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30th International Conference on Nuclear Engineering, ICONE 2023

作者： Hidaka, Shinjiro Shoji, Gaku Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Ibaraki Japan Division of Engineering Mechanics and Energy Institute of Systems and Information Engineering University of Tsukuba Ibaraki Japan

ISBN: (纸本)9784888982566

Clarifying the dynamic buckling behavior of PWR steel reactor containment vessels (PWR-CVs) subject to seismic excitation is critical for improving a numerical seismic design scheme for PWR-CVs. In evaluating the static elastic-plastic buckling strength for PWR-CVs by a finite element (FE) analysis, first we compute the moments and axial forces acting onto the multiple lumped mass beam model of a targeted PWR-CV from the linear dynamic analysis, second using the buckling evaluation formula on JEAG 4601 addenda-1984 we calculate the equivalent static load distributions in terms of shear and axial forces as input loads to the FE model. This static FE buckling analysis for a PWR-CV idealizes dynamic buckling phenomena as be static phenomena, so we cannot basically consider the effects of dynamic behavior on the buckling strength of a PWR-CV. To tackle more realistic buckling assessment of a PWR-CV, we carried out the linear dynamic analysis for a PWR-CV FE numerical model and discussed the features of the response considering the oval vibration modes. It was revealed that the response accompanying the oval vibration modes showed the lower value compared with that from the static FE buckling analysis. In contrast, in a previous study by Hidaka et al., 2022, it was discussed that the buckling load of static FE buckling analysis for a PWR-CV is higher than the buckling load of buckling evaluation formula on JEAG4601. As a result, the ratio of buckling load to response in the linear dynamic FE analysis was within 3% of that in the static FE buckling analysis. © 2023 by JSME.

关键词： Elastoplasticity

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GACL-Net:Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

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Computers, Materials & Continua 2025年第4期83卷 517-536页

作者： Chayut Bunterngchit Laith H.Baniata Mohammad H.Baniata Ashraf ALDabbas Mohannad A.Khair Thanaphon Chearanai Sangwoo Kang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Computing Gachon UniversitySeongnam13120Republic of Korea Computer Science Department Faculty of Information TechnologyThe World Islamic Sciences and Education UniversityAmman11947Jordan Intelligent Systems Department Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan IT Infrastructure Department Qatrana Cement CompanyAmman11821Jordan Division of Industrial and Logistics Engineering Technology Faculty of Engineering and TechnologyKing Mongkut’s University of Technology North BangkokRayong CampusRayong21120Thailand

Stroke is a leading cause of death and disability worldwide,significantly impairing motor and cognitive *** rehabilitation is often hindered by the heterogeneity of stroke lesions,variability in recovery patterns,and the complexity of electroencephalography(EEG)signals,which are often contaminated by *** classification of motor imagery(MI)tasks,involving the mental simulation of movements,is crucial for assessing rehabilitation strategies but is challenged by overlapping neural signatures and patient-specific *** address these challenges,this study introduces a graph-attentive convolutional long short-term memory(LSTM)network(GACL-Net),a novel hybrid deep learning model designed to improve MI classification accuracy and ***-Net incorporates multi-scale convolutional blocks for spatial feature extraction,attention fusion layers for adaptive feature prioritization,graph convolutional layers to model inter-channel dependencies,and bidi-rectional LSTM layers with attention to capture temporal *** on an open-source EEG dataset of 50 acute stroke patients performing left and right MI tasks,GACL-Net achieved 99.52%classification accuracy and 97.43%generalization accuracy under leave-one-subject-out cross-validation,outperforming existing state-of-the-art ***,its real-time processing capability,with prediction times of 33–56 ms on a T4 GPU,underscores its clinical potential for real-time neurofeedback and adaptive *** findings highlight the model’s potential for clinical applications in assessing rehabilitation effectiveness and optimizing therapy plans through precise MI classification.

关键词： Motor imagery EEG stroke rehabilitation deep learning brain-computer interface

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Effectiveness of Using Deep Learning for Blister Blight Identification in Sri Lankan Tea

Effectiveness of Using Deep Learning for Blister Blight Iden...

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2023 International Research Conference on Smart Computing and systems Engineering, SCSE 2023

作者： Hewawitharana, G.H.A.U. Nawarathne, U.M.L.A. Hassan, A.S.F. Wijerathna, Lochana M. Sinniah, G.D. Vidhanaarachchi, Samitha P. Wickramarathne, Jagath Wijekoon, Janaka L. Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Tea Research Institute of Sri Lanka Plant Pathology Division Talawakelle Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Military Technological College Systems Engineering Department Muscat Oman

