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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Anmol Aggarwal Bhuvan Khoshoo John Agapiou Shanelle N. Foster General Motors Pontiac MI USA Department of Electrical & Computer Engineering Michigan State University East Lansing MI USA Retired Manufacturing Systems Research Laboratory General Motors Warren MI USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Using oriented steel for segmented stator construction in AC electric machine can improve the efficiency of machine by decreasing core losses compared to a machine designed with non-oriented steel. Therefore, analysis of the oriented steel stator in AC electric machines in finite analysis is of great interest. Several attempts were made to accurately simulate oriented steel in segmented stators; however, the insight into the flux distribution and consequently the perceived properties of the oriented steel is at-large missing. In this work, a physics-based approach to model oriented steel for radial flux AC machines is developed to accurately capture the magnetic properties by considering the direction of flux. The determined magnetic properties are used to model an equivalent isotropic model in FEA. The accuracy of developed FEA model is validated experimentally.

关键词： Stator cores Accuracy Correlation AC machines Core loss Energy conversion Finite element analysis Steel Magnetic properties

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Seven-level Cascade Multilevel Inverter based Minimum Switches for Photovoltaic applications

Seven-level Cascade Multilevel Inverter based Minimum Switch...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Ali Abedaljabar Al-Samawi Hafedh Trabelsi Department of Electronic and Communications Engineering College of Engineering Al-Muthanna University Al Muthanna Iraq Department of Electrical Engineering National Engineering School of Sfax (ENIS) Computer and Embedded Systems Laboratory (CES-Lab) Sfax University Sfax Tunisia

To enhance power quality and obtain high power from photovoltaic(PV), and mitigate the impact of the PV system's partial shading condition(PSC) and electrical mismatch power problems. This paper presents a single-phase, simple seven-level multilevel inverter architecture With a lower number of power components connected with four individual group PV systems integration converter DC/DC with independent Maximum Power Point Tracking(MPPT)in each group. The proposed inverter provides a reduced total harmonic distortion (THD) of voltage and unity active power. This reduction in the number of switches generates a decrease in the losses of switching and the number of drive circuits, which in turn causes a decrease in the control complication and decreases the cost and size of the control circuit. We compared this cascaded multilevel topology architecture to evaluate the performance of the suggested inverter, which needed modern cascade multilevel topologies with the same seven levels of voltage. The achievement of the comparison is dependent on several elements, including a set of parameters(diodes and capacitors), the overall harmonic distortion, and the number of switches included inside the inverter. The program(Simulink/Matlab) was used to verify the critical evaluation of the presented topology through simulation results.

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Privacy-Aware Joint DNN Model Deployment and Partition Optimization for Delay-Efficient Collaborative Edge Inference

arXiv

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arXiv 2025年

作者： Cheng, Zhipeng Xia, Xiaoyu Wang, Hong Liwang, Minghui Chen, Ning Fan, Xuwei Wang, Xianbin School of Future Science and Engineering Soochow University Suzhou215006 China School of Computing Technologies RMIT University MelbourneVIC Australia Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai201804 China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai201804 China Qingdao China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou350002 China Department of Electrical and Computer Engineering Western University ON Canada

Edge inference (EI) is a key solution to address the growing challenges of delayed response times, limited scalability, and privacy concerns in cloud-based Deep Neural Network (DNN) inference. However, deploying DNN models on resource-constrained edge devices faces more severe challenges, such as model storage limitations, dynamic service requests, and privacy risks. This paper proposes a novel framework for privacy-aware joint DNN model deployment and partition optimization to minimize long-term average inference delay under resource and privacy constraints. Specifically, the problem is formulated as a complex optimization problem considering model deployment, user-server association, and model partition strategies. To handle the NP-hardness and future uncertainties, a Lyapunov-based approach is introduced to transform the long-term optimization into a single-time-slot problem, ensuring system performance. Additionally, a coalition formation game model is proposed for edge server association, and a greedy-based algorithm is developed for model deployment within each coalition to efficiently solve the problem. Extensive simulations show that the proposed algorithms effectively reduce inference delay while satisfying privacy constraints, outperforming baseline approaches in various scenarios. Copyright © 2025, The Authors. All rights reserved.

