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8th EAI International Conference on Advancement of Science and technology, ICAST 2020

作者： Workineh, Tewodros G. Yetayew, Tefera T. Egziabher, Assefa G. Faculty of Electrical and Computer Engineering Bahir Dar Institute of Technology Bahir Dar University Bahir Dar Ethiopia School of Electrical Engineering and Computing Electrical Power and Control Engineering Adama Science and Technology University Adama Ethiopia

ISBN: (纸本)9783030806200

This paper presents the control scheme Modeling and analysis of three phase voltage switching inverter in using Space vector Pulse Width Modulation (SVPWM) technique for induction motor driven three-wheel electric vehicles. Induction motors are now widely applied in electric vehicle industries as the replacement of internal combustion engine due to the over striking price and environmental concerns. Performance of speed, direction and torque control for three wheel electric drives (Bajaj) has been studied. Better dc utilization for medium performance drive system, more efficient use of DC supply voltage, produce less ripples makes space vector pulse width modulation technique a good choice for this work. By keeping the ratio of stator voltage to frequency constant, this system tipscan adjust the speed of the motor by control the frequency and amplitude of the stator voltage. Transfer model of induction motor, vehicle dynamic model and voltage source inverter type SVPWM model are designed and simulated using matlab Simulink. control scheme visual realization has been done though Protues and Arduino IDE software. To demonstrate good performance of SVPWM based induction motor for three wheel drive, parameters such has stator current, rotor current, torque and speed as well as switching patter of the inverter waveforms have been displayed and analyzed. © 2021, ICST institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Induction motors

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Rethinking development and major research plans of Industrial Internet in China

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Fundamental Research 2024年第1期4卷 3-7页

作者： Chunxiao Jiang Yang Cong Jiming Chen Chenghong Wang Guozheng Wu Ruizhen Zhao Zhiheng Wang Bin Xiao Ting Chen Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Tsinghua Space Center Tsinghua UniversityBeijing 100084China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Division III Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Division II Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Chongqing Key Laboratory of Image Cognition School of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqing 400065China University of Electronic Science and Technology of China Chengdu 611731China

This paper gives a definition of the Industrial Internet and expounds on the academic connotation of the future Industrial *** this foundation,we outline the development and current status of the Industrial Internet in China and ***,we detail the avant-garde paradigms encompassed within the National Natural Science Foundation of China(NSFC)’s“Future Industrial Internet Fundamental Theory and Key Technologies”research plan and its corresponding management *** research initiative endeavors to enhance interdisciplinary collaborations,aiming for a synergistic alignment of industry,academia,research,and practical *** primary focus of the research plan is on the pivotal scientific challenges inherent to the future industrial *** is poised to traverse the“first mile”,encompassing foundational research and pioneering innovations specific to the industrial internet,and seamlessly bridges to the“last mile”,ensuring the effective commercialization of scientific and technological breakthroughs into tangible industrial market *** anticipated contributions from this initiative are projected to solidify both the theoretical and practical scaffolding essential for the cultivation of a globally competitive industrial internet infrastructure in China.

关键词： Industrial Internet Academic connotation Major research plan Scientific problem Policy advice

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Custom-made Near Infrared Spectroscope as a Tool for Obtaining Information Regarding the Brain Condition

Custom-made Near Infrared Spectroscope as a Tool for Obtaini...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Anna Wieczorek Edward Jacek Gorzelańczyk Mariusz Pelc Saravanakumar Duraisamy Luis A. Leiva Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg

We can obtain valuable information about the human brain using functional Near Infrared Spectroscopy (fNIRS). This paper describes the theoretical basis associated with this neuroimaging method through a custom-made prototype of a single-channel fNIRS device. The optodes were soldered to a milled Printed Circuit Board (PCB) and enclosed in a 3D printed housing. Using this fNIRS device, we performed a preliminary study to measure emotional responses from participants. Our results suggest that fNIRS allows for accurate measurement of emotions evoked by positive and negative images.

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Performance Analysis of a QoS System with WFQ Queuing Using Temporal Petri Nets 1

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20th International Conference on computer Information Systems and Industrial Management Applications, CISIM 2021

作者： Strzęciwilk, Dariusz Nafkha, Rafik Zawiślak, Rafal Institute of Information Technology University of Life Sciences Nowoursynowska Street 159 Warsaw02-787 Poland Faculty of Electrical Electronic Computer and Control Engineering Lodz University of Technology Stefanowskiego 18/22 Lódź Poland

ISBN: (数字)9783030843403

ISBN: (纸本)9783030843397

The paper presents the results of analysis and modelling of differentiated services using Petri nets. Mechanisms and methods of implementation of QoS (Quality of Service) services in packet networks are discussed. A network model supporting data transfers related to different traffic classes was designed and studied. Traffic shaping mechanisms based on WFQ (Weighted Fair Queuing) system used in QoS were studied. The impact of the traffic shaping mechanism was studied and the performance of the modelled systems was evaluated. The application of simulation tools in the form of TPN (Temporal Petri Nets) was aimed at verifying the traffic shaping mechanisms and evaluating the performance of the studied WFQ system. Our simulation results show that the number of high-priority flows have a critical impact on average waiting times and queue length. © 2021, Springer Nature Switzerland AG.

