = (PL − σH) with R2 = 0.68 was proposed and it was found that σH had an insignificant effect on the proposed relationship. The effect of physical properties of soil, including plastic index (PI), liquid limit (LL), and water content (ω), was evaluated, and a multivariate equation was proposed between them. A comparison between the equations obtained in this research and those proposed by other researchers reveals that the empirical relationships between Su and PL are associated with the consistency of soils; the stiffer the soil is, the slope of relationship between Su and PL is less.
Chiang, YK, Oberst, S, Melnikov, A, Quan, L, Marburg, S, Alù, A & Powell, DA 2020, 'Reconfigurable Acoustic Metagrating for High-Efficiency Anomalous Reflection', Physical Review Applied, vol. 13, no. 6, pp. 064067-064067.
View/Download from: Publisher's site
View description>>
Recent study revealed that the scattering behaviors of bianisotropic scatterers can be controlled by an additional degree of freedom, represented as Willis coupling, which can be endowed with asymmetric wave scattering to form an acoustic metagrating for wavefront manipulation. Here, we introduce a flexible acoustic metagrating, formed by periodic arrays of properly design Willis scatterers, for anomalous reflection with nearly unitary efficiency and significantly less necessity of fine discretization. Numericalapproaches to predict the wave steering efficiency of the proposed acoustic metagratings with infinite and finite length are developed, which are utilized to demonstrate the strength and flexible features of the metagratings. Results reveal that the proposed acoustic metagrating can reroute incident wave into desired direction at a large angle with nearly unitary efficiency in reflection. The numerical predictions also show that the proposed designs offer a high efficient tunable platform in controlling the steering angles and operating frequencies. To practically realize the ability of extreme angle steering and tunable characteristics of the metagratings, designed structures are fabricated and examined experimentally. The acoustic wave is successfully rerouted to the targeted reflection angles by the finite metagrating. The flexibility regarding different steering angles and operating frequencies of the proposed metagratings are also demonstrated experimentally.
Chowdhuri, I, Pal, SC, Arabameri, A, Saha, A, Chakrabortty, R, Blaschke, T, Pradhan, B & Band, SS 2020, 'Implementation of Artificial Intelligence Based Ensemble Models for Gully Erosion Susceptibility Assessment', Remote Sensing, vol. 12, no. 21, pp. 3620-3620.
View/Download from: Publisher's site
View description>>
The Rarh Bengal region in West Bengal, particularly the eastern fringe area of the Chotanagpur plateau, is highly prone to water-induced gully erosion. In this study, we analyzed the spatial patterns of a potential gully erosion in the Gandheswari watershed. This area is highly affected by monsoon rainfall and ongoing land-use changes. This combination causes intensive gully erosion and land degradation. Therefore, we developed gully erosion susceptibility maps (GESMs) using the machine learning (ML) algorithms boosted regression tree (BRT), Bayesian additive regression tree (BART), support vector regression (SVR), and the ensemble of the SVR-Bee algorithm. The gully erosion inventory maps are based on a total of 178 gully head-cutting points, taken as the dependent factor, and gully erosion conditioning factors, which serve as the independent factors. We validated the ML model results using the area under the curve (AUC), accuracy (ACC), true skill statistic (TSS), and Kappa coefficient index. The AUC result of the BRT, BART, SVR, and SVR-Bee models are 0.895, 0.902, 0.927, and 0.960, respectively, which show very good GESM accuracies. The ensemble model provides more accurate prediction results than any single ML model used in this study.
Chowdhury, PN, Shivakumara, P, Pal, U, Lu, T & Blumenstein, M 2020, 'A new augmentation-based method for text detection in night and day license plate images', Multimedia Tools and Applications, vol. 79, no. 43-44, pp. 33303-33330.
View/Download from: Publisher's site
View description>>
Despite a number of methods that have been developed for License Plate Detection (LPD), most of these focus on day images for license plate detection. As a result, license plate detection in night images is still an elusive goal for researchers. This paper presents a new method for LPD based on augmentation and Gradient Vector Flow (GVF) in night and day images. The augmentation involves expanding windows for each pixel in R, G and B color spaces of the input image until the process finds dominant pixels in both night and day license plate images of the respective color spaces. We propose to fuse the dominant pixels in R, G and B color spaces to restore missing pixels. For the results of fusing night and day images, the proposed method explores Gradient Vector Flow (GVF) patterns to eliminate false dominant pixels, which results in candidate pixels. The proposed method explores further GVF arrow patterns to define a unique loop pattern that represents hole in the characters, which gives candidate components. Furthermore, the proposed approach uses a recognition concept to fix the bounding boxes, merging the bounding boxes and eliminating false positives, resulting in text/license plate detection in both night and day images. Experimental results on night images of our dataset and day images of standard license plate datasets, demonstrate that the proposed approach is robust compared to the state-of-the-art methods. To show the effectiveness of the proposed method, we also tested our approach on standard natural scene datasets, namely, ICDAR 2015, MSRA-TD-500, ICDAR 2017-MLT, Total-Text, CTW1500 and MS-COCO datasets, and their results are discussed.
Das, S, Pradhan, B, Shit, PK & Alamri, AM 2020, 'Assessment of Wetland Ecosystem Health Using the Pressure–State–Response (PSR) Model: A Case Study of Mursidabad District of West Bengal (India)', Sustainability, vol. 12, no. 15, pp. 5932-5932.
View/Download from: Publisher's site
View description>>
Wetlands are essential for protein production, water sanctification, groundwater recharge, climate purification, nutrient cycling, decreasing floods and biodiversity preservation. The Mursidabad district in West Bengal (India) is situated in the floodplain of the Ganga–Padma and Bhagirathi rivers. The region is characterized by diverse types of wetlands; however, the wetlands are getting depredated day-by-day due to hydro-ecological changes, uncontrolled human activities and rapid urbanization. This study attempted to explore the health status of the wetland ecosystem in 2013 and 2020 at the block level in the Mursidabad district, using the pressure–state–response model. Based on wetland ecosystem health values, we categorized the health conditions and identified the blocks where the health conditions are poor. A total of seven Landsat ETM+ spaceborne satellite images in 2001, 2013 and 2020 were selected as the data sources. The statistical data included the population density and urbanization increase rate, for all administrative units, and were collected from the census data of India for 2001 and 2011. We picked nine ecosystem indicators for the incorporated assessment of wetland ecosystem health. The indicators were selected considering every block in the Mursidabad district and for the computation of the wetland ecosystem health index by using the analytical hierarchy processes method. This study determined that 26.92% of the blocks fell under the sick category in 2013, but increased to 30.77% in 2020, while the percentage of blocks in the very healthy category has decreased markedly from 11.54% to 3.85%. These blocks were affected by higher human pressure, such as population density, urbanization growth rate and road density, which resulted in the degradation of wetland health. The scientific protection and restoration techniques of these wetlands should be emphasized in these areas.
Deng, S, Ji, J, Wen, G & Xu, H 2020, 'Delay-induced novel dynamics in a hexagonal centrifugal governor system', International Journal of Non-Linear Mechanics, vol. 121, pp. 103465-103465.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Inherent time delays are often neglected in the modeling and dynamic analysis of centrifugal governor systems for the sake of simplicity, yet they can have a significant effect on the dynamic behavior of the governor systems. This paper investigates the effect of time-delay on the dynamics of a hexagonal centrifugal governor system through a comparative study on the stability and bifurcation of the equilibrium for the system with and without delay considered. It is found that the presence of time-delay can decrease the stability region of the equilibrium and generate many fine structures on the stability boundaries. New dynamic phenomena can be induced by the time-delay, including the 1:4 resonant and non-resonant double Hopf bifurcations. In addition, generic Hopf and Bautin bifurcations can be observed in the system for both the non-delay and delay cases. The unfolding of bifurcations which exhibits all possible behavior at the points of such complicated bifurcations is given by studying the normal form of the response amplitude obtained using the method of multiple scales. Numerical simulations are performed to validate the proposed theoretical analyses.
Dikshit, A, Pradhan, B & Alamri, AM 2020, 'Short-Term Spatio-Temporal Drought Forecasting Using Random Forests Model at New South Wales, Australia', Applied Sciences, vol. 10, no. 12, pp. 4254-4254.
View/Download from: Publisher's site
View description>>
Droughts can cause significant damage to agriculture and water resources, leading to severe economic losses and loss of life. One of the most important aspect is to develop effective tools to forecast drought events that could be helpful in mitigation strategies. The understanding of droughts has become more challenging because of the effect of climate change, urbanization and water management; therefore, the present study aims to forecast droughts by determining an appropriate index and analyzing its changes, using climate variables. The work was conducted in three different phases, first being the determination of Standard Precipitation Evaporation Index (SPEI), using global climatic dataset of Climate Research Unit (CRU) from 1901–2018. The indices are calculated at different monthly intervals which could depict short-term or long-term changes, and the index value represents different drought classes, ranging from extremely dry to extremely wet. However, the present study was focused only on forecasting at short-term scales for New South Wales (NSW) region of Australia and was conducted at two different time scales, one month and three months. The second phase involved dividing the data into three sample sizes, training (1901–2010), testing (2011–2015) and validation (2016–2018). Finally, a machine learning approach, Random Forest (RF), was used to train and test the data, using various climatic variables, e.g., rainfall, potential evapotranspiration, cloud cover, vapor pressure and temperature (maximum, minimum and mean). The final phase was to analyze the performance of the model based on statistical metrics and drought classes. Regarding this, the performance of the testing period was conducted by using statistical metrics, Coefficient of Determination (R2) and Root-Mean-Square-Error (RMSE) method. The performance of the model showed a considerably higher value of R2 for both the time scales. However, statistical metrics analyzes the varia...
Dikshit, A, Pradhan, B & Alamri, AM 2020, 'Temporal Hydrological Drought Index Forecasting for New South Wales, Australia Using Machine Learning Approaches', Atmosphere, vol. 11, no. 6, pp. 585-585.
View/Download from: Publisher's site
View description>>
Droughts can cause significant damage to agriculture and water resources leading to severe economic losses. One of the most important aspects of drought management is to develop useful tools to forecast drought events, which could be helpful in mitigation strategies. The recent global trends in drought events reveal that climate change would be a dominant factor in influencing such events. The present study aims to understand this effect for the New South Wales (NSW) region of Australia, which has suffered from several droughts in recent decades. The understanding of the drought is usually carried out using a drought index, therefore the Standard Precipitation Evaporation Index (SPEI) was chosen as it uses both rainfall and temperature parameters in its calculation and has proven to better reflect drought. The drought index was calculated at various time scales (1, 3, 6, and 12 months) using a Climate Research Unit (CRU) dataset. The study focused on predicting the temporal aspect of the drought index using 13 different variables, of which eight were climatic drivers and sea surface temperature indices, and the remainder were various meteorological variables. The models used for forecasting were an artificial neural network (ANN) and support vector regression (SVR). The model was trained from 1901–2010 and tested for nine years (2011–2018), using three different performance metric scores (coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The results indicate that ANN was better than SVR in predicting temporal drought trends, with the highest R2 value of 0.86 for the former compared to 0.75 for the latter. The study also reveals that sea surface temperatures and the climatic index (Pacific Decadal Oscillation) do not have a significant effect on the temporal drought aspect. The present work can be considered as a first step, wherein we only study the temporal trends, towards the use of climatological...
Dikshit, A, Sarkar, R, Pradhan, B, Acharya, S & Alamri, AM 2020, 'Spatial Landslide Risk Assessment at Phuentsholing, Bhutan', Geosciences, vol. 10, no. 4, pp. 131-131.
View/Download from: Publisher's site
View description>>
Landslides are one of the most destructive and most recurring natural calamities in the Himalayan region. Their occurrence leads to immense damage to infrastructure and loss of land, human lives, and livestock. One of the most affected regions is the Bhutan Himalayas, where the majority of the landslides are rainfall-induced. The present study aims to determine the hazard and risk associated with rainfall-induced landslides for the Phuentsholing region located in the southwestern part of the Bhutan Himalayas. The work involves developing a landslide risk map using hazard and vulnerability maps utilizing landslide records from 2004 to 2014. The landslide hazard map was generated by determining spatial and temporal probabilities for the study region. The spatial probability was computed by analyzing the landslide contributing factors like geology, slope, elevation, rainfall, and vegetation based on comprehensive field study and expertise about the area. The contributing factors were divided into various classes and the percentage of landslide occurrence under each class was calculated to understand its contributing significance. Thereafter, a weighted linear combination approach was used in a GIS environment to develop the spatial probability map which was multiplied with temporal probabilities based on regional rainfall thresholds already determined for the region. Consequently, vulnerability assessment was conducted using key elements at risk (population, land use/land cover, proximity to road, proximity to stream) and the weights were provided based on expert judgment and comprehensive field study. Finally, risk was determined and the various regions in the study area were categorized as high, medium, and low risk. Such a study is necessary for low-economic countries like Bhutan which suffers from unavailability of extensive data and research. The study is conducted for a specific region but can be extended to other areas around the investigate...
Dikshit, A, Sarkar, R, Pradhan, B, Jena, R, Drukpa, D & Alamri, AM 2020, 'Temporal Probability Assessment and Its Use in Landslide Susceptibility Mapping for Eastern Bhutan', Water, vol. 12, no. 1, pp. 267-267.
View/Download from: Publisher's site
View description>>
Landslides are one of the major natural disasters that Bhutan faces every year. The monsoon season in Bhutan is usually marked by heavy rainfall, which leads to multiple landslides, especially across the highways, and affects the entire transportation network of the nation. The determinations of rainfall thresholds are often used to predict the possible occurrence of landslides. A rainfall threshold was defined along Samdrup Jongkhar–Trashigang highway in eastern Bhutan using cumulated event rainfall and antecedent rainfall conditions. Threshold values were determined using the available daily rainfall and landslide data from 2014 to 2017, and validated using the 2018 dataset. The threshold determined was used to estimate temporal probability using a Poisson probability model. Finally, a landslide susceptibility map using the analytic hierarchy process was developed for the highway to identify the sections of the highway that are more susceptible to landslides. The accuracy of the model was validated using the area under the receiver operating characteristic curves. The results presented here may be regarded as a first step towards understanding of landslide hazards and development of an early warning system for a region where such studies have not previously been conducted.
Dikshit, A, Sarkar, R, Pradhan, B, Segoni, S & Alamri, AM 2020, 'Rainfall Induced Landslide Studies in Indian Himalayan Region: A Critical Review', Applied Sciences, vol. 10, no. 7, pp. 2466-2466.
View/Download from: Publisher's site
View description>>
Landslides are one of the most devastating and recurring natural disasters and have affected several mountainous regions across the globe. The Indian Himalayan region is no exception to landslide incidences affecting key economic sectors such as transportation and agriculture and often leading to loss of lives. As reflected in the global landslide dataset, most of the landslides in this region are rainfall triggered. The region is prone to 15% of the global rainfall-induced landslides, and thereby a review of the studies in the region is inevitable. The high exposure to landslide risk has made the Indian Himalayas receive growing attention by the landslides community. A review of landslides studies conducted in this region is therefore important to provide a general picture of the state-of-the-art, a reference point for researchers and practitioners working in this region for the first time, and a summary of the improvements most urgently needed to better address landslide hazard research and management. This article focuses on various studies ranging from forecasting and monitoring to hazard and susceptibility analysis. The various factors used to analyze landslide are also studied for various landslide zones in the region. The analysis reveals that there are several avenues where significant research work is needed such as the inclusion of climate change factors or the acquisition of basic data of highest quality to be used as input data for computational models. In addition, the review reveals that, despite the entire region being highly landslide prone, most of the studies have focused on few regions and large areas have been neglected. The aim of the review is to provide a reference for stakeholders and researchers who are currently or looking to work in the Indian Himalayas, to highlight the shortcomings and the points of strength of the research being conducted, and to provide a contribution in addressing the future developments most urge...
Dikshit, A, Satyam, N, Pradhan, B & Kushal, S 2020, 'Estimating rainfall threshold and temporal probability for landslide occurrences in Darjeeling Himalayas', Geosciences Journal, vol. 24, no. 2, pp. 225-233.
View/Download from: Publisher's site
View description>>
© 2020, The Association of Korean Geoscience Societies and Springer. The Indian Himalayan region has been severely affected by landslides causing an immense loss in terms of human lives and economic loss. The landslides are usually induced by rainfall which can be slow and continuous or heavy downpour. The incidences of landslide events in Indian Himalayas have been further aggravated due to the rapid increase in urbanization and thus its increasing impact on socio-economic aspects. There is a dire need for understanding landslide phenomena, estimating its occurrence potential and formulating strategies to minimize the damage caused by them. One of the most affected area is Kalimpong of Darjeeling Himalayas where significant studies have been conducted on zonation, threshold estimation and other related aspects. However, a comprehensive study in terms of temporal prediction for this region remains unattended. The paper deals with assessing landslide hazard using a rainfall threshold model involving daily and cumulative antecedent rainfall values for landslide events. The threshold values were determined using daily rainfall and antecedent rainfall using precipitation and landslide records for 2010–2016. The results show that 20-day antecedent rainfall provides the best fit for landslide occurrences in the region. The rainfall thresholds were further validated using rainfall and landslide data of 2017, which was not considered for threshold estimation. Finally, the results were used to determine the temporal probability for landslide incidence using a Poisson probability model. The validated results suggest that the model has the potential to be used as a preliminary early warning system.
Doan, S & Fatahi, B 2020, 'Analytical solution for free strain consolidation of stone column-reinforced soft ground considering spatial variation of total stress and drain resistance', Computers and Geotechnics, vol. 118, pp. 103291-103291.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd This paper provides an analytical solution for consolidation problem of a stone column-improved soft soil layer subjected to an instantly applied loading under free strain condition. The radial and vertical consolidation equations are solved in a coupled fashion for both the stone column and its surrounding soil. A general solution of excess pore water pressure at any point of a unit cell model in terms of a Fourier-Bessel series was achieved using the combination of separation of variables method and orthogonal expansion technique. The obtained solution can capture the drain (well) resistance effect and the space-dependent distribution of total vertical stress induced by the external loading. Indeed, since the permeability and size of the stone column are directly utilised in the governing equations and the analytical solution, the drain resistance is directly captured. The capabilities of the proposed solution are exhibited through a comprehensive worked example, while the accuracy of the solution is verified against a finite element simulation and field measurements of a case history with good agreements. To examine the effect of various factors on consolidation behaviour of the composite ground, a parametric study involving column spacing, modulus and permeability of soft soil along with distribution pattern of total stress and thickness of soil layer is also conducted. A decrease in the column spacing or an increase in the modulus or permeability of soft soil led to the acceleration of the consolidation process of the soil region, while the variation of the total stress with depth and the thickness of soil deposit primarily affected the consolidation rate of stone column. Under the free strain condition, the average differential settlement between the stone column and encircling soil was indeed considerable during the consolidation process.
Dodangeh, E, Panahi, M, Rezaie, F, Lee, S, Tien Bui, D, Lee, C-W & Pradhan, B 2020, 'Novel hybrid intelligence models for flood-susceptibility prediction: Meta optimization of the GMDH and SVR models with the genetic algorithm and harmony search', Journal of Hydrology, vol. 590, pp. 125423-125423.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. Floods are among the deadliest natural hazards for humans and the environment. Identifying the most flood-susceptible areas is a fundamental step in the development of flood mitigation strategies and for reducing flood damage. There is an ongoing global debate regarding the most suitable model for flood-susceptibility modeling and predictions. There is also a growing interest in the development of parsimonious and precise models for flood-susceptibility prediction. This study proposed several novel hybrid intelligence models based on the meta-optimization of the support vector regression (SVR) and group method of data handling (GMDH) using different meta-heuristic algorithms, i.e., the genetic algorithm (GA) and harmony search (HS). In contrast to the traditional models, in the SVR model computational complexity does not depend on the dimensionality of the input space. GMDH model has also advantage of being appropriate to analyze multi-parametric data sets. The methodology was developed for the Haraz-Neka watershed, one of the most flood-prone areas in the coastal margins of the Caspian Sea. A total of nine geospatial parameters (slope degree, aspect, elevation, plan curvature, profile curvature, distance to the river, land use, lithology, and rainfall) were identified as the main flood-conditioning factors using information gain ratio (IGR) analyses. Based on existing reports, 132 flood locations were identified in the study area, 92 points (70%) were used together with geospatial data for flood-susceptibility modeling, and the remaining 40 points (30%) were used to validate the models. An initial flood-susceptibility model was constructed based on the SVR and GMDH models. The model parameters were optimized using the GA and HS to reproduce the flood-susceptibility maps. The prediction accuracy of the resultant maps was evaluated in terms of various statistical measures, i.e., mean square error (MSE), root mean square error (RMSE),...
Dong, W, Li, W, Guo, Y, He, X & Sheng, D 2020, 'Effects of silica fume on physicochemical properties and piezoresistivity of intelligent carbon black-cementitious composites', Construction and Building Materials, vol. 259, pp. 120399-120399.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Carbon black (CB) filled cementitious composites as cement-based sensors with intrinsic piezoresistivity have the potential applications for structural health monitoring (SHM). Effect of silica fume (SF) replacement ratio on the physicochemical, mechanical and piezoresistive properties, and microstructure of CB-cementitious composite were experimentally investigated in this study. The results show that 5% or 10% replacement ratio of SF can improve the water impermeability, setting time and electrical conductivity, but decrease the fresh flowability. Cementitious composite with 10% SF exhibiteds excellent compressive and flexural strengths. Moreover, cement hydration in the acceleration stage decreased with the increase of SF content in the early stage, but the phase analysis after 28 days curing demonstrates that with the addition of SF, there are more hydrated products and less ettringite. In addition, the microstructures of cementitious composites without SF present more porous structures and CB agglomerations. In contrast, the amount of micropores or voids was significantly reduced by the addition of SF due to the physical filling effect and less CB agglomerations. In terms of piezoresistivity, SF can obviously improve the fractional changes of resistivity (FCR) under cyclic compression. With 10% SF, CB-cementitious composites as cement-based sensors exhibited excellent FCR and electrical stability, which will promote their development and application in the SHM for smart infrastructures.
Dong, W, Li, W, Luo, Z, Long, G, Vessalas, K & Sheng, D 2020, 'Structural response monitoring of concrete beam under flexural loading using smart carbon black/cement-based sensors', Smart Materials and Structures, vol. 29, no. 6, pp. 065001-065001.
View/Download from: Publisher's site
View description>>
© 2020 IOP Publishing Ltd. The fractional changes of resistivity (FCR) of cement-based sensors with various carbon black (CB) contents were firstly investigated under uniaxial compression in this study. Then the piezoresistive behaviours of embedded cement-based sensors in unreinforced small-scale concrete beams were investigated under flexural bending load. As for the embedded cement-based sensors in the compression zones of the beam, the stress magnitude and crack failure initiation of the beams can be detected and monitored by a gradual decrease and then a sharp increase in the FRC. On the other hand, as for the counterpart sensors in the tension zones of the beam, the stress magnitude and crack failure initiation can be recognized by the gradual increase in resistivity and then a rapid jump in the FRC. During the stress monitoring of the concrete beam, the FCR values of cement-based sensors in both the compression and tension zones were consistent with the flexural stress changes, which exhibit acceptable sensitivity and reversibility. Moreover, very firm and dense interfaces in the boundaries indicate the excellent cohesion between embedded CB/cement-based sensors and beams. The related results demonstrate that the CB/cement-based sensors embedded in concrete exhibit excellent piezoresistive behaviours to potentially monitor the stress magnitude and failure process of concrete structures and pavements.
Dong, W, Li, W, Shen, L, Sun, Z & Sheng, D 2020, 'Piezoresistivity of smart carbon nanotubes (CNTs) reinforced cementitious composite under integrated cyclic compression and impact', Composite Structures, vol. 241, pp. 112106-112106.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The cyclic compression and four series of fixed magnitude impact loads with an increment of 50 times were conducted alternatively on the smart carbon nanotubes (CNTs) reinforced cementitious composites, to evaluate the piezoresistive sensitivity and repeatability of composites after exposed to different drop impact energies. The results show that the impacts procedure suddenly increased in electrical resistivity due to the emerged micro-cracks and pores, and higher impact energy led to faster resistivity increase. On the other hand, when the impact is repeatedly applied, a high impact resistance of the cementitious composites could be observed, which was attributed to the dense microstructures. Moreover, instead of instable and uneven output of electrical resistivity during cyclical compression, more stable and uniform fractional changes of resistivity were achieved after exposed to impact load. However, severe nonlinearity with swift resistivity reduction of cementitious composites under low loads was observed at the beginning and the end of cyclic compression after subjected to many impacts with impact energy of 18.72 × 10−4 J/cm3. The related outcomes of smart conductive cementitious composites subjected to cyclic compression and impact will provide an insight into the stable electrical signal output and promote the applications of cement-based sensors for structural health monitoring under various loading conditions.
Dong, W, Li, W, Wang, K, Guo, Y, Sheng, D & Shah, SP 2020, 'Piezoresistivity enhancement of functional carbon black filled cement-based sensor using polypropylene fibre', Powder Technology, vol. 373, pp. 184-194.
View/Download from: Publisher's site
View description>>
In this study, different dosages of carbon black (CB) and polypropylene (PP) were added to develop functional cementitious composites as cement-based sensors. The results show that electrical conductivity increased with the amount of PP fibres, due to the enclosed CB nanoparticles and more conductive passages. The compressive strength slightly decreased, while the flexural strength was significantly increased with the increased amount of PP fibres. The improvement is mainly achieved by the reduced CB concentration in cement matrix and the excellent tensile strength of PP fibres. Under the cyclic compression, the piezoresistivity increased by three times for 0.4 wt% PP fibres filled CB/cementitious composite, regardless of the loading rates. The flexural stress sensing efficiency was considerably lower than that of compressive stress sensing, but it increased with the amount of PP fibres. Moreover, fitting formulas were proposed and used to evaluate the self-sensing capacity, with the attempts to apply cement-based sensors for structural health monitoring.
Dong, W, Li, W, Wang, K, Han, B, Sheng, D & Shah, SP 2020, 'Investigation on physicochemical and piezoresistive properties of smart MWCNT/cementitious composite exposed to elevated temperatures', Cement and Concrete Composites, vol. 112, pp. 103675-103675.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Piezoresistivity of smart carbon nanotube/cementitious composite has been experimentally investigated, but the piezoresistive performance had been rarely studied when exposed to elevated temperatures. In this study, the physicochemical and mechanical properties, and piezoresistive behaviours of multi-walled carbon nanotube (MWCNT) reinforced smart cementitious composite were investigated under heat treatments of elevated temperatures of 300 °C and 600 °C. The microstructures, crystal deterioration and thermal gravity relationships were characterized by scanning electron microscope (SEM), X-ray diffraction (XRD) and thermos-gravimetric (TG) analysis. The results show that the compressive strength and elastic modulus of MWCNT/cementitious composite after heat treatments gradually decreased, especially under the high temperature of 600 °C. There was a sudden growth of fractional changes of resistivity (FCR) after heat treatment. The higher temperature treatments led to more extensive sudden increase in the piezoresistivity. In the linear part of the relationship curves of FCR to the strain, the gauge factor even increased at the temperature of 300 °C. Moreover, the mechanism for the altered piezoresistivity was fundamentally explained and discussed by the MWCNT purification and destructions of MWCNT, cement matrix and agglomerations after heat treatments. Therefore, the related outcomes will promote the understanding and application of smart MWCNT/cementitious composite for structural health monitoring (SHM) under extreme environments.
Dong, W, Li, W, Wang, K, Luo, Z & Sheng, D 2020, 'Self-sensing capabilities of cement-based sensor with layer-distributed conductive rubber fibres', Sensors and Actuators A: Physical, vol. 301, pp. 111763-111763.
View/Download from: Publisher's site
Dong, Y & Fatahi, B 2020, 'Discrete element simulation of cavity expansion in lightly cemented sands considering cementation degradation', Computers and Geotechnics, vol. 124, pp. 103628-103628.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd This study aims to investigate the influence of cementation on the stress-strain and strength characteristics of soil during cavity expansion in lightly cemented sand deposit using three-dimensional discrete element simulations. Contact models, simulating the cementation effects of bonded clumps and capturing the interlocking effects between discrete sand particles, are incorporated to mimic the cemented sands with various cement contents. The microscopic parameters are calibrated and validated against existing experimental results. Real scale cylindrical cavity expansion models starting from zero initial cavity radius with different levels of cementation are developed, and each proposed model consists of 150,000 particles with boundary conditions carefully selected to reproduce the realistic scenario. The embedded scripting is utilised to precisely measure both the local and global stress–strain variations, and record and analyse the cementation bond breakage during the cavity expansion process. The results confirm that the cementation enhances the material strength through the increase in cohesion and tensile strength at the contacting interfaces, whereas the friction angle is not altered notably. Hence, the failure envelope of the cemented sand gradually merges with the critical state line due to the cementation degradation, particularly at a high confining pressure. It was found that the failure mode of the lightly cemented sand adopted in this study, was mainly controlled by the shear rather than tensile strength at the contacting interfaces. Referring to the numerical predictions it is evident that the zone with significant cementation degradation due to the cavity expansion extends as far as 4af for all cemented specimens (af being the final cavity radius). In addition, specimens with higher cement content experience a more pronounced dilation at the internal cavity wall, while an inverse trend is captured at a greater radial ...
Dong, Y, Fatahi, B & Khabbaz, H 2020, 'Three dimensional discrete element simulation of cylindrical cavity expansion from zero initial radius in sand', Computers and Geotechnics, vol. 117, pp. 103230-103230.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd This study seeks to assess the influence of choice of initial cavity radius on the soil response during cavity expansion in sandy soil adopting three-dimensional discrete element simulations and obtaining the size of the influence zone when the expansion starts from zero initial radius. Sandy soil is modelled adopting rolling resistance contact model to capture the effects of particle interlocking, and the microscopic parameters are calibrated utilising linear model deformability method for both loose and dense sands against experimental results. Four cylindrical cavity expansions that commenced from different initial radii are simulated in dense and loose sand specimens. The large-scale three-dimensional model is proposed with more than 500,000 particles, enabling precise volumetric dilation and contraction predictions using strain rate tensors. During the cavity expansion process, cavity pressure is constantly recorded by appropriate subroutines, while the stress-strain and void ratio variations are continuously monitored using an array of prediction spheres situated close to the internal cavities. The results confirm that the initial cavity radius chosen has conspicuous effects on the cavity pressure, the stress path, the volumetric strain and the deviatoric stress, especially at the initial stage of expansion; however, these effects become less pronounced and are ultimately minor as the cavity reaches full expansion. The results confirmed that given the same expansion volume, the pressure required to create a cavity is significantly larger than expanding an existing cavity in the same soil medium, whereas the pressure needed to maintain an already expanded cavity is not sensitive to the choice of initial cavity radius. The results obtained were further validated adopting the variations of stress path, deviatoric stress and volumetric strain in the vicinity of the cavity wall. The findings from this study may provide practicing en...
Du, X, Yin, H, Chen, L, Wang, Y, Yang, Y & Zhou, X 2020, 'Personalized Video Recommendation Using Rich Contents from Videos', IEEE Transactions on Knowledge and Data Engineering, vol. 32, no. 3, pp. 492-505.
View/Download from: Publisher's site
View description>>
IEEE Video recommendation has become an essential way of helping people explore the massive videos and discover the ones that may be of interest to them. In the existing video recommender systems, the models make the recommendations based on the user-video interactions and single specific content features. When the specific content features are unavailable, the performance of the existing models will seriously deteriorate. Inspired by the fact that rich contents (e.g., text, audio, motion, and so on) exist in videos, in this paper, we explore how to use these rich contents to overcome the limitations caused by the unavailability of the specific ones. Specifically, we propose a novel general framework that incorporates arbitrary single content feature with user-video interactions, named as collaborative embedding regression (CER) model, to make effective video recommendation in both in-matrix and out-of-matrix scenarios. Our extensive experiments on two real-world large-scale datasets show that CER beats the existing recommender models with any single content feature and is more time efficient. In addition, we propose a priority-based late fusion (PRI) method to gain the benefit brought by the integrating the multiple content features. The corresponding experiment shows that PRI brings real performance improvement to the baseline and outperforms the existing fusion methods.
Eldosouky, AM, Pham, LT, Mohmed, H & Pradhan, B 2020, 'A comparative study of THG, AS, TA, Theta, TDX and LTHG techniques for improving source boundaries detection of magnetic data using synthetic models: A case study from G. Um Monqul, North Eastern Desert, Egypt', Journal of African Earth Sciences, vol. 170, pp. 103940-103940.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The boundaries detection techniques have a great role in enhancing and interpreting the geologic features of magnetic data. In the literature, several filters (THG, AS, TA, NTilt, Theta, TDX, TAHG, LTHG) for identifying the boundaries of the magnetic sources have been suggested. These methods are generally performed based on gradients (vertical and horizontal) of the potential field. This paper presents a comparative investigation of different boundary detection filters including THG (total horizontal gradient), AS (analytical signal), TA (tilt angle), Theta (Cos θ), TDX (horizontal tilt angle), and LTHG (Logistic function of the THG). The effect of each filter was examined on two synthetic magnetic data sets. Moreover, the filters are also applied to a real magnetic data set from the Gabal (G) Um Monqul, North Eastern Desert (NED) of Egypt. The obtained results were correlated with known geologic structures of the study area. From the comparison between several applied methods, the horizontal boundaries of geologic sources obtained by the LTHG were found to be sharper and clearer than other ones. The results confirm that the LTHG method is an effective filter for interpreting aeromagnetic data qualitatively and can be applied for enhancing the source edges of different potential field datasets.
Fanos, AM, Pradhan, B, Alamri, A & Lee, C-W 2020, 'Machine Learning-Based and 3D Kinematic Models for Rockfall Hazard Assessment Using LiDAR Data and GIS', Remote Sensing, vol. 12, no. 11, pp. 1755-1755.
View/Download from: Publisher's site
View description>>
Rockfall is one of the most hazardous phenomena in mountainous and hilly regions with high and steep terrain. Such incidents can cause massive damage to people, properties, and infrastructure. Therefore, proper rockfall hazard assessment methods are required to save lives and provide a guide for the development of an area. The aim of this research is to develop a method for rockfall hazard assessment at two different scales (regional and local). A high-resolution airborne laser scanning (ALS) technique was utilized to derive an accurate digital terrain model (DTM); next, a terrestrial laser scanner (TLS) was used to capture the topography of the two most critical areas within the study area. A staking machine-learning model based on different classifiers, namely logistic regression (LR), random forest (RF), artificial neural network (ANN), support vector machine (SVM), and k-nearest neighbor (KNN), was optimized and employed to determine rockfall probability by utilizing various rockfall conditioning factors. A developed 3D rockfall kinematic model was used to obtain rockfall trajectories, velocity, frequency, bouncing height, kinetic energy, and impact location. Next, a spatial model combined with a fuzzy analytical hierarchy process (fuzzy-AHP) integrated in the Geographic Information System (GIS) was developed to assess rockfall hazard in two different areas in Ipoh, Malaysia. Additionally, mitigation processes were suggested and assessed to provide a comprehensive information for urban planning management. The results show that, the stacking random forest–k-nearest neighbor (RF-KNN) model is the best hybrid model compared to other tested models with an accuracy of 89%, 86%, and 87% based on training, validation, and cross-validation datasets, respectively. The three-dimension rockfall kinematic model was calibrated with an accuracy of 93% and 95% for the two study areas and subsequently the rockfall trajectories and their characteristics wer...
Fatahi, B, Huang, B, Yeganeh, N, Terzaghi, S & Banerjee, S 2020, 'Three-Dimensional Simulation of Seismic Slope–Foundation–Structure Interaction for Buildings Near Shallow Slopes', International Journal of Geomechanics, vol. 20, no. 1, pp. 04019140-04019140.
