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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Urakawa, Yoshiyuki Sirichai, Ngamlamai Robotics Department Advanced Engineering Faculty Nippon Institute of Technology Saitama Japan Mechanical System Engineering Major Graduated School Nippon Institute of Technology Saitama Japan

ISBN: (纸本)9781665464543

Positioning systems with motors are widely used in industrial use. Many production systems, mechatronics systems or industrial robots use high speed and high precision positioning systems with motors. Generally, the controllers of the positioning systems are proportional-to-proportional-integral (P-PI) controllers. They are often used because they have small overshoots and easy to tune. However, it needs fine-tunings to make settling motions smooth. There may be two reasons why the fine-tunings are needed for P-PI controllers. One is the pole assignment constraint of P-PI controller. Three poles of the P-PI control systems for motor positioning cannot be assigned freely. One of the three poles always stay at a slow position. Another reason is the digital delay when the P-PI controllers are applied to the practical systems. The digital system with the delay becomes vibrational because of the phase delay of the calculation time. It makes the overshoot of the trajectory. In this paper, the influences and solutions of the pole assignment constraint and the digital delay are shown. The pole assignment constraint limits the performance of the closed loop. The feedforward controller is shown to be the solution of this constraint. The digital delay makes the overshoot, but it can be corrected by the limited pole placement (LPP) method proposed by the author. It enables accurate pole-zero assignment without overshoots under the conditions of the digital delay. © 2024 IEEE.

关键词： Industrial robots

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Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1544-1556页

作者： Wenhua Li Xingyi Yao Kaiwen Li Rui Wang Tao Zhang Ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Xiangjiang Laboratory and also with the College of Systems EngineeringNational University of Defense TechnologyChangsha 410073China College of Systems Engineering National University of Defense Technologyand also with the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection TechnologyChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China

Most multimodal multi-objective evolutionary algorithms(MMEAs)aim to find all global Pareto optimal sets(PSs)for a multimodal multi-objective optimization problem(MMOP).However,in real-world problems,decision makers(DMs)may be also interested in local ***,searching for both global and local PSs is more general in view of dealing with MMOPs,which can be seen as generalized ***,most state-of-theart MMEAs exhibit poor convergence on high-dimension MMOPs and are unable to deal with constrained *** address the above issues,we present a novel multimodal multiobjective coevolutionary algorithm(Co MMEA)to better produce both global and local PSs,and simultaneously,to improve the convergence performance in dealing with high-dimension ***,the Co MMEA introduces two archives to the search process,and coevolves them simultaneously through effective knowledge *** convergence archive assists the Co MMEA to quickly approach the Pareto optimal *** knowledge of the converged solutions is then transferred to the diversity archive which utilizes the local convergence indicator and the-dominance-based method to obtain global and local PSs *** results show that Co MMEA is competitive compared to seven state-of-the-art MMEAs on fifty-four complex MMOPs.

关键词： Coevolution ∈-dominance generalized multimodal multi-objective optimization(MMO) local convergence two archives

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Artificial intelligence algorithms for object detection and recognition in video and images

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Multimedia Tools and Applications 2025年 1-18页

作者： Dakshinamoorthy, Prabakar Rajaram, Gnanajeyaraman garg, Shruti Murugan, Prabhu Manimaran, A. Sundar, Ramesh Department of Data Science and Business System School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur Chennai India Department of Computer Science Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Birla Institute of Technology Mesra Ranchi India Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India Department of Computer Science Engineering Saveetha School Of EngineeringSaveetha Institute of Medical and Technical Sciences Chennai6021055 India Department of Netwoking and Communication School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur Chennai India

The usage of machine learning and deep learning algorithms have necessitated Artificial Intelligence'. AI is aimed at automating things by limiting human interference. It is widely used in IT, healthcare, finance, and agriculture. It is achieved through several deep learning algorithms that reflect the human brain's intelligence. These AI algorithms can be manipulated according to changing needs and improved efficiency. This paper tries to utilize the developments made in AI technology to classify the images and recognize the objects present in them. One widely used AI algorithm is CNN (Convolutional Neural Networks). The CNN is a deep learning-based algorithm that consists of various layers that extract and filters the parameters present in the images. Some additional layers of ResNet50 and the CNN algorithm are used to extract the parameters to improve image recognition accuracy. The image dataset taken for training and testing the proposed model is imageNet. The images are initially processed before sending them to the proposed model. The proposed model is trained, validated, and tested through the images obtained after the initial processing. The same process is repeated several times until getting the maximum accuracy. The accuracy of the proposed model in terms of image recognition is recorded. The obtained results are compared with other image classification algorithms like VGG16 and VGG19. It is concluded that the proposed model outperforms other traditional methods in terms of accuracy. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Joint Task Allocation and Resource Optimization for Blockchain Enabled Collaborative Edge Computing

