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An Approach for Real Time Implementation of Charging of Shunt Reactor Using Point on Wave Technique with Variable Pre-Insertion Resistor

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Journal of The Institution of Engineers (India): Series B 2025年 1-12页

作者： Shivani, S.N. Vyas, Bhargav Bhatt, K.A. Bhavsar, Meet I. Mistry, Vrushank M. Gujarat Technological University Gujarat Ahmedabad India Department of Electrical Engineering Lukhdhirji Engineering College Morbi India Department of Electrical Engineering L. D. College of Engineering Gujarat Ahmedabad India H. V. Cell Torrent Power Ltd Ahmedabad India

Nowadays, rapid pace growth in the field of solid-state devices and smart grid technologies, it is possible to minimize the Switching Transients (STs) very effectively. Recently, Point on Wave device (PoWd) is used to limit the level of Charging Current (CC) and Asymmetrical dC Component (AdCC) during charging of Shunt Reactor (SR). For successful implementation of the PoW Switching (PoWS) technique, it is essential to minimize the effect of Operating Time Variations (OTV) which is obtained using union of Pre-Insertion Resistor (PIR) and PoWd. In this paper, a novel techniqueis suggested which minimizes the energy consumption (EC) in PIR using variable PIR along with PoWd. Variable PIR is framed using Solid-state Switches (SS). Here, suggested algorithm proposes utilization of variable PIR instead of fixed PIR to minimize the magnitude of CC and AdCC, and EC in PIR during charging of SR. The suggested technique is tested by precise modeling of real-time power system. The comparison of the suggested algorithm with past published paper [1] suggests that the suggested algorithm minimizes the level of CC, AdCC, and EC in PIR during charging of SR. At last, suggested algorithm is tested on hardware model. The validation of the suggested algorithm has been proved using results obtained from hardware model,and performing sensitivity analysis such as testing using different strength of sources and considering effect of various system capacitances is also presented. © The Institution of Engineers (India) 2025.

关键词： Sensitivity analysis

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Parameters for cladding using plasma transfer arc welding –A critical

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Materials Today: Proceedings 2023年 77卷 614-618页

作者： Momin, Altafhussain G. Khatri, Bharatlal C. chaudhari, Mrunalkumar V.Shah, U. Valaki, Janak Gujarat Ahmedabad 380015 India Mechanical Engineering Government Engineering College Gujarat Modasa India Mechanical Engineering L.D College of Engineering Gujarat Ahmedabad 380015 India Mechanical Engineering Government Engineering College Gujarat Bhavnagar India

Arc welding is a type of welding in which there is an electric arc formed joining the base material and the electrode, as well as metals are melted at the welding spot with the help of a welding power source. Arc welding is commonly used because of its low capital and operational costs. due to cost concerns, it is typically not viable to fabricate components from solid high alloyed materials. As a result, non-alloyed or low-alloy base materials must be encased with high-alloy cladding. In high-tech welding technique processes, Strip electrodes are used to apply welded deposits over large surface *** most important contribution of this article is to optimize plasma arc welding process parameters for dissimilar metal welding and other quality factors such as bead shape, microstructure, hardness, ferrite measurement, and tensile *** to its exceptional features, low dispersion, and high coatings efficacy, Welding with plasma transmitted arc (PTAW) is a broadly applied overlay coating method. The impacts of transferred welding current, welding travel speed, powder flow rate, welding oscillation speed, and stand-off distance on weld bead form parameters such as width of deposition and reinforcing are given and examined using experimental data and a developed model. Reduced current (100–120 A), intermediate travel speed (120–140 mm/min), intermediate powder feed rate (12–14 g/min), oscillation speed (450–550 mm/min), and stand-off distance (6–8 mm) would result in superior deposition characteristics with less distortion, residual stresses, and no surface defects. © 2022

关键词： Welds

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Architecture Based Classification for Intrusion detection System Using Artificial Intelligence and Machine learning Classifiers 7th

Architecture Based Classification for Intrusion Detection Sy...

