检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Wang, Jiajia Xu, Xingyuan Zhang, Haoran Zeng, Xuecheng Bai, Yunping Lowery, Arthur J. Xu, Kun State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Electro-Photonics Laboratory Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia

Photonic integrated circuits (PICs) offer ultra-broad optical bandwidths that enable unprecedented data throughputs for signal processing applications. Dynamic reconfigurability enables compensation of fabrication flaws and fluctuating external environments, tuning for adaptive equalization and training of optical neural networks. The initial step in PIC reconfiguration entails measuring its dynamic performance, often described by its frequency response. While measuring the amplitude response is straightforward, e.g. using a tunable laser and optical power meter, measuring the phase response presents challenges due to various factors, including phase variations in test connections and instrumentation limitations. To address these challenges, a universal and robust characterization technique is proposed, which uses an on-chip reference path coupled to the signal processing core (SPC), with a delay larger or smaller than the total delay across the signal processing paths. A Fourier transform of the chip's power response reveals the SPC's impulse response. The method is more robust against low reference-path power and imprecise delays. Experiments using a finite-impulse-response (FIR) structure demonstrate rapid SPC training, overcoming thermal crosstalk and device imperfections. This approach offers a promising solution for PIC characterization, facilitating expedited physical parameter training for advanced applications in communications and optical neural networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Photonic integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Meta-Critic Reinforcement Learning for IOS-Assisted Multi-User Communications in Dynamic Environments

Meta-Critic Reinforcement Learning for IOS-Assisted Multi-Us...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Qinpei Luo Boya Di Zhu Han State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Electrical and Computer Engineering Department University of Houston TX USA

Capable of reflecting and refracting the incident signals on both sides simultaneously, the intelligent omnidirectional surface (IOS) has recently been proposed as a promising solution to enhance the capacity of wireless networks. However, the large number of IOS elements brings a heavy burden to the beamforming scheme design, especially for applications that require a fast response to varying environments. In this paper, aiming to maximize the sum rate of an IOS-aided multi-user system via IOS-enabled beamforming design that can rapidly adapt to dynamic channel states and user mobility, we develop a novel meta-critic reinforcement learning framework where a meta-critic network recognizes the environment change and automatically re-trains of the learning model. A stochastic Explore and Reload procedure is tailored to reduce the high-dimensional action space problem. Simulation results show the proposed scheme can converge to a higher sum rate more rapidly compared to the benchmark methods in dynamic settings. The robustness of our scheme against different IOS sizes is also verified.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Toward Value-oriented Renewable Energy Forecasting: An Iterative Learning Approach

arXiv

引用

arXiv 2023年

作者： Zhang, Yufan Jia, Mengshuo Wen, Honglin Bian, Yuexin Shi, Yuanyuan Department of Electrical and Computer Engineering University of California San Diego United States Power Systems Laboratory ETH Zürich Zürich8092 Switzerland Department of Electrical Engineering Shanghai Jiao Tong University China

Energy forecasting is an essential task in power system operations. Operators usually issue forecasts and use them to schedule energy dispatch in advance. However, forecasting models are typically developed in a way that overlooks the decision value of forecasts. To bridge the gap, we design a value-oriented point forecasting approach for sequential energy dispatch problems with renewable energy sources. At the training phase, we align the training objective with the decision value, i.e., minimizing the overall operating cost. The forecasting model parameter estimation is formulated as a bilevel program. Under mild assumptions, we convert the upper-level objective into an equivalent form using the dual solutions obtained from the lower-level operation problems. In addition, a novel iterative solution strategy is proposed for the newly formulated bilevel program. Under such an iterative scheme, we show that the upper-level objective is locally linear with respect to the forecasting model output and can act as the loss function. Numerical experiments demonstrate that, compared to commonly used forecasts predicting expected realization, forecasts obtained by the proposed approach result in lower operating costs. Meanwhile, the proposed approach achieves performance comparable to that of two-stage stochastic programs, but is more computationally efficient. © 2023, CC BY.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Over-the-Air Computation for Federated Generative Model Fine-Tuning in Unmanned Vehicle-Assisted Disaster Relief

