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H∞ state Estimation for Stochastic Jumping Neural Networks with Fading Channels Over a Finite-Time Interval

Neural Processing Letters 2019年第1期50卷 1-18页

作者： Shen, Liang Shen, Hao Gao, Mingming Liu, Yajuan Huang, Xia School of Electrical and Information Engineering Anhui University of Technology Ma’anshan243002 China School of Metallurgical Engineering Anhui University of Technology Ma’anshan243002 China The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

In the work, a class of Markov jump neural networks in the discrete-time domain with fading channels are taken into account. The main aim is to investigate the H∞ state estimation issue when the Rice fading occurs in measured networks. In the first place, the analyses of the finite-time boundedness and the H∞ performance for the estimation error system with the aid of finite-time stability theory are presented. Some conditions which guarantee the solvability of the addressed problem are established. Furthermore, by applying an unique decoupling method, the gains of the presented estimator are obtained under the feasible solutions of the conditions derived before. Finally, the validity of the presented approach is verified by a numerical example. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

关键词： state estimation

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一款X86架构处理器保护模式及长模式下复杂指令的验证

一款X86架构处理器保护模式及长模式下复杂指令的验证

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第七届中国测试学术会议

作者： Hao Shuai 郝帅 Lv Tao 吕涛 Li Xiao Wei 李晓维 State Key Laboratory of Computer System and Architecture Chinese Academy of Sciences Beijing 10019 中国科学院计算技术研究所计算机体系结构国家重点实验室北京100190

本文对一款X86架构处理器的复杂指令在保护模式以及长模式下进行了功能验证。通过对X86架构处理器运行模式进行分析，搭建了进入保护模式以及长模式(长模式包括兼容模式及64bit模式)的模板，为指令集在这3种模式下进行功能验证奠定基础... 详细信息

本文对一款X86架构处理器的复杂指令在保护模式以及长模式下进行了功能验证。通过对X86架构处理器运行模式进行分析，搭建了进入保护模式以及长模式(长模式包括兼容模式及64bit模式)的模板，为指令集在这3种模式下进行功能验证奠定基础。基于对X86指令访存次数及访存难度的研究，将指令集分为一般指令、一般复杂指令与复杂指令，并对复杂指令：CALL FAR、JUMP FAR、RETURN FAR、INT和IRET进行了定向功能验证，编写测试激励800余条，实现功能点覆盖率100％，发现设计错误32处。

关键词：集成电路测试复杂指令运行模式功能验证

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Analysis of Malicious Injection Attack on CAN Data in In-Vehicle Network Based on Driving Behavior and Velocity

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Ruan Jian Xue Bao/Journal of Software 2017年 28卷 1-10页

作者： Ding, Nan Liang, Wen-Bin Xu, Li Song, Cai-Xia Tan, Guo-Zhen School of Computer Science and Technology Dalian University of Technology Dalian116023 China Liaoning Engineering Technology Research Center of IoT and Cooperative Sensing Dalian University of Technology Dalian116023 China State Key Laboratory of Software Architecture Neusoft Corporation Shenyang110179 China

Because of the opening of In-vehicle network, there are several important problems to be dealt with, such as the security and validity of data. Firstly, the article builds a construct model based on driving behavior and speed. Secondly, it makes an analysis of preventing data injection by using the construct model above and the naive Bayesian network classifier, so as to take effective measures to guarantee the vehicle security. In the end, an experimental simulation is carried out to prove that the proposed method can effectively improve the accuracy of data quality analysis and lower the false rate as well. © Copyright 2017, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Bayesian networks

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Research on collaborative frequency regulation control strategy of wind farm based on decentralized exit

Research on collaborative frequency regulation control strat...

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8th Renewable Power Generation Conference (RPG 2019)

作者： Y. H. Ren P. Song X. S. Wang R. F. Shi School of Control and Computer Engineering North China Electric Power University Beijing 102206 PR China State Grid Jibei Electric Power Research Institute North China Electric Power Research Institute Co. Ltd. Beijing 100045 China Grid-connected Operation Technology for Wind-Solar Storage Hybrid System State Grid Corporation Key Laboratory Beijing 100045 China State Grid Jibei Electric Power Research Institute North China Electric Power Research Institute Co. Ltd. Beijing 100045 China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

When the wind turbine adopts the rotor inertia control to participate in grid frequency regulation, it is easy to cause the second frequency drop, which will be more serious when applied to the wind farm. To solve this problem, the influence of wind speed on the unit's ultimate support time under the constant power support mode is analyzed quantitatively and wind turbine recovery time is defined. The functional relationship between the unit's support time and recovery time suitable for engineering application is given. A wind farm frequency regulation optimization model aiming at the longest supporting time of all units in the whole station is established, and the wind farm coordinated frequency regulation control strategy based on decentralized exit is proposed, taking full account of capacity differences of units under different working conditions. Simulation examples show that the real-time coordination of the exit of the wind turbine frequency regulation can effectively alleviate the secondary frequency drop problem of a wind farm.

