Abraham, MT, Satyam, N & Pradhan, B 2024, 'A novel approach for quantifying similarities between different debris flow sites using field investigations and numerical modelling', Terra Nova, vol. 36, no. 2, pp. 138-147.
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AbstractDebris flows are geomorphological processes that affect the landscape evolution process of any region. In this study, an integrated methodology is proposed to identify the chance of further debris flows and quantify the similarities between debris flow locations, materials and rheology, using field and laboratory investigations and remote sensing data. The method was tested for four failure‐triggered debris flow sites in the Western Ghats of India, using dimensionless parametric similarity values ranging from 0 to 1. The maximum parametric similarity was observed as 0.84 when comparing the flow accumulation values of Sites 3 and 4, and the maximum overall site similarity was 0.68. The calibrated rheological parameters of one site were found to be satisfactory in modelling the shape of debris flow at all other sites. The findings can be used to identify similar hotspots in the region and to simulate debris flows for quantitative hazard assessment.
Atapattu, S, Indraratna, B & Rujikiatkamjorn, C 2024, 'Influence of periodic cyclic loading and rest period on soft clay consolidation', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 177, no. 1, pp. 30-43.
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Railways are often subjected to periodic cyclic loading and intermittent rest periods. Excessive consolidation settlements can affect the performance of railway tracks built on the soft subgrade. The consolidation behaviour under railway loading conditions with rest periods has not been evaluated thoroughly. In this study, laboratory testing was conducted to investigate the influence of periodic cyclic loading and rest periods on the consolidation of Holocene soft clay from Ballina NSW. The specimens were subjected to a loading frequency of 1 Hz for 54 h with multiple rest periods. The recorded settlements and excess pore-water pressures (EPWP) during cyclic consolidation were employed to determine the corresponding hydraulic gradient, void ratio, resilient (dynamic) modulus and damping ratio. The settlement and accumulated EPWP can be observed during cyclic loading. In contrast, settlements do not occur within a rest period, despite the rapidly dissipating EPWP at the start of a given rest period. The maximum EPWP and settlements decrease as the number of resting period increases. An analytical model capturing the effect of cyclic loading and rest period is proposed where the unique relationships between the hydraulic gradient and the flow rate are established.
Athuraliya, S, Indraratna, B, Medawela, S, Rowe, RK & Thamwattana, N 2024, 'Modelling biogeochemical clogging affecting piezometers in acid sulfate soil terrain', Canadian Geotechnical Journal, vol. 61, no. 1, pp. 149-164.
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This study offers an analytical solution for radial consolidation that captures the biogeochemical clogging effect in acid sulfate soils. Field sites and personal communication with industry practitioners have provided evidence of piezometers exhibiting retarded pore pressure readings that do not follow conventional soil consolidation and seepage principles when installed in coastal acidic floodplains. This retarded response together with a variation in pH, ion concentrations, and piezometric heads provided evidence of clogging at and around the piezometers. This paper uses the proposed biogeochemical clogging model, which is an analytically derived system of equations to estimate the excess pore water pressure dissipation of piezometers installed in clogging-prone acid sulfate soils. The inclusion of the total porosity reduction attributed to biological and geochemical clogging improves the predictions of the retarded dissipation of excess pore pressure, especially after about 1 year. This method is validated for two previously identified acidic field sites in coastal Australia, where piezometers measured a very slow rate of dissipation. It is concluded that this model has potential to accurately monitor the performance of critical infrastructure, such as dams and embankment foundations built on acidic terrain.
Chen, K, He, X, Liang, F & Sheng, D 2024, 'Influences of ink-bottle effect evolution on water retention hysteresis of unsaturated soils: An experimental investigation', Engineering Geology, vol. 330, pp. 107409-107409.
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Dai, S, He, X, Tong, C, Gao, F, Zhang, S & Sheng, D 2024, 'Stability of sandy soils against internal erosion under cyclic loading and quantitatively examination of the composition and origin of eroded particles', Canadian Geotechnical Journal, vol. 61, no. 4, pp. 732-747.
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Internal erosion refers to the movement of fine particles within soil framework due to subsurface water seepage. Existing criteria for assessing internal erosion usually are based on static loading, and the effect of cyclic load is not considered. Additionally, there are limited studies to examine the particle-size distribution and origin of eroded fine particles. This study presents an experimental investigation that examines the impact of cyclic loading on internal stability through a series of seepage tests. The composition and origin of lost particles are quantitatively studied using particle staining and image recognition techniques. With increasing hydraulic gradient, particle erosion progresses from top layer to bottom layer, with a gradual increase in the maximum particle size of eroded particles from each layer. After significant loss of particles, the specimens reach a state of transient equilibrium, resulting in a gradual slowdown of both particle loss rate and average flow velocity. The results indicate that cyclic loading promotes massive particle loss and causes erosion failure of specimens that are considered stable according to existing criteria. The reason is that under cyclic loading, local hydraulic gradients is oscillating, and a larger than average hydraulic gradient may occur, which is responsible for the internal instability. The analysis suggests that existing criteria can provide a reasonable assessment of the relative stabilities of specimens under static loads but fail to capture the stabilities under cyclic loading conditions.
