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6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Akhtaruzzaman, M. Islam, Md Shofiqul Shahryer, Fahim Arif, Muammer Din Mollik, Md. Sazib Rahman, Muhammad Towfiqur Rahman, Md. Mahbubur Hasan, Mohammad Kamrul Ahmed, Shugata Ashrafuzzaman, Md. Department of Computer Science and Engineering Dhaka1216 Bangladesh Department of Mechanical Engineering Dhaka1216 Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh Faculty of Information Science and Technology Bangi Malaysia Department of Robotics and Mechatronics Engineering Bangladesh Sdn. Bhd. Cyberjaya Malaysia

ISBN: (纸本)9798350385779

The persistent challenges faced by sun-tracking systems include inefficient power production, wastage of energy, ineffective control, and high costs. Most of the existing systems are either static or dual-axis tracking which lead to inefficient output or increasing energy wastage and cost overheads. Though, single-axis tracking system has some benefits over the static or dual-axis tracking, most of the systems do not analyze the selection of optimal sun-path which again leads to inefficient and inadequate absorption of sunlight. Addressing the issues, this article presents a design of optimal parameters for single-axis solar-tracking by analyzing the sun-path and tracking vector dynamics. The study mainly focuses on analyzing solar-tracking dynamics, variations in sunray angles, Azimuth and Elevation dynamics throughout the day for the twelve months, Sun-vector calculation for local coordinates, joint rotational-axis, and joint motion control using a Proportional-Derivative controller. Additionally, the article outlines a conceptual architecture for automated control, monitoring, and power distribution for the potential development of a sustainable smart city. The proposed strategy addresses the issues of the optimal design of a single-axis solar-tracker, thus ensuring the reduction of cost overhead and energy wastage. © 2024 IEEE.

关键词： Dynamics

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A comprehensive survey on 6G-security: physical connection and service layers

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Discover Internet of Things 2025年第1期5卷 1-30页

作者： Saeed, Mamoon M. Saeed, Rashid A. Hasan, Mohammad Kamrul Ali, Elmustafa Sayed Mazha, Tehseen Shahzad, Tariq Khan, Sunawar Hamam, Habib Sana00967 Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electronics Engineering College of Electronics Engineering Sudan University of Science and Technology Omdurman Sudan Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Red Sea University Port Sudan33312 Sudan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Computer Science and Software Engineering International Islamic University Islamabad44000 Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa BP 1989 Av. Grandes Ecoles Libreville Gabon Bridges for Academic Excellence-Spectrum Tunis Tunisia Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations. © The Author(s) 2025.

关键词： 5G mobile communication systems

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Classification of Stress using Machine Learning Based on Physiological and Psychological Data from Wearables 15

Classification of Stress using Machine Learning Based on Phy...

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15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Pauzi, Tuan Muhamad Affiq Aimullah Tuan Mohd Samah, Asma Abu Dela Cruz, Jennifer C. Ghaffa, Dalilah Nordin, Rosdiadee Abdullah, Nor Fadzilah Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and Systems Engineering Bangi Malaysia Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Wireless Research@UKM Department of Electrical Electronic and Systems Engineering Bangi Malaysia School of Electrical Electronics and Computer Engineering Mapua University Manila Philippines

ISBN: (纸本)9798350381177

Stress is a common psychological issue in today's world, causing individuals to experience physiological and behavioral changes. When someone experiences stress for a prolonged period, it can have an impact on their body and thoughts, leading to severe behaviors. Stress-related problems can be prevented if identified early. Nowadays, researchers' use of machine learning in early disease detection is increasing, offering a solution to stress-related issues. This study focuses on developing a machine learning predictive model for classifying stress levels using physiological data. Physiological data is obtained from an open-source dataset containing biosignal data such as Electrodermal (EDA), Skin Temperature, Heart Rate (HR), Blood Volume Pulse (BVP), and others. The dataset is then used to train a machine learning model using Support Vector Machine (SVM), Random Forest (RF), Adaboost, and Bootstrapping algorithms. Accuracy, precision, recall, and F1-score are used to evaluate the model's performance. As a result, the predictive model using the Bootstrapping algorithm achieves the best performance with an accuracy of 95.82%, a precision of 99.33%, a recall of 98.02%, and F1-score of 94.69% compared to other machine learning classifiers. Creating such models can aid in early stress detection once they are integrated into a wearable device for continuous monitoring purposes. © 2023 IEEE.

