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2024 International Conference on Sustainable Energy: Energy Transition and Net-Zero Climate Future, ICUE 2024

作者： Barua, Avrojyoti Ongsakul, Weerakorn Nahid, Firuz Ahamed Roy, Joyashree Asian Institute of Technology Dept. of Energy Environment and Climate Change Pathum Thani12120 Thailand Pathum Thani12120 Thailand International University of Business Agriculture and Technology - Iubat Dept. of Electrical and Electronic Engineering Dhaka1230 Bangladesh

ISBN: (纸本)9798331517076

Comparative analysis is crucial for evidence-based decision-making for sustainable energy transitions. Identifying the strengths and weaknesses of various approaches is necessary before application. This review article presents a comparative analysis of energy system modeling approaches applied in the literature to develop decarbonization pathways for the electricity sector. The six most widely used applications are analyzed: TIMES/MARKAL, PyPSA, EnergyRT, SWITCH, OSeMOSYS, LEAP, and TIMES. SWOT analysis evaluates the strengths, weaknesses, opportunities, and threats of these models when applied toward net zero electricity systems by midcentury. PyPSA and Switch models emerge as top choices in analyzing the decarbonized future electricity sector due to adaptability, stakeholder compatibility, and policy alignment. The study aids researchers and policymakers in selecting an appropriate modeling approach by considering the strengths and limitations of each modeling technique. Furthermore, it underscores the necessity of ongoing evaluation and refinement to meet the evolving needs of the energy sector effectively, especially with the development of a new generation of open-source non-proprietary models. © 2024 IEEE.

关键词： Decarbonization Energy system modeling Net Zero Energy system PyPSA Sustainable energy transitions Switch

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Sustainable Future for India's Power Sector Through Smart Grid and Microgrid Initiatives

Sustainable Future for India's Power Sector Through Smart Gr...

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International Conference on Electrical Power and Energy systems (ICEPES)

作者： Pratik Sarkar Saibal Chatterjee Rajeeb Dey Dept. of Electrical Engineering Dream Institute of Technology Kolkata India Dept. of Electrical Engineering National Institute of Technology Mizoram India Dept. of Electrical Engineering National Institute of Technology Silchar India

ISBN: (数字)9798350390728

ISBN: (纸本)9798350390735

Modern society is largely dependent on the usage of energy, which is an indispensable requirement propelled by the expanding global population. The escalating need for energy presents substantial challenges for traditional energy sources, which are depleting at an accelerated rate and giving rise to considerable environmental apprehensions. Developing countries like India also have problems with their power grids because they are old, wasteful, and cannot last forever. It has problems with being reliable, having frequent blackouts, high transmission losses, bad power quality, and not enough electricity during peak hours. To tackle these difficulties, a substantial restructuring of the electrical supply system is necessary, accomplished by implementing Smart Grid and microgrid technologies, which will facilitate a remarkable transition. This article explores the components of Smart Grid systems, with a specific focus on microgrids, and their significance within the context of India. This study examines the many government efforts and regulatory agencies that are actively pushing the deployment of smart grid and microgrid technologies. Furthermore, this paper provides a concise assessment of India's endeavours, identifies probable obstacles, and proposes viable solutions. The implementation of Smart Grid and microgrid technologies plays a crucial role in promoting global sustainability in the energy sector.

关键词： Government Power quality Microgrids Propulsion Propagation losses Smart grids Power system reliability

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Privacy and Data Control on Social Networks using Deep Learning 4

Privacy and Data Control on Social Networks using Deep Learn...

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4th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2022

作者： Parimala, A. Vijayalata, Y. Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Telangana Hyderabad India

ISBN: (数字)9781665462464

ISBN: (纸本)9781665462464

Online social networks are huge data exchange platforms that help to promote and share a lot of good information about products, news, education, tourism, health care, etc., also there is a great risk involved to individual's privacy and security. Online posted photos can be shared, tagged, and reposted again without having any consent from the people present in the images. In this project, we are proposing a facial recognition-based system that detects every single individual and checks their online account relationship between the individual. The post or image that is reposted, tagged, or copied by known or unknown individuals will be checked. If it is an unknown individual the images convolved through a low-pass filter kernel which removes the high-frequency content like noise and edges to smooth the images that make the image blur. For this mechanism, we proposed to use deep learning based VGG19 architecture for image classification and Haar cascade viola jones algorithm for detection, and computer vision-based blurring techniques used. algorithm performance as the area under the ROC curve (AUC) accuracy of 88% obtained. This proposed model achieved 91.53% classification accuracy and further we evaluated the model using Accuracy, Precision, Recall and F1-Score metrices and achieved 70.83%, 82%, 71% and 0.68%. © 2022 IEEE.

关键词： Deep learning

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Eye Contact During Live Video Conferencing Using External Video Camera

Eye Contact During Live