检索结果-内蒙古大学图书馆

IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

Physical Intrusion Attack Detection in Fieldbus Network With Passive Fail-Safe Biasing

引用

IEEE Transactions on automation Science and engineering 2025年 22卷 14008-14019页

作者： Wang, Xiangming Liu, Yang Yu, Nanpeng Liu, Pengfei Deng, Nanyi Li, Yanan Liu, Ting Xi’an Jiaotong University School of Cyber Science and Engineering MoE KLINNS Laboratory Xi’an710049 China University of California at Riverside Department of Electrical and Computer Engineering RiversideCA92521 United States Xi’an Thermal Power Research Institute Company Ltd. Power Infrastructure Cyber Security Research Center Xi’an710054 China Electric Power Dispatch and Control Center of Guangdong Power Grid Company Ltd. Guangzhou510699 China

Fieldbus is widely used for real-time distributed control in Industrial Control Systems (ICSs) due to its simplicity and stability. The real-world fieldbus network contains hundreds of interconnected devices, presenting a widespread network layout. Attackers can attach external intrusion devices to these communication lines to launch various attacks. In this paper, we model the fieldbus network’s channel fingerprint based on the signal’s amplitude and propose a detection method to identify potential attackers (silent intrusion devices that are eavesdropping) via channel fingerprint differences. Leveraging the passive fail-safe biasing voltage in the fieldbus network such as RS485, we can still detect the intrusion device when the fieldbus is idle (i.e., no devices are transmitting commands), which can significantly reduce the detection delay with lower sampling costs. Moreover, our method can adapt to environmental changes with little computational overhead by generating dynamic thresholds. Using a monitoring unit with stored channel fingerprints, our method can be easily deployed in fieldbus networks without occupying communication resources. The effectiveness and robustness of the proposed method have been demonstrated via extensive experiments on two real-world scenarios and one simulation scenario, where we can achieve 100% accuracy and 0% false alarm rates against various intrusion devices. © 2004-2012 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Enhancing malware detection performance: leveraging K-Nearest Neighbors with Firefly Optimization Algorithm

引用

Multimedia Tools and Applications 2025年第12期84卷 10071-10094页

作者： Al Saaidah, Adeeb Abualhaj, Mosleh M. Shambour, Qusai Y. Abu-Shareha, Ahmad Adel Abualigah, Laith Al-Khatib, Sumaya N. Alraba’nah, Yousef H Department of Networks and Cybersecurity Al-Ahliyya Amman University Amman Jordan Department of Software Engineering Al-Ahliyya Amman University Amman Jordan Department of Data Science and Artificial Intelligence Al-Ahliyya Amman University Amman Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Research Center University of Tabuk Tabuk71491 Saudi Arabia MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon College of Engineering Yuan Ze University Taoyuan32003 Taiwan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia

Malware detection plays a crucial role in ensuring robust cybersecurity amidst the ever-evolving cyber threats. This research paper delves into the realm of machine learning (ML) algorithms for malware detection, with a specific emphasis on the K-Nearest Neighbors (KNN) algorithm, utilizing tailored parameter settings and the Firefly Optimization Algorithm (FOA). The study leverages the MalMem-2022 dataset to assess the efficacy of KNN and KNN with FOA in malware detection. The impact of parameter tuning and feature selection on classification is elucidated by comparing the performance of both approaches. Encouragingly, the results reveal promising advancements in one of the multiclass classification scenarios when employing KNN with FOA, yielding noteworthy enhancements in Accuracy, Recall, Precision, Matthews Correlation Coefficient, TNR, and F1-score by 2.65%, 2.65%, 2.47%, 3.59%, 0.17%, and 2.61%, respectively. These findings accentuate the significance of optimizing KNN’s parameters and implementing FOA for feature selection, culminating in heightened accuracy in malware detection. The symbiotic fusion of KNN and FOA exhibits remarkable effectiveness in augmenting the classification model’s performance, thus offering valuable insights for bolstering cybersecurity measures. Adopting ML algorithms, particularly KNN with specific parameter settings and FOA, presents a promising avenue for enhancing malware detection capabilities. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