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7th International Conference on Information and Communication Technology for Intelligent Systems, ICTIS 2023

作者： Gondalia, Archana Shah, Apurva Computer Engineering Department L.D. College of Engineering Ahmedabad India Computer Science and Engineering Department The Maharaja Sayajirao University of Baroda Vadodara India

ISBN: (纸本)9789819940394

The study of intrusion detection systems (IdSs) has drawn a lot of interest pertaining to computer science due to the increasing network load and security concern. In addition to arbitrary intrusion categories, current IdSs also require a lot of processing capacity. despite the fact that there is a wealth of literature on IdS issues, we aim to provide a more detailed picture for a thorough review. We provide the taxonomy to delineate contemporary IdSs based on the large survey and sophisticated arrangement. Also, the architecture we provided in the material help the reader quickly understands the big picture of IdSs. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte ltd.

关键词： Intrusion detection

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Edge-Enabled Metaverse:The Convergence of Metaverseand Mobile Edge Computing

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Tsinghua Science and Technology 2024年第3期29卷 795-805页

作者： Nyothiri Aung Sahraoui dhelim liming Chen Huansheng Ning luigi Atzori Tahar Kechadi Information Engineering College Xinjiang Institute of EngineeringUrumqi 830023Chinaand also with School of Computer ScienceUniversity College DublinDublinD04 V1W8Ireland School of Computing Ulster UniversityBelfastBT151EDUK School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Department of Electrical and Electronic Engineering University of CagliariSardinia 09124Italy School of Computer Science University College DublinDublinD04 V1W8Ireland

Metaverse is a virtual environment where users are represented by their avatars to navigate a virtual world having strong links with its physical *** state-of-the-art Metaverse architectures rely on a cloud-based approach for avatar physics emulation and graphics rendering *** current centralized architecture of such systems is unfavorable as it suffers from several drawbacks caused by the long latency of cloud access,such as low-quality *** this end,we propose a Fog-Edge hybrid computing architecture for Metaverse applications that leverage an edge-enabled distributed computing *** applications leverage edge devices’computing power to perform the required computations for heavy tasks,such as collision detection in the virtual universe and high-computational 3d physics in virtual *** computational costs of a Metaverse entity,such as collision detection or physics emulation,are performed at the device of the associated physical *** validate the effectiveness of the proposed architecture,we simulate a distributed social Metaverse *** simulation results show that the proposed architecture can reduce the latency by 50%when compared with cloud-based Metaverse applications.

关键词： industrial Metaverse edge computing Blockchain virtual environment task offloading fog computing

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EPdTNet + -EM: Advanced Transfer learning and SubNet Architecture for Medical Image diagnosis

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Cognitive Computation 2025年第2期17卷 1-22页

作者： K, dhivya K, Sangamithrai S, Indra Priyadharshini M, Vedaraj Department of Electronics and Communication Engineering SRM Institute of Science and Technology Tamilnadu Kattankulathur India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R & d Institute of Science and Technology Tamilnadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering R.M.D. Engineering College RSM Nagar Tamilnadu Kavaraipettai Thiruvallur601206 India

This paper presents a novel medical imaging framework, Efficient Parallel deep Transfer SubNet+-based Explainable Model (EPdTNet + -EM), designed to improve the detection and classification of abnormalities in medical images. The model integrates Enhanced Exponential Transfer learning (En-ETl) and the Parallel SubNet (PSNet +) architecture, addressing challenges like overfitting, high computational cost, and limited generalization across complex datasets. En-ETl accelerates learning and enhances precision, while PSNet + balances computational efficiency and performance through parallel convolutional layers and an axis attention mechanism. The proposed framework preprocesses medical images using resizing, noise removal, and contrast enhancement, ensuring high-quality inputs for analysis. For classification, the PSNet + model categorizes medical images into normal and abnormal cases. Explainable AI (XAI) is applied to highlight key features in classified images, improving interpretability and clinical decision-making. Experimental results validate the framework on various datasets, including MRI, CT, X-ray, and mammography images. The proposed model achieves a classification accuracy of 98.83%, a false positive rate of 2%, and an execution time of 5.3 ms. Comparative Analysis show superior performance over existing approaches in classification accuracy and efficiency. Ablation studies confirmed the significant contributions of the proposed model using each component in enhancing performance. © The Author(s), under exclusive licence to Springer Science+Business Media, llC, part of Springer Nature 2025.