关键词： Petri nets

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Network Protocol Recognition Based on Convolutional Neural Network

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China Communications 2020年第4期17卷 125-139页

作者： Wenbo Feng Zheng Hong Lifa Wu Menglin Fu Yihao Li Peihong Lin Institute of Command and Control Engineering Army Engineering University of PLANanjing210007China School of Computer Science and Technology Nanjing University of Posts and TelecommunicationsNanjing210023China

How to correctly acquire the appropriate features is a primary problem in network protocol recognition *** to avoid the trouble of artificially extracting features in traditional methods and improve recognition accuracy,a network protocol recognition method based on Convolutional Neural Network(CNN)is *** method utilizes deep learning technique,and it processes network flows ***,normalization is performed on the intercepted network flows and they are mapped into two-dimensional matrix which will be used as the input of ***,an improved classification model named Ptr CNN is built,which can automatically extract the appropriate features of network ***,the classification model is trained to recognize the network *** proposed approach is compared with several machine learning *** results show that the tailored CNN can not only improve protocol recognition accuracy but also ensure the fast convergence of classification model and reduce the classification time.

关键词： convolutional neural network protocol recognition network flow classification model

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Differential Privacy-based Avatar Update in Cooperative Intelligent Transportation System Metaverse 10

Differential Privacy-based Avatar Update in Cooperative Inte...

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10th International Conference on computer and Communications, ICCC 2024

作者： Khan, Salabat Luo, Fei Khan, Mansoor Ullah, Insaf Amin, Farhan Ullah, Shamsher Rahim, Mussadiq Abdul School of Computer and Enformation Engineering Qilu Institute of Technology Jinan China School of Computing and Information Technology Great Bay University Dongguan China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China Institute for Analytics and Data Science University of Essex ColchesterCO4 3SQ United Kingdom School of Computer Science and Engineering Yeungnam University Korea Republic of Shenzhen University National Engineering Laboratory for Big Data Shenzhen China Dhahran31261 Saudi Arabia

Metaverse is the next generation and the successor to the Internet. Various sectors allocated capital to adapt the metaverse due to its inherent importance. Cooperative Intelligent Transportation Systems (C-ITS) is one of the important sectors that can benefit from metaverse adaptation and integration. The C-ITS and metaverse integration give rise to new use cases and cyber attacks. However, traditional Pseudonym Certificate (PCert) authentication based on Vehicular Public Key Infrastructure (VPKI) cannot meet the new use cases and thwart cyber attacks. We present a Differential Privacy (DP)-based PCert and avatar update model to ensure the privacy of end-devices (e.g., vehicles) in the C-ITS metaverse. The proposed DP-based model adds noise to avatar attributes (e.g., color, behavior) to prevent avatar linkage during the PCert update process. Our method ensures that PCerts and avatars cannot be linked to end-devices and the previous PCerts and avatars. We simulate the DP-based method to investigate it in terms of privacy, latency, color distortion, and adversarial success rate, and the results show that DP-based is effective and practical for avatar updates. © 2024 IEEE.

关键词： Advanced driver assistance systems

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Data-driven Optimal Cooperative Output Regulation of Unknown Linear Discrete-time Multi-agent Systems

Data-driven Optimal Cooperative Output Regulation of Unknown...

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第35届中国控制与决策会议

作者： Dong Liang Yi Dong Chaoli Wang Engang Tian Department of Control Science and Engineering School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University

The cooperative output regulation problem has been extensively studied on the basis of the distributed observer ***,the majority of the existing research assumes that the dynamics is known *** remove this condition,the cooperative output regulation problem is further solved via the data-driven framework where the dynamics of the plant is ***,a data-driven distributed observer is established to estimate the state of the leader with unknown dynamics subject to external ***,the unknown regulator equations are solved using the iterative recurrent neural network ***,the state-based data-driven distributed control law is synthesized to solve the *** optimal gains are derived by solving convex optimization problems using input and state ***,a numerical example is presented to verify the feasibility of the proposed framework.