Dai, S, Zhang, S, Gao, F, He, X & Sheng, D 2024, 'Investigation of particle segregation in a vertically vibrated binary mixture: Segregation process and mechanism', Computers and Geotechnics, vol. 169, pp. 106236-106236.
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Deshpande, NM, Gite, S, Pradhan, B, Alamri, A & Lee, C-W 2024, 'A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database', Computer Modeling in Engineering & Sciences, vol. 139, no. 1, pp. 593-631.
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Dhull, P, Schreurs, D, Paolini, G, Costanzo, A, Abolhasan, M & Shariati, N 2024, 'Multitone PSK Modulation Design for Simultaneous Wireless Information and Power Transfer', IEEE Transactions on Microwave Theory and Techniques, vol. 72, no. 1, pp. 446-460.
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Dikshit, A, Pradhan, B, Matin, SS, Beydoun, G, Santosh, M, Park, H-J & Maulud, KNA 2024, 'Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment', Geoscience Frontiers, vol. 15, no. 4, pp. 101815-101815.
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Ding, L, Chen, C, Shan, X, Liu, B, Wang, D, Du, Z, Zhao, G, Su, QP, Yang, Y, Halkon, B, Tran, TT, Liao, J, Aharonovich, I, Zhang, M, Cheng, F, Fu, L, Xu, X & Wang, F 2024, 'Optical Nonlinearity Enabled Super‐Resolved Multiplexing Microscopy', Advanced Materials, vol. 36, no. 2.
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AbstractOptical multiplexing for nanoscale object recognition is of great significance within the intricate domains of biology, medicine, anti‐counterfeiting, and microscopic imaging. Traditionally, the multiplexing dimensions of nanoscopy are limited to emission intensity, color, lifetime, and polarization. Here, a novel dimension, optical nonlinearity, is proposed for super‐resolved multiplexing microscopy. This optical nonlinearity is attributable to the energy transitions between multiple energy levels of the doped lanthanide ions in upconversion nanoparticles (UCNPs), resulting in unique optical fingerprints for UCNPs with different compositions. A vortex beam is applied to transport the optical nonlinearity onto the imaging point‐spread function (PSF), creating a robust super‐resolved multiplexing imaging strategy for differentiating UCNPs with distinctive optical nonlinearities. The composition information of the nanoparticles can be retrieved with variations of the corresponding PSF in the obtained image. Four channels multiplexing super‐resolved imaging with a single scanning, applying emission color and nonlinearity of two orthogonal imaging dimensions with a spatial resolution higher than 150 nm (1/6.5λ), are demonstrated. This work provides a new and orthogonal dimension – optical nonlinearity – to existing multiplexing dimensions, which shows great potential in bioimaging, anti‐counterfeiting, microarray assays, deep tissue multiplexing detection, and high‐density data storage.
Doan, S & Fatahi, B 2024, 'Simplified analytical solution for time dependent deformation of soft soil improved with pervious column considering load transfer between column and soil', Computers and Geotechnics, vol. 166, pp. 105988-105988.
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Dong, Z-L, Tong, C-X, Zhang, S, Teng, J-D & Sheng, D 2024, 'A Comparative Study on Shear Behavior of Uniform-, Gap-, and Fractal-Graded Carbonate Soils', Journal of Geotechnical and Geoenvironmental Engineering, vol. 150, no. 1.
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Fallahpoor, M, Chakraborty, S, Pradhan, B, Faust, O, Barua, PD, Chegeni, H & Acharya, R 2024, 'Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space', Computer Methods and Programs in Biomedicine, vol. 243, pp. 107880-107880.
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Farooq, MA & Nimbalkar, S 2024, 'Monotonic and cyclic triaxial testing of untreated and polyurethane-treated soil and soil–rubber mixtures', Acta Geotechnica, vol. 19, no. 2, pp. 605-630.
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AbstractThe present research focuses on developing alternate sustainable base materials for a high-speed slab track. In this study, a series of monotonic triaxial, cyclic triaxial and permeability tests were conducted on four types of materials, viz. mix-A (gravel soil), mix-B (soil mixed with rubber), mix-C (polyurethane foam adhesive (PFA)-treated soil), and mix-D (PFA-treated soil–rubber mixture). The influence of cyclic loading frequency, effective confining pressure, drainage condition and relative density on the deformation, excess pore water pressure, resilient modulus and damping ratio of these different mixes is evaluated. The monotonic triaxial test results indicate that the PFA treatment of mix-A and mix-B increased their shear strength and critical state strength. In contrast, incorporating rubber into mix-A and mix-C helped enhance their ductility. The cyclic triaxial test results show that the PFA treatment of mix-A and mix-B significantly reduced the magnitude of deformation and generation of excess pore water pressure, which caused these untreated mixes to fail prematurely under lower confinement to which a typical base layer is subjected. The influence of cyclic loading frequency and effective confining pressure on the material's response differed for untreated and treated soil. The permeability test results indicate good drainage for mix-D comparable to mix-A.