State Transfer Induced Transient Synchronization Instability of GFM-VSC: Analysis and Improvement

引用

IEEE Transactions on Sustainable Energy 2025年

作者： Liu, Yushuang Geng, Hua Yang, Geng Huang, Meng He, Changjun Zha, Xiaoming Ding, Wenze Liu, Feng Tsinghua University Beijing National Research Center for Information Science and Technology Department of Automation Beijing100084 China Wuhan University School of Electrical Engineering and Automation Wuhan430072 China Tsinghua University Department of Electrical Engineering Beijing100084 China

The operation mode of grid-forming voltage source converters (GFM-VSCs) may switch between voltage source mode (VSM) and current source mode (CSM) under some situations such as grid faults, owing to the current limitation control. During the mode-switching process, there is state transfer from the final state of the last mode to the initial state of the next mode, which impacts the transient synchronization stability (TSS) of GFM-VSCs. This paper primarily focuses on analyzing and improving the TSS of GFM-VSCs by considering the effect of state transfer. A novel transient instability mechanism is revealed through the existence analysis of equilibrium points. It clarifies that the state transfer may cause the operating trajectory during faults to bypass the stable equilibrium point in CSM before diverging to the next cycle, thereby resulting in transient synchronization instability. Besides, to further analyze the TSS of mode-switched VSCs considering the dynamics during faults, multiple Lyapunov functions are adopted to derive the TSS criteria and boundaries. It has been identified that lowering the minimum critical current and adjusting the saturated current phase in accordance with virtual power angle (VPA) dynamics can enhance the TSS of GFM-VSCs. Therefore, a VPA feedback-based current limiting strategy is proposed to safeguard GFM-VSCs against overcurrent and ensure the TSS. The validity of the new transient instability mechanism and the efficacy of the proposed strategy are confirmed through simulations of a GFM-VSC connected to an IEEE 39-bus power grid and hardware-in-the-loop experiments. © 2010-2012 IEEE.

关键词： Transient stability

来源：评论

学校读者我要写书评

暂无评论

Toward Understanding Federated Learning over Unreliable Networks

IEEE Transactions on Machine Learning in Communications and ...

引用

IEEE Transactions on Machine Learning in Communications and Networking 2025年 3卷 80-97页

作者： Feng, Chenyuan Arafa, Ahmed Chen, Zihan Zhao, Mingxiong Quek, Tony Q. S. Yang, Howard H. EURECOM Department of Communication Biot06410 France University of North Carolina at Charlotte Department of Electrical and Computer Engineering CharlotteNC28223 United States Singapore University of Technology and Design Information Systems Technology and Design Pillar Tampines487372 Singapore Yunnan University Engineering Research Center of Cyberspace National Pilot School of Software Kunming650106 China Zhejiang University ZJU-UIUC Institute Haining314400 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310007 China University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering ChampaignIL61820 United States

This paper studies the efficiency of training a statistical model among an edge server and multiple clients via Federated Learning (FL) - a machine learning method that preserves data privacy in the training process - over wireless networks. Due to unreliable wireless channels and constrained communication resources, the server can only choose a handful of clients for parameter updates during each communication round. To address this issue, analytical expressions are derived to characterize the FL convergence rate, accounting for key features from both communication and algorithmic aspects, including transmission reliability, scheduling policies, and momentum method. First, the analysis reveals that either delicately designed user scheduling policies or expanding higher bandwidth to accommodate more clients in each communication round can expedite model training in networks with reliable connections. However, these methods become ineffective when the connection is erratic. Second, it has been verified that incorporating the momentum method into the model training algorithm accelerates the rate of convergence and provides greater resilience against transmission failures. Last, extensive empirical simulations are provided to verify these theoretical discoveries and enhancements in performance. © 2023 CCBY.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Stable Task Assignment Mechanism for Multi-Platform Mobile Crowdsensing

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 8079-8094页

作者： Peng, Shuo Zhang, Guo Zhang, Baoxian Yao, Zheng Liu, Chen Li, Cheng University of Chinese Academy of Sciences Research Center of Ubiquitous Sensor Networks Beijing100049 China University of British Department of Electrical and Computer Engineering BCV6T 1Z4 Canada Simon Fraser University School of Engineering Science BurnabyBCV5A 1S6 Canada

