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Effective Energy Efficiency Methods for Distribution Transformers 1

Effective Energy Efficiency Methods for Distribution Transfo...

1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Singh, Navdeep Kundu, Sombir Verma, Vikas Nangru, Yogesh Electrical Engineering Department Ambala India

ISBN: (纸本)9798331518578

In this paper, three different energy efficiency schemes have been studied for the different ratings of distribution transformers. The schemes used for calculating the efficiency are single-point efficiency methods (SPEM), Multi-point efficiency method (MPEM), and Dual criteria method (DCM). The objectives of these schemes are mainly used to calculate the efficiency at various loading levels and provide a better variation of designs for the selection of transformers as per the needs of the manufacturers and customers. A simulation study has been carried out to demonstrate the effectiveness of the applied schemes. A comparative analysis among the schemes has been done in terms of efficiencies at several loading levels as per schemes which help the manufacturers to select the optimal design criteria and differentiate the design alternatives at specific loading levels. © 2025 IEEE.

关键词： Distribution transformers

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Performance Enhancement of MIMO-OFDM System with Perfect Channel Estimation Using Delayed Feedback 1

Performance Enhancement of MIMO-OFDM System with Perfect Cha...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Suban, A. Jagaprathaban, J. Nithin Narayanan, S. Thanaseelan, A. UG-Final year in Electronics and Communication Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518578

Using multiple broadcast and capturing antennas to create MIMO channels can enhance capacity by a factor equal to the smaller of the number of broadcasting or capturing elements. To reduce inter-symbol interference and increase system capacity, Subcarrier-Based Transmission Technique (OFDM) is employed in MIMO channels (MIMO-OFDM) to enable efficient wideband transmission in this study. Two separate space-time codes are used by the MIMO-OFDM system for two sets of two broadcasting antennas. Pre-whitening and Closest-point interpretation based on Iterative interference suppression are used at the receiver to decode the separate space-time codes. The primary goal of this work is to estimate the ideal channel utilising delayed feedback, in which the transmitter and receiver estimate the feedback. Guard bits are used here for the OFDM signals. We discovered that LS is a perfect channel by examining the estimators' results in MATLAB. Thus, the optimal method for channel estimation is delayed feedback. Additionally, the experimental results guarantee improved performance when a MIMO-OFDM system employs Delayed Feedback and Channel Estimation. © 2025 IEEE.

关键词： Space time codes

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Real-Time OCR and Translation System with Text-to-Speech Ability 1

Real-Time OCR and Translation System with Text-to-Speech Abi...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Manoj, Kevin Nallamilli, Vinay Rahul, Jitendra Ramesh, T.K. Amrita School of Engineering Amrita Vishwa Vidyapeetham Dept. of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798331518578

The demand for the seamless cross-linguistic interaction has heightened with increasingly high globalization and digital connectivity, particularly in contexts where real-time interaction is required. This paper aspires to address the development of an integrated Optical Character Recognition system, translation, and Text-to-Speech system in behalf of these demands. The proposed system uses OpenCV for video capture, Tesseract for multilingual OCR citeMishra2022, Google Translate API for translation, and gTTS for audio output. This approach offers an adaptive and flexible accessibility solution in educational and multilingual interactions. The language switch is done dynamically, thus giving the user flexibility to change the language of choice in real-time so that it becomes a very flexible and all-inclusive environment. The design of this system went through three iterations that continue to improve with respect to the accuracy of outcomes, efficiency of processing, and usability. Results have indicated that the system is quite efficient in its application, making high accuracy for OCR, reliable translations, and clear audio outputs-applicable in real-world applications. Future improvements will be made in increasing language support, latency reduction, along with other features of accessibility to enhance inclusivity and engagement. © 2025 IEEE.