关键词： Transfer learning

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An Advanced Encryption Algorithm for Enhancing data Security in Cloud Computing

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Recent Advances in Electrical and Electronic engineering 2025年第5期18卷 623-636页

作者： Anandh, R. Swaminathan, A. Jadhav, Swati dhondiram Valarmathi, P. Gopinath, N. Tiwari, Kanchan S. Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India Department of Computer Science and Business Systems Panimalar Engineering College Poonamallee Chennai India Department of Computer Engineering Keystone School of Engineering Maharashtra Pune India Computer Science and Engineering B.S. Abdur Rahman Crescent Institute of Science and Technology Chennai India Department of Electronics and Telecommunication Modern Education Society’s Wadia College of Engineering Pune India

Aim: Cloud computing (CC) is a revolutionary new archetype in which users pool their computing resources to provide greater efficiency for everyone. data become increasingly vulnerable to diverse security threats from attackers when millions of users circulate the same network for data transmission. Protecting these reports has shifted to the vanguard of priorities. The existing data security approach prioritizes protecting data at rest in cloud storage but gives less thought to protecting data in transit. during transmission, the data are vulnerable to intrusion attempts. Methods: The third-party auditor is provided access to data during the transfer phase, which is also the current pattern. As the attacker can now pose as a trusted third party, it makes the data more susceptible to unauthorized access. However, growing concerns regarding data privacy and security have made outsourcing sensitive information to faraway data centers difficult. As a result, new security concerns in the cloud necessitate an improved version of the tried-and-true advanced encryption standard (AES) algorithm. Key aspects presented in this study include a secure and private framework for owner data. It improves upon the 128 AES technique by adding a second round of encryption using a different key, allowing for a throughput of 1000 blocks per second. However, the standard method uses a single round key and only 800 blocks per second. The suggested approach reduces energy consumption, improves load distribution, and optimizes network trust and resource management. Results: The proposed architecture allows for the use of AES with cipher lengths of 16, 32, 64, and 128 bytes. The effectiveness of the algorithm in terms of attaining target quality metrics is illustrated graphically via simulation results. This strategy reduces power consumption by 13.23%, network utilization by 12.43%, and delay by 16.53%, according to the outcomes. Conclusion: As a result, the recommended architecture enhance

关键词： Sensitive data

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A Tolerant and Energy Optimization Approach for Internet of Things to Enhance the QoS Using Adaptive Blended Marine Predators Algorithm

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computers, Materials & Continua 2025年第5期83卷 2449-2479页

作者： Vijaya Krishna Akula Tan Kuan Tak Pravin Ramdas Kshirsagar Shrikant Vijayrao Sonekar Gopichand Ginnela Department of Information Technology G.Narayanamma Institute of Technology and Science for WomenHyderabad500104India Engineering Cluster Singapore Institute of Technology10 Dover DriveSingapore138683Singapore Department of Electronics and Telecommunication Engineering J.D.College of Engineering&ManagementNagpur441501India Department of Computer Science and Engineering J.D.College of Engineering&ManagementNagpur441501India School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014TamilnaduIndia

The rapid expansion of Internet of Things(IoT)networks has introduced challenges in network management,primarily in maintaining energy efficiency and robust connectivity across an increasing array of *** paper introduces the Adaptive Blended Marine Predators Algorithm(AB-MPA),a novel optimization technique designed to enhance Quality of Service(QoS)in IoT systems by dynamically optimizing network configurations for improved energy efficiency and *** results represent significant improvements in network performance metrics such as energy consumption,throughput,and operational stability,indicating that AB-MPA effectively addresses the pressing needs ofmodern IoT *** are initiated with 100 J of stored energy,and energy is consumed at 0.01 J per square meter in each node to emphasize energy-efficient *** algorithm also provides sufficient network lifetime extension to a resourceful 7000 cycles for up to 200 nodes with a maximum Packet delivery Ratio(PdR)of 99% and a robust network throughput of up to 1800 kbps in more compact node *** study proposes a viable solution to a critical problem and opens avenues for further research into scalable network management for diverse applications.