Mobile crowdsensing (MCS) is a new paradigm for Internet of Things. It can fully utilize the smart devices carried by mobile users for accomplishing various sensing tasks. Most existing task assignment mechanisms have assumed the availability of just a single service platform and without considering the preference of users and platforms. In this paper, we focus on studying how to design efficient task assignment mechanism when there are multiple service platforms in the MCS system and further the preferences of both users and platforms are considered while the sensing quality of each user is unknown in advance. The design objective is to maximize the overall sensing qualities of all completed tasks while respecting the budget constraint of each platform. We build a multi-platform oriented task assignment framework and formulate the problem under study as a 0-1 integer linear programming (ILP) problem. We propose a Multi-platform Stable Task Assignment mechanism (MSTA). MSTA works in a round by round manner. In each round, MSTA first performs budget splitting among different task locations for each platform, then makes stable matching between users and platforms and performs online learning of users' sensing qualities by using the multi-armed bandit (MAB) model. We deduce the time complexity of MSTA and prove that MSTA has the properties of stability, individual rationality, budget feasibility, and truthfulness. Simulation results demonstrate the high performance of the proposed MSTA mechanism. © 1967-2012 IEEE.

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

A Thyristor-Based Fault Current Bypass Solid-State Circuit Breaker for DC Microgrid Applications 14

A Thyristor-Based Fault Current Bypass Solid-State Circuit B...

引用

14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Zhou, Jiale Sun, Xiuhu Mu, Qiang Zhao, Tiefu University of North Carolina at Charlotte Dept. of Electrical & Computer Engineering CharlotteNC United States University of North Carolina at Charlotte Batt Cave Research Center Ece Department CharlotteNC United States

ISBN: (纸本)9798331516116

Thyristor-based solid-state circuit breaker (SSCB) has high efficiency as a protection device for DC microgrid distribution. However, the passive turn-off and microsecond-level turn-off time make thyristor-based SSCBs more suitable for high-inertia DC systems. Large inductance in DC systems extends the fault clearing time. This paper proposes a thyristor-based fault current bypass SSCB (TFCB-SSCB) for DC microgrids. The proposed topology, compared to conventional thyristor-based SSCBs, not only offers high efficiency but also achieves rapid isolation of the source and fault side, with the only additional cost being a switch with a low breakdown voltage. Initially, the superiority of the proposed topology is analyzed in comparison to the prior-art thyristor-based topology. Next, the operating principles and key design considerations are presented for the proposed topology. Finally, the effectiveness of the proposed topology is verified through simulation results on an 800 V/ 165 A TFCB-SSCB model and experimental results on a 100 V/68 A TFCB-SSCB prototype. The fault isolation time of the proposed topology is five times faster than that of the traditional topology in simulations and twice as fast in experiments. © 2025 IEEE.

关键词： Electric fault location

来源：评论

学校读者我要写书评

暂无评论

On Error-Based Step Size Control for Discontinuous Galerkin Methods for Compressible Fluid Dynamics

引用

应用数学与计算数学学报 2025年第1期7卷 3-39页

作者： Hendrik Ranocha Andrew R.Winters Hugo Guillermo Castro Lisandro Dalcin Michael Schlottke-Lakemper Gregor J.Gassner Matteo Parsani Applied Mathematics University of HamburgBundesstr.5520146 HamburgGermany Department of Mathematics Applied Mathematics Linköping UniversityLinköpingSweden Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Applied and Computational Mathematics RWTH Aachen UniversityAachenGermany High-Performance Computing Center Stuttgart University of StuttgartStuttgartGermany Department of Mathematics and Computer Science University of CologneCologneGermany Center for Data and Simulation Science University of CologneCologneGermany Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Physical Science and Engineering Division(PSE) King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fluid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler *** demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more classical step size control based on a Courant-Friedrichs-Lewy(CFL)*** numerical examples show that the error-based step size control is easy to use,robust,and efficient,e.g.,for(initial)transient periods,complex geometries,nonlinear shock captur-ing approaches,and schemes that use nonlinear entropy *** demonstrate these properties for problems ranging from well-understood academic test cases to industrially relevant large-scale computations with two disjoint code bases,the open source Julia pack-ages *** with *** and the C/Fortran code SSDC based on PETSc.

