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

作者： Farajpour, Reza Sarparast, Mojtaba Adabi, Jafar Noshirvani University Of Technology Faculty of Electrical and Computer Engineering Babol Iran

ISBN: (纸本)9798331533946

This paper addresses the challenge of commonmode voltage (CMV) generation in three-phase two-level back-to-back converters, which are a significant source of electromagnetic interference (EMI) in variable-speed drive (VSD) applications. The rapid switching in these converters often produces high CMV, inducing damaging shaft voltages in motor bearings and requiring costly EMI filtering to meet electromagnetic compatibility (EMC) standards. A novel pulsewidth modulation (PWM) strategies are proposed in two steps and evaluated to reduce CMV amplitudes without compromising inverter performance. These strategies operate by controlling the switching sequences of both rectifier and inverter, effectively limiting CMV to two distinct levels: ± 23 V d c, ± 13 Vdc. Simulation results demonstrate significant CMV reductions for each method, validating their effectiveness and practical feasibility. This work provides a promising approach to improving the EMI profile of back-to-back converters used in industrial drives, high-voltageDC transmission, and renewable energy systems, with applications in electric vehicles and microgrids. © 2025 IEEE.

关键词： Variable speed drives

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Investigation and Performance Analysis of a gridtied Multilevel Inverter for Industrial Applications 16

Investigation and Performance Analysis of a gridtied Multile...

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

作者： Roshan, Maryam Reza Ali Sani Farajpour, Reza Adabi, Jafar Noshirvani University Of Technology Faculty of Electrical and Computer Engineering Babol Iran

ISBN: (纸本)9798331533946

This paper presents a adaptable multilevel inverter design utilizing the Packed E-Cell (PEC) configuration. This topology is well-suited for converting energy generated by photovoltaic systems to power AC loads and for use in uninterruptible power supplies (UPS). Key benefits of this inverter include a reduced requirement for power switches and gate drivers compared with traditional inverters, as well as a simplified control system. By positioning the shunt capacitors horizontally, both can be charged and discharged simultaneously to one-fourth of the input source. Consequently, with two isolated input sources, the inverter achieves the output voltage with 17 levels. A simple level-shifted pulse width modulation (LS-PWM) technique is employed to regulate the operation of the inverter. The performance and use of the multilevel inverter are verified through MATLAB-based simulations. © 2025 IEEE.

关键词： Uninterruptible power systems

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Contactless Diagnostics of Dry Transformers During Operation Condition 15

Contactless Diagnostics of Dry Transformers During Operation...

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15th International Conference Elektro, ELEKTRO 2024

作者： Gutten, Miroslav Korenciak, Daniel Karman, Martin Paskala, Marek Koltunowicz, Tomasz N. University of Zilina Faculty of Electrical Engineering and Information Technology Zilina Slovakia University of Zilina Faculty of Electrical Engineering and Information Technology Slovakia Lublin University of Technology Department of Electrical Apparatus and High Voltages Technology Poland

ISBN: (纸本)9798350372359

The examination of the increasing noise in the distribution transformer station next to the offices is the focus of this paper. Office workers' mental health has been found to be disturbed by some features of transformer noise at tone frequencies about 400 Hz, even if the standard for noise exposure in the workplace is satisfactory. The noise analysis is focused on acoustic measurements carried out on two 22/0.4kV power dry transformers with the same performance, while one of them, referred to as 'noisier', negatively affects the working well-being of employees. During the acoustic analysis, a parabolic camera was used to identify the cause of the increased noise from the exposed transformer. This procedure makes it possible to analyze the frequency spectrum with the possibility of 3D observation of the dry transformer and to determine the displayed point with the highest noise and acoustic emission. The analysis was carried out during the operation of only one power transformer under no-load conditions and under real load in order to avoid the mutual influence of emission interference. © 2024 IEEE.