View/Download from: Publisher's site
View description>>
© 2019 American Society of Civil Engineers. Buildings constructed adjacent to the slope crest in seismically active areas might be exposed to serious danger when they are subjected to strong earthquake excitations. The ground conditions can influence the seismic response of structures through a phenomenon known as the slope-foundation-structure interaction. Indeed, the presence of the slope in the vicinity of a building foundation can significantly affect the seismic response of the superstructure. In this study, the impact of shallow slopes on the seismic performance of nearby buildings was numerically assessed. In the adopted three-dimensional finite-element simulation, the nonlinear variations of the soil stiffness and damping with the cyclic shear strain plus varying distances between the edge of the foundation and crest of the slope were employed. A 15-story moment-resisting structure, a 30-m-thick clayey deposit, and a 2-m-high shallow slope were considered as the benchmark model, being simulated using the direct method in the time domain. According to the results of the analyses, the seismic response of a building could be highly sensitive to the distance between the slope crest and foundation. Particularly, the building closer to the slope crest experienced more severe foundation rocking, lateral deformation, and interstory drifts owing to the amplified effect of the slope-foundation-structure interaction. Moreover, the results highlighted the importance of the slope-foundation-structure interaction in altering the natural period and damping of the system. Hence, it is critical for practicing engineers to assess the impact of nearby slopes on the seismic performance of structures with extreme care to ensure the reliability and safety of the design.
Ghasemkhani, N, Vayghan, SS, Abdollahi, A, Pradhan, B & Alamri, A 2020, 'Urban Development Modeling Using Integrated Fuzzy Systems, Ordered Weighted Averaging (OWA), and Geospatial Techniques', Sustainability, vol. 12, no. 3, pp. 809-809.
View/Download from: Publisher's site
View description>>
This paper proposes a model to identify the changing of bare grounds into built-up or developed areas. The model is based on the fuzzy system and the Ordered Weighted Averaging (OWA) methods. The proposed model consists of four main sections, which include physical suitability, accessibility, the neighborhood effect, and a calculation of the overall suitability. In the first two parts, physical suitability and accessibility were obtained by defining fuzzy inference systems and applying the required map data associated with each section. However, in order to calculate the neighborhood effect, we used an enrichment factor method and a hybrid method consisting of the enrichment factor with the Few, Half, Most, and Majority quantifiers of the ordered weighted averaging (OWA) method. Finally, the three maps of physical suitability, accessibility, and the neighborhood effect were integrated by the fuzzy system method and the quantifiers of OWA to obtain the overall suitability maps. Then, the areas with high suitability were selected from the overall suitability map to be changed from bare ground into built-up areas. For this purpose, the proposed model was implemented and calibrated in the first period (2004–2010) and was evaluated by being applied to the second period (2010–2016). By comparing the estimated map of changes to the reference data and after the formation of the error matrix, it was determined that the OWA-Majority method has the best estimation compared to those of the other methods. Finally, the total accuracy and the Kappa coefficient for the OWA-Majority method in the second period were 98.98% and 98.98%, respectively, indicating this method’s high accuracy in predicting changes. In addition, the results were compared with those of other studies, which showed the effectiveness of the suggested method for urban development modeling.
Ghosh, S, Das, A, Hembram, TK, Saha, S, Pradhan, B & Alamri, AM 2020, 'Impact of COVID-19 Induced Lockdown on Environmental Quality in Four Indian Megacities Using Landsat 8 OLI and TIRS-Derived Data and Mamdani Fuzzy Logic Modelling Approach', Sustainability, vol. 12, no. 13, pp. 5464-5464.
View/Download from: Publisher's site
View description>>
The deadly COVID-19 virus has caused a global pandemic health emergency. This COVID-19 has spread its arms to 200 countries globally and the megacities of the world were particularly affected with a large number of infections and deaths, which is still increasing day by day. On the other hand, the outbreak of COVID-19 has greatly impacted the global environment to regain its health. This study takes four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. An environmental quality index was formulated using remotely sensed biophysical parameters like Particulate Matters PM10 concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). Fuzzy-AHP, which is a Multi-Criteria Decision-Making process, has been utilized to derive the weight of the indicators and aggregation. The results showing that COVID-19 induced lockdown in the form of restrictions on human and vehicular movements and decreasing economic activities has improved the overall quality of the environment in the selected Indian cities for a short time span. Overall, the results indicate that lockdown is not only capable of controlling COVID-19 spread, but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.
Gong, S, Oberst, S & Wang, X 2020, 'An experimentally validated rubber shear spring model for vibrating flip-flow screens', Mechanical Systems and Signal Processing, vol. 139, pp. 106619-106619.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Vibrating flip-flow screens (VFFS) provide an effective solution for screening highly moist and fine-grained minerals, and the dynamic response of the main and the floating screen frames largely accounts for a VFFS's screening performance and its processing capacity. An accurate dynamic model of the rubber shear springs inserted between the frames of the VFFS is critical for its dynamic analysis but has rarely been studied in detail. In this paper, a variance-based global sensitivity analysis is applied to actually illustrate that the rubber shear spring is the most important component for the dynamics of VFFS. Then a nonlinear rubber shear spring model is proposed to predict its amplitude and frequency dependency, which is described by a friction model and a fractional derivative viscoelastic model, respectively, and the elasticity is predicted by a nonlinear spring. The reasonability of the proposed model is verified by experimental cyclic tests of the rubber shear spring. Comparisons between the newly proposed model and other classic models, including the Generalized Maxwell model, adopted for the dynamic analysis of the VFFS are carried out, and experimental tests of an industrial VFFS's dynamic response show that dynamics of the VFFS can be better described using the proposed model than the existing models. Furthermore, the method of the global sensitivity analysis is also applied to the newly VFFS dynamic model to calculate the sensitivities of model outputs caused by the input parameters. The results reveal that the dynamic response of an operating VFFS is most sensitive to changes in the stiffness of the rubber shear spring, followed by the mass of the floating screen frames.
Gu, X, Li, J & Li, Y 2020, 'Experimental realisation of the real‐time controlled smart magnetorheological elastomer seismic isolation system with shake table', Structural Control and Health Monitoring, vol. 27, no. 1.
View/Download from: Publisher's site
View description>>
© 2019 John Wiley & Sons, Ltd. Traditional base isolation protects structures against severe seismic events by providing a designated lateral flexibility at the base level of the structures. Due to its inherent passive nature, in the design process, compromises have to be made among performance of different design targets (displacements, interstorey drifts, accelerations, etc.). In addition, as the working principle, the effectiveness of a base isolation relies on the degree of “decoupling” between ground excitation and superstructure. However, a higher degree of decoupling compromises the stability of the structures. In other words, for a base solation system, it possesses inherent conflicts between the effectiveness of the isolation and the lateral stability of the structure. A concept of new smart base isolation system is proposed, in which real-time controllable decoupling for a base isolation structure is achieved by employing magnetorheological elastomer (MRE) base isolators. With controllable lateral stiffness, the smart base isolation system can achieve an optimal decoupling by instantly shifting the structure's natural frequencies to a nonresonant region. This paper aims at experimentally proving and validating this innovative concept, including designing a three-storey shear building model equipped with MRE base isolators, demonstrating the feasibility and evaluating the performance of the proposed system by a series of shake table testing. The comprehensive experimental design and results of shake table testing have concept-proved the proposed smart MRE base isolation system for future development in practical applications.
Gupta, A, Pradhan, B & Maulud, KNA 2020, 'Estimating the Impact of Daily Weather on the Temporal Pattern of COVID-19 Outbreak in India', Earth Systems and Environment, vol. 4, no. 3, pp. 523-534.
View/Download from: Publisher's site
View description>>
AbstractThe COVID-19 pandemic has spread obstreperously in India. The increase in daily confirmed cases accelerated significantly from ~ 5 additional new cases (ANC)/day during early March up to ~ 249 ANC/day during early June. An abrupt change in this temporal pattern was noticed during mid-April, from which can be inferred a much reduced impact of the nationwide lockdown in India. Daily maximum (TMax), minimum (TMin), mean (TMean) and dew point temperature (TDew), wind speed (WS), relative humidity, and diurnal range in temperature and relative humidity during March 01 to June 04, 2020 over 9 major affected cities are analyzed to look into the impact of daily weather on COVID-19 infections on that day and 7, 10, 12, 14, 16 days before those cases were detected (i.e., on the likely transmission days). Spearman’s correlation exhibits significantly lower association with WS,TMax,TMin,TMean,TDew, but is comparatively better with a lag of 14 days. Support Vector regression successfully estimated the count of confirmed cases (R2 > 0.8) at a lag of 12–16 days, thus reflecting a probable incubation period of 14 ± 02 days in India. Approximately 75% of total cases were registered whenTMax,TMean,TMin,TDew, and WS at 12–16 days previously were varying within the range of 33.6–41.3 °C, 29.8–36.5 °C, 24.8–30.4 °C, 18...
Hakdaoui, S, Emran, A, Pradhan, B, Qninba, A, Balla, TE, Mfondoum, AHN, Lee, C-W & Alamri, AM 2020, 'Assessing the Changes in the Moisture/Dryness of Water Cavity Surfaces in Imlili Sebkha in Southwestern Morocco by Using Machine Learning Classification in Google Earth Engine', Remote Sensing, vol. 12, no. 1, pp. 131-131.
View/Download from: Publisher's site
View description>>
Imlili Sebkha is a stable and flat depression in southern Morocco that is more than 10 km long and almost 3 km wide. This region is mainly sandy, but its northern part holds permanent water pockets that contain fauna and flora despite their hypersaline water. Google Earth Engine (GEE) has revolutionized land monitoring analysis by allowing the use of satellite imagery and other datasets via cloud computing technology and server-side JavaScript programming. This work highlights the potential application of GEE in processing large amounts of satellite Earth Observation (EO) Big Data for the free, long-term, and wide spatio-temporal wet/dry permanent salt water cavities and moisture monitoring of Imlili Sebkha. Optical and radar images were used to understand the functions of Imlili Sebkha in discovering underground hydrological networks. The main objective of this work was to investigate and evaluate the complementarity of optical Landsat, Sentinel-2 data, and Sentinel-1 radar data in such a desert environment. Results show that radar images are not only well suited in studying desertic areas but also in mapping the water cavities in desert wetland zones. The sensitivity of these images to the variations in the slope of the topographic surface facilitated the geological and geomorphological analyses of desert zones and helped reveal the hydrological functions of Imlili Sebkha in discovering buried underground networks.
Halkon, BJ & Rothberg, SJ 2020, 'Establishing correction solutions for Scanning Laser Doppler Vibrometer measurements affected by sensor head vibration', Mechanical Systems and Signal Processing, vol. 150.
View/Download from: Publisher's site
View description>>
Scanning Laser Doppler Vibrometer (SLDV) measurements are affected by sensorhead vibrations as if they are vibrations of the target surface itself. Thispaper presents practical correction schemes to solve this important problem.The study begins with a theoretical analysis, for arbitrary vibration and anyscanning configuration, which shows that the only measurement required is ofthe vibration velocity at the incident point on the final steering mirror inthe direction of the outgoing laser beam and this underpins the two correctionoptions investigated. Correction sensor location is critical; the first schemeuses an accelerometer pair located on the SLDV front panel, either side of theemitted laser beam, while the second uses a single accelerometer located alongthe optical axis behind the final steering mirror. Initial experiments with avibrating sensor head and stationary target confirmed the sensitivity to sensorhead vibration together with the effectiveness of the correction schemes whichreduced overall error by 17 dB (accelerometer pair) and 27 dB (singleaccelerometer). In extensive further tests with both sensor head and targetvibration, conducted across a range of scan angles, the correction schemesreduced error by typically 14 dB (accelerometer pair) and 20 dB (singleaccelerometer). RMS phase error was also up to 30% lower for the singleaccelerometer option, confirming it as the preferred option. The theorysuggests a geometrical weighting of the correction measurements and thisprovides a small additional improvement. Since the direction of the outgoinglaser beam and its incident point on the final steering mirror both change asthe mirrors scan the laser beam, the use of fixed axis correction transducersmounted in fixed locations makes the correction imperfect. The associatederrors are estimated and expected to be generally small, and the theoreticalbasis...
Hayati, H, Eager, D, Peham, C & Qi, Y 2020, 'Dynamic Behaviour of High Performance of Sand Surfaces Used in the Sports Industry', Vibration, vol. 3, no. 4, pp. 410-424.
View/Download from: Publisher's site
View description>>
The sand surface is considered a critical injury and performance contributing factor in different sports, from beach volleyball to greyhound racing. However, there is still a significant gap in understanding the dynamic behaviour of sport sand surfaces, particularly their vibration behaviour under impact loads. The purpose of this research was to introduce different measurement techniques to the study of sports sand surface dynamic behaviour. This study utilised an experimental drop test, accelerometry, in-situ moisture content and firmness data, to investigate the possible correlation between the sand surface and injuries. The analysis is underpinned by data gathered from greyhound racing and discussed where relevant.
He, B, He, N, Xu, BH, Cai, R, Shao, HL & Zhang, QL 2020, 'Tests on distributed monitoring of deflection of concrete faces of CFRDs', Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering, vol. 42, no. 5, pp. 837-844.
View/Download from: Publisher's site
View description>>
Ensuring the safety of concrete faces is the key to the safe operation of concrete face rockfill dams (CFRDs). The deflection is an important index to monitor the integrity of a concrete face. Based on the distributed optical fiber sensing technology, a new technology is proposed to monitor the deflection of concrete faces of CFRDs, and systematic tests are carried out to verify the measurement accuracy of this new technology as well as its feasibility. Based on the Matlab program and the quasi-distributed scatter strain test data, a method for calculating deflection is established. The research findings show that the calculated deflection at each measurement point on the concrete face is consistent with the measured one at the corresponding position (the absolute error is 5 mm, and the average relative error is 3%). It is validated that this new technology can monitor the deflection including irregular deflection with millimeter accuracy. It is also suitable for the distributed monitoring of the deflection of the full section of concrete faces and the measurement of large deflection. The proposed advanced technology is proved to be applicable to monitoring the deflection of the entire concrete face of a 300-meter level CFRD in a distributed manner.
He, X, Wu, W, Cai, G, Qi, J, Kim, JR, Zhang, D & Jiang, M 2020, 'Work–energy analysis of granular assemblies validates and calibrates a constitutive model', Granular Matter, vol. 22, no. 1.
View/Download from: Publisher's site
He, X, Xu, H, Li, W & Sheng, D 2020, 'An improved VOF-DEM model for soil-water interaction with particle size scaling', Computers and Geotechnics, vol. 128, pp. 103818-103818.
View/Download from: Publisher's site
View description>>
© 2020 This study presents an improved VOF-DEM model where the Darcian velocity and a compound variable are treated as unknowns in the pressure-velocity calculation procedure such that the use of interpolated porosity at cell faces is minimised and stability is ensured even if the porosity field is not smooth or even ragged. A higher-order porosity estimation method is also used such that the porosity and interaction force are evaluated correctly when the CFD cell size is of the same order as the DEM particle size. Additionally, a particle size scaling technique is proposed to let the DEM particle size different from the real soil particle size and soil-water interaction forces are the same as when the real soil particle size is used. This is achieved by modifying the calculation of drag force. The solution scheme is verified in two case where analytical solutions exist. Particle size scaling technique is also used and tested in permeability tests and wave interaction with porous structure. Subsequently, the settling and collision of particles in water, dambreak of soil-water mixture and submerged landslides are simulated. With the present improvements and the particle size scaling, the capability of the VOF-DEM is extended in soil-water interaction problems.
He, X, Xu, H, Sabetamal, H & Sheng, D 2020, 'Machine learning aided stochastic reliability analysis of spatially variable slopes', Computers and Geotechnics, vol. 126, pp. 103711-103711.
View/Download from: Publisher's site
View description>>
© 2020 This paper presents machine learning aided stochastic reliability analysis of spatially variable slopes, which significantly reduces the computational efforts and gives a complete statistical description of the factor of safety with promising accuracy compared with traditional methods. Within this framework, a small number of traditional random finite-element simulations are conducted. The samples of the random fields and the calculated factor of safety are, respectively, treated as training input and output data, and are fed into machine learning algorithms to find mathematical models to replace finite-element simulations. Two powerful machine learning algorithms used are the neural networks and the support-vector regression with their associated learning strategies. Several slopes are examined including stratified slopes with 3 or 4 layers described by 4 or 6 random fields. It is found that with 200 to 300 finite-element simulations (finished in about 5 ~ 8 h), the machine-learning generated model can predict the factor of safety accurately, and a stochastic analysis of 105 samples takes several minutes. However, the same traditional analysis would require hundreds of days of computation.
He, Z, Teng, J, Yang, Z, Liang, L, Li, H & Zhang, S 2020, 'An analysis of vapour transfer in unsaturated freezing soils', Cold Regions Science and Technology, vol. 169, pp. 102914-102914.
View/Download from: Publisher's site
Hoque, MA-A, Pradhan, B & Ahmed, N 2020, 'Assessing drought vulnerability using geospatial techniques in northwestern part of Bangladesh', Science of The Total Environment, vol. 705, pp. 135957-135957.
View/Download from: Publisher's site
Horry, MJ, Chakraborty, S, Paul, M, Ulhaq, A, Pradhan, B, Saha, M & Shukla, N 2020, 'COVID-19 Detection Through Transfer Learning Using Multimodal Imaging Data', IEEE Access, vol. 8, pp. 149808-149824.
View/Download from: Publisher's site
Indraratna, B, Israr, J & Vaughan, LPR 2020, 'From Particles to Constrictions: Scientific Evolution of Enhanced Criteria for Internal Stability Assessment of Soils', Geotechnical Engineering, vol. 51, no. 3, pp. 65-72.
View description>>
Internal instability occurs when steady seepage forces erode the finer fractions from non-uniform soils along pre-existing openings such as cracks in cohesive soils and voids in non-cohesive soil to induce permanent changes in the original particle size distribution. Given that the drainage characteristics of soils are significantly influenced by the shape, packing arrangement, compaction, and size distribution of their particles, even limited erosion can markedly alter their drainage characteristics. The geometrical assessment of internal instability potential is normally conducted using classical filter retention criterion based on mere particle size distribution and without giving due consideration to the above factors. These methods would determine the risk of instability by approximating the soil’s constrictions based on its particle size distribution; these constrictions are pore channels connecting neighbouring void spaces that would control both permeability and retention phenomena. However, recent advances in mathematical computations have facilitated the exact delineation of constriction sizes and the introduction of more accurate constriction based methods. This study purports to shed light on the scientific evolution of particle and constriction based methods over the past four decades, including the enhanced accuracy, reduced bias, and robustness associated with the latter. An interesting case study from our experience of using these approaches for a permeable barrier design at Bomaderry, NSW (Australia) for subsurface flow treatment is presented, and recommendations for their use by practicing engineers are made to conclude this study.
Indraratna, B, Korkitsuntornsan, W & Nguyen, TT 2020, 'Influence of Kaolin content on the cyclic loading response of railway subgrade', Transportation Geotechnics, vol. 22, pp. 100319-100319.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Rail tracks passing through saturated subgrade soil often face a serious deterioration of bearing capacity and excessive deformation. One major reason is the excessive cyclic pore pressure that accumulates under the track that leads to soil softening and infiltration over the surface, i.e., subgrade mud pumping (fluidization). Although this issue has received considerable attention in recent decades, how the cyclic stress ratio and soil properties such as plasticity and void ratio influence the cyclic loading response of soft subgrade soil is still not properly understood. In this study, Kaolin – an artificial cohesive fines soil is used to modify a low plasticity subgrade soil to examine how the Kaolin content (cK) can affect its cyclic response. Soil specimens including the original soil and its mixture with 10 and 30% of Kaolin have been subjected to undrained cyclic testing. A cyclic stress ratio (CSR) varying from 0.2 to 1.2 is used and a low initial confining pressure of 20 kPa is applied. The results show 3 different responses of soil, i.e., (i) stable, (ii) cyclic undrained failure, and (iii) fluidization, depending on the magnitude of CSR. Where fluidization becomes imminent, the shear stress rapidly decreases at early stages. Adding cohesive fines, i.e., Kaolin reduces the static undrained shear strength and increases the plasticity index. This enables the test specimen to undergo a larger number of cycles (N) before failure, thus enhancing its resistance to fluidization. Specimens with a smaller initial void ratio, i.e., greater level of compaction, are less susceptible to fluidization because they can withstand larger CSR and N. Moreover, this study shows where there is potential fluidization upon cyclic loading, a significant redistribution of the water content seems to occur over the height of the test specimens.
Indraratna, B, Medawela, S, Rowe, K, Thamwattana, N & Heitor, A 2020, 'Bio-Geochemical clogging of Permeable Reactive Barriers in Acid Sulphate Soil Floodplain', Journal of Geotechnical and Geoenvironmental Engineering, vol. 146, no. 5.
Indraratna, B, Medawela, S, Rowe, RK, Thamwattana, N & Heitor, A 2020, 'Biogeochemical Clogging of Permeable Reactive Barriers in Acid-Sulfate Soil Floodplain', Journal of Geotechnical and Geoenvironmental Engineering, vol. 146, no. 5, pp. 04020015-04020015.
View/Download from: Publisher's site
View description>>
Column experiments that investigate the use of calcitic limestone as a potential material for permeable reactive barriers (PRBs), as well as its clogging behavior, are conducted under conditions that involve continuous acidic flow containing Al, Fe, and acidophilic bacteria. Results show that nonhomogenous biogeochemical clogging occurred toward the outlet, resulting in a 45% reduction of hydraulic conductivity at the inlet and 10% reduction at the outlet after the bicarbonate buffering period. A mathematical model developed to capture the reductions in longevity is presented. The model, which considers the effects of time-varying porosity, hydraulic conductivity, and head at a particular point on the horizontal flow path, is used for assessing the effect of coupled clogging in a calcitic porous medium.
Indraratna, B, Ngo, T & Rujikiatkamjorn, C 2020, 'Performance of Ballast Influenced by Deformation and Degradation: Laboratory Testing and Numerical Modeling', International Journal of Geomechanics, vol. 20, no. 1, pp. 04019138-04019138.
View/Download from: Publisher's site
View description>>
© 2019 American Society of Civil Engineers. This paper presents a study on the deformation and degradation responses of railway ballast using large-scale laboratory testing and computational modeling approaches. A series of large-scale triaxial tests were carried out to investigate the ballast breakage responses under cyclic train loading subjected to varying frequencies, f=10-40 Hz. The role of recycled rubber energy-absorbing mats (REAMs) on reducing ballast breakage was also examined. Laboratory test results show that the ballast experiences significant degradation (breakage) and deformation, while the inclusion of REAMs can reduce the ballast breakage up to about 35%. Numerical modeling using the coupled discrete-continuum approach [coupled discrete-element method-finite-difference method (DEM-FDM)] is introduced to provide insightful understanding on the deformation and breaking of ballast under cyclic loading. Discrete ballast grains were simulated by bonding of many circular elements together at appropriate sizes and locations. Selected cylinders located at corners, surfaces, and sharp edges of the simulated particles were connected by parallel bonds; and when those bonds were broken, they were considered to represent ballast breakage. The subgrade and rubber mat were simulated as a continuum media using FDM. The predicted axial strain ϵa and volumetric strain ϵv obtained from the coupled DEM-FDM model are in good agreement with those measured in the laboratory. The model was then used to explore micromechanical aspects of ballast aggregates including the evolution of particle breakage, contact force distributions, and orientation of contacts during cyclic loading. These findings are imperative for a more insightful understanding of the breakage behavior of ballast from the perspective of microstructure characteristics of discrete particle assemblies.
Indraratna, B, Ngo, T, Bessa Ferreira, F, Rujikiatkamjorn, C & Shahkolahi, A 2020, 'Laboratory examination of ballast deformation and degradation under impact loads with synthetic inclusions', Transportation Geotechnics, vol. 25, pp. 100406-100406.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd This paper presents a laboratory study on alleviating the deformation and degradation (breakage) of ballast subjected to impact loads using geogrids and rubber mats. A series of drop hammer impact tests are carried out to determine how well the geogrid, under-ballast mat (UBM) or under-sleeper pad (USP) can attenuate impact loads and mitigate ballast degradation. Geogrids to be placed at different locations in a ballast assembly, in combination either with a UBM or a USP are tested. Laboratory test results prove that the inclusion of rubber mats and geogrids decrease the dynamic impact loads transferred to the ballast aggregates and subsequently decrease the degradation (breakage) and deformation of ballast. The tensile strength of geogrids and subgrade stiffness are found to considerably influence the performance of geogrid-reinforced ballast under impact loading conditions. The measured impact forces and accelerations of ballast with and without an artificial inclusion show that rubber mats definitely reduce track vibration (acceleration) and the subsequent deformation and breakage of ballast. These inclusions will not only increase safety and passenger comfort they will also lead to more economical and efficient track designs.
Indraratna, B, Singh, M & Nguyen, TT 2020, 'The mechanism and effects of subgrade fluidisation under ballasted railway tracks', Railway Engineering Science, vol. 28, no. 2, pp. 113-128.
View/Download from: Publisher's site
View description>>
AbstractThe rapid growth in railway infrastructure and the construction of high-speed heavy-haul rail network, especially on ground that is basically unsuitable, poses challenges for geotechnical engineers because a large part of the money invested in the development of railway lines is often spent on track maintenance. In fact around the world, the mud pumping of subgrade fines is one of the common reasons why track performance deteriorates and track stability is hindered. This article presents a series of laboratory tests to examine following aspects of mud pumping: (1) the mechanisms of subgrade fluidisation under undrained condition, (2) the effects of mud pumping on the engineering characteristics of ballast, and (3) the use of vertical drains to stabilize subgrade under cyclic loads. The undrained cyclic triaxial testing on vulnerable soft subgrade was performed by varying the cyclic stress ratio (CSR) from 0.2 to 1.0 and the loading frequency f from 1.0 to 5.0 Hz. It is seen from the test results that for a specimen compacted at an initial dry density of 1790 kg/m3, the top portion of the specimen fluidises at CSR = 0.5, irrespective of the applied loading frequency. Under cyclic railway loading, the internal redistribution of water at the top of the subgrade layer softens the soil and also reduces its stiffness. In response to these problems, this paper explains how the inclusion of vertical drains in soft subgrade will help to prevent mud pumping by alleviating the build-up of excess pore pressures under moving train loads.
Indraratna, B, Singh, M, Nguyen, TT, Leroueil, S, Abeywickrama, A, Kelly, R & Neville, T 2020, 'Laboratory study on subgrade fluidization under undrained cyclic triaxial loading', Canadian Geotechnical Journal, vol. 57, no. 11, pp. 1767-1779.
View/Download from: Publisher's site
View description>>
A long-term issue that has hampered the efficient operation of heavy-haul tracks is the migration of fluidized fines from the shallow soft subgrade to the overlying ballast, i.e., mud pumping. This paper presents a series of undrained cyclic triaxial tests where realistic cyclic loading conditions were simulated at low confining pressure that is typical of shallow subgrade beneath a ballast track. Subgrade soil specimens with a low-plasticity index collected from a field site with recent history of mud pumping were tested at frequencies from 1.0 to 5.0 Hz and a cyclic stress ratio (CSR) from 0.1 to 1.0. The experimental results indicate that under adverse loading conditions of critical cyclic stress ratio (CSRc) and frequency, there is upward migration of moisture and the finest particles towards the specimen top and this causes the uppermost part of the soil specimen to soften and fluidize. Conversely, a smaller value of CSR tends to maintain stability of the specimen despite the increasing number of loading cycles. It is noteworthy that for any given combination of CSR and frequency, the relative compaction has a significant influence on the cyclic behaviour of the soil and its potential for fluidization.
Jafarizadeh, S, Tofigh, F, Lipman, J & Abolhasan, M 2020, 'Optimizing synchronizability in networks of coupled systems', Automatica, vol. 112, pp. 108711-108711.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd Of collective behaviors in networks of coupled systems, synchronization is of central importance and an extensively studied area. This is due to the fact that it is essential for the proper functioning of a wide variety of natural and engineered systems. Traditionally, uniform coupling strength has been the default choice and the synchronizability measure has been employed for analysis and enhancement of synchronizability. The main drawback of optimizing the synchronizability measure is that it can reach the Pareto frontier but not necessarily a unique point on the Pareto frontier. Additionally, the shortcoming of uniform coupling strength is that it can reach Pareto frontier in specific topologies including edge-transitive graphs. To achieve a unique optimal answer on the Pareto frontier, this paper takes a different approach and addresses the synchronizability in networks of coupled dynamical systems with nonuniform coupling strength and optimizing the synchronizability via maximizing the minimum distance between the nonzero eigenvalues of the Laplacian and the acceptable boundaries for the stability of the system. Furthermore, two solution methods, namely the concave–convex fractional programming and the Semidefinite Programming (SDP) formulations of the problem have been provided. The proposed solution methods have been compared over different topologies and branches of an arbitrary network, where the SDP based approach has shown to be less restricted and more suitable for a wider range of topologies.
Jayasuriya, C, Indraratna, B & Ferreira, FB 2020, 'The Use of Under Sleeper Pads to Improve the Performance of Rail Tracks', Indian Geotechnical Journal, vol. 50, no. 2, pp. 204-212.
View/Download from: Publisher's site
View description>>
© 2020, Indian Geotechnical Society. In recent years, with the growing demand for both passenger and freight mobility, faster and heavier rail traffic has been the norm rather than the exception in many countries. As a result, track geometry and the safety of ballasted rail tracks have been adversely affected, leading to exacerbated maintenance costs. Increased stresses in granular foundation induce progressive track degradation, which can result in excessive vertical and lateral deformation, ballast and subballast fouling and impeded drainage. These effects tend to be more severe at specific locations, such as bridges, level crossings and tunnels (i.e. over stiff subgrade). Finding an economical strategy to mitigate ballast degradation has been a challenging task for practitioners, and the inclusion of energy-absorbing rubber pads underneath the sleepers (under sleeper pads—USPs) to minimise track damage is an attractive solution. This paper presents a laboratory study conducted at the University of Wollongong to investigate the use of USPs as resilient elements in ballasted rail tracks involving a stiff subgrade. Test results have shown a significant improvement in track performance resulting from the use of USPs, whereby it is demonstrated that ballast damage induced by the applied cyclic loads can be reduced due to the favourable damping characteristics of these rubber pads. A significant attenuation in particle breakage was observed along with a reduction in both the vertical settlement and lateral movement of the ballast layer, thereby suggesting that USPs can be an effective means of improving the stability and serviceability of the track system.
Jayawardane, VS, Anggraini, V, Li-Shen, AT, Paul, SC & Nimbalkar, S 2020, 'Strength Enhancement of Geotextile-Reinforced Fly-Ash-Based Geopolymer Stabilized Residual Soil', International Journal of Geosynthetics and Ground Engineering, vol. 6, no. 4.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature Switzerland AG. Soils in their natural form are often deemed unsatisfactory to be directly used as a construction material for their respective applications. Under such circumtances, employment of ground improvement techniques to better suit the soil for its function is typically the most economical approach. Consequently, the present research investigated into the beneficial effect of modernized soil treatment techniques, i.e., geopolymer stabilization using fly ash as the precursor and geotextile reinforcement, on the strength enhancement of natural residual soil. A series of unconsolidated undrained (UU) triaxial compression tests were carried out to assess variation of geopolymer stabilized residual soil strength based on the varying number of geotextile layers, geotextile arrangement, and confining pressures. It was found that the increase in the number of geotextile layers resulted in a corresponding rise in soil strength and stiffness. It was also discovered that placement of geotextile layers at sample regions which suffered the maximum tensile stress–strain during loading was more effective compared to random placement. Soil strength was observed to reduce with increasing confining pressure which demonstrated the effectiveness of utilizing geotextile reinforcement at greater depths below the ground to be less. Failure patterns showed that while unreinforced soil resulted in failure along a shear plane at an approximate angle of 45 + φ/2 (φ: angle of internal friction), reinforced samples demonstrated a bulging failure where the soil between adjacent layers of geotextiles appeared to bulge. The findings deemed the employment of geopolymer stabilization and geotextile reinforcement on natural residual soil very effective with regards to the enhancement of soil strength and stiffness.
Jena, R & Pradhan, B 2020, 'A Model for Visual Assessment of Fault Plane Solutions and Active Tectonics Analysis Using the Global Centroid Moment Tensor Catalog', Earth Systems and Environment, vol. 4, no. 1, pp. 197-211.
View/Download from: Publisher's site
View description>>
In this study, individual fault plane solutions are developed using various methods to improve the understanding of active tectonics on a regional scale. The comparative analysis of a focal mechanism solution (FMS) has not elicited the attention of researchers. Therefore, this study aims (1) to visually analyze the fault plane solution for 20 local faults that are responsible for all the earthquakes that occurred using visualization techniques such as: fault parameters, the linked Bingham method, the ad hoc pressure (P) axis and tension (T) axis method, and the moment tensor method; (2) to identify the best method for FMS; and (3) to understand the active tectonics of a fault population. A comparative analysis of the models is systematically documented to improve the understanding of the methods. An analysis of the overall fault mechanism is conducted for the analytic determination of fault movement using fault population data from the Global Centroid Moment Tensor catalog. The approach used in this work is a newly designed method for analyzing the reliability of various techniques for fault mechanism and overall fault movement research. Findings show that for the fault mechanism analysis, the P and T axes method and the moment tensor method are better than the fault plane solution from the fault parameters and the linked Bingham method based on the input parameters, output information, model outfit, and accuracy. The moment tensor method is one of the best approaches for analyzing fault mechanism because the errors in the nine components used as input data for the modeling are negligible. Meanwhile, the P and T axes method is one of the best techniques for the overall analysis of fault movement. P and T dihedral analysis using Kamb contouring is modeled. It indicates that the overall mechanisms of compression and dilation are features at the NW–SE and E–W directions, respectively. This comprehensive and consistent analysis of the fault mechanism provides an over...
Jena, R & Pradhan, B 2020, 'Integrated ANN-cross-validation and AHP-TOPSIS model to improve earthquake risk assessment', International Journal of Disaster Risk Reduction, vol. 50, pp. 101723-101723.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The current study presents a novel combination of artificial neural network cross-validation (fourfold ANN-CV) with a hybrid analytic hierarchy process-Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) method to improve the earthquake risk assessment (ERA) and applied it to Aceh, Indonesia, to test the model. Recent studies have suggested that neural networks improve probability mapping in a city scale. The network architecture design with probability index remains unexplored in earthquake-based probability studies. This study explored and specified the major indicators needed to improve the predictive accuracy in probability mapping. First, probability mapping was conducted and used for hazard assessment in the next step. Second, a vulnerability map was created based on social and structural factors. Finally, hazard and vulnerability indices were multiplied to produce the ERA, and the population and areas under risk were calculated. Results show that the proposed model achieves 85.4% accuracy, and its consistency ratio is 0.06. Risk varies from very high to high in the city center, approximately covering an area of 23% (14.82 km2) and a total population of 54,695. The model's performance changes on the basis of the input parameters, indicating the selection and importance of input layers on network architecture selection. The proposed model is found to generalize better results than traditional and some existing probabilistic models. The proposed model is simple and transferable to other regions by localizing the input parameters that contribute to earthquake risk mitigation and prevention planning.
Jena, R, Pradhan, B & Alamri, AM 2020, 'Geo-structural stability assessment of surrounding hills of Kuala Lumpur City based on rock surface discontinuity from geological survey data', Arabian Journal of Geosciences, vol. 13, no. 2.
View/Download from: Publisher's site
Jena, R, Pradhan, B & Alamri, AM 2020, 'Susceptibility to Seismic Amplification and Earthquake Probability Estimation Using Recurrent Neural Network (RNN) Model in Odisha, India', Applied Sciences, vol. 10, no. 15, pp. 5355-5355.
View/Download from: Publisher's site
View description>>
The eastern region of India, including the coastal state of Odisha, is a moderately seismic-prone area under seismic zones II and III. However, no major studies have been conducted on earthquake probability (EPA) and hazard assessment (EHA) in Odisha. This paper had two main objectives: (1) to assess the susceptibility of seismic wave amplification (SSA) and (2) to estimate EPA in Odisha. In total, 12 indicators were employed to assess the SSA and EPA. Firstly, using the historical earthquake catalog, the peak ground acceleration (PGA) and intensity variation was observed for the Indian subcontinent. We identified high amplitude and frequency locations for estimated PGA and the periodograms were plotted. Secondly, several indicators such as slope, elevation, curvature, and amplification values of rocks were used to generate SSA using predefined weights of layers. Thirdly, 10 indicators were implemented in a developed recurrent neural network (RNN) model to create an earthquake probability map (EPM). According to the results, recent to quaternary unconsolidated sedimentary rocks and alluvial deposits have great potential to amplify earthquake intensity and consequently lead to acute ground motion. High intensity was observed in coastal and central parts of the state. Complicated morphometric structures along with high intensity variation could be other parameters that influence deposits in the Mahanadi River and its delta with high potential. The RNN model was employed to create a probability map (EPM) for the state. Results show that the Mahanadi basin has dominant structural control on earthquakes that could be found in the western parts of the state. Major faults were pointed towards a direction of WNW–ESE, NE–SW, and NNW–SSE, which may lead to isoseismic patterns. Results also show that the western part is highly probable for events while the eastern coastal part is highly susceptible to seismic amplification. The RNN model achieved an accura...