关键词： Optical character recognition

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Enhancing Malicious URL Detection with Advanced Machine Learning Techniques 1

Enhancing Malicious URL Detection with Advanced Machine Lear...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Alavala, Hemanth Reddy Singh, Shambhavi Joshi, Priyam Basavaraju, Sagar Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798331518578

Malicious URLs pose a significant threat to online security. The can steal our personal information and can even hack out system. Refraining ourselves from using such malicious websites is the need of the hour. This paper presents a comprehensive evaluation of various machine learning algorithms which are used to effectively detect and mitigate these threats. This research explores the performance of traditional machine learning techniques including Random Forests, Decision Trees, Logistic Regression, Support Vector Machines, as well as advanced techniques like XGBoost, LightGBM, and CatBoost while the previous works focused on only traditional classification techniques. Additionally, this work investigates the potential of deep learning models, including LSTM and CNN, to capture intricate patterns within URL sequences. Machine learning algorithms are evaluated using the evaluations metrics including Accuracy, Recall, Precision and F1 score. Experimental Results and analysis have shown that advanced models outperform traditional classification techniques. These results valuable insights into the most effective approaches for safeguarding online users from malicious attacks. © 2025 IEEE.

关键词： Phishing

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From Code Analysis to Fault Localization: A Survey of Graph Neural Network Applications in Software engineering

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international Journal of Advanced computer science and Applications 2025年第4期16卷 609-617页

作者： Pan, Maojie Lin, Shengxu Xiao, Zhenghong School of Computer Science Guangdong Polytechnic Normal University Guangdong Guangzhou510665 China

Graph Neural Networks (GNNs) represent a class of deep machine learning algorithms for analyzing or processing data in graph structure. Most software development activities, such as fault localization, code analysis, and measures of software quality, are inherently graph-like. This survey assesses GNN applications in different subfields of software engineering with special attention to defect identification and other quality assurance processes. A summary of the current state-of-the-art is presented, highlighting important advances in GNN methodologies and their application in software engineering. Further, the factors that limit the current solutions in terms of their use for a wider range of tasks are also considered, including scalability, interpretability, and compatibility with other tools. Some suggestions for future work are presented, including the enhancement of new architectures of GNNs, the enhancement of the interpretability of GNNs, and the design of a large-scale dataset of GNNs. The survey will, therefore, provide detailed insight into how the application of GNNs offers the possibility of enhancing software development processes and the quality of the final product. © (2025), (science and Information Organization). All Rights Reserved.

关键词： Software quality

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Artificial Intelligence in Next Generation IoT Infrastructure: Challenges and Opportunities 1

Artificial Intelligence in Next Generation IoT Infrastructur...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Arabelli, Rajeshwarrao Chotaliya, Dhwanit K. Gadhave, Rajashree Tukaram Haritha, B. Kasireddy, Lakshmi Chandrakanth Soni, Mukesh School of Engineering SR University Department of Electronics and Communications Engineering Warangal India GEC-Rajkot Department of Instrumentation and Control Engineering Gujarat Rajkot360005 India Pillai HOC College of Engineering and Technology Rasayani Tal. Khalapur MH 410207 India St. martin's Engineering College Department of ECE Hyderabad India ThoughtSpot Inc Enterprise DevSecOps Architect R&D - Engineering FranklinTN United States Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Pune India

ISBN: (纸本)9798331518578

Numerous facets of the public realm could be revolutionised by the convergence of the Internet of Things (the Internet of Things) and Artificial Intelligence (AI). This project developed a based-on data predictive maintenance system for manufacturing production lines. One of these anticipated improvements that can be included into the factory's production system is 'AI of Things (AIoT),' which refers to the use of the IoT to carry out intelligent tasks with the aid of AI integration. By using the information created by IoT sensors progressively, the system utilizes machine learning (ML), a part of AI, to recognize expected blunders preceding they happen. The viability of the innovation was surveyed utilizing IoT information from genuine assembling frameworks, and the results of the appraisal demonstrated that the prescient support structure was effective in distinguishing potential failure indicators and could assist with forestalling some production stops. Comparing the performance of ML techniques revealed that frameworks of the bagging ensemble technique Random Forest and the boosting technique XGBoost appeared to outperform each of the techniques in the assessment. The factory's production system now uses the best-performing ML techniques from the present research. © 2025 IEEE.