关键词：

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Soybeannet: Transformer-Based Convolutional Neural Network for Soybean Pod Counting from Unmanned Aerial Vehicle (Uav) Images

SSRN

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SSRN 2023年

作者： Li, Jiajia Magar, Raju Thada Chen, Dong Lin, Feng Wang, Dechun Yin, Xiang Zhuang, Weichao Li, Zhaojian Department of Electrical and Computer Engineering Michigan State University East LansingMI United States Department of Plant Soil and Microbial Sciences Michigan State University East LansingMI United States Environmental Institute & Link Lab University of Virginia CharlottesvilleVA United States Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Southeast University Nanjing China Department of Mechanical Engineering Michigan State University East LansingMI48824 United States

Soybean is a critical source of food, protein, and oil, and thus has received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques. Within this context, soybean pod counting plays an essential role in understanding and optimizing production. Despite recent advancements, the development of a robust pod-counting algorithm capable of performing effectively in real-field conditions remains a significant challenge This paper presents a pioneering work of accurate soybean pod counting utilizing unmanned aerial vehicle (UAV) images captured from actual soybean fields in Michigan, USA. Specifically, this paper presents SoybeanNet, a novel point-based counting network that harnesses powerful transformer backbones for simultaneous soybean pod counting and localization with high accuracy. In addition, a new dataset of UAV-acquired images for soybean pod counting was created and open-sourced, consisting of 113 drone images with more than 260k manually annotated soybean pods captured under natural lighting conditions. Through comprehensive evaluations, SoybeanNet demonstrates superior performance over five state-of-the-art approaches when tested on the collected images. Remarkably, SoybeanNet achieves a counting accuracy of 84.51% when tested on the testing dataset, attesting to its efficacy in real-world scenarios. The publication also provides both the source at https://***/JiajiaLi04/Soybean-Pod-Counting-from-UAV-Images and the labeled soybean dataset at https://***/datasets/jiajiali/uav-based-soybean-pod-images, offering a valuable resource for future research endeavors in soybean pod counting and related fields. © 2023, The Authors. All rights reserved.

关键词： Statistical tests

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Blockchain based Consensus Checking in Cloud Storage

Blockchain based Consensus Checking in Cloud Storage

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International Symposium on Autonomous Decentralized systems (ISADAS)

作者： Guanqiu Qi Zhiqin Zhu Matthew Haner Jaesung Sim Jian Sun Yi Chai Yinong Chen Li Yongfu Mathematics and Computer Information Science Mansfield University of Pennsylvania Mansfield PA 16933 USA College of Automation Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Electronic and Information Engineering Southwest University Chongqing 400715 China Ministry of Education Key Laboratory of Complex System Safety and Control (Chongqing University) Chongqing 400044 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287 USA

ISBN: (数字)9781728116723

ISBN: (纸本)9781728116730

In cloud computing, data is duplicated to prevent data loss. One way to achieve data consistency in such a distributed computing systems is to use a blockchain. Based on practical Byzantine fault tolerance (PBFT), a specific type of blockchain, this paper proposes a synchronous Byzantine fault tolerance (SBFT) algorithm that not only maintains data consistency, but also has much higher efficiency than other general blockchain algorithms. We provide experimental results that demonstrate the algorithm's data consistency, efficiency, and reliability.

关键词： Cloud computing Fault tolerance Fault tolerant systems Peer-to-peer computing

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SoybeanNet: Transformer-Based Convolutional Neural Network for Soybean Pod Counting from Unmanned Aerial Vehicle (UAV) Images

arXiv

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arXiv 2023年

作者： Li, Jiajia Magar, Raju Thada Chen, Dong Lin, Feng Wang, Dechun Yin, Xiang Zhuang, Weichao Li, Zhaojian Department of Electrical and Computer Engineering Michigan State University East LansingMI United States Department of Plant Soil and Microbial Sciences Michigan State University East LansingMI United States Environmental Institute Link Lab University of Virginia CharlottesvilleVA United States Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Southeast University Nanjing China Department of Mechanical Engineering Michigan State University East LansingMI48824 United States

Soybean is a critical source of food, protein and oil, and thus has received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques. Within this context, soybean pod counting plays an essential role in understanding and optimizing production. Despite recent advancements, the development of a robust pod-counting algorithm capable of performing effectively in real-field conditions remains a significant challenge This paper presents a pioneering work of accurate soybean pod counting utilizing unmanned aerial vehicle (UAV) images captured from actual soybean fields in Michigan, USA. Specifically, this paper presents SoybeanNet, a novel point-based counting network that harnesses powerful transformer backbones for simultaneous soybean pod counting and localization with high accuracy. In addition, a new dataset of UAV-acquired images for soybean pod counting was created and open-sourced, consisting of 113 drone images with more than 260k manually annotated soybean pods captured under natural lighting conditions. Through comprehensive evaluations, SoybeanNet demonstrates superior performance over five state-of-the-art approaches when tested on the collected images. Remarkably, SoybeanNet achieves a counting accuracy of 84.51% when tested on the testing dataset, attesting to its efficacy in real-world scenarios. The publication also provides both the source code (https://***/JiajiaLi04/Soybean-Pod-Counting-from-UAV-Images) and the labeled soybean dataset (https://***/datasets/jiajiali/uav-based-soybean-pod-images), offering a valuable resource for future research endeavors in soybean pod counting and related fields. © 2023, CC BY-NC-SA.