Jena, R, Pradhan, B & Beydoun, G 2020, 'Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model', International Journal of Disaster Risk Reduction, vol. 46, pp. 101518-101518.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The prerequisite for earthquake risk estimation is vulnerability assessment. Therefore, estimating vulnerability is necessary to reduce future fatalities. This study aims to evaluate the earthquake vulnerability assessment (EVA) in Banda Aceh by using the multi-criteria decision-making approach through an analytical hierarchy process and VIseKriterijumska Optimizacija I Kompromisno Resenje method using a geographical information system. Banda Aceh City is located close to the Great Sumatran Fault in North Sumatra. Several factors were used to produce social vulnerability, structural vulnerability, and geotechnical vulnerability indices. Subsequently, the adopted approaches were integrated and applied to estimate the criteria weight, priority ranking, and alternatives of criterion by applying the pair-wise comparison at all levels. Finally, vulnerability layers were superimposed to estimate the earthquake vulnerability index and produce the vulnerability map. Results showed that the central part of the city exhibits high to very high vulnerability. A tiny part of the northern–central part is under severe vulnerability conditions. The consistency ratios for all three vulnerability layers were 1.9%, 4.6% and 5.5%. The consistency ratios for the final EVA was 1.9%. The developed map revealed that 3.39% of Banda Aceh City falls under very high, 11.86% high, 23.73% medium, 28.82% low, and 32.20% of very low vulnerability areas. The proposed method for the EVA provides useful information that could assist in earthquake disaster mitigation.
Jena, R, Pradhan, B, Al-Amri, A, Lee, CW & Park, H-J 2020, 'Earthquake Probability Assessment for the Indian Subcontinent Using Deep Learning', Sensors, vol. 20, no. 16, pp. 4369-4369.
View/Download from: Publisher's site
View description>>
Earthquake prediction is a popular topic among earth scientists; however, this task is challenging and exhibits uncertainty therefore, probability assessment is indispensable in the current period. During the last decades, the volume of seismic data has increased exponentially, adding scalability issues to probability assessment models. Several machine learning methods, such as deep learning, have been applied to large-scale images, video, and text processing; however, they have been rarely utilized in earthquake probability assessment. Therefore, the present research leveraged advances in deep learning techniques to generate scalable earthquake probability mapping. To achieve this objective, this research used a convolutional neural network (CNN). Nine indicators, namely, proximity to faults, fault density, lithology with an amplification factor value, slope angle, elevation, magnitude density, epicenter density, distance from the epicenter, and peak ground acceleration (PGA) density, served as inputs. Meanwhile, 0 and 1 were used as outputs corresponding to non-earthquake and earthquake parameters, respectively. The proposed classification model was tested at the country level on datasets gathered to update the probability map for the Indian subcontinent using statistical measures, such as overall accuracy (OA), F1 score, recall, and precision. The OA values of the model based on the training and testing datasets were 96% and 92%, respectively. The proposed model also achieved precision, recall, and F1 score values of 0.88, 0.99, and 0.93, respectively, for the positive (earthquake) class based on the testing dataset. The model predicted two classes and observed very-high (712,375 km2) and high probability (591,240.5 km2) areas consisting of 19.8% and 16.43% of the abovementioned zones, respectively. Results indicated that the proposed model is superior to the traditional methods for earthquake probability assessment in terms of accuracy. Asid...
Jena, R, Pradhan, B, Beydoun, G, Al-Amri, A & Sofyan, H 2020, 'Seismic hazard and risk assessment: a review of state-of-the-art traditional and GIS models', Arabian Journal of Geosciences, vol. 13, no. 2.
View/Download from: Publisher's site
View description>>
© 2020, Saudi Society for Geosciences. The historical records of earthquakes play a vital role in seismic hazard and risk assessment. During the last decade, geophysical, geotechnical, geochemical, topographical, geomorphological, geological data, and various satellite images have been collected, processed, and well-integrated into qualitative and quantitative spatial databases using geographical information systems (GIS). Various types of modeling approaches, such as traditional and GIS-based models, are used. Progressively, seismic studies can improve and modify systematic models and standardize the inventory map of earthquake-susceptible regions. Therefore, this paper reviews different approaches, which are organized and discussed on various models primarily used to create an earthquake scenario focusing on hazard and risk assessment. The reviews are divided into two major parts. The first part is the basic principles, data, and the methodology of various models used for seismic hazard and risk assessment. In the second part, a comparative analysis in terms of the limitations and strengths of the models, as well as application variability is presented. Furthermore, the paper includes the descriptions of software, data resources, and major conclusions. The main findings of this review explain that the capability of machine learning techniques regularly enhances the state of earthquake research, which will provide research opportunities in the future. The model suitability depends on the improvement of parameters, data, and methods that could help to prevent future risk. This paper will help researchers further understand the models based on their strengths, limitations, and applicability.
Jena, R, Pradhan, B, Beydoun, G, Alamri, AM, Ardiansyah, Nizamuddin & Sofyan, H 2020, 'Earthquake hazard and risk assessment using machine learning approaches at Palu, Indonesia', Science of The Total Environment, vol. 749, pp. 141582-141582.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. On 28th September 2018, a very high magnitude of earthquake Mw 7.5 struck the Palu city in the Island of Sulawesi, Indonesia. The main objective of this research is to estimate the earthquake risk based on probability and hazard in Palu region using cross-correlation among the derived parameters, Silhouette clustering (SC), pure locational clustering (PLC) based on hierarchical clustering analysis (HCA), convolutional neural network (CNN) and analytical hierarchy process (AHP) techniques. There is no specific or simple way of identifying risks as the definition of risk varies with time and space. The main aim of this study is: i) to conduct the clustering analysis to identify the earthquake-prone areas, ii) to develop a CNN model for probability estimation, and iii) to estimate and compare the risk using two calculation equations (Risk A and B). Owing to its high prediction ability, the CNN model assessed the probability while SC and PLC were implemented to understand the spatial clustering, Euclidean distance among clusters, spatial relationship and cross-correlation among the estimated Mw, PGA and intensity including events depth. Finally, AHP was implemented for the vulnerability assessment. To this end, earthquake probability assessment (EPA), susceptibility to seismic amplification (SSA) and earthquake vulnerability assessment (EVA) results were employed to generate risk A, while earthquake hazard assessment (EHA), SSA and EVA were used to generate risk B. The risk maps were compared and the differences in results were obtained. This research concludes that in the case of earthquake risk assessment (ERA), results obtained in Risk B are better than the risk A. This study achieved 89.47% accuracy for EPA while for EVA a consistency ratio of 0.07. These results have important implications for future large-scale risk assessment, land use planning and hazard mitigation.
Jena, R, Pradhan, B, Beydoun, G, Nizamuddin, Ardiansyah, Sofyan, H & Affan, M 2020, 'Integrated model for earthquake risk assessment using neural network and analytic hierarchy process: Aceh province, Indonesia', Geoscience Frontiers, vol. 11, no. 2, pp. 613-634.
View/Download from: Publisher's site
View description>>
© 2019 China University of Geosciences (Beijing) and Peking University Catastrophic natural hazards, such as earthquake, pose serious threats to properties and human lives in urban areas. Therefore, earthquake risk assessment (ERA) is indispensable in disaster management. ERA is an integration of the extent of probability and vulnerability of assets. This study develops an integrated model by using the artificial neural network–analytic hierarchy process (ANN–AHP) model for constructing the ERA map. The aim of the study is to quantify urban population risk that may be caused by impending earthquakes. The model is applied to the city of Banda Aceh in Indonesia, a seismically active zone of Aceh province frequently affected by devastating earthquakes. ANN is used for probability mapping, whereas AHP is used to assess urban vulnerability after the hazard map is created with the aid of earthquake intensity variation thematic layering. The risk map is subsequently created by combining the probability, hazard, and vulnerability maps. Then, the risk levels of various zones are obtained. The validation process reveals that the proposed model can map the earthquake probability based on historical events with an accuracy of 84%. Furthermore, results show that the central and southeastern regions of the city have moderate to very high risk classifications, whereas the other parts of the city fall under low to very low earthquake risk classifications. The findings of this research are useful for government agencies and decision makers, particularly in estimating risk dimensions in urban areas and for the future studies to project the preparedness strategies for Banda Aceh.
Jena, R, Pradhan, B, Jung, HS, Rai, AK & Rizeei, HM 2020, 'Seasonal water change assessment at Mahanadi River, India using multi-temporal data in Google Earth engine', Korean Journal of Remote Sensing, vol. 36, no. 1, pp. 1-13.
View/Download from: Publisher's site
View description>>
Seasonal changes in river water vary seasonally as well as locationally, and the assessment is essential. In this study, we used the recent technique of post-classification by using the Google earth engine (GEE) to map the seasonal changes in Mahanadi river of Odisha. However, some fixed problems results during the rainy season that affects the livelihood system of Cuttack such as flooding, drowning of children and waste material deposit. Therefore, this study conducted 1) to map and analyse the water density changes and 2) to analyse the seasonal variation of river water to resolve and prevent problem shortcomings. Our results showed that nine types of variation can be found in the Mahanadi River each year. The increase and decrease of intensity of surface water analysed, and it varies in between -130 to 70 m3/nf. The highest frequency change is 2900 Hz near Cuttack city. The pi diagram provides the percentage of seasonal variation that can be observed as permanent water (30%), new seasonal (28%), ephemeral (12%), permanent to seasonal (7%) and seasonal (10%). The analysis is helpful and effective to assess the seasonal variation that can provide a platform for the development of Cuttack city that lies in Mahanadi delta.
Jiang, Y, He, N, Zhou, Y, Xu, B, Zhan, X & Ding, Y 2020, 'Investigation on in situ test and measurement technique of groundwater level in vacuum preloading', Bulletin of Engineering Geology and the Environment, vol. 79, no. 3, pp. 1209-1223.
View/Download from: Publisher's site
Jung, H-S, Lee, S & Pradhan, B 2020, 'Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations', Sustainability, vol. 12, no. 6, pp. 2390-2390.
View/Download from: Publisher's site
View description>>
The Special Issue on “Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations” is published. A total of 20 qualified papers are published in this Special Issue. The topics of the papers are the application of remote sensing and geospatial information systems to Earth observations in various fields such as (1) object change detection, (2) air pollution, (3) earthquakes, (4) landslides, (5) mining, (6) biomass, (7) groundwater, and (8) urban development using the techniques of remote sensing and geospatial information systems. More than 100 researchers have participated in this Special Issue. We hope that this Special Issue is helpful for sustainable applications.
Kalhori, H, Alamdari, MM, Li, B, Halkon, B, Hosseini, SM, Ye, L & Li, Z 2020, 'Concurrent Identification of Impact Location and Force Magnitude on a Composite Panel', International Journal of Structural Stability and Dynamics, vol. 20, no. 10, pp. 2042004-2042004.
View/Download from: Publisher's site
View description>>
Simultaneous estimation of both the location and force history of an impact applied on a lattice truss core sandwich panel is inversely carried out utilizing velocity signals collected by means of a scanning laser Doppler vibrometer. The algorithm assumes that several impact forces are exerted concurrently on a number of specified locations on a panel, provided that the magnitude of all impact forces but one is actually equal to zero. This condition equates to a scenario where an impact occurs at only one location. The purpose is therefore to detect the actual impact location among all potential locations, together with its force history, through minimizing error functions. Two algorithms, the one-to-one (even-determined) approach and the superposition approach, are considered. The one-to-one approach solves the reconstruction problem independently for each pair of impact and measurement points. However, in the superposition approach, the impact forces at all potential locations are concurrently reconstructed through a single matrix equation. It is shown that the one-to-one approach fails to detect the true impact location while the superposition approach recognizes the actual impact location based on some qualitative evaluating criteria. Adopting the superposition approach, for a problem with four possible impact locations, two scenarios one with four and one with 12 measurement points, are investigated. It is observed that the additional measurement points do not necessarily enhance the efficiency and accuracy of the proposed method. It is found that different arrangements of measuring points lead to identification of the location and the magnitude of the impact force, though the use of four evenly distributed measurement points seems to be most effective in simultaneous identification of the location and magnitude of the impact force. Further, a quantitative index based on the concept of similarity search for time-series using wavelet transf...
Karimidastenaei, Z, Torabi Haghighi, A, Rahmati, O, Rasouli, K, Rozbeh, S, Pirnia, A, Pradhan, B & Kløve, B 2020, 'Fog-water harvesting Capability Index (FCI) mapping for a semi-humid catchment based on socio-environmental variables and using artificial intelligence algorithms', Science of The Total Environment, vol. 708, pp. 135115-135115.
View/Download from: Publisher's site
View description>>
Fog is an important component of the water cycle in northern coastal regions of Iran. Having accurate tools for mapping the precise spatial distribution of fog is vital for water harvesting within integrated water resources management in this semi-humid region. In this study, environmental variables were considered in prediction mapping of areas with high concentrations of fog in the Vazroud watershed, Iran. Fog probability maps were derived from four artificial intelligence algorithms (Generalized Linear Model, Generalized Additive Model, Generalized Boosted Model, and Generalized Dissimilarity Model). Models accuracy were assessed using Receiver Operating characteristic Curve (ROC). Three social variables were also selected according to their relevance for fog suitability mapping. Finally, Fog-water harvesting Capability Index (FCI) maps were produced by multiplying fog probability by fog suitability maps. The results showed high accuracy in fog probability mapping for the study area, with all models proving capable of identifying areas with high fog concentrations in the south and southeast. For all models, the highest values of importance were obtained for sky view factor and the lowest for slope curvature. Analytic Hierarchy Process results showed the relative importance of social conditioning factors in fog suitability mapping, with the highest weight given to distance to residential area, followed by distance to livestock buildings and distance to road. Based on the fog suitability map, southeast and southern parts of the study area are most suitable for fog water harvesting. The fog spatial distribution maps obtained can increase fog water harvesting efficiency. They also indicate areas for future study with regions where fog is a critical component in the water cycle.
Lazaar, A, Hammouti, KE, Naiji, Z, Pradhan, B, Gourfi, A, Andich, K & Monir, A 2020, 'The manifestation of VIS-NIRS spectroscopy data to predict and map soil texture in the Triffa plain (Morocco)', Kuwait Journal of Science, vol. 48, no. 1, pp. 111-121.
View/Download from: Publisher's site
View description>>
The use of standard laboratory methods to estimate the soil texture is complicated, expensive, and time-consuming and needs considerable effort. The reflectance spectroscopy represents an alternative method for predicting a large range of soil physical properties and provides an inexpensive, rapid, and reproducible analytical method. This study aimed to assess the feasibility of Visible (VIS: 350-700 nm) and Near-Infrared and Short-Wave-Infrared (NIRS: 701-2500 nm) spectroscopy for predicting and mapping the clay, silt, and sand fractions of the soils of Triffa plain (north-east of Morocco). A total of 100 soil samples were collected from the non-root zone of soil (0-20 cm) and then analyzed for texture using the VIS-NIRS spectroscopy and the traditional laboratory method. The partial least squares regression (PLSR) technique was used to assess the ability of spectral data to predict soil texture. The results of prediction models showed excellent performance for the VIS-NIRS spectroscopy to predict the sand fraction with a coefficient of determination R2 = 0.93 and Root Mean Squares Error (RMSE) =3.72, good prediction for the silt fraction (R2=0.87; RMSE = 4.55), and acceptable prediction for the clay fraction (R2 = 0.53; RMSE = 3.72). Moreover, the range situated between 2150 and 2450 nm is the most significant for predicting the sand and silt fractions, while the spectral range between 2200 and 2440 nm is the optimal to predict the clay fraction. However, the maps of predicted and measured soil texture showed an excellent spatial similarity for the sand fraction, a certain difference in the variability of clay fraction, while the maps of silt fraction show a lower difference.
Lazaar, A, Mouazen, AM, EL Hammouti, K, Fullen, M, Pradhan, B, Memon, MS, Andich, K & Monir, A 2020, 'The application of proximal visible and near-infrared spectroscopy to estimate soil organic matter on the Triffa Plain of Morocco', International Soil and Water Conservation Research, vol. 8, no. 2, pp. 195-204.
View/Download from: Publisher's site
View description>>
© 2020 Soil organic matter (SOM) is a fundamental soil constituent. The estimation of this parameter in the laboratory using the classical method is complex time-consuming and requires the use of chemical reagents. The objectives of this study were to assess the accuracy of two laboratory measurement setups of the VIS-NIR spectroscopy in estimating SOM content and determine the important spectral bands in the SOM estimation model. A total of 115 soil samples were collected from the non-root zone (0–20 cm) of soil in the study area of the Triffa Plain and then analysed for SOM in the laboratory by the Walkley–Black method. The reflectance spectra of soil samples were measured by two protocols, Contact Probe (CP) and Pistol Grip (PG)) of the ASD spectroradiometer (350–2500 nm) in the laboratory. Partial least squares regression (PLSR) was used to develop the prediction models. The results of coefficient of determination (R2) and the root mean square error (RMSE) showed that the pistol grip offers reasonable accuracy with an R2 = 0.93 and RMSE = 0.13 compared to the contact probe protocol with an R2 = 0.85 and RMSE = 0.19. The near-Infrared range were more accurate than those in the visible range for predicting SOM using the both setups (CP and PG). The significant wavelengths contributing to the prediction of SOM for (PG) setup were at: 424, 597, 1432, 1484, 1830,1920, 2200, 2357 and 2430 nm, while were at 433, 587, 1380, 1431, 1929, 2200 and 2345 nm for (CP) setup.
Li, H, Li, Y & Li, J 2020, 'Negative stiffness devices for vibration isolation applications: A review', Advances in Structural Engineering, vol. 23, no. 8, pp. 1739-1755.
View/Download from: Publisher's site
View description>>
In recent years, negative stiffness vibration isolation device with nonlinear characteristic has become an emerging research area and attracted a significant amount of attentions in the community due to the promising potentials it brought into the field. Its high-static-low-dynamic stiffness property endows the capacity to realize effective vibration isolation and in the meantime to maintain the system stability. This article presents a comprehensive review of the recent research and developments on negative stiffness vibration isolation device. It begins with an introduction on the concept of negative stiffness and then provides a summary and discussion regarding the realization and characteristics of negative stiffness vibration isolation device. The article places its special interest on the principles, structure design, and device characterisation of different types of negative stiffness vibration isolation devices, including spring type, pre-bucked beam type, magnetism type, geometrically nonlinear structural type, and composite structural type. Besides, the applications of negative stiffness vibration isolation device, as well as negative stiffness damper, are summarized and discussed based on the current state-of-the-art. Finally, the conclusions and further discussion provide highlights of the investigation.
Li, L, Ju, N, He, C, Li, C & Sheng, D 2020, 'A computationally efficient system for assessing near-real-time instability of regional unsaturated soil slopes under rainfall', Landslides, vol. 17, no. 4, pp. 893-911.
View/Download from: Publisher's site
View description>>
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. The objective of this paper is to obtain an applicable assessment method and a Web-GIS-based prediction system for regional landslides. The traditional Richards function is reconstructed using the soil-water characteristic curve (SWCC) and the coordinate transformation technique. The analytical pore pressure for a slope model is derived by solving the modified Richard equation via the Green function and Fourier transformation. The obtained transient pore pressure field is then incorporated with Brakensiek’s matric suction theory, to build a conceptual model for rainfall-induced shallow landslides. The safety factor is obtained by solving the limit equilibrium equation of the conceptual model. The method is then implemented in a Web-GIS system, considering influence of slope geometry features, geology parent material, and near-real-time rainfall intensity of the study area. It is verified that this method is computationally efficient and reliable for gentle slopes and short rainfall durations. Moreover, an extensive parameter study shows that the two commonly used coefficients in the intensity-duration equation are both correlated to rainfall inter-event time via exponential functions, and rainfall event time via power functions. The primary influential factor for regional landslides is the initial water content, followed by the rainfall duration and intensity, and least by soil thickness.
Li, S, Liang, Y, Li, Y, Li, J & Zhou, Y 2020, 'Investigation of dynamic properties of isotropic and anisotropic magnetorheological elastomers with a hybrid magnet shear test rig', Smart Materials and Structures, vol. 29, no. 11, pp. 114001-114001.
View/Download from: Publisher's site
View description>>
Abstract Magnetorheological elastomers (MREs) exhibit instantaneous and reversible adaptability of stiffness and damping properties under the influence of magnetic field, which can be implemented in the development of controllable devices. The main MRE components are normally elastomeric matrix and magnetisable particles. Depending on the distribution of the particles in the matrix, MREs can be classified into isotropic and anisotropic. This work experimentally explored, compared, and modelled the dynamic characteristics of both isotropic and anisotropic MREs with different iron particle weight fractions (17%, 22%, and 32%). A novel shear test rig was designed with hybrid magnets system, i.e. permanent magnet and electromagnets, to fulfil the characterisation tasks. The involvement of the hybrid magnets effectively cuts down the maximum electric current and energy consumption of the rig. The tests were conducted under sinusoidal shear motions with excitation frequency ranging from 0.1 Hz to 2 Hz and shear strain varying from 20% to 60% to record the force-displacement hysteresis of MRE samples. Four different levels of magnetic field (0.02, 0.54, 0.77, 1.01 T) were supplied by the hybrid magnetic system and were considered in the tests to evaluate the influence of the magnetic fields. Furthermore, characterised hysteretic behaviours for both isotropic and anisotropic MRE were modelled by a strain stiffening phenomenological model with ideal accuracy under the shear excitation inputs and magnetic fields considered.
Li, S, Tian, T, Wang, H, Li, Y, Li, J, Zhou, Y & Wu, J 2020, 'Development of a four-parameter phenomenological model for the nonlinear viscoelastic behaviour of magnetorheological gels', Materials & Design, vol. 194, pp. 108935-108935.
View/Download from: Publisher's site
Li, S, Watterson, PA, Li, Y, Wen, Q & Li, J 2020, 'Improved magnetic circuit analysis of a laminated magnetorheological elastomer device featuring both permanent magnets and electromagnets', Smart Materials and Structures, vol. 29, no. 8, pp. 085054-085054.
View/Download from: Publisher's site
View description>>
As an essential and critical step, magnetic circuit modelling is usually implemented in the design of efficient and compact magnetorheological (MR) devices, such as MR dampers and MR elastomer isolators. Conventional magnetic circuit analysis simplifies the analysis by ignoring the magnetic flux leakage and magnetic fringing effect. These assumptions are sufficiently accurate in dealing with less complicated designs, featuring short magnetic path lengths such as in an MR damper. However, when dealing with MR elastomer devices, such simplification in magnetic circuit analysis results in inaccuracy of dimensioning and performance estimation of the devices due to their sophisticated design and complex magnetic paths. Modelling permanent magnets also imposes challenges in the magnetic circuit analysis. This work proposes an improved approach to include magnetic flux fringing effect in magnetic circuit analysis for MR elastomer devices. An MRE-based isolator containing multiple MRE layers and both a permanent magnet and an exciting coil was designed and built as a case study. The results of the proposed method are compared to those of conventional magnetic circuit modelling, finite element analysis and experimental measurements to demonstrate the effectiveness of the proposed approach.
Li, W, Huang, L & Ji, J 2020, 'Globally exponentially stable periodic solution in a general delayed predator-prey model under discontinuous prey control strategy', Discrete & Continuous Dynamical Systems - B, vol. 25, no. 7, pp. 2639-2664.
View/Download from: Publisher's site
View description>>
This paper studies the solution behaviour of a general delayed predator-prey model with discontinuous prey control strategy. The positiveness and boundeness of the solution of the system is firstly investigated using the comparison theorem. Then the sufficient conditions are derived for the existence of positive periodic solutions using the differential inclusion theory and the topological degree theory. Furthermore, the positive periodic solution is proved to be globally exponentially stable by employing the generalized Lyapunov approach. The global finite-time convergence is also discussed for the system state. Finally, the numerical simulations of four examples are given to validate the correctness of the theoretical results.
Li, W, Huang, L, Guo, Z & Ji, J 2020, 'Global dynamic behavior of a plant disease model with ratio dependent impulsive control strategy', Mathematics and Computers in Simulation, vol. 177, pp. 120-139.
View/Download from: Publisher's site
View description>>
© 2020 International Association for Mathematics and Computers in Simulation (IMACS) In this paper, we consider the dynamics of a plant disease model with a ratio-dependent state impulsive control strategy. It is shown that the boundary equilibrium point of the controlled system is globally asymptotically stable. By combining LaSalle's invariant theorem, Brouwer's fixed point theorem and some analysis techniques, we are able to determine the basic reproduction number, confirm the well-posedness of the model, describe the structure of possible equilibria as well as establish the stability of the equilibria. Most interestingly, we find that in the case that the basic reproduction number is more than unity and the endemic equilibrium locates above the impulsive control strategy, we can obtain a unique k-order periodic solution and the critical values between 1-order and 2-order periodic solutions. Furthermore, it is found that the endemic equilibrium point is also globally asymptotically stable under the control strategy. Finally, we present a numerical example to substantiate the effectiveness of the theoretical results.
Li, W, Ji, J & Huang, L 2020, 'Dynamics of a controlled discontinuous computer worm system', Proceedings of the American Mathematical Society, vol. 148, no. 10, pp. 4389-4403.
View/Download from: Publisher's site
View description>>
© 2020 American Mathematical Society This paper studies the dynamic behaviour of a computer worm system under a discontinuous control strategy. Some conditions for globally asymptotically stable solutions of the discontinuous system are obtained by using the Bendixson–Dulac theorem, Green’s formula, and the Lyapunov function. It is found that the solutions of the controlled computer worm system can converge to either of two local equilibrium points or the sliding equilibrium point on the discontinuous surface. It is shown that a threshold control strategy can effectively control the spread of computer viruses. The research results may be applicable to control other types of virus systems.
Li, W, Ji, J & Huang, L 2020, 'Global dynamic behavior of a predator–prey model under ratio-dependent state impulsive control', Applied Mathematical Modelling, vol. 77, pp. 1842-1859.
View/Download from: Publisher's site
View description>>
© 2019 This paper studies the global dynamic behavior of a prey–predator model with square root functional response under ratio-dependent state impulsive control strategy. It is shown that the boundary equilibrium point of the controlled system is globally asymptotically stable. An order-k periodic orbit is obtained by employing the Brouwer's fixed point theorem. Furthermore, the critical values are determined for the existence of orbitally asymptotically stable order-1 and order-2 periodic orbits in finite time. These critical values play an important role in determining different kinds of order-k periodic orbits and can also be used for designing the control parameters to obtain the desirable dynamic behavior of the controlled prey–predator system. Moreover, it is found that the local equilibrium point is also globally asymptotically stable under the control strategy. Numerical examples are provided to validate the effectiveness and feasibility of the theoretical results.
Li, W, Ji, J, Huang, L & Wang, J 2020, 'Bifurcations and dynamics of a plant disease system under non-smooth control strategy', Nonlinear Dynamics, vol. 99, no. 4, pp. 3351-3371.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature B.V. Mathematical models and analyses can assist in designing the control strategies to prevent the spread of infectious disease. The present paper investigates the bifurcations and dynamics of a plant disease system under non-smooth control strategy. The generalized Lyapunov approach is employed to perform the analysis of the plant disease model with non-smooth control. It is found that the controlled disease system can have three types of equilibria. The globally asymptotically attractor for each of three types of equilibria is determined by constructing Lyapunov functions and using Green’s Theorem. It is shown that the disease system can exhibit rich dynamic behaviors including globally stable equilibrium, stable pseudo-equilibrium and sliding mode bifurcations. The solution of the disease system can converge to the disease-free equilibrium, endemic equilibrium or sliding equilibrium on discontinuous surfaces. Biological implications of the obtained results are discussed for implementing the control strategies to the infectious plant diseases.
Liu, J, Li, H, Ji, J & Luo, J 2020, 'Group-Bipartite Consensus in the Networks With Cooperative-Competitive Interactions', IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 67, no. 12, pp. 3292-3296.
View/Download from: Publisher's site
View description>>
© 2004-2012 IEEE. This brief addresses the group-bipartite consensus problem of multi-agent systems with cooperative-competitive interactions. By combining the characteristics of group consensus and bipartite consensus, the concept of group-bipartite consensus is introduced to specify multiple bipartite consensus behavior. A distributed control protocol is then proposed for the topology graphs with acyclic partition and sign-balanced couples. The network topology studied in this brief eliminates the constraint that negative links can only exist between different groups, and thus the weights between agents in the same group can be either positive or negative. Some necessary and sufficient conditions for solving group-bipartite consensus problems are established by constructing a new form of the Laplacian matrix associated with the directed communication graphs. A simulation example is given to validate the theoretical results.
Liu, L, Guo, R, Ji, J, Miao, Z & Zhou, J 2020, 'Practical consensus tracking control of multiple nonholonomic wheeled mobile robots in polar coordinates', International Journal of Robust and Nonlinear Control, vol. 30, no. 10, pp. 3831-3847.
View/Download from: Publisher's site
View description>>
This paper proposes a sliding-mode control (SMC) method to achieve practical cooperative consensus tracking for a network of multiple nonholonomic wheeled mobile robots (MNWMRs) with input disturbances. A novel SMC surface under the nonholonomic constraints is first formulated to characterize the network communication interactions among the networked robots under the framework of polar coordinates. A unified distributed consensus tracking strategy is then proposed by systematically combining a position controller and a direction controller. Furthermore, a simple yet general criterion is derived to achieve the desired practical consensus of trajectory tracking and posture stabilization for MNWMRs. In particular, for a specific common consensus trajectory, the complete asymptotic tracking in heading direction can be fully guaranteed when the perfect asymptotic position-tracking errors are realized. Accordingly, the developed consensus tracking strategy for MNWMRs demonstrates some advantages of control performance including stability, robustness, and effectiveness over the existing control method proposed for their single-robot counterparts. Some comparative simulation results are given to confirm the effectiveness of the proposed cooperative consensus control method.
Liu, MD, Airey, DW, Indraratna, B, Zhuang, Z & Horpibulsuk, S 2020, 'An extended modified cam clay model for improved accuracy at low and high-end stress levels', Marine Georesources & Geotechnology, vol. 38, no. 4, pp. 423-436.
View/Download from: Publisher's site
Liu, X, Zhou, A, Shen, S-L, Li, J & Sheng, D 2020, 'A micro-mechanical model for unsaturated soils based on DEM', Computer Methods in Applied Mechanics and Engineering, vol. 368, pp. 113183-113183.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. A micro-mechanical model to study the microscopic and macroscopic behavior of unsaturated soils under different suctions is proposed in this study. In the model, a novel pore-scale numerical method for simulating the liquid–solid interfaces is proposed first. A discretization of the particle surface using Fibonacci-Lattice is then introduced to calculate the capillary forces from the complex liquid–solid interfaces. The joint influence of capillary forces and the interparticle contact forces on the motion of the particles are handled by the discrete element method (DEM). The effective stress parameter estimated by the model is compared with the experimental results for unsaturated soils, which confirms the validity of the proposed micro-mechanical model. The microscopic responses (liquid–solid interfaces, capillary forces, contact forces and coordination numbers) and macroscopic responses (strength, stress–strain relationship and volume change) of unsaturated soils in desaturation tests and triaxial tests are studied by the proposed model.
Liu, Y, Lan, C, Blumenstein, M & Li, J 2020, 'Bi-Level Error Correction for PacBio Long Reads', IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 17, no. 3, pp. 899-905.
View/Download from: Publisher's site
View description>>
IEEE The latest sequencing technologies such as the Pacific Biosciences (PacBio) and Oxford Nanopore machines can generate long reads at the length of thousands of nucleic bases which is much longer than the reads at the length of hundreds generated by Illumina machines. However, these long reads are prone to much higher error rates, for example 15%, making downstream analysis and applications very difficult. Error correction is a process to improve the quality of sequencing data. Hybrid correction strategies have been recently proposed to combine Illumina reads of low error rates to fix sequencing errors in the noisy long reads with good performance. In this paper, we propose a new method named Bicolor, a bi-level framework of hybrid error correction for further improving the quality of PacBio long reads. At the first level, our method uses a de Bruijn graph-based error correction idea to search paths in pairs of solid < formula > < tex > $k$ < /tex > < /formula > -mers iteratively with an increasing length of < formula > < tex > $k$ < /tex > < /formula > -mer. At the second level, we combine the processed results under different parameters from the first level. In particular, a multiple sequence alignment algorithm is used to align those similar long reads, followed by a voting algorithm which determines the final base at each position of the reads. We compare the superior performance of Bicolor with three state-of-the-art methods on three real data sets. Results demonstrate that Bicolor always achieves the highest identity ratio. Bicolor also achieves a higher alignment ratio ( < formula > < tex > $ & #x003E; 1.3\%$ < /tex > < /formula > ) and a higher number of aligned reads than the current methods on two data sets. On the third data set, our method is closely competitive to the current methods in terms of number of aligned reads and genome coverage. The C++ source codes of our algorithm are freely available at https://github.com/yuansliu/Bicolor.
Makhdoom, I, Zhou, I, Abolhasan, M, Lipman, J & Ni, W 2020, 'PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities', Computers & Security, vol. 88, pp. 101653-101653.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, agriculture, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present “PrivySharing,” a blockchain-based innovative framework for privacy-preserving and secure IoT data sharing in a smart city environment. The proposed scheme is distinct from existing strategies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel comprises a finite number of authorized organizations and processes a specific type of data such as health, smart car, smart energy or financial details. Moreover, access to users’ data within a channel is controlled by embedding access control rules in the smart contracts. In addition, data within a channel is further isolated and secured by using private data collection and encryption respectively. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. We also present a system of reward in the form of a digital token named “PrivyCoin” for users sharing their data with stakeholders/third parties. Lastly, the experimental outcomes advocate that a multi-channel blockchain scales well as compared to a single-channel blockchain system.
Malisetty, RS, Indraratna, B & Vinod, J 2020, 'Behaviour of ballast under principal stress rotation: Multi-laminate approach for moving loads', Computers and Geotechnics, vol. 125, pp. 103655-103655.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Railway tracks are subjected to millions of loading cycles over time and at high speeds, these moving trains induce dynamic amplification of vertical stresses and rotation of principal stress axes in the track layers. It is important to predict and analyse the behaviour of ballast under these loads with complex stress paths involving principal stress rotation. In this paper, a constitutive model based on a multi-laminate framework is used to predict the deformation and degradation of ballast under complex stress paths. The yield and plastic potential surfaces are developed based on a non-linear critical state and bounding surface plasticity concepts. The proposed model is validated with independent test data to capture the influence of confining stress, loading frequency, Cyclic Stress Ratio (CSR) and Shear Stress Ratio (ητ) on the permanent strain response. Furthermore, the response of ballast under traffic loading stress paths with different CSR and ητ is analysed. These model predictions show that higher CSRand ητ values lead to exacerbated particle breakage of ballast, large and unstable axial strains and dilatant volumetric strains. Furthermore, a stability surface is proposed based on model predictions, to estimate the allowable CSR and ητ for a stable response.
Malisetty, RS, Indraratna, B & Vinod, JS 2020, 'Multilaminate Mathematical Framework for Analyzing the Deformation of Coarse Granular Materials', International Journal of Geomechanics, vol. 20, no. 6, pp. 06020004-06020004.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. Coarse granular materials such as railway ballast and rockfill are often subjected to three-dimensional (3D) stress conditions including the influence of intermediate principal stress. Modeling the deformation and breakage of these materials under the presence of intermediate principal stress is important for assessing their long-term performance. This paper presents a mathematical model to describe the mechanical behavior of granular materials incorporating the intermediate principal stress and capture particle breakage. The model formulation encompasses interparticle contact planes using a multilaminate mathematical framework based on generalized plasticity and associated critical state concepts. The model that has been calibrated based on recent experimental data on latite basalt, captures the stress-strain and volumetric strain behavior for a range of confining pressures under triaxial compression. This paper also describes the influence of intermediate principal stress on the strength and deformation response of selected granular materials following 3D stress paths. It is evident from the results that the current modeling technique successfully captured the effects of particle breakage, intermediate principal stress, and confining pressure on the shear behavior of various granular assemblies. The results also highlight the influence of intermediate principal stress in reducing the peak deviatoric strength of the material. The model predictions were validated using four independent sets of past experimental data on crushed basalt, limestone, sandstone, and granite aggregates.