关键词： Power transformers

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Monitoring COVID-19 environment: a real-time facial mask detection using YOLO models

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Research on Biomedical engineering 2025年第1期41卷 1-18页

作者： Pandiyan, P. Thangaraj, Rajasekaran V, Balasubramanian V. K, Manavalasundaram S, Balakrishnan Department of Electrical and Electronics Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Nandha Engineering College Erode India Department of Information Technology Velalar College of Engineering and Technology Erode India Department of Computer Science and Engineering Aarupadai Veedu Institute of Technology Chennai India Department of Computer Science and Engineering Sri Ramakrishna Institute of Technology Coimbatore India

Purpose: The rapid spread of COVID-19 has resulted in significant harm and impacted tens of millions of people globally. In order to prevent the transmission of the virus, individuals often wear masks as a protective measure for themselves and others. Coronavirus protection guidelines have been published by the World Health Organization (WHO). According to WHO standards, COVID-19 can be prevented by wearing a mask in public places and congested regions. In these places, it is very difficult to personally check to see if people are wearing face masks or not. Methods: The objective of this research work is to build a powerful, efficient, and real-time approach for detecting people not wearing masks. Three cutting-edge object identification models, namely YOLOv4, Tiny-YOLOv4, and YOLOv5, are employed in this study for the identification of masked faces. Result: The proposed YOLOv5 model is evaluated using real-time images captured using a smartphone or tablet. The test images include both single and multiple people with and without masks. The YOLOv5 model achieved recognition accuracy of 88.90% with an average detection speed of 0.0316 s per image, whereas the YOLOv4 and Tiny-YOLOv4 produced recognition accuracy of 82.24% and 74.80% with an average detection speed of 0.0530 s and 0.0541 s per image, respectively. Conclusion: The comparative performance suggests that the YOLOv5 model has a maximum recognition accuracy of 88.90% in face mask identification tasks compared to other models such as the YOLOv4 and Tiny-YOLOv4. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2025.

关键词： COVID-19

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib Mushtaq Muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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An artificial systems,computational experiments and parallel execution-based surface electromyogram-driven anti-disturbance zeroing neurodynamic strategy for upper limb human-robot interaction control

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CAAI Transactions on Intelligence technology 2024年第2期9卷 511-525页

作者： Yongbai Liu Keping Liu Gang Wang Jiliang Zhang Yao Chou Zhongbo Sun Department of Mechanical Engineering Changchun University of TechnologyChangchunChina Department of Control Engineering Changchun University of TechnologyChangchunChina School of Electrical and Information Engineering Jilin Engineering Normal UniversityChangchunChina College of Information Science and Engineering Northeastern UniversityShenyangChina Department of Electrical and Computer Engineering Brigham Young UniversityProvoUtahUSA

In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ***,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be *** deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI *** upper limb-robotic exoskeleton system is re-modelled as an artificial *** on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical ***,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and *** results substantiate the global convergence and robustness of the proposed controller in the presence of different external *** addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.

关键词： neural network pattern recognition robotics signal processing

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Deploying Testbed Docker-based application for Encryption as a Service in Kubernetes 32

Deploying Testbed Docker-based application for Encryption as...

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32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Javadpour, Amir Ja'fari, Forough Taleb, Tarik Benzaid, Chafika Rosa, Luis Tomas, Pedro Cordeiro, Luis Ictficial Oy Espoo Finland Sharif University of Technology Department of Computer Engineering Iran Ruhr University Bochum Faculty of Electrical Engineering and Information Technology Bochum Germany University of Oulu Faculty of Information Technology and Electrical Engineering Oulu Finland OneSource Coimbra Portugal

ISBN: (纸本)9789532901382

The scalability of today's networking infrastructures, such as Kubernetes, has increased the demand for everything-as-a-service concepts, including encryption services. This paper details deploying an Encryption as a Service (EaaS) framework on Kubernetes. In our current implementation, a web platform is dedicated to the subscription processes and managing the requested services. Service providers subscribe to receive encryption and decryption services for their clients, and a token is assigned to them. The client, or better to say, the devices covered by that service provider, can use encryption/decryption to specify that token. As our implemented web platform is written in Django, through this paper, we have discussed the deployment of Django applications on Kubernetes and the role of two other services (i.e., Database and Nginx) to make it available. The services are executed on Docker containers and deployed on Kubernetes pods. We have also explained the steps to build Docker containers, including the details of Dockerfiles. We have deployed this framework on both local and remote Kubernetes environments. The former deployment was performed by setting up a local Minikube cluster, while the latter assumes a remote Kubernetes cluster, and we are connecting to it through a VPN. We have tested the availability and accuracy of the encryption/decryption services and checked the logs to ensure that these services work correctly. We aim to present this article to assist researchers wishing to conduct effective testing or a Testbed in the real world. © 2024 University of Split, FESB.

