Article
Multidisciplinary Sciences
J. Selva, S. Lorito, M. Volpe, F. Romano, R. Tonini, P. Perfetti, F. Bernardi, M. Taroni, A. Scala, A. Babeyko, F. Lovholt, S. J. Gibbons, J. Macias, M. J. Castro, J. M. Gonzalez-Vida, C. Sanchez-Linares, H. B. Bayraktar, R. Basili, F. E. Maesano, M. M. Tiberti, F. Mele, A. Piatanesi, A. Amato
Summary: Probabilistic tsunami forecasting (PTF) offers a method for tsunami early warning that factors in uncertainties, improving accuracy and enabling rational decision making. Developed and tested for near-source tsunami warning, PTF demonstrates accurate forecasting over a wide range of past earthquakes.
NATURE COMMUNICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Mohamed Noureldin, Tamer Abuhmed, Melike Saygi, Jinkoo Kim
Summary: A new probabilistic framework is proposed for distribution-free prediction interval (PI) of seismic responses in earthquake engineering. It overcomes the limitations of point prediction models and complexity of traditional probabilistic methods. The framework utilizes a few assumptions of probability distributions and requires no prior statistical distribution assumption for the PI.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Environmental Sciences
Roya Kolachian, Bahram Saghafian
Summary: Prediction of drought severity class/state using standardized hydrological drought index (SHDI) was conducted in this study. Results showed that considering drought classes as inputs/outputs leads to more accurate predictions, with SHDI3 prediction being more accurate than SHDI1 prediction. Rough set theory (RST) showed slightly better accuracy than support vector classification (SVC) and support vector regression (SVR) in forecasting.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Computer Science, Interdisciplinary Applications
Tanvir Ibna Kaisar, Kais Zaman, Mohammad T. Khasawneh
Summary: This paper proposes three algorithms that combine Support Vector Machine and Gaussian Process to efficiently classify large datasets and obtain probability information on the classification results. Experimental results demonstrate that these algorithms have good performance in terms of computational efficiency and accuracy.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Geochemistry & Geophysics
Ao Wang, Shanyou Li, Jianqi Lu, Haifeng Zhang, Borui Wang, Zhinan Xie
Summary: A continuous PGA prediction LSTM neural network model is proposed to measure ground motion strength and initiate emergency protocols in earthquake early warning systems. The model utilizes fault continuity rupture information to improve accuracy and resolves the underestimation problem of traditional P-wave peak displacement-dependent PGA prediction models for large earthquakes.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Operations Research & Management Science
M. A. Ganaie, M. Tanveer, Jatin Jangir
Summary: In this study, a novel universum twin support vector machine with pinball loss function (Pin-UTSVM) is proposed for the classification of EEG signals. The Pin-UTSVM model is more robust to noise compared to existing models and performs better in experimental results.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Engineering, Chemical
Junhua Zheng, Chao Wu, Qingqiang Sun, Zhihuan Song, Le Zhou
Summary: This study introduces a deep learning model SPDN for fault classification, utilizing sparse GRBM and LSTM for feature extraction and sequence modeling. Experimental results demonstrate that the proposed method outperforms traditional methods in data-driven process monitoring in terms of classification accuracy.
JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS
(2022)
Article
Computer Science, Artificial Intelligence
Ganesan Kalaiarasi, Sureshbabu Maheswari
Summary: In this study, an effective classification of hyperspectral images was modeled and simulated with the proximal support vector machine (PSVM) by integrating them with the deep learning approach. The new deep PSVM classifiers, designed to handle the complexity, discrepancies, and irregularities in traditional hyperspectral image classifiers, showed better classification accuracy compared to other techniques.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Shili Peng, Wenwu Wang, Yinli Chen, Xueling Zhong, Qinghua Hu
Summary: This article presents a new idea for addressing the challenge of unifying classification and regression in machine learning. It proposes converting the classification problem into a regression problem and using regression methods to solve key problems in classification. Experimental results demonstrate that the proposed method outperforms existing algorithms in terms of prediction accuracy and model uncertainty.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Review
Agriculture, Multidisciplinary
Zhi Hong Kok, Abdul Rashid Mohamed Shariff, Meftah Salem M. Alfatni, Siti Khairunniza-Bejo
Summary: The Support Vector Machine (SVM) shows excellent performance in precision agriculture (PA), with comparisons to other machine learning algorithms highlighting its strengths and weaknesses in model performance and characteristics.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Computer Science, Artificial Intelligence
Xin Yan, Hongmiao Zhu
Summary: This paper proposes a novel support vector machine model with feature mapping and kernel trick to handle datasets with different distributions. The model improves robustness by pre-selecting training points, and converts the problem into a convex quadratic programming problem solved efficiently by the sequential minimal optimization algorithm. Numerical tests demonstrate the superior performance of the proposed method compared to other classification methods.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Biochemical Research Methods
Chaolu Meng, Ying Ju, Hua Shi
Summary: This study used machine learning to explore the mechanism and important components of protein thermostability, and provided an accessible web server.
ANALYTICAL BIOCHEMISTRY
(2022)
Article
Geosciences, Multidisciplinary
Xiong Zhang, Miao Zhang, Xiao Tian
Summary: The article introduces a novel deep learning Earthquake Early Warning (EEW) system that can determine earthquake locations and magnitudes with high reliability as early as 4 seconds after the earliest P phase, utilizing continuous seismic waveform streams.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Meteorology & Atmospheric Sciences
Hua Bai, Bingxiang Wang, Bin Li, Zhangjun Liu, Zhenyu Wen, Yang Zhang, Feng Xiao, Xinfa Xu, Yongfeng Huang
Summary: A new algorithm was proposed to extract polygons of easily waterlogged urban areas in Jiangxi Province, China, and a predictive model for disaster risk level was built using multiple intelligent algorithms. The model showed high prediction accuracies, and the early-warning precipitation values identified differed from the government-issued ones.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Automation & Control Systems
Xinjiang Lu, Yunxu Bai
Summary: This article proposes a novel probabilistic LS-SVM method to enhance the modeling reliability of data contaminated by non-Gaussian noise. The effectiveness of the proposed method is demonstrated using both artificial and real cases.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Engineering, Civil
Yousef Abu-Zidan, Kate Nguyen, Priyan Mendis, Sujeeva Setunge, Hojjat Adeli
Summary: The study proposes a new design for a sanitising chamber to provide additional protection for healthcare workers against the virus. The design, aided by computer-aided design and advanced computational fluid dynamics simulation, aims to improve the uniform deposition of sanitising fluid and reduce discomfort caused by excessive moisture.
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT
(2021)
Article
Engineering, Biomedical
Golrokh Mirzaei, Hojjat Adeli
Summary: Currently, early identification of Alzheimer's disease remains a challenge in the medical field, with no specific biomarker known for accurate detection. AD is incurable with a high failure rate in clinical trials for drugs, but researchers are working towards finding methods for early detection.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Sajad Javadinasab Hormozabad, Mariantonieta Gutierrez Soto, Hojjat Adeli
Summary: Cities that adopt innovative and technology-driven solutions to improve efficiency are considered smart cities. Smart infrastructures aim to self-diagnose, self-power, self-adapt, and self-heal during normal and extreme conditions. Structural vibration control and structural health monitoring technologies are expected to play pivotal roles in the development of modern smart and resilient structures.
Article
Chemistry, Multidisciplinary
Alireza Joorabloo, Mohammad Taghi Khorasani, Hassan Adeli, Peiman Brouki Milan, Moein Amoupour
Summary: A study employed response surface methodology and artificial neural network to design hydrogel dressings including polyvinyl alcohol, chitosan, and starch. The addition of zinc-oxide nanoparticles and heparin improved the physical and mechanical properties, antibacterial activities, and wound healing ability of the hydrogel dressings.
JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY
(2022)
Article
Neurosciences
Bin Gu, Hojjat Adeli
Summary: This article presents recent developments in the study of sudden unexpected death in epilepsy (SUDEP), focusing on the pathophysiologic basis of SUDEP and the computational implications of machine learning techniques. The article discusses novel ideas for SUDEP prediction and rescue, including principal component analysis and closed-loop intervention.