Farooq, MA & Nimbalkar, S 2024, 'Static and cyclic performance of polyurethane foam adhesive bound soil–rubber mixtures under drained conditions', Acta Geotechnica, vol. 19, no. 2, pp. 561-589.
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AbstractThe major drawbacks of a railway track include noise, vibration, and aggravated track degradation. Resilient mats and asphalt have been increasingly used in recent years to mitigate this noise and vibration. However, these materials are quite expensive. Conventional asphalt is very stiff and brittle, making it more prone to cracking. The present work aims to develop a novel material that can be used as a base layer in ballasted and slab tracks. The current research proposes a sustainable and resilient base course layer comprising ground rubber (GR) and polyurethane foam adhesive (PFA). In this study, the performance of GR embedded in the sand is investigated. The use of PFA-treated sand with and without GR is then explored. The optimum dosage of PFA for soil and GR for treated and untreated soil is recommended based on static direct simple shear (SDSS) and cyclic direct simple shear (CDSS) tests. SDSS tests were performed to evaluate the monotonic performance of all mixtures. CDSS tests were performed to assess the long-term performance of these different mixes under repeated cyclic loading (50,000 load cycles) and varying cyclic shear stress amplitude. It is shown that PFA helps reduce the settlement and enhance soil shear strength, while GR increases the damping ratio of the soil. The optimum dosage of PFA is recommended 10%. The optimum GR content for untreated and PFA-treated soil is recommended 5 and 10%, respectively.
Fatahi, B 2024, 'Uncertainty, modeling, and decision making in geotechnics Uncertainty, modeling, and decision making in geotechnics , edited by Kok-Kwang Phoon, Takayuki Shuku, and Jianye Ching, Boca Raton, CRC Press, 2024, 502 pp., ISBN: 978-1-032-36749-1 (hbk), ISBN: 978-1-032-36750-7 (pbk), ISBN: 978-1-003-33358-6 (ebk), $315 hardback, doi:10.1201/9781003333586', Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, vol. 18, no. 1, pp. 314-316.
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Habaraduwa Peellage, W, Fatahi, B & Rasekh, H 2024, 'Stiffness and damping characteristics of jointed rocks under cyclic triaxial loading subjected to prolonged cyclic loading', International Journal of Fatigue, vol. 181, pp. 108121-108121.
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Haddad, H, Fatahi, B, Khabbaz, H, Hsi, J & Li, I 2024, 'Effects of stress history on compressibility characteristics of undisturbed landfill waste material', Construction and Building Materials, vol. 422, pp. 135725-135725.
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Halder, A, Shivakumara, P, Pal, U, Blumenstein, M & Ghosal, P 2024, 'A Locally Weighted Linear Regression-Based Approach for Arbitrary Moving Shaky and Nonshaky Video Classification', International Journal of Pattern Recognition and Artificial Intelligence, vol. 38, no. 01.
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Classification and identification of objects are complex and challenging in pattern recognition and artificial intelligence if a shaky and nonshaky camera captures the videos at different distances during the day and nighttime. This work presents a model for classifying a given video as a static, uniform, or arbitrarily moving videos so that the complexity of the problem can be reduced. To avoid the threat of different distances between the objects and the camera, the proposed work introduces new steps for estimating the depth of the objects in the video frames. We explore locally weighted linear regression for feature extraction from depth information based on the notion that the regression line fits almost all the points for uniformity and does not fit for arbitrary moving. The extracted features are fed to a random forest classifier to classify static, uniform, or arbitrary moving video. The results on a large dataset, which includes videos captured day and night, show that the proposed method successfully classifies static, uniform and arbitrary videos with 0.86, 1.00 and 0.67 F-measures, respectively. Overall, our method obtains 87% accuracy for classification of static, uniform and arbitrary video, which is superior to the state-of-the-art methods.
Halkon, B, Perrin, R & Guo, Z 2024, 'Extensional and inextensional modes of axisymmetric structures', Experimental Techniques: a publication for the practicing engineer.
Hassani, S, Dackermann, U, Mousavi, M & Li, J 2024, 'A systematic review of data fusion techniques for optimized structural health monitoring', Information Fusion, vol. 103, pp. 102136-102136.
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Hassani, S, Dackermann, U, Mousavi, M & Li, J 2024, 'Enhanced damage detection for noisy input signals using improved reptile search algorithm and data analytics techniques', Computers & Structures, vol. 296, pp. 107293-107293.
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Hertrampf, T & Oberst, S 2024, 'Recurrence Rate spectrograms for the classification of nonlinear and noisy signals', Physica Scripta, vol. 99, no. 3, pp. 035223-035223.
