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2022 IEEE Global Conference on Computing, Power and Communication Technologies, GlobConPT 2022

作者： Faisal, M. Ker, Pin Jern Hossain, M.R.T. Hannan, M.A. School of Electrical Computer and Telecommunications Engineering University of Wollongong NSW Australia Department of Electrical and Electronic Engineering International Islamic University Chittagong Chattogram4318 Bangladesh Institute of Sustainable Energy Universiti Tenaga Nasional Kajang43000 Malaysia Department of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh Department of Electrical and Electronic Engineering Universiti Tenaga Nasional Kajang43000 Malaysia

ISBN: (数字)9781665493659

ISBN: (纸本)9781665493659

This research introduced a new three-phase buck AC voltage controller consisting of two three-phase bidirectional switches for maintaining the stable output voltage under load and input voltage variations for suitable AC-AC applications. Existing pieces of literature on AC-AC controller topology have limitations of unbalanced output voltage for rapid load and input voltage variations. Addressing these shortcomings, a new and modified AC buck controller topology has been proposed which operates on per phase basis and thus maintains the constant output voltage for unbalanced loads. These topologies allow simple control circuits and reliable operation with acceptable efficiency, improved power factor, and input current shaping. A voltage mode feedback control system is introduced for controlling the regulator and thus shows the capability to get desired output voltage by adjusting the duty cycle. Obtained results for open and close loop control systems from both topologies have been compared and found improved performance regarding output voltage, input current, and THD values in the case of modified buck AC voltage controller topology. © 2022 IEEE.

关键词： Topology

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Machine Learning-Driven Early Detection And Monitoring Of Respiratory Disorder Using PCO2 Analysis

Machine Learning-Driven Early Detection And Monitoring Of Re...

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Smart Technologies, Communication and Robotics (STCR)

作者： Mohamed Afsal J Dhamodharan B Hariharan C Dinesh Chellappan Harikumar Rajaguru Department Of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore Department of Electrical and Electronic Engineering KPR Institute of Engineering and Technology Coimbatore KPR Institute of Engineering and Technology Coimbatore Department of ECE Bannari Amman Institute of Technology Sathyamangalam

ISBN: (数字)9798350357530

ISBN: (纸本)9798350357547

Respiratory disorders like Chronic Obstructive Pulmonary Disease (COPD), asthma, and Acute Respiratory Distress Syndrome (ARDS) pose significant health risks worldwide. This study presents a machine learning-driven framework for early detection and monitoring of these conditions using Partial Pressure of Carbon Dioxide (PCO 2 ) analysis. The methodology employs the Chi 2 Probability Density Function (Chi 2 PDF) and Cuckoo Search (CS) model for dimensionality reduction. Harmonic Search (HS) and Particle Swarm Optimization (PSO) are utilized for optimized feature selection. Models such as Nonlinear Regression (NLR), Gaussian Mixture Model (GMM), Linear Regression (LR), Support Vector Machine with Radial Basis Function (SVM-RBF), and Logistic Regression (LoR) are used for disorder detection. The proposed system achieved an accuracy of 95.71. This approach offers a non-invasive, cost-effective solution to enhance respiratory healthcare and improve patient outcomes.

关键词： Support vector machines Dimensionality reduction Acute respiratory distress syndrome Accuracy Medical services Probability density function Feature extraction Particle swarm optimization Monitoring Robots

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Integrated Decision Making and Trajectory Planning for Autonomous Driving Under Multimodal Uncertainties: A Bayesian Game Approach

arXiv

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arXiv 2024年

作者： Huang, Zhenmin Li, Tong Shen, Shaojie Ma, Jun Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Modeling the interaction between traffic agents is a key issue in designing safe and non-conservative maneuvers in autonomous driving. This problem can be challenging when multi-modality and behavioral uncertainties are engaged. Existing methods either fail to plan interactively or consider unimodal behaviors that could lead to catastrophic results. In this paper, we introduce an integrated decision-making and trajectory planning framework based on Bayesian game (i.e., game of incomplete information). Human decisions inherently exhibit discrete characteristics and therefore are modeled as types of players in the game. A general solver based on noregret learning is introduced to obtain a corresponding Bayesian Coarse Correlated Equilibrium, which captures the interaction between traffic agents in the multimodal context. With the attained equilibrium, decision-making and trajectory planning are performed simultaneously, and the resulting interactive strategy is shown to be optimal over the expectation of rivals' driving intentions. Closed-loop simulations on different traffic scenarios are performed to illustrate the generalizability and the effectiveness of the proposed framework. Copyright © 2024, The Authors. All rights reserved.

