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Single-source Switched-capacitor Boost Nine-level Inverter with Reduced Components

CSEE Journal of Power and Energy Systems 2023年第5期9卷 1688-1697页

作者： Kaibalya Prasad Panda R.T.Naayagi Pravat Kumar Ray Gayadhar Panda the Department of Electrical Engineering Pandit Deendayal Energy UniversityGandhinagar 382007India the School of Electrical and Electronic Engineering Newcastle University International Singapore567739Singapore the Department of Electrical Engineering National Institute of Technology RourkelaRourkela 769008India the Department of Electrical Engineering National Institute of Technology MeghalayaShillong 793003India

Increasing demands for improvement in power quality and power capacity have contributed to development of switched-capacitor multilevel inverters(SCMLIs).Recently developed SCMLIs enable single-stage voltage boosting,as well as inversion resulting in step-up ac *** reduction in number of components,this paper introduces a boost type singlesource nine-level(9-level)SCMLI employing two capacitors and three *** to the series-parallel connection process,capacitor voltages are inherently balanced and assist in quadruple voltage boosting from a *** voltage stress across semiconductor devices is limited to twice input voltage *** a minimum number of components,the proposed SCMLI can be extended to increase voltage levels without additional dc *** extension module adds two additional voltage steps in the output while maintaining maximum voltage stress the same as 9-level *** by in-depth analysis of circuit operation and power losses,a thorough comparison of recently developed single-phase 9-level MLIs is carried out,which verifies design *** simulation and experimental results are presented to verify the prominent features of the 9-level SCMLI under dynamic operating conditions.

关键词： Multilevel inverter reduced components,self-voltage balance single-source switched-capacitor voltage gain

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A user-adaptive privacy-preserving authentication of IoMT using zero knowledge proofs with ECC

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Multimedia Tools and Applications 2025年 1-32页

作者： Misra, Garima Hazela, Bramah Chaurasia, Brijesh Kumar Department of Computer Science and Engineering Amity School of Engineering and Technology Lucknow Amity University Uttar Pradesh India Department of Computer Science & Engineering Pranveer Singh Institute of Technology Utter Pradesh Kanpur India

The Internet of Things (IoT) has developed into a crucial component for meeting the connection needs of the current smart healthcare systems. The Internet of Medical Things (IoMT) consists of medical devices that are connected to patients in order to sense their medical parameters and exchange that information with healthcare professionals so they can deliver remote healthcare services. The need to protect the patient’s private information from being misused makes IoMT security an urgent issue that merits further study. Elliptic Curve cryptography (ECC), a popular substitute for traditional public key encryption like RSA, has several advantages. ECC is a prime contender for implementation on constrained devices with confined memory and speed, as well as wireless communication protocols that use low power like IoMT environment. The economic complexity of the current security protocols makes them inappropriate, hence new security protocols must be developed for resource-constrained and diverse IoT networks. This work suggests an authenticated key agreement protocol for the IoMT that is based on elliptic curve encryption based zero-knowledge proof (ZKP) protocols. The proposed mechanism completes in order of milliseconds up to 300 ms for 160 bits. The research will include the comparison between computational delays in traditional protocols and ZKP-ECC protocol. This paper provides a protocol to obtain privacy of data in IoMT environment on the basis of zero knowledge phenomenon and anonymous communication by ZKP-ECC. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Authentication Protocol

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Fully Soft Switched Bridgeless Buck Power Factor Correction Converter 16

Fully Soft Switched Bridgeless Buck Power Factor Correction ...

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

作者： Kaviani, Kosar Maghsoudi, Mohammad Farzanehfard, Hosein Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan Iran

ISBN: (纸本)9798331533946

In this paper, a bridgeless buck PFC structure is presented. To Fulfill soft switching for the main switches an auxiliary circuitry is utilized. The main switches of the proposed structure operate under ZVS condition and the auxiliary switch operate under ZCS condition. The introduced topology operates at Discontinuous conduction mode (DCM) leading to intrinsic PFC capability. A 120 W, 100 kHz prototype is designed and simulated to validate theoretical analysis using PSIM software. The results show 97% efficiency and fully soft switching operation. © 2025 IEEE.