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Abstract Time series analysis of real-world measurements is fundamental in natural sciences and engineering, and machine learning has been recently of great assistance especially for classification of signals and their understanding. Yet, the underlying system’s nonlinear response behaviour is often neglected. Recurrence Plot (RP) based Fourier-spectra constructed through τ-Recurrence Rate (RR τ ) have shown the potential to reveal nonlinear traits otherwise hidden from conventional data processing. We report a so far disregarded eligibility for signal classification of nonlinear time series by training RESnet-50 on spectrogram images, which allows recurrence-spectra to outcompete conventional Fourier analysis. To exemplify its functioning, we employ a simple nonlinear physical flow of a continuous stirred tank reactor, able to exhibit exothermic, first order, irreversible, cubic autocatalytic chemical reactions, and a plethora of fast-slow dynamics. For dynamics with noise being ten times stronger than the signal, the classification accuracy was up to ≈ 75% compared to ≈ 17% for the periodogram. We show that an increase in entropy only detected by the RR τ allows differentiation. This shows that RP power spectra, combined with off-the-shelf machine learning techniques, have the potential to significantly improve the detection of nonlinear and noise contaminated signals.
Huang, Z, Su, Q, Huang, J, He, X, Pei, Y & Yang, C 2024, 'Field assessment of a subgrade-culvert transition zone constructed with foamed concrete in the ballasted railway', International Journal of Rail Transportation, vol. 12, no. 3, pp. 391-413.
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Hwang, Y-S, Um, J-S, Pradhan, B, Choudhury, T & Schlueter, S 2024, 'How does ChatGPT evaluate the value of spatial information in the 4th industrial revolution?', Spatial Information Research, vol. 32, no. 2, pp. 187-194.
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AbstractChat Generative Pre-trained Transformer (ChatGPT), developed by OpenAI, is a prominent AI model capable of understanding and generating human-like text based on input. Since terms and concepts of spatial information are contextual, the applications of ChatGPT on spatial information disciplines can be biased by the perceptions and perspectives of ChatGPT towards spatial information. Therefore, a thorough understanding of the real magnitude and level of comprehension of spatial information by ChatGPT is essential before exploring its potential applications in spatial information disciplines. This article aims to investigate how ChatGPT evaluates spatial information and its potential contributions to 4th Industrial Revolution (Industry 4.0). ChatGPT has summarized a notable perspective on evaluating and utilizing spatial information in the context of the Industry 4.0. The result of this study shows that ChatGPT has a good understanding on contextual concepts related to spatial information. However, it exhibits potential biases and challenges, as its responses lean towards the technological and analytical aspects. The results provide a crucial understanding on how to leverage ChatGPT’s benefits to the fullest while recognizing its constraints, with the aim to enhance the efficacy from the perspective of applications linked to spatial information.
Indraratna, B, Arachchige, CMK, Rujikiatkamjorn, C, Heitor, A & Qi, Y 2024, 'Utilization of Granular Wastes in Transportation Infrastructure', Geotechnical Testing Journal, vol. 47, no. 1, pp. 20220233-20220233.
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Abstract Attributed to environmental preservation in urban infrastructure development, the recycling of waste materials produced in the coal and steel industry as well as the reusing of waste tires is a high priority in Australia. In this article, the practical applications of (i) coal wash (CW) and steel furnace slag mixtures, (ii) CW and fly ash mixtures, and (iii) rubber elements derived from recycled tires are discussed. In this regard, some examples of real-life applications are elucidated in relation to coastal reclamation as well as road and rail construction (e.g., Port Kembla, Kangaroo Valley highway, and Chullora Rail Precinct). The article outlines various aspects of site investigation, construction techniques, and the installation of instrumentation to evaluate the field performance of these waste materials in contrast to traditional (natural) quarried materials. The results from these case studies demonstrate that properly engineered granular waste mixtures can exhibit promising characteristics even to exceed the current technical standards, implying reduced intensity of maintenance. The research outcomes strongly support sustainable solutions to be embraced in the future development of transportation infrastructure, capable of withstanding increased freight loading and enhanced longevity.
Indraratna, B, Atapattu, S, Rujikiatkamjorn, C, Arivalagan, J & Jing, N 2024, 'Soft Soil Improvement by Geosynthetics for Enhanced Performance of Transport Infrastructure', Geotechnical Engineering Journal of the SEAGS & AGSSEA, vol. 55, no. 1.
Indraratna, B, Malisetty, RS, Nair, L & Rujikiatkamjorn, C 2024, 'Instrumentation and Data Interpretation in Transportation Geotechnics', Indian Geotechnical Journal, vol. 54, no. 1, pp. 40-62.