关键词： Explicit Runge-Kutta(RK)methods Step size control Compressible fluid dynamics Adaptivity in space and time Shock capturing

来源：评论

学校读者我要写书评

暂无评论

Practical aberration correction using deep transfer learning with limited experimental data

引用

Optics Express 2025年第6期33卷 14431-14444页

作者： Kok, Yong En Bentley, Alexander Parkes, Andrew J. Somekh, Michael G. Wright, Amanda J. Pound, Michael P. University of Nottingham School of Computer Science NottinghamNG8 1BB United Kingdom Optics and Photonics Group Department of Electrical and Electronic Engineering University of Nottingham NottinghamNG7 2RD United Kingdom Research Center for Humanoid Sensing Zhejiang Laboratory Hangzhou3111100 China

Adaptive optics is a technique for correcting aberrations and improving image quality. When adaptive optics was first used in microscopy, it was common to rely on iterative approaches to determine the aberrations present. It is advantageous to avoid iteration, and therefore there has been a shift to deep learning for aberration prediction. However, issues remain regarding the practicalities of machine learning for adaptive optics, an important one being the requirement for a large training dataset. Here, we explore transfer learning to overcome this need for data by pre-training a network on a large simulated dataset and fine-tuning it with reduced experimental data for application in an experimental setting. We demonstrate that the pre-trained network can make noticeable improvements with fine-tuning on just 24 experimental samples. To further enhance practicality, we significantly extend the range of aberrations present, predicting up to 25 Zernike modes with each coefficient ranging from −1 to 1, and perform a thorough analysis of the type and magnitude of phase-diversity required in the input data for a successful network. Our approach demonstrates substantial aberration reduction on experimental data for 10 Zernike modes, with an average 73% decrease in RMS wavefront error from 1.81 to 0.48 rad when correction is applied. This method achieves complete experimental image capture and aberration inference at rates comparable to the image acquisition time of a typical laser scanning microscope. Additionally, we consider the benefits of further improvements via an iterative step. As such, this work addresses some of the key practical hurdles that remain in the use of deep learning for aberration prediction and correction. © 2025 Optica Publishing Group (formerly OSA). All rights reserved.

关键词： Adaptive optics

来源：评论

学校读者我要写书评

暂无评论

A Dual-Core Dual-Mode Class-F VCO With Wide Frequency Tuning Range Using Wide Inductance-Switching-Range Inductor

引用

IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 460-463页

作者： Hou, Yaru Li, Runlong Chi, Pei-Ling Yang, Tao University of electronic Science and Technology of China Chengdu610036 China Sichuan Province Engineering Research Center for Broadband Microwave Circuit High Density Integration Chengdu610036 China University of Electronic Science and Technology of China School of Electronic Science and Engineering Sichuan Chengdu610054 China National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A novel dual-core dual-mode class-F voltage-controlled oscillator (VCO) with wide frequency tuning range (TR) is proposed in this letter. It consists of two coupled parallel "8"-shaped inductor and two crossed-coupled VCO cores. To increase the TR of the proposed VCO without adding additional footprint size, a single-turn common-mode inductor is embedded inside the "8"-shaped inductor. By controlling the mode switches, the inductor can work in different modes with large inductance difference, realizing large VCO TR consequently. Then, the two coupled inductors were engineered to form the fundamental and third harmonic resonances, respectively, thereby producing a pseudo-square wave output waveform and realizing class-F operation. With the proposed configuration, the phase noise (PN) of the proposed VCO can be significantly reduced without increasing VCO core size. To demonstrate the proposed idea, a VCO prototype is fabricated in a 65-nm CMOS process with a core size of 1.235×0.8mm. It achieves a wide frequency TR from 2.84 to 7.04 GHz. The measured PN at 1-MHz offset is from -123.9 to -113.1 dBc/Hz, demonstrating an FOMT of 196.0-201.3 dBc/Hz. © 2023 IEEE.

关键词： Variable frequency oscillators

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：