关键词： Multi agent systems

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Pareto Analysis of PI Tuning in Direct Digital Control of Multi-phase Drives ⁎

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IFAC-PapersOnLine 2024年第7期58卷 144-149页

作者： Manuel G. Satué J.D. Álvarez Manuel A. Perales Systems Engineering and Automation Department University of Seville 41092 Seville Spain Department of Computer Engineering Automation and Robotics CIESOL—ceiA3 University of Almería 04120 Almería Spain Electronic Engineering Department University of Seville 41092 Seville Spain

PI tuning for variable-speed multi-phase drives is a complex task. In this paper, a Pareto analysis is introduced to reveal not previously reported links between figures of merit. The drive used for the study includes a 5-phase induction motor supplied by a voltage source inverter. A finite state predictive method is used for the inner loop (current control). The outer loop (speed control) is governed by a PI. The analysis is done experimentally thus including all sorts of non-idealities not appearing in commonly found models. The experimental results show how the pursuit for better performance is hindered by the existence of links between figures of merit. The importance of the result lies in showing that arbitrary performance enhancements are not possible in a general case.

关键词： Application of power electronics Digital implementation Modeling simulation of power systems PI control Tuning

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Distraction Detection in Driving Using Pose Extraction and Machine Learning Techniques 7

Distraction Detection in Driving Using Pose Extraction and M...

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7th International Conference on Information Technology, Information Systems and Electrical engineering, ICITISEE 2023

作者： Bachtiar, Fitra Abdurrachman Arwani, Issa Prasetyo, Ridwan Aji Budi Pangestu, Gusti Soetedjo, Riza Setiawan Mahesa, Al Ravie Muthiar Brawijaya University Informatics Engineering Department Malang Indonesia Brawijaya University Information System Department Malang Indonesia Brawijaya University Psychology Department Malang Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350382266

There are a lot of technologies have been implemented in the modern cars these days, ranging from preventive braking system to driving assistance. It is believe that equipping car with modern technology would enhance safety. However, there are other aspects need to be considered in safety driving, that is human factor. Human factors are believed have high contribution in road accidents. Human factors such as emotional control and distraction may leads to dangerous driving behaviours. This study investigates the driver pose distraction. The distracted driver pose detected through pose detection using landmark feature extraction. The dataset used in this study is State Farm Distracted Driving Detection which is a secondary dataset. The extracted driver pose are in numeric form and used as the input for the classification model to detect ten kinds of driving distraction ranging from safety driving to talking to passenger. Four classifiers used to detect distracted driver are CatBoost, Decision Tress, Random Forest and SVM. The model performance evaluated using Precision, Recall, Accuracy, and F1-score. Furthermore, prediction time recorded to determine the best model to detect driver distraction. The results shows that CatBoost model outperformed all other model with F1-score and prediction time of 0.899 and 0.014 second. Random Forest model performance is the second highest compared to four other with F1-score and prediction time of 0.881 and 0.028 seconds. CatBoost model is the best model even though Cat Boost model execution time is not the highest and the model performance is not significantly different compared to Random Forest. © 2023 IEEE.

关键词： Extraction

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A Python-Based Study of Resonant Processes in Electric Circuits 37

A Python-Based Study of Resonant Processes in Electric Circu...

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37th International Conference on Information Technologies, InfoTech 2023

作者： Hinov, Nikolay Popov, Stoyan Technical University of Sofia Faculty of Electronic Engineering and Technologies Department of Power Electronics Sofia1000 Bulgaria Technical University of Sofia Faculty of Applied Mathematics and Informatics Department of Mathematical Modeling and Numerical Methods Sofia1000 Bulgaria

ISBN: (纸本)9798350338058

The manuscript presents a study of resonance processes in electrical circuits with the Python programming language. Basic resonant circuits with series and parallel resonance are considered. The obtained results were compared and verified with computer simulations implemented with the popular LTspice program simulator. In this way, the possibilities of researching different electrical circuits with Python have been proven. This is convenient in view of Python's better data collection, processing and analysis capabilities compared to standard Spice-based simulators. In addition, the presented approach is useful for implementation in the learning process of software engineers, where it is important to use different software tools in the study of fundamental disciplines such as electrical engineering and electronics. © 2023 IEEE.

关键词： Python

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BioMAS: A Wear-Free Biomechanical Motion Assessor for Physical Self-Training

BioMAS: A Wear-Free Biomechanical Motion Assessor for Physic...

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2025 IEEE International Conference on Consumer electronics, ICCE 2025

作者： Huh, Jungwoo Park, Yeseung Kim, Seongjean Kim, Jungsu Cheng, Wen-Huang Lee, Sanghoon Department of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798331521165

Physical training is essential for enhancing human health and aesthetics, playing a crucial role in daily life. However, individuals lacking expertise may face challenges in performing exercises correctly, which increases the risk of injury due to improper posture. To promote efficient physical self-training for individuals, we propose BioMAS, a novel motion assessor which captures and evaluates the performers motion through biomechanical analysis. BioMAS maximizes the performer's convenience by eliminating the need for wearable devices and instead utilizing video sensors for motion estimation. The proposed assessor first estimates human motion from multi-view RGB videos by leveraging deep learning and biomechanical models. From the estimated motion, biomechanical metric scores for balance, stability, and neutrality are provided for motion assessment. To validate the effectiveness of BioMAS, we developed the BioPT dataset, which includes biomechancial motion sequences paired with RGB videos on major weightlifting motion. Experimental results show that the estimated biomechanical motion from BioMAS has a joint error of approximately 53.2 mm compared to ground-truth human motion. Furthermore, we show that the proposed biomechanical metric scores exhibit a high correlation (≥ 80%) with the subjective scores evaluated by experts, confirming the efficacy of BioMAS for pyhsical self-training. © 2025 IEEE.

