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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： João P. Ferreira António P. Coimbra Manuel Crisóstomo Department of Electrical Engineering Superior Institute of Engineering of Coimbra Portugal Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Nowadays, handwriting still plays an important role in our lives, even though we live in a progressively more digital era. Therefore, losing the ability to write, whether because of physical or psychological complications, can become a huge handicap. The system described herein aims, in a first stage, to enable handwriting training through haptic guidance. The implementation was performed in Visual Studio and with the use of OpenHaptics toolkit. The second stage consists in character classification, written using a haptic joystick. The pre-eminent procedure for digit classification consists in the use of Histogram of Oriented Gradients coupled with a multiclass Support Vector Machine (HOG-SVM) whereas for letters the strategy involves using a Convolutional Neural Network (CNN).

关键词： Training Support vector machines Visualization Accuracy Shape Writing Time measurement Haptic interfaces Trajectory Convolutional neural networks

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization *** past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer ***,it is hard to traverse the huge search space within reasonable resource as problem dimension *** evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory *** reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent *** there lacks a thorough review of the state of the art in this specific and important *** paper provides a comprehensive survey of these evolutionary algorithms for *** start with a brief introduction to the research status and the basic concepts of ***,we present surrogate-assisted evolutionary algorithms for HEPs from four main *** also give comparative results of some representative algorithms and application ***,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Centralizing Data Warehouse Platform for Mining Management Using AWS Computing Instance

Centralizing Data Warehouse Platform for Mining Management U...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Sathaporn, Posathip Chaowalittawin, Vasutorn Krungseanmuang, Woranidtha Benjangkaprasert, Chawalit Purahong, Boonchana School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Robotics and Computational Intelligent Systems Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Computer Engineering Department Bangkok Thailand

ISBN: (纸本)9798350350821

Mining industry is one of significant industry in the world. In order to increase efficiency, safety, sustainability and environmental impacts in mining process. This article presents a centralized data platform for mining process by design based on microservices architecture which can be supported various of input data source such as manual form, excel file and internet of things (IoT) device and notification when the value is abnormal. Our platform implementation on Amazon Web Service (AWS) cloud. For development of productivity in process and controlling quality the mine environment. The results of the platform operations with various source of data acquisition with response time is less than 1.5 seconds per each request. © 2024 IEEE.

关键词： Cloud Computing Data Warehouse Internet of Things Microservices Architecture Mining Industry

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A Single DC-source Asymmetrical Multilevel Inverter With Solid State Transformer With New Switching Approach

A Single DC-source Asymmetrical Multilevel Inverter With Sol...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Karunakaran, E. Suresh, Y. Rao, Bhukya Nageswar Vivek, P.S.S. Aditya, K. National Institute of Technology Department of Electrical and Electronics Engineering Karnataka Surathkal India Kolhapur Institute of Technology College of Engineering Department of Computer Science and Business Systems Kolhapur India

ISBN: (纸本)9798350309140

Cascaded H-bridge (CHB) MLI have emerged as the preferred choice due to their high quality in output waveforms with low harmonic distortion. However, a key limitation in these inverters lies in the requirement of a dedicated DC source for each bridge. To overcome this challenge, there is a transition towards asymmetrical cascaded H-bridge (ACHB) MLIs, enabling the use of a variable DC source for each bridge. The variability in DC supply is achieved through a high-frequency link. This paper introduces a novel optimized switching technique for asymmetrical cascaded H-bridge (ACHB) MLIs with a single DC input incorporating a high-frequency link (HFL). The effectiveness of the suggested approach in achieving a 27-level asymmetric multilevel inverter is substantiated by experimental outcomes obtained through MATLAB/Simulink simulations. © 2024 IEEE.

关键词： DC transformers

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An In-depth Investigation on the Structure, Characteristics, and Potential Applications of GaN/SiC Mosfet-Based systems 6

An In-depth Investigation on the Structure, Characteristics,...