REVIEWS IN THE NEUROSCIENCES
(2022)
Article
Engineering, Civil
Milad Hafezolghorani, Farzad Hejazi, Mohd Saleh Jaffar, Hojjat Adeli
Summary: This paper presents a new 3D analytical model for partially prestressed concrete (PPC) beam-column elements subjected to static and dynamic loads. The model includes plasticity theory and yielding surfaces to detect damage and determine the location of plastic hinges in the structural components. Experimental tests were conducted to verify the accuracy of the analytical model, and the results showed good agreement with numerical analysis. Additionally, a comparison of seismic response between reinforced concrete (RC) and PPC structures demonstrated the improved stiffness and energy dissipation capacity of the structure with PPC members, as well as a decrease in the number of plastic hinges.
Article
Biology
Milad Mousavi, Mahsa Dehghan Manshadi, Madjid Soltani, Farshad M. Kashkooli, Arman Rahmim, Amir Mosavi, Michal Kvasnica, Peter M. Atkinson, Levente Kovacs, Andras Koltay, Norbert Kiss, Hojjat Adeli
Summary: Accurate simulation of tumor growth during chemotherapy can optimize clinical trials and reduce the risk of unknown side effects. This study developed a 3D simulation model to evaluate the efficacy of different anti-angiogenic drugs and proposed comprehensive mechanisms for accurate predictions of drug treatments. The results showed that Beovu was the most effective drug, and machine learning techniques were used to extract additional features for understanding tumor growth and drug efficacy.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Amir H. Mosavi, Ardashir Mohammadzadeh, Sakthivel Rathinasamy, Chunwei Zhang, Uwe Reuter, Kovacs Levente, Hojjat Adeli
Summary: This study proposes a novel approach for glucose regulation in type-I diabetes patients. The approach considers uncertainties in glucose-insulin metabolism and utilizes the Immersion and Invariance (I&I) theorem to derive adaptation rules for unknown parameters. A deep learned type-II fuzzy logic system (T2FLS) is introduced to compensate for estimation errors and ensure stability. The effectiveness of the approach is demonstrated through simulations, which show that the suggested method can regulate glucose levels effectively in a short period of time.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Automation & Control Systems
Zhijun Li, Hojjat Adeli
Summary: This paper presents a new adaptive robust Hc control methodology for vibration control of large and complex structures, considering the uncertainties of both earthquake loads and structural parameters simultaneously. Through simulation experiments on benchmark buildings and shear wall buildings, the effectiveness and accuracy of the control method are demonstrated.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Engineering, Ocean
Hadi Pezeshki, Dimitrios Pavlou, Hojjat Adeli, Sudath C. Siriwardane
Summary: An analytical solution is developed to study the dynamic response of offshore wind turbines under wave load. The solution considers nonlinear Stokes's wave theory, wave-structure and soil-foundation interactions. The effect of various factors, including wave-structure interaction, added mass, foundation stiffness, and nacelle translational and rotational inertia, on the structure's motion is investigated. The proposed analytical solution is compared to numerical results through a parametric study.
JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING-TRANSACTIONS OF THE ASME
(2023)
Article
Engineering, Biomedical
Hidir Selcuk Nogay, Hojjat Adeli
Summary: This study proposes an automatic autism diagnostic model based on sMRI, which achieves outstanding diagnostic accuracy through preprocessing and optimization of neural networks.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Environmental
Mona Sadeghi, Mostafa Rahimnejad, Hassan Adeli, Farideh Feizi
Summary: Nanofibrous mats composed of ALG/PVA/CIP/ZO were fabricated and characterized. The mats showed uniform morphology, good exudate absorption ability, and pH-sensitive drug release. The addition of ZO nanoparticles increased antibacterial activity and improved physical and thermal stabilities. CIP in the mats enhanced antibacterial properties significantly.