关键词： Buck converter

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Performance analysis and improvement of a high-efficiency DCMLI based PMSM drive for electric vehicle using AVR microcontroller

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International Journal of Vehicle Noise and Vibration 2024年第3-4期19卷 133-164页

作者： Shriwastava, Rakesh Dhote, Nitin Kadlag, Sunil Somnath Thakare, Mohan P. Kadam, Deepak P. Khule, Shridhar S. Electrical Engineering Department Matoshri College of Engineering and Research Centre Nashik India Electrical Engineering Department St. Vincent Pallotti College of Engineering and Technology Nagpur India Department of Electrical Engineering Amrutvahini College of Engineering Sangamner India Shri Vithal Education and Research Institute College of Engineering Pandharpur India Department of Electrical Engineering MET’s Institute of Engineering Nashik India

This paper presents the performance evaluation and improvement of a high-efficiency diode clamped multilevel inverter (DCMLI)-based PMSM drive for electric vehicle using AVR microcontroller. Due to capability of permanent magnet synchronous motor (PMSM) for providing huge torque to current ratio, more power to weight ratio, more robustness and more efficiency, it is used in DTC and FOC. It is an effective method for the control of motor torque and flux control by controlling the stator reference currents but having a problem of switching frequency and torque ripple. These problems are solved by using CBSVM for providing more inverter voltage and it compensates torque and flux error in a DTC and FOC. The hardware and simulation results in MATLAB environment are validated. The proposed DTC and FOC based DCMLI driven PMSM drive is found suitable for electric vehicles owing to good speed response and less torque ripple. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Controllers

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Performance improvement of a system-level harmonic using a harmonic power flow controller

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Scientia Iranica 2024年第2期31卷 161-173页

作者： Mehri, R. Mokhtari, H. Zolghadri, M.R. Department of Engineering College of Electrical Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Electrical Engineering Sharif University of Technology Tehran Iran

Penetration of harmonics from downstream low voltage networks and resonance phenomenon has caused the level of harmonics to increase in transmission networks. Compensation for these harmonics at high voltage levels is neither recommended nor cost-effective. This is dne to the fact that there is no single large nonlinear load that canses these harmonics, yet filtering at low voltage non-linear load sites cannot completely compensate the harmonics, and the remaining harmonics at standard levels still flow into the upstream networks. The idea of controlling harmonics at a medium/high voltage level caused by the remaining harmonics flown from low voltage networks and possibly amplified by resonance conditions with the nse of a series of active power filters has been proposed by the authors in a published work. Since this application of a series of active filters was new, it was preferred to assign a new name for stich device, i.e., harmonic power flow controller or simply HPFC. This work looks into the control strategies applicable to an HPFC in more detail. The shortcomings of the previous methods are now removed, resulting in better performance for an HPFC. © 2024 Sharif University of technology.

关键词： Electric power transmission networks

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Performance Assessment of a Real PV System Connected to a Low-Voltage Grid

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Energy engineering 2024年第1期121卷 13-26页

作者： Gaber Magdy Mostafa Metwally Adel A.Elbaset Esam Zaki Electrical Engineering Department Faculty of Energy EngineeringAswan UniversityAswanEgypt `2Faculty of Engineering King Salman International UniversityEl-Tor46511Egypt Electrical Engineering Department Faculty of EngineeringMinia UniversityMiniaEgypt Department of Electromechanics Engineering Faculty of EngineeringHeliopolis UniversityCairoEgypt Computer Department Faculty of EngineeringModern Academy of Engineering&TechnologyCairoEgypt

The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean *** the past,generation systems depended on non-renewable sources such as oil,coal,and ***,this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City,*** performance analysis of the considered grid-connected PV system is carried out using power system simulator for engineering(PSS/E)*** the PSS/E program,monitors and uses the power analyzer that displays the parameters and measures some parameters such as current,voltage,total power,power factor,frequency,and current and voltage harmonics,the used inverter from the type of grid inverter for the considered *** results conclude that when the maximum solar radiation is reached,the maximum current can be obtained from the solar panels,thus obtaining the maximum power and power *** total voltage harmonic distortion,a current harmonic distortion within permissible limits using active harmonic distortion because this type is fast in processing up to 300 *** connection between solar stations and the national grid makes the system more efficient.

