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4th IEEE Global Conference for Advancement in technology, GCAT 2023

作者： Sajedul Islam, Md. Tabassum, Fariya Dept. of Electrical & Computer Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (纸本)9798350305258

Wide bandgap (WBG) semiconductor devices namely SiC-MOSFET enable high-frequency power converters, which have benefits over many other switching devices in terms of power density and dynamic performance. However, switching oscillation is a common problem for this class of devices, and it has a lot of unfavorable effects. This work examines the underlying causes of the switching oscillation, its effects on the system, and modeling analysis to derive control mechanisms to prevent undesirable outcomes. This work discusses the underlying causes of the switching oscillation, which are: (1) di/dt or/and dv/dt -induced damped oscillation in the presence of parasitic factors;(2) undamped oscillation brought on by the switch's negative resistance;(3) effect of the negative capacitance phenomena brought on by the semiconductor devices' physical orientation. An effective control approach is proposed in this research work to inhibit the switching oscillation of SiC-MOSFET. The proposed integrator-based damper takes into account the turn on switching oscillation. The performance of the proposed damper is compared with the integral and proportional-integral-derivative (PID) controller for justifying its effectiveness. © 2023 IEEE.

关键词： Control System Power Converter Semiconductor WBG Device

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YOLOv8 Based Object Detection for Self-driving Cars 26

YOLOv8 Based Object Detection for Self-driving Cars

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Afrin, Zakia Tabassum, Fariya Kibria, Hafsa Binte Imam, Md. Rafi Hasan, Md. Rokibul Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350359015

The investigation focuses on improving object detection in roadmaps for self-driving cars using the YOLOv8 model. Object detection is a pivotal component in developing autonomous vehicles, enabling them to identify and track diverse objects like cars, trucks, pedestrians, bicyclists, and traffic lights in their natural surroundings. The central goal of this study is to elevate the accuracy and efficiency of object detection methods for self-driving cars. The critical methodology employed in this research is the "You Only Look Once"(YOLO) approach. YOLO is indispensable for real-time object detection, allowing the vehicle to process a single image in a single forward pass, facilitating rapid decision-making. Object detection holds paramount importance in the realm of self-driving cars as it empowers vehicles to perceive and respond to their environment effectively. YOLO addresses this imperative by introducing a swift and precise object detection algorithm. This study's hardware configuration meticulously designed for computational tasks ensures efficient processing, a critical aspect for real-time applications in self-driving cars. The integration of advanced hardware accelerators significantly contributes to the study's success. The model's mean Average Precision (mAP) achieved an impressive 77.8%, underscoring its proficiency in accurately detecting objects across various scenarios. The YOLOv8 model met and surpassed expectations through this research, providing robust object detection capabilities in real-world situations. This remarkable outcome emphasizes the YOLOv8 model's effectiveness in self-driving cars, offering dependable object detection for safe navigation. © 2023 IEEE.

关键词： Autonomous Vehicles Self-Driving YOLOv8

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Drivers' Drowsiness Detection System Enhancement Using Deep Learning: CNN-based Approach 26

Drivers' Drowsiness Detection System Enhancement Using Deep ...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Ahmed, Tamal Jyoti, Oishi Mou, Tamanna Hossain Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350359015

Driver drowsiness detection is a critical safety technology aimed at reducing accidents caused by driver fatigue. This study presents the creation of a real-time system for detecting driver drowsiness through the application of machine learning techniques. The system utilizes data on eye and mouth states, recognized as reliable indicators of drowsiness. The model, developed using Convolutional Neural Network (CNN), was trained on two factors and four features, providing a comprehensive approach to drowsiness detection. The resulting driver drowsiness detection system achieved an average accuracy of 97.23%. This research contributes significantly to the progress of road safety technology and accident prevention. Additionally, the proposed model demonstrates superior accuracy and speed compared to previous work, with a detailed comparison of outcomes from various models employed. © 2023 IEEE.