ISBN: (纸本)9798350341454

Ceylon tea industry faces a major challenge in the form of pathogen-induced crop loss, with Blister Blight (BB) caused by Exobasidium vexans posing the greatest threat, leading to harvest losses of over 30%. This fungus attacks the tender tea shoots, resulting in a direct negative impact on the tea harvest. This paper presents a system to identify the suspicious tea leaves and BB disease at its early stages along with an assessment of severity, offering a potential solution to this critical issue. By utilizing real-time object detection, the system filters out non-tea leaves from the captured initial image of a segment of a tea plant. The identified tea leaves are then subjected to BB identification and severity assessment based on differing visual symptoms of the BB stages. This approach enables the system to accurately identify BB in the initial stage and severity stage, allowing for timely and targeted intervention to minimize crop losses. The YOLOv8 model has been able to correctly identify 98% of the objects it has detected as relevant (precision), and it has been able to correctly identify 96% of all the relevant objects present in the scene (recall). The Residual Network 50 (Resnet50) convolutional neural network (CNN) model was selected as the final model, achieving an accuracy of 89.90% during the training phase and an accuracy of 88.26% during the testing phase. © 2023 IEEE.

关键词： Convolutional neural networks

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on Robotics, Engineering, science, and technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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Secure-by-Construction Synthesis for Control systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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A hybrid machine learning approach for analysis of stegomalware

International Journal of Industrial Engineering and Operatio...

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International Journal of Industrial Engineering and Operations Management 2023年第2期5卷 104-117页

作者： Kadebu, Prudence Shoniwa, Robert T.R. Zvarevashe, Kudakwashe Mukwazvure, Addlight Mapanga, Innocent Thusabantu, Nyasha Fadzai Gotora, Tatenda Trust Department of Computer Engineering University of Zimbabwe Harare Zimbabwe Zimbabwe Information and Communication Technology Harare Zimbabwe Victoria Institute of Technology Adelaide Australia A Division of Zimbabwe Institution of Engineers Zimbabwe Information and Communication Technology Harare Zimbabwe Department of Academics Harare Institute of Technology Belvedere Zimbabwe Department of Computer Science Midlands State University Gweru Zimbabwe Department of Information Systems Women's University in Africa Harare Zimbabwe

Purpose: Given how smart today’s malware authors have become through employing highly sophisticated techniques, it is only logical that methods be developed to combat the most potent threats, particularly where the malware is stealthy and makes indicators of compromise (IOC) difficult to detect. After the analysis is completed, the output can be employed to detect and then counteract the attack. The goal of this work is to propose a machine learning approach to improve malware detection by combining the strengths of both supervised and unsupervised machine learning techniques. This study is essential as malware has certainly become ubiquitous as cyber-criminals use it to attack systems in cyberspace. Malware analysis is required to reveal hidden IOC, to comprehend the attacker’s goal and the severity of the damage and to find vulnerabilities within the system. Design/methodology/approach: This research proposes a hybrid approach for dynamic and static malware analysis that combines unsupervised and supervised machine learning algorithms and goes on to show how Malware exploiting steganography can be exposed. Findings: The tactics used by malware developers to circumvent detection are becoming more advanced with steganography becoming a popular technique applied in obfuscation to evade mechanisms for detection. Malware analysis continues to call for continuous improvement of existing techniques. State-of-the-art approaches applying machine learning have become increasingly popular with highly promising results. Originality/value: Cyber security researchers globally are grappling with devising innovative strategies to identify and defend against the threat of extremely sophisticated malware attacks on key infrastructure containing sensitive data. The process of detecting the presence of malware requires expertise in malware analysis. Applying intelligent methods to this process can aid practitioners in identifying malware’s behaviour and features. This is especially e

关键词： Machine learning Malware analysis Malware detection Steganography Stegomalware

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On Approximate Opacity of Stochastic Control systems

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IEEE Transactions on Automatic Control 2024年第6期70卷 3846-3861页

作者： Liu, Siyuan Yin, Xiang Dimarogonas, Dimos V. Zamani, Majid Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Shanghai Jiao Tong University and Key Lab of System Control & Information Processing Ministry of Education Department of Automation Shanghai China University of Colorado Boulder Computer Science Department CO80309 United States Ludwig Maximilian University of Munich Computer Science Department Germany

This paper investigates an important class of information-flow security property called opacity for stochastic control systems. Opacity captures whether a system's secret behavior (a subset of the system's behavior that is considered to be critical) can be kept from outside observers. Existing works on opacity for control systems only provide a binary characterization of the system's security level by determining whether the system is opaque or not. In this work, we introduce a quantifiable measure of opacity that considers the likelihood of satisfying opacity for stochastic control systems modeled as general Markov decision processes (gMDPs). We also propose verification methods tailored to the new notions of opacity for finite gMDPs by using value iteration techniques. Then, a new notion called approximate opacity-preserving stochastic simulation relation is proposed, which captures the distance between two systems' behaviors in terms of preserving opacity. Based on this new system relation, we show that one can verify opacity for stochastic control systems using their abstractions (modeled as finite gMDPs). We also discuss how to construct such abstractions for a class of gMDPs under certain stability conditions. © 1963-2012 IEEE.

