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Computing in Natural Sciences, Biomedicine and engineering (COMCONF), International Conference on

作者： Fabian Arun Panaite Monica Leba Computer and System Control Engineering Department University of Petrosani Petrosani Romania

ISBN: (数字)9798350353358

ISBN: (纸本)9798350353365

This paper presents the use of AI-based uncertainty management in the processing of multiple modalities for the purpose of gait motion tracking using Inertial Measurement Units (IMU) sensors. More precisely, it deploys its effort on the assessment of gait abnormalities in Alzheimer disease and other health related illnesses. It can be used to perform a long-term tracking of gait patterns for Alzheimer's patients and identification of the changes that occur allowing for the evaluation of the disease's progression or the outcomes of treatments. Therefore, this research greatly boosts the efficiency of gait analysis systems especially in the identification of mechanical disorders of the musculoskeletal system and the subsequent treatments and the core of diagnosis and rehabilitation. Over the last decade, progress in technology has led to the enhancements in the IMUs that are used in gait analysis where IMUs have shifted from single sensor to multiple sensors where the sensor data is processed through a method known as sensor fusion and machine learning. These developments have made possible their use in both clinical and consumer contexts. Recent developments in gait motion capture enabled by AI are as the continuous trends in deep learning and video-based approaches made marker-less and non-invasive methods possible. Such analyses are crucial for identification work, which in turn positively affects the identification and reintegration into the delivery of health care, of diagnosis and rehabilitation.

关键词： Mechanical sensors Legged locomotion Filters Measurement units Tracking Medical services Inertial navigation Sensor fusion Motion capture Gait recognition

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Analysis and Suppression of Voltage Overshoot in Symmetrical Hybrid Five-level Converter 10

Analysis and Suppression of Voltage Overshoot in Symmetrical...

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10th IEEE International Power Electronics and Motion control Conference, IPEMC 2024 ECCE Asia

作者： Liu, Nianzhou Zhang, Mingqi Pang, Jupeng Xie, Pengfei Qiu, Changqing Wang, Kui Li, Yongdong State Key Laboratory of Electromagnetic Energy Wuhan430064 China Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China

ISBN: (纸本)9798350351330

This paper analyzes the device voltage overshoot in the symmetrical hybrid five-level converter. Owing to the presence of stray inductance, the voltage that the power devices need to withstand during switching operations may exceed their rated values. To address this issue, a device voltage overshoot suppression method suitable for the topology is proposed in this paper. This method suppresses SiC MOSFET voltage overshoot through adjustment of switching speed and the utilization of snubber capacitance, and it employs the design of RC and dual-RCD snubber circuits to suppress Si IGBT voltage overshoot. Simulation and experimental results certificate the effectiveness of the proposed method in suppressing device voltage overshoot. © 2024 IEEE.

关键词： Capacitance

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Comparative Analysis of Wearable and Computer Vision-Based Methods for Human Torso Posture Estimation

Comparative Analysis of Wearable and Computer Vision-Based M...

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International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)

作者： Emanuel Muntean Monica Leba Department of System Control and Computer Engineering University of Petrosani Petrosani Romania

ISBN: (数字)9798350377224

ISBN: (纸本)9798350377231

This paper conducts a comparative analysis of human torso posture estimation methodologies, focusing on an inertial measurement unit (IMU) sensor coupled with an Arduino UNO as a wearable approach, and Kinect V2, utilizing OpenCV for posture analysis. The core objective of this study is to ascertain which method yields greater precision in the estimation of human torso posture. The IMU sensor, characterized by its wearability, provides the distinct advantage of unobtrusiveness and the capability to record motion across diverse environments. Conversely, Kinect V2 leverages computer vision techniques to derive posture estimations from visual data in real-time. Through comprehensive experimentation, this research evaluates the accuracy of both methodologies by juxtaposing their posture estimation outcomes. The findings of this investigation aim to significantly contribute to the enhancement of human posture estimation systems, with wide-ranging implications for health, sports, and ergonomics.

