Engineering Science and Technology-An International Journal-Jestech最新文献

{"title":"Graph-based EEG analysis for seizure prediction enhanced with Kolmogorov–Arnold Networks and Self-Supervised Learning","authors":"Safa Ben Atitallah ,&nbsp;Maha Driss ,&nbsp;Wadii Boulila ,&nbsp;Anis Koubaa","doi":"10.1016/j.jestch.2025.102245","DOIUrl":"10.1016/j.jestch.2025.102245","url":null,"abstract":"<div><div>Epilepsy is a common neurological disorder in which seizures pose major health problems, including sudden death. Despite advances in medicine, many patients do not react positively to treatments; therefore, early prediction of seizures is essential. However, precise detection remains challenging due to the complexity and variability of brain signals, as well as the scarcity of labeled clinical data to train conventional learning models. In this work, we propose SeizureNet-KAN, a novel fusion-based approach to predict seizures by transforming EEG data into graphs and integrating a custom-designed Kolmogorov–Arnold Network (KAN) layer into the Graph Convolutional Network (GCN). Furthermore, the proposed approach incorporates Self-Supervised Learning (SSL) to capture latent features from the EEG graph data effectively. To the best of our knowledge, this is the first time that the idea of KAN has been used in graph SSL. We demonstrated that the proposed SeizureNet-KAN model, implemented within an SSL framework, effectively enhances seizure prediction. Unlike traditional methods, our model captures complex non-linear EEG dynamics and reduces dependence on labeled data. The hybrid SSL pretraining strategy effectively extracts meaningful representations, improving generalization across patients. The experimental findings on the CHB-MIT dataset demonstrated that our proposed approach achieves excellent accuracy and resilience in seizure prediction, with a mean accuracy of 97.68%, precision of 97.72%, recall of 97.53%, F1-score of 97.59%, and AUC of 99.28%. These results highlight the potential of SSL-driven graph models for real-time seizure prediction in personalized healthcare applications.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102245"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State-of-the-art soft robotic systems for unstructured and real-world environments: A systematic review","authors":"Arameh Eyvazian ,&nbsp;Yooseob Song ,&nbsp;Chibukhchyan Hovhannes ,&nbsp;Ardeshir Savari ,&nbsp;Narinderjit Singh Sawaran Singh","doi":"10.1016/j.jestch.2025.102264","DOIUrl":"10.1016/j.jestch.2025.102264","url":null,"abstract":"<div><div>Soft robotics has emerged as a transformative paradigm in automation, offering unprecedented compliance, adaptability, and safety for operation in unstructured and dynamic environments. This study systematically reviews the latest advances in soft robotic systems, spanning novel material innovations, intelligent hybrid architectures, and cutting-edge actuation and control strategies. Key developments in integration with artificial intelligence, computer vision, and machine learning are highlighted, enabling enhanced perception, autonomy, and adaptive behavior. Application-driven case studies in healthcare, exploration, and search-and-rescue showcase the evolving capabilities of soft robots in challenging real-world settings. Persistent challenges, such as untethered operation, robust sensorimotor integration, scalable fabrication, and interpretable AI, are discussed alongside emerging multidisciplinary solutions. The review concludes by outlining future research directions, emphasizing the need for unified codesign approaches and collaboration across robotics, materials science, AI, and biology. This synthesis provides a roadmap for advancing next-generation soft robotic systems, aiming to bridge the gap between laboratory innovations and impactful deployment in complex, unpredictable environments, in support of industrial and innovation progress.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102264"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and implementation of PIλDμ controller for ROVs: Thruster modeling, controller parameter optimization, and FPGA realization","authors":"Hakan Ersoy,&nbsp;Berke Akgül,&nbsp;Emin Akpınar,&nbsp;Aslihan Kartci,&nbsp;Umut Engin Ayten","doi":"10.1016/j.jestch.2025.102261","DOIUrl":"10.1016/j.jestch.2025.102261","url":null,"abstract":"<div><div>Remotely operated and autonomous underwater vehicles (ROVs/AUVs) operate in a harsh environment dominated by nonlinear hydrodynamics, strong coupling, and wave–current disturbances. In most of the existing literature, surge-axis motion is still regulated by integer-order PID controllers that are tuned either heuristically or via single-scenario optimization. Such designs often exhibit limited robustness: their performance degrades significantly under severe noise, targeted wave