JOURNAL OF POLYMERS AND THE ENVIRONMENT
(2023)
Article
Computer Science, Artificial Intelligence
Mohammad H. Rafiei, Lynne V. Gauthier, Hojjat Adeli, Daniel Takabi
Summary: This article introduces the application and advantages of self-supervised learning in EEG studies, and proposes future research directions and implementation tips.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Clinical Neurology
Hidir Selcuk Nogay, Hojjat Adeli
Summary: The study utilized deep learning and transfer learning methods to detect epileptic seizures using EEG signals, achieving 100% accuracy without requiring additional feature extraction steps. This automatic identification and classification model can aid in early diagnosis of epilepsy, providing effective early treatment opportunities.
EUROPEAN NEUROLOGY
(2021)
Article
Multidisciplinary Sciences
M. Murugappan, L. Murugesan, S. Jerritta, Hojjat Adeli
Summary: This study aims to predict SCA using the Rpeak to T-end (R-T-end) feature in ECG signals, extracting four nonlinear features and classifying them using three classifiers. The combination of sample entropy feature and support vector machine classifier can effectively predict the onset of SCA with the highest classification accuracy.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Geological
Shaohui Liu, Lizhong Jiang, Wangbao Zhou, Jian Yu
Summary: This study evaluates the post-earthquake damage to track-bridge systems by conducting nonlinear time history analysis on a CRTS II ballastless track simply-supported beam system subjected to transverse earthquake loading. It explores the characteristics of residual displacement and stiffness degradation of the track-bridge system under transverse earthquakes. The research investigates the effect of earthquake-induced stiffness degradation on high-speed trains and proposes a reconstruction method for earthquake-induced dynamic irregularity characteristic curve considering probability guarantee rates. The results indicate that earthquake-induced dynamic irregularity can effectively quantify the running performance of high-speed trains under earthquake-induced stiffness degradation conditions.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Rui Zhang, Xiangqian Sheng, Wenliang Fan
Summary: This study introduces a novel approach for the probabilistic assessment of seismic earth pressure against nonlinear backfills. Nonlinear upper bound analysis is used to obtain the seismic earth pressure through optimization procedure, and probability analysis of nonlinear backfill properties is considered by combining adaptive dimension decomposition with the direct integral method.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Qiangqiang Sun, Yu Xue, Menghao Hou
Summary: This study investigated the use of Tire-derived aggregate (TDA) as backfill material for geotechnical seismic isolation in utility tunnels. Nonlinear numerical analyses were conducted, and the results showed that TDA backfill was an excellent alternative for risk mitigation during strong earthquakes, significantly reducing deformation and forces. The proposed system could potentially save costs compared to expensive seismic mitigation measures.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Yan-Guo Zhou, Dong-Chao Zhang, Kai Liu, Yun-Min Chen
Summary: This study investigated the large deformations caused by liquefaction in sloping ground and the methods for evaluation and mitigation. Soil element tests and centrifuge model tests were conducted to study the relationship between residual strain and Post-liquefaction Deformation Potential (PLDP). The tests showed that the developments of residual strain were controlled by PLDP, which is correlated with the maximum cyclic shear strain. The applicability of PLDP was verified in model tests, and the mitigation mechanisms of densification and drainage induced by stone columns were observed.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Jiajin Zhao, Zhehao Zhu, Dexuan Zhang, Hao Wang, Xi Li
Summary: This paper studies the fabric properties during sand liquefaction using 3D constant-volume cyclic triaxial DEM tests. The results show good consistency with experimental data. The evolution of fabric characteristics is assessed using the coordination number and mechanical coordination number. The second-order contact normal fabric tensor is introduced to analyze complex inter-particle contacts and the shear strain is used as a bridge to describe the evolution of coordination number and anisotropy degree.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Jinqiang Li, Zilan Zhong, Shurui Wang, Kaiming Bi, Hong Hao
Summary: The corrosion-protection liner technology improves the seismic performance of water supply pipelines and reduces the failure probability under earthquake excitations.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Abdellah Cherif Taiba, Youcef Mahmoudi, Mostefa Belkhatir