Mao, Y, Jianxi, Y, Ji, J, Xu, W & Guo, Q 2020, 'An analytical solution of Reynolds equation for evaluating the characteristics of surface textured bearing', Industrial Lubrication and Tribology, vol. 72, no. 9, pp. 1075-1085.
View/Download from: Publisher's site
View description>>
PurposeCurrently, there is a lack of fast and highly accurate on analytical solution of Reynolds equation for evaluating the characteristics of surface textured bearing. This paper aims to develop such an analytical solution of Reynolds equation for an effective analysis of the characteristics of surface textured bearings.Design/methodology/approachBy using the separation of variables method and mean eigenvalue method, the analytical solution is constructed. The CFD simulations and experimental results are used to validate the correctness of the analytical solution.FindingsThe analytical solution can accurately evaluate the characteristics of textured bearings. It is found that the larger the eccentricity ratio and aspect ratio, the greater the oil film force. It also found that the smaller the eccentricity ratio, the larger the Sommerfeld number S. When eccentricity ratio e = 0.65, the attitude angles of different oil boundaries are same. The effect of different aspect ratios on dynamic stiffness and damping coefficient generally follows a same trend. It is numerically shown that the critical speed of rotor-bearing is 3500 rpm.Originality/valueThe analytical solution provides a simple yet effective way to study the characteristics of surface textured bearings.
Medawela, S & Indraratna, B 2020, 'Computational modelling to predict the longevity of a permeable reactive barrier in an acidic floodplain', Computers and Geotechnics, vol. 124, pp. 103605-103605.
View/Download from: Publisher's site
Meena, NK, Nimbalkar, S, Fatahi, B & Yang, G 2020, 'Effects of soil arching on behavior of pile-supported railway embankment: 2D FEM approach', Computers and Geotechnics, vol. 123, pp. 103601-103601.
View/Download from: Publisher's site
Mehrabi, M, Pradhan, B, Moayedi, H & Alamri, A 2020, 'Optimizing an Adaptive Neuro-Fuzzy Inference System for Spatial Prediction of Landslide Susceptibility Using Four State-of-the-art Metaheuristic Techniques', Sensors, vol. 20, no. 6, pp. 1723-1723.
View/Download from: Publisher's site
View description>>
Four state-of-the-art metaheuristic algorithms including the genetic algorithm (GA), particle swarm optimization (PSO), differential evolutionary (DE), and ant colony optimization (ACO) are applied to an adaptive neuro-fuzzy inference system (ANFIS) for spatial prediction of landslide susceptibility in Qazvin Province (Iran). To this end, the landslide inventory map, composed of 199 identified landslides, is divided into training and testing landslides with a 70:30 ratio. To create the spatial database, thirteen landslide conditioning factors are considered within the geographic information system (GIS). Notably, the spatial interaction between the landslides and mentioned conditioning factors is analyzed by means of frequency ratio (FR) theory. After the optimization process, it was shown that the DE-based model reaches the best response more quickly than other ensembles. The landslide susceptibility maps were developed, and the accuracy of the models was evaluated by a ranking system, based on the calculated area under the receiving operating characteristic curve (AUROC), mean absolute error, and mean square error (MSE) accuracy indices. According to the results, the GA-ANFIS with a total ranking score (TRS) = 24 presented the most accurate prediction, followed by PSO-ANFIS (TRS = 17), DE-ANFIS (TRS = 13), and ACO-ANFIS (TRS = 6). Due to the excellent results of this research, the developed landslide susceptibility maps can be applied for future planning and decision making of the related area.
Melnikov, A, Maeder, M, Friedrich, N, Pozhanka, Y, Wollmann, A, Scheffler, M, Oberst, S, Powell, D & Marburg, S 2020, 'Acoustic metamaterial capsule for reduction of stage machinery noise', The Journal of the Acoustical Society of America, vol. 147, no. 3, pp. 1491-1503.
View/Download from: Publisher's site
View description>>
Noise mitigation of stage machinery can be quite demanding and requires innovative solutions. In this work, an acoustic metamaterial capsule is proposed to reduce the noise emission of several stage machinery drive trains, while still allowing the ventilation required for cooling. The metamaterial capsule consists of c-shape meta-atoms, which have a simple structure that facilitates manufacturing. Two different metamaterial capsules are designed, simulated, manufactured, and experimentally validated that utilize an ultra-sparse and air-permeable reflective meta-grating. Both designs demonstrate transmission loss peaks that effectively suppress gear mesh noise or other narrow band noise sources. The ventilation by natural convection was numerically verified, and was shown to give adequate cooling, whereas a conventional sound capsule would lead to overheating. The noise spectra of three common stage machinery drive trains are numerically modelled, enabling one to design meta-gratings and determine their noise suppression performance. The results fulfill the stringent stage machinery noise limits, highlighting the benefit of using metamaterial capsules of simple c-shape structure.
Moayedi, H, Mehrabi, M, Bui, DT, Pradhan, B & Foong, LK 2020, 'Fuzzy-metaheuristic ensembles for spatial assessment of forest fire susceptibility', Journal of Environmental Management, vol. 260, pp. 109867-109867.
View/Download from: Publisher's site
View description>>
Forests are important dynamic systems which are widely affected by fire worldwide. Due to the complexity and non-linearity of the forest fire problem, employing hybrid evolutionary algorithms is a logical task to achieve a reliable approximation of this environmental threat. Three fuzzy-metaheuristic ensembles, based on adaptive neuro-fuzzy inference systems (ANFIS) incorporated with genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE) evolutionary algorithms are used to produce the forest fire susceptibility map (FFSM) of a fire-prone region in Iran. A sensitivity analysis is also executed to evaluate the effectiveness of the proposed ensembles in terms of time and complexity. The results revealed that all models produce FFSMs with acceptable accuracy. However, the superiority of the GA-ANFIS was shown in both recognizing the pattern (AUROCtrain = 0.912 and Error = 0.1277) and predicting unseen fire events (AUROCtest = 0.850 and Error = 0.1638). The optimized structures of the proposed GA-ANFIS and PSO-ANFIS ensembles could be good alternatives to traditional forest fire predictive models, and their FFSMs can be promisingly used for future planning and decision making in the proposed area.
Munadi, K, Muchtar, K, Maulina, N & Pradhan, B 2020, 'Image Enhancement for Tuberculosis Detection Using Deep Learning', IEEE Access, vol. 8, pp. 217897-217907.
View/Download from: Publisher's site
Nag, S, Shivakumara, P, Pal, U, Lu, T & Blumenstein, M 2020, 'A new unified method for detecting text from marathon runners and sports players in video (PR-D-19-01078R2)', Pattern Recognition, vol. 107, pp. 107476-107476.
View/Download from: Publisher's site
View description>>
© 2020 Detecting text located on the torsos of marathon runners and sports players in video is a challenging issue due to poor quality and adverse effects caused by flexible/colorful clothing, and different structures of human bodies or actions. This paper presents a new unified method for tackling the above challenges. The proposed method fuses gradient magnitude and direction coherence of text pixels in a new way for detecting candidate regions. Candidate regions are used for determining the number of temporal frame clusters obtained by K-means clustering on frame differences. This process in turn detects key frames. The proposed method explores Bayesian probability for skin portions using color values at both pixel and component levels of temporal frames, which provides fused images with skin components. Based on skin information, the proposed method then detects faces and torsos by finding structural and spatial coherences between them. We further propose adaptive pixels linking a deep learning model for text detection from torso regions. The proposed method is tested on our own dataset collected from marathon/sports video and three standard datasets, namely, RBNR, MMM and R-ID of marathon images, to evaluate the performance. In addition, the proposed method is also tested on the standard natural scene datasets, namely, CTW1500 and MS-COCO text datasets, to show the objectiveness of the proposed method. A comparative study with the state-of-the-art methods on bib number/text detection of different datasets shows that the proposed method outperforms the existing methods.
Naghibi, SA, Vafakhah, M, Hashemi, H, Pradhan, B & Alavi, SJ 2020, 'Water Resources Management Through Flood Spreading Project Suitability Mapping Using Frequency Ratio, k-nearest Neighbours, and Random Forest Algorithms', Natural Resources Research, vol. 29, no. 3, pp. 1915-1933.
View/Download from: Publisher's site
Navaratnarajah, SK & Indraratna, B 2020, 'Stabilisation of Stiffer Rail Track Substructure Using Artificial Inclusion', Indian Geotechnical Journal, vol. 50, no. 2, pp. 196-203.
View/Download from: Publisher's site
View description>>
© 2020, Indian Geotechnical Society. The railway transport system in many countries plays a significant role in the passage of bulk freight and passengers. However, increased train speeds and higher freight loads (large dynamic wheel loads) accelerate the deterioration of rail track substructure. This problem is more critical in isolated rail track locations where the track substructure is much stiffer than the regular surface track assembly such as track at the bridges and tunnels. Ballast is a key track foundation material placed underneath the sleepers which provides structural support against high cyclic and impact stresses caused by moving trains. Inclusion of rubber mats called under ballast mats (UBMs) placed between the ballast and stiffer base layer is one of the measures to minimise the ballast deterioration. In this study, cyclic loads representing fast and heavy haul trains were simulated on stiffer track foundation condition using a large-scale process simulation prismoidal triaxial apparatus to investigate the mitigation of strain, stress and degradation characteristics of ballast stabilised with UBM. These UBMs were locally manufactured from recycled tyre wastes. The results show that ballast on a stiff foundation substructure stabilised with UBM experienced significantly less vertical and lateral deformation, ballast interface and inter-particle stresses and degradation. This study also confirmed that the recycled tyre UBMs used in this study had adequate damping to absorb the energy transmitted to the moving train to the track, thus preventing excessive plastic deformation and degradation of the ballast layer.
Ngo, T & Indraratna, B 2020, 'Analysis of Deformation and Degradation of Fouled Ballast: Experimental Testing and DEM Modeling', International Journal of Geomechanics, vol. 20, no. 9, pp. 06020020-06020020.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. The deformation and degradation of fouled ballast have been examined by large-scale triaxial tests and discrete element modeling (DEM) to understand how clay fouling changes the shear strength and micromechanical aspects of ballast. Particle shape analysis using 3D aggregate imaging and a laser scanner is introduced to construct more realistic polyhedral discrete elements that will represent natural ballast particles. Shear stress-strain and volumetric changes of fresh and clay-fouled ballast are analyzed. Micromechanical analysis of the fouled ballast is carried out and the effects of fines are quantified by considering the changes of ballast breakage, particle connectivity number Cn, and the associated distribution of contact forces that could not be measured experimentally. These findings enable a more insightful understanding of the load-deformation of fouled ballast from a micromechanical perspective.
Ngo, T & Indraratna, B 2020, 'Mitigating ballast degradation with under-sleeper rubber pads: Experimental and numerical perspectives', Computers and Geotechnics, vol. 122, pp. 103540-103540.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd This paper presents a study on mitigating the degradation of ballast by placing an under-sleeper rubber pad (USP) beneath a sleeper. Large-scale track process simulation apparatus (TPSA) tests have been carried out on ballast assemblies (with and without USP) subjected to cyclic loadings. Numerical modelling has been performed using a coupled discrete-continuum modelling (coupled DEM-FDM) approach to investigate the role of USP from a micromechanical perspective. Ballast grains are simulated in DEM by bonding of many cylinders together at appropriate sizes and locations; and when those bonds break, they are considered to represent ballast breakage. The capping and subgrade layers are simulated as continuum media using the finite difference method (FDM). Interface elements were developed for transmitting forces and displacements between the discrete and continuum domains. The coupled model is validated by comparing the predicted load-deformation responses with those measured from large-scale TPSA tests. The model is then used to explore changes in the micromechanical aspects of ballast subjected to cyclic loading, including particle connectivity number, contact force distributions, and contact orientations and associated particle breakage. These findings are needed to gain a better insight as to how USPs help to attenuate the load applied in a ballast assembly.
Ngoc, TP, Fatahi, B, Khabbaz, H & Sheng, D 2020, 'Impacts of matric suction equalization on small strain shear modulus of soils during air drying', Canadian Geotechnical Journal, vol. 57, no. 12, pp. 1982-1997.
View/Download from: Publisher's site
View description>>
In this study, a weight-control bender element system has been developed to investigate the impact of matric suction equalization on the measurement of small strain shear modulus (Gmax) during an air-drying process. The setup employed is capable of measuring the shear wave velocity and the corresponding Gmax of the soil sample in either an open system in which the soil sample evaporates freely or in a closed system that allows the process of matric suction equalization. The comparison between measurements of Gmax in the open and closed systems revealed underestimations of Gmax when matric suction equalization was ignored due to the nonuniform distribution of water content across the sample cross-sectional area. This study also investigated the time required for matric suction equalization tse to be established for samples with different sizes. The experimental results indicated two main mechanisms driving the matric suction equalization in a closed system during an air-drying process, namely the hydraulic flow of water and the flow of vapour. While the former played the key role when the micropores were still saturated at the high range of water content, effects of the latter increased and finally dominated when more air invaded the micropores at lower water contents.
Nguyen, TN, Emre Erkmen, R, Sanchez, LFM & Li, J 2020, 'Stiffness Degradation of Concrete Due to Alkali-Silica Reaction: A Computational Homogenization Approach', ACI Materials Journal, vol. 117, no. 6, pp. 65-76.
View/Download from: Publisher's site
View description>>
Alkali-silica reaction (ASR) is one of the most harmful distress mechanisms affecting concrete infrastructure worldwide. ASR is a chemical reaction that generates a secondary product, which induces expansive pressure within the reacting aggregate material and adjacent cement paste upon moisture uptake, leading to cracking, loss of material integrity, and functionality of the affected structure. In this work, a computational homogenization approach is proposed to model the impact of ASR-induced cracking on concrete stiffness as a function of its development. A representative volume element (RVE) of the material at the mesoscale is developed, which enables the input of the cracking pattern and extent observed from a series of experimental testing. The model is appraised on concrete mixtures presenting different mechanical properties and incorporating reactive coarse aggregates. The results have been compared with experimental results reported in the literature. The case studies considered for the analysis show that stiffness reduction of ASR-affected concrete presenting distinct damage degrees can be captured using the proposed mesoscale model as the predictions of the proposed methodology fall in between the upper and lower bounds of the experimental results.
Nguyen, TT & Indraratna, B 2020, 'A Coupled CFD–DEM Approach to Examine the Hydraulic Critical State of Soil under Increasing Hydraulic Gradient', International Journal of Geomechanics, vol. 20, no. 9, pp. 04020138-04020138.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. Increasing hydraulic gradients and associated seepage in a soil foundation accompanied by a reduction in effective stress, degradation of soil stiffness, and diminished internal stability contribute to adverse conditions in engineered earth structures, including dams and transport infrastructure. Although much attention has been drawn into these geotechnical challenges, most previous analytical and experimental studies could not properly capture the detailed response of fluid and soil particles, especially the localized or microscopic fluid-soil perspectives. In this regard, this paper aims to apply a numerical approach to analyze the response of a soil-fluid system under increasing hydraulic gradients. Soils with different gradation properties and porosities are created using the discrete element method (DEM), which is then coupled with computational fluid dynamics (CFD) based on Navier-Stokes equations. This numerical investigation reveals different stages in the development of hydraulic critical state, that is, from localized erosion (e.g., piping) to overall heave and fluidization. The transformation of fluid and particle characteristics, such as particle migration, the erosion rate, and hydraulic conductivity associated with porosity when soil approaches critical state, is discussed in detail. Micromechanical degradation within the contact network and the associated reduction in effective stress of soil due to an increasing hydraulic gradient are also analyzed in this study. A number of key factors that govern the soil response, such as friction, porosity, and grain uniformity, are addressed through numerical investigations. This study demonstrates acceptable numerical predictions for hydraulic behavior and erosion rates that are in good agreement with previous experimental data.
Nguyen, TT & Indraratna, B 2020, 'The energy transformation of internal erosion based on fluid-particle coupling', Computers and Geotechnics, vol. 121, pp. 103475-103475.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The transformation of energy is an intrinsic process that is needed to trigger the internal erosion of soils subjected to a fluid flow, but how to capture this process is not understood very well. This is why this study aims to address these complex processes through a numerical fluid-particle coupling simulation. The computational fluid dynamics (CFD) is used to model fluid flows which is coupled with the discrete element method (DEM) employed to simulate soil particles. Detailed migration of particles and fluid variables are recorded to enable their kinetic energy to be computed. Successful experiments are used to demonstrate how the numerical method can be used to model the internal erosion associated with energy computation. This study shows a good agreement between the numerical and experimental results in terms of the hydraulic conductivity and erosion rate of soils subjected to upward flows. A significant loss in energy is also found as fluid flows through the soil whereas only a small amount of kinetic energy is needed to make particles migrate at a considerable degree. The influence that the porosity and uniformity of soils has on the transformation of energy is also discussed in the paper.
Nguyen, TT & Indraratna, B 2020, 'The role of particle shape on hydraulic conductivity of granular soils captured through Kozeny–Carman approach', Géotechnique Letters, vol. 10, no. 3, pp. 398-403.
View/Download from: Publisher's site
View description>>
Previous studies indicate that particle shape plays an important role in the hydraulic conductivity (k) of granular materials, often represented through the Kozeny–Carman (KC) concept. Several recent studies have improved the accuracy of the KC approach using the particle-size distribution (PSD) to estimate the specific surface area of particles but overly simplifying the effect of particle shape. This current study innovatively adopts the micro-computed tomography technique to compute particle shape parameters of different granular materials (e.g. glass beads, sand and crushed gravel) and then incorporate these parameters into the KC equation to estimate k more accurately, which is then validated with experimental data. The results indicate that k varies significantly according to different particle shapes even if the same mean porosity and PSD are retained. Particles that are less spherical and rounded have a larger fluid–particle contact area (i.e. larger shape factor), hence a smaller hydraulic conductivity. The study suggests a shape factor of 1·28–1·52 for natural sand and 1·84–2·1 for crushed sand and gravel can be used for KC method to estimate k while a porosity-dependent equation is proposed to estimate the tortuosity for different shaped materials.
Nguyen, TT, Indraratna, B & Baral, P 2020, 'Biodegradable prefabricated vertical drains: From laboratory to field studies', Geotechnical Engineering, vol. 51, no. 2, pp. 39-46.
View description>>
Biodegradable prefabricated vertical drains (BPVDs) made from natural fibres have been in use for several decades to improve soft soil, especially in East and Southeast Asia despite the fact that this type of drain has still not been fully addressed and evaluated. This study presents a series of laboratory tests where a drain made from coconut cores wrapped in Indian jute sheath filters is compared to conventional synthetic prefabricated vertical drains (SPVDs). Discharge volume tests are carried out with and without soil clogging to understand how jute drains can resist soil clogging under increasing confining pressure. Along with these macro-hydraulic tests, the influence that the micro-characteristics of natural fibre drains can have on their hydraulic conductivity is also examined using micro-CT scanning and an optical microscopic to capture the micro-details of these drains. This study shows that the porous structure of BPVDs is much more complex than SPVDs, which causes them to have a lower discharge capacity. Unlike SPVDs, micro-properties also play an important role in the hydraulic properties of BPVDs. A pilot project in soft soil at Ballina, Australia, where BPVDs were installed in parallel to SPVDs, was used to evaluate their performance in assisting soil consolidation considering the biodegradation of natural fibres. The identical performance of these two types of PVDs added further evidence to prove how well BPVDs can facilitate soil consolidation.
Nikoloska, R, Bykerk, L, Vitanage, D, Valls Miro, J, Chen, F, Wang, Y & Liang, B 2020, 'Enhancing Sydney Water’s leak prevention through acoustic monitoring', Water e-Journal, vol. 5, no. 2, pp. 1-15.
View/Download from: Publisher's site
Nimbalkar, S, Kolay, PK & Sun, Y 2020, 'Editorial: Geotechnical Innovation for Transport Infrastructures', Frontiers in Built Environment, vol. 6.
View/Download from: Publisher's site
Nimbalkar, S, Pain, A & Annapareddy, VSR 2020, 'A Strain Dependent Approach for Seismic Stability Assessment of Rigid Retaining Wall', Geotechnical and Geological Engineering, vol. 38, no. 6, pp. 6041-6055.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature Switzerland AG. A new method is proposed to evaluate the seismic stability of a rigid retaining wall undergoing translation or rotational failure. In the present method, strain-dependent dynamic properties are used to assess the seismic stability of rigid retaining walls against sliding and overturning failure conditions. The effect of foundation soil properties on the stability of retaining walls is also considered. From the parametric study, it is observed that the foundation soil properties have a significant effect on both sliding and rotational stability of rigid retaining walls. This can be attributed to the use of strain-dependent dynamic properties and the consideration of foundation soil properties. The predictions of the proposed method are compared and verified against the results from other methods proposed in the past. The percentage increase in the results compared to the existing literature is a maximum of 10 and 28% for rigid (bedrock) and flexible (sand deposit) foundation, respectively.
Oberst, S, Halkon, B, Ji, J & Brown, T 2020, 'Preface', Vibration Engineering for a Sustainable Future: Active and Passive Noise and Vibration Control, Vol. 1, vol. 1, pp. v-vi.
Oberst, S, Lai, JCS, Martin, R, Halkon, BJ, Saadatfar, M & Evans, TA 2020, 'Revisiting stigmergy in light of multi-functional, biogenic, termite structures as communication channel', Computational and Structural Biotechnology Journal, vol. 18, pp. 2522-2534.
View/Download from: Publisher's site
View description>>
Termite mounds are fascinating because of their intriguing composition of nu- merous geometric shapes and materials. However, little is known about these structures, or of their functionalities. Most research has been on the basic com- position of mounds compared with surrounding soils. There has been some targeted research on the thermoregulation and ventilation of the mounds of a few species of fungi-growing termites, which has generated considerable inter- est from human architecture. Otherwise, research on termite mounds has been scattered, with little work on their explicit properties.This review is focused on how termites design and build functional structures as nest, nursery and food storage; for thermoregulation and climatisation; as defence, shelter and refuge; as a foraging tool or building material; and for colony communication, either as in indirect communication (stigmergy) or as an information channel essential for direct communication through vibrations (biotremology).Our analysis shows that systematic research is required to study the prop- erties of these structures such as porosity and material composition. High res- olution computer tomography in combination with nonlinear dynamics and methods from computational intelligence may provide breakthroughs in un- veiling the secrets of termite behaviour and their mounds. In particular, the ex- amination of dynamic and wave propagation properties of termite-built struc- tures in combination with a detailed signal analysis of termite activities is re- quired to better understand the interplay between termites and their nest as superorganism. How termite structures serve as defence in the form of disguis- ing acoustic and vibration signals from detection by predators, and what role local and global vibration synchronisation plays for building are open ques- tions that need to be addressed to provide insights into how termites utilise materials to thrive in a world of predators and competitors.
Ogie, R & Pradhan, B 2020, 'Social vulnerability to natural hazards in Wollongong: Comparing strength-based and traditional methods', Australian Journal of Emergency Management, vol. 35, no. 1, pp. 60-68.
View description>>
Social vulnerability is a widely recognised way of assessing the sensitivity of a population to natural hazards and its ability to respond to and recover from them. In the traditional approach to computing social vulnerability, the emphasis is mainly on the weaknesses only (e.g. old age, low income, language barriers). This study presents a strengthbased social vulnerability index that identifies the strengths that communities have that help minimise disaster risk exposure. The strength-based social vulnerability index method is compared with the traditional approach using various statistical procedures like the one-sample T-test and the Wilcoxon signed rank test. This is performed through a case study measuring the social vulnerability for the 108 suburbs of Wollongong in New South Wales. The results show there is a significant difference between the values obtained from measurements using the strength-based social vulnerability index technique and those generated by the traditional approach. The implications of the results for emergency and disaster management are broadly discussed.
Pain, A, Nimbalkar, S & Hussain, M 2020, 'Applicability of Bouc-Wen Model to Capture Asymmetric Behavior of Sand at High Cyclic Shear Strain', International Journal of Geomechanics, vol. 20, no. 6, pp. 06020009-06020009.
View/Download from: Publisher's site
Pardeshi, V, Nimbalkar, S & Khabbaz, H 2020, 'Field Assessment of Gravel Loss on Unsealed Roads in Australia', Frontiers in Built Environment, vol. 6, pp. 1-11.
View/Download from: Publisher's site
View description>>
The gravel loss is a major limitation for unsealed roads and it needs major maintenance annually. The continual process of gravel loss leads to the unsustainability of these roads. The unsealed road management faces several issues, viz., difficulty to forecast behavior, huge data collection needs, and a vulnerability in the service and maintenance practices. The quality of gravel material also plays a major role in the process of gravel loss. In view of the aforementioned, appropriate revisions to ARRB material specifications are proposed in this study. The gravel material as per modified ARRB specifications is used on the unsealed road network in the Scenic Rim Regional Council in the state of Queensland. Gravel loss monitoring stations were established over the entire region in order to assess the gravel loss and the implication of using a better quality of gravel material. This study discusses the gravel loss monitoring approaches, data analyses, and improved material specification for gravel. It is found that the modified gravel used on unsealed road performs better than conventionally used gravel.
Paryani, S, Neshat, A, Javadi, S & Pradhan, B 2020, 'Comparative performance of new hybrid ANFIS models in landslide susceptibility mapping', Natural Hazards, vol. 103, no. 2, pp. 1961-1988.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature B.V. Abstract: Many landslides occur in the Karun watershed in the Zagros Mountains. In the present study, we employed a novel comparative approach for spatial modeling of landslides given the high potential of landslides in the region. The aim of the study was to combine adaptive neuro-fuzzy inference system (ANFIS) with grey wolf optimizer (GWO) and particle swarm optimizer (PSO) algorithms using the outputs of qualitative stepwise weight assessment ratio analysis (SWARA) and quantitative certainty factor (CF) models. To this end, 264 landslide positions and twelve conditioning factors including slope, aspect, altitude, distance to faults, distance to rivers, distance to roads, land use, lithology, rainfall, plan and profile curvature and TWI were then extracted considering regional characteristics, literature review and available data. In the next step, the multi-criteria SWARA decision-making model and CF probability model were used to evaluate a correlation between landslide distribution and conditioning factors. Ultimately, landslide susceptibility maps were generated by ANFIS-GWO and ANFIS-PSO hybrid models and the accuracy of models was assessed by ROC curve. According to the results, the area under the curve (AUC) for the hybrid models ANFIS - GWO SWARA, ANFIS - PSO SWARA, ANFIS - GWO CF and ANFIS - PSO CF was 0.789, 0.838, 0.850 and 0.879, respectively. The hybrid models ANFIS - PSO CF and ANFIS - GWO SWARA showed the highest and lowest prediction rate, respectively. Moreover, CF outperformed the SWARA method in terms of evaluating correlation between conditioning factors and landslides. The map produced in this study can be used by regional authorities to manage landslide risk. Graphic abstract: [Figure not available: see fulltext.].
Paryani, S, Neshat, A, Javadi, S & Pradhan, B 2020, 'GIS-based comparison of the GA-LR ensemble method and statistical models at Sefiedrood Basin, Iran', Arabian Journal of Geosciences, vol. 13, no. 19.
View/Download from: Publisher's site
Pashaki, PV & Ji, J-C 2020, 'Nonlocal nonlinear vibration of an embedded carbon nanotube conveying viscous fluid by introducing a modified variational iteration method', Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 42, no. 4.
View/Download from: Publisher's site
Peters, A, Liang, B, Tian, H, Li, Z, Doolan, C, Vitanage, D, Norris, H, Simpson, K, Wang, Y & Chen, F 2020, 'Data-driven water quality prediction in chloraminated systems', Water e-Journal, vol. 5, no. 4, pp. 1-19.
View/Download from: Publisher's site
View description>>
This paper proposes a data-driven method that provides water quality prediction within the entire Woronora delivery system in Sydney. Specifically, the key factors relating to water quality are identified through factor analysis. A Bayesian parametric decay model is formulated using the key factors to predict water quality. To estimate the water travel time, which links the upstream (reservoir) data to the downstream (resident) data, the hydraulic system is employed to capture the topology of the delivery system. Moreover, the uncertainties of both data and the model are analysed to define the boundaries of prediction for better decision making.
Pradhan, B 2020, 'Preface', Advances in Science, Technology and Innovation, pp. v-x.
Pradhan, B, Al-Najjar, HAH, Sameen, MI, Mezaal, MR & Alamri, AM 2020, 'Landslide Detection Using a Saliency Feature Enhancement Technique From LiDAR-Derived DEM and Orthophotos', IEEE Access, vol. 8, pp. 121942-121954.
View/Download from: Publisher's site
Pradhan, B, Al-Najjar, HAH, Sameen, MI, Tsang, I & Alamri, AM 2020, 'Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks', Remote Sensing, vol. 12, no. 10, pp. 1676-1676.
View/Download from: Publisher's site
View description>>
Zero-shot learning (ZSL) is an approach to classify objects unseen during the training phase and shown to be useful for real-world applications, especially when there is a lack of sufficient training data. Only a limited amount of works has been carried out on ZSL, especially in the field of remote sensing. This research investigates the use of a convolutional neural network (CNN) as a feature extraction and classification method for land cover mapping using high-resolution orthophotos. In the feature extraction phase, we used a CNN model with a single convolutional layer to extract discriminative features. In the second phase, we used class attributes learned from the Word2Vec model (pre-trained by Google News) to train a second CNN model that performed class signature prediction by using both the features extracted by the first CNN and class attributes during training and only the features during prediction. We trained and tested our models on datasets collected over two subareas in the Cameron Highlands (training dataset, first test dataset) and Ipoh (second test dataset) in Malaysia. Several experiments have been conducted on the feature extraction and classification models regarding the main parameters, such as the network’s layers and depth, number of filters, and the impact of Gaussian noise. As a result, the best models were selected using various accuracy metrics such as top-k categorical accuracy for k = [1,2,3], Recall, Precision, and F1-score. The best model for feature extraction achieved 0.953 F1-score, 0.941 precision, 0.882 recall for the training dataset and 0.904 F1-score, 0.869 precision, 0.949 recall for the first test dataset, and 0.898 F1-score, 0.870 precision, 0.838 recall for the second test dataset. The best model for classification achieved an average of 0.778 top-one, 0.890 top-two and 0.942 top-three accuracy, 0.798 F1-score, 0.766 recall and 0.838 precision for the first test dataset and 0.737 top-one, 0.906 top-two...
Premadasa, W & Indraratna, B 2020, 'Discussion of “Numerical Simulation of the Shear Behavior of Rock Joints Filled with Unsaturated Soil” by Libin Gong, Jan Nemcik, and Ting Ren', International Journal of Geomechanics, vol. 20, no. 4, pp. 07020001-07020001.
View/Download from: Publisher's site
Punetha, P, Nimbalkar, S & Khabbaz, H 2020, 'Analytical Evaluation of Ballasted Track Substructure Response under Repeated Train Loads', International Journal of Geomechanics, vol. 20, no. 7, pp. 04020093-04020093.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. The irrecoverable deformations in the substructure layers are detrimental to the track stability and demand frequent maintenance. With an escalation in axle load and traffic volume, the frequency of maintenance operations has remarkably increased. Consequently, there is an inevitable need to predict the long-term behavior of the track substructure layers. This article presents a methodology to evaluate the recoverable and irrecoverable responses of the substructure layers under the train-induced repetitive loads. The present method utilizes an integrated approach combining track loading, resiliency, and settlement models. The track substructure layers are simulated as lumped masses that are connected by springs and dashpots. The method is successfully validated against the field investigation data reported in the literature. A parametric study is conducted to investigate the influence of substructure layer properties on the track response. The results reveal that the response of each track layer is significantly influenced by the neighboring layer properties and the incorporation of multilayered track structure enables more accurate prediction of track behavior. The present analytical approach is simple, computationally efficient and may assist the practicing engineers in the safer design of the ballasted track.
Punetha, P, Nimbalkar, S & Khabbaz, H 2020, 'Evaluation of additional confinement for three-dimensional geoinclusions under general stress state', Canadian Geotechnical Journal, vol. 57, no. 3, pp. 453-461.
View/Download from: Publisher's site
View description>>
Three-dimensional cellular geoinclusions (e.g., geocells, scrap tires) offer all-around confinement to the granular infill materials, thus improving their strength and stiffness. The accurate evaluation of extra confinement offered by these geoinclusions is essential for predicting their performance in the field. The existing models to evaluate the additional confinement are based on either a plane-strain or axisymmetric stress state. However, these geoinclusions are more likely to be subjected to the three-dimensional stresses in actual practice. This note proposes a semi-empirical model to evaluate the additional confinement provided by cellular geoinclusions under the three-dimensional stress state. The proposed model is successfully validated against the experimental data. A parametric study is conducted to investigate the influence of input parameters on additional confinement. Results reveal that the simplification of the three-dimensional stress state into axisymmetric or plane-strain condition has resulted in inaccurate and unreliable results. The extra confinement offered by the geoinclusion shows substantial variation along the intermediate and minor principal stress directions depending on the intermediate principal stress, infill soil, and geoinclusion properties. The magnitude of additional confinement increases with an increase in the geoinclusion modulus. The findings are crucial for accurate assessment of the in situ performance of three-dimensional cellular geoinclusions.
Qi, Y & Indraratna, B 2020, 'Energy-Based Approach to Assess the Performance of a Granular Matrix Consisting of Recycled Rubber, Steel-Furnace Slag, and Coal Wash', Journal of Materials in Civil Engineering, vol. 32, no. 7, pp. 04020169-04020169.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. Ballasted track progressively deteriorates due to ballast degradation and track deformation under dynamic loading, and this process accelerates when train speeds increase and axle loads become heavier as the railways are seeking to serve the enhanced productivity of the mining and agriculture sectors; on this basis, improving track performance is imperative. One effective solution is to incorporate energy-absorbing materials in the rail track, particularly when these materials are recycled from mining waste and recycled rubber. In this paper the performance of the track specimen with a synthetic energy absorbing layer (SEAL) (i.e., a matrix of recycled rubber crumbs with mining waste) is investigated by a series of large-scale (prototype) cubical triaxial tests. The test results indicate that the inclusion of rubber inside the SEAL matrix has a significant influence on the lateral movement, vertical deformation, ballast degradation, and energy distribution of the track specimen. To facilitate a better understanding of the energy-absorbing mechanism with the addition of rubber, an energy-based analysis has been adopted to identify the critical amount of rubber crumbs needed to efficiently distribute the accumulated energy, hence improve track performance. It is shown that adding 10% of rubber into the SEAL matrix will provide superior performance with less ballast breakage, less vibration (as reflected by the elastic energy), and comparable settlement compared to traditional track.
Qu, F, Li, W, Zeng, X, Luo, Z, Wang, K & Sheng, D 2020, 'Effect of microlimestone on properties of self-consolidating concrete with manufactured sand and mineral admixture', Frontiers of Structural and Civil Engineering, vol. 14, no. 6, pp. 1545-1560.
View/Download from: Publisher's site
View description>>
© 2020, Higher Education Press. Self-consolidating concrete (SCC) with manufactured sand (MSCC) is crucial to guarantee the quality of concrete construction technology and the associated property. The properties of MSCC with different microlimestone powder (MLS) replacements of retreated manufactured sand (TMsand) are investigated in this study. The result indicates that high-performance SCC, made using TMsand (TMSCC), achieved high workability, good mechanical properties, and durability by optimizing MLS content and adding fly ash and silica fume. In particular, the TMSCC with 12% MLS content exhibits the best workability, and the TMSCC with 4% MLS content has the highest strength in the late age, which is even better than that of SCC made with the river sand (Rsand). Though MLS content slightly affects the hydration reaction of cement and mainly plays a role in the nucleation process in concrete structures compared to silica fume and fly ash, increasing MLS content can evidently have a significant impact on the early age hydration progress. TMsand with MLS content ranging from 8% to 12% may be a suitable alternative for the Rsand used in the SCC as fine aggregate. The obtained results can be used to promote the application of SCC made with manufactured sand and mineral admixtures for concrete-based infrastructure.