关键词： Low-voltage grid photovoltaic(PV)system total harmonic distortion grid-connected PV system

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ECG Signal Classification of Cardiovascular Disorder using CWT and DCNN

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Journal of Biomedical Physics and engineering 2025年第1期15卷 77-92页

作者： Rahman, Tawfikur Ahommed, Rasel Deb, Nibedita Das, Utpal Kanti Moniruzzaman, Md. Bhuiyan, Md. Alamgir Sultana, Farzana Kausar, Md. Kamruzzaman Department of Electrical and Electronic Engineering Faculty of Engineering International University of Business Agriculture and Technology Uttara Dhaka 1230 Bangladesh Department of Agriculture International University of Business Agriculture and Technology Uttara Dhaka 1230 Bangladesh Department of Computer Science and Engineering Faculty of Engineering International University of Business Agriculture and Technology Uttara Dhaka 1230 Bangladesh

Background: Cardiovascular Diseases (CVD) requires precise and efficient diagnostic tools. The manual analysis of Electrocardiograms (ECGs) is labor-intensive, necessitating the development of automated methods to enhance diagnostic accuracy and efficiency. Objective: This research aimed to develop an automated ECG classification using Continuous Wavelet Transform (CWT) and Deep Convolutional Neural Network (DCNN), and transform 1D ECG signals into 2D spectrograms using CWT and train a DCNN to accurately detect abnormalities associated with CVD. The DCNN is trained on datasets from PhysioNet and the MIT-BIH arrhythmia dataset. The integrated CWT and DCNN enable simultaneous classification of multiple ECG abnormalities along-side normal signals. Material and Methods: This analytical observational research employed CWT to generate spectrograms from 1D ECG signals, as input to a DCNN trained on di-verse datasets. The model is evaluated using performance metrics, such as precision, specificity, recall, overall accuracy, and F1-score. Results: The proposed algorithm demonstrates remarkable performance metrics with a precision of 100% for normal signals, an average specificity of 100%, an average recall of 97.65%, an average overall accuracy of 98.67%, and an average F1-score of 98.81%. This model achieves an approximate average overall accuracy of 98.67%, highlighting its effectiveness in detecting ***: The integration of CWT and DCNN in ECG classification improves accuracy and classification capabilities, addressing the challenges with manual analy-sis. This algorithm can reduce misdiagnoses in primary care and enhance efficiency in larger medical institutions. By contributing to automated diagnostic tools for cardiovascular disorders, it can significantly improve healthcare practices in the field of CVD detection. © Journal of Biomedical Physics and engineering.

关键词： Wavelet transforms

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ViT-LSTM synergy: a multi-feature approach for speaker identification and mask detection

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Neural Computing and Applications 2024年第35期36卷 22569-22586页

作者： Nassif, Ali Bou Shahin, Ismail Bader, Mohamed Ahmed, Abdelfatah Werghi, Naoufel Department of Computer Engineering University of Sharjah Sharjah United Arab Emirates Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electrical Engineering and Computer Sciences Khalifa University Abu Dhabi United Arab Emirates

The global health crisis caused by the COVID-19 pandemic has brought new challenges to speaker identification systems, particularly due to the acoustic alterations caused by the widespread use of face masks. Aiming to mitigate these distortions and improve the accuracy of speaker identification, this study introduces a novel two-level classification system, leveraging a unique integration of Vision Transformers (ViT) and Long Short-Term Memory (LSTM). This ViT-LSTM model was trained and tested on an extensive dataset composed of diverse speakers, both masked and unmasked, allowing a comprehensive evaluation of its capabilities. Our experimental results demonstrate remarkable improvements in speaker identification, with an accuracy score of 95.67%, significantly surpassing traditional and other deep learning-based methods. Moreover, our framework also shows considerable strength in detecting the presence of a mask, achieving an accuracy of 91.15% and outperforming existing state-of-the-art models. This study provides the first-ever benchmark for mask detection in the context of speaker identification, opening new pathways for research in this emerging area and presenting a robust solution for speaker identification in the era of face masks. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Convolutional neural networks