Summary: This article provides a comprehensive analysis of Liu et al.'s (2023) published paper in the Soil Dynamics and Earthquake Engineering journal, which examines the impact of particle shape on the wave velocity of sand. By enhancing the content integrity, this article serves as a valuable discussion piece for readers interested in this research topic.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Weijian Zhong, Binbin Li, Yanhui Liu, Ping Tan, Fulin Zhou
Summary: In this paper, the Flexible Limit Protective Device (FLPD) was improved to a Flexible Energy Dissipating Device (FEDD) to better control the seismic response of base-isolated structures. Experimental investigation and numerical simulation were conducted to study the compression behavior and optimize the design of FEDDs. The results showed that FEDDs with optimal parameters effectively reduced isolator displacements and kept the inter-story drift angle within a safe range during earthquakes.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Xinhua Xue, Xiaojie Yuan, Li Tao
Summary: In this study, gene expression programming (GEP) was used to establish the relationship between the capacity energy required to trigger sand liquefaction and several major parameters. The GEP model showed higher accuracy and better performance compared to existing models, as confirmed by experimental data.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Xiao-ling Zhang, Hao Lan, Xian-hui Zhao, Cheng-shun Xu, Ke-min Jia
Summary: The study investigates the reinforcement principle of inclined liquefiable site using concrete pile and gravel pile methods. The results show that concrete piles have a better reinforcement effect on inclined liquefiable site compared to gravel piles, and increasing the diameter of gravel piles greatly improves the reinforcement effect. The pile group reinforcement model is more effective in reducing lateral displacement of the site soil compared to the single pile reinforcement model.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Jinxin Sun, Haoyu Sun, Mengmeng Lu, Bolin Han
Summary: The implementation of stone columns is an effective way to improve the stability of liquefiable soil. However, existing mathematical models often neglect vertical seepage within the soil, leading to calculation errors. This study proposes a new mathematical model that considers both radial and vertical seepage, and conducts a parameter analysis to investigate the effects of column spacing, cyclic stress ratio, and consolidation parameters on excess pore water pressure.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Jonathan F. Hubler, James P. Hanley, Andrew C. Stolte, Liam Wotherspoon, Kyle M. Rollins
Summary: This study performed blast liquefaction tests in an area that experienced extensive liquefaction. It used multi-channel analysis of surface waves (MASW) testing to evaluate changes in shear wave velocity (VS) before and after blasting. The study found that array length has an impact on the immediate changes in VS following blasting, but these changes decrease at 24 hours post-blast.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Lowell Tan Cabangon, Gaetano Elia, Mohamed Rouainia, Suraparb Keawsawasvong, Teraphan Ornthammarath
Summary: The impact of far-field earthquakes on underground structures, especially tunnels, has been relatively less explored compared to near-field earthquakes. However, the study found that far-field earthquakes can generate forces in tunnel lining that are equally destructive as those induced by near-field motions, especially when they contain long-period waves. The amplification of these ground motions in soft natural clays, common in Bangkok, can lead to significant soil displacements and shear strains.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Jinjun Hu, Longbing Ding, Xutong Zhou, Mingji Liu, Jingyang Tan
Summary: Offshore near-fault ground motions during the 2016 OffMie Mw6.0 earthquake in the Nankai Trough of Japan were studied using data from the DONET1 seafloor seismic network. The results show that offshore spectral acceleration and peak ground velocity are higher than onshore values. Analysis of pulse-like ground motions reveals differences in amplitude, frequency content, and energy between offshore and onshore motions. These findings have implications for seismic design of offshore engineering structures.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
Article
Engineering, Geological
Radu Popescu, Pradipta Chakrabortty
Summary: The natural spatial variability of soil properties affects the mechanical response of geotechnical structures and can deviate failure surfaces. For soil liquefaction induced by seismic activity, it has been found that greater excess pore water pressure is generated in soils with small-scale variability. This paper provides an explanation based on centrifuge experiments and numerical simulations, showing that partial drainage during earthquakes may trigger softening of dilative soils.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2024)