关键词： Torso Visualization Accuracy Measurement units Estimation Inertial navigation Sensor fusion Reliability Wearable devices Sports

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The Deployment of Microservice at Edge based on MQTT for Low Latency 22

The Deployment of Microservice at Edge based on MQTT for Low...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Han, Mengqi Yang, Bo Liu, Yuxiang Liu, Sicheng Liu, Qi Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798331527471

With the rapid development of smart manufacturing, existing microservice deployment strategies based on the TCP protocol tend to encounter problems such as network latency, excessive header length, and port exhaustion in high concurrency scenarios. MQTT Broker can relay data between microservices, effectively alleviating these issues. However, the communication overhead of the Broker is significantly related to its deployment and the dependency of microservices. An appropriate deployment solution can significantly improve service quality. To address this issue, this paper models the deployment of MQTT Broker and microservices as a graph with cycles. By introducing auxiliary variables, the NP-hard problem is transformed into a mixed-integer quadratic programming problem, improving problem-solving efficiency and optimizing the microservices deployment strategy to reduce communication overhead. Meanwhile, a real-world heterogeneous cluster was constructed to experiment on fault detection applications, elaborating on the superiority of the microservice deployment strategy designed in this paper. Experimental results demonstrate that our approach reduces communication overhead by 20% in comparison to both the greedy strategy and the K8s strategy. This suggests that achieving an optimal balance between the number of Brokers and microservices is vital for ensuring efficient resource utilization and maintaining low communication latency, particularly as the scale of services expands. © 2024 IEEE.

关键词： Smart manufacturing

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L1adaptive controller design for a tail fin controlled fixed wing unmanned aerial vehicle 13

L1adaptive controller design for a tail fin controlled fixed...

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13th EASN International Conference on Innovation in Aviation and Space for Opening New Horizons

作者： Demirli, Alican Koc, Ilker Murat Kurkcu, Burak Aselsan INC. Yenimahalle Ankara Turkey Department of Mechanical Engineering Istanbul Technical University Istanbul Turkey Mechanical System Control Laboratory UC Berkeley CA United States

The aim of this study is to design L1 adaptive controller, which is one of the robust control methods that can overcome model uncertainties, disturbances and noises, for a fixed-wing unmanned aerial vehicle (UAV) with tail fin controlled. In this context, first of all, the decoupled equations of motion of the six-degrees-of-freedom system are derived for the roll, pitch and yaw channels of the UAV. Then, the performance of the controller is demonstrated by simulation results for linearized system representation. By adding parameter errors to the system in question, the feature of tracking the given angle commands are analyzed. It has been observed that the L1 adaptive control structure exhibits rapid adaptation even in presence of system uncertainties. Finally, the controller is applied to the nonlinear system and operated throughout the entire flight envelope. © Published under licence by IOP Publishing Ltd.

关键词： Fixed wings

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Availability Evaluation of Finite Element Analysis Data for Data Supplementation with Motor Failure Diagnosis Algorithm Training Data 5

Availability Evaluation of Finite Element Analysis Data for ...

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5th IEEE Student Conference on Electric Machines and systems, SCEMS 2022

作者： Han, Ji-Hoon Choi, Eui-Jin Hong, Sun-Ki Hoseo University Department of Information Control Engineering Asan Korea Republic of Hoseo University Department of Digital and System Control Engineering Asan Korea Republic of

ISBN: (数字)9781665476898

ISBN: (纸本)9781665476898

The classic method of diagnosing motor failure is to analyze the signal characteristics of the motor. If a deep learning algorithm is used, the above process is omitted. This is replaced by a lot of data. However, the number of data that can be collected is limited. This is because the degree of failure and the condition of the motor are different in each situation. To solve this problem, research on data propagation using FEM (Finite Element Method) is in progress. FEM is used to check whether the propagated data is similar to classical theory and whether it can be used as training data for deep learning algorithms. Through these experiments, it was confirmed that the FEM data is data that helps in learning the deep learning algorithm that can classify the initial failure state. © 2022 IEEE.

