检索结果-内蒙古大学图书馆

IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： Fan Wang Ruihong Jiang Yuan Liu Tingnan Bao Mugen Peng State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Zhejiang Laboratory Research Center for Space Computing System Hangzhou China School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada

ISBN: (数字)9798350362312

ISBN: (纸本)9798350362329

The rising demand for reliable, high-bandwidth satellite communications in far-reach areas drives the integration of low earth orbit (LEO) satellites into future 6G networks. In this paper, we investigate the deployment of reconfigurable intelligent surface (RIS) technology and rate splitting multiple access (RSMA) within LEO satellite systems to improve communication quality and system capacity. We derive closed-form expressions for outage probability (OP) and reliable throughput that validate the theoretical advantages of these technologies under various signal-to-noise ratio conditions. Numerical results demonstrate that, compared with traditional space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) approaches, our RSMA and RIS-integrated framework significantly can reduce OP and enhance reliable throughput with an appropriate power-splitting factor, showcasing its superiority in RIS-enabled satellite communication scenarios.

关键词： NOMA Satellites Closed-form solutions computer network reliability Low earth orbit satellites Reconfigurable intelligent surfaces Reliability theory Throughput Multiaccess communication Satellite communications

来源：评论

学校读者我要写书评

暂无评论

A Surveillance system Utilizing mmWave-FMCW Radar for Restricted Control Area

A Surveillance System Utilizing mmWave-FMCW Radar for Restri...

引用

International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Nattakarn Shutimarrungson Seksan Eiadkaew Akkarat Boonpoonga Krit Athikulwongse Suramate Chalermwisutkul Department of Business Computer Mahasarakham Business School Mahasarakham University Maha Sarakham Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering Research Center of Innovation Digital and Electromagnetic Technology (iDEMT) King Mongkut's University of Technology North Bangkok Bangkok Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathumthani Thailand Communication and Smart System Engineering The Sirindhorn International Thai- German Graduate School of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

In this paper, we introduce a surveillance system utilizing mmWave-FMCW radar designed for restricted control areas. The experiment, conducted in our laboratory, defines the restricted control area parameters. Employing the TI-IWR6843AOPEVM model, operating at 60–64 GHz, and providing point cloud and Doppler information, we assumed walking paths for testing, partitioning scenarios into four distinct cases to simulate real-world scenarios. system performance evaluation, assessed through confusion matrices, demonstrates an achieved accuracy of up to 76.9%. Notably, errors are mainly caused by multipath effects due to static objects within the testing environment.

关键词： Point cloud compression Measurement Accuracy Surveillance system performance Radar tracking Doppler radar

来源：评论

学校读者我要写书评

暂无评论

A LiDAR-Assist Yaw Misalignment Compensation Method Based on Machine Learning Algorithms

A LiDAR-Assist Yaw Misalignment Compensation Method Based on...

引用

Chinese Control Conference (CCC)

作者： Pei Chen Zhongwei Lin Zihan Zhang Zhen Xie State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing P. R. China

Yaw misalignment is common in the yaw system control of wind turbines, resulting in reduced power generation efficiency and increased load. The advantage of LiDAR is that the accuracy of wind measurement is greatly improved, while its disadvantage is that the cost remains high. In this paper, an efficient machine learning method for estimating LiDAR measurement, XGBoost, is used to establish the data-driven wind turbine yaw misalignment compensation framework. To choose a suitable algorithm, four machine learning algorithms are studied, namely Linear Regression, Random Forest, Gradient Boosting and XGBoost. Moreover, to verify the effectiveness of the proposed method, a 2MW WT was taken as the research object for filed testing, and the power generation was quantitatively evaluated under the three strategies of wind vane control, LiDAR control and ML algorithm control. The results show that the proposed yaw misalignment compensation method is feasible for field application. In this way, the yaw-to-wind error can be mitigated even after the LiDAR is removed.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Ordinal Data Science

arXiv

引用

arXiv 2023年

作者： Stumme, Gerd Dürrschnabel, Dominik Hanika, Tom Knowledge & Data Engineering Group Research Center for Information System Design Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Computer Science University of Hildesheim Germany Berlin School of Library and Information Science Humboldt-Universität zu Berlin Germany

Order is one of the main instruments to measure data. In this paper, we will therefore discuss difthe relationship between objects in (empirical) data. ferent means for measuring and ‘calculating’ with However, compared to methods that use numerical ordinal structures — a specific class of directed properties of objects, the amount of ordinal meth- graphs — and show how to infer knowledge from ods developed is rather small. One reason for this is them. Our aim is to establish Ordinal Data Science the limited availability of computational resources as a fundamentally new research agenda. Besides in the last century that would have been required cross-fertilization with other cornerstone machine for ordinal computations. Another reason — partic- learning and knowledge representation methods, a ularly important for this line of research — is that broad range of disciplines will benefit from this en-order-based methods are often seen as too mathe- deavor, including, psychology, sociology, economics, matically rigorous for applying them to real-world web science, knowledge engineering, *** Codes 03G10, 06A15, 68T27, 68T30 Copyright © 2023, The Authors. All rights reserved.