关键词： Decision trees

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Efficient CNN-Based Automatic Modulation Classification in UWA Communication Systems Using Constellation Diagrams and Gabor Filtering 3

Efficient CNN-Based Automatic Modulation Classification in U...

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3rd IEEE International Conference on electronic engineering, ICEEM 2023

作者： Abdel-Moneim, Mohamed A. El-Rabaie, S. Abd El-Samie, Fathi E. Ramadan, Khaled Abdel-Salam, Nariman Ramadan, Khalil F. Egyptian Russian University Faculty of Engineering Department of Telecommunication Cairo Egypt Menoufia University Faculty of Electronic Engineering Electronics and Electrical Communications Engineering Department Menouf32952 Egypt The Higher Institute of Engineering at Al-Shorouk City Communication and Computer Engineering Department Cairo Egypt Faculty of Engineering Communications and Electronics Engineering Department Giza Egypt

ISBN: (纸本)9798350323511

Underwater Acoustic (UWA) communication channels are varying in nature due to various underwater conditions. The efficiency of the UWA communication system can be increased by changing transmission parameters over UWA channels based on the state of the channel. The aim of Automatic Modulation Classification (AMC) is to recognize efficiently the modulation schemes from signals received over UWA channels. In this paper, we propose an efficient method that combines equalization, Gabor filtering of constellation diagrams, thresholding and deep convolutional neural networks (CNNs) for modulation classification over the Signal-to-Noise Ratio (SNR) range of -10 to 30 dB in UWA systems. Simulation results of the proposed method indicated an acceptable performance over a wide SNR range. © 2023 IEEE.

关键词： Gabor filters

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Enhancing the Evaluation Performance of Convolutional Neural Networks-Based Vehicle Classification Systems

Enhancing the Evaluation Performance of Convolutional Neural...

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2023 International Conference on Cognitive Computing and Complex Data, ICCD 2023

作者： Kiyindou, Michel Precieux Sunday, Samuel Enobong Hong, Zhou Huaiyin Institute of Technology Faculty of Electronic Information Engineering Huai'an City China Huaiyin Institute of Technology Foreign Expeert Workshop Huai'an Faculty of Computer Engineering Huai'an City China

ISBN: (纸本)9798350306293

The rapid advancement of artificial intelligence, particularly deep learning, has spurred its integration into diverse domains. Among these, the application of deep learning in vehicle classification stands out as a vital focus within intelligent transportation systems, road traffic planning, safety warning, and driverless driving. In this research, a comprehensive approach of CNN's evolution such as LeNet, AlexNet, and other CNN-based vehicle classification techniques are enhanced for a better performance, while also investigating R-CNN, YOLO, and related methods for vehicle detection. Evaluative datasets for these methods are highlighted. Moreover, the enhancement of the computing power of the Graphics Processing Unit (GPU) and the sharp increase in the amount of data, deep learning based on convolutional neural networks has become a research hotspot. To evaluate the accuracy and efficiency of our vehicle detection methods, RCNN and YOLO series datasets were used to evaluate these methods and an the development of CNN as the main line was introduced and use to analyze the vehicle classification methods based on LeNet, AlexNet and other CNNs. This research is pivotal for vehicle tracking, traffic management, and autonomous driving progress. In this landscape, convolutional neural networks (CNNs), self-encoder neural networks, and deep belief networks take prominence, with CNNs evolving as the most dynamic. Notably, CNN's development has led to refined vehicle classification through models like LeNet, AlexNet, VGG, and GoogLeNet. The paper concludes by outlining prospective research directions in this domain. © 2023 IEEE.

关键词： Convolutional neural networks

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Differential coding scheme based FSO channel for optical coherent DP-16 QAM transceiver systems

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Journal of Optical Communications 2024年第2期45卷 331-345页

作者： Urooj, Shabana Alwadai, Norah Muhammad Sorathiya, Vishal Lavadiya, Sunil Parmar, Juveriya Patel, Shobhit K. Abd El-Aziz, Ismail A. Rashed, Ahmed Nabih Zaki Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf 32951 Egypt Department of Electrical Engineering College of Engineering Princess Nourah bint Abdulrahman University Riyadh84428 Saudi Arabia Department of Physics College of Sciences Princess Nourah bint Abdulrahman University Riyadh84428 Saudi Arabia Department of Information and Communication Technology Marwadi University Rajkot India Department of Physics Marwadi University Rajkot360003 India Department of Electronics and Communication Engineering Marwadi University Rajkot360003 India Department of Computer Engineering Marwadi University Rajkot360003 India Benha Faculty of Engineering Benha University Benha Egypt