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AbstractTransportation networks on the eastern coast of Australia are often built on or traverse coastal flood plains and marine clays with unfavourable soil conditions. In the past two decades, a significant number of laboratory investigations were carried out in soft soil improvement using Prefabricated Vertical Drains (PVDs) combined with vacuum-assisted surcharge preloading. In addition, significant research efforts were made to reduce the maintenance costs of railway tracks and increase their longevity by using synthetic inclusions such as geocomposites, geogrids and shock mats. These research outcomes were implemented and validated in practice through several field investigations along the eastern coast of Australia. This paper demonstrates the significance of instrumentation and data interpretation in geotechnical field investigations through 6 case histories. Field trials including Port of Brisbane Land Reclamation, Ballina Bypass Upgrade and Sandgate Rail Separation Projects were presented highlighting innovative ways of monitoring the performance of PVDs with vacuum and non-vacuum surcharge preloading. Also, railway track design improvements using geosynthetic and shock mats were discussed through Bulli and Singleton trial track case studies. Further, the heavy haul track testing facility at Russell Vale, New South Wales, was discussed as an alternative for expensive and time-consuming field trials.
Jiang, Y, Ke, Y, Yang, F, Ji, J & Peng, W 2024, 'State of Health Estimation for Second-Life Lithium-Ion Batteries in Energy Storage System With Partial Charging-Discharging Workloads', IEEE Transactions on Industrial Electronics, pp. 1-11.
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Kumar, A, Singh, UK & Pradhan, B 2024, 'Enhancing subsurface contamination assessment via ensemble prediction of ground electrical property: A Colorado AMD-impacted wetland case study', Journal of Environmental Management, vol. 351, pp. 119943-119943.
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Li, S, Ji, JC, Xu, Y, Feng, K, Zhang, K, Feng, J, Beer, M, Ni, Q & Wang, Y 2024, 'Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults', Mechanical Systems and Signal Processing, vol. 210, pp. 111142-111142.
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Liu, G-Y, Li, J-P, Indraratna, B & Zhou, P 2024, 'A hydraulic-mechanical (HM) coupling constitutive model for unsaturated soil-continuum interfaces considering bonding effect', Computers and Geotechnics, vol. 166, pp. 105989-105989.
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Malisetty, RS & Indraratna, B 2024, 'Critical speed of ballasted railway tracks: Influence of ballast and subgrade degradation', Transportation Geotechnics, vol. 46, pp. 101246-101246.
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Mohammadi, M, Oberst, S & Halkon, BJ 2024, 'Application of Time Synchronous Averaging in Mitigating UAV Noise and Signal Loss for Continuous Scanning Laser Doppler Vibrometry', Journal of Physics: Conference Series, vol. 2698, no. 1, pp. 012005-012005.
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Abstract The laser Doppler vibrometer (LDV) has been shown to be effective for a wide application of vibration assessments that are well accepted. One of the new avenues for exploring alternative measurement scenarios, mounting LDVs on unmanned aerial vehicles (UAVs) is emerging as a potential avenue for remote and harsh environment measurements. Such configurations grapple with the challenge of the LDV sensor head being sensitive to UAV vibration during flight and signal loss due to tracking error. This study investigates the effectiveness of several Time Synchronous Averaging (TSA) techniques to circumvent these obstacles. Through comprehensive evaluations, all three TSA techniques under investigation demonstrated significant potential in suppressing UAV-induced noise and minimising the effects of signal dropout. Traditional TSA showcased a remarkable sixfold enhancement in signal quality when analysed via the mean square error. However, the study also highlighted that while TSA and Multi-Cycle Time Synchronous Average (MCTSA) elevated signal clarity, there is a trade-off between noise suppression and signal duration. Additionally, the findings emphasise the importance of synchronisation between scanning and target vibration. To achieve optimal results in Continuous Scanning Laser Doppler Vibrometer measurements, there is a need for advanced algorithms capable of estimating target vibration and synchronising scanning in real-time. As the study was rooted in steady-state vibrations, future research should explore transient vibration scenarios, thereby broadening the application scope of TSA techniques in UAV-mounted LDV systems.
Nandanwar, L, Shivakumara, P, Jalab, HA, Ibrahim, RW, Raghavendra, R, Pal, U, Lu, T & Blumenstein, M 2024, 'A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection', IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 4, pp. 5407-5420.
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Ni, Q, Ji, JC, Feng, K, Zhang, Y, Lin, D & Zheng, J 2024, 'Data-driven bearing health management using a novel multi-scale fused feature and gated recurrent unit', Reliability Engineering & System Safety, vol. 242, pp. 109753-109753.
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Nikkhah, N, Keshavarz, R, Abolhasan, M, Lipman, J & Shariati, N 2024, 'Highly Sensitive Differential Microwave Sensor Using Enhanced Spiral Resonators for Precision Permittivity Measurement', IEEE Sensors Journal, vol. 24, no. 9, pp. 14177-14188.
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Nimbalkar, S & Basack, S 2024, 'Pile group in clay subjected to cyclic lateral load: Numerical modelling and design recommendation', Marine Georesources & Geotechnology, vol. 42, no. 1, pp. 67-87.
