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2nd International Conference on Intelligent Medicine and Image Processing, IMIP 2020

作者： Jaffri, Nasif Raza Shi, Liu Abrar, Usama School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781450377799

In the course of image reconstruction, pixel values can scatter in a diverse way (e.g., speckling, diffraction and diffusion). Speckle is a kind of scattering that leads towards blur. Speckled signal values swing from high to low in concerned pixel. Speckle is not a random error. It removed by further processing of image using suitable deconvolution technique. The digitalization of the problem leads towards linear equations of an ill-posed matrix - - Krylov operator such as steepest descent useful tool to handle such situations. The methods discussed in this paper are modified residual norm steepest descent (MRNSD) and conjugate gradient for least-square problems (CGLS). These two techniques variation of steepest descent, hence the iterative algorithm in nature. Like many other iterative algorithms, these two practices suffer from semi-convergence. This paper focus on the deblurring of image reconstructed from the received data in industrial tomography along-with effective way to tackle semi-convergence. © 2020 ACM.

关键词： Image reconstruction

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Dynamic Weighted Anytime Bounded Cost Search Algorithm

Dynamic Weighted Anytime Bounded Cost Search Algorithm

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International Conference on Systems and Informatics (ICSAI)

作者： Jiaying Che Xiangrong Tong School Computer and Control Engineering Yantai University Yantai Shandong China

ISBN: (纸本)9781665426251

The best first algorithm like A* can find the optimal path if the time and memory is enough. However, it is usually difficult to do it in many cases. Moreover, there is always not enough time to support algorithm to find the optimal solution. On the other hand, users usually need an available solution rather than the optimal solution. Based on this, we propose Dynamic weighted Anytime Bounded Cost Search(DW-ABCS) algorithm. It combines the Bounded sub-optimal search(BSS) with the Bounded cost search(BCS) and improves the problem that BCS may not find a solution if the cost bound set is less than the optimal solution. Furthermore, in order to improve the efficiency of search, DW-ABCS algorithm dynamically modify the cost bound by considering the depth of nodes in the search process. In this way, the nodes considered become less and less and the complexity of algorithm will be lower and lower along the depth of search increasing, which improves the search efficiency significantly. In addition, the idea of anytime algorithm is used to find a better solution in every iteration. In this way, the algorithm can quickly find a sub-optimal path within suboptimal bound, and then reducing the sub-optimal bound to optimize it until the time out. If time permitted, the algorithm can converge to the optimal solution. Specially, we conducted a rigorous theoretical analysis. The various gird maps are used to verify the performance of DW-ABCS. Experimental results show that DW-ABCS algorithm can effectively identify the sub-optimal solution in different scenes.

关键词： Costs Heuristic algorithms Search problems Path planning Complexity theory Informatics

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Classification of Wind Turbine Defects based on the SqueezeNet Neural Network

Classification of Wind Turbine Defects based on the SqueezeN...

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International computer Sciences and Information Technologies (CSIT)

作者： Lesia Dubchak Anatoliy Sachenko Carsten Wolff Nadiia Vasylkiv Zenovii Bernas Department of Computer Engineering West Ukrainian National University Ternopil Ukraine Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Tele-Informatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland Dortmund University of Applied Science and Arts Dortmund Germany Department of Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

The article presents a study on classifying wind turbine defects using the SqueezeNet neural network. Wind turbines are critical for renewable energy, but defects such as corrosion, erosion, and cracks can significantly reduce their efficiency. The study proposes using image classification techniques with neural networks, particularly SqueezeNet, to automate defect detection. The compact nature of SqueezeNet makes it suitable for real-time applications with limited computing resources. Through training and testing, the network achieved an accuracy of 89%, demonstrating its potential to improve wind turbine maintenance and reduce operational costs.

关键词： Training Accuracy Costs Neural networks Real-time systems Wind turbines Maintenance Defect detection Testing Image classification

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Students’ use of large language models in engineering education: A case study on technology acceptance, perceptions, efficacy, and detection chances

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computers and Education: Artificial Intelligence 2023年 5卷

作者： Bernabei, Margherita Colabianchi, Silvia Falegnami, Andrea Costantino, Francesco Department of Mechanical and Aerospace Engineering Sapienza University of Rome Via Eudossiana 18 Rome00184 Italy Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 Rome00185 Italy Management Engineering Faculty Uninettuno University Corso Vittorio Emanuele II 39 00186 Rome Italy