Rahim, MS, Nguyen, KA, Stewart, RA, Giurco, D & Blumenstein, M 2020, 'Machine Learning and Data Analytic Techniques in Digital Water Metering: A Review', Water, vol. 12, no. 1, pp. 294-294.
View/Download from: Publisher's site
View description>>
Digital or intelligent water meters are being rolled out globally as a crucial component in improving urban water management. This is because of their ability to frequently send water consumption information electronically and later utilise the information to generate insights or provide feedback to consumers. Recent advances in machine learning (ML) and data analytic (DA) technologies have provided the opportunity to more effectively utilise the vast amount of data generated by these meters. Several studies have been conducted to promote water conservation by analysing the data generated by digital meters and providing feedback to consumers and water utilities. The purpose of this review was to inform scholars and practitioners about the contributions and limitations of ML and DA techniques by critically analysing the relevant literature. We categorised studies into five main themes: (1) water demand forecasting; (2) socioeconomic analysis; (3) behaviour analysis; (4) water event categorisation; and (5) water-use feedback. The review identified significant research gaps in terms of the adoption of advanced ML and DA techniques, which could potentially lead to water savings and more efficient demand management. We concluded that further investigations are required into highly personalised feedback systems, such as recommender systems, to promote water-conscious behaviour. In addition, advanced data management solutions, effective user profiles, and the clustering of consumers based on their profiles require more attention to promote water-conscious behaviours.
Rahmati, O, Panahi, M, Ghiasi, SS, Deo, RC, Tiefenbacher, JP, Pradhan, B, Jahani, A, Goshtasb, H, Kornejady, A, Shahabi, H, Shirzadi, A, Khosravi, H, Moghaddam, DD, Mohtashamian, M & Tien Bui, D 2020, 'Hybridized neural fuzzy ensembles for dust source modeling and prediction', Atmospheric Environment, vol. 224, pp. 117320-117320.
View/Download from: Publisher's site
Ramos, A, Gomes Correia, A, Indraratna, B, Ngo, T, Calçada, R & Costa, PA 2020, 'Mechanistic-empirical permanent deformation models: Laboratory testing, modelling and ranking', Transportation Geotechnics, vol. 23, pp. 100326-100326.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Geomaterials exhibit elastoplastic behaviour during dynamic and repeated loading conditions. These loads are induced by the passage of a train or vehicle which then generates recoverable (resilient) deformation and/or permanent (plastic) deformation. Modelling this behaviour is still a challenge for geotechnical engineers as it implies the understanding of the complex deformation mechanism and application of advanced constitutive models. This paper reviews on the major causes of permanent deformation and the factors that influence the long-term performance of materials. It will also present the fundamental concepts of permanent deformation as well as the models and approaches used to characterise this behaviour, including: elastoplastic models, shakedown theory and mechanistic-empirical permanent deformation models. This paper will focus on the mechanistic-empirical approach and highlight the evolution of the models, and the main similarities and differences between them. A comparison between several empirical models as well as the materials used to develop the models is also discussed. These materials are compared by considering the reference conditions on the type of material and its physical state. This approach allows for an understanding of which properties can influence the performance of railway subgrade and pavement structures, as well as the main variables used to characterise this particular behaviour. An innovative ranking of geomaterials that relate to the expected permanent deformation and classification (UIC and ASTM) of soil is also discussed because it can be used as an important tool for the design process.
Rasouli, H & Fatahi, B 2020, 'Geofoam blocks to protect buried pipelines subjected to strike-slip fault rupture', Geotextiles and Geomembranes, vol. 48, no. 3, pp. 257-274.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd This paper proposes using geofoam blocks to improve the safety of buried steel pipelines under permanent ground deformation due to strike-slip fault rupture. Since these geofoam blocks are deformable, they can compress during fault rupture and thus reduce the pressure imposed on the pipeline by the surrounding soil. This means that the pipe can sustain a higher level of tectonic deformations. For the pipeline system adopted in this study, the geofoam blocks consist of two 1 m thick blocks at each side and another on the top of the pipeline. The effectiveness of this configuration is then assessed in comparison to the conventional buried pipeline by three dimensional numerical simulations that consider the interaction between soil and structure and the impact of critical parameters such as the pipeline-fault trace crossing angle, geofoam blocks thickness and the internal pressure of the pipeline. The results indicated that the geofoam blocks reduced the axial tensile strain of non-pressurised pipeline from the unacceptable 4.16% to the safe level of 0.75% when the crossing angle was 135°. In addition, geofoam blocks successfully decreased the maximum ovalisation parameter and compressive strain of the non-pressurised pipeline from 0.237 and −25.8% to 0.065 and −0.47%, respectively when the crossing angle was 65°.
Rasouli, H, Fatahi, B & Nimbalkar, S 2020, 'Liquefaction and post-liquefaction assessment of lightly cemented sands', Canadian Geotechnical Journal, vol. 57, no. 2, pp. 173-188.
View/Download from: Publisher's site
View description>>
Post-liquefaction response of lightly cemented sands during an earthquake may change and become similar to uncemented sands due to bonding breakage. In the current study, the effect of degree of cementation on liquefaction and post-liquefaction behaviour of lightly cemented sands was studied through a series of cyclic and monotonic triaxial tests. Portland cement with high early strength and Sydney sand were used to reconstitute the lightly cemented specimens with unconfined compression strength ranging from 25 to 220 kPa. A series of multi-stage soil element tests including stress-controlled cyclic loading events with different amplitudes and post-cyclic undrained monotonic shearing tests were carried out on both uncemented and cemented specimens. Furthermore, a series of undrained monotonic shearing tests without cyclic loading history on different types of specimens was conducted to investigate the effect of cyclic loading history on the post-cyclic response of the specimens. The results show that residual excess pore-water pressure is correlated to the cyclic degradation of lightly cemented sands during cyclic loading. In addition, optical microstructure images of the cemented specimens after liquefaction showed that a major proportion of cementation bonds remained unbroken, which resulted in a superior post-liquefaction response with respect to initial stiffness and shear modulus in comparison to the uncemented sand.
Razzak, I, Saris, RA, Blumenstein, M & Xu, G 2020, 'Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection', Neural Networks, vol. 121, pp. 441-451.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd Since the principal component analysis and its variants are sensitive to outliers that affect their performance and applicability in real world, several variants have been proposed to improve the robustness. However, most of the existing methods are still sensitive to outliers and are unable to select useful features. To overcome the issue of sensitivity of PCA against outliers, in this paper, we introduce two-dimensional outliers-robust principal component analysis (ORPCA) by imposing the joint constraints on the objective function. ORPCA relaxes the orthogonal constraints and penalizes the regression coefficient, thus, it selects important features and ignores the same features that exist in other principal components. It is commonly known that square Frobenius norm is sensitive to outliers. To overcome this issue, we have devised an alternative way to derive objective function. Experimental results on four publicly available benchmark datasets show the effectiveness of joint feature selection and provide better performance as compared to state-of-the-art dimensionality-reduction methods.
Roslidar, R, Rahman, A, Muharar, R, Syahputra, MR, Arnia, F, Syukri, M, Pradhan, B & Munadi, K 2020, 'A Review on Recent Progress in Thermal Imaging and Deep Learning Approaches for Breast Cancer Detection', IEEE Access, vol. 8, pp. 116176-116194.
View/Download from: Publisher's site
View description>>
© 2013 IEEE. Developing a breast cancer screening method is very important to facilitate early breast cancer detection and treatment. Building a screening method using medical imaging modality that does not cause body tissue damage (non-invasive) and does not involve physical touch is challenging. Thermography, a non-invasive and non-contact cancer screening method, can detect tumors at an early stage even under precancerous conditions by observing temperature distribution in both breasts. The thermograms obtained on thermography can be interpreted using deep learning models such as convolutional neural networks (CNNs). CNNs can automatically classify breast thermograms into categories such as normal and abnormal. Despite their demostrated utility, CNNs have not been widely used in breast thermogram classification. In this study, we aimed to summarize the current work and progress in breast cancer detection based on thermography and CNNs. We first discuss of breast thermography potential in early breast cancer detection, providing an overview of the availability of breast thermal datasets together with publicly accessible. We also discuss characteristics of breast thermograms and the differences between healthy and cancerous thermographic patterns. Breast thermogram classification using a CNN model is described step by step including a simulation example illustrating feature learning. We cover most research related to the implementation of deep neural networks for breast thermogram classification and propose future research directions for developing representative datasets, feeding the segmented image, assigning a good kernel, and building a lightweight CNN model to improve CNN performance.
Rostami, AA, Karimi, V, Khatibi, R & Pradhan, B 2020, 'An investigation into seasonal variations of groundwater nitrate by spatial modelling strategies at two levels by kriging and co-kriging models', Journal of Environmental Management, vol. 270, pp. 110843-110843.
View/Download from: Publisher's site
View description>>
Nitrate pollution of groundwater through spatial models is investigated in this paper by using a sample of nitrate values at monitoring wells using the data from four seasons of a year, in which data are sparse. Two spatial modelling strategies are formulated at two levels, in which Strategy 1 comprises: three variations of kriging-based models (ordinary kriging, simple kriging and universal kriging), which are constructed at Level 1 to predict nitrate concentrations; and a Multiple Co-Kriging (MCoK) model is used at Level 2 to enhance the accuracy of the predictions. Strategy 2 is also at two levels but employs Indicator Kriging (IK) at Level 1 as a probabilistic spatial model to predict areas at risk of exceeding two thresholds of 37.5 mg/L and 50 mg/L of nitrate concentration, and Multiple Co-Indicator Kriging (MCoIK) at Level 2 for a better accuracy. The improvements at Level 2 for both strategies are remarkable and hence they are used to gain an insight into inherent problems. The results of a study delineate areas with excessive nitrate concentrations, which are in the vicinity of urban areas and hence reflect poor planning practices since the 1990s. The results further reveal the patterns on sensitivities to seasonal variations driven by aquifer recharge and strong dilution processes in spring times; and on the role of pumpage impacting aquifers giving rise to possible hotspots of nitrate concentrations.
Roy, P, Chandra Pal, S, Arabameri, A, Chakrabortty, R, Pradhan, B, Chowdhuri, I, Lee, S & Tien Bui, D 2020, 'Novel Ensemble of Multivariate Adaptive Regression Spline with Spatial Logistic Regression and Boosted Regression Tree for Gully Erosion Susceptibility', Remote Sensing, vol. 12, no. 20, pp. 3284-3284.
View/Download from: Publisher's site
View description>>
The extreme form of land degradation through different forms of erosion is one of the major problems in sub-tropical monsoon dominated region. The formation and development of gullies is the dominant form or active process of erosion in this region. So, identification of erosion prone regions is necessary for escaping this type of situation and maintaining the correspondence between different spheres of the environment. The major goal of this study is to evaluate the gully erosion susceptibility in the rugged topography of the Hinglo River Basin of eastern India, which ultimately contributes to sustainable land management practices. Due to the nature of data instability, the weakness of the classifier andthe ability to handle data, the accuracy of a single method is not very high. Thus, in this study, a novel resampling algorithm was considered to increase the robustness of the classifier and its accuracy. Gully erosion susceptibility maps have been prepared using boosted regression trees (BRT), multivariate adaptive regression spline (MARS) and spatial logistic regression (SLR) with proposed resampling techniques. The re-sampling algorithm was able to increase the efficiency of all predicted models by improving the nature of the classifier. Each variable in the gully inventory map was randomly allocated with 5-fold cross validation, 10-fold cross validation, bootstrap and optimism bootstrap, while each consisted of 30% of the database. The ensemble model was tested using 70% and validated with the other 30% using the K-fold cross validation (CV) method to evaluate the influence of the random selection of training and validation database. Here, all resampling methods are associated with higher accuracy, but SLR bootstrap optimism is more optimal than any other methods according to its robust nature. The AUC values of BRT optimism bootstrap, MARS optimism bootstrap and SLR optimism bootstrap are 87.40%, 90.40% and 90.60%, respectively. According ...
Sadeghi, F, Li, J & Zhu, X 2020, 'A Steel-Concrete Composite Beam Element for Structural Damage Identification', International Journal of Structural Stability and Dynamics, vol. 20, no. 10, pp. 2042015-2042015.
View/Download from: Publisher's site
View description>>
The composite action between the layers of steel and concrete is governed by the shear connection. Because of the complicated interconnection behavior of these composite layers, it is difficult to detect damage in the composite structures, especially, the interfacial integrity of the two layers. In this paper, anovel method has been developed for structural damage identification of composite structures based on a steel-concrete composite beam element with bonding interface. In displacement-based finite element (FE) formulation, three damage indicators have been embedded into stiffness matrix of the composite beam that are defined as a stiffness reduction in the concrete, steel and interface layers. An algorithm-based on recursive quadratic programming has been proposed to identify structural damage in the composite beam from static measurements. The analytical FE model is validated by adapting its static responses in undamaged state with those obtained from an equal experimental model as well as a FE model developed in commercial software ABAQUS. A convergence study is conducted to determine the number of the composite beam FEs. To verify the proposed method, the static responses of the FE model with different damage cases at a given loading are calculated, and the measurements are simulated by adding different levels of white noise. Then, the proposed algorithm is applied to identify damage of the composite beam. The effects of measurement noise, loading location and amplitude, measurement numbers and the sizes of FE mesh on the identified results have been investigated. The numerical results show that this method is efficient and accurate to separately identify small damage in the concrete slab, and the steel girder and bonding interface of the composite beam.
Saha, S, Saha, A, Hembram, TK, Pradhan, B & Alamri, AM 2020, 'Evaluating the Performance of Individual and Novel Ensemble of Machine Learning and Statistical Models for Landslide Susceptibility Assessment at Rudraprayag District of Garhwal Himalaya', Applied Sciences, vol. 10, no. 11, pp. 3772-3772.
View/Download from: Publisher's site
View description>>
Landslides are known as the world’s most dangerous threat in mountainous regions and pose a critical obstacle for both economic and infrastructural progress. It is, therefore, quite relevant to discuss the pattern of spatial incidence of this phenomenon. The current research manifests a set of individual and ensemble of machine learning and probabilistic approaches like an artificial neural network (ANN), support vector machine (SVM), random forest (RF), logistic regression (LR), and their ensembles such as ANN-RF, ANN-SVM, SVM-RF, SVM-LR, LR-RF, LR-ANN, ANN-LR-RF, ANN-RF-SVM, ANN-SVM-LR, RF-SVM-LR, and ANN-RF-SVM-LR for mapping landslide susceptibility in Rudraprayag district of Garhwal Himalaya, India. A landslide inventory map along with sixteen landslide conditioning factors (LCFs) was used. Randomly partitioned sets of 70%:30% were used to ascertain the goodness of fit and predictive ability of the models. The contribution of LCFs was analyzed using the RF model. The altitude and drainage density were found to be the responsible factors in causing the landslide in the study area according to the RF model. The robustness of models was assessed through three threshold dependent measures, i.e., receiver operating characteristic (ROC), precision and accuracy, and two threshold independent measures, i.e., mean-absolute-error (MAE) and root-mean-square-error (RMSE). Finally, using the compound factor (CF) method, the models were prioritized based on the results of the validation methods to choose best model. Results show that ANN-RF-LR indicated a realistic finding, concentrating only on 17.74% of the study area as highly susceptible to landslide. The ANN-RF-LR ensemble demonstrated the highest goodness of fit and predictive capacity with respective values of 87.83% (area under the success rate curve) and 93.98% (area under prediction rate curve), and the highest robustness correspondingly. These attempts will play a significant role in ensemble ...
Saharkhiz, MA, Pradhan, B, Rizeei, HM & Jung, HS 2020, 'Land use feature extraction and sprawl development prediction from quickbird satellite imagery using Dempster-Shafer and land transformation model', Korean Journal of Remote Sensing, vol. 36, no. 1, pp. 15-27.
View/Download from: Publisher's site
View description>>
Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future...
Sahoo, S, Dhar, A, Debsarkar, A, Pradhan, B & Alamri, AM 2020, 'Future Water Use Planning by Water Evaluation and Planning System Model', Water Resources Management, vol. 34, no. 15, pp. 4649-4664.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature B.V. Assessment of future water availability is a challenging task under changing climatic conditions and anthropogenic interventions. The current research focuses on future water resources scenario generation for contributing areas of proposed hydraulic structures generated from the Water Evaluation and Planning (WEAP) System model. The proposed methodology was implemented for the Dwarakeswar-Gandherswari river basin (India) which needs a long-term future water use plan. Bias-corrected Representative Concentration Pathways (RCPs) data were used for climate change analysis through a hydrological model. Different simulation model outputs [e.g. Dynamic Conversion of Land-Use and its Effects (Dyna-CLUE), Soil and Water Assessment Tool (SWAT), Modular Finite-Difference Flow Model (MODFLOW)] were utilized in water evaluation model for a generation of future water resources scenarios. Four scenarios (2010–2030–2050-2080) were generated for the sustainability of limited water resources management strategies. SWAT simulated results show an increase in river discharge for 2030 or 2080 and a decrease for 2050. MODFLOW simulated results show a visible groundwater storage change for 2030 but minimal change for 2050 and 2080 scenarios. The results also show a decrease in agricultural land and an increase in population for the contributing areas of three hydraulic structures during 2010–2030–2050-2080. These results provide a piece of valuable information for decision-makers in future water management plan preparation.
Saki, M, Abolhasan, M & Lipman, J 2020, 'A Novel Approach for Big Data Classification and Transportation in Rail Networks', IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 3, pp. 1239-1249.
View/Download from: Publisher's site
View description>>
This paper introduces a new framework into future data-driven railway condition monitoring systems (RCM). For this purpose, we have proposed an edge processing unit that includes two main parts: a data classification model that classifies Internet of Things (IoT) data into maintenance-critical data (MCD) and maintenance-non-critical data (MNCD) and a data transmission unit that, based on the class of data, employs appropriate communication methods to transmit data to railway control centers. For the transmission of MNCD, we propose a travel pattern method that employs train stations as points of data offloading so that trains can deliver data as well as passengers at stations. The performance of our proposed solution is successfully validated via three various data sets under different operating conditions.
Saki, M, Abolhasan, M, Lipman, J & Jamalipour, A 2020, 'A Comprehensive Access Point Placement for IoT Data Transmission Through Train-Wayside Communications in Multi-Environment Based Rail Networks', IEEE Transactions on Vehicular Technology, vol. 69, no. 10, pp. 11937-11949.
View/Download from: Publisher's site
View description>>
In this paper, we propose three algorithms for placement of access points (APs) for the purpose of data transportation via train-to-wayside (T2W) communications along a rail network. The first algorithm is proposed to find the minimum number of APs so that the path-loss (PL) does not exceed a desired threshold. Through the second algorithm, the most optimal places for a desired number of APs are determined so that the average PL is minimum. The goal of the third algorithm is to determine the required number and optimal places of APs in a rail network. Furthermore, we propose a model to consider the effects of changes of communication characteristics on the efficiency of the network in different environments. Through such model, the algorithms proposed for placement of APs can be used in different railway scenarios. The proposed algorithms are validated through extensive simulations in Sydney Trains of Australia. The simulation results show that the proposed approach can improve the efficiency of the system at least 21% and up to 165% within 10 different scenarios. We also show that we can approximately transmit over 250 Gigabit data through T2W communications over common WiFi networks.
Sameen, MI, Pradhan, B & Lee, S 2020, 'Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment', CATENA, vol. 186, pp. 104249-104249.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier B.V. This study developed a deep learning based technique for the assessment of landslide susceptibility through a one-dimensional convolutional network (1D-CNN) and Bayesian optimisation in Southern Yangyang Province, South Korea. A total of 219 slide inventories and 17 slide conditioning variables were obtained for modelling. The data showed a complex scenario. Some past slides have spread over steep lands, while others have spread through flat terrain. Random forest (RF) served to keep only important factors for further analysis as a pre-processing measure. To select CNN hyperparameters, Bayesian optimization was used. Three methods contributed to overcoming the overfitting issue owing to small training data in our research. The selection of key factors by RF helped first of all to reduce information dimensionality. Second, the CNN model with 1D convolutions was intended to considerably decrease the number of its parameters. Third, a high rate of drop-out (0.66) helped reduce the CNN parameters. Overall accuracy, area under the receiver operating characteristics curve (AUROC) and 5-fold cross-validation were used to evaluate the models. CNN performance was compared to ANN and SVM. CNN achieved the highest accuracy on testing dataset (83.11%) and AUROC (0.880, 0.893, using testing and 5-fold CV, respectively). Bayesian optimization enhanced CNN accuracy by~3% (compared with default configuration). CNN could outperform ANN and SVM owing to its complicated architecture and handling of spatial correlations through convolution and pooling operations. In complex situations where some variables make a non-linear contribution to the occurrence of landslides, the method suggested could thus help develop landslide susceptibility maps.
Sameen, MI, Pradhan, B, Bui, DT & Alamri, AM 2020, 'Systematic sample subdividing strategy for training landslide susceptibility models', CATENA, vol. 187, pp. 104358-104358.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier B.V. Current practice in choosing training samples for landslide susceptibility modelling (LSM) is to randomly subdivide inventory information into training and testing samples. Where inventory data differ in distribution, the selection of training samples by a random process may cause inefficient training of machine learning (ML)/statistical models. A systematic technique may, however, produce efficient training samples that well represent the entire inventory data. This is particularly true when inventory information is scarce. This research proposed a systemic strategy to deal with this problem based on the fundamental distribution of probabilities (i.e. Hellinger) and a novel graphical representation of information contained in inventory data (i.e. inventory information curve, IIC). This graphical representation illustrates the relative increase in available information with the growth of the training sample size. Experiments on a selected dataset over the Cameron Highlands, Malaysia were conducted to validate the proposed methods. The dataset contained 104 landslide inventories and 7 landslide-conditioning factors (i.e. altitude, slope, aspect, land use, distance from the stream, distance from the road and distance from lineament) derived from a LiDAR-based digital elevation model and thematic maps acquired from government authorities. In addition, three ML/statistical models, namely, k-nearest neighbour (KNN), support vector machine (SVM) and decision tree (DT), were utilised to assess the proposed sampling strategy for LSM. The impacts of model's hyperparameters, noise and outliers on the performance of the models and the shape of IICs were also investigated and discussed. To evaluate the proposed method further, it was compared with other standard methods such as random sampling (RS), stratified RS (SRS) and cross-validation (CV). The evaluations were based on the area under the receiving characteristic curves. The results show that IICs a...
Sameen, MI, Sarkar, R, Pradhan, B, Drukpa, D, Alamri, AM & Park, H-J 2020, 'Landslide spatial modelling using unsupervised factor optimisation and regularised greedy forests', Computers & Geosciences, vol. 134, pp. 104336-104336.
View/Download from: Publisher's site
Sekandari, M, Masoumi, I, Beiranvand Pour, A, M Muslim, A, Rahmani, O, Hashim, M, Zoheir, B, Pradhan, B, Misra, A & Aminpour, SM 2020, 'Application of Landsat-8, Sentinel-2, ASTER and WorldView-3 Spectral Imagery for Exploration of Carbonate-Hosted Pb-Zn Deposits in the Central Iranian Terrane (CIT)', Remote Sensing, vol. 12, no. 8, pp. 1239-1239.
View/Download from: Publisher's site
View description>>
The exploration of carbonate-hosted Pb-Zn mineralization is challenging due to the complex structural-geological settings and costly using geophysical and geochemical techniques. Hydrothermal alteration minerals and structural features are typically associated with this type of mineralization. Application of multi-sensor remote sensing satellite imagery as a fast and inexpensive tool for mapping alteration zones and lithological units associated with carbonate-hosted Pb-Zn deposits is worthwhile. Multiple sources of spectral data derived from different remote sensing sensors can be utilized for detailed mapping a variety of hydrothermal alteration minerals in the visible near infrared (VNIR) and the shortwave infrared (SWIR) regions. In this research, Landsat-8, Sentinel-2, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and WorldView-3 (WV-3) satellite remote sensing sensors were used for prospecting Zn-Pb mineralization in the central part of the Kashmar–Kerman Tectonic Zone (KKTZ), the Central Iranian Terrane (CIT). The KKTZ has high potential for hosting Pb-Zn mineralization due to its specific geodynamic conditions (folded and thrust belt) and the occurrence of large carbonate platforms. For the processing of the satellite remote sensing datasets, band ratios and principal component analysis (PCA) techniques were adopted and implemented. Fuzzy logic modeling was applied to integrate the thematic layers produced by image processing techniques for generating mineral prospectivity maps of the study area. The spatial distribution of iron oxide/hydroxides, hydroxyl-bearing and carbonate minerals and dolomite were mapped using specialized band ratios and analyzing eigenvector loadings of the PC images. Subsequently, mineral prospectivity maps of the study area were generated by fusing the selected PC thematic layers using fuzzy logic modeling. The most favorable/prospective zones for hydrothermal ore mineralizations and car...
Senanayake, S, Pradhan, B, Huete, A & Brennan, J 2020, 'A Review on Assessing and Mapping Soil Erosion Hazard Using Geo-Informatics Technology for Farming System Management', Remote Sensing, vol. 12, no. 24, pp. 4063-4063.
View/Download from: Publisher's site
View description>>
Soil erosion is a severe threat to food production systems globally. Food production in farming systems decreases with increasing soil erosion hazards. This review article focuses on geo-informatics applications for identifying, assessing and predicting erosion hazards for sustainable farming system development. Several researchers have used a variety of quantitative and qualitative methods with erosion models, integrating geo-informatics techniques for spatial interpretations to address soil erosion and land degradation issues. The review identified different geo-informatics methods of erosion hazard assessment and highlighted some research gaps that can provide a basis to develop appropriate novel methodologies for future studies. It was found that rainfall variation and land-use changes significantly contribute to soil erosion hazards. There is a need for more research on the spatial and temporal pattern of water erosion with rainfall variation, innovative techniques and strategies for landscape evaluation to improve the environmental conditions in a sustainable manner. Examining water erosion and predicting erosion hazards for future climate scenarios could also be approached with emerging algorithms in geo-informatics and spatiotemporal analysis at higher spatial resolutions. Further, geo-informatics can be applied with real-time data for continuous monitoring and evaluation of erosion hazards to risk reduction and prevent the damages in farming systems.
Senanayake, S, Pradhan, B, Huete, A & Brennan, J 2020, 'Assessing Soil Erosion Hazards Using Land-Use Change and Landslide Frequency Ratio Method: A Case Study of Sabaragamuwa Province, Sri Lanka', Remote Sensing, vol. 12, no. 9, pp. 1483-1483.
View/Download from: Publisher's site
View description>>
This study aims to identify the vulnerable landscape areas using landslide frequency ratio and land-use change associated soil erosion hazard by employing geo-informatics techniques and the revised universal soil loss equation (RUSLE) model. Required datasets were collected from multiple sources, such as multi-temporal Landsat images, soil data, rainfall data, land-use land-cover (LULC) maps, topographic maps, and details of the past landslide incidents. Landsat satellite images from 2000, 2010, and 2019 were used to assess the land-use change. Geospatial input data on rainfall, soil type, terrain characteristics, and land cover were employed for soil erosion hazard classification and mapping. Landscape vulnerability was examined on the basis of land-use change, erosion hazard class, and landslide frequency ratio. Then the erodible hazard areas were identified and prioritized at the scale of river distribution zones. The image analysis of Sabaragamuwa Province in Sri Lanka from 2000 to 2019 indicates a significant increase in cropping areas (17.96%) and urban areas (3.07%), whereas less dense forest and dense forest coverage are significantly reduced (14.18% and 6.46%, respectively). The average annual soil erosion rate increased from 14.56 to 15.53 t/ha/year from year 2000 to 2019. The highest landslide frequency ratios are found in the less dense forest area and cropping area, and were identified as more prone to future landslides. The river distribution zones Athtanagalu Oya (A-2), Kalani River-south (A-3), and Kalani River- north (A-9), were identified as immediate priority areas for soil conservation.
Shukla, N, Pradhan, B, Dikshit, A, Chakraborty, S & Alamri, AM 2020, 'A Review of Models Used for Investigating Barriers to Healthcare Access in Australia', International Journal of Environmental Research and Public Health, vol. 17, no. 11, pp. 4087-4087.
View/Download from: Publisher's site
View description>>
Understanding barriers to healthcare access is a multifaceted challenge, which is often highly diverse depending on location and the prevalent surroundings. The barriers can range from transport accessibility to socio-economic conditions, ethnicity and various patient characteristics. Australia has one of the best healthcare systems in the world; however, there are several concerns surrounding its accessibility, primarily due to the vast geographical area it encompasses. This review study is an attempt to understand the various modeling approaches used by researchers to analyze diverse barriers related to specific disease types and the various areal distributions in the country. In terms of barriers, the most affected people are those living in rural and remote parts, and the situation is even worse for indigenous people. These models have mostly focused on the use of statistical models and spatial modeling. The review reveals that most of the focus has been on cancer-related studies and understanding accessibility among the rural and urban population. Future work should focus on further categorizing the population based on indigeneity, migration status and the use of advanced computational models. This article should not be considered an exhaustive review of every aspect as each section deserves a separate review of its own. However, it highlights all the key points, covered under several facets which can be used by researchers and policymakers to understand the current limitations and the steps that need to be taken to improve health accessibility.
Singh, M, Indraratna, B, Rujikiatkamjorn, C & Kelly, R 2020, 'Cyclic response of railway subgrade prone to mud pumping', Australian Geomechanics Journal, vol. 55, no. 1, pp. 43-54.
View description>>
Given the fast pace of growth in today's world, the need for a cost-effective and sustainable mode of transportation is indispensable. Railways provide a mode of mass transportation which facilitates travel between two places. Rails are often laid on subgrade soils with difficult conditions such as low bearing capacity, and high groundwater tables, etc., so when trains pass over these challenging ground conditions, the subgrade softens into a slurry and starts pumping the fines into the upper ballast layers. In Australia, this phenomenon is commonly known as mud pumping or mud holes. This paper investigates the cyclic response of subgrade prone to mud pumping. It is observed that the cyclic stress ratio (CSR) has a threshold value beyond which the cyclic axial strains and mean excess pore pressures rapidly accumulate. An empirical model is proposed to capture the generation of mean excess pore pressure in relation to the applied CSR. Further, numerical simulations have been carried out using PLAXIS2D to model vertical drain inclusions in the railway subsoil. The results indicate that vertical drains not only reduce the accumulation of excess pore pressure but also assist in their dissipation under cyclic loading, thereby providing a viable alternative to mitigate the effects of mud pumping.
Singh, RP, Nimbalkar, S, Singh, S & Choudhury, D 2020, 'Field assessment of railway ballast degradation and mitigation using geotextile', Geotextiles and Geomembranes, vol. 48, no. 3, pp. 275-283.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd Rail tracks continue to deform due to degradation of ballast under the application of heavy train traffic. The resulting track deformations often lead to drainage impairment as well as loss of resiliency. For track replenishment, deep screening of ballast is usually adopted by Indian Railway (IR) either after 10 years or passage of 500 MGT traffic, whichever is earlier. To study the effectiveness of geotextile on track stability and assess possible reductions in maintenance costs, a layer of woven geotextile was installed at the ballast-subgrade interface in Bhusawal-Akola central railway section of IR which is the present study area. The results show that the amount of degradation and fouling are different in UP and DN tracks due to inherent variation in traffic characteristics. This study also shows that the placement of geotextile in the track has led to prolonged maintenance cycle with favorable implications on cost and track shutdown periods. The findings of the present case study results will be useful for IR to reduce the ballast procurement and reuse of discarded material during deep screening in future.
Sinha, A, Chand, S, Wijayaratna, KP, Virdi, N & Dixit, V 2020, 'Comprehensive safety assessment in mixed fleets with connected and automated vehicles: A crash severity and rate evaluation of conventional vehicles', Accident Analysis & Prevention, vol. 142, pp. 105567-105567.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Connected and Automated Vehicle (CAV) technology, although in the development stage, is quickly expanding throughout the vehicle market. However, full market penetration will most likely require considerable planning as key stakeholders, manufacturers, consumers and governing agencies work together to determine optimal deployment strategies. Specifically, road safety is a critical challenge to the widespread deployment and adoption of this disruptive technology. During the transition period fleets will be composed of a combination of CAVs and conventional vehicles, and therefore it is imperative to investigate the repercussions of CAVs on traffic safety at different penetration rates. Since crash severity and frequency in conjunction reflect traffic safety, this study attempts to investigate the effect of CAVs on both crash severity and frequency through a microsimulation modelling exercise. VISSM microsimulation platform is used to simulate a case study of the M1 Geelong Ring Road network (Princes Freeway) in Victoria, Australia. Network performance is evaluated using performance metrics (Total System Travel Time, Delay) and kinematic variables (Speed, acceleration, jerk rate). Surrogate safety measures (time to collision, post encroachment time, etc.) are examined to inspect the safety in the network. The results indicate that the introduction of CAVs does not achieve the expected decrease in crash severity and rates involving manual vehicles, despite the improvement in network performance, given the demand and the set of parameters used in our operational CAV algorithm are intact. Additionally, the study identifies that the safety benefits of CAVs are not proportional to CAV penetration, and full-scale benefits of CAVs can only be achieved at 100 % CAV penetration. Further, considering network efficiency as a performance metric and total crash rate involving conventional vehicles as a safety metric, a Pareto frontier is extracted, for varyi...
Sinha, A, Chand, S, Wijayaratna, KP, Virdi, N & Dixit, V 2020, 'Crash Severity and Rate Evaluation of Conventional Vehicles in Mixed Fleets with Connected and Automated Vehicles', Procedia Computer Science, vol. 170, pp. 688-695.
View/Download from: Publisher's site
View description>>
© 2020 The Authors. Published by Elsevier B.V.All rights reserved. Connected and Automated Vehicle (CAV) technology, although in the development stage, is quickly expanding its market but a full market penetration might not be rapid. The safety concern is the paramount challenge to widespread adoption of this disruptive technology. During the transition period, fleets will be composed of a combination of CAVs and conventional vehicles, therefore it is germane to investigate the repercussions of CAVs on traffic safety at different penetration. Since crash severity and frequency in conjunction reflect the traffic safety, this study attempts to investigate the effect of CAVs on both crash severity and frequency. PTV VISSM microsimulation platform is used to simulate M1 Geelong Ring Road network (Princes Freeway) in Victoria, Australia, which is the testbed for this study. Network performance is evaluated using performance metrics (Total System Travel Time, Delay and instantaneous speed profiles). Surrogate safety measures (time to collision, post encroachment time, etc.) are examined to inspect the safety in the network. The results showed that CAVs would not inevitably decrease the crash severity and crash rate involving manual vehicles, despite the improvement in network performance, given the demand and the set of parameters used in our operational CAV algorithm are intact. Additionally, the study identifies that the safety benefits of CAVs are not proportional to CAV penetration, a full-scale benefits CAVs can only be achieved at 100% CAV penetration. The results presented in this study provide an insight into the repercussion of CAVs on comprehensive traffic safety to the insurance companies and other industry participants, enabling safety-related services and more enterprising business models.
Syifa, M, Kadavi, PR, Lee, C-W & Pradhan, B 2020, 'Landsat images and artificial intelligence techniques used to map volcanic ashfall and pyroclastic material following the eruption of Mount Agung, Indonesia', Arabian Journal of Geosciences, vol. 13, no. 3.
View/Download from: Publisher's site
Tabasi, M, Alesheikh, AA, Sofizadeh, A, Saeidian, B, Pradhan, B & AlAmri, A 2020, 'A spatio-temporal agent-based approach for modeling the spread of zoonotic cutaneous leishmaniasis in northeast Iran', Parasites & Vectors, vol. 13, no. 1, pp. 572-572.
View/Download from: Publisher's site
View description>>
AbstractBackgroundZoonotic cutaneous leishmaniasis (ZCL) is a neglected tropical disease worldwide, especially the Middle East. Although previous works attempt to model the ZCL spread using various environmental factors, the interactions between vectors (Phlebotomus papatasi), reservoir hosts, humans, and the environment can affect its spread. Considering all of these aspects is not a trivial task.MethodsAn agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions.ResultsThe results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends.ConclusionsThis study demonstrates the capability and efficiency of ABM to model and predict the spre...