引用

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Zhao, Yikun Feng, Lei Zhou, Fanqin Li, Wenjing Xiong, Zehui Du, Hongyang Wu, Celimuge Guo, Song Quek, Tony Q.S Han, Zhu State Key Laboratory of Networking and Switching Technology Beijing100876 China Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore487372 Singapore University of Hong Kong Department of Electrical and Electronic Engineering Pok Fu Lam Hong Kong University of Electro-Communications Meta-Networking Research Center Tokyo Japan Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The utilization of emergent generative artificial intelligence (GAI) within the realm of unmanned vehicles (UVs) can boost edge intelligence and potentially enhance the efficiency and effectiveness of rescue operations. However, to facilitate specialized generative edge intelligence in dynamic UV networks, GAI models need to tap into local data and conduct online fine-tuning, and the dispersed distribution of UVs makes distributed fine-tuning paradigms crucial. Although the federated generative model fine-tuning brings a potential solution, the large number of parameter transmissions involved in its fine-tuning process are often constrained by communication bottlenecks, which are more pronounced for resource-constrained UV networks. To cope with these challenges, we introduce an energy-efficient GAI model fine-tuning framework for the hierarchical UV networks, which employs over-the-air technology to save computational resource costs for unmanned aerial vehicle (UAV) during federated aggregation within a federated learning paradigm. Thereafter, we study the resource allocation problem in the fine-tuning process of the generative model and formulate a joint optimization problem for the bandwidth allocation, power control, computation resource allocation, and denoising factor control, aiming to minimize the system energy consumption. Then, we decouple the original problem into four tractable subproblems, and propose a block coordinate descent algorithm to solve them iteratively. Particularly, we derive a closed-form solution for the denoising factor to minimize the local model uploading transmission energy consumption under a specific AirComp communication error threshold. Simulation based on the state-of-the-art generative models shows that our AirComp-assisted federated generative model fine-tuning scheme can achieve satisfactory customized field-of-view image generation capability compared with the traditional fine-tuning scheme in an energy-efficient way. © 2015 I

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Innate Cyber-Immunity and Acquired Cyber-Immunity across Multi-Area Power systems

引用

IEEE Transactions on Power systems 2025年

作者： Hou, Jiazuo Song, Yue Hou, Yunhe Peng, Jimmy Chih-Hsien National University of Singapore Department of Electrical and Computer Engineering Singapore Tongji University Department of Control Science and Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology Shanghai201804 China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518057 China

Organisms have evolved innate and acquired immune systems to defend against pathogens like coronaviruses. Similarly, power networks, threatened by cyber-attacks, desire cyber-immunity. Inspired by the immunology research, this study develops a cyber-immune strategy-characterizing innate cyber-immunity and establishing acquired cyber-immunity-for any selected portion of a power network (termed as power subnetwork) against stealthy false data injection (FDI) cyberattacks. Therein, without extrinsic protection and information asymmetry, this paper for the first time confirms the existence and provides closed-form conditions for power subnetworks that are innately immune to FDI cyber-attacks despite all measurements being compromised. Single-leader-multi-follower bi-level optimization models are then developed to strategically allocate measurement protection, leading to the acquired cyber-immunity, whose conditions for existence and the least cost are explicitly formulated. More importantly, a bi-directional cyber-immunity propagation mechanism is presented to provide the optimal spatial allocation of defense resources across adjacent subnetworks. It also explicitly determines the temporal allocation sequence, revealing its sequential and cumulative impacts on establishing cyber-immunity. This is achieved by designing recursive traversal algorithms, one of which is modelled as a post-order depth-first-search problem of a multi-fork tree. The proposed subnetwork-specific cyber-immune strategy is verified in a modified Australian National Electricity Market. © 1969-2012 IEEE.