This article has indicated optical coherent differential polarization (DP) 16 quadrature amplitude modulation (QAM) transceiver systems with free-space optical (FSO) channel in the presence of differential coding scheme. The optical coherent DP 16-QAM receiver executes the reverse process conversion of the optical signal into an electrical one that is detected to the users. The proposed optical coherent DP-16 QAM transceiver systems based FSO channel model with differential coding has been presented and compared with the previous model. However, the simulation results have confidence realization about the superiority of the proposed simulation model. Hence the proposed optical coherent DP-16 QAM transceiver systems simulation model with differential coding is verified and validated the enhancement performance based on simulation performance parameters. © 2024 Walter de Gruyter GmbH. All rights reserved.

关键词： Quadrature amplitude modulation

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High-Efficiency Asymmetrically Designed Three-Phase Virtual 48-Pulse Power Supply for Electrolytic Hydrogen

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IEEE Transactions on Power electronics 2025年第8期40卷 10335-10342页

作者： Tian, Hanlei Cui, Haoran Han, Wei Sathik M, Jagabar Liang, Guozhuang Chen, Maolin Mekhilef, Saad Electrical Engineering School of Hebei University of Science and Technology Shijiazhuang050091 China Sustainable Energy and Environment Thrust Guangzhou511453 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong SRM Institute of Science and Technology Faculty of Engineering and Technology Kattankulathur603203 India Sichuan University College of Electrical Engineering Chengdu610065 China Swinburne University of Technology School of Science Computing and Engineering Technologies MelbourneVIC3122 Australia

To address the low-voltage, high-current requirements in hydrogen production applications, a virtual 48-pulse three-phase rectifier is proposed, and achieves the equivalent performance of four parallel 12-pulse rectifiers (12-PR). The proposed approach builds upon the conventional 12-PR design and incorporates novel asymmetric current injection units (ACIU). The ACIU is installed on the dc side of the ac-dc converter, generating a specific current at the dc link to modulate and enhance the operating modes of the 12-PR. Consequently, the 12-pulse is extended to 48, resulting in an almost sinusoidal input current with a total harmonic distortion of 3.2% and an output current with a ripple rate of 2.3%, thus significantly improving power quality. Furthermore, the asymmetric design of the current injection units eliminates the need for a phase-shifting transformer. The efficacy of the proposed rectifier for electrolytic hydrogen production is validated using a 2.2-kW experimental prototype. © 1986-2012 IEEE.

关键词： Voltage Hydrogen Rectifiers Production Windings Circuits Inductors Transformers Harmonic analysis Electrochemical processes

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IoT-Based Healthcare Monitoring System 1

IoT-Based Healthcare Monitoring System

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Al-Hadi, Marwa Abdulrahman Al-Gaphari, Ghaleb Hamoud Al-Baltah, Ibrahim Ahmed Julian, Francisco Bacallao Al-Hadi, Ahmed Abdulrahman Department of Computer Science Faculty of Computer Science and IT Sana’a University Sana’a Yemen Department of Information Technology Faculty of Computer Science and IT Sana’a University Sana’a Yemen Faculty of Science and Engineering Al-Hikma University Sana’a Yemen Cardiac-Center Military Hospital Yemen Department of Science and Technologies Faculty of Engineering and Technology Mohamed Boudiaf University M'sila Algeria Department of Industrial Electronic and Automatic Engineering Faculty of Higher Polytechnic Technology Burgos University Burgos Spain

ISBN: (纸本)9798331533557

In an era when healthcare was becoming increasingly crucial, many developing nations, including Yemen, struggled to provide basic medical services. Nearly half of Yemen's population lacked access to adequate healthcare, with the situation being even more dire in rural and remote areas. While sectors such as industry, agriculture, and environmental science rapidly embraced technological advancements, healthcare systems in these regions lagged, with limited research addressing affordable and accessible solutions. This gap was further highlighted by the global healthcare crisis and the urgent need for innovative, cost-effective approaches. In response, this study outlined the creation and deployment of a cost-effective health monitoring system utilizing Internet of Things (IoT) technology to address these challenges. The system was designed to monitor vital signs, specifically heart rate (HR), using an Arduino Uno and ECG sensor, at a meager total cost of $27.25. It provided real-time monitoring for situations requiring immediate intervention. Power consumption tests demonstrated that the system operated efficiently, consuming between 1.061 and 1.35 watts, making it practical and affordable. Additionally, the potential integration of deep learning techniques promises to enhance the system's accuracy and efficiency. Although this study focused on IoT-based health monitoring, its potential extended beyond this, offering broader implications for future healthcare technology solutions. © 2024 IEEE.