Tai, P, Indraratna, B & Rujikiatkamjorn, C 2020, 'Consolidation Analysis of Soft Ground Improved by Stone Columns Incorporating Foundation Stiffness', International Journal of Geomechanics, vol. 20, no. 6, pp. 04020067-04020067.
View/Download from: Publisher's site
Takodjou Wambo, JD, Pour, AB, Ganno, S, Asimow, PD, Zoheir, B, Salles, RDR, Nzenti, JP, Pradhan, B & Muslim, AM 2020, 'Identifying high potential zones of gold mineralization in a sub-tropical region using Landsat-8 and ASTER remote sensing data: A case study of the Ngoura-Colomines goldfield, eastern Cameroon', Ore Geology Reviews, vol. 122, pp. 103530-103530.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier B.V. Climatic conditions and vegetation constrain the use of optical satellite imagery as an exploration tool for hydrothermal ore mineralization in tropical and subtropical regions. In this investigation, Landsat-8 and ASTER satellite imagery were used to detect hydrothermal alteration zones associated with gold mineralization in the Ngoura-Colomines region, Eastern Cameroon. The study area contains several gold-bearing quartz veins associated with zones of pyritization, muscovite/sericite, iron oxides, and silicification. Principal Component Analysis (PCA), Independent Component Analysis (ICA), and specialized spectral band ratios were used to extract spectral information related to vegetation, iron oxide/hydroxide minerals, Al–OH, Fe-Mg–OH, carbonate group minerals, and silicification using Landsat-8 data at regional scale. Linear Spectral Unmixing (LSU) algorithm was implemented to ASTER VNIR + SWIR bands for detailed discrimination of hematite, jarosite, kaolinite, muscovite, chlorite and epidote at district scale. The Automated Spectral Hourglass (ASH) technique was employed to extract reference spectra directly from the ASTER bands for producing fraction images of end-members using the LSU. A comprehensive field survey was used to verify the remote sensing results. Petrographic study, X-ray diffraction analysis and reflectance spectroscopy indicated the presence of quartz, goethite and sericite, as well as the absorption features of Fe3+/Fe2+, Al–OH, OH/H2O and SiO2 in the alteration zones. Several hydrothermal alteration zones of iron oxide/hydroxide, clay, carbonate minerals and silicification zones were identified, which are spatially associated with known mining areas and gold occurrences in the study area. High potential prospects were also delineated, including the Ngoura-Colomines prospects and the newly discovered Yangamo-Ndatanga and Taparé-Tapondo prospects in the southwestern and southeastern parts of the study area. Co...
Tempa, K, Sarkar, R, Dikshit, A, Pradhan, B, Simonelli, AL, Acharya, S & Alamri, AM 2020, 'Parametric Study of Local Site Response for Bedrock Ground Motion to Earthquake in Phuentsholing, Bhutan', Sustainability, vol. 12, no. 13, pp. 5273-5273.
View/Download from: Publisher's site
View description>>
Earthquakes, when it comes to natural calamities, are characteristically devastating and pose serious threats to buildings in urban areas. Out of multiple seismic regions in the Himalayas, Bhutan Himalaya is one that reigns prominent. Bhutan has seen several moderate-sized earthquakes in the past century and various recent works show that a major earthquake like the 2015 Nepal earthquake is impending. The southwestern city of Bhutan, Phuentsholing is one of the most populated regions in the country and the present study aims to explore the area using geophysical methods (Multispectral Analysis of Surface Waves (MASW)) for understanding possibilities pertaining to infrastructural development. The work involved a geophysical study on eight different sites in the study region which fall under the local area plan of Phuentsholing City. The geophysical study helps to discern shear wave velocity which indicates the soil profile of a region along with possible seismic hazard during an earthquake event, essential for understanding the withstanding power of the infrastructure foundation. The acquired shear wave velocity by MASW indicates visco-elastic soil profile down to a depth of 22.2 m, and it ranged from 350 to 600 m/s. A site response analysis to understand the correlation of bedrock rigidness to the corresponding depth was conducted using EERA (Equivalent-linear Earthquake Site Response Analysis) software. The amplification factors are presented for each site and maximum amplification factors are highlighted. These results have led to a clear indication of how the bedrock characteristics influence the surface ground motion parameters for the corresponding structure period. The results infer that the future constructional activity in the city should not be limited to two- to five-story buildings as per present practice. Apart from it, a parametric study was initiated to uncover whatever effects rigid bedrock has upon hazard parameters for various d...
Teng, J, Kou, J, Yan, X, Zhang, S & Sheng, D 2020, 'Parameterization of soil freezing characteristic curve for unsaturated soils', Cold Regions Science and Technology, vol. 170, pp. 102928-102928.
View/Download from: Publisher's site
View description>>
© 2019 The soil freezing characteristic curve (SFCC) describes the relationship between the temperature and unfrozen water content in a soil. The SFCC is indispensable in modelling the hydro-mechanical behaviour of frozen soils, but is less understood for the unsaturated soils. A series of SFCC tests of unsaturated silica sand, silt and red clay are preformed based on a newly developed nuclear magnetic resonance (NMR) apparatus, which can precisely control the sample temperature in the magnetic field. The experimental results show that the measured SFCC varies significantly for different initial water contents, and that a lower initial water content leads to a slower increase in unfrozen water content, proving that the SFCC is closely related to the initial unsaturated state. It is found that the thawing curve is better to represent the SFCC, in contrast the freezing curve is significantly affected by the supercooling phenomenon. A new parameterization of the SFCC is presented for unsaturated soils by combining the Clapeyron equation and the model for Soil Water Characteristic Curve (SWCC). A number of test results from the literature and this study are used to validate the new SFCC model. By inputting the parameters for the SWCC and initial state into the proposed model, the predicted SFCC can agree well with the measured results. The new model has a theoretical basis and simple form and is applicable to both saturated and unsaturated soils.
Teng, J, Liu, J, Zhang, S & Sheng, D 2020, 'Modelling frost heave in unsaturated coarse-grained soils', Acta Geotechnica, vol. 15, no. 11, pp. 3307-3320.
View/Download from: Publisher's site
View description>>
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Coarse-grained soils were considered not susceptible to frost heave. However, substantial frost heave has been observed in unsaturated coarse fills in high-speed railway embankments. Recent experimental results in the literature show that vapour transfer has a considerable influence on the frost heaving of coarse-grained soil. However, vapour transfer has rarely been considered in modelling frost heave. This study presents a new frost heave model that considers vapour transfer and its contribution to ice formation. An updated computer program (PCHeave) is developed to account for the vapour transfer in unsaturated coarse-grained soils, where the rigid ice theory is applied to initiate ice lens formation in the frozen fringe. The results of the proposed model are compared with laboratory test results, which show reasonable agreement. The frost heave data monitored in 2013–2014 along the embankment of the Harbin–Dalian Passenger Dedicated Railway are also used to validate the proposed model. The prediction of the model agrees well with the measured results of frost heave and frost depth. This indicates that the proposed model can reasonably reflect the process of frost heave caused by vapour transfer in unsaturated coarse-grained soils.
Thanh, HT, Li, J & Zhang, YX 2020, 'Numerical simulation of self-consolidating engineered cementitious composite flow with the V-funnel and U-box', Construction and Building Materials, vol. 236, pp. 117467-117467.
View/Download from: Publisher's site
Tian, S, Indraratna, B, Tang, L, Qi, Y & Ling, X 2020, 'A semi-empirical elasto-plastic constitutive model for coarse-grained materials that incorporates the effects of freeze-thaw cycles', Transportation Geotechnics, vol. 24, pp. 100373-100373.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd A volume-shear coupling mechanism is imperative for developing high-speed railways in very cold regions. A series of consolidated drained static triaxial experiments were carried out to investigate the effect of freeze-thaw (F-T) cycles on the stress-strain features of coarse-grained materials (CGM) typically used at the bottom layer of subgrade for high-speed rail tracks in China. Mathematical expressions describing the effect of F-T cycles for residual stress state stress ratio, elastic shear modulus, and specific volume have been proposed. Laboratory observations enabled an empirical dilatancy equation to be incorporated in a constitutive model to capture the salient aspects of the monotonic deformation behaviour of CGM including the F-T effects. After comparing with experimental observations and validating through past independent studies, the proposed constitutive model could accurately predict the monotonic shear behaviour of the CGM exposed to F-T cycles.
Tofigh, F, Amiri, M, Shariati, N, Lipman, J & Abolhasan, M 2020, 'Crowd Estimation Using Electromagnetic Wave Power-Level Measurements: A Proof of Concept', IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 784-792.
View/Download from: Publisher's site
View description>>
© 1967-2012 IEEE. Current crowd density estimation technologies that leverage IR depth perception, video and image processing or WiFi/BLE-based sniffing and probing have privacy and deployment issues. This paper presents a novel method for non-intrusive crowd density estimation that monitors variation in EM radiation within an environment. The human body's electrical and magnetic characteristics can be correlated with variations in available EM energy. This allows for the determination of the number of people within a room. Simulations conducted using Comsol to analyse and measure electromagnetic energy levels inside a room containing human bodies. Experimental analysis provides validation of the simulation results by showing $\text{0.8}\;\text{dBm}$ drop on the average level of EM energy per person.
Tofigh, F, Amiri, M, Shariati, N, Lipman, J & Abolhasan, M 2020, 'Polarization-Insensitive Metamaterial Absorber for Crowd Estimation Based on Electromagnetic Energy Measurements', IEEE Transactions on Antennas and Propagation, vol. 68, no. 3, pp. 1458-1467.
View/Download from: Publisher's site
View description>>
© 2020 IEEE. Noninvasive crowd estimation has remained a challenging issue among researchers. Methods such as image analysis and Wi-Fi/Bluetooth probing can always be used to identify and track people. Lately, authors have introduced a noninvasive method for crowd estimation based on ambient RF energy measurements. In this article, a polarization-insensitive multilayer metamaterial absorber is introduced to measure the variation in the available RF energy levels for crowd estimation purposes. The proposed dual-band absorber is designed to absorb and transfer the maximum of the available Wi-Fi energy to a lumped element to enable proper and accurate measurements. To evaluate the design, the proposed structure is fabricated as an array, and its performance is tested, proving perfect absorption at the desired frequencies, 2.4 and 5 GHz.
Toghroli, A, Mehrabi, P, Shariati, M, Trung, NT, Jahandari, S & Rasekh, H 2020, 'Evaluating the use of recycled concrete aggregate and pozzolanic additives in fiber-reinforced pervious concrete with industrial and recycled fibers', Construction and Building Materials, vol. 252, pp. 118997-118997.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The aim of this study is to investigate the effects of using recycled concrete aggregate (RCA) and pozzolanic materials as a partial replacement of natural coarse aggregate (NCA) and cement, respectively, on the mechanical and permeability properties of fiber-reinforced pervious concrete mixes. For this purpose, mixes were prepared with 25%, 50%, 75%, and 100% (by weight) RCA as coarse aggregate, and cement was partially replaced with 10% silica fume (SF) and 1%, 2%, and 3% nano-clay (NC). In order to enhance the mechanical strength of mixes, steel fiber (STF) and waste plastic fiber (WPF) were incorporated in the mixtures at a volume fraction of 1% and 2%. The experiments were carried out on a total number of 2310 samples casted from 110 mixes. Based on the test results, up to 25% increase in permeability and about 60% reduction in strength properties of mix incorporating 100% RCA were observed. The use of SF and NC led to enhancements in the strength properties because of micro-filling ability and pozzolanic reactivity. In general, the addition of fibers enhanced both compressive and flexural strengths up to 65% and 79%, respectively, over that of the unreinforced counterpart mix by incorporating 2% STF. WPF-reinforced mixes showed inferior performance compared to the STF-reinforced counterparts, due to the low quality and poor dispersion of WPF in mixes. It was found that, incorporating 100% RCA combined with 2% STF and 2% NC yields a pervious concrete suitable for structural applications.
Tong, C-X, Burton, GJ, Zhang, S & Sheng, D 2020, 'Particle breakage of uniformly graded carbonate sands in dry/wet condition subjected to compression/shear tests', Acta Geotechnica, vol. 15, no. 9, pp. 2379-2394.
View/Download from: Publisher's site
Torghabeh, AK, Pradhan, B & Jahandari, A 2020, 'Assessment of geochemical and sedimentological characteristics of atmospheric dust in Shiraz, southwest Iran', Geoscience Frontiers, vol. 11, no. 3, pp. 783-792.
View/Download from: Publisher's site
View description>>
© 2019 China University of Geosciences (Beijing) and Peking University Geogenic dust is commonly believed to be one of the most important environmental problems in the Middle East. The present study investigated the geochemical characteristics of atmospheric dust particles in Shiraz City (south of Iran). Atmospheric dust samples were collected through a dry collector method by using glass trays at 10 location sites in May 2018. Elemental composition was analysed through inductively coupled plasma optical emission spectrometry. Meteorological data showed that the dustiest days were usually in spring and summer, particularly in April. X-ray diffraction analysis of atmospheric dust samples indicated that the mineralogical composition of atmospheric dust was calcite + dolomite (24%)>palygorskite (18%)>quartz (14%)>muscovite (13%)>albite (11%)>kaolinite (7%)>gypsum (7%)>zircon = anatase (3%). The high occurrence of palygorskite (16%–23%) could serve as a tracer of the source areas of dust storms from the desert of Iraq and Saudi Arabia to the South of Iran. Scanning electron microscopy indicated that the sizes of the collected dust varied from 50 μm to 0.8 μm, but 10 μm was the predominant size. The atmospheric dust collected had prismatic trigonal–rhombohedral crystals and semi-rounded irregular shapes. Moreover, diatoms were detected in several samples, suggesting that emissions from dry-bed lakes, such as Hoor Al-Azim Wetland (located in the southwest of Iran), also contributed to the dust load. Backward trajectory simulations were performed at the date of sampling by using the NOAA HYSPLIT model. Results showed that the sources of atmospheric dust in the studied area were the eastern area of Iraq, eastern desert of Saudi Arabia, Kuwait and Khuzestan Province. The Ca/Al ratio of the collected samples (1.14) was different from the upper continental crust (UCC) value (UCC = 0.37), whereas Mg/Al (0.29), K/Al (0.22) and Ti/Al (0.07) ratios were close to the UC...
Velasco, SÁ 2020, 'Ilegalizados en Ecuador, el país de la “ciudadanía universal”', Sociologias, vol. 22, no. 55, pp. 138-170.
View/Download from: Publisher's site
View description>>
Resumen En base a un análisis etnográfico multisituado conducido en Ecuador entre 2015 y 2017, este artículo analiza cómo en el marco del mayor progresismo constitucional en materia migratoria, en el país de la “ciudadanía universal”, varios mecanismos legales y sociales fueron adoptados y terminaron confinando a migrantes y refugiados regionales y extracontinentales a encarnar situaciones de ilegalidad, posible deportación y desechabilidad. Se parte de una revisión teórica sobre el régimen de control fronterizo neoliberal global y sobre cómo la producción legal de la ilegalidad migrante es nodal en su funcionamiento, para después analizar por qué inmigrantes caribeños, africanos y de Medio Oriente escogieron a Ecuador como su destino, cuáles fueron los principales reveses e incongruencias en la política migratoria y cómo éstos impactaron en la cotidianeidad de esos inmigrantes hasta multiplicar sus salidas irregularizadas posteriores. El artículo constata que el giro progresista ecuatoriano no estuvo exento de mecanismos análogos al régimen de control fronterizo neoliberal global, hecho que ayuda a comprender el rol que el país andino cumple en la geopolítica de las migraciones contemporáneas: ser un espacio de producción de migrantes ilegalizados o mano de obra barata en ruta a EE.UU., rol que confirma su funcionalidad como un nodo conector dentro de un sistema mucho más amplio y complejo de control neoliberal de la movilidad.
Wan Mohd Jaafar, WS, Said, NFS, Abdul Maulud, KN, Uning, R, Latif, MT, Muhmad Kamarulzaman, AM, Mohan, M, Pradhan, B, Saad, SNM, Broadbent, EN, Cardil, A, Silva, CA & Takriff, MS 2020, 'Carbon Emissions from Oil Palm Induced Forest and Peatland Conversion in Sabah and Sarawak, Malaysia', Forests, vol. 11, no. 12, pp. 1285-1285.
View/Download from: Publisher's site
View description>>
The palm oil industry is one of the major producers of vegetable oil in the tropics. Palm oil is used extensively for the manufacture of a wide variety of products and its production is increasing by around 9% every year, prompted largely by the expanding biofuel markets. The rise in annual demand for biofuels and vegetable oil from importer countries has caused a dramatic increase in the conversion of forests and peatlands into oil palm plantations in Malaysia. This study assessed the area of forests and peatlands converted into oil palm plantations from 1990 to 2018 in the states of Sarawak and Sabah, Malaysia, and estimated the resulting carbon dioxide (CO2) emissions. To do so, we analyzed multitemporal 30-m resolution Landsat-5 and Landsat-8 images using a hybrid method that combined automatic image processing and manual analyses. We found that over the 28-year period, forest cover declined by 12.6% and 16.3%, and the peatland area declined by 20.5% and 19.1% in Sarawak and Sabah, respectively. In 2018, we found that these changes resulted in CO2 emissions of 0.01577 and 0.00086 Gt CO2-C yr−1, as compared to an annual forest CO2 uptake of 0.26464 and 0.15007 Gt CO2-C yr−1, in Sarawak and Sabah, respectively. Our assessment highlights that carbon impacts extend beyond lost standing stocks, and result in substantial direct emissions from the oil palm plantations themselves, with 2018 oil palm plantations in our study area emitting up to 4% of CO2 uptake by remaining forests. Limiting future climate change impacts requires enhanced economic incentives for land uses that neither convert standing forests nor result in substantial CO2 emissions.
Wang, G, Ji, J & Zhou, J 2020, 'Stochastic distribution synchronization and pinning control for complex heterogeneous dynamical networks', Asian Journal of Control, vol. 22, no. 4, pp. 1547-1564.
View/Download from: Publisher's site
View description>>
AbstractThis paper investigates the stochastic synchronization and pinning control in the sense of probability distribution for a general model of complex heterogeneous dynamical networks subjected to stochastic disturbances. Some generic stochastic synchronization criteria are established for both cases of undirected and directed topology by using the ergodic theory on stochastic dynamical systems. Compared with most existing studies on the stochastic synchronization in the sense of mean square, it is demonstrated that the concept of stochastic distribution synchronization can well characterize the realistic structure and essential nature of complex practical stochastic systems. Subsequently, two representative examples of complex heterogeneous dynamical networks, namely coupled stochastic Duffing oscillators and coupled FitzHugh‐Nagumo neuron oscillators, are given to illustrate and numerically verify the theoretical results.
Wang, Q, Huang, Y, Jia, W, He, X, Blumenstein, M, Lyu, S & Lu, Y 2020, 'FACLSTM: ConvLSTM with focused attention for scene text recognition', Science China Information Sciences, vol. 63, no. 2.
View/Download from: Publisher's site
View description>>
© 2020, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature. Scene text recognition has recently been widely treated as a sequence-to-sequence prediction problem, where traditional fully-connected-LSTM (FC-LSTM) has played a critical role. Owing to the limitation of FC-LSTM, existing methods have to convert 2-D feature maps into 1-D sequential feature vectors, resulting in severe damages of the valuable spatial and structural information of text images. In this paper, we argue that scene text recognition is essentially a spatiotemporal prediction problem for its 2-D image inputs, and propose a convolution LSTM (ConvLSTM)-based scene text recognizer, namely, FACLSTM, i.e., focused attention ConvLSTM, where the spatial correlation of pixels is fully leveraged when performing sequential prediction with LSTM. Particularly, the attention mechanism is properly incorporated into an efficient ConvLSTM structure via the convolutional operations and additional character center masks are generated to help focus attention on right feature areas. The experimental results on benchmark datasets IIIT5K, SVT and CUTE demonstrate that our proposed FACLSTM performs competitively on the regular, low-resolution and noisy text images, and outperforms the state-of-the-art approaches on the curved text images with large margins.
Wilson, KJ, Alabd, R, Abolhasan, M, Safavi-Naeini, M & Franklin, DR 2020, 'Optimisation of monolithic nanocomposite and transparent ceramic scintillation detectors for positron emission tomography', Scientific Reports, vol. 10, no. 1.
View/Download from: Publisher's site
View description>>
AbstractHigh-resolution arrays of discrete monocrystalline scintillators used for gamma photon coincidence detection in PET are costly and complex to fabricate, and exhibit intrinsically non-uniform sensitivity with respect to emission angle. Nanocomposites and transparent ceramics are two alternative classes of scintillator materials which can be formed into large monolithic structures, and which, when coupled to optical photodetector arrays, may offer a pathway to low cost, high-sensitivity, high-resolution PET. However, due to their high optical attenuation and scattering relative to monocrystalline scintillators, these materials exhibit an inherent trade-off between detection sensitivity and the number of scintillation photons which reach the optical photodetectors. In this work, a method for optimising scintillator thickness to maximise the probability of locating the point of interaction of 511 keV photons in a monolithic scintillator within a specified error bound is proposed and evaluated for five nanocomposite materials (LaBr3:Ce-polystyrene, Gd2O3-polyvinyl toluene, LaF3:Ce-polystyrene, LaF3:Ce-oleic acid and YAG:Ce-polystyrene) and four ceramics (GAGG:Ce, GLuGAG:Ce, GYGAG:Ce and LuAG:Pr). LaF3:Ce-polystyrene and GLuGAG:Ce were the best-performing nanocomposite and ceramic materials, respectively, with maximum sensitivities of 48.8% and 67.8% for 5 mm localisation accuracy with scintillator thicknesses of 42.6 mm and 27.5 mm, respectively.
Xiao, T, Qiu, X & Halkon, B 2020, 'Ultra-broadband local active noise control with remote acoustic sensing', Scientific Reports, vol. 10, no. 1, p. 20784.
View/Download from: Publisher's site
View description>>
AbstractOne enduring challenge for controlling high frequency sound in local active noise control (ANC) systems is to obtain the acoustic signal at the specific location to be controlled. In some applications such as in ANC headrest systems, it is not practical to install error microphones in a person’s ears to provide the user a quiet or optimally acoustically controlled environment. Many virtual error sensing approaches have been proposed to estimate the acoustic signal remotely with the current state-of-the-art method using an array of four microphones and a head tracking system to yield sound reduction up to 1 kHz for a single sound source. In the work reported in this paper, a novel approach of incorporating remote acoustic sensing using a laser Doppler vibrometer into an ANC headrest system is investigated. In this “virtual ANC headphone” system, a lightweight retro-reflective membrane pick-up is mounted in each synthetic ear of a head and torso simulator to determine the sound in the ear in real-time with minimal invasiveness. The membrane design and the effects of its location on the system performance are explored, the noise spectra in the ears without and with ANC for a variety of relevant primary sound fields are reported, and the performance of the system during head movements is demonstrated. The test results show that at least 10 dB sound attenuation can be realised in the ears over an extended frequency range (from 500 Hz to 6 kHz) under a complex sound field and for several common types of synthesised environmental noise, even in the presence of head motion.
Xiao, T, Qiu, X & Halkon, B 2020, 'Ultra-broadband local active noise control with remote acoustic sensing.', Scientific reports, vol. 10, no. 1.
View/Download from: Publisher's site
View description>>
One enduring challenge for controlling high frequency sound in local active noise control (ANC) systems is to obtain the acoustic signal at the specific location to be controlled. In some applications such as in ANC headrest systems, it is not practical to install error microphones in a person's ears to provide the user a quiet or optimally acoustically controlled environment. Many virtual error sensing approaches have been proposed to estimate the acoustic signal remotely with the current state-of-the-art method using an array of four microphones and a head tracking system to yield sound reduction up to 1 kHz for a single sound source. In the work reported in this paper, a novel approach of incorporating remote acoustic sensing using a laser Doppler vibrometer into an ANC headrest system is investigated. In this "virtual ANC headphone" system, a lightweight retro-reflective membrane pick-up is mounted in each synthetic ear of a head and torso simulator to determine the sound in the ear in real-time with minimal invasiveness. The membrane design and the effects of its location on the system performance are explored, the noise spectra in the ears without and with ANC for a variety of relevant primary sound fields are reported, and the performance of the system during head movements is demonstrated. The test results show that at least 10 dB sound attenuation can be realised in the ears over an extended frequency range (from 500 Hz to 6 kHz) under a complex sound field and for several common types of synthesised environmental noise, even in the presence of head motion.
Xu, B-H, He, N, Jiang, Y-B, Zhou, Y-Z & Zhan, X-J 2020, 'Experimental study on the clogging effect of dredged fill surrounding the PVD under vacuum preloading', Geotextiles and Geomembranes, vol. 48, no. 5, pp. 614-624.
View/Download from: Publisher's site
Xu, D-S, Xu, X-Y, Li, W & Fatahi, B 2020, 'Field experiments on laterally loaded piles for an offshore wind farm', Marine Structures, vol. 69, pp. 102684-102684.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd Pile foundations are widely used to support offshore wind turbines due to their cost effectiveness and rapid constructions. Offshore piles must be designed with enough capacity to withstand overturning moments caused by wind turbines and other environmental factors such as wave excitations and extreme winds. In this study, a full-scale field experimental test is undertaken to determine the pile behaviour under various lateral loading conditions. A distributed fiber optic sensing technology is used to measure strains along two instrumented piles. The bending moments and lateral deflections are calculated from distributed fiber optic sensors, and then analysed with the various p-y methods. Field measurements indicated that for two offshore piles ZK01 and ZK28 with diameter of 2 m and length of 71.5 m and 77.5 m, the maximum lateral movements under a given lateral load of 800 kN were 369.1 mm and 351.7 mm, respectively. The maximum bending moment occurred at 6.5 m and 5.5 m below seabed level with the corresponding depth of 12.15D and 11.95D for pile ZK01 and ZK28, respectively. The position of “zero crossing” of soil resistance for two instrumented piles is almost the same, even though the piles have different lengths. The lateral deflections and bending moments of the two instrumented piles are predicted by the API and hyperbolic method, which indicates that the hyperbolic method yields larger prediction errors than the API method. A modified p-y approach is then proposed for more reliable predictions when compared with field measurements.
Xue, C, Li, W, Castel, A, Wang, K & Sheng, D 2020, 'Effect of incompatibility between healing agent and cement matrix on self-healing performance of intelligent cementitious composite', Smart Materials and Structures, vol. 29, no. 11, pp. 115020-115020.
View/Download from: Publisher's site
View description>>
Abstract Encapsulation-based intelligent self-healing cementitious composite with a potential of crack self-healing and closure is promising to recovery concrete from damage and improve the durability and serviceability of infrastructures. The efficiency of self-healing concrete were investigated, but limited studies have been conducted on effect of incompatibility between the self-healing agent and cement matrix on the cracking behaviour and recovery efficiency of crack-healed concrete. In this study, a coupled experimental and numerical investigations were adopted to understand the cracking behaviours of crack-healed cementitious composites using traction–separation law by extended finite element method (XFEM). Firstly, experimental investigation was conducted to characterize the properties and parameters of cement matrix and healing agent-crack interface to calibrate the traction–separation law. Then, various parameters of healing agent, cement matrix, and their interface on the performance of crack-healed cementitious composite was numerically analysed. The results indicate that to achieve excellent self-healing performance, it is vital to consider the incompatibility between healing agent and cement matrix in the design of intelligent self-healing cementitious composites.
Xue, C, Li, W, Wang, K, Sheng, D & Shah, SP 2020, 'Novel experimental and numerical investigations on bonding behaviour of crack interface in smart self-healing concrete', Smart Materials and Structures, vol. 29, no. 8, pp. 085004-085004.
View/Download from: Publisher's site
View description>>
© 2020 IOP Publishing Ltd. There are crack interfaces between self-healing agent and cement matrix in smart encapsulation-based self-healing concrete, whose mechanical properties significantly affects the load capacity recovery of crack-healed concrete. In this study, both experimental and numerical investigations were conducted on the crack-healed concrete under uniaxial tension to investigate the interface bonding behaviours and the self-healing agent distribution on the crack surface. The results show that the bonding behaviour of the crack interface depends on the content of healing agent and mechanical properties of the crack surface. However, it is still difficult to accurately understand their effects on the bonding behaviour by experimental investigation due to the high brittleness of the crack interface and the discrepancy of self-healing concrete. Therefore, based on the experimental results, a novel numerical model of the interface between self-healing agent and cement matrix was developed to investigate effects of aggregates, pores and interface properties on the bonding behaviour of crack interface by the cohesive surface technique (CS). Parametric analysis was also performed on the bonding behaviours and a method was proposed for assessing the load capacity of crack-healed concrete. Based on the experimental and numerical investigations on the healing agent-concrete crack interface in the smart encapsulation-based self-healing concrete, this novel numericla methods can be used to assess the recovery efficiency and performance of smart self-healing concrete structure.
Xue, M, Shivakumara, P, Wu, X, Lu, T, Pal, U, Blumenstein, M & Lopresti, D 2020, 'Deep invariant texture features for water image classification', SN Applied Sciences, vol. 2, no. 12, p. 2068.
View/Download from: Publisher's site
View description>>
Detecting potential issues in naturally captured images of water is a challenging task due to visual similarities between clean and polluted water, as well as causes posed by image acquisition with different camera angles and placements. This paper presents novel deep invariant texture features along with a deep network for detecting clean and polluted water images. The proposed method first divides an input image into H, S and V components to extract finer details. For each of the color spaces, the proposed approach generates two directional coherence images based on Eigen value analysis and gradient distribution, which results in enhanced images. Then the proposed method extracts scale invariant gradient orientations based on Gaussian first order derivative filters on different standard deviations to study texture of each smoothed image. To strengthen the above features, we explore the combination of Gabor-wavelet-binary pattern for extracting texture of the input water image. The proposed method integrates merits of aforementioned features and the features extracted by VGG16 deep learning model to obtain a single feature vector. Furthermore, the extracted feature is fed to a gradient boosting decision tree for water image detection. A variety of experimental results on a large dataset containing different types of clean and stagnant water images show that the proposed method outperforms the existing methods in terms of classification rate and accuracy.
Yariyan, P, Janizadeh, S, Van Phong, T, Nguyen, HD, Costache, R, Van Le, H, Pham, BT, Pradhan, B & Tiefenbacher, JP 2020, 'Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping', Water Resources Management, vol. 34, no. 9, pp. 3037-3053.
View/Download from: Publisher's site
Ye, K, Ji, J & Han, S 2020, 'Semi-active noise control for a hermetic digital scroll compressor', Journal of Low Frequency Noise, Vibration and Active Control, vol. 39, no. 4, pp. 1204-1215.
View/Download from: Publisher's site
View description>>
Hermetic digital scroll compressor has been widely used as a small-scale organic Rankine cycle application in the heating, ventilation, and air conditioning systems. A clunking noise issue is recently found in an air conditioning outdoor unit, and the main cause of the noise is experimentally identified to be the impact of the scrolls in the compressor unit during the switching process. The semi-active control methods are thus designed to greatly reduce the noise level by using additional valves to adjust the pressure changing rate within the modulation chamber. The response time for the impact of the scrolls can then be controlled by the added valves. The additional release valve with a smaller diameter pipe parallel to the main valve is tested firstly for its performance. Slower flow rate is produced and the pipe can extend the response time and decrease the speed of the impact process by reducing the pressure changing rate. The use of a discharge valve is also tested for controlling the pressure changing rate inside the chamber. The discharge valve with an opposite effect to the release valve is found useful for solving the noise issue. Both noise and vibration results confirm that the impact noise in the frequency range of interest can be reduced by using the proposed semi-active control methods.
Ye, K, Ji, JC & Brown, T 2020, 'Design of a quasi-zero stiffness isolation system for supporting different loads', Journal of Sound and Vibration, vol. 471, pp. 115198-115198.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd The quasi-zero stiffness (QZS) vibration isolation system using negative stiffness structure can generally increase the workable frequency range and improve the isolation performance, in comparison with a linear vibration isolator. However, most of the QZS isolation systems are sensitive to the loads applied for achieving effective isolation. A QZS system designed for a certain load supported cannot provide an effective vibration isolation for another load, as the designed QZS region is not suitable for the new load and thus it no longer demonstrates the anticipated isolation performance. This paper presents an optimized structure for the QZS system to adaptively respond to different loads based on a cam-roller mechanism. Innovation of the present design is the capacity of supporting multi-load levels to isolate the vibrations in low frequency range. Frictional force occurring on the cam-roller contact is considered in the modelling to represent practical application situations. Both static and dynamic responses are theoretically studied for the QZS characteristic and isolation performance. A prototype of the proposed QZS structure is designed, fabricated and tested to verify its isolation performance. Experimental results demonstrate an excellent agreement with the theoretical results, which promotes the implementation of the proposed design into engineering applications.
Ye, S-Q, Mao, X-Y, Ding, H, Ji, J-C & Chen, L-Q 2020, 'Nonlinear vibrations of a slightly curved beam with nonlinear boundary conditions', International Journal of Mechanical Sciences, vol. 168, pp. 105294-105294.
View/Download from: Publisher's site
View description>>
© 2019 The existing studies of nonlinear vibration of elastic structures are usually focused on straight structures with homogeneous linear boundaries. Differently, this paper investigates the nonlinear transverse vibrations of a slightly curved beam with nonlinear boundary conditions. By using the generalized Hamilton's principle, the governing equation with geometric nonlinearity is obtained for the dynamics of the curved beam. A method of dealing with nonlinear boundaries is proposed, which is considered as a nonlinear concentrated force at the boundary. The normal modes and natural frequencies of the curved beam are determined using two different hypothetical modes based on the derived system. The harmonic balance method in combination with the pseudo arc-length method is employed to obtain the primary resonance response and 1/2 super-harmonic resonance response of the slightly curved beam. It is found that the initial curvature plays a significant role in the characteristics of the nonlinear vibrations of the curved beam. With an increase of the initial curvature, the nonlinear characteristics of softening and hardening types can coexist in the steady-state amplitude-frequency response. Moreover, the results show that the initial curvature can induce 1/2 super-harmonic resonance. Furthermore, it is also found that the nonlinear boundary has a significant influence on the nonlinear vibration of the curved structure. Therefore, the obtained results provide useful information for further studying the nonlinear vibrations of the curved beam with nonlinear and time-dependent boundary conditions.
Ye, X, Wang, S, Li, Q, Zhang, S & Sheng, D 2020, 'Negative Effect of Installation on Performance of a Compaction-Grouted Soil Nail in Poorly Graded Stockton Beach Sand', Journal of Geotechnical and Geoenvironmental Engineering, vol. 146, no. 8, pp. 04020061-04020061.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. In this study, a latex membrane with a diameter of 50 mm and thickness of 0.5 mm is used to encase an injection hole. The gap between the membrane and the nail rod is fixed to achieve compaction grouting and to prevent fracturing and permeating; hence, a regular grout bulb is easily formed and locked into the soil matrix to provide a pullout force for a compaction-grouted soil nail. For this type of soil nail, two series of physical model tests for an embedded soil nail and a soil nail with a predrilled hole (the soil sample was moistened and could sustain the hole without collapsing during the placement of the nail rod) were conducted to study the influence of the installation methods on the performance of a compaction-grouted soil nail. The results of the two series of tests were compared, and some conclusions were drawn: First, the aforementioned installation methods for a soil nail had little impact on the mass of injected grout, whereas the shape of the cured grout bulb showed some differences based on the type of soil response. Second, compared with that of an embedded soil nail, the pullout force of a postplaced soil nail remarkably decreased because the hole drilled for installation led to a gap between the soil nail and the surrounding soil. In addition, the loss rate correlated with the grouting pressure (i.e., the diameter of the grout bulb). Third, because of the lower soil densification, dilation, and squeeze effect, a slower growth rate (with increasing grouting pressure) of the pullout force (i.e., resistance) was found for the postplaced soil nail relative to that of the embedded soil nail, during which the efficiency of the increasing pullout force decreased.
Yin, S, Wen, G, Ji, J & Xu, H 2020, 'Novel two-parameter dynamics of impact oscillators near degenerate grazing points', International Journal of Non-Linear Mechanics, vol. 120, pp. 103403-103403.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Following the previous work on the degenerate grazing bifurcations of impact oscillators, this paper aims to explore novel two-parameter dynamics near the degenerate grazing points using GPU parallel computing technology. By using the technology, a further understanding of the near-grazing dynamics can be developed for impact oscillators. Three main indicators, i.e., the largest Lyapunov exponent, number of excitation periods and number of impacts, are calculated for each grid of the two-parameter plane chosen. Based on these indicators, the dynamic response in the vicinity of degenerate grazing points can be characterized and more dynamic behaviors than the published results can be discovered. Phenomena of coexisting attractors and chaotic transitions including crisis are also discussed. The single and two degree-of-freedom impact oscillators are selected as illustrative examples to demonstrate the results.