关键词： Internet of things trust energy marine predators algorithm(MPA) differential evolution(dE) nodes throughput lifetime

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Metro Cities House Price Prediction Using Ml

Metro Cities House Price Prediction Using ML

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Naik, Sonal Puthran, Aarti Computer Engineering Shree L.R.Tiwari College of Engineering Mumbai India Computer Engineering Vidyavardhini's College of Engineering Mumbai India

ISBN: (纸本)9798350300857

due to changes in local infrastructure as well as real estate values, home prices fluctuate every single year. Customers can figure out the value of the house with the aid of a centralized system that predicts house prices and has infrastructure. It aids the consumer in making decisions on where and when to buy a home. When forecasting a property's value, several factors are taken into account, such as location, neighborhood, size, etc. The intention of this study is to predicate house prices for individuals depending on financial situation. This study matched the outcomes of many machine learning methods including linear, XGB, decision tree, lasso regression and random forest regression, due to its outstanding accuracy. House value forecast on a data set will be performed by utilizing all of aforementioned methodologies and selecting the best among them. This study establishes the application of machine learning algorithms in the prediction of house values using datasets collected from Kaggle. This study can construct a regression model that can precisely estimate the cost of a property created on its characteristics. © 2023 IEEE.

关键词： decision trees

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TeenSenti - A novel approach for sentiment analysis of short words and slangs

TeenSenti - A novel approach for sentiment analysis of short...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Kamath, Sahil Padiya, Vaishnavi d'Silva, Sonia Patil, Nilesh Narvekar, Meera D.J. Sanghvi College Of Engineering Dept. Of Computer Engineering Mumbai India

ISBN: (纸本)9798350371567

The present prevalence of online platforms and the internet has seen a substantial increase in the utilization of Generation Z slang, abbreviated expressions, and short words. These lexical subtleties have become a vital part of a person's daily interactions, and therefore evident in reviews, product comments, and throughout the internet. Resultantly, there exists a need to integrate these Informal expressions such as abbrevi-ations, slang, and short words into natural language processing (NlP) systems. The Informal expressions naturally contain some contextual relevance and therefore can be used to improvise sentiment analysis, as these expressions contribute significantly to the overall context and sentiment of sentences. However, traditional NlP techniques often fall short in recognizing and incorporating these informal expressions, resulting in an atten-uated accuracy of sentiment analysis. To address this issue, this study ventures to provide a comprehensive slang dictionary, encompassing short words, abbreviated expressions, and slang along with the sentiment and sentences of each. This curated slang dictionary is effectively integrated into NlP systems using FastText Embeddings. Through extensive testing across multi-ple machine learning (Ml) and deep learning (dl) models, this approach significantly enhances the accuracy of sentiment analysis when compared to conventional methodologies. This research emphasizes the importance of accommodating informal expression in NlP systems thus opening the possibility of future research. © 2024 IEEE.

关键词： Sentiment analysis

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FusionSegNet: Integrating Modalities for Enhanced Brain Tumor detection and Segmentation

FusionSegNet: Integrating Modalities for Enhanced Brain Tumo...

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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Rehmanji, Husain d'Silva, Sonia Thakker, Kunj Bagul, Sudhir D.J. Sanghvi College of Engineering Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350390759

Improving diagnostic accuracy and striving for thorough analysis is always crucial in medical imaging, Multi Modal Medical Imaging has proved to be a useful approach in this area, providing computational power and accuracy for tasks that humans would otherwise have a tough time doing. This paper investigates the fusion of Magnetic Resonance Imaging (MRI) with Fluorodeoxyglucose Positron Emission Tomography (FdG-PET) or Technetium-99m-Tilmanocept Single-Photon Emission Computed Tomography (TITc-SPECT) scans which are generally used for detecting Gliomas or Metastatic Bronchogenic Carcinoma (Brain Tumors that are formed due to lung cancer). This paper targets a pipeline that will investigate the fusion of Magnetic Resonance Imaging (MRI) with Fluorodeoxyglucose Positron Emission Tomography (FdG-PET) or Technetium-99m-Tilmanocept Single-Photon Emission Computed Tomography (TITc-SPECT) scans which are usually used to detect these brain tumors. The denoising diffusion image Fusion Model (ddFM) is used to combine the structural and functional information from these medical scans and the fused results of these images are then used as input to CNN as well as a U-Net model for brain tumor detection and segmentation respectively. The performance of these models is evaluated based on the probability of tumor detection and the accuracy of segmentation. The main objective of this paper is to validate the effectiveness of the ddFM fusion approach for medical scans by demonstrating tumor detection and classification accuracy in the fused multi-modal images. The results of this paper, therefore, hold a potential for improving the clinical decision-making process and making more effective strategies for brain tumor diagnosis and its management through the use of complementary imaging data. © 2024 IEEE.

关键词： Positron emission tomography

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