关键词： 4D CNN Convolutional Neural Network(CNN) Driver Drowsiness Detection

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Implementation of Variable Capacitance to Improve Efficiency for Asymmetric LCC-LCC Compensated Wireless Power Transfer Systems

Implementation of Variable Capacitance to Improve Efficiency...

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2024 Energy Conversion Congress and Expo Europe, ECCE Europe 2024

作者： Zhu, Gangwei Dong, Jianning Wang, Jundong Deng, Zichen Li, Yongpeng Bauer, Pavol Delft University of Technology Mathematics and Computer Science Department of Electrical Engineering Delft Netherlands

ISBN: (纸本)9798350364446

This paper proposes a variable-capacitance-based control strategy to improve efficiency for asymmetric LCC-LCC compensated wireless power transfer (WPT) systems. While the existing triple-phase-shift (TPS) method can achieve power regulation and wide-range zero-voltage-switching (ZVS), it results in significantly increased reactive power under asymmetric LCC-LCC compensation topology. To this end, this paper incorporates a switch-controlled-capacitor (SCC) on the primary side. The impact of variable capacitance on the system characteristics is first investigated. Furthermore, the optimal capacitor tuning factor is derived to achieve the inverter ZVS with minimal reactive power. Through the implementation of variable capacitance, the primary inductor current is notably reduced within a wide range of power. Moreover, the turn-off currents of power switches are minimized. These factors contribute to a reduction in inductor and inverter losses, thus improving the overall efficiency. Experimental results confirm that the proposed method improves the efficiency of an asymmetric LCC-LCC compensated WPT prototype, with a maximum efficiency improvement of up to 1.8%. © 2024 IEEE.

关键词： Capacitor bank

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Different Schemes for Reducing the Number of Measurement Components in Alternate Arm Multilevel Converter (AAMC) 16

Different Schemes for Reducing the Number of Measurement Com...

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16th Annual Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2025

作者： Bagheri Hashkavayi, M. Masoud Barakati, S. Saeid Mohtavipour, S. Sadafi, Mojtaba Darmian, Saeed Yousofi University of Sistan and Baluchestan Department of Electrical and Computer Engineering Zahedan Iran University of Guilan Department of Electrical and Computer Engineering Rasht Iran Esfarayen University of Technology Department of Electrical and Computer Engineering Esfarayen Iran Regional Electric Co. of Sistan and Baluchestan Department of Research and Planning Zahedan Iran

ISBN: (纸本)9798331533946

A promising solution for operations in the moderate voltage and high-power ranges, the Alternate Arm Multilevel Converter (AAMC) distinguishes itself with a distinctive topology as an AC-DC Voltage Source Converter (VSC). However, traditional implementations require numerous sensors to maintain capacitor voltage balancing across series Full-Bridge Sub-Modules (FB-SBs). Introducing an innovative approach to enhance AAMC efficiency, this study proposes two sensor reduction methods for calculating capacitor voltages with estimation algorithms, demonstrating the current paths within each method. These streamlined approaches simplify the control structure and eliminate the requirement for individual current sensors in each phase and voltage sensors per FB-SBs. By continuously adjusting capacitor voltages based on estimated values used by data from executed last steps and switching signals, the provided methods achieve precise voltage balance with minimal estimation error. The methods' effectiveness is validated through extensive simulations achieved by MATLAB Simulink software across various operational conditions. The results demonstrate notable reductions in measurement component requirements while maintaining robust performance in AAMC applications. This research highlights the potential of optimizing sensor utilization to improve the performance of voltage source converter technologies in the future. © 2025 IEEE.

关键词： Capacitor bank

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Effect of Cotton Dust Morphology on Photovoltaic Module Performance

Effect of Cotton Dust Morphology on Photovoltaic Module Perf...