Yu, J, Ji, J, Miao, Z & Zhou, J 2020, 'Region-based flocking control for networked robotic systems with communication delays', European Journal of Control, vol. 52, pp. 78-86.
View/Download from: Publisher's site
View description>>
© 2019 European Control Association Based on a self-tuning adaptive control gain technique, this paper proposes a novel adaptive controller to implement the region-based flocking control for the networked robotic systems with communication delays. It is shown that under the proposed control strategy, all the robots can always reach into the objective region, realize velocity matching and ensure collision avoidance, if the network topology graph is connected under certain initial position conditions. Some simulation results are provided to illustrate the effectiveness and robustness of the proposed novel controller.
Yu, JW, Zhang, XH, Ji, JC, Tian, JY & Zhou, J 2020, 'Region-Reaching Control of a Flexible-Joint Manipulator', Journal of Dynamic Systems, Measurement, and Control, vol. 142, no. 11.
View/Download from: Publisher's site
View description>>
Abstract This paper addresses the region-reaching control problem for a flexible-joint robotic manipulator which is formulated by Lagrangian dynamics. An adaptive control scheme is proposed for the manipulator system having two constrained regions which are constructed by selecting appropriate objective functions. The two joints of the flexible-joint manipulator can be, respectively, confined in different regions, and this gives more flexibility than the traditional fixed-point tracking control. By performing a straightforward Lyapunov stability analysis, a simple control algorithm is established to provide a solution for the region-reaching control problem. Finally, numerical simulations are given to validate the theoretical results.
Zhang, M, Gao, Y, Sun, C & Blumenstein, M 2020, 'A robust matching pursuit algorithm using information theoretic learning', Pattern Recognition, vol. 107, pp. 107415-107415.
View/Download from: Publisher's site
View description>>
© 2020 Current orthogonal matching pursuit (OMP) algorithms calculate the correlation between two vectors using the inner product operation and minimize the mean square error, which are both suboptimal when there are non-Gaussian noises or outliers in the observation data. To overcome these problems, a new OMP algorithm is developed based on information theoretic learning (ITL), which is built on the following new techniques: (1) an ITL-based correlation (ITL-Correlation) is developed as a new similarity measure which can better exploit higher-order statistics of the data, and is robust against many different types of noise and outliers in a sparse representation framework; (2) a non-second order statistic measurement and minimization method is developed to improve the robustness of OMP by overcoming the limitation of Gaussianity inherent in a cost function based on second-order moments. The experimental results on both simulated and real-world data consistently demonstrate the superiority of the proposed OMP algorithm in data recovery, image reconstruction, and classification.
Zhang, S, Yan, H, Teng, J & Sheng, D 2020, 'A mathematical model of tortuosity in soil considering particle arrangement', Vadose Zone Journal, vol. 19, no. 1.
View/Download from: Publisher's site
View description>>
AbstractTortuosity is an important parameter for studying the permeability of soil. Existing studies of soil tortuosity are usually of empirical nature and attempt to relate tortuosity to soil porosity alone. By assuming a laminar flow through the pores of two‐dimensional square solid particles, we present a mathematical model for calculating soil tortuosity under different particle arrangements. The effect of the randomness of the particle arrangement on the tortuosity is evaluated, which generates the variation range of the tortuosity. The proposed model provides the upper and lower bounds of the tortuosity, while existing empirical models tend to fall within these bounds. The consistency between the proposed model and the numerical calculation provides a validity for the proposed model.
Zhang, X, Li, W, Tang, Z, Wang, X & Sheng, D 2020, 'Sustainable regenerated binding materials (RBM) utilizing industrial solid wastes for soil and aggregate stabilization', Journal of Cleaner Production, vol. 275, pp. 122991-122991.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd This study presents an experimental investigation on a sustainable regenerated binding material (RBM), which is derived from several industrial solid wastes. Initially, the hydration process, mechanical behaviors, and microstructural characteristics of the RBM were investigated. Subsequently, the feasibility of RBM for the stabilization of macadam, expansive soil, and weathered sand was evaluated. The results reveal that in comparison with the ordinary Portland cement (OPC), the RBM exhibits a slightly faster hydration rate at the initial stage and comparable mechanical performance. For the stabilized macadam, the one stabilized by the RBM exhibits better unconfined compressive strength, scouring resistance and freeze-thaw resistance than the counterpart stabilized by OPC. Furthermore, the RBM can significantly improve the performance index of the expansive soil and weathered sand, and this enhancement is more significant as the RBM content increasing. Additionally, the RBM has been successfully applied in practical engineering, manifesting the promising application potential of the RBM. Overall, the excellent performance of RBM as an alternative stabilizer of the subgrade soil and aggregates can promote the application of the RBM low-carbon pavement construction in the future.
Zhang, Y, Ji, J & Ma, B 2020, 'Fault diagnosis of reciprocating compressor using a novel ensemble empirical mode decomposition-convolutional deep belief network', Measurement, vol. 156, pp. 107619-107619.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd In order to denoise the raw signal and fuse multiple sources of information for the fault diagnosis of reciprocating compressor, this paper proposes a novel convolutional deep belief network-based method and employs a novel framework fusing multi-source information to improve the performance of fault diagnosis. Firstly, signals from different sensors of the RC are input into an auto-denoising network, namely, ensemble empirical model decomposition-convolutional deep belief network, to denoise the signal and to extract more robust features by the unsupervised learning. Secondly, the extracted features of each source are input into multiple Gaussian process classifiers which are adopted as the members of probabilistic committee machine (PCM) to calculate the probabilities that each fault occurs. Finally, these probabilities are combined with an optimized weight to make a committee decision on fault type. The proposed method combines the information from multiple sources and enhances the robustness of fault diagnosis. Data from an industrial plant were collected to verify the proposed method. The obtained results demonstrate that the proposed method can effectively diagnose the RC faults with the accuracy rate of up to 91.89%. Furthermore, a comparison of the proposed method with the other methods illustrates the superiority of the proposed method for the diagnosis of RC faults.
Zhang, Y, Ji, J & Ma, B 2020, 'Reciprocating compressor fault diagnosis using an optimized convolutional deep belief network', Journal of Vibration and Control, vol. 26, no. 17-18, pp. 1538-1548.
View/Download from: Publisher's site
View description>>
This article proposes an optimized convolutional deep belief network for fault diagnosis of reciprocating compressors. Sparse filtering is first used to compress raw signal into compact time series by refining the most representative information and to reduce the computational burden. Then, the proposed convolutional deep belief network is adopted to learn the unsupervised features of the compressed signal without the need of feature extraction by human effort. To improve the generalization ability of the network, an optimized probabilistic pooling out is proposed in this article to replace the standard one in the pooling layer of the convolutional deep belief network. Finally, the unsupervised features calculated by the optimized convolutional deep belief network are fed as the input of the softmax regression classifier for fault identification. Four types of vibration signals reflecting different operating conditions are collected from the industry to validate the effectiveness of the proposed method. The obtained results demonstrate that the proposed convolutional deep belief network method can achieve a higher classification accuracy rate of up to 91% for fault diagnosis than the traditional methods and accomplish the fault diagnosis of reciprocating compressor effectively.
Zhang, Z, He, N, He, B, Xu, B & Jiang, Y 2020, 'New method to measure structure stress based on distributed optical fiber technology', Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, vol. 41, no. 9, pp. 45-55.
View/Download from: Publisher's site
View description>>
Stress and deformation monitoring is the significant content for evaluating the structure working characteristics and safety. On the basis of the research results of existing distributed optical fiber sensing technology, this paper optimizes the strain and deformation fitting algorithm is optimized. Aiming at the two cases of concentrated force and multi-point force a distributed structural stress measurement method is troposed based on optical fiber sensing technology. The bending moment and shear force calculation program is written. Through the indoor test of square steel and H-steel beam, the force magnitude and position fitting of the measurement method is studied. The study results show that the fitting values of the measurement method agree well with the theoretical values in terms of bending moment and shear force. The maximum average relative error of shear position fitting in square steel test is only 2.75%, and average relative error of shear force fitting at most stress points is less than 6%, The larger the strain of the stress point is, the higher the fitting accuracy of shear force position and shear force magnitude can be. At the same time, the measurement method can match the accuracy upgrade of the optical fiber measurement equipment. With the improvement of the accuracy specification, more details of the data changes can be captured and the distributed measurement of more stress points can be realized. The measurement method was applied to an example of foundation pit excavation with SMW retaining structures, which can accurately reflect the stress changes of H-steel pile in the excavation process, and has certain engineering practicability.
Zhao, F, Ji, JC, Ye, K & Luo, Q 2020, 'Increase of quasi-zero stiffness region using two pairs of oblique springs', Mechanical Systems and Signal Processing, vol. 144, pp. 106975-106975.
View/Download from: Publisher's site
View description>>
© 2020 Elsevier Ltd Quasi-zero stiffness (QZS) nonlinear isolation systems have demonstrated better performance than their linear counterparts. However, their optimal performance is achieved only in a small displacement range around the static equilibrium position. Based on the QZS system with one pair of oblique springs, this paper proposes a new limb-like QZS system with two pairs of oblique springs to enlarge the QZS range and thus improve its isolation performance. Two pairs of oblique springs are configured to provide the dynamic stiffness opposite to the vertical spring for generating QZS characteristics. In comparison with the corresponding QZS system with one pair of oblique springs, the proposed QZS system with two pairs of oblique springs can achieve a lower dynamic stiffness in a much wider region around the static equilibrium position. Based on the theoretical analysis, a prototype is designed and fabricated to physically realize the QZS isolation system. Experimental results are found to be in good agreement with the theoretical predictions which also confirm the proposed QZS system has better isolation performance than the corresponding QZS system with one pair of oblique springs. The proposed model can be adopted for isolating low frequency vibrations in practical applications.
Zheng, J, Ji, J, Yin, S & Tong, V-C 2020, 'Fatigue life analysis of double-row tapered roller bearing in a modern wind turbine under oscillating external load and speed', Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 234, no. 15, pp. 3116-3130.
View/Download from: Publisher's site
View description>>
Fatigue life analysis of roller bearing is usually performed for bearings under constant rotating speed and invariant loading conditions. For the bearings used in offshore floating direct-drive wind turbines, they often experience oscillating motions with varying loading patterns, for which the standard fatigue life analysis is not valid due to the presence of fluctuating loads. This paper presents the fatigue life analysis of a double-row tapered roller bearing under oscillating external load and speed conditions, which is used to support the main shaft of a large modern direct-drive wind turbine. First, a comprehensive quasi-static model of the double-row tapered roller bearing is developed for determining the internal load distribution of rollers. The contact pressure of rollers is then studied using an iterative scheme based on the elastic contact model. After that, the formulation of basic rating life of the double-row tapered roller bearing with oscillating external load and speed is given to calculate the fatigue life. Numerical simulations are carried out to investigate the effects of the oscillating load and speed, angular misalignment, and internal clearance on the fatigue life of the bearing.
Zheng, J, Ji, J, Yin, S & Tong, V-C 2020, 'Internal loads and contact pressure distributions on the main shaft bearing in a modern gearless wind turbine', Tribology International, vol. 141, pp. 105960-105960.
View/Download from: Publisher's site
View description>>
© 2019 Elsevier Ltd The double-row tapered roller bearing (TRB) widely used to support the main shaft in a modern gearless wind turbine is one of the main components and its faults can lead to the malfunctions and downtime of wind turbines. Over the past decades, some numerical approaches have been proposed for calculating the contact force and pressure distribution of double-row TRBs. Nevertheless, most of the existing studies did not take the angular misalignment between inner and outer rings and the frictional force between the rollers and raceways into account. This paper presents a comprehensive quasi-static model to investigate the internal load and contact pressure distribution in a double-row TRB by considering the angular misalignment, the combined external loads and frictional force. It is found that a small misalignment angle between inner and outer rings can result in a significant change in the magnitude and distribution of the contact force and pressure. The double-row TRB with crowned roller profile exhibits a substantial improvement in contact pressure distribution by eliminating the occurrence of pressure concentration. Moreover, the peak contact pressure can be significantly reduced on the roller with the crowned profile, even if in the case of misaligned bearing. Comparisons of the simulated contact loads and pressure distributions demonstrate the necessity of considering angular misalignment and frictional force in the modelling of large size and heavily loaded double-row TRB.
Zhou, F, Li, Z, Fan, X, Wang, Y, Sowmya, A & Chen, F 2020, 'Efficient inference for nonparametric hawkes processes using auxiliary latent variables', Journal of Machine Learning Research, vol. 21, pp. 1-31.
View description>>
The expressive ability of classic Hawkes processes is limited due to the parametric assumption on the baseline intensity and triggering kernel. Therefore, it is desirable to perform inference in a data-driven, nonparametric approach. Many recent works have proposed nonparametric Hawkes process models based on Gaussian processes (GP). However, the likelihood is non-conjugate to the prior resulting in a complicated and time-consuming inference procedure. To address the problem, we present the sigmoid Gaussian Hawkes process model in this paper: the baseline intensity and triggering kernel are both modeled as the sigmoid transformation of random trajectories drawn from a GP. By introducing auxiliary latent random variables (branching structure, Pólya-Gamma random variables and latent marked Poisson processes), the likelihood is converted to two decoupled components with a Gaussian form which allows for an efficient conjugate analytical inference. Using the augmented likelihood, we derive an efficient Gibbs sampling algorithm to sample from the posterior; an efficient expectation-maximization (EM) algorithm to obtain the maximum a posteriori (MAP) estimate and furthermore an efficient mean-field variational inference algorithm to approximate the posterior. To further accelerate the inference, a sparse GP approximation is introduced to reduce complexity. We demonstrate the performance of our three algorithms on both simulated and real data. The experiments show that our proposed inference algorithms can recover well the underlying prompting characteristics efficiently.
Zhou, F, Li, Z, Fan, X, Wang, Y, Sowmya, A & Chen, F 2020, 'Fast multi-resolution segmentation for nonstationary Hawkes process using cumulants', International Journal of Data Science and Analytics, vol. 10, no. 4, pp. 321-330.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature Switzerland AG. The stationarity is assumed in the vanilla Hawkes process, which reduces the model complexity but introduces a strong assumption. In this paper, we propose a fast multi-resolution segmentation algorithm to capture the time-varying characteristics of the nonstationary Hawkes process. The proposed algorithm is based on the first- and second-order cumulants. Except for the computation efficiency, the algorithm can provide a hierarchical view of the segmentation at different resolutions. We extensively investigate the impact of hyperparameters on the performance of this algorithm. To ease the choice of hyperparameter, we propose a refined Gaussian process-based segmentation algorithm, which is proved to be a robust method. The proposed algorithm is applied to a real vehicle collision dataset, and the outcome shows some interesting hierarchical dynamic time-varying characteristics.
Zhou, I, Lipman, J, Abolhasan, M, Shariati, N & Lamb, DW 2020, 'Frost Monitoring Cyber–Physical System: A Survey on Prediction and Active Protection Methods', IEEE Internet of Things Journal, vol. 7, no. 7, pp. 6514-6527.
View/Download from: Publisher's site
Zhu, D, Indraratna, B, Poulos, H & Rujikiatkamjorn, C 2020, 'Field study of pile – prefabricated vertical drain (PVD) interaction in soft clay', Canadian Geotechnical Journal, vol. 57, no. 3, pp. 377-390.
View/Download from: Publisher's site
View description>>
Piles and prefabricated vertical drains (PVDs) are two well-established inclusions used by geotechnical practitioners when dealing with soft compressible foundations. Induced movements in highly compressible soil can adversely influence the pile response by inducing additional movements and stresses in the piles. Especially, undesirable soil–pile interaction often leads to the development of excess pore-water pressure during pile installation and negative skin friction caused by the settlement of compressible soil surrounding the piles. Additional drainage by PVDs prior to the installation of a pile could reduce excess pore-water pressure, lateral soil movement, and negative skin friction on the pile. In this paper, full-scale field testing on two trial embankments built on soft soil is reported and the relative behaviour of these two embankments is compared and discussed. Soft soil underneath both embankments was consolidated before one pile was installed at the centre of each embankment. The pore-water pressure, lateral soil movement, surface settlement, and associated strain at the pile shaft were recorded. The pile capacity was tested immediately and 3 h after pile installation. The monitoring and testing results indicated that preconsolidation with PVDs before piling can effectively reduce the excess pore-water pressure, lateral soil movement, and downdrag on the pile.
Zhu, QH, Shen, JW & Ji, JC 2020, 'Internal signal stochastic resonance of a two-component gene regulatory network under Lévy noise', Nonlinear Dynamics, vol. 100, no. 1, pp. 863-876.
View/Download from: Publisher's site
View description>>
© 2020, Springer Nature B.V. Noises are ubiquitous in nature and can often induce some curious phenomena. In this paper, we investigate the internal signal stochastic resonance (ISSR) phenomenon of a two-component gene regulatory network under the excitation of Lévy noise. Our results reveal that the Lévy noise can induce the periodic oscillation of the protein concentration when the control parameter is close to its bifurcation points. Furthermore, we consider the noise-induced periodic signal as the periodic excitation and study the ISSR phenomenon under the cooperation of the nonlinear system, noise-induced periodic signal and random noise. And we found that there may be a connection between the ISSR phenomenon and the bifurcation mechanism. Besides, we also investigate the effects of different noise parameters on the ISSR phenomenon. The simulation results indicate that there is an optimal interval of the stability index α which can induce the ISSR phenomenon, and the skewness parameter β has a negative correlation with the ISSR phenomenon. Our results may provide a pathway to uncover the positive functional mechanism of noises in complex gene regulatory networks.
Adak, C, Chaudhuri, BB, Lin, C-T & Blumenstein, M 1970, 'Why Not? Tell us the Reason for Writer Dissimilarity', 2020 International Joint Conference on Neural Networks (IJCNN), 2020 International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1-7.
View/Download from: Publisher's site
View description>>
© 2020 IEEE. Writer verification has drawn significant attention over the past few decades due to its extensive applications in forensics and biometrics. In traditional writer verification, handwriting similarity/dissimilarity analysis is mostly performed by extracting two feature vectors from two respective handwritten samples, followed by comparing them in relation to their similarity. In the state-of-the-art writer verification approaches, a distance metric is usually employed in terms of the similarity between two handwritten samples. If the distance between two handwritten samples is greater than a given threshold, then the samples are assumed to be written by two different writers, otherwise, they are considered to be due to the same writer. In this paper, for the very first time, we propose a model that generates English sentences to explain reasons for writer dissimilarity/similarity. First, our proposed model obtains features from handwritten images by employing a convolutional neural network, verifies the writer using a Siamese architecture, and generates English words using a recurrent neural network. Finally, these two networks are merged using an affine transformation to produce an explanatory sentence in support of writer similarity/dissimilarity. We evaluated our model on a handwritten numeral database of 100 writers and obtained promising results.
Alqaisi, R, Le, TM & Khabbaz, H 1970, 'Applications of Recycled Sustainable Materials and By-Products in Soil Stabilization', International Congress and Exhibition "Sustainable Civil Infrastructures”, Springer International Publishing, Egypt, pp. 91-117.
View/Download from: Publisher's site
Amiri, M, Tofigh, F, Shariati, N, Lipman, J & Abolhasan, M 1970, 'Ultra Wideband Dual Polarization Metamaterial Absorber for 5G frequency spectrum', 2020 14th European Conference on Antennas and Propagation (EuCAP), 2020 14th European Conference on Antennas and Propagation (EuCAP), IEEE, Copenhagen, Denmark.
View/Download from: Publisher's site
View description>>
Implementing 5G technology contributes to improve communication quality and facilitate several interesting applications in daily life such as Internet of things. Despite outstanding features of 5G, the amount of ambient electromagnetic waves will be increased significantly in the environment, which may be undesired. Ultra-wideband metamaterial perfect absorber is a promising solution to collect these undesired signals. Using lumped elements in absorber structure to increase the absorption bandwidth leads to design and fabrication process complexity. In this paper, a low profile polarization angle selective metamaterial absorber has been designed to absorb signals in the frequency range of 21.79 GHz to 53.23 GHz with more than 90% efficiency. The relative absorption bandwidth of the final structure is 83.81%. Moreover, the final structure is reasonably insensitive facing different incident angle up to 40 degree.
Cai, GQ, Zhou, AN & Sheng, D 1970, 'Predicting the dependency of a permeability function on initial density for unsaturated soils', Unsaturated Soils: Research and Applications - Proceedings of the 6th International Conference on Unsaturated Soils, UNSAT 2014, 6th International Conference on Unsaturated Soils (UNSAT), CRC Press, Sydney, AUSTRALIA, pp. 1091-1097.
View/Download from: Publisher's site
View description>>
This paper presents a simple approach to quantify the effect of initial density on the relative coefficient of permeability for unsaturated soils. This approach is derived on two bases: an incremental relationship between the degree of saturation and the initial void ratio;- predicting the permeability function for unsaturated soils by use of the water retention curve. For a given soil, only one additional parameter is required, which can conveniently be calibrated by the conventional water retention curve tests. The relative coefficient of permeability for the same soil at different initial densities can be predicted by the proposed approach. The proposed approach has been validated by experimental data from the literature where both the water retention curves and the coefficients of permeability under different initial densities were measured. © 2014 Taylor & Francis Group.
Charles, M, Yu, HS & Sheng, D 1970, 'Finite element analysis of pressuremeter tests using critical state soil models', NUMERICAL MODELS IN GEOMECHANICS - NUMOG VII, 7th International Symposium on Numerical Models in Geomechanics (NUMOG), CRC Press, GRAZ, AUSTRIA, pp. 645-650.
View/Download from: Publisher's site
Chemalamarri, VD, Braun, R & Abolhasan, M 1970, 'Constraint-Based Rerouting mechanism to address Congestion in Software Defined Networks', 2020 30th International Telecommunication Networks and Applications Conference (ITNAC), 2020 30th International Telecommunication Networks and Applications Conference (ITNAC), IEEE, Melbourne, VIC, Australia, pp. 1-6.
View/Download from: Publisher's site
View description>>
In this paper, we propose a traffic rerouting mechanism to address congestion in Software-Defined networks. We employ back-tracking and constraint propagation techniques to find alternate paths to reroute multiple active flows simultaneously. Cost function is based on standard deviation of link-loads. We then compare traffic distribution and link utilisation with and without rerouting active flows. We measure and compare network performance using parameters such as total rate of transfer, jitter, and packet loss with that of Shortest Path First with no rerouting. Our proposed solution produces lower jitter, packet drops, and higher transfer rate. We finally conclude the paper by making observations and discussing the scope of the future work.
Chowdhury, PN, Shivakumara, P, Raghavendra, R, Pal, U, Lu, T & Blumenstein, M 1970, 'A New U-Net Based License Plate Enhancement Model in Night and Day Images', Pattern Recognition, ACPR, Springer International Publishing, Auckland, New Zealand, pp. 749-763.
View/Download from: Publisher's site
View description>>
A new trend of smart city development opens up many challenges. One such issue is that automatic vehicle driving and detection for toll fee payment in night or limited light environments. This paper presents a new work for enhancing license plates captured in limited or low light conditions such that license plate detection methods can be expanded to detect images at night. Due to the popularity of Convolutional Neural Network (CNN) in solving complex issues, we explore U-Net-CNN for enhancing contrast of license plate pixels. Since the difference between pixels that represent license plates and pixels that represent background is too due to low light effect, the special property of U-Net that extracts context and symmetric of license plate pixels to separate them from background pixels irrespective of content. This process results in image enhancement. To validate the enhancement results, we use text detection methods and based on text detection results we validate the proposed system. Experimental results on our newly constructed dataset which includes images captured in night/low light/limited light conditions and the benchmark dataset, namely, UCSD, which includes very poor quality and high quality images captured in day, show that the proposed method outperforms the existing methods. In addition, the results on text detection by different methods show that the proposed enhancement is effective and robust for license plate detection.
Darwish, A, Halkon, B, Oberst, S, Fitch, R & Rothberg, S 1970, 'CORRECTION OF LASER DOPPLER VIBROMETER MEASUREMENTS AFFECTED BY SENSOR HEAD VIBRATION USING TIME DOMAIN TECHNIQUES', XI International Conference on Structural Dynamics, XI International Conference on Structural Dynamics, EASD, Athens, pp. 4842-4850.
View/Download from: Publisher's site
View description>>
Despite widespread use in a variety of areas, in-field applications of laser Doppler vibrometers (LDVs) are still somewhat limited due to their inherent sensitivity to vibration of the instrument sensor head itself. Earlier work, briefly reviewed herein, has shown it to be possible
to subtract the instrument vibration via a number of means, however, it has been difficult up to now to truly compare the performance of these. This is compounded by the constraint that a frequency domain based approach only holds for stationary vibration signals while, particularly for in-field applications, an approach that is also applicable to transient signals is necessary.
This paper therefore describes the development of a novel time domain post-processing based approach for vibrating LDV measurement correction and compares it with the frequency domain counterpart. Results show that, while both techniques offer significant improvements in the corrected LDV signal when compared to a reference accelerometer measurement, the time domain based correction outperforms the frequency domain based method by a factor of eight
Das, A, Suwanwiwat, H, Pal, U & Blumenstein, M 1970, 'ICFHR 2020 Competition on Short answer ASsessment and Thai student SIGnature and Name COMponents Recognition and Verification (SASIGCOM 2020)', 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Dortmund, Germany, pp. 222-227.
View/Download from: Publisher's site
View description>>
This paper describes the results of the competition on Short answer ASsessment and Thai student SIGnature and Name COMponents Recognition and Verification (SASIGCOM 2020) in conjunction with the 17th International Conference on Frontiers in Handwriting Recognition (ICFHR 2020). The competition was aimed to automate the evaluation process short answer-based examination and record the development and gain attention to such system. The proposed competition contains three elements which are short answer assessment (recognition and marking the answers to short-answer questions derived from examination papers), student name components (first and last names) and signature verification and recognition. Signatures and name components data were collected from 100 volunteers. For the Thai signature dataset, there are 30 genuine signatures, 12 skilled and 12 simple forgeries for each writer. With Thai name components dataset, there are 30 genuine and 12 skilfully forged name components for each writer. There are 104 exam papers in the short answer assessment dataset, 52 of which were written with cursive handwriting; the rest of 52 papers were written with printed handwriting. The exam papers contain ten questions, and the answers to the questions were designed to be a few words per question. Three teams from distinguished labs submitted their systems. For short answer assessment, word spotting task was also performed. This paper analysed the results produced by their algorithms using a performance measure 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 made freely available for research purposes via the TC10/TC11.
EL-HAWAT, O, FATAHI, B & MOSAVI, AA 1970, 'IMPACTS OF TRANSVERSE EARTHQUAKES ON SEISMIC RESPONSE OF BRIDGES WITH ROCKING FOUNDATIONS AND VARIOUS SHEAR KEYS', WIT Transactions on The Built Environment, SUSI 2020, WIT Press, Online, pp. 125-137.
View/Download from: Publisher's site
View description>>
Rocking foundations are proven to be an effective base isolation technique that improves the seismic performance of bridges and minimises the damage at the piers during large earthquakes. However, due to the foundations ability to uplift, the subsequent reduction of the pier’s stiffness leads to larger column drifts and deck displacements. This not only attracts larger stresses to the transverse direction of the deck, but also at the abutment which, if not carefully considered, can lead to severe damages. Therefore, this study will investigate the seismic response of bridges with rocking pile foundations subjected to transverse earthquake excitations and compare it to the response of conventional fixed base bridges. Two separate shear key performance levels are investigated for each bridge: (1) non-linear shear keys that break off; and (2) shear keys that remain rigid. 3D numerical models of the bridges are developed using finite element software with consideration of soil-structure interaction. Moreover, non-linear time history analyses are performed on the bridges using four ground-motion records, where their dynamic response are then compared. Results show that the conventional bridges collapsed due to the development of plastic hinging at the piers. However, the bridges with the rocking pile foundations experienced significant deck displacements which caused flexural plastic hinging of the deck and the subsequent collapse of the bridge. Moreover, when the shear keys failed, the deck experienced large displacements at the abutment which caused the bearing to rupture and displace permanently with the risk of unseating and span failure. Bridges with this foundation system will require additional design provisions to prevent such failures from occurring.
Hadgraft, RG, Francis, B, Fitch, R, Halkon, B & Brown, T 1970, 'Renewing mechanical and mechatronics programs using studios', SEFI 47th Annual Conference: Varietas Delectat... Complexity is the New Normality, Proceedings, SEFI Annual Conference, SEFI, Budapest, Hungary, pp. 511-522.
View description>>
In a world of rapid change, engineering programs need to adapt to be relevant. This paper addresses the renewal processes for mechanical and mechatronics engineering programs at a large university of technology. The paper sits within a wider curriculum change movement, including all engineering and IT programs at this university. Several meetings have been held over the last 3 years with both industry panels and with academic staff and students to understand the nature of the problem. Using a design-thinking approach, we have explored: global trends, the nature of engineering work and projects, the capabilities required by engineers, and the kinds of capabilities that graduates need to operate confidently in this new world of work. There is a clear need for graduates to be more operational as they move from study to work. Consequently, a major focus on experiential learning is emerging as the key delivery vehicle for new kinds of graduates including projects, studios, and internships. These forms of learning are supported by ready access to online materials as required. A central thread is personalisation of the student learning experience through learning contracts and portfolios. There has been constant demand for change in engineering education for at least the last 20 years. Making change happen, however, is another matter. We are in the fortunate position at this university to have high level support from the Chancellery and the Dean to move our engineering programs to be more relevant to the future. This paper describes the process for engaging our academics, students and industry supporters in that process and will be of interest to many who are grappling with similar transitions.
Halkon, B, Cheong, I, Visser, G, Walker, P & Oberst, S 1970, 'An experimental assessment of torsional and package vibration in an industrial engine-compressor system', 12th International Conference on Vibrations in Rotating Machinery, Vibrations in Rotating Machinery, CRC Press, Liverpool, pp. 625-639.
View description>>
An experimental field vibration measurement campaign was conducted on an engine-compressor system. Torsional vibrations were measured using both a strain-gauge based technique at the engine-compressor coupling and a rotational laser vibrometer at the torsional vibration damper. Package vibration measurements were simultaneously captured using a number of accelerometers mounted at various locations on the engine and compressor casings. Findings from the study include the observation that the coupling/damper dominant order 1.5 torsional vibration level was higher at idle (c14.1 Hz) than at full speed (c19.1 Hz) and that this is likely the result of the coincidence of the first torsional natural frequency (c19-20 Hz); vibration remained within limits. The package vibration observed was in general within limits and displayed the expected behaviour when shaft speeds coincided with structural resonances. Increasing of system load was observed to result in package vibration level increase in the engine but reduction in the compressor and this is suspected to be as a result of the effect of increased damping. Induced cylinder misfire scenarios were shown to lead to higher vibration levels. To the authors’ knowledge, this is the first time that angular displacement, vibratory torque and package vibration have been simultaneously measured, analysed and reported in an industrial context/scenario. It is hoped that this contribution might, therefore, serve as a practical guide to vibration engineers that wish to embark on similar campaigns.
Indraratna, B, Ngo, T, Rujikiatkamjorn, C & Ferreira, F 1970, 'Advancement of Rail Ballast Testing Methodologies and Design Implications', Geo-Congress 2020, Geo-Congress 2020, American Society of Civil Engineers, Minneapolis, MN, pp. 355-363.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. Given the limited capacity of available railway tracks in Australia, to sustain increasingly faster and heavier trains, the development of innovative and sustainable ballasted tracks is essential for Australian transport infrastructure. Upon repeated train loading, ballast aggregates become degraded and fouled owing to the intrusion of external fines either from the subbase or surface, which decreases track drainage potentially leading to track instability. This paper reviews some advancements in testing methodologies and design implications of ballasted tracks stabilized with artificial inclusions, including geocomposites, energy absorbing rubber mats, and end-of-life tires. Measured test data shows that the use of these waste rubber products and geosynthetics provides an appropriate solution for mitigating unacceptable track degradation and for improving sustainable track alignment, apart from reducing the thickness of the ballast layer. Field monitoring data from fully instrumented tracks constructed at Singleton, Australia, is presented and discussed. The outcomes of this study contribute to a better understanding of the performance of reinforced ballasted tracks, which will be imperative for the development of more efficient and cost-effective track designs with enhanced safety and passenger comfort.
Jayasuriya, C, Indraratna, B, Rujikiatkamjorn, C & Navaratnarajah, SK 1970, 'Application of Elastic Inclusions to Improve the Performance of Ballasted Track', Geo-Congress 2020, Geo-Congress 2020, American Society of Civil Engineers, pp. 364-373.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. Ballast is the most common foundation material of railways and as such is subjected to deformation and degradation from the large cyclic and impact loads generated by heavy, fast moving trains. These inevitable effects hamper the safety and efficiency of tracks and increase the track maintenance frequency. One of several promising approaches to mitigate these problems is stabilizing ballasted track with rubber mats (under sleeper pads -USP and under ballast mats -UBM), to absorb energy and reduce particle breakage, track stability, longevity, and safety. This paper analyses the current knowledge of using rubber elements in ballasted track acquired through large scale laboratory testing carried out at the University of Wollongong (UOW). This investigation reveals that indicate that the damping characteristics of rubber mats reduce the deformation and degradation of ballast. The results shows that USPs are better at reducing vertical permanent deformation while UBMs are better at reducing lateral deformation.
Jena, R & Pradhan, B 1970, 'Earthquake Risk Assessment Using Integrated Influence Diagram–AHP Approach', IOP Conference Series: Earth and Environmental Science, International Conference and Exhibition on Geospatial & Remote Sensing, IOP Publishing, Kuala Lumpur, Malaysia, pp. 012078-012078.
View/Download from: Publisher's site
View description>>
Abstract Indonesia is located at the joint situation of four major world tectonic plates in the Pacific Ring of Fire. Mostly, the coastal regions of Indonesia are highly prone to several natural hazards, such as tsunamis, earthquakes, and volcanic activity. The major earthquake incident in the country was the 2004 earthquake in Aceh, whereas a major volcanic eruption was the Mount Merapi volcanic eruption in 2010. With the present advancement of knowledge regarding the existing hazards, we acknowledge the importance of vulnerability and risk in monitoring and mitigating earthquake hazards. However, to date, a specific effort is unavailable for assessing the risk of earthquake hazards that will cover the city-level in Indonesia. Moreover, a comprehensive profile for risk assessment has yet to be created for small-scale urban areas. Few studies have been organized in Indonesia on city-scale risk assessment. Therefore, we attempt to fill this gap by calculating the risk percentage of Banda Aceh City by determining its conditioning factors and analyzing its variations spatially. We used an influence diagram approach and considered all the factors that affect the risk in Banda Aceh. Results show that only the central parts and some parts in the surrounding areas are under high risk compared with other locations. We validated the results using inventory earthquake events and the results of previously published articles.
Jena, R & Pradhan, B 1970, 'Earthquake Social Vulnerability Assessment Using Entropy Method', IOP Conference Series: Earth and Environmental Science, 10th Institution-of-Geospatial-and-Remote-Sensing-Malaysia(IGRSM) International Conference and Exhibition on Geospatial and Remote Sensing (IGRSM), IOP Publishing, ELECTR NETWORK, pp. 012079-012079.
View/Download from: Publisher's site
View description>>
Abstract Earthquake is the most devastating event in the current time. Given the probability of highly dangerous future events, risk estimation should be given focus by using the limited and freely available data to predict future vulnerable scenarios of an area that observe the involved uncertainty in the analysis. However, vulnerability assessments should be prospective and based on expected scientifically acceptable events. Therefore, we applied a valuable weight calculation approach called entropy to produce a social vulnerability map for a particular city. We used the population data, including educated and non-educated people and household information, to develop the earthquake social vulnerability map. We used entropy to evaluate the actual weight and produce a good quality map because of some difficulty in the fuzzy synthetic evaluation method for factor weight calculation and relationship ignorance among layers. Results showed that approximately 6% of the population is under very high vulnerability and around 14% are under high vulnerability areas in Banda Aceh City. The developed model is accurate by considering the inventory earthquake vulnerability map. The applied method was favorable, and the process provided good evaluation results, which was reasonable for earthquake hazard, vulnerability, and risk assessment.