excitation, or time-varying operational profiles. These limitations motivate the use of fractional-order control and more systematic tuning procedures. This paper investigates fractional-order <span><math><mrow><msup><mrow><mi>PI</mi></mrow><mrow><mi>λ</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>μ</mi></mrow></msup></mrow></math></span> (FOPID) controllers for surge control and compares two popular meta-heuristics, Particle Swarm Optimization (PSO) and Differential Evolution Algorithm (DEA), in comparison with classical PID. A fourth-order surge plant model is first obtained via system identification of experimental data from a BlueRobotics T200 thruster. Then, PSO and DEA are used to tune both PID and <span><math><mrow><msup><mrow><mi>PI</mi></mrow><mrow><mi>λ</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>μ</mi></mrow></msup></mrow></math></span> parameters over a multi-scenario cost function that combines step-response quality, disturbance rejection, and control effort. The resulting controllers are evaluated under four increasingly demanding tests: noiseless step tracking, severe white-noise excitation, sinusoidal “storm” disturbance, and a final scenario with time-varying set-points under the same storm condition. Across all 16 scalar performance metrics (IAE, ISE, and, ITAE over four tests), the DEA-tuned <span><math><mrow><msup><mrow><mi>PI</mi></mrow><mrow><mi>λ</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>μ</mi></mrow></msup></mrow></math></span> achieves the best value in 12 cases, consistently outperforming both PID designs and the PSO-based <span><math><mrow><msup><mrow><mi>PI</mi></mrow><mrow><mi>λ</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>μ</mi></mrow></msup></mrow></math></span>. In the most demanding final test (multi-level reference + storm), it reduces the integral time-weighted absolute error ITAE from 0.1065 (best PID) to 0.0893, i.e., by approximately 16%, while preserving competitive control effort. These results provide quantitative evidence that DEA-tuned <span><math><mrow><msup><mrow><mi>PI</mi></mrow><mrow><mi>λ</mi></mrow></msup><msup><mrow><mi>D</mi></mrow><mrow><mi>μ</mi></mrow></msup></mrow></math></span> offers a more robust and energy-aware solution for single-axis surge control in ROV/AUV applications.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102261"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constrained optimal formation control for nonlinear multi-agent systems using data-driven adaptive neural networks","authors":"Saleh Mobayen ,&nbsp;Mai The Vu ,&nbsp;Reza Rahmani ,&nbsp;Hamid Toshani ,&nbsp;Wudhichai Assawinchaichote ,&nbsp;Paweł Skruch","doi":"10.1016/j.jestch.2025.102269","DOIUrl":"10.1016/j.jestch.2025.102269","url":null,"abstract":"<div><div>This paper presents a constrained optimal adaptive control strategy for formation control in nonlinear multi-agent systems (MASs) using a data-driven approach. In contrast to traditional methods that require detailed system models, the proposed method employs Locally Linearized Dynamic Models (LLDMs), in which key parameters as Pseudo-Partial Derivatives (PPDs) are estimated adaptively from input–output data. This removes the need for explicit mathematical modeling and broadens the method’s applicability to uncertain systems. To address actuator limitations and reduce control effort, a performance criterion incorporating control constraints is defined, and the problem is reformulated as a Constrained Quadratic Program (CQP) with control increments as optimization variables. A Projection Recurrent Neural Network (PRNN) is developed to solve this CQP in real time, which ensures convergence of the numerical optimizer and guarantees closed-loop stability using Lyapunov analysis and singular value approach. The proposed algorithm achieves robust, model-free formation control, explicitly manages input constraints, and enables fast convergence. Simulation results show that this approach outperforms existing data-driven methods under uncertainty, which demonstrates its potential for applications in multi-agent system applications.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102269"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DGait: Robust gait recognition using dynamic ST-GCN with global aware attention","authors":"Md. Khaliluzzaman ,&nbsp;Kaushik Deb","doi":"10.1016/j.jestch.2025.102267","DOIUrl":"10.1016/j.jestch.2025.102267","url":null,"abstract":"<div><div>Gait recognition, a promising behavioral soft biometric technology, has a significant research area in security and computer vision. Nowadays, joint position-based approaches are of significant interest in gait recognition. ST-GCN, the spatio-temporal graph convolutional network, is employed on the joint stream to identify the gait feature from the spatial–temporal graph, prone to provide attention to