The accessibility of advanced Artificial Intelligence-based tools, like ChatGPT, has made Large Language Models (LLMs) readily available to students. These LLMs can generate original written content to assist students in their academic assessments. With the rapid adoption of LLMs, exemplified by the popularity of OpenAI's ChatGPT, there is a growing need to explore their application in education. Few studies examine students' use of LLMs as learning tools. This paper focuses on the application of ChatGPT in engineering higher education through an in-depth case study. It investigates whether engineering students can generate high-quality university essays with LLMs assistance, whether existing LLMs identification systems can detect essays produced with LLMs, and how students perceive the usefulness and acceptance of LLMs in learning. The research adopts a deductive/inductive approach, combining conceptualization and empirical evidence analysis. The study involves mechanical and management engineering students, who compose essays using LLMs. The essay assessment showed good results, but some recommendations emerged for teachers and students. Thirteen LLMs detectors were tested without achieving satisfactory results, suggesting to avoid LLMs ban. In addition, students were administered a questionnaire based on constructs and items that follow the technology acceptance models available in the literature. The results contribute to qualitative evidence by highlighting possible future research and educational practices. © 2023 The Authors

关键词： Students

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Performance comparison active disturbance rejection control tuned by particle swarm optimization technique and gravitational search algorithm based load frequency control 16

Performance comparison active disturbance rejection control ...

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16th IET International Conference on AC and DC Power Transmission, ACDC 2020

作者： Abdalla, Mohammed A. Yang, Guotian Huang, Congzhi School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781839533914

In this paper, ADRC adjusted by the Gravitational Search Algorithm and Particle Swarm Optimization Technique for determination of the optimal value for parameters in load frequency control of a single- area power system. A single - area non-reheat thermal system considered to design the ADRC controller tuning PSO and GSA. The performance is comparing ADRC-GSA, ADRC-PSO controllers, and classic ADRC controller. The simulation outcomes demonstrate that the ADRC approach using the GSA algorithm provides a better overshoot and less settling time compared to those of the ADRC controller and ADRC-PSO. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： controllers

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Neural-Network-Based Recursive State Estimation for Nonlinear Networked Systems With Binary-Encoding Mechanisms

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IEEE Transactions on Neural Networks and Learning Systems 2025年第6期36卷 10072-10083页

作者： Yuhan Zhang Zidong Wang Lei Zou Wei Qian Shuxin Du College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Department of Computer Science Brunel University of London Middlesex Uxbridge U.K. College of Information Science and Technology Donghua University Shanghai China Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education Shanghai China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo China Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems School of Engineering Huzhou University Huzhou China

This work addresses the problem of recursive state estimation for networked control systems with unknown nonlinearities and binary-encoding mechanisms (BEMs). To enhance transmission reliability and reduce network resource consumption, BEMs are used to convert measurement signals into binary bit strings (BBSs) of limited length, which are then transmitted to the estimator through noisy communication channels. During transmission, random bit errors may occur in the BBSs due to channel noise. For the considered nonlinear networked control systems affected by random bit errors, a neural-network (NN)-based recursive estimation strategy is proposed, where an NN with a time-varying tuning scalar is employed to approximate the unknown nonlinearity of the networked control systems. By using the proposed strategy, the upper bounds of the estimation error of the system state and the trace of the estimation error of the NN weight (NNW) are first derived. These bounds are then minimized by recursively designing both the estimator gain matrix and the tuning scalar of the NNW. Finally, the effectiveness of the proposed estimation strategy is demonstrated through a numerical example.

关键词： Artificial neural networks State estimation Encoding Noise Networked control systems Electronic mail Symmetric matrices Estimation error Tuning Recursive estimation

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Operation of Queue and Stack by DNA Tiles

Operation of Queue and Stack by DNA Tiles

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2020 International Symposium on Energy, Environmental Science and engineering, ISEESE 2020

作者： Zhang, Xinxin Zhao, Nan Yang, Jing School of Control and Computer Engineering North China Electric Power University Beijing China

DNA is used as self-nanomaterials to assemble into specific structures. DNA tile provides a new idea for the application of DNA tile in the field of computing. Recent years, Queue and Stack are important linear data structures which are used in various software systems widely. The implementation of DNA based queue and stack has been studied continuously for many years. In the traditional DNA computing, queue and stack are mostly realized by DNA strands displacement, restriction endonuclease and ligase were used. However, as an active material, it has a high requirement for enzyme experimental conditions. The purpose of this paper is to implement queue and stack structures using non-enzyme systems. The rule of Queue is characterized by FIFO (first in first out), which allows for insertion at one end of the list and deletion at the ot ar. The rule of Stack is characterized by FILO(first in last out), which allows for insertion and deletion at one end of the list. We are aimed to implement Queue and Stack using self-assembly and disassembly via DNA Tiles. No enzymes are needed for the whole experiment. As an enzyme-free system, it provides a new method to implement stack and queue. © The Authors, publis ad by EDP Sciences, 2020.