关键词： Gait analysis

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Social Robots - Robotics and Toy Computing Minitrack 58

Social Robots - Robotics and Toy Computing Minitrack

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58th Hawaii International Conference on System Sciences, HICSS 2025

作者： Hung, Patrick C.K. Huang, Shih-Chia Peres, Sarajane Marques Lee, Ha-Eun Yoon, Young Faculty of Business and Information Technology Ontario Tech University Canada Department of Electronic Engineering National Taipei University of Technology Taiwan School of Arts Sciences and Humanities University of Sao Paulo Brazil Department of AI Immersive Content Hongik University Korea Republic of Department of Computer Engineering Hongik University Korea Republic of

ISBN: (纸本)9780998133188

This HICSS-58 mini-track aims to present novel and industrial solutions to challenging technical issues of Human-Robot Interaction (HRI) and compelling social robot use cases. In addition, this mini-track will share related practical experiences to benefit the reader and provide clear proof that social robots play an ever-increasing essential and critical role in supporting robotic and toy computing applications - a new cross-discipline research topic in computer science, decision science, management sciences, and information systems. This year, we also have a symposium on Social Robots and Smart Toys at HICSS-58, which is co-organized with MR Media Lab, Hongik University, Korea. © 2025 IEEE computer Society. All rights reserved.

关键词： Social robots

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Time-multiplexing Method Using Dual Ferroelectric Liquid Crystal Shutters for Light Field 3D Display

Time-multiplexing Method Using Dual Ferroelectric Liquid Cry...

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International Conference on Display Technology, 2024

作者： Sun, Zhi-Bo Yuan, Zheng-Nan Huo, Yi-Peng Dong, Shou-Cheng Cheung, Alex Vashchenko, Valerii Vashchenko, Olena Srivastava, Abhishek Kwok, Hoi-Sing State Key Laboratory of Advanced Displays and Optoelectronics Technologies Center for Display research Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Road Kowloon Hong Kong

In light field displays, the resolution loss is a serious problem, leading to insufficient image depth, display size, and resolution. Here, we achieve a high refresh time multiplexing method that can effectively increase the display resolution by up to 32 times. Ferroelectric Liquid Crystal (FLC) with a fast response at 2 kHz and an optimized charge compensation method is proposed in this *** is very promising for light field 3D displays in the future. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Time division multiplexing

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GCN-LSTM Based Transient Angle Stability Assessment Method for Future Power Systems Considering Spatial-temporal Disturbance Response Characteristics

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Protection and Control of Modern Power Systems 2024年第6期9卷 108-121页

作者： Shiwei Xia Chenhui Zhang Yahan Li Gengyin Li Linlin Ma Ning Zhou Ziqing Zhu Huan Ma the School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China the State Grid Shandong Dispatch and Control Center Jinan 250003China the State Grid Shandong Electric Power Research Institute Jinan 250001China the Department of Computer Science Hong Kong Baptist UniversityHong Kong 999077China

Traditional transient angle stability analysis methods do not fully consider the spatial characteristics of the network topology and the temporal characteristics of the time-series ***,a data-driven method is proposed in this study,combining graph convolution network and long short-term memory network(GCN-LSTM)to analyze the transient power angle sta-bility by exploring the spatiotemporal disturbance char-acteristics of future power systems with high penetration of renewable energy sources(wind and solar energy)and power *** key time-series electrical state quantities are considered as the initial input feature quantities and normalized using the Z-score,whereas the network adjacency matrix is constructed according to the system network *** normalized feature quan-tities and network adjacency matrix were used as the inputs of the GCN to obtain the spatial features,reflecting changes in the network ***,the spa-tial features are inputted into the LSTM network to ob-tain the temporal features,reflecting dynamic changes in the transient power angle of the ***,the spatiotemporal features are fused through a fully con-nected network to analyze the transient power angle stability of future power systems,and the softmax activa-tion cross-entropy loss functions are used to predict the stability of the *** proposed transient power angle stability assessment method is tested on a 500 kV AC-DC practical power system,and the simulation results show that the proposed method could effectively mine the spatiotemporal disturbance characteristics of power sys-tems. Moreover, the proposed model has higher accuracy, higher recall rate, and shorter training and testing times than traditional transient power angle stability algo-rithms.

关键词： Future power system spatiotemporal disturbance characteristics transient power angle stabil-ity graph convolutional network long short-term memory network.

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