关键词： Phishing

来源：评论

学校读者我要写书评

暂无评论

Maximum Power Point Tracking Based on Crayfish Optimization Algorithm for Photovoltaic systems Operating Under Partial Shading Conditions

Maximum Power Point Tracking Based on Crayfish Optimization ...

引用

electrical engineering and Automatic Control (ICEEAC), International Conference on

作者： Abdelghani Draoui Ahmed Saidi Oubelaid Adel Mohammed Amine Meziane Boumediene Allaoua Abdrabbi Bourezg Department of Computer Science Laboratory of Environmental and Energy Systems (LSEE) University Center of Ali Kafi Tindouf Algeria Department of Electrical Engineering Laboratory of Sustainable Development and Computer Science University of Ahmed Draria Adrar Algeria Laboratoire de Technologie Industrielle de l'information Faculté de Technologie Bejaia University Bejaia Algeria Department of Electrical Engineering University center of Naama Naama Algeria Department of Electrical Engineering University of Tahri Mohamed Bechar Bechar Algeria Department of Electrical Engineering Dubai Men's College Higher Colleges of Technology Dubai Algeria

ISBN: (数字)9798350349740

ISBN: (纸本)9798350349757

The clean and renewable nature of energy harvested using the Photovoltaic (PV) technology makes it one the fastest growing technologies used in producing electricity. Due to the relatively low efficiency of the various solar cells available in the market, solar trackers and Maximum Power Point Tracking (MPPT) algorithms are used extensively to operate the system at its full potentials. Knowing that such systems are installed in outdoor spaces, they are inevitably subjected to partial shading conditions, where different parts of the system are subjected to different levels of solar irradiance. In case of occurrence of partial shading conditions on a PV system equipped with bypass diodes, the Power-Voltage (P-V) curve will have multiple peaks. This multi-peak curve requires using a sophisticated algorithm to track the Global Maximum Power Point (GMPP) instead of being deceived and trapped in a Local Maximum Power Point (LMPP). In this paper, the Crayfish Optimization Algorithm (COA) is suggested to track the GMPP of a PV system under partial shading conditions. The COA algorithm fetch for the GMPP by reading the PV panel output power and setting accordingly the duty cycle of the buck converter. Simulation is carried out using the MATLAB/Simulink platform and results demonstrate good tracking performance and prove the robustness of the system against rapid variations in solar irradiance levels.

关键词： Maximum power point trackers Solar irradiance Photovoltaic systems Renewable energy sources Microcontrollers Photovoltaic cells Robustness

来源：评论

学校读者我要写书评

暂无评论

Study of Partial Discharge Inception Characteristics of Aviation Wire Stressed by PWM Voltages Under Various Air Pressures

Study of Partial Discharge Inception Characteristics of Avia...

引用

2022 IEEE International Power Modulator and High Voltage Conference, IPMHVC 2022

作者： Wei, Zhuo Alkhalid, Khalid Alsaif, Faisal Wang, Jin Grosjean, Dennis Schweickart, Daniel The Ohio State University Department of Electrical and Computer Engineering ColumbusOH United States Innovative Scientific Solutions Inc. DaytonOH United States Air Force Research Laboratory Aerospace Systems Directorate Ohio United States

ISBN: (纸本)9781665471657

Partial discharge (PD) is a common and detrimental phenomenon that can cause damage and potential breakdown in insulation systems. According to the air breakdown voltage behaviors shown by Paschen's curve, from sea level to high altitude, the partial discharge inception voltage (PDIV) of the air is expected to decrease with decreasing pressure. So far, there has not been a widely accepted PD testing method for aviation wires in low pressure environments with pulse width modulated (PWM) voltage excitations. There have been studies of the PD behaviors of aviation wires with conventional triangular impulses, ac voltages, and PWM pulses with relatively low dv/dt. But existing test methods and study results cannot be directly utilized to test and predict PDIV of aviation wires when high dv/dt PWM excitation is applied with wide-bandgap (WBG) power devices, such as Silicon Carbide (SiC) Metal Oxide Semiconductor Field Effect Transistors (MOSFETs). Thus, this paper aims to provide more insights on PD behaviors of aviation wires under high dv/dt PWM excitations and possible ways to improve the existing PD test methods. A test setup including an ultra-high dv/dt PWM generator, a test sample fixture, and associated PD sensors including a photomultiplier tube (PMT), a high frequency current transducer (HFCT), and an ultra-high-frequency (UHF) antenna will be introduced. Experimental results and associated analysis for aviation wire test samples at various pressures under high dv/dt PWM excitations will be presented. The effect of the rise time of the PWM will be discussed in detail. Suggestions on how to improve test methods and test standards will be provided. © 2022 IEEE.