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Niu, G, He, X, Xu, H & Dai, S 2024, 'Tunnelling-induced ground surface settlement: A comprehensive review with particular attention to artificial intelligence technologies', Natural Hazards Research, vol. 4, no. 1, pp. 148-168.
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Oberst, S & Martin, R 2024, 'Feature-preserving synthesis of termite-mimetic spinodal nest morphology', iScience, vol. 27, no. 1, pp. 108674-108674.
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Peng, R, Guo, R, Liu, L, Ji, J, Miao, Z & Zhou, J 2024, 'Practical consensus tracking control for networked Euler–Lagrange systems based on UDE integrated with RBF neural network', Neurocomputing, vol. 583, pp. 127554-127554.
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Perrin, R & Halkon, B 2024, 'Sacred Geometry in the English Church Bell', IMA Journal of Applied Mathematics.
Puthal, D, Yeun, CY, Damiani, E, Mishra, AK, Yelamarthi, K & Pradhan, B 2024, 'Blockchain Data Structures and Integrated Adaptive Learning: Features and Futures', IEEE Consumer Electronics Magazine, vol. 13, no. 2, pp. 72-80.
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Qi, Y, Indraratna, B, Ngo, T, Arachchige, CMK & Hettiyahandi, S 2024, 'Sustainable solutions for railway using recycled rubber', Transportation Geotechnics, vol. 46, pp. 101256-101256.
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Rao, P, Feng, W, Ouyang, P, Cui, J, Nimbalkar, S & Chen, Q 2024, 'Formation of plasma channel under high-voltage electric pulse and simulation of rock-breaking process', Physica Scripta, vol. 99, no. 1, pp. 015604-015604.
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Abstract In the context of rock fragmentation, the application of high voltage electric pulses results in the transfer of electrical energy onto the surface of the rock material, leading to a rapid electrical breakdown and the formation of a plasma channel. The ionized plasma expands at a fast velocity, generating a shock wave that causes significant damage to the rock’s integrity. In this study, we develope a numerical model that couples electrical, thermal, and mechanical forces to simulate the formation of plasma channels within rocks due to high-voltage electric pulses. The model’s accuracy is verified through field tests, and the results indicate that the configuration of the high-voltage pulse waveform, electrode spacing, and conductor particles within the rock impact the pathway of plasma channel formation. Prior to the formation of the plasma channel, minimal changes are observed in temperature and stress levels, with the majority of electric pulse energy dedicated to the creation of the plasma channel. Following the establishment of the plasma channel, the application of the electric pulse continues, resulting in notable alterations in temperature and stress levels. When the duration of the action reaches 105 ns, the temperature and stress levels surpass 104 K and 50 MPa, respectively, leading to fracture and extensive damage to the rock. The outcomes derived from the numerical model’s calculations can help to facilitate the cross-integration between physics and civil engineering and contribute to a deeper understanding of the rock fragmentation process under high voltage electric pulses.
Rao, P, Meng, J, Cui, J & Nimbalkar, S 2024, 'Field Study on Rectangular Inclined Deep Foundation Excavation in Soft Soils', Geotechnical and Geological Engineering, vol. 42, no. 3, pp. 2151-2168.
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Raza, MA, Abolhasan, M, Lipman, J, Shariati, N, Ni, W & Jamalipour, A 2024, 'Multi-Agent Multi-Armed Bandit Learning for Grant-Free Access in Ultra-Dense IoT Networks', IEEE Transactions on Cognitive Communications and Networking, pp. 1-1.
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Ren, Z, Ji, J, Zhu, Y & Feng, K 2024, 'An Investigation Into the Behavior of Intelligent Fault Diagnostic Models Under Imbalanced Data', IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-20.
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Senanayake, S, Pradhan, B, Wedathanthirige, H, Alamri, A & Park, H-J 2024, 'Monitoring soil erosion in support of achieving SDGs: A special focus on rainfall variation and farming systems vulnerability', CATENA, vol. 234, pp. 107537-107537.
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Shivakumara, P, Banerjee, A, Nandanwar, L, Pal, U, Antonacopoulos, A, Lu, T & Blumenstein, M 2024, 'A new deep CNN for 3D text localization in the wild through shadow removal', Computer Vision and Image Understanding, vol. 238, pp. 103863-103863.
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Singh, RB, Patra, KC, Pradhan, B & Samantra, A 2024, 'HDTO-DeepAR: A novel hybrid approach to forecast surface water quality indicators', Journal of Environmental Management, vol. 352, pp. 120091-120091.
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Singha, C, Sahoo, S, Govind, A, Pradhan, B, Alrawashdeh, S, Hamdi Aljohani, T, Almohamad, H, Md Towfiqul Islam, AR & Abdo, HG 2024, 'Impacts of hydroclimate change on climate-resilient agriculture at the river basin management', Journal of Water and Climate Change, vol. 15, no. 1, pp. 209-232.