关键词： Data Science

来源：评论

学校读者我要写书评

暂无评论

FMCW Radar-Based Enhancing Moving Target Positioning Accuracy in Spectrogram Mapping

FMCW Radar-Based Enhancing Moving Target Positioning Accurac...

引用

International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

In this paper, we propose a methodology aimed to enhancing the accuracy of moving target positioning using FMCW radar within spectrogram mapping. Utilizing a 10 GHz operating frequency, the FMCW radar effectively detects moving targets. However, the interpretation of intermediate frequency (IF) signals posed challenges due to multiple reflections and resulting ambiguous distances between objects. For solving this problem, we propose two steps of solution: employing an enveloping method and normalization of the IF signal. This process can extract maximum amplitude peaks specific to the target. Experimental validation involved detecting a drone moving away from the radar. Comparative analysis pre and post signal processing in spectrogram terms demonstrate the efficacy of our technique. Furthermore, verification of the detection range of radar was conducted using the GSM-015 GNSS speed meter. Results confirm the accuracy of the positioning capabilities of radar, emphasizing the effectiveness of the proposed approach.

关键词： Visualization Accuracy Refining Radar detection Radar Radar antennas Reflection

来源：评论

学校读者我要写书评

暂无评论

Review of 3D Networks-On-Chip Simulators and Plugins

Review of 3D Networks-On-Chip Simulators and Plugins

引用

2021 IEEE Conference on Postgraduate Research in Microelectronics and Electronics, PRIMEASIA 2021

作者： Al-Hchaimi, Ahmed Abbas Jasim Flayyih, Wameedh Nazar Hashim, Fazirulhisyam Rusli, Mohd Shahrizal Rokhani, Fakhrul Zaman Universiti Putra Malaysia Department of Computer and Communication Systems Engineering Malaysia University of Baghdad College of Engineering Iraq Universiti Teknologi Malaysia School of Electrical Engineering Malaysia Universiti Putra Malaysia System-On-Chip Research Center Malaysia

ISBN: (纸本)9781665439374

A comprehensive review focuses on 3D network-on-chip (NoC) simulators and plugins while paying attention to the 2D simulators as the baseline is presented. Discussions include the programming languages, installation configuration, platforms and operating systems for the respective simulators. In addition, the simulator's properties and plugins for design metrics evaluations are addressed. This review is intended for the early career researchers starting in 3D NoC, offering selection guidelines on the right tools for the targeted NoC architecture, design, and requirements. © 2021 IEEE.

关键词： Network-on-chip

来源：评论

学校读者我要写书评

暂无评论

MPC Implementation for Optimal Active Power Control of Large-Scale Wind-PV-Battery Hybrid system

MPC Implementation for Optimal Active Power Control of Large...

引用

Chinese Control Conference (CCC)

作者： Zihan Zhang Zhongwei Lin Ze Zhao Jiawei Zhou Chenzhi Qu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing P. R. China

This paper investigates the operational strategy for real-time optimal active power control of large-scale wind-PV-battery hybrid system. The MPC strategy is established with objective, forecast models and constraints for active power control of wind-PV-battery hybrid system, which simultaneously maximizes tracking accuracy and minimizes settling time. To guarantee the industrial reliability, the corresponding optimization solver and control architecture have been specifically developed and designed. Hardware-in-loop (HIL) experiments are conducted using the real-time digital simulator (RTDS) and programmable logic controllers (PLCs). Under different operating scenarios, HIL-RTDS testing results demonstrate that the MPC strategy significantly improves the tracking speed and accuracy compared to the conventional strategy in both normal and abnormal operating scenarios, which also sustain the feasibility of industrial implementation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Power Loss Analysis of Three-Phase Four-leg Four-Wire Inverter Using SiC/Si HyS 2

Power Loss Analysis of Three-Phase Four-leg Four-Wire Invert...

引用

2nd IEEE China International Youth Conference on electrical engineering, CIYCEE 2021

作者： Jing, Zhengting Fu, Yongsheng Chen, Jianfei Ren, Haipeng Xi'An Technological University School of Electrical Information Engineering Xi'an710021 China Xi'An Technological University School of Mechatronic Engineering And the School of Electrical Information Engineering Xi'an710021 China University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States Xi'An Technological University School of Mechatronic Engineering Xi'an710021 China Shaanxi Key Laboratory of Comple System Control and Intelligent Information Xi an University of Technology Xi'an710048 China

ISBN: (纸本)9781665400640

Three-phase four-leg four-wire voltage source inverter (3P4L4W VSI) attracts more attention in many power electronics applications due to its flexibility for both balanced and unbalanced loads, where the power efficiency is a critical point. Conventional Si semiconductor devices suffer from large switching loss due to large parasitic capacitances and thus limit its switching frequency. As a result, it further limits the power density and efficiency improvement. The SiC/Si hybrid switch formed by SiC-MOSFET and Si-IGBT in parallel (SiC/Si HyS) can improve the switching frequency with high efficiency and low cost, which helps to design a power converter with high power density and high efficiency. However, the application of SiC/Si HyS in 3P4L4W faces some challenges, such as the drive circuit design, the proper delay selection, etc.. In this paper, a SiC/Si HyS based 3P4L4W VSI is introduced and the optimal turn-off time delay selection for the SiC/Si HyS used in 3P4L4W VSI is analyzed. A systematical way to calculate the power loss in the SiC/Si HyS is presented. A 5-kW/50kHz 3P4L4W VSI is taken as an example for validating the theory and method. It is found the peak efficiency of the 3P4L4W VSI is 97.5%, and the unbalanced phase load leads to more power loss and degrade the efficiency. The work in this paper provides practical guidance for a SiC/Si HyS based 3P4L4W VSI inverter design. © 2021 IEEE.

