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Oversampling-Enhanced Feature Fusion-Based Hybrid ViT-1DCNN Model for Ransomware Cyber Attack Detection

computer Modeling in engineering & Sciences 2025年第2期142卷 1667-1695页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saifur Rahman Saad Arif Salim Nasar Faraj Mursal Muhammad Irfan Haris Aziz Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa31982Saudi Arabia Department of Mechanical Industrial and Energy System EngineeringUniversity of SargodhaSargodha40100Pakistan

Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural network(1DCNN)architectures to enhance ransomware detection *** common challenges in ransomware detection,particularly dataset class imbalance,the synthetic minority oversampling technique(SMOTE)is employed to generate synthetic samples for minority class,thereby improving detection *** integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features,resulting in comprehensive ransomware *** on the UNSW-NB15 dataset,the proposed ViT-1DCNN model achieved 98%detection accuracy with precision,recall,and F1-score metrics surpassing conventional *** approach not only reduces false positives and negatives but also offers scalability and robustness for real-world cybersecurity *** results demonstrate the model’s potential as an effective tool for proactive ransomware detection,especially in environments where evolving threats require adaptable and high-accuracy solutions.

关键词： Ransomware attacks cybersecurity vision transformer convolutional neural network feature fusion encryption threat detection

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Orbit-Orbit Interaction in Spatiotemporal Optical Vortex

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engineering 2025年第2期45卷 44-51页

作者： Jian Chen Jie Zhao Xi Shen Dewei Mo Cheng-Wei Qiu Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

While spin-orbit interaction has been extensively studied,few investigations have reported on the interaction between orbital angular momenta(OAMs).In this work,we study a new type of orbit-orbit coupling between the longitudinal OAM and the transverse OAM carried by a three-dimensional(3D)spatiotemporal optical vortex(STOV)in the process of tight *** 3D STOV possesses orthogonal OAMs in the x-y,t-x,and y-t planes,and is preconditioned to overcome the spatiotemporal astigmatism effect.x,y,and t are the axes in the spatiotemporal *** corresponding focused wavepacket is calculated by employing the Debye diffraction theory,showing that a phase singularity ring is generated by the interactions among the transverse and longitudinal vortices in the highly confined *** Fourier-transform decomposition of the Debye integral is employed to analyze the mechanism of the orbit-orbit *** is the first revelation of coupling between the longitudinal OAM and the transverse OAM,paving the way for potential applications in optical trapping,laser machining,nonlinear light-matter interactions,and more.

关键词： Spatiotemporal optical vortex Orbital angular momentum Momentum interaction Highly confined wavepacket Diffraction

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Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel Noises

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IEEE Transactions on Wireless Communications 2025年第5期24卷 4055-4072页

作者： Pei, Jianhua Feng, Cheng Wang, Ping Tabassum, Hina Shi, Dongyuan Huazhong University of Science and Technology School of Electrical and Electronic Engineering Hubei Wuhan China Cornell University Energy Systems Engineering System Engineering IthacaNY United States York University Lassonde School of Engineering Department of Electrical Engineering and Computer Science TorontoON Canada

Deep learning (DL)-based Semantic Communications (SemCom) is becoming critical to maximize overall efficiency of communication networks. Nevertheless, SemCom is sensitive to wireless channel uncertainties, source outliers, and suffer from poor generalization bottlenecks. To address the mentioned challenges, this paper develops a latent diffusion model-enabled SemCom system with three key contributions, i.e., i) to handle potential outliers in the source data, semantic errors obtained by projected gradient descent based on the vulnerabilities of DL models, are utilized to update the parameters and obtain an outlier-robust encoder, ii) a lightweight single-layer latent space transformation adapter completes one-shot learning at the transmitter and is placed before the decoder at the receiver, enabling adaptation for out-of-distribution data and enhancing human-perceptual quality, and iii) an end-to-end consistency distillation (EECD) strategy is used to distill the diffusion models trained in latent space, enabling deterministic single or few-step low-latency denoising in various noisy channels while maintaining high semantic quality. Extensive numerical experiments across different datasets demonstrate the superiority of the proposed SemCom system, consistently proving its robustness to outliers, the capability to transmit data with unknown distributions, and the ability to perform real-time channel denoising tasks while preserving high human perceptual quality, outperforming the existing denoising approaches in semantic metrics such as multiscale structural similarity index measure (MS-SSIM) and learned perceptual image path similarity (LPIPS). © 2002-2012 IEEE.

关键词： Image enhancement

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A Fully LTPS-TFT-Based Bi-Directional Biomedical Interface Circuit for Large-Area Healthcare Applications

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2025年第12期3卷 526-532页

作者： Zhang, Hanbo Lou, Yuqing Zhang, Zhihang Li, Yongfu Rokhan, Fakhrul Wang, Guoxing Zhao, Jian Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication System Engineering Selangor Serdang43400 Malaysia

This paper proposed a fully LTPS-TFT-based bi-directional biomedical pixel interface with integrated a high linearity stimulator and a high-performance bio-potential sensing front-end circuit to amplify and digitize biological signals for high robustness data transmission. All circuits are designed and manufactured under a 3-μm LTPS process. We demonstrated the experiment in saline using the stimulator circuit to simulate stimulation inside the organism, achieving stimulation with different average currents under different duty cycles. The proposed front-end circuit has a gain of 40 dB. The referred input voltage noise of the entire signal chain is 86.2 μV/√Hz, and the ENOB is 9.13 bits at an input of 0.5 mVPP. Simultaneously conducting statistical testing on 20 chips has achieved a 1.05 dB SNDR standard deviation. Finally, we use a function signal generator to simulate the input signals of ECoG, ECG, and EOG, then use front-end circuits to read and reconstruct them to demonstrate that the proposed pixel interface can correctly read common biomedical signals for healthcare applications. © 2022 IEEE.