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China Communications 2024年第12期21卷 218-229页

作者： Xu Wenjing Wang Wei Li Zuguang Wu Qihui Wang Xianbin College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyNanjing 211106China Department of Electrical and Computer Engineering Western UniversityCanada

Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless ***,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be *** this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different *** minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each *** apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal ***,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the *** results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.

关键词： blockchain collaborative edge computing resource optimization task allocation

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Time-based Equalization Strategy of Parallel Charge Balancing Architecture for Lithium-ion Battery Application

Time-based Equalization Strategy of Parallel Charge Balancin...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Sahoo, Jyotirmaya Ramesh, P. Patra, Amit Mukhopadhyay, Siddhartha Indian Institute of Technology Battery Management and Integrated System Lab Department of Electrical Engineering Kharagpur India

ISBN: (纸本)9798350376067

Lithium-ion battery packs are prone to charge imbalances due to series configuration and the non-ideal nature of parameter variation. Therefore, a battery management system (BMS) configured with a charge equalization circuit (CEC) carried out the balancing operation, improving the capacity utilization of the battery storage system. A multi-cell-to-multi-cell (MC2MC) balancing architecture provides parallel equalization of each series module with faster balancing than other types. For balancing operation, the cell terminal voltage, state of charge (SOC), or capacity is used as an equalization monitoring variable, which requires additional sensing circuits, limiting real-world implementation in electric vehicles or battery energy storage applications. This paper proposes a Time-based equalization method for the parallel (MC2MC) equalization CEC, reducing the sensing component count for active balancing and the overall BMS sizing. The proposed methodology is validated using a 14.5 V, 10.4 Ah equalization model in the PLECS simulation environment and a 4S4P LCO battery pack in an experimental setup. A sensorless balancing current calculation is validated in this work using a cell series terminal current sensing unit. © 2024 IEEE.

关键词： State of charge

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Interval analysis for neural networks with application to fault detection

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Science China(Information Sciences) 2024年第11期67卷 222-237页

作者： Zhenhua WANG Youdao MA Song ZHU Thach Ngoc DINH Yi SHEN Department of Control Science and Engineering Harbin Institute of Technology National Key Laboratory of Complex System Control and Intelligent Agent Cooperation School of Mathematics China University of Mining and Technology The CEDRIC-Lab Conservatoire National des Arts et Métiers (CNAM)

This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.

关键词： interval analysis feedforward neural network fault detection adaptive thresholds

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Exploring User Satisfaction for Health Application Among Pregnant Women in Indonesia : A Case Study with Aspect Based Sentiment Analysis 8

Exploring User Satisfaction for Health Application Among Pre...

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8th International Conference on Information technology, InCIT 2024

作者： Fauzi, Rahmat Permanasari, Adhistya Erna Fauziati, Silmi Universitas Gadjah Mada Department of Electrical Engineering and Information Technology Yogyakarta Indonesia Telkom University School of Industrial Engineering and System Bandung Indonesia

ISBN: (纸本)9798350366303

The development of information technology has brought significant changes in seeking and obtaining health information. Health is a major factor affecting the development and well-being of individuals and communities, especially for health monitoring applications for pregnant women and toddlers. In Indonesia, despite the high development of technology, the adoption of health apps is still relatively low. This research investigates user sentiment regarding health apps targeted at pregnant women, focusing on four main aspects - social, individual, technical and security. Through sentiment classification and Aspect Based Sentiment Analysis (ABSA) on thousands of user reviews from the Google Play Store, we identified critical areas of concern and appreciation. The results showed significant negative sentiment on social and individual aspects, with users experiencing dissatisfaction over insufficient community support, lack of personalization, and emotional relevance. Security aspects also showed negative sentiments due to concerns over privacy and data protection. In contrast, the technical aspects were the most positively received, with users appreciating the overall functionality and performance of the application. © 2024 IEEE.