关键词： Statistical tests

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Reconfigurable Intelligent Surface Assisted High-Speed Train Communications: Coverage Performance Analysis and Placement Optimization

arXiv

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arXiv 2023年

作者： Liu, Changzhu He, Ruisi Niu, Yong Han, Zhu Ai, Bo Gao, Meilin Ma, Zhangfeng Wang, Gongpu Zhong, Zhangdui The State Key Laboratory of Advanced Rail Autonomous Operation The School of Electronics and Information Engineering The Frontiers Science Center for Smart High-speed Railway System The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China The Tsinghua Space Center the Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100091 China The College of Information Engineering Shaoyang University Shaoyang422000 China The Beijing Key Lab of Transportation Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

Reconfigurable intelligent surface (RIS) emerges as maximization problem is formulated to facilitate RIS discrete an efficient and promising technology for the next wireless phase design and RIS placement optimization, which is subject generation networks and has attracted a lot of attention owing to coverage probability constraint. Simulation results validate to the capability of extending wireless coverage by reflecting that better coverage performance and higher travel distance signals toward targeted receivers. In this paper, we consider can be achieved with deployment of RIS. The impacts of some a RIS-assisted high-speed train (HST) communication system key system parameters including transmission power, signal-to-to enhance wireless coverage and improve coverage probability. noise ratio threshold, number of RIS elements, number of RIS First, coverage performance of the downlink single-input-single- quantization bits, horizontal distance between base station and output system is investigated, and the closed-form expression RIS, and speed of HST on system performance are investigated. of coverage probability is derived. Moreover, travel distance In addition, it is found that RIS can well improve coverage probability with limited power consumption for HST communications. Copyright © 2023, The Authors. All rights reserved.

关键词： Railroads

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Control-Oriented Wind Farm Wake Modeling with Near Wake Performance and LES Validation

Control-Oriented Wind Farm Wake Modeling with Near Wake Perf...

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Chinese Automation Congress (CAC)

作者： Zhen Xie Zhongwei Lin Zhenyu Chen Chuanxi Wang Qingru Cui Gengda Li Weidong Wang Daizhen Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control Computer and Engineering North China Electric Power University Beijing P. R. China Guodian New Energy Technology Research Institute Co. Ltd Beijing P. R. China CHN ENERGY (Shandong) New Energy Co. Ltd. Jinan P. R. China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

With the deepening research on wind farms, wake effects have gradually been paid attention to and used in wind farm optimization. During this development, the engineering wake models are adopted, which could be further improved in modeling accuracy. This paper adopts a control-oriented wake model to improve the modeling accuracy, especially in the near wake region. A double-Gaussian wake model is incorporated with appropriate wake deflection and combination models and a vertical wind profile function. Based on a Large-eddy simulated dataset, the proposed model is adopted and verified. The widely-used Gaussian wake model is also adopted and compared with the proposed model. Results show good agreement between the presented model and LES results, especially in the focused near wake region.

关键词： Wind turbines Computational modeling Wind farms Rotors Electron tubes Wind speed Mathematical model

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Wind Process Pattern Forecasting Based Ultra-Short-Term Wind Speed Hybrid Prediction

SSRN

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SSRN 2022年

作者： Wang, Fei Tong, Shuang Sun, Yiqian Xie, Yongsheng Zhen, Zhao Li, Guoqing Cao, Chunmei Duić, Neven Liu, Dagui Department of Electrical Engineering North China Electric Power University Baoding071003 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Hebei Key Laboratory of Distributed Energy Storage and Microgrid North China Electric Power University Baoding071003 China Dispatch and Control Center State Grid Xinjiang Electric Power Co. Ltd Urumqi830018 China Department of Mathematics and Physics North China Electric Power University Baoding071003 China Department of Energy Power and Environmental Engineering Faculty of Mechanical Engineering and Naval Architecture University of Zagreb Ivana Lucica 5 ZagrebHR-10000 Croatia

Wind power has received extensive attention due to its superiorities of clean and pollution-free. However, because of the randomness and volatility of wind power, accurate power prediction is needed to help its consumption. Wind speed is the key to wind power prediction. To tackle the deficiency of traditional prediction methods such as lacking of master the variation trend of wind speed, an ultra-short-term wind speed hybrid prediction method based on wind process pattern forecasting is proposed in this paper. Firstly, a wind process (WP) division method considering the influence of wind speed on the operation state, mode switch and output power of wind turbine is proposed. Secondly, according to the operating characteristics of the wind turbine, all the WPs is classified into different wind process patterns (WPP), and the effectiveness of the classification is verified. Then, the Adaboost classification algorithm is used to forecast the WPP of the next four hours. Finally, the wind speed hybrid prediction model of each pattern is established, the corresponding model is automatically selected based on WPP to predict the wind speed. Simulation results show that the proposed model can reliably forecast future WPP and the wind speed prediction accuracy is better than conventional models. © 2022, The Authors. All rights reserved.

关键词： Wind

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