关键词： Image segmentation

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An Affordable Sophisticated Frequency Control Ancillary Services for Australian National Electricity Market system Considering Industry and Infrastructure Challenges

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2025年第1期3卷 72-82页

作者： Alhelou, Hassan Haes Bahrani, Behrooz Ma, Jin School of Engineering CambridgeMA02139 United States Monash University Department of Electrical and Computer System Engineering ClaytonVIC3800 Australia University of Sydney School of Electrical and Information Engineering SydneyNSW2006 Australia

This industry-oriented paper proposes a novel sophisticated frequency control and its ancillary services framework for the Australian National Electricity Market (NEM) power system considering the special design of its current automatic generation control system, which does not involve interconnectors between different power regions, resulting in technical challenges for both stability and security of the system. The proposed new method converts the NEM centralized frequency control system to a fully decentralized one with virtual consideration of interconnectors' power, thus the stability and security would be improved, and high fluctuations in interchanged power would be smoothed without extra costs of infrastructure and procurement of frequency control ancillary reserves (FCASs). The novel idea is to model the interconnectors' power deviation as unknown input to the operator in each power region, like load disturbances and renewable power variations, using dynamic observation techniques, for enabling the proposed method capabilities. The method is theoretically verified that it can enhance stability and security and stabilize both local frequencies and power exchanges. The experiment results confirm the capability of the proposed method for the NEM system and its superiority over the existing adopted approaches in industries. © 2024 IEEE.

关键词： Stability criteria

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Architecture of AC-DC Energy Nodes in Supergrids: A Technical Foundation for Future Renewable Integration 5

Architecture of AC-DC Energy Nodes in Supergrids: A Technica...

引用

5th National and the 1st International Conference on Applied Research in electrical engineering, AREE 2025

作者： Mousavi, Mohammad Hossein Moradi, Hassan Rouzbehi, Kumars Razi University Department of Computer and Electrical Engineering Kermanshah Iran University of Seville Department of System Engineering and Automatic Control Seville Spain

ISBN: (纸本)9798350377170

The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment. © 2025 IEEE.

关键词： Wind power integration

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Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution systems

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IEEE Transactions on Smart Grid 2025年第3期16卷 2635-2646页

作者： Liu, Liming Yuan, Yuxuan Wang, Zhaoyu Yao, Yiyun Ding, Fei Iowa State University Department of Electrical and Computer Engineering AmesIA50011 United States National Renewable Energy Laboratory Power System Engineering Center GoldenCO80214 United States

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. The framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness. © 2010-2012 IEEE.

关键词： Soft sensors Data models Topology Probabilistic logic Data integration Accuracy Renewable energy sources Observability Government Support vector machines

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Hybrid signaling-droop dc-link voltage control for trains with multiple onboard power sources

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IEEE Access 2025年 13卷 75434-75447页

作者： Ahmad, Saad Saeed, Mariam Guerrero, Juan Manuel Muniategui, Iker Nuñez, Guillermo Larrazabal, Igor Briz, Fernando University of Oviedo Department of Electrical Computer & System Engineering Gijón33204 Spain Ingeteam Power Technology S.A. Traction R&D Zamudio48170 Spain

The increasing trend in efficiency and performance requirements of electric trains is leading to the deployment of more onboard energy storage elements. Hydrogen fuel cells along with battery systems are being considered by several train manufacturers. Control of the dc-link connecting all energy sources and loads can be challenging due to the need to guarantee reliable operation in all possible scenarios. This paper presents a dc-link control strategy for trains with multiple energy sources. The proposed method combines the advantages of dc bus signalling and droop methods, and allows smooth enabling and disabling of power sources by voltage command modification without any change in the overall control structure. Further, it is fault tolerant to communication loss between the battery and the central control. The proposed concepts are validated in multiple scenarios by means of simulation, as well as experimentally using a down-scaled test bench. © 2013 IEEE.

关键词： Electric traction

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Stable Stochastic MPC for Uncertain Wind Energy Conversion system Over Whole Operating Regions

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IEEE Transactions on Energy Conversion 2025年第1期40卷 515-528页

作者： Liu, Xiangjie Guo, Shifan Ma, Lele Kong, Xiaobing Lee, Kwang Y. North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China Baylor University Department of Electrical and Computer Engineering WacoTX76798-7356 United States

The stochastic uncertainty of wind speed presents a great challenge for achieving reliable power control in wind energy conversion system (WECS). Due to the excellence in handling the uncertainties based on probabilistic descriptions, stochastic model predictive control (SMPC) has been regarded as a promising strategy for WECS. However, owing to fluctuation characteristic of wind speed, operating points commonly change in WECS. Thus, an important limitation of applying SMPC to WECS stems from the fact that feasibility and stability of the traditional SMPC can only be ensured at one single predesigned operating point. Regarding this issue, a stable SMPC strategy for uncertain WECS is proposed in this paper to ensure the feasibility and stability of WECS under changing operating points over the whole operating regions. A Luenberger observer is employed to estimate model-plant mismatch introduced by linearization process, while a tube-based control framework is deployed to cope with stochastic wind speed disturbance. The feasibility of SMPC is ensured by incorporating artificial steady targets as optimization variables, while the stability of WECS is guaranteed by modifying the cost function and extending the terminal constraint. The effectiveness of the proposed strategy is validated through simulations and experiments under different scenarios. © 1986-2012 IEEE.

关键词： Stochastic systems

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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