关键词： Linear systems multi-agent systems cooperative output regulation data-driven control optimal control

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Towards Trustworthy AI: Sandboxing AI-Based Unverified controllers for Safe and Secure Cyber-Physical Systems

Towards Trustworthy AI: Sandboxing AI-Based Unverified Contr...

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IEEE Conference on Decision and control

作者： Bingzhuo Zhong Siyuan Liu Marco Caccamo Majid Zamani TUM School of Engineering and Design Technical University of Munich Germany Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science University of Colorado Boulder USA

In the past decade, artificial-intelligence-based (AI-based) techniques have been widely applied to design controllers over cyber-physical systems (CPSs) for complex control missions (e.g., motion planning in robotics). Nevertheless, AI-based controllers, particularly those developed based on deep neural networks, are typically very complex and are challenging to be formally verified. To cope with this issue, we propose a secure-by-construction architecture, namely Safe-Sec-visor architecture, to sandbox AI-based unverified controllers. By applying this architecture, the overall safety and security of CPSs can be ensured simultaneously, while formal verification over the AI-based controllers is not required. Here, we consider invariance and opacity properties as the desired safety and security properties, respectively. Accordingly, by leveraging a notion of (augmented) control barrier functions, we design a supervisor to check the control inputs provided by the AI-based controller and decide whether to accept them. At the same time, a safety-security advisor runs in parallel and provides fallback control inputs whenever the AI-based controller is rejected for safety and security reasons. To show the effectiveness of our approaches, we apply them to a case study on a quadrotor controlled by an AI-based controller. Here, the initial state of the quadrotor contains secret information which should not be revealed while the safety of the quadrotor should be ensured.

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Labeled Graph Partitioning Scheme for Distributed Edge Caching

SSRN

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SSRN 2023年

作者： Wang, Pengfei Li, Shiqi Sun, Geng Zhou, Changjun Gao, Chengxi Qiu, Sen Tao, Tiwei Zhang, Qiang School of Computer Science and Technology Dalian University of Technology Dalian116024 China Changchun130012 China School of Computer Science and Technology Zhejiang Normal University Jinhua321000 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China School of Artificial Intelligence Dalian University of Technology Dalian116024 China

Distributed edge caching could address latency and congestion problems in large-scale data access effectively, improving system throughput and performance. However, the lack of specialized edge caching solutions for graph data results in low cache hit rates and high data access latency. This limitation stems from existing graph partitioning schemes that overlook the specific requirements of edge caching, such as communication overhead between edge servers, data query frequency, and query patterns. To overcome these challenges, we propose LGPE, a labeled graph partitioning scheme for distributed edge caching based on frequent query patterns. LGPE generates frequent query pattern according to the user’s historical query subgraphs, and then performs labeled graph partitioning based on the frequent pattern, ensuring that the labeled graph divided into edge servers has a high hit rate for frequent user queries while satisfying minimum edge-cut. Evaluation on real datasets from various application domains demonstrates that LGPE achieves approximately 40% higher cache hit rates compared to benchmarks like METIS and SCOTCH, and it also performs well in terms of edge cuts in special graph cases. © 2023, The Authors. All rights reserved.

关键词： Internet of things

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Hyperbolic Binary Neural Network

arXiv

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arXiv 2025年

作者： Chen, Jun Xiang, Jingyang Huang, Tianxin Zhao, Xiangrui Liu, Yong National Special Education Resource Center for Children with Autism Zhejiang Normal University Hangzhou311231 China Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China School of Computer Science and Technology Zhejiang Normal University Jinhua321004 China

Binary Neural Network (BNN) converts full-precision weights and activations into their extreme 1-bit counterparts, making it particularly suitable for deployment on lightweight mobile devices. While binary neural networks are typically formulated as a constrained optimization problem and optimized in the binarized space, general neural networks are formulated as an unconstrained optimization problem and optimized in the continuous space. This paper introduces the Hyperbolic Binary Neural Network (HBNN) by leveraging the framework of hyperbolic geometry to optimize the constrained problem. Specifically, we transform the constrained problem in hyperbolic space into an unconstrained one in Euclidean space using the Riemannian exponential map. On the other hand, we also propose the Exponential Parametrization Cluster (EPC) method, which, compared to the Riemannian exponential map, shrinks the segment domain based on a diffeomorphism. This approach increases the probability of weight flips, thereby maximizing the information gain in BNNs. Experimental results on CIFAR10, CIFAR100, and ImageNet classification datasets with VGGsmall, ResNet18, and ResNet34 models illustrate the superior performance of our HBNN over state-of-the-art methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Constrained optimization

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