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2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024

作者： Ali, Basit Khan, M. Faisal Ishaque, Kashif Faculty Of Engineering Sciences & Technology Hamdard University Graduate School Of Engineering Sciences & Information Technology Karachi Pakistan Bahria University Department Of Electrical Engineering Karachi Pakistan Faculty Of Engineering Sciences & Technology Hamdard University Department Of Electrical Engineering Karachi Pakistan Muhammad Ali Jinnah University Department Of Electrical And Computer Engineering Karachi Pakistan

ISBN: (纸本)9798331515850

The use of renewable energy is increasing due to the high cost of conventional fuels and climate issues. Textile industries, specifically in Asian region, are shifting towards large PV plants in order to acquire cheap and clean energy. However, cotton dust presence in the textile mill environment causes performance issues for PV modules. This study examines the cotton dust particle effect on PV module by employing an experimental methodology. An indoor experimental setup is utilized to test the PV modules in two schemes, that are clean and dusty. The experiment is conducted for eight days with an hourly interval. It is observed that PV power output reduces significantly up to 15% in eight days as compared to clean PV module. The deposited cotton dust particles are also physically examined through compound microscope in order to determine its physical nature. It is being observed that cotton particles are composed of long, smooth fibers with irregular shapes. The particles are highly influenced by humidity, and their own high content of cellulose makes them vulnerable to stick on the PV surface and forming clumps and aggleromates that develop the hotspots on the PV surface. Along with that, as time progresses the cotton dust opaqueness also increases, ultimately reducing the transmittance and decreasing PV module performance. This study helps to devise a unique cleaning patterns and methods for textile units to enhance performance output. © 2024 IEEE.

关键词： Textile industry

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DeePLS: Personalize Lighting in Smart Home by Human Detection, Recognition, and Tracking

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SN computer Science 2023年第6期4卷 773页

作者： Sobhani, Ali Khorshidi, Fatemeh Fakhredanesh, Mohammad Faculty of Electrical and Computer Engineering Malek-Ashtar University of Technology Tehran Iran

In recent years, the intelligence of different parts of the home has become one of the essential features of any modern home. One of these parts is the intelligence lighting system that personalizes the light for each person. This paper proposes such an intelligent system based on machine vision approaches: human detection to detect and localize the person in each given video frame, face recognition to identify the detected person, and human tracking to track the person in the sequence of video frames. In the proposed method, a unique profile is provided for each person, including specifications, face images, and custom lighting settings. This profile is used in the lighting adjustment process. Unlike some other methods that consider constant lighting for every person, our system can apply each person’s desired lighting in terms of color and light intensity without direct user intervention. Therefore, the lighting is adjusted with higher speed and better efficiency. In addition, the desired lighting creates more pleasant and comfortable conditions for the residents of the home. In the experimental results, the system applied the desired lighting in an average time of 1.4 s from the moment of entry, as well as a performance of 22.1mAp in human detection, 95.12% accuracy in face recognition, and 93.3% MDP in human tracking. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep neural network Face recognition Human detection Smart home Smart lighting Tracking

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Heat Transfer Area Optimization for Heat Exchanger System

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computer Modeling in engineering & Sciences 2025年第4期143卷 335-349页

作者： Yu-Cheng Liao Fu-I Chou Po-Yuan Yang Jyh-Horng Chou Department of Electrical Engineering National Kaohsiung University of Science and TechnologyKaohsiung807Taiwan Department of Intelligent Robotics National Pingtung UniversityPingtung900Taiwan Department of Mechanical and Computer-Aided Engineering Feng Chia UniversityTaichung407Taiwan