关键词： Differential privacy

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Towards A Secured SCADA Architecture: A DNP3 Test Case

Towards A Secured SCADA Architecture: A DNP3 Test Case

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IEEE Southeastcon

作者： Ahmed S. Soliman Rocio Devine Diego Landi S M Sajjad Hossain Rafin M. H. Cintuglu Osama A. Mohammed Dept. of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Florida USA ECE Department Energy System Research Laboratory Florida International University Miami FL USA Dept. of Electrical and Computer Engineering Florida International University Miami Florida USA

The foundation of a country's critical infrastructures (CI), which provide crucial services, is its security, healthcare, and economic systems. By lowering CI's operational costs and associated expenses and enhancing its effectiveness and safety, appropriately functional CI infrastructure plays an essential role in the prosperity of the nations. To do so, businesses that manage CIs frequently combine the Internet of Things (IoT) with Cyber-Physical systems (CPS), such as SCADA systems. SCADA systems were not initially built with web security in mind, exposing CIs open to security risks. National security issues can arise when these technologies are connected to power plants and water treatment facilities. This study aims to demonstrate how security features can be implemented in DNP3-based SCADA infrastructures. By creating a functional configuration and consensus amongst the communicating devices, the DNP3 protocol will support digital signatures. The team proposed a SCADA architecture to accomplish this, making it possible for these systems more secure manner.

关键词： Protocols Industrial control SCADA systems Medical services Safety Security Internet of Things

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Multi-microgrid Energy Management systems: Architecture, Communication, and Scheduling Strategies

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Journal of Modern Power systems and Clean Energy 2021年第3期9卷 463-476页

作者： Bin Zhou Jianting Zou Chi Yung Chung Huaizhi Wang Nian Liu Nikolai Voropai Daosen Xu the College of Electrical and Information Engineering Hunan UniversityChangsha 410082China the Department of Electrical and Computer Engineering University of SaskatchewanSaskatoonSK S7N5A9Canada the College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China the Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences Irkutsk 664033Russia

The increasing penetration of various distributed and renewable energy resources at the consumption premises,along with the advanced metering,control and communication technologies,promotes a transition on the structure of traditional distribution systems towards cyber-physical multi-microgrids(MMGs).The networked MMG system is an interconnected cluster of distributed generators,energy storage as well as controllable loads in a distribution *** its operation complexity can be decomposed to decrease the burdens of communi-cation and control with a decentralized ***,the multi-microgrid energy management system(MIVIGEIV1S)plays a significant role in improving energy efficiency,power quality and reliability of distribution systems,especially in enhancing system resiliency during contingencies.A comprehensive overview on typical functionalities and architectures of MMGEMS is ***,the emerging communication technologies for information monitoring and interaction among MMG clusters are ***,various energy scheduling and control strategies of MMGs for interactive energy trading,multi-energy management,and resilient operations are thoroughly analyzed and ***,some challenges with great importance in the future research are presented.

关键词： Energy management system(EMS) microgrid communication renewable energy multi-energy system

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Quality Assessment of Screen Content Videos

Quality Assessment of Screen Content Videos

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International Conference on Pattern Recognition and Image Analysis (IPRIA)

作者： Hossein Motamednia Pooryaa Cheraaqee Azadeh Mansouri Ahmad Mahmoudi-Aznaveh Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyber Research Institute Shahid Beheshti University Tehran Iran

Perceptual quality assessment has always been challenging due to the difficulty in modeling the no-linear human visual system. With the diversity in the contents of multimedia signals, the conventional methods for traditional media seems no longer satisfying. One of these emerging media, is the screen content images/videos (SCINs), Containing texts and computer generated graphics, SCVs cannot be sufficiently expressed with features designed for natural sceneries. Therefore, new researches tried to devise objective quality assessment metrics, specificly for screen contents. Recently, a dataset was proposed for quality assessment of screen content videos. Since screen contents are full of structures that spread in cardinal directions, we were motivated to employ the horizontal and vertical subbands of the wavelet transform to characterize these types of visual contents. The features were incorporated in a full-reference method that showed promising results on the publicly available dataset for SCV quality assessment. The method can bo accessed via: https://***/motamedNia/QASCV.