关键词： Predictive maintenance

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20th international conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd international conference on Quantum Technologies, ICEQT 2024, and 21st international conference on Modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

20th International Conference on Grid, Cloud, and Cluster Co...

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20th international conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd international conference on Quantum Technologies, ICEQT 2024, and 21st international conference on Modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031858833

The proceedings contain 20 papers. The special focus in this conference is on Grid, Cloud, and Cluster Computing. The topics include: Scientific Workflow Provenance Management: System Requirements and a Reference Architecture;Enhancing Data Security with Decentralized Cloud Storage: An IPFS Approach;learning Robust Observable to Address Noise in Quantum Machine Learning;evaluating Cost-Effective Reconfigurable Hardware for Quantum Simulation;an Efficient Quantum Solver for Multidimensional Partial Differential Equations;explaining the Design of the Quantum Fourier Transform;Optimizing Depth of Quantum Circuit for Generating GHZ States;a Comparative Analysis of Hybrid-Quantum Classical Neural Networks;NRQNN: The Role of Observable Selection in Noise-Resilient Quantum Neural Networks;studying the Impact of Quantum-Specific Hyperparameters on Hybrid Quantum-Classical Neural Networks;Eclipse Qrisp QAOA: Description and Preliminary Comparison with Qiskit Counterparts;federal Cloud Computing Adoption Case Study: A Retrospective Analysis as a Precursor to Optimized Quantum Adoption Methodologies;integrating Secure Quantum Digital Signature into Quantum Communications;methodology to Accelerate Federal Agency Adoption of Quantum Technologies;understanding Public Policy Effects on Alcohol-Related Behaviors and Outcomes Using System Dynamics;Performance Investigation of Small UAV Attitude Control Based on Optimized Nonlinear Dynamic Inversion;Prediction of 1st Year Registration Renewal of General-Use JP Domain Names with the Use of Machine Learning;data Clustering and Visualization with Recursive Max k-Cut Algorithm.

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Enhancing Two-Area Interconnected Power Systems Using Model Predictive and PID Control Approaches 1

Enhancing Two-Area Interconnected Power Systems Using Model ...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kushwaha, Ritesh Kumar Prakashyadava, Ram Malik, Monu Alam, Monauwer Ahamad, Isarar Naugai, Divyanshu Chandigarh University Dept. of Electronic and Communication Engineering Punjab Mohali India Integral University Deptt. of Electrical Engineering U.P. Lucknow India Maharaja SurajMal institute of Technology Electronics and Electrical Engg Deptt India Integral University Deptt. of Electrical Engineering Lucknow India BTKIT Dwarahat Dept. of Electronics and Communication Engineering Uttarakhad Almora India

ISBN: (纸本)9798331518578

This research represents a comparative study of Load Frequency Control (LFC) using Model Predictive Control (MPC). The results have also been compared with Proportional-Integral-Derivative (PID) controllers. LFC is evident for power system stability which keeps equilibrium between generation and load. PID controllers are widely employed, however in the modern-day power systems which are complex in nature the performance of the PID controllers is not as par. Therefore, different control schemes have and are being explored. MPC is one of them techniques. The aim of this research is to evaluate and compare the effectiveness of MPC and PID controllers, in two-area system. A case study featuring a two-area system is presented to illustrate how the controllers respond to load conditions and disturbances. This paper aims to provide insights into the merits and limitations of each controller. The results contribute to a more profound comprehension of the practical implications associated with implementing MPC in LFC systems, thereby influencing future research and practical applications. © 2025 IEEE.