关键词： Stochastic control systems

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Microwave Tomography Based on Time of Flight of Signals from Scattering

Microwave Tomography Based on Time of Flight of Signals from...

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IEEE MTT-S International Microwave Bio Conference ((IMBIOC)

作者： Cheng-Chung Lin Ai-Jung Lee Wei-Chen Chiu Chemical Systems Research Division National Chung-Shan Institute of Science and Technology Taoyuan Taiwan Information and Communication Research Division National Chung-Shan Institute of Science and Technology Taoyuan Taiwan

ISBN: (数字)9798331510473

ISBN: (纸本)9798331510480

Multi-target echo positions in two dimensions can be achieved by combining time of flight (TOF) of signals gathering from vector network analyzer (VNA) and two kinds of geometric placements of two antennas (quasi-mono-static and bi-static). In this study, the positioning formulas are derived simply on the basis of triangular geometry. To effectively obtain multi-echo image, an approach similar to Klimontovich equation in counting plasma density is adopted. The proposed method has successfully been verified by a series of randomly arranged three-target experiments. The image reconstruction results precisely showed the positions of the targets in assistance with reference target.

关键词： Geometry Radar cross-sections Scattering Tomography Radar imaging Microwave theory and techniques Vectors Time-domain analysis Image reconstruction Microwave imaging

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LightEnsemble-Guard: An Optimized Ensemble Learning Framework for Securing Resource-Constrained IoT systems

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IEEE Access 2025年 13卷 101764-101781页

作者： Tanveer, Muhammad Usama Munir, Kashif Amjad, Madiha Alyamani, Hasan J. Bermak, Amine Rehman, Atiq Ur Khwaja Fareed University of Engineering and Information Technology Institute of Information Technology Rahim Yar Khan 64200 Pakistan King Abdulaziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Jeddah 21589 Saudi Arabia Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar

The rapid proliferation of real-time Internet of Things (IoT) devices has increased the need for efficient and accurate security mechanisms. Real-time IoT devices are highly vulnerable to cyberattacks due to their continuous connectivity and limited security mechanisms. In this work, we propose LightEnsemble-Guard, an ensemble learning-based approach specifically designed for resource-constrained IoT environments. Our method achieves a high detection accuracy of 99.55%, with strong precision, recall, and F1-score, while maintaining a low computational cost of just 22.23 seconds. To ensure robustness, we conducted 5-fold cross-validation and ROC curve evaluations, confirming the model’s reliability and generalizability. LightEnsemble-Guard integrates three lightweight classifiers LightGBM, XGBoost, and Extra Trees using a majority voting mechanism to improve detection performance on highly imbalanced datasets without burdening system resources. This ensemble strategy ensures an optimal balance between detection performance and computational resource utilization, making it well-suited for IoT networks, where processing power and memory are limited. The results highlight LightEnsemble-Guard as an effective, scalable and lightweight solution for real-time IoT security, significantly outperforming traditional models in both accuracy and computational efficiency. © 2013 IEEE.

关键词： Attack Detection Cybersecurity Ensemble Learning LightEnsemble-Guard Machine Learning

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Polarization-induced photocurrent switching effect in heterojunction photodiodes

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Nano Research 2023年第4期16卷 5503-5510页

作者： Dingbo Chen Yu-Chang Chen Guang Zeng Yu-Chun Li Xiao-Xi Li Dong Li Chao Shen Nan Chi Boon S.Ooi David Wei Zhang Hong-Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics&SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433China Key Laboratory for Information Science of Electromagnetic Waves Department of Communication Science and EngineeringFudan UniversityShanghai 200433China Photonics Laboratory Division of ComputerElectricaland Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The unipolar photocurrent in conventional photodiodes(PDs)based on photovoltaic effect limits the output modes and potential versatility of these devices in *** photodiodes with photocurrent switching are emerging as a promising solution for obtaining photoelectric devices with unique and attractive functions,such as optical logic ***,we design an all-solid-state chip-scale ultraviolet(UV)PD based on a hybrid GaN heterojunction with engineered bipolar polarized electric *** introducing the polarization-induced photocurrent switching effect,the photocurrent direction can be switched in response to the wavelength of incident light at 0 V *** particular,the photocurrent direction exhibits negative when the irradiation wavelength is less than 315 nm,but positive when the wavelength is longer than 315 *** device shows a responsivity of up to−6.7 mA/W at 300 nm and 5.3 mA/W at 340 nm,*** particular,three special logic gates in response to different dual UV light inputs are demonstrated via a single bipolar PD,which may be beneficial for future multifunctional UV photonic integrated devices and systems.

关键词： GaN heterostructure ultraviolet(UV)photodiodes bipolar photocurrent optical logic device

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