This paper presents an allowable-tolerance-based group search optimization(AT-GSO),which combines the robust GSO(R-GSO)and the external quality design planning of the Taguchi ***-GSO algorithm is used to optimize the heat transfer area of the heat exchanger *** R-GSO algorithm integrates the GSO algorithm with the Taguchi method,utilizing the Taguchi method to determine the optimal producer in each iteration of the GSO algorithm to strengthen the robustness of the search process and the ability to find the global *** conventional parameter design optimization,it is typically assumed that the designed parameters can be applied accurately and consistently throughout ***,for systems that are sensitive to changes in design parameters,even minor inaccuracies can substantially reduce overall system ***,the permissible variations of the design parameters are considered in the tolerance-optimized design to ensure the robustness of the *** optimized design of the heat exchanger system assumes that the system’s operating temperature parameters are ***,fixing the systemoperating temperature parameters at a constant value is *** paper assumes that the system operating temperature parameters have an uncertainty error when optimizing the heat transfer area of the heat exchanger *** results show that the AT-GSO algorithm optimizes the heat exchanger system and finds the optimal operating temperature in the absence of tolerance and under three tolerance conditions.

关键词： Heat exchanger system allowable tolerance-based group search optimization Taguchi method tolerance design

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Practical Implementation of Robust Human Activity Cataloguing with mmWave Radar

Practical Implementation of Robust Human Activity Cataloguin...

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2024 IEEE Opportunity Research Scholars Symposium, ORSS 2024

作者： Mii, Hiroki Shah, Swarna Lu, Bozhou Liu, Alan Lin, Yu-Tai Sundaresan, Karthikeyan Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States

ISBN: (纸本)9798350390698

Millimeter wave (mmWave) radar has recently become a popular choice of sensing technology for privacy-protecting health monitoring solutions. Though mmWave radar improves upon invasive alternatives like computer vision, the cost of privacy protection is sparser data. Many machine learning models designed to process this data are either computationally heavy or lack robustness and are impractical to deploy in real-time as required by applications such as physical therapy assistance, remote healthcare, and personal fitness assistance. Therefore, we aim to deploy a well-designed RF-driven Human Activity Cataloguer (RF-HAC) [1] for real-time operation. The model detects, categorizes, and counts repetitions of human exercises, and has a robust, accurate classification algorithm. To deploy this model into a real-time system, we focused on optimizing the data flow pipeline to stream data from the radar and process it to receive an output within seconds of the activity occurrence. Our system reduces the processing time from 3.1819 seconds to 1.1161 seconds, and our implemented data streaming pipeline produces a real-time output while maintaining a classification accuracy of 94%. © 2024 IEEE.

关键词： Data transfer

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Comparative Analysis of MEMS Tuning Fork Gyroscope Designs with Microlever Amplification Mechanism for Enhanced Sensitivity and Robustness 6

Comparative Analysis of MEMS Tuning Fork Gyroscope Designs w...

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6th International Conference on Robotics and Automation in Industry, ICRAI 2024

作者： Bashir, Uzair Javaid, Faraz Ali, Osama Arshad, Adeel Rehman, Masood Ur Department of Electrical and Computer Engineering Islamabad Pakistan Department of Mechatronics Engineering Islamabad Pakistan Superior University Faculty of Engineering and Technology Lahore Pakistan

ISBN: (纸本)9798350355703

This paper presents a comparative analysis of two MEMS Tuning Fork Gyroscope (TFG) designs employing microlever amplification mechanisms for sensitivity amplification in the sense mode. An input frame added in microlever amplification frame to increase the robustness of MEMS gyroscope. Design A incorporates a non-anchored input frame in microlever, while Design B features an anchored input frame in microlever. Frequency response analysis and modal analysis were performed using CoventorMEMS+ to evaluate the impact of input frame of microlever on undesired mode suppression, mechanical sensitivity, and robustness. The results indicate that anchoring the microlever in Design B significantly reduces quadrature displacement arise because of environmental linear acceleration in the sense mode while maintaining comparable amplified sensitivity to Design A. Design B offers enhanced stability and robustness, making it a more suitable candidate for precision applications such as autonomous vehicle navigation systems. © 2024 IEEE.

关键词： Gyroscopes

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