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Abstract This paper focuses on exploring the potential of Climate resilient agriculture (CRA) for river basin-scale management. Our analysis is based on long-term historical and future climate and hydrological datasets within a GIS environment, focusing on the Ajoy River basin in West Bengal, Eastern India. The standardized anomaly index (SAI) and slope of the linear regression (SLR) methods were employed to analyse the spatial pattern of the climate variables (precipitation, Tmax and Tmin) and hydrological variables (actual evapotranspiration (AET), runoff (Q), vapor pressure deficit (VPD), potential evapotranspiration (PET), and climate water deficit (DEF)) using the TerraClimate dataset spanning from 1958 to 2020. Future climate trend analysis spanning 2021 to 2050 was conducted using the CMIP6 based GCMs (MIROC6 and EC-Earth3) dataset under shared socio-economic pathway (SSP2-4.5, SSP5-8.5 and historical). For spatiotemporal water storage analysis, we relied on Gravity Recovery and Climate Experiment (GRACE) from the Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL) data, covering the period from 2002 to 2021. Validation was performed using regional groundwater level data, employing various machine learning classification models. Our findings revealed a negative precipitation trend (approximately −0.04 mm/year) in the southern part, whereas the northern part exhibited a positive trend (approximately 0.10 mm/year).
Stone, B, Mitchell, S, Halkon, B, Peirce, N & Harland, A 2024, 'The Dynamic Properties of Cricket and Cricket Training Balls', Sports Engineering (SPEN).
Swain, S, Mishra, PK, Nandi, S, Pradhan, B, Sahoo, S & Al-Ansari, N 2024, 'A simplistic approach for monitoring meteorological drought over arid regions: a case study of Rajasthan, India', Applied Water Science, vol. 14, no. 2.
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AbstractThe commonly used precipitation-based drought indices typically rely on probability distribution functions that can be suitable when the data exhibit minimal discrepancies. However, in arid and semi-arid regions, the precipitation data often display significant discrepancies due to highly irregular rainfall patterns. Consequently, imposing any probability distributions on the data for drought analysis in such regions may not be effective. To address this issue, this study employs a novel drought index called the Discrepancy Precipitation Index (DPI), specifically designed for arid regions. Unlike traditional methods, the DPI does not impose a probability distribution on the precipitation data; instead, it relies on the discrepancy between the data and the mean value. Drought severity classifications (i.e., Drought-I, Drought-II, and Drought-III) are proposed based on the DPI values. The DPI is used to characterize and assess the meteorological drought years based on annual and monsoonal precipitation over nineteen districts in Western Rajasthan, India, during 1901–2019. Additionally, a novel statistic called Discrepancy Measure (DM) is employed to assess the degree of discrepancy in the precipitation climatology of the districts for annual and monsoon precipitation time series. Based on annual precipitation, Jaisalmer district exhibited the highest number of historical drought years (35), whereas three districts, i.e., Jhunjhunu, Dausa, and Bhilwara exhibited the lowest number of drought years (11). Similarly, based on monsoon precipitation, Jaisalmer and Bhilwara encountered the highest (34) and the lowest (11) number of drought years, respectively. The return period of Drought-II is lower for monsoon precipitation-based DPI as compared to that of the annual precipitation-based DPI for all the districts. The DM and DPI-based total number of droughts are found to be strongly correlated for both annual and monsoon...
Wan, Z, Liu, X, Wang, B, Qiu, J, Li, B, Guo, T, Chen, G & Wang, Y 2024, 'Spatio-temporal Contrastive Learning-enhanced GNNs for Session-based Recommendation', ACM Transactions on Information Systems, vol. 42, no. 2, pp. 1-26.
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Session-based recommendation (SBR) systems aim to utilize the user’s short-term behavior sequence to predict the next item without the detailed user profile. Most recent works try to model the user preference by treating the sessions as between-item transition graphs and utilize various graph neural networks (GNNs) to encode the representations of pair-wise relations among items and their neighbors. Some of the existing GNN-based models mainly focus on aggregating information from the view of spatial graph structure, which ignores the temporal relations within neighbors of an item during message passing and the information loss results in a sub-optimal problem. Other works embrace this challenge by incorporating additional temporal information but lack sufficient interaction between the spatial and temporal patterns. To address this issue, inspired by the uniformity and alignment properties of contrastive learning techniques, we propose a novel framework called Session-based Recommendation with Spatio-temporal Contrastive Learning-enhanced GNNs (RESTC). The idea is to supplement the GNN-based main supervised recommendation task with the temporal representation via an auxiliary cross-view contrastive learning mechanism. Furthermore, a novel global collaborative filtering graph embedding is leveraged to enhance the spatial view in the main task. Extensive experiments demonstrate the significant performance of RESTC compared with the state-of-the-art baselines. We release our source code at https://github.com/SUSTechBruce/RESTC-Source-code .
Wang, C, Ji, J, Miao, Z & Zhou, J 2024, 'Formation tracking of multi-robot systems with switching directed topologies based on Udwadia-Kalaba approach', Applied Mathematical Modelling, vol. 126, pp. 147-158.