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Outdoor navigation for visually impaired people using YOLOv5 and Transfer learning: an analytical study

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Multimedia Tools and Applications 2024年 1-20页

作者： Shariatinezhad, Monir Molaeezadeh, Seyyedeh Fatemeh Gholami, Mohammad Department of Electrical and Computer Engineering Jundi-Shapur University of Technology Po.Box: 64615-334 Dezful Iran

This study introduces an obstacle detection system for visual impairment rehabilitation in visually impaired individuals, leveraging YOLOv5 and transfer learning. The methodology comprises four main phases. First phase is sidewalk dataset generation, involving creating our customized PESID dataset and a proprietary dataset. Second phase is image annotation into eight essential obstacle classes. We pay special attention to edges, slopes, and holes—often overlooked in existing sidewalk datasets. These aspects are crucial for ensuring the safety of visually impaired individuals. Third phase is model pretraining with the large-scale COCO dataset. Last phase is fine-tuning using transfer learning on specialized datasets. The evaluated models for obstacle detection include YOLOv3, YOLOv5s, YOLOv5l, YOLOv5x, YOLOv5n, MobilenetSSDv2, Detectron2, RetinaNet, and Faster RCNN. On the customized PESID dataset, YOLOv5s, YOLOv5x, YOLOv5m, and YOLOv5l outperform other models in terms of Mean Average Precision at an Intersection of Union (IOU) of 0.5 (MAP0.5) and detection speed. On our proprietary dataset, the YOLOv5l model achieves a MAP0.5 of 84.5% and 77 frames per second. Notably, the MAP0.5 scores for edges, slopes, and holes are 77%, 85%, and 84%, respectively. Additionally, improving image annotation quality significantly enhances model accuracy by more than 10% for two datasets. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image annotation

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GAN-Based Federated Adversarial Learning for Enhancing Security Towards Consumer Digital Ecosystems

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IEEE Transactions on Consumer Electronics 2025年第1期71卷 1102-1114页

作者： Murmu, Anita Kumar, Piyush Namasudra, Suyel Reddy, M Rajasekhar National Institute of Technology Patna Department of Computer Science and Engineering Patna India Bennett University School of Computer Science Engineering and Technology India National Institute of Technology Department of Computer Science and Engineering Patna India National Institute of Technology Agartala Department of Computer Science and Engineering Tripura India Amrita Vishwa Vidyapeetham Amrita School of Computing Andhra Pradesh India

Federated Adversarial Learning (FAL) maintains the decentralization of adversarial training for data-driven innovations while allowing the collaborative training of a common model to protect privacy facilities. Before sharing with bigger global aggregation, it allows users to change settings locally over many iterations. However, a strong network against attackers in Industry 5.0 towards consumer digital ecosystems is a challenge for adversarial training methodologies. To solve this issue, a novel FAL-based Customized Inequality-Aware Federated Learning (CusIAFL) technique is proposed in this paper for classifying and securing color images. The proposed method reduces the instability brought on by the heterogeneity of the data and optimizes each data sample by understanding the client-label distribution. A unique Pix2Pix Generative Adversarial Network (GAN) algorithm is employed to generate realistic images in the presented research work, while a hybrid approach is used to guarantee consistency in the time series data. This innovative research work is evaluated on various non-medical, consumer electronic, and medical imagery. The experimental results have been evaluated using performance metrics, namely accuracy, entropy, Peak Signal-to-Noise Ratio (PSNR), Hausdorff Distance (HD95), Structural Similarity Index (SSIM), and Mean Square Error (MSE). The results show that the proposed technique outperforms the existing models in terms of security. © 1975-2011 IEEE.

关键词： Generative adversarial networks

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