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An effective Reinforcement Learning method for preventing the overfitting of Convolutional Neural Networks

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Advances in Computational Intelligence 2022年第5期2卷 1-15页

作者： Mahdavi-Hormat, Ali Menhaj, Mohammad Bagher Shakarami, Ashkan Department of Electrical Computer and Biomedical Engineering Islamic Azad University Qazvin Iran Department of Electrical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran Intelligent Autonomous Systems Laboratory (IAS-Lab) Department of Information Engineering University of Padova Padua Italy

Convolutional Neural Networks are machine learning models that have proven abilities in many variants of tasks. This powerful machine learning model sometimes suffers from overfitting. This paper proposes a method based on Reinforcement Learning for addressing this problem. In this research, the parameters of a target layer in the Convolutional Neural Network take as a state for the Agent of the Reinforcement Learning section. Then the Agent gives some actions as forming parameters of a hyperbolic secant function. This function’s form is changed gradually and implicitly by the proposed method. The inputs of the function are the weights of the layer, and its outputs multiply by the same weights to updating them. In this study, the proposed method is inspired by the Deep Deterministic Policy Gradient model because the actions of the Agent are into a continuous domain. To show the proposed method’s effectiveness, the classification task is considered using Convolutional Neural Networks. In this study, 7 datasets have been used for evaluating the model; MNIST, Extended MNIST, small-notMNIST, Fashion-MNIST, sign language MNIST, CIFAR-10, and CIFAR-100.

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Interconnectedness of Circular Economy, Artificial Intelligence and Vertical Farming as a Technosignature Model for Sustainable Space Food Production 15

Interconnectedness of Circular Economy, Artificial Intellige...

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15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Ii, Ronnie Concepcion Cabaccan, Carlo Ducut, Jullian Dominic Relano, R-Jay Alejandrino, Jonnel Agulto, Ronnel Bandala, Argel Mohamad, Roslina Dadios, Elmer Culaba, Alvin Department of Manufacturing Engineering and Management De la Salle University Manila Philippines De la Salle University Center for Engineering and Sustainability Development Research Intelligent Systems Research Unit Manila Philippines De la Salle University Bio-energy Environment and Renewables Laboratory Center for Engineering and Sustainability Development Research Manila Philippines Plant and Soil Health Research Unit Center for Natural Sciences and Environmental Research De la Salle University Manila Philippines School of Electrical Electronics and Computer Engineering Mapua University Manila Philippines School of Electrical Engineering College of Engineering Universiti Teknologi Mara Shah Alam Malaysia De la Salle University Department of Electronics and Computer Engineering Manila Philippines De la Salle University Department of Mechanical Engineering Manila Philippines

ISBN: (纸本)9798350381177

The degradation of Earth's natural resources and environmental health due to improper anthropological activities, mainly through unoptimized food production, is manifested through climate change that negatively alters the productivity in the agricultural sector. Because of this challenge in open terrestrial agriculture, the concept of space farming is believed to be significant in delivering fresh and quality food for the people on top of providing for astronauts and making them healthy in space. However, another problem emerges in the view of circular economy (CE) which is a production and consumption idealism that avoids degradation of natural resources and environment in producing one food unit and despite the collaborative advances in space technology, particularly in astrobotany, the materialization of CE and the absolutism of artificial intelligence (AI) are still partly imaginary. This study employed a bibliometric, scientometric and systematic analysis to highlight the advantages, limitations, and connections of CE, AI, and vertical farming (VF) which led to establishing a technosignature model for sustainable space food production. Here, CE, AI and VF were singularized as a model for sustainable space food production and identified their potential interplay. Based on scientific correlations, it is undoubtedly true that CE, AI, and VF have existing mutualism in Earth-based systems, but the degree of its importance as a whole is not yet completely appreciated for space farming. The developed CE-AI-VF technosignature model is scalable and adaptable if the government and scientific community put it into action accompanied by science policies. © 2023 IEEE.