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Wu, Z, Rao, P, Cui, J, Chen, Q & Nimbalkar, S 2024, 'Lateral Response Evaluation of Existing Pile by Adjacent Pile Driving in Claye Slope', Geotechnical and Geological Engineering, vol. 42, no. 2, pp. 1313-1337.
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Xiao, T, Halkon, B, Wang, S, Oberst, S & Qiu, X 2024, 'Refracto-vibrometry for active control of sound radiation through an opening', Journal of Sound and Vibration, vol. 577, pp. 118242-118242.
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Yu, J, Wu, M, Ji, J & Yang, W 2024, 'Neural Network-Based Region Tracking Control for a Flexible-Joint Robot Manipulator', Journal of Computational and Nonlinear Dynamics, vol. 19, no. 2.
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Abstract The present paper proposes a neural network-based adaptive region-tracking control strategy for a flexible-joint robot manipulator subjected to region constraints. The developed neural network-based control strategy can globally stabilize the robot manipulator and cope with model uncertainties and the external unknown bounded disturbances. Different from the existing literature, by using the sliding mode technology and the singular perturbation theory, the developed control strategy does not require the high-order derivatives of the link states such as jerk and acceleration since the high-order derivative information is not always available in practical applications. By using Lyapunov stability theory, it is proved that the proposed neural network-based control strategy can guarantee that all the parameter variables in the closed-loop system are bounded, and the flexible-joint robot manipulator with unknown dynamics can reach inside the dynamic region and also maintain the velocity matching with the desired moving region. Since the assumption of linearization of the unknown dynamic parameters is removed, the proposed control strategy does not require the calculation of the complex regression matrix. Therefore, the proposed method has great robustness and the ability of model generalization. Simulations are given to demonstrate the validity of the proposed control strategy.
Yu, J, Wu, M, Yang, W & Ji, J 2024, 'A system decomposition method for region tracking control of a non‐holonomic mobile robot with dynamic parameter uncertainties', Asian Journal of Control, vol. 26, no. 3, pp. 1459-1471.
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AbstractThe tracking control problem of non‐holonomic mobile robot systems has been extensively investigated in the past decades, however, most of the existing control strategies were developed specifically for the fixed‐point tracking. This technical note focuses on the region tracking control for a non‐holonomic mobile robot system with parameter uncertainties in the robot dynamics. With the system decomposition and adaptive control method, some restrictions imposed on the angular and linear velocities of the non‐holonomic mobile robot in recent literature are removed, enabling to track dynamic trajectories with any values of the angular and line velocities. The proposed adaptive control scheme can simultaneously solve both the regulation and region tracking problems of a non‐holonomic mobile robot with one passive wheel and two actuated wheels. By utilizing the designed control laws, the mobile robot system is able to globally reach inside a moving region specified by potential functions whose path can be a circular curve, a straight line, or sinusoidal curve, by using a single adaptive controller. Since the dynamic region can be specified arbitrarily small, the fixed‐point tracking can be regarded as a special case of region tracking studied in this paper. Compared with the traditional fixed‐point tracking, region tracking has more flexibility and better robustness. Numerical results are presented to show the effectiveness of the designed strategy.
Yu, L, Wang, Y & Pradhan, B 2024, 'Enhancing landslide susceptibility mapping incorporating landslide typology via stacking ensemble machine learning in Three Gorges Reservoir, China', Geoscience Frontiers, vol. 15, no. 4, pp. 101802-101802.
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Zhang, X, Peng, H, Tang, T, Liu, Y, Wang, Y & Zhang, J 2024, 'Knowledge-based Dual External Attention Network for peptide detectability prediction', Knowledge-Based Systems, vol. 286, pp. 111378-111378.
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Zhao, F, Ji, JC, Cao, S, Ye, K & Luo, Q 2024, 'QZS isolators with multi-pairs of oblique bars for isolating ultralow frequency vibrations', Nonlinear Dynamics, vol. 112, no. 3, pp. 1815-1842.
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Zheng, B, Ji, J, Peng, R, Miao, Z & Zhou, J 2024, 'Energy shaping-based consensus control in networked underactuated Euler–Lagrange systems with communication and input delays', Journal of the Franklin Institute, vol. 361, no. 6, pp. 106705-106705.
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Zhou, I, Tofigh, F, Piccardi, M, Abolhasan, M, Franklin, D & Lipman, J 2024, 'Secure Multi-Party Computation for Machine Learning: A Survey', IEEE Access, vol. 12, pp. 53881-53899.
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Zhou, S, Halkon, B, Guo, Z & Eager, D 2024, 'Transient waveform replication for flexible structures in shaker testing using time-domain convolution techniques'.
Zhu, Y, Zhang, Z & Ji, J 2024, 'Bifurcations of a Filippov ecological system with an A-type discontinuity boundary', Chaos, Solitons & Fractals, vol. 182, pp. 114834-114834.
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