关键词： electronic health record

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MESSI: Task Mapping and Scheduling Strategy for FPGA-based Heterogeneous Real-Time Systems

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ACM Transactions on Design Automation of electronic Systems 2025年第3期30卷 1-29页

作者： Ahmadi-Pour, Sallar Saha, Sangeet Mcdonald-Maier, Klaus Drechsler, Rolf Institute of Computer Science University of Bremen Faculty 3 Mathematics and Computer Science Bremen Bremen Germany Robotics and Embedded Systems Research Group University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom Cyber-Physical Systems DFKI Rheinland-Pfalz Kaiserslautern Germany

Continuous demands for improved performance within constrained resource budgets are driving a move from homogeneous to heterogeneous processing platforms for the implementation of today's Real-Time (RT) embedded systems. The applications executing on such systems are typically represented as a Precedence Task Graph (PTG), where a node represents a task or algorithm for one functionality and edges represent the complex interactions between multiple functionalities. Due to RT constraints, the task graph needs to be executed within a specified deadline. Although some existing studies have looked into solving this challenge, comprehensive studies that combine the theoretical features of RT task-graph mapping and scheduling with practical runtime architectural characteristics have mostly been ignored to date. Hence, in this article, we consider the challenge of scheduling an RT application modeled as a single PTG, with the objective of minimizing the overall execution time under Hardware (HW) resource and deadline constraints for heterogeneous Central Processing Unit (CPU) + Field Programmable Gate Array (FPGA) architectures. First, we introduce an optimal solution using Integer Linear Programming (ILP). However, this ILP-based optimal solution suffers from computational complexity and does not scale well even for moderately large problem sizes. Hence, we additionally propose heuristic algorithms for task mapping and scheduling. The efficiency of the proposed scheme, named MESSI, has been evaluated through experiments using PTG on a practical CPU+FPGA system regarding current technology restrictions. Our experiments demonstrate that performance gains of 55.6% and area usage reductions of 46.3% are possible compared to full Software (SW) and HW execution, respectively. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Integer programming

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An MPC-controlled Bidirectional Battery Charger with DC-DC and Three-level F-type Converters 4

An MPC-controlled Bidirectional Battery Charger with DC-DC a...

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4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Guler, Naki Bagheri, Farzaneh Komurcugil, Hasan Bayhan, Sertac Gazi University Electrical and Electronic Engineering Technology Faculty Ankara Turkey Antalya Bilim University Department of Electrical and Electronic Engineering Antalya Turkey Eastern Mediterranean University Department of Computer Engineering FamagustaVia Mersin 10 Turkey Qatar Environment and Energy Research Institute Doha Qatar

ISBN: (纸本)9798350306262

This paper proposes a single-phase bidirectional battery charger which comprises a three-level F-type converter and a bidirectional dc-dc converter. The proposed charger is suitable for electric vehicles and battery energy storage systems. The bidirectional dc-dc converter is integrated into the system to prevent the charge current oscillations caused by double-line frequency voltage ripples of the F-type converter when operates as a single-phase rectifier. The F-type converter operates as rectifier and inverter during charging and discharging modes, respectively. The power flow of the battery is controlled with a bidirectional dc-dc converter. The current control of both F-type and bidirectional dc-dc converters is achieved by the model predictive control (MPC) method. The control strategy is designed by considering the power balance theory. For this purpose, the voltage of the common connection point of both converters (dc-link) is regulated. The grid current reference of the F-type converter is obtained by using a proportional-integral (PI) controller whose input is the dc-link voltage error. Thus, bidirectional power flow control is achieved. The effectiveness of the proposed power converter structure as well as the control strategy is investigated by simulation studies performed on MATLAB/Simulink environments. The results show that the proposed system is capable of controlling the grid and battery currents in both power directions. © 2024 IEEE.

关键词： Model predictive control

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