关键词： Climate change

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Digital Over-the-Air Federated Learning in Multi-Antenna systems

arXiv

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arXiv 2023年

作者： Wang, Sihua Chen, Mingzhe Shen, Cong Yin, Changchuan Brinton, Christopher G. The Beijing Laboratory of Advanced Information Network The Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Charles L. Brown Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA United States The School of Electrical and Computer Engineering Purdue University West LafayetteIN United States

In this paper, the performance optimization of federated learning (FL), when deployed over a realistic wireless multiple-input multiple-output (MIMO) communication system with digital modulation and over-the-air computation (AirComp) is studied. In particular, a MIMO system is considered in which edge devices transmit their local FL models (trained using their locally collected data) to a parameter server (PS) using beamforming to maximize the number of devices scheduled for transmission. The PS, acting as a central controller, generates a global FL model using the received local FL models and broadcasts it back to all devices. Due to the limited bandwidth in a wireless network, AirComp is adopted to enable efficient wireless data aggregation. However, fading of wireless channels can produce aggregate distortions in an AirComp-based FL scheme. To tackle this challenge, we propose a modified federated averaging (FedAvg) algorithm that combines digital modulation with AirComp to mitigate wireless fading while ensuring the communication efficiency. This is achieved by a joint transmit and receive beamforming design, which is formulated as an optimization problem to dynamically adjust the beamforming matrices based on current FL model parameters so as to minimize the transmitting error and ensure the FL performance. To achieve this goal, we first analytically characterize how the beamforming matrices affect the performance of the FedAvg in different iterations. Based on this relationship, an artificial neural network (ANN) is used to estimate the local FL models of all devices and adjust the beamforming matrices at the PS for future model transmission. The algorithmic advantages and improved performance of the proposed methodologies are demonstrated through extensive numerical experiments. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

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Application of Normal Form Theory to Power systems: A Proof of Concept of a Novel Structure-Preserving Approach

Application of Normal Form Theory to Power Systems: A Proof ...

引用

IEEE General Meeting Power& Energy Society

作者： Bin Wang Xavier Kestelyn Erfan Kharazian Aurélien Grolet Department of Electrical and Computer Engineering University of Texas at San Antonio San Antonio TX Laboratory of Electrical Engineering of Lille (L2EP) Arts et Metiers Institute of Technology (ENSAM) Lille France Laboratory of Physical and Numerical Systems (LISPEN) Arts et Metiers Institute of Technology (ENSAM) Lille France

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Differential algebraic equations (DAE) of power systems, classically obtained by aggregating all component equations and network equations, are a standard input of transient stability simulation software. To add a parametric approach to the provided transient stability simulation, the linear modal analysis is a commonly adopted approach because it provides insights about system dynamics, such as eigenvalues and eigenvectors, that can be used for control design. When the power system is more heavily loaded, the linear modal analysis becomes less accurate in terms of capturing system dynamic behaviors when subjected to large disturbances. Normal form analysis, based on a higher-order Taylor expansion of the system model, has been proved to capture the major nonlinear effects occurring in the system. Unfortunately, the normal form method is currently only applicable to ordinary differential equations (ODE) and imposes a recast of the DAE system onto an ODE system, which is feasible only under restrictive assumptions and is usually time-consuming. In this paper, we propose a novel method in order to directly apply the normal form theory to power system DAE without the need to recast DAE into an ODE form. A single-machine-infinite-bus (SMIB) system is adopted to show the feasibility and accuracy of the proposed method.

关键词： Accuracy System dynamics Modal analysis Power system stability Mathematical models Stability analysis Software Transient analysis Thermal stability Standards

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