关键词： Enzymes

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A blockchain-based trading matching scheme in energy internet 2

A blockchain-based trading matching scheme in energy interne...

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2nd ACM International Symposium on Blockchain and Secure Critical Infrastructure, BSCI 2020, Co-located with AsiaCCS 2020

作者： Lu, Xin Guan, Zhitao School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781450376105

With the advent of the Industry 4.0 era, the energy industry system revolution will also face new challenges. Against the backdrop of the global energy crisis, renewable energy has received great attention from countries around the world. Due to the characteristics of geographical dispersion, randomness, volatility and uncontrollability of renewable energy, the centralized traditional electrical energy networks cannot meet the management requirements of large-scale access to renewable energy. The emergence of the energy internet has enabled the effective use of renewable energy. As a distributed trading and data management technology, blockchain solves the problem of distributed electrical energy trading in the energy Internet. However, the distributed energy trading based on blockchain cannot satisfy the rational matching of trading objects. Therefore, we propose a blockchain-based electrical energy trading system BC-TMS Blockchain-based trading matching system, which can reasonably match trading objects according to the user's personalized needs and maximize the benefits of both parties to the trading. At the same time, the system also provides a certain degree of privacy protection. Finally, through security and application prospect analysis, we prove the usability and practicability of our proposed scheme. © 2020 ACM.

关键词： Blockchain

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Insulating materials for realising carbon neutrality:Opportunities,remaining issues and challenges

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High Voltage 2022年第4期7卷 610-632页

作者： Chuanyang Li Yang Yang Guoqiang Xu Yao Zhou Mengshuo Jia Shaolong Zhong Yu Gao Chanyeop Park Qiang Liu Yalin Wang Shakeel Akram Xiaoliang Zeng Yi Li Fangwei Liang Bin Cui Junpeng Fang Lingling Tang Yulin Zeng Xingtao Hu Jiachen Gao Giovanni Mazzanti Jinliang He Jianxiao Wang Davide Fabiani Gilbert Teyssedre Yang Cao Feipeng Wang Yunlong Zi The State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Simpson Querrey Institute Northwestern UniversityEvanstonIllinoisUSA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA Department of Information Technology and Electrical Engineering ETH ZürichZürichSwitzerland School of Electrical and Information Engineering Tianjin UniversityTianjinChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina College of Electrical Engineering Sichuan UniversityChengduChina Shenzhen Institute of Advanced Technology Chinese Academy of Sciences ShenzhenShenzhenChina School of Electrical Engineering Wuhan UniversityWuhanChina School of Integrated Circuits Tsinghua UniversityBeijingChina Jiangsu Jinxin Electric Appliance Co.Ltd. YangzhouChina Tai'an Tiancheng Safety Evaluation Co. Ltd.Tai'anChina Department Electrical Electronic and Information EngineeringUniversity of BolognaBolognaItaly National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijingChina Laplace Paul Sabatier Universityand CNRSToulouseFrance Electrical and Computer Engineering University of ConnecticutStorrsConnecticutUSA State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqingChina Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)GuangzhouChina De

The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment *** material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and *** goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first *** engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are *** materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being *** the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material *** is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality *** authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.

关键词： neutral insulation extreme

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Distributed Economic Model Predictive control of Standalone Wind/Solar/Battery Power System

Distributed Economic Model Predictive Control of Standalone ...

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第32届中国过程控制会议(CPCC2021)

作者： Xuan Wang Xiaobing Kong Xiangjie Liu School of Control and Computer Engineering North China Electric Power University

Regarding the large-scale,geographically dispersed standalone wind/solar/battery power generation system,this paper constituted a distributed economic model predictive control(DEMPC).In this DEMPC,the real-time economic optimization can be achieved by solving the cost function which represents the priority of solar power,attenuating fluctuations of battery power and avoiding the frequent charge/discharge cycle in *** satisfaction of load demand is expressed in terms of coupling constraint and have to be satisfied at all *** results demonstrate the advantages and efficiency of the proposed method.

关键词： Distributed economic model predictive control standalone wind/solar/battery system economic cost function

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