dynamic information. Many methods utilize multi-scale operations to integrate long-range relationships among joints. However, these approaches fail to assign equal significance to all joints, leading to an incomplete perception of long-range joint connections. Furthermore, considering the joint stream solely may fail to extract the discriminative features produced by motion and bone structures. This paper presents a multi-stream dynamic spatio-temporal graph convolution (DSTGCN) approach with attention, denoted as DGait. It leverages bone and joint data from the spatial frames and joint-motion data from successive frames to early fusion of informative skeleton features. An improved HOP-extraction approach is introduced to provide equal importance to the relationship between further and closer joints while avoiding redundant dependencies. To address the limitations of ST-GCN, Global Aware Attention (GAA) is incorporated into the ST-GCN units, enhancing the capability for dynamically correlating the spatial–temporal joints. The suggested model exhibits remarkable accuracy on widely used CASIA-B, OUMVLP-Pose, and GREW datasets. The CASIA-B reveals an average accuracy of 96.94 %, 93.56 %, and 90.78 % for the normal walking, carrying-bag, and clothing conditions, respectively. The OUMVLP-Pose and GREW exhibit an average and rank-1 accuracy of 92.7 % and 72.6 %, respectively.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102267"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurocomputing capability evaluation of FHN model-based MSNN architectures with different window functions through the XOR problem","authors":"Ahmet Yasin Baran ,&nbsp;Obeid Abdalla ,&nbsp;İsmail Öztürk ,&nbsp;Nimet Korkmaz ,&nbsp;Recai Kiliç","doi":"10.1016/j.jestch.2025.102259","DOIUrl":"10.1016/j.jestch.2025.102259","url":null,"abstract":"<div><div>This study focuses on utilizing Memristive Spiking Neural Network (MSNN) structures based on the Fitzhugh-Nagumo (FHN) neuron model coupled with the Voltage ThrEshold Adaptive Memristor (VTEAM), and constrained by five different window functions, to solve the Exclusive OR (XOR) problem through both numerical simulations and real-time hardware implementations. Specifically, two input and two output neurons have been constructed as the 2 <span><math><mo>×</mo></math></span> 2 MSNN architectures, and the Joglekar, Biolek, Strukov, Prodromakis, and Blackman window functions define their memristor models. The optimal memductance values for synaptic connections in these five network configurations are set using the Spike-Timing-Dependent Plasticity (STDP) learning rule combined with the Winner-Takes-All (WTA) algorithm. The performance of these networks is evaluated based on their efficiency in solving the XOR problem. In this context, the XOR problem has been conducted as an image formed by a 2-pixel array. These pixels are transmitted as noisy signals from the MSNN input layer, where input neurons convert them into spike activities. These spike activities are then integrated through the memristive synapse layer and forwarded to the output layer as excitatory current signals, enabling the output layer to classify the input correctly. The simulation and Field-Programmable Gate Array (FPGA) hardware implementation results exhibit strong consistency. This work demonstrates, for the first time, the capacity of MSNNs to solve nonlinear problems by providing both simulation-based and hardware-based solutions to the XOR problem using various MSNN architectures with different window functions.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102259"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracking with attention: A review of transformer-based object tracking","authors":"Seyed Alireza Khoshnevis ,&nbsp;Abdollah Amirkhani","doi":"10.1016/j.jestch.2025.102263","DOIUrl":"10.1016/j.jestch.2025.102263","url":null,"abstract":"<div><div>Traditional object tracking methods are often based on convolutional neural networks and handcrafted feature extraction techniques where they have seen remarkable success. However, these methods still face limitations in capturing global dependencies and contextual relationships in complex scenarios. Transformers, which were initially introduced to the field of natural language processing, have transfigured vision tasks by leveraging the self-attention mechanisms and global feature modeling capabilities. One of the tasks that has been most affected by the use of transformers is the object tracking task. This review explores the transformative impact of attention-based architectures in object tracking, and provides a comprehensive analysis of the current frameworks and their core principles. The ability of the attention mechanism to capture local and global dependencies and to associate queries between frames, has helped transformer-based models to achieve