Jena, R & Pradhan, B 1970, 'Seismic vulnerability assessment for buildings typology using DEMATEL approach', IOP Conference Series: Earth and Environmental Science, 10th Institution-of-Geospatial-and-Remote-Sensing-Malaysia(IGRSM) International Conference and Exhibition on Geospatial and Remote Sensing (IGRSM), IOP Publishing, ELECTR NETWORK, pp. 012063-012063.
View/Download from: Publisher's site
View description>>
Abstract During the last two decades, the severity of high magnitude earthquakes rose to a vast extent. A large amount of damage due to such devastating events reflects poor construction planning. Before the 2004 event in Indonesia, we assume poor construction planning with indigent seismic resistance in the Northern Sumatra. However, this event affected the modern buildings in Aceh province. Therefore, authors have categories all the building types into a catalogue. The typologies considered are hierarchical, construction material, structural irregularities, structural system, building height, and maintenance quality. We applied the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to prepare the vulnerability map using the typology of the building. In addition, the results show that the prepared approach is effective and useful for seismic vulnerability assessment.
Kundu, S, Shivakumara, P, Grouver, A, Pal, U, Lu, T & Blumenstein, M 1970, 'A New Forged Handwriting Detection Method Based on Fourier Spectral Density and Variation', Pattern Recognition, Asian Conference on Pattern Recognition, Springer International Publishing, Auckland, New Zealand, pp. 136-150.
View/Download from: Publisher's site
View description>>
Use of handwriting words for person identification in contrast to biometric features is gaining importance in the field of forensic applications. As a result, forging handwriting is a part of crime applications and hence is challenging for the researchers. This paper presents a new work for detecting forged handwriting words because width and amplitude of spectral distributions have the ability to exhibit unique properties for forged handwriting words compared to blurred, noisy and normal handwriting words. The proposed method studies spectral density and variation of input handwriting images through clustering of high and low frequency coefficients. The extracted features, which are invariant to rotation and scaling, are passed to a neural network classifier for the classification for forged handwriting words from other types of handwriting words (like blurred, noisy and normal handwriting words). Experimental results on our own dataset, which consists of four handwriting word classes, and two benchmark datasets, namely, caption and scene text classification and forged IMEI number dataset, show that the proposed method outperforms the existing methods in terms of classification rate.
Le, TM & Khabbaz, H 2020, 'Predicting consolidation coefficient of soft clay by time-displacement-velocity methods', 16th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, ARC 2019.
View description>>
Copyright © Soil Mechanics and Geotechnical Engineering, ARC 2019.All rights reserved. The coefficient of consolidation is a parameter, governing the rate at which saturated clay undergoes consolidation when subjected to an increase in pressure. The rate and amount of compression in clay varies with the rate that excess pore water pressure is dissipated; and hence depends on clay permeability. Over many years, various methods have been proposed to determine the coefficient of consolidation, cv, which is an indication of the rate of foundation settlement on soft ground. However, defining this parameter is often problematic and greatly relies on graphical techniques, which are subject to some uncertainties. This paper initially presents an overview of many well-established methods to determine the vertical coefficient of consolidation from the incremental loading consolidation tests. An array of consolidation tests was conducted on fully-saturated and undisturbed clay samples retrieved by an oil-operated sampler, collected at various depths from a site in Nakdong river delta, Busan, South Korea. The test results on these soft sensitive clay samples were employed to predict the settlement rate of Busan clay. To establish the relationship of time-displacement-velocity, a total of 3 method groups from 10 common procedures were classified and compared together. Detailed discussion on the results of this study is also provided.
Le, TM & Khabbaz, H 1970, 'Predicting consolidation coefficient of soft clay by time-displacement-velocity methods', 16th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, ARC 2019, Asian Regional Conference on Soil Mechanics and Geotechnical Engineering, AGSSEA, Taiwan, pp. 1-4.
View description>>
The coefficient of consolidation is a parameter, governing the rate at which saturated clay undergoes consolidation when subjected to an increase in pressure. The rate and amount of compression in clay varies with the rate that excess pore water pressure is dissipated; and hence depends on clay permeability. Over many years, various methods have been proposed to determine the coefficient of consolidation, cv, which is an indication of the rate of foundation settlement on soft ground. However, defining this parameter is often problematic and greatly relies on graphical techniques, which are subject to some uncertainties. This paper initially presents an overview of many well-established methods to determine the vertical coefficient of consolidation from the incremental loading consolidation tests. An array of consolidation tests was conducted on fully-saturated and undisturbed clay samples retrieved by an oil-operated sampler, collected at various depths from a site in Nakdong river delta, Busan, South Korea. The test results on these soft sensitive clay samples were employed to predict the settlement rate of Busan clay. To establish the relationship of time-displacement-velocity, a total of 3 method groups from 10 common procedures were classified and compared together. Detailed discussion on the results of this study is also provided.
Liang, B, Verma, S, Xu, J, Liang, S, Li, Z, Wang, Y & Chen, F 1970, 'A Data Driven Approach for Leak Detection with Smart Sensors', 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), IEEE, Shenzhen, China, pp. 1311-1316.
View/Download from: Publisher's site
View description>>
Preventing water pipe leaks and breaks has high priority for water utilities. It is a critical task for the utility to reduce water loss through leaks and breaks detection in water mains. The failure prediction and data analytics research have been conducted for an Australian water utility over the last few years to enhance the prediction of leaks and breaks detection in water mains. Intelligent sensing at sensitive locations with current research aids in prioritising investigation and prevention of potential breaks and leaks in water mains. The purpose of this work is to integrate the predictive analytics and intelligent sensing applications to identify high risk mains prior to failures. Predictive analytics and minimum night flow (MNF) analysis have been utilised to prioritise risky zones over the whole water network, and then risky pipes are identified to optimise sensors deployment. The sensing data is being collected for analysis and validation, and a machine learning model is being built based on the analysis results. This work is currently under progress and the planned outcomes will help the utility reduce water loss, improve leak detection, and enhance customer satisfaction by automating the process of leak detection using a data driven approach with smart sensors.
Liu, J, Teng, J, Zhang, S & Sheng, D 1970, 'A frost heave model of unsaturated coarse-grained soil considering vapour transfer', E3S Web of Conferences, EDP Sciences, pp. 02017-02017.
View/Download from: Publisher's site
View description>>
Substantial frost heave has been observed in coarse fills in high-speed railway embankments. These coarse fills have low fine contents and very low water content. The groundwater table is located below the coarse fills. The coarse fills were considered not susceptible to frost heave. Recent experimental results in the literature showed that vapour transfer has a considerable influence on the frost heaving of unsaturated coarse-grained soil. But vapour transfer has been rarely considered in the modelling of frost heave. This study presents a new frost heave model with considering vapour transfer and its contribution to ice formation. The rigid ice theory is applied to initiate an ice lens formation in the frozen fringe. An updated computer programme PCHeave is developed by considering the vapour transfer. The results of the proposed model are compared with laboratory test results, which show reasonable agreement. The prediction of the model agrees well with the measured frost heave and frost depth, which indicates that the proposed model can reasonably reflects the process of frost heave in unsaturated coarse soil.
Makhdoom, I, Tofigh, F, Zhou, I, Abolhasan, M & Lipman, J 1970, 'PLEDGE: A Proof-of-Honesty based Consensus Protocol for Blockchain-based IoT Systems', 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), IEEE, Toronto, ON, Canada, pp. 1-3.
View/Download from: Publisher's site
View description>>
Exhibition of malicious behavior during blockchain consensus, threats against reputation systems, and high TX latency are significant issues for blockchain-based IoT systems. Hence, to mitigate such challenges we propose 'Pledge', a unique Proof-of-Honesty based consensus protocol. Initial experimentation shows that Pledge is economical with low computations and communications complexity and low latency in transaction confirmation.
Makhdoom, I, Tofigh, F, Zhou, I, Abolhasan, M & Lipman, J 1970, 'PLEDGE: An IoT-oriented Proof-of-Honesty based Blockchain Consensus Protocol', 2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020 IEEE 45th Conference on Local Computer Networks (LCN), IEEE, Australia, pp. 54-64.
View/Download from: Publisher's site
View description>>
The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are mostly used for blockchain-based financial technology applications. Similarly, the Byzantine Fault Tolerance algorithms do provide consensus finality, yet they are either communications intensive, vulnerable to Denial-of-Service attacks, poorly scalable, or have a low faulty node tolerance level. Moreover, these algorithms are not designed for the Internet of Things systems that require near-real-time transaction confirmation, maximum fault tolerance, and appropriate transaction validation rules. Hence, we propose 'Pledge, 'a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus. Pledge also introduces the Internet of Things centric transaction validation rules. Initial experimentation shows that Pledge is economical and secure with low communications complexity and low latency in transaction confirmation.
Mittal, A, Shivakumara, P, Pal, U, Lu, T, Blumenstein, M & Lopresti, D 1970, 'A New Context-Based Method for Restoring Occluded Text in Natural Scene Images', Document Analysis Systems, International Workshop on Document Analysis Systems, Springer International Publishing, Wuhan, China, pp. 466-480.
View/Download from: Publisher's site
View description>>
Text recognition from natural scene images is an active research area because of its important real world applications, including multimedia search and retrieval, and scene understanding through computer vision. It is often the case that portions of text in images are missed due to occlusion with objects in the background. Therefore, this paper presents a method for restoring occluded text to improve text recognition performance. The proposed method uses the GOOGLE Vision API for obtaining labels for input images. We propose to use PixelLink-E2E methods for detecting text and obtaining recognition results. Using these results, the proposed method generates candidate words based on distance measures employing lexicons created through natural scene text recognition. We extract the semantic similarity between labels and recognition results, which results in a Global Context Score (GCS). Next, we use the Natural Language Processing (NLP) system known as BERT for extracting semantics between candidate words, which results in a Local Context Score (LCS). Global and local context scores are then fused for estimating the ranking for each candidate word. The word that gets the highest ranking is taken as the correction for text which is occluded in the image. Experimental results on a dataset assembled from standard natural scene datasets and our resources show that our approach helps to improve the text recognition performance significantly.
Muchtar, K, Munadi, K, Maulina, N, Pradhan, B, Arnia, F & Yanti, B 1970, 'Performance Evaluation of Binary Classification of Tuberculosis through Unsharp Masking and Deep Learning Technique', 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings, pp. 924-928.
View description>>
The latest World Health Organization (WHO) study in 2018 shows that about 1.5 million people died and around 10 million people are infected with tuberculosis (TBC) each year. Moreover, more than 4,000 people die every day from TBC. Important work can be found in automating the diagnosis by applying techniques of deep learning (DL) to the medical image. DL requires a large number of high-quality training samples to reach better performance. Due to the low contrast of TBC x-ray images, the image obtained is poor in quality. Our work assesses the effect of image enhancement on the performance of the DL technique based on this problem. An image enhancement algorithm will highlight the overall or local characteristics of the images, and highlight some interesting features. Specifically, an image enhancement algorithm called Unsharp Masking (UM), is evaluated. The enhanced image samples are then fed to the pre-trained ResNet model for transfer learning. In a TB image dataset, we achieve 88.69% and 96.15% of classification accuracy and AUC scores, respectively. All the results are obtained using the Shenzhen dataset which is available in the public domain.
Nalamati, M, Sharma, N, Saqib, M & Blumenstein, M 1970, 'Automated Monitoring in Maritime Video Surveillance System', 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, New Zealand, pp. 1-6.
View/Download from: Publisher's site
View description>>
Maritime surveillance for intruders/illegal activities requires monitoring of a large area of the coastline. This task being manually exhaustive, would benefit immensely by application of object detection techniques to surveillance videos. However, object detection models trained on general objects datasets cannot be expected to give best performance for this scenario as marine vessels are only a small subset of these huge datasets and also do not classify the specific type of sea vehicle. Hence, their benchmarks are not appropriate for maritime surveillance. Some studies have been done with applications of Convolutional Neural Networks (CNN) for ship/boat detection on private and publicly available sea vessels datasets. This paper presents a summary of the benchmarks so far and presents our experiments of the latest object detection techniques for combined marine vessels dataset. A survey of the currently available datasets is also given. Results of our experiments in terms of mean Average Precision (mAP) and Frames Per Second (FPS) are presented.
Nandanwar, L, Shivakumara, P, Manna, S, Pal, U, Lu, T & Blumenstein, M 1970, 'A New DCT-FFT Fusion Based Method for Caption and Scene Text Classification in Action Video Images', Pattern Recognition and Artificial Intelligence, International Conference on Pattern Recognition and Artificial Intelligence, Springer International Publishing, Zhongshan, China, pp. 80-92.
View/Download from: Publisher's site
View description>>
Achieving better recognition rate for text in video action images is challenging due to multi-type texts with unpredictable backgrounds. We propose a new method for the classification of captions (which is edited text) and scene texts (which is part of an image in video images of Yoga, Concert, Teleshopping, Craft, and Recipe classes). The proposed method introduces a new fusion criterion-based on DCT and Fourier coefficients to extract features that represent good clarity and visibility of captions to separate them from scene texts. The variances for coefficients of corresponding pixels of DCT and Fourier images are computed to derive the respective weights. The weights and coefficients are further used to generate a fused image. Furthermore, the proposed method estimates sparsity in Canny edge image of each fused image to derive rules for classifying caption and scene texts. Lastly, the proposed method is evaluated on images of five above-mentioned action image classes to validate the derived rules. Comparative studies with the state-of-the-art methods on the standard databases show that the proposed method outperforms the existing methods in terms of classification. The recognition experiments before and after classification show that the recognition performance rate improves significantly after classification.
Navaratnarajah, SK & Indraratna, B 1970, 'Application of Under Sleeper Pads to Enhance the Sleeper-Ballast Interface Behaviors', Springer Singapore, pp. 619-636.
View/Download from: Publisher's site
Ngo, T & Indraratna, B 1970, 'Numerical Modelling of Track Behavior Capturing Particle Breakage under Dynamic Loading', Geo-Congress 2020, Geo-Congress 2020, American Society of Civil Engineers, Minneapolis, MN, pp. 374-382.
View/Download from: Publisher's site
View description>>
© 2020 American Society of Civil Engineers. This paper presents a study on ballasted track behavior, capturing particle breakage under dynamic loading using large-scale laboratory testing, supplemented with computational modeling approaches. Four large-scale triaxial tests are conducted to investigate the ballast breakage responses subjected to cyclic loading subjected to varying frequencies, f=10-40Hz. Measured laboratory observations show that an increase in loading frequency and magnitude results in significantly increased degradation (breakage) and deformation of ballast. Computational modeling using a coupled discrete-continuum approach (coupled DEM-FEM) is introduced to provide insightful understanding of the deformation and breaking of ballast under cyclic loading. Discrete ballast grains are simulated by bonding of many cylinders together at appropriate sizes and locations. Selected elements located at corners, surfaces, and sharp edges of the simulated particles are connected by parallel bonds; and when those bonds are broken, they are considered to represent ballast breakage. The predicted axial strain ϵa, volumetric strain ϵv obtained from the coupled DEM-FEM model agree reasonably well with those observed experimentally. The coupled model is then used to investigate micromechanical aspects of ballast aggregates including the evolution of particle breakage, contact force distributions, and orientation of contacts during cyclic loading.
Nguyen, TN, Erkmen, E, Sanchez, LFM & Li, J 1970, 'A Probabilistic Homogenization Approach for the Computation of Stiffness Degradation in ASR-affected Concrete', The 16th International Conference on Alkali Aggregate Reaction in Concrete.
Pour, AB, Park, Y, Hong, JK, Muslim, AM & Pradhan, B 1970, 'Geological mapping in Morozumi range and Helliwell hills areas, northern Victoria Land (NVL), Antarctica using remote sensing imagery', 40th Asian Conference on Remote Sensing, ACRS 2019: Progress of Remote Sensing Technology for Smart Future.
View description>>
Many regions remain poorly studied in terms of geological mapping in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistical difficulties. Application of specialized image processing techniques is capable of revealing the hidden linearly mixed spectral sources in multispectral and hyperspectral satellite images. In this study, the application of Independent component analysis (ICA) and Constrained Energy Minimization (CEM) algorithms was evaluated for Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. ICA algorithm was able to detect hidden linearly mixed spectral sources and low probability target materials in Landsat-8 and ASTER datasets. Fraction images of endmember target minerals such as hematite, goethite, jarosite, alunite, kaolinite, muscovite, epidote, chlorite, calcite, quartz, opal and chalcedony were produced using CEM algorithm for two spatial subsets of ASTER scene covering the Morozumi Range and Helliwell Hills areas. CEM classification image maps indicated that chlorite/hematite, goethite/jarosite/calcite and kaolinite/muscovite are governed in the Morozumi Range and goethite, chlorite, hematite and epidote are most dominated mineral assemblages in the Helliwell Hills area. GPS survey and XRD analysis verified the alteration mineral assemblages detected by ICA and CEM image processing algorithms. The results of this investigation demonstrate the capability of the two algorithms in distinguishing pixel and subpixel targets in the multispectral satellite data. The application of the methods for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable implications for geological mapping and mineral exploration in inaccessible regions.
Pour, AB, Park, Y, Hong, JK, Muslim, AM & Pradhan, B 1970, 'Geological mapping in Morozumi range and Helliwell hills areas, northern Victoria Land (NVL), Antarctica using remote sensing imagery', 40th Asian Conference on Remote Sensing, ACRS 2019: &amp;amp;amp;amp;amp;quot;Progress of Remote Sensing Technology for Smart Future&amp;amp;amp;amp;amp;quot;.
View description>>
© 2020 40th Asian Conference on Remote Sensing, ACRS 2019: 'Progress of Remote Sensing Technology for Smart Future'. All rights reserved. Many regions remain poorly studied in terms of geological mapping in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistical difficulties. Application of specialized image processing techniques is capable of revealing the hidden linearly mixed spectral sources in multispectral and hyperspectral satellite images. In this study, the application of Independent component analysis (ICA) and Constrained Energy Minimization (CEM) algorithms was evaluated for Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. ICA algorithm was able to detect hidden linearly mixed spectral sources and low probability target materials in Landsat-8 and ASTER datasets. Fraction images of endmember target minerals such as hematite, goethite, jarosite, alunite, kaolinite, muscovite, epidote, chlorite, calcite, quartz, opal and chalcedony were produced using CEM algorithm for two spatial subsets of ASTER scene covering the Morozumi Range and Helliwell Hills areas. CEM classification image maps indicated that chlorite/hematite, goethite/jarosite/calcite and kaolinite/muscovite are governed in the Morozumi Range and goethite, chlorite, hematite and epidote are most dominated mineral assemblages in the Helliwell Hills area. GPS survey and XRD analysis verified the alteration mineral assemblages detected by ICA and CEM image processing algorithms. The results of this investigation demonstrate the capability of the two algorithms in distinguishing pixel and subpixel targets in the multispectral satellite data. The application of the methods for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable ...
Pour, AB, Park, Y, Hong, JK, Muslim, AM & Pradhan, B 1970, 'Geological mapping in Morozumi range and Helliwell hills areas, northern Victoria Land (NVL), Antarctica using remote sensing imagery', 40th Asian Conference on Remote Sensing, ACRS 2019: &amp;amp;amp;amp;amp;quot;Progress of Remote Sensing Technology for Smart Future&amp;amp;amp;amp;amp;quot;.
View description>>
Many regions remain poorly studied in terms of geological mapping in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistical difficulties. Application of specialized image processing techniques is capable of revealing the hidden linearly mixed spectral sources in multispectral and hyperspectral satellite images. In this study, the application of Independent component analysis (ICA) and Constrained Energy Minimization (CEM) algorithms was evaluated for Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. ICA algorithm was able to detect hidden linearly mixed spectral sources and low probability target materials in Landsat-8 and ASTER datasets. Fraction images of endmember target minerals such as hematite, goethite, jarosite, alunite, kaolinite, muscovite, epidote, chlorite, calcite, quartz, opal and chalcedony were produced using CEM algorithm for two spatial subsets of ASTER scene covering the Morozumi Range and Helliwell Hills areas. CEM classification image maps indicated that chlorite/hematite, goethite/jarosite/calcite and kaolinite/muscovite are governed in the Morozumi Range and goethite, chlorite, hematite and epidote are most dominated mineral assemblages in the Helliwell Hills area. GPS survey and XRD analysis verified the alteration mineral assemblages detected by ICA and CEM image processing algorithms. The results of this investigation demonstrate the capability of the two algorithms in distinguishing pixel and subpixel targets in the multispectral satellite data. The application of the methods for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable implications for geological mapping and mineral exploration in inaccessible regions.
Pour, AB, Park, Y, Hong, JK, Muslim, AM & Pradhan, B 1970, 'Listvenite occurrences in the fault zones of northern Victoria Land, Antarctica: Aster-based mapping approach', 40th Asian Conference on Remote Sensing, ACRS 2019: &amp;amp;amp;amp;amp;quot;Progress of Remote Sensing Technology for Smart Future&amp;amp;amp;amp;amp;quot;.
View description>>
Listvenite, a Mg-carbonate-quartz-fuchsite±Cr-chlorite±pyrite±chromite rock, forms by hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represents a key indicator for hydrothermal mineral deposits in orogenic belts. Hydrothermal/metasomatic alteration zones in the damage zones of accretionary plate boundaries are efficiently detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data are used to identify listvenite occurrences and alteration mineral zones in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL) of Antarctica. Spectral information for detecting alteration mineral assemblages and listvenite zones were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineral phases containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were are distinguished in the damage zones through PCA/ICA fusion of ASTER visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate rocks are discriminated from the PCA/ICA fusion of the ASTER thermal infrared (TIR) bands. The extracted mineral images of goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and listvenite occurrences were produced using the LSU and CEM algorithms. Listvenite occurrences are confined to mafic metavolcanic rocks (Glasgow Volcanics) in the Bowers Mountains. New field investigations verified the presence of listvenite in the mapped zones and further constrain on the efficiency of the integrative methodology used in this study.
Pour, AB, Park, Y, Hong, JK, Muslim, AM & Pradhan, B 1970, 'Listvenite occurrences in the fault zones of northern Victoria Land, Antarctica: Aster-based mapping approach', 40th Asian Conference on Remote Sensing, ACRS 2019: &amp;amp;amp;amp;amp;quot;Progress of Remote Sensing Technology for Smart Future&amp;amp;amp;amp;amp;quot;.
View description>>
© 2020 40th Asian Conference on Remote Sensing, ACRS 2019: 'Progress of Remote Sensing Technology for Smart Future'. All rights reserved. Listvenite, a Mg-carbonate-quartz-fuchsite±Cr-chlorite±pyrite±chromite rock, forms by hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represents a key indicator for hydrothermal mineral deposits in orogenic belts. Hydrothermal/metasomatic alteration zones in the damage zones of accretionary plate boundaries are efficiently detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data are used to identify listvenite occurrences and alteration mineral zones in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL) of Antarctica. Spectral information for detecting alteration mineral assemblages and listvenite zones were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineral phases containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were are distinguished in the damage zones through PCA/ICA fusion of ASTER visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate rocks are discriminated from the PCA/ICA fusion of the ASTER thermal infrared (TIR) bands. The extracted mineral images of goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and listvenite occurrences were produced using the LSU and CEM algorithms. Listvenite occurrences are confined to mafic metavolcanic rocks (Glasgow Volcanics) in the Bowers Mountains. New field investigations verified the presence of listven...
Pour, AB, Park, Y, Hong, JK, Muslim, AM & Pradhan, B 1970, 'Listvenite occurrences in the fault zones of northern Victoria Land, Antarctica: Aster-based mapping approach', 40th Asian Conference on Remote Sensing, ACRS 2019: Progress of Remote Sensing Technology for Smart Future.
View description>>
Listvenite, a Mg-carbonate-quartz-fuchsite±Cr-chlorite±pyrite±chromite rock, forms by hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represents a key indicator for hydrothermal mineral deposits in orogenic belts. Hydrothermal/metasomatic alteration zones in the damage zones of accretionary plate boundaries are efficiently detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data are used to identify listvenite occurrences and alteration mineral zones in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL) of Antarctica. Spectral information for detecting alteration mineral assemblages and listvenite zones were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineral phases containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were are distinguished in the damage zones through PCA/ICA fusion of ASTER visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate rocks are discriminated from the PCA/ICA fusion of the ASTER thermal infrared (TIR) bands. The extracted mineral images of goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and listvenite occurrences were produced using the LSU and CEM algorithms. Listvenite occurrences are confined to mafic metavolcanic rocks (Glasgow Volcanics) in the Bowers Mountains. New field investigations verified the presence of listvenite in the mapped zones and further constrain on the efficiency of the integrative methodology used in this study.
Qi, Y, Indraratna, B & Tawk, M 1970, 'Use of Recycled Rubber Elements in Track Stabilisation', Geo-Congress 2020, Geo-Congress 2020, American Society of Civil Engineers, USA, pp. 49-59.
View/Download from: Publisher's site
View description>>
This paper introduces two novel methods of using waste materials i.e., steel furnace slag (SFS), coal wash (CW), and rubber crumbs (RC) in rail tracks. One method is to optimize the mixtures of SFS, CW, and RC (SFS+CW+RC matrix) compacted with the standard compaction energy to serve as a subballast material. The other one is to examine the potential usage of CW and RC mixtures (CW+RC matrix) which are compacted under adjusted compaction effort. To investigate the geotechnical properties of these waste mixtures, comprehensive laboratory tests have been conducted. Based on the test results, the stress-strain relationship is studied with special focus on the effect of rubber content on the ductility and energy-absorbing potential of the proposed mixtures. In addition, for the CW+RC matrix, the role of rubber content and compaction effort on the compaction and degradation characteristics of the material is examined.
Raza, MA, Abolhasan, M, Lipman, J, Shariati, N & Ni, W 1970, 'Statistical Learning-Based Dynamic Retransmission Mechanism for Mission Critical Communication: An Edge-Computing Approach', 2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020 IEEE 45th Conference on Local Computer Networks (LCN), IEEE, Australia, pp. 393-396.
View/Download from: Publisher's site
View description>>
Mission-critical machine type communication (MC-MTC) systems in which machines communicate to perform various tasks such as coordination, sensing, and actuation, require stringent requirements of ultra-reliable and low latency communications (URLLC). Edge computing being an integral part of future wireless networks, provides services that support URLLC applications. In this paper, we use the edge computing approach and present a statistical learning-based dynamic retransmission mechanism. The proposed approach meets the desired latency-reliability criterion in MC-MTC networks employing framed ALOHA. The maximum number of retransmissions Nr under a given latency-reliability constraint is learned statistically by the devices from the history of their previous transmissions and shared with the base station. Simulations are performed in MATLAB to evaluate a framed-ALOHA system's performance in which an active device can have only one successful transmission in one round composed of (Nr + 1) frames, and the performance is compared with the diversity transmission-based framed-ALOHA.
Roy, S, Shivakumara, P, Pal, U, Lu, T & Blumenstein, M 1970, 'New Moments Based Fuzzy Similarity Measure for Text Detection in Distorted Social Media Images', Pattern Recognition, Asian Conference on Pattern Recognition, Springer International Publishing, New Zealand, pp. 720-734.
View/Download from: Publisher's site
View description>>
A trend towards capturing or filming images using cellphone and sharing images on social media is a part and parcel of day to day activities of humans. When an image is forwarded several times in social media it may be distorted a lot due to several different devices. This work deals with text detection from such distorted images. In this work, we consider images pass through three mobile devices on WhatsApp social media, which results in four images (including the original image) Unlike the existing methods that aim at developing new ways, we utilize the results detected by the existing ones to improve performances. The proposed method extracts Hu moments and fuzzy logic from detected texts of images. The similarity between text detection results given by three existing text detection methods is studied for determining the best pair of texts. The same similarity estimation is then used in a novel way to remove extra background or non-texts and restoring missing text information. Experimental results on own dataset and benchmark datasets of natural scene images, namely, MSRA-TD500, ICDAR2017-MLT, Total-Text, CTW1500 dataset and COCO datasets, show that the proposed method outperforms the existing methods.
Sadeghi, F, Zhu, X & Li, J 1970, 'DAMAGE ANALYSIS OF STEEL-CONCRETE COMPOSITE BEAMS UNDER STATIC LOADS', XI International Conference on Structural Dynamics, XI International Conference on Structural Dynamics, EASD, Athens, Greece, pp. 1053-1062.
View/Download from: Publisher's site
View description>>
© 2020 European Association for Structural Dynamics. All rights reserved. This paper presents a study of the static behavior of steel-concrete composite beams with different types of damage. Since the behavior of a composite beam under load is governed by the shear connection, it is important to investigate the overall structural response due to different levels of damage in the interface and composite layers. A finite element (FE) model of a steel-concrete composite beam is developed based on two Euler-Bernoulli beams as the composite layers coupled with a deformable shear connection. Three different damage indices are defined for the concrete slab, the steel girder, and the distributed shear connection and then embedded into the stiffness matrix of the composite beam. This model is validated by comparing its load-displacement behavior with an equivalent FE model developed using the commercial FE software ABAQUS. The impact that the loading location has on the results is then investigated. A convergence study is also carried out in terms of the displacements and strains to determine the number of composite beam FEs. The maximum displacements and strains of composite beams with different types and levels of damage are then investigated. The numerical analysis showed that after an initial reduction when the number of FEs increase, the changes in displacement and strain at each location are very small. Moreover, the bonding slip has almost no effect on the measurements, and the changes in maximum displacement and strain from undamaged to maximum damage are almost the same.
SHARARI, N, FATAHI, B & HOKMABADI, AS 1970, 'IMPACT OF WALL SUPPORT CONDITIONS ON SEISMIC RESPONSE OF GROUND-SUPPORTED REINFORCED CONCRETE CONTAINMENT TANKS', WIT Transactions on The Built Environment, SUSI 2020, WIT Press, pp. 139-151.
View/Download from: Publisher's site
View description>>
Concrete liquid storage tanks are commonly used in regions that may be highly seismic, for the storage of water, petroleum products and other chemicals. In some cases, such as for liquefied natural gas (LNG) tanks, a secondary concrete containment is designed for external protection, ignoring any direct contact or interaction with the inner storage liquid by creating a gap, as another inner tank is used to hold the liquid. Typical secondary containment tanks for LNG are circular, upright concrete tanks, with fixed roofs, while the support wall conditions at its base can be hinged or fixed. In this study, the nonlinear behavior of ground supported circular reinforced concrete containment tank under the effect of the seismic loads is investigated for both hinged and fixed wall support conditions. A three-dimensional finite element model considering material nonlinearities was included. In particular, the Concrete Damage Plasticity (CDP) model, capturing the possible tensile cracking and compressive crushing of the concrete containment systems under seismic loads was adopted. By adopting time history analyses, deformation and stresses developed in the tank were assessed when subjected to large earthquakes, namely the 1994 Northridge and 1995 Kobe earthquakes, while frequency domain analyses were also conducted, to obtain the natural period and mode shapes for different wall support conditions. The results showed that in the hinged tank, the walls experience higher structural responses (in terms of shear force and bending moment); compared with the fixed tank, particularly around the mid-height zone of the tank wall. Conversely, at the base of the fixed tank, shear forces and bending moments were higher, compared with the hinged tank’s base. Under the effects of large earthquakes, both tanks experienced damage, yet larger seismic forces upon a hinged tank could potentially create more damage.
Sheng, D & Sloan, SW 1970, 'Load stepping schemes and unbalanced force norms in geotechnical analysis', NUMERICAL MODELS IN GEOMECHANICS - NUMOG VII, 7th International Symposium on Numerical Models in Geomechanics (NUMOG), CRC Press, GRAZ, AUSTRIA, pp. 201-208.
View/Download from: Publisher's site
Tohidi, F, Paul, M, Hooshmandasl, MR, Chakraborty, S & Pradhan, B 1970, 'Block-Wise Authentication and Recovery Scheme for Medical Images Focusing on Content Complexity', Image and Video Technology, Pacific-Rim Symposium on Image and Video Technology, Springer International Publishing, Sydney, NSW, Australia, pp. 86-99.
View/Download from: Publisher's site
View description>>
© Springer Nature Switzerland AG 2020. Digital images are used to transfer most critical data in areas like medical, research, business, military, etc. The images transfer takes place over an unsecured Internet network. Therefore, there is a need for reliable security and protection for these sensitive images. Medical images play an important role in the field of Telemedicine and Tele surgery. Thus, before making any diagnostic decisions and treatments, the authenticity and the integrity of the received medical images need to be verified to avoid misdiagnosis. This paper proposes a block-wise and blind fragile watermarking mechanism for medical image authentication and recovery. By eliminating embedded insignificant data and considering different content complexity for each block during feature extraction and recovery, the capacity of data embedding without loss of quality is increased. This new embedding watermark method can embed a copy of the compressed image inside itself as a watermark to increase the recovered image quality. In our proposed hybrid scheme, the block features are utilized to improve the efficiency of data concealing for authentication and reduce tampering. Therefore, the scheme can achieve better results in terms of the recovered image quality and greater tampering protection, compared with the current schemes.
Verma, S, Wang, J, Ge, Z, Shen, R, Jin, F, Wang, Y, Chen, F & Liu, W 1970, 'Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis', 2020 IEEE International Conference on Data Mining (ICDM), 2020 IEEE International Conference on Data Mining (ICDM), IEEE, Sorrento, Italy, pp. 561-570.
View/Download from: Publisher's site
View description>>
Multimodal sentiment analysis utilizes multiple heterogeneous modalities for sentiment classification. The recent multimodal fusion schemes customize LSTMs to discover intra-modal dynamics and design sophisticated attention mechanisms to discover the inter-modal dynamics from multimodal sequences. Although powerful, these schemes completely rely on attention mechanisms which is problematic due to two major drawbacks 1) deceptive attention masks, and 2) training dynamics. Nevertheless, strenuous efforts are required to optimize hyperparameters of these consolidate architectures, in particular their custom-designed LSTMs constrained by attention schemes. In this research, we first propose a common network to discover both intra-modal and inter-modal dynamics by utilizing basic LSTMs and tensor based convolution networks. We then propose unique networks to encapsulate temporal-granularity among the modalities which is essential while extracting information within asynchronous sequences. We then integrate these two kinds of information via a fusion layer and call our novel multimodal fusion scheme as Deep-HOSeq (Deep network with higher order Common and Unique Sequence information). The proposed Deep-HOSeq efficiently discovers all-important information from multimodal sequences and the effectiveness of utilizing both types of information is empirically demonstrated on CMU-MOSEI and CMU-MOSI benchmark datasets. The source code of proposed Deep-HOSeq is available at https://github.com/sverma88/Deep-HOSeq-ICDM-2020.
Xie, Q, Pradhan, B, Dikshit, A, Tran, NN, Liu, Y, Abdollahi, A & Huete, AR 1970, 'Forecasting Grass Pollen with Satellite Sensor Time-series, Meteorology data, and Machine Learning Tools', AGU Fall Meeting 2020, online.
Zhong, J, Xiao, T, Halkon, B, Kirby, R & Qiu, X 1970, 'An experimental study on the active noise control using a parametric array loudspeaker', Proceedings of 2020 International Congress on Noise Control Engineering, INTER-NOISE 2020, Seoul, Korea.
View description>>
An active noise control (ANC) system using a parametric array loudspeaker (PAL) was designed to cancel broadband noise at a person's ear, where a custom-made low-mass membrane pick-up from a retroreflective film and a laser Doppler vibrometer was used to form a remote sensing apparatus to determine the acoustic information with minimum obstructions to the person. The experiment results show that such an ANC system can achieve similar overall noise reductions from 1 kHz to 6 kHz at the ear as a similar one albeit using a traditional omnidirectional loudspeaker. The noise reductions at nine points around the person were used to evaluate the effects of the ANC system in the other areas, and the results show the side effect of the ANC system with the PAL is much smaller than that with the traditional loudspeaker due to the sharp radiation directivity of the PAL. It is also shown that when the PAL was placed away from the person, the ANC performance and the side effect to the other areas remained similar due to its low geometrical spreading attenuation, but the side effect caused by a traditional loudspeaker to the other areas increased with its distance to the person.