关键词： Testbeds

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Deep Learning in Medical Image Analysis for Personalized Medicine 65

Deep Learning in Medical Image Analysis for Personalized Med...

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65th International Symposium ELMAR, ELMAR 2023

作者： Galic, Irena Habijan, Marija Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek31000 Croatia

ISBN: (纸本)9798350325126

Deep learning (DL) has transformed the field of medical image processing, enabling unprecedented accuracy and efficiency in various applications. It has been widely utilized for medical image analysis of different anatomical regions. In this article, we provide an overview of commonly used deep learning methods, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). We briefly overview their applications in medical image analysis, such as image classification, object detection/localization, segmentation, generation, and registration. We also highlight the strengths and limitations of each method and identify the challenges that still need to be addressed, including the limited availability of annotated data, variability in medical images, and the interpretability issue. Finally, we discuss future research directions, including developing explainable deep learning methods and integrating multi-modal data. © 2023 IEEE.

关键词： Object detection

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A Comprehensive Synthesis of Frequency Stability in Isolated AC Microgrids

A Comprehensive Synthesis of Frequency Stability in Isolated...

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2024 IEEE International Conference on Smart Systems and Power Management, IC2SPM 2024

作者： Abedini, Fatemeh Teuscher, Jens Chemnitz University of Technology Faculty of Electrical Engineering and Information Technology Chemnitz Germany

ISBN: (纸本)9798331529796

Conventional power grids consist predominantly of traditional power generation assets and sources such as oil, coal, and gas power plants. Nowadays power grids are rapidly developing towards an increasing share of power generation from renewable energy sources such as wind, solar power and fuel cells. These new assets need power electronic converters to be connected to the main grid. With this increasing trend in using inverter-based power generation equipment inverters will play a crucial role in regulation and stability of grids in the future. The management of stability in modern power grids is based on a wealth of experience and knowledge accumulated over decades of research, experimentation, and practical application. In particular, this expertise includes a deep understanding of the physical properties of large synchronous generators, which have played a critical role in maintaining grid's stability and reliability. In future grids, energy sources are mainly photovoltaic and wind energy feed, which are connected to the grid through power electronic equipment and therefore do not provide any additional inertia to the grid. Hence, the stability turns out to be a serious problem, as the power system may lose its stability under slight perturbation, e.g., start-up or shut down of a diesel generator. Therefore, new control methods or new combinations of control methods need to be considered. This paper offers important perspectives on the present state and future trends of frequency stability in AC microgrids and power systems. © 2024 IEEE.

关键词： Frequency stability

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MQTT based monitoring and control system for remote stations in automotive industry

MQTT based monitoring and control system for remote stations...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Ivanovic, Denis Job, Josip Puntaric, Marko Herceg, Marijan TTTech-Auto CX Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Software Engineering Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Communications Osijek Croatia

ISBN: (纸本)9798350347722

In this paper is presented implementation of a lightweight supervisory control and data acquisition system for remote test stations as a part of a larger test house in the automotive industry. It is necessary to allow remote set up and monitoring of the test stations, which means defining the structure of a system with numerous test stations as endpoints. The test stations are meant to be virtual machines but can be both virtual and physical machines. A communication protocol must be used that enables this within the organization's network, regardless of actual distance and location. The parameters of the test stations to be monitored can be defined according to the needs and purpose. Even when creating your own tool, this function is not unique, i.e. on one test station parameters of operating system resources such as memory usage can be monitored, while on another test station logged-in users or running programs, reported system errors and others must be monitored. Data storage is one of the mandatory functions of this system. This process allows viewing data throughout history and more detailed analysis of events. There are numerous benefits that can be drawn and used from the data stored in the database. It is necessary to pay attention to the data stored as well as the scope and retention throughout history. The correct and secure setup of a database is one of the prerequisites for any serious system that processes data. Appropriate views should be created for users involved in the data monitoring process using all the elements mentioned so far. Creating a visually acceptable and easy-To-use interface that serves the main purpose is the final presentation of the entire system to users. A complete system leads to higher productivity, profitability and better organization of the company. It also allows project managers to better plan the use and occupancy of test stations. At any time, they have insight into the status of individual test stations, their activitie

关键词： Automotive industry

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