关键词： Silicon carbide

来源：评论

学校读者我要写书评

暂无评论

arXiv

引用

arXiv 2024年

作者： Ren, Yingying Li, Qiuli Guo, Yangyang Pedrycz, Witold Xing, Lining Liu, Anfeng Song, Yanjie School of Computer Electronics and Information Guangxi University Nanning China Guangxi Key Laboratory of Multimedia Communications and Network Technology China Key Laboratory of Parallel Distributed and Intelligent Computing Guangxi University China School of Systems Science Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer Istanbul Turkey School of Electronic Engineering Xidian University Xian China School of Electronic Engineering Central South University Changsha China National Engineering Research Center of Maritime Navigation System Dalian Maritime University Dalian China

With the rapid development of the satellite industry, the information transmission network based on communication satellites has gradually become a major and important part of the future satellite ground integration network. However, the low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system and needs to be solved urgently. Effectively planning the task of satellite ground networking by reasonably scheduling resources is crucial for the efficient transmission of task data. In this paper, we hope to provide a task execution scheme that maximizes the profit of the networking task for satellite ground network planning considering feeding mode (SGNPFM). To solve the SGNPFM problem, a mixed-integer planning model with the objective of maximizing the gain of the link-building task is constructed, which considers various constraints of the satellite in the feed-switching mode. Based on the problem characteristics, we propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks. To obtain more high-quality solutions, different similarity evaluation methods are designed to assist the algorithm in intelligently screening individuals. The DSGAalso uses an adaptive crossover strategy based on similarity mechanism, which guides the algorithm to achieve efficient population search. In addition, a task scheduling algorithm considering the feed-switching mode is designed for decoding the algorithm to generate a highquality scheme. The results of simulation experiments show that the DSGA can effectively solve the SGNPFM problem. Compared to other algorithms, the proposed algorithm not only obtains higher quality planning schemes but also has faster algorithm convergence speed. The proposed algorithm improves data trans

关键词： Profitability

来源：评论

学校读者我要写书评

暂无评论

Integrated Modeling and Optimal Operation of Multi-Energy System for Coastal Community

Integrated Modeling and Optimal Operation of Multi-Energy Sy...

引用

2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Chen, Yang Chen, Jun Liu, Chenang Liu, Guodong Ferrari, Maximiliano Sundararajan, Aditya Department of Industrial and Systems Engineering North Carolina Agricultural and Technical State University Greensboro United States Department of Electrical and Computer Engineering Oakland University RochesterMI48309 United States School of Industrial Engineeering and Management Oklahoma State University Stillwater United States Electrification and Energy Infrastructures Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

ISBN: (纸本)9781665493765

Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands. © 2023 IEEE.

关键词： Desalination

来源：评论

学校读者我要写书评

暂无评论

Evaluating Large Language Models in Interaction with Open Government Data 24

Evaluating Large Language Models in Interaction with Open Go...

引用

Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and Informatics

作者： Ioannis Maslaris Areti Karamanou Evangelos Kalampokis Konstantinos Tarabanis Database & Information Retrieval Laboratory Department of Electrical & Computer Engineering Democritus University of Thrace Xanthi Greece Information Systems Laboratory Department of Business Administration University of Macedonia Thessaloniki Greece Information Technologies Institute Center for Research & Technology HELLAS (CERTH) Thessaloniki Greece and Information Systems Laboratory Department of Business Administration University of Macedonia Thessaloniki Greece

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：