关键词： Electronic health record

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Adsorption properties of polycarboxylate ether-based superplasticizer on cement particles and their resultant dispersion

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Frontiers of Structural and Civil engineering 2022年第4期16卷 506-514页

作者： Jinyoung YOON Byoung Il CHOI Jae Hong KIM Department of Structural Engineering Research Korea Institute of Civil Engineering and Building Technology(KICT)Goyang 10223Republic of Korea System Safety Research Department Korea Shipbuilding and Offshore EngineeringSeongnam 13591Republic of Korea Department of Civil and Environmental Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141Republic of Korea

The cement dispersion performance of a polycarboxylate(PCE)-based superplasticizer is highly related to their adsorption behaviors as a function of *** study evaluated effects of PCEs on rheological properties of cementitious ***,characteristics of PCEs were characterized via permeation chromatography(GPC)and Fourier-transform infrared spectrometry(FT-IR).The adsorption behavior of single and blended PCEs on cementitious composites was identified using total organic carbon analyzer(TOC).Based on the measurement of PCE adsorption,the changes of rheological properties of cementitious materials as well as the number of dispersed cement particles were characterized using a rheometer and laser spectroscopy,*** experimental results support the systematic mechanism of PCE adsorption,cement dispersion,and the decrease in viscosity of cementitious materials.

关键词： adsorption polycarboxylate superplasticizer rheology dispersion

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THE SKILLS FOR MEASURING THE EFFECTIVE THERMAL DIFFUSION CONDUCTIVITY OF THE VAPOR CHAMBER WITH THE ÅNGSTRÖM THEORY

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Heat Transfer Research 2023年第11期54卷 51-74页

作者： Lin, Wei-Keng Zhang, Wen-Hua Hsaio, Kenny Tseng, Wen-Ching Chu, Yi-Jing Department of Engineering and System Science National Tsing Hua University Hsinchu City Taiwan T-Global Technology Taoyuan City Taiwan

Most people measure the thermal resistance of vapor chambers by using Fourier's law of thermal conduction. However, Fourier's thermal conduction law is generally applied when the evaporator area is the same as that of the condenser, and this is completely different from the realistic condition;that is, the heated area of the evaporator is much smaller than the condenser area. Therefore, we proposed a new method to initially measure the thermal diffusivity of the test sample by the Ångström theory and then convert it into effective thermal diffusion conductivity of the vapor chamber. The Ångström theory is originally used for the one-dimensional test sample. However, the results of measurements that are applied to heat spreaders such as vapor chambers, heat pipes, or graphene are generally not accurate enough. The reason is that some test samples are not one-dimensional, or the test skill is not high. Therefore, the accuracy of measuring the effective thermal diffusivity of vapor chambers is very important for identifying the performance of the vapor chamber. The method in this paper using the Ångström theory has successfully divided the size of the current vapor chamber into three zones by the method of thickness-to-width aspect ratio. The repeatability error of obtained data is less than 5%, and the accuracy error is less than 10%. © 2023 by Begell House, Inc.

关键词： Thermal diffusivity

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Clock Recovery Circuit for 3-Gsymbol/s/lane MIPI C-PHY Receiver 21

Clock Recovery Circuit for 3-Gsymbol/s/lane MIPI C-PHY Recei...

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21st International system-on-Chip Design Conference, ISOCC 2024

作者： Shin, Dong-Seob Park, Jong-Ho Song, Chang-Min Kim, Seong-Yun Lee, Hyeonseok Lee, Jinyeong Jang, Young-Chan Graduate School Kumoh National Institute of Technology Department of Semiconductor System Engineering Gumi Korea Republic of

ISBN: (纸本)9798350377088

A clock recovery circuit for use in the receive circuit of the MIPI C-PHY is proposed. The proposed clock recovery circuit removes the glitch noise that may be generated in the process of recovering the clock by detecting the edge of the received data. It performs an optimization of the control of the delay line used for the implementation of the short pulse in the conventional clock recovery circuit. To optimize this delay line, the proposed clock recovery circuit is designed by adding a clock recovery calibration circuit to the conventional clock recovery circuit, which controls the delay lines according to the pattern of data sampled by the recovered clock. The proposed clock recovery circuit supporting the MIPI C-PHY with a symbol rate of 3 GHz per lane is designed using a 65-nm CMOS process and consumes 0.2 mW during clock recovery calibration operations at a supply voltage of 1.2 V. © 2024 IEEE.

关键词： Calibration

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