关键词： Finite element method

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Failure Detection from the Knocking Sounds Using Convolutional Neural Network 38

Failure Detection from the Knocking Sounds Using Convolution...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Areerob, Punyapat Sum, Rithea Khongprasongsiri, Chanon Boonto, Sudchai King Mongkut's University of Technology Thonburi Department of Control System and Instrumentation Engineering Bangkok10140 Thailand National Astronomical Research Institute Thailand

ISBN: (纸本)9798350302196

Toilet quality assurance is a crucial process in ensuring lavatories meet rigorous performance, durability, and hygiene standards. The current standard of Maximum Performance (MaP) testing faces challenges, leading researchers to explore innovative approaches such as sound source classification for quality assurance. This approach involves collecting a diverse dataset of lavatory sounds and extracting relevant acoustic features. Deep learning models, particularly convolutional neural networks (CNNs), are trained on these features to accurately classify sound sources. The trained models were evaluated and compared by considering metrics such as classification accuracy, computational complexity, and model parameters. This paper performs these tests and chooses the most effective model to enhance the quality assurance process for toilets. Incorporating sound source classification techniques has several benefits, including the optimization of testing processes, non-intrusive performance assessment, and efficient resource utilization through targeted testing and troubleshooting. By improving the standards of lavatory quality, this approach ensures enhanced performance, durability, and hygiene of lavatories. © 2023 IEEE.

关键词： Convolution

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Network system capacity:Towards integrating sensing,communication and control

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National Science Open 2024年第1期3卷 147-149页

作者： Xinping Guan Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

Network systems refer to a new generation of systems with integrated information perception,transmission and utilization capabilities through communication networks,which are adopted to achieve desirable objectives under physical and information related uncertainties and/or adversary *** the information-rich era[1,2],one of the fundamental issues is to exploit the limit of feedback control on dissipating such uncertainties in the scenarios of networked sensing and communication[3].

关键词： communication integrating system

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Small Signal Stability-Guaranteed Moving Target Defense Against Load Redistribution Attack On IoT-based Smart Grid

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IEEE Internet of Things Journal 2025年第11期12卷 17413-17429页

作者： Wang, Bingdong Zhang, Zhenyong Wang, Mufeng Liu, Mengxiang Ye, Rui Deng, Ruilong Zhang, Xin Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Guizhou Power Grid Co. Ltd. Intelligent Operation Center China Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou313000 China

Moving target defense (MTD) is a promising approach to defend against load redistribution attacks on the internet-of-things (IoT)-based smart grid networks by probing the distorted state estimates with the distributed flexible AC transmission system. However, existing studies mainly focus on optimizing the performance of MTD and ignore the safety effect of it on the system’s operation. In this paper, we fill this gap by deeply analyzing the effect of MTD on the small signal stability and aim to alleviate the negative impact and guarantee its defending performance simultaneously. Firstly, the stability is formally described using the eigenvalue sensitivity. The relationship between the MTD-induced perturbation (MTDper) and the stability criteria is derived. Secondly, a new indicator is proposed to measure the effectiveness of MTDper. Thirdly, a constrained optimization problem is formulated to compute the bound of MTDper for guaranteeing the small signal stability. In addition, a surprising finding is that the stability margin can be improved and enhanced by optimizing the value of MTDper without losing the MTD’s effectiveness. Finally, we evaluate the performance of MTDper and its impact on the small signal stability with extensive simulations on the IEEE 30-bus, 39-bus, and 68-bus test power systems. © 2014 IEEE.

关键词： Constrained optimization

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Fall Detection for the Elderly using YOLOv4 and LSTM 19

Fall Detection for the Elderly using YOLOv4 and LSTM

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Chutimawattanakul, Pongsatorn Samanpiboon, Pranchalee King Mongkut's University of Technology Thonburi Department of Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

In elderly society, the falling of the elderly inside the house is the one of the causes of injury or death to the elderly. It negatively affects both the family and the elderly themselves. Therefore, taking care of the elderly at home is extremely important. In this paper, we used YOLOv4 technique to detect posture and LSTM to detect sequence of postures. YOLOv4 is the most efficient detection model compared to other detection models. LSTM is helpful in learning temporal features. Tests with 2 fall datasets showed an efficiency of posture detection by YOLOv4 at 87.88% and YOLOv4 and efficiency of fall detection by combination of YOLOv4 and LSTM at 100%. © 2022 IEEE.

关键词： Fall detection

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