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6th International Conference on Information Technologies and electrical engineering, ICITEE 2023

作者： Ren, Yan Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy12180 United States

ISBN: (纸本)9798400708299

In an era of rapid technological innovation, this article provides a comprehensive examination of Gallium Nitride (GaN) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs). The background section highlights the emergence and application of GaN MOSFETs and their significant advantages over silicon-based and Silicon Carbide (SiC) MOSFETs, such as smaller size, faster switching speed, less heat generation, and optimum operation at high temperatures, indicating that GaN MOSFETs are leading us into a more advanced, digitized future. The article delves into the basic theory of GaN MOSFETs, detailing their unique structure and properties that demonstrate massive potential and practicality in real-world applications such as electric vehicles and 5G technology. The conclusion emphasizes that GaN MOSFETs have already shown their importance in a wider range of industrial sectors and are set to revolutionize various industries, thereby driving overall progress. With diversified applications and broad prospects, the impact and value of GaN MOSFETs have gone beyond single-component applications, and their societal significance is undergoing profound changes. © 2023 ACM.

关键词： Gallium nitride

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A Nested Ensemble Method to Bilevel Machine Learning 48

A Nested Ensemble Method to Bilevel Machine Learning

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Chen, Lisha Abbas, Momin Chen, Tianyi Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering Department TroyNY United States

ISBN: (纸本)9781728163277

Modern machine learning problems, such as hyperparameter optimization, meta learning, and adversarial training, adopt a bilevel learning formulation. Such problems involve a nested relation between inner- and outer-level problems, which often have suboptimal solutions with poor generalization ability. To address this issue, this paper proposes an ensemble method tailored to bilevel learning. Our method finds a nested ensemble of inner and outer parameters that improve generalization. We instantiate our general results with meta learning. We show theoretically and empirically that the diversity and the smoother loss landscape of the proposed ensemble methods lead to improved generalization over the state-of-the-art method. © 2023 IEEE.

关键词： Machine learning

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Corrections to "Reed Solomon Codes Against Adversarial Insertions and Deletions"

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IEEE Transactions on Information Theory 2025年第4期71卷 3237-3238页

作者： Con, Roni Shpilka, Amir Tamo, Itzhak Technion – Israel Institute of Technology Department of Computer Science Haifa3200003 Israel Tel Aviv University Blavatnik School of Computer Science Tel Aviv6997801 Israel Tel Aviv University Department of Electrical Engineering-Systems Tel Aviv6997801 Israel

The purpose of this note is to correct an error made by Con et al. (2023), specifically in the proof of Theorem 9. Here we correct the proof but as a consequence we get a slightly weaker result. In Theorem9, we claimed that for integers k and n such that k q RS code that can decode from n - 2k + 1 insdel errors where (Formula presented). Here we prove the following. Theorem 1: For integers n and k q RS-code, where (Formula presented) is a prime power, that can decode from n - 2k + 1 adversarial insdel errors. Note that the exponent of n is 4k - 3 whereas in Theorem 9 it is 4k - 4. For constant dimensional codes, the field size is of order O(n4k-3) , and in particular, for k = 2 the field size is of order O(n5) . © 1963-2012 IEEE.

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Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

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Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games 63

Conjectural Online Learning with First-order Beliefs in Asym...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Li, Tao Hammar, Kim Stadler, Rolf Zhu, Quanyan New York University Department of Electrical and Computer Engineering United States Kth Royal Institute of Technology Division of Network and Systems Engineering Sweden

ISBN: (纸本)9798350316339

Asymmetric information stochastic games (AISGs) arise in many complex socio-technical systems, such as cyberphysical systems and IT infrastructures. Existing computational methods for AISGs are primarily offline and can not adapt to equilibrium deviations. Further, current methods are limited to particular information structures to avoid belief hierarchies. Considering these limitations, we propose conjectural online learning (COL), an online learning method under generic information structures in AISGs. COL uses a forecaster-actorcritic (FAC) architecture, where subjective forecasts are used to conjecture the opponents' strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures. To adapt strategies to nonstationary environments based on information feedback, COL uses online rollout with cost function approximation (actor-critic). We prove that the conjectures produced by COL are asymptotically consistent with the information feedback in the sense of a relaxed Bayesian consistency. We also prove that the empirical strategy profile induced by COL converges to the Berk-Nash equilibrium, a solution concept characterizing rationality under subjectivity. Experimental results from an intrusion response use case demonstrate COL's faster convergence over state-of-the-art reinforcement learning methods against nonstationary attacks. © 2024 IEEE.

关键词： Cost functions

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