关键词： Predictive control systems

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A High-Gain DC-DC Boost Converter for Solar Microgrid Systems Using a Switching Inductor and a Capacitor 1

A High-Gain DC-DC Boost Converter for Solar Microgrid System...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Prasanth, S. Priyadarsini, S. Lakshmi, R. Sneha, G. Ajitha, S.S. Saravanakumar, R. Narendra, Konnaiah Gari Unnamalai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Kovilpatti India PSR Engineering College Department of Computer Science and Engineering Tamil Nadu Sivakasi India Siddharth Institute of Engineering and Technology Department of Elecrical and Electroncis Engineering Puttur India St. Joseph's Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Iconix Software Solution Tamil Nadu Tirunelveli India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electonics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331518578

This paper outlines the design and implementation of a solar microgrid-specific high-gain DC-DC booster converter that makes use of a variable inductor and capacitors. To improve the suitability of photovoltaic (PV) panels for incorporation into microgrids, the proposed converter efficiently increases their low-voltage outputs. Conventional boost converters can't offer that kind of voltage increase because they lose too much performance and put too much strain on their internal components. The converter increases the voltage gain dramatically while maintaining a high degree of efficiency thanks to a switching inductor-capacitor network. The main breakthrough is an inventive multi-stage energy transfer and storage device that cleverly employs a switching inductor and capacitor. This configuration increases the output voltage while decreasing the voltage and current ripples, which in turn reduces the amount of electromagnetic interference (EMI) and increases the life of the components. Thorough assessments of the converter's working via theoretical modeling and simulation studies confirm its performance across several load and input situations common to solar microgrids. The prototype's testing findings show a significant voltage increase and a peak efficiency of over 95% when compared to traditional boost converters. Moreover, the converter's reliable performance over a wide range of voltage sources and workload scenarios proves its suitability for practical solar applications. As a result, the proposed high-gain boost converter will greatly improve the efficiency and reliability of solar microgrids, leading to a rise in the use of renewable energy sources in DGS. © 2025 IEEE.

关键词： Microgrids

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Bibliometric and Content Analysis of Large Language Models Research in Software engineering: The Potential and Limitation in Software engineering

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international Journal of Advanced computer science and Applications 2025年第4期16卷 344-356页

作者： Damayanti, Annisa Dwi Gani, Hamdan Zhipeng, Feng Gani, Helmy Zuhriyah, Sitti Nurani Djabir, St. Nurhayati Wardani, Nur Ilmiyanti Department of Environmental Engineering Faculty of Engineering Hasanuddin University Makassar Indonesia Department of Machinery Automation System ATI Makassar Polytechnic Makassar Indonesia School of Culture Creativity and Media Hangzhou Normal University Zhejiang Hangzhou China Department of Industrial Hygiene Faculty of Public Health Occupational Health and Safety Makassar College of Health Sciences Indonesia Department of Computer System Universitas Handayani Makassar Makassar Indonesia Department of Information Systems and Technology Institut Teknologi dan Bisnis Nobel Indonesia Jl. Sultan Alauddin No.212 Makassar90221 Indonesia Department of Informatics Engineering Universitas Handayani Makassar Makassar Indonesia

Large Language Models (LLM) is a type of artificial neural network that excels at language-related tasks. The advantages and disadvantages of using LLM in software engineering are still being debated, but it is a tool that can be utilized in software engineering. This study aimed to analyze LLM studies in software engineering using bibliometric and content analysis. The study data were retrieved from Web of science and Scopus. The data were analyzed using two popular bibliometric approaches: bibliometric and content analysis. VOS Viewer and Bibliometrix software were used to conduct the bibliometric analysis. The bibliometric analysis was performed using science mapping and performance analysis approaches. Various bibliometric data, including the most frequently referenced publications, journals, and nations, were evaluated and presented. Then, the synthetic knowledge method was utilized for content analysis. This study examined 235 papers, with 836 authors contributing. The publications were published in 123 different journals. The average number of citations per publication is 1.44. Most publications were published in Proceedings international conference on Software engineering and ACM international conference Proceeding Series, with China and the United States emerging as the leading countries. It was discovered that international collaboration on the issue was inadequate. The most often used keywords in the publications were "software design," "code (symbols)," and "code generation." Following the content analysis, three themes emerged: 1) Integration of LLM into software engineering education, 2) application of LLM in software engineering, and 3) potential and limitation of LLM in software engineering. The results of this study are expected to provide researchers and academics with insights into the current state of LLM in software engineering research, allowing them to develop future conclusions. © (2025), (science and Information Organization). All Rights Res

关键词： Software design

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