关键词： Silicon carbide

来源：评论

学校读者我要写书评

暂无评论

Investigation of the Robustness of XAI-Based Federated Learning Against Adversarial Attacks for Smart Grid False Data Detection

引用

IEEE Internet of Things Journal 2025年

作者： Elgarhy, Islam Badr, Mahmoud M. Mahmoud, Mohamed Ni, Jianbing Alsabaan, Maazen Alshawi, Tariq Western Carolina University School of Engineering and Technology Cullowhee 28723 NC United States Ain Shams University Faculty of Computer and Information Sciences Department of Computer System Cairo 11566 Egypt Benha University Faculty of Engineering at Shoubra Department of Network and Computer Security College of Engineering SUNY Polytechnic Institute Department of Electrical Engineering Utica Cairo 11672 Egypt Department of Electrical and Computer Engineering Tennessee Tech. University Cookeville 38505 TN United States Queen’s University Department of Electrical and Computer Engineering Ingenuity Labs Research Institute Smith Engineering Kingston K7L 3N6 ON Canada King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh 11451 Saudi Arabia King Saud University College of Engineering Department of Electrical Engineering Riyadh 11421 Saudi Arabia

Federated Learning (FL) enables decentralized training of machine learning (ML) models, making it a valuable approach for detecting false data in smart power grids (SGs) to enhance grid stability while protecting consumers privacy. However, FL-based ML models remain vulnerable to adversarial attacks during both training and inference phases, which can compromise data security. To address these vulnerabilities, we first investigate the robustness of a novel FL-based false data detection approach using Explainable Artificial Intelligence (XAI), referred to as XAI-based FL detection. This approach utilizes explanations of consumers power consumption data, rather than raw data, during the training process. We assess the robustness of the XAI-based FL detection compared to traditional data-driven FL detection against two types of adversarial attacks: Gradient Inversion attacks in the training phase, where adversaries reconstruct private data from shared gradients, and Evasion attacks in the inference phase, where adversaries subtly modify input data to deceive the detection model. Then, we propose a secure XAI-based FL detector with adversarial training to defend against both attack types. The key idea is that XAI helps mask model gradients during training because XAI-generated explanations remain nearly identical across different samples. Therefore, attackers struggle to accurately reconstruct the original training data, even if they obtain precise explanations using gradient inversion attacks. Additionally, XAI effectively distinguishes between benign and malicious samples. When combined with adversarial training, XAI strengthens model robustness against evasion attacks without compromising accuracy, effectively resolving the trade-off between security and performance. Our proposed detector reduced the success rate of evasion attacks from 94.99% to 29.11 explanations, and further to 0% with adding adversarial training. It also increased the mean square error for gradie

关键词： Adversarial Attacks Electricity Theft Evasion Explainable Artificial Intelligence False Data Detection Federated Learning Gradient Inversion Privacy Preservation Smart Grid

来源：评论

学校读者我要写书评

暂无评论

Differentially Private Deep Q-Learning for Pattern Privacy Preservation in MEC Offloading

arXiv

引用

arXiv 2023年

作者： Gan, Shuying Siew, Marie Xu, Chao Quek, Tony Q.S. School of Information Engineering Northwest A&F University Shaanxi Yangling China Department of Electrical and Computer Engineering Carnegie Mellon University United States Information System Technology and Design Pillar Singapore University of Technology and Design Singapore

Mobile edge computing (MEC) is a promising paradigm to meet the quality of service (QoS) requirements of latency-sensitive IoT applications. However, attackers may eavesdrop on the offloading decisions to infer the edge server’s (ES’s) queue information and users’ usage patterns, thereby incurring the pattern privacy (PP) issue. Therefore, we propose an offloading strategy which jointly minimizes the latency, ES’s energy consumption, and task dropping rate, while preserving PP. Firstly, we formulate the dynamic computation offloading procedure as a Markov decision process (MDP). Next, we develop a Differential Privacy Deep Q-learning based Offloading (DP-DQO) algorithm to solve this problem while addressing the PP issue by injecting noise into the generated offloading decisions. This is achieved by modifying the deep Q-network (DQN) with a Function-output Gaussian process mechanism. We provide a theoretical privacy guarantee and a utility guarantee (learning error bound) for the DP-DQO algorithm and finally, conduct simulations to evaluate the performance of our proposed algorithm by comparing it with greedy and DQN-based algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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：