state-of-the-art performance. The utilization of transformers in object tracking has drastically increased over the past few years, initiating the new “tracking-by-attention” paradigm. This work focuses on different applications of transformer architecture in both single and multi-object tracking where each task is divided further by methodology. End-to-end approaches and hybrid fusion models that leverage additional data for tracking are also discussed. The models that are discussed, are categorized by their main approaches and transformer usage, and challenges such as computational cost and scalability are outlined, along with future research opportunities informed by successful methods. By examining recent advancements, this review is intended to advance understanding of transformer-based tracking capabilities and to promote continued innovation in this rapidly evolving field.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102263"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing the FRA curves of transformer tertiary helical windings by deriving transfer functions from FRA data","authors":"Zhi Zhang","doi":"10.1016/j.jestch.2025.102268","DOIUrl":"10.1016/j.jestch.2025.102268","url":null,"abstract":"<div><div>Interpreting frequency response analysis (FRA) data presents a formidable challenge in transformer fault diagnosis. Previous attempts to derive transfer functions (TF) for characterizing FRA curves have been both desirable and unsuccessful. The collected FRA data aims to represent the mechanical conditions of the transformer windings under examination. Nonetheless, the techniques applied to FRA results for assessing mechanical integrity face inherent uncertainty due to the lack of a direct link between the measured data and the electrical characteristics of an equivalent circuit (EC) consisting of resistance, inductance, and capacitance (RLC) components. As such, a rigorous analysis of the FRA data becomes crucial for a comprehensive assessment and interpretation of the mechanical state of these windings. The proposed investigation into TF is designed to offer a detailed mathematical interpretation of FRA characteristics, potentially enabling the early detection of potential faults through the derived TF and relevant parameters. This research paper revolves around the computation of TFs for power transformer helical windings. Consequently, a strong correlation emerges between the recorded FRA curves and the computed TF curves, affirming the precision of TF estimation and its significant contribution to advance FRA technology.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102268"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive review of noise-cancellation antenna sensors in ultra-high frequency: techniques, challenges, and future directions","authors":"Zongxing Wei ,&nbsp;Mohamadariff Othman ,&nbsp;Tarik Abdul Latef ,&nbsp;Hazlee Azil Illias ,&nbsp;S. M. Kayser Azam ,&nbsp;Tengku Faiz Tengku Mohmed Noor Izam ,&nbsp;Muhammad Ubaid Ullah ,&nbsp;Mohamed Alkhatib ,&nbsp;Mousa I. Hussein","doi":"10.1016/j.jestch.2025.102271","DOIUrl":"10.1016/j.jestch.2025.102271","url":null,"abstract":"<div><div>This paper provides a comprehensive review of ultra-high frequency (UHF) noise-cancellation antenna (NCA) sensors. It identifies the critical challenges posed by noise interference in UHF bands and their impact on signal quality, particularly in partial discharge (PD) detection applications. The paper summarises the various types of noise present in the UHF range and highlights the importance of advanced design methods to enhance signal integrity. A significant contribution of this work is the detailed analysis of several noise-cancellation (NC) techniques, including the integrated feedline approach, embedded filter antenna technique, slot design modification, parasitic element incorporation, and shorting pin integration. These are systematically evaluated for their effectiveness in reducing interference. The review also provides a comparative analysis using tabular data, covering performance metrics such as NC implementation, radiation nulls (RN) frequency, bandwidth, gain, and other parameters. In addition, the paper identifies the most suitable techniques for PD detection and discusses their practical limitations. By highlighting potential directions for future research, this study offers valuable insights for advancing UHF antenna sensor design and its application in industrial PD monitoring systems.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102271"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)","authors":"","doi":"10.1016/S2215-0986(26)00009-1","DOIUrl":"10.1016/S2215-0986(26)00009-1","url":null,"abstract":"","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"73 ","pages":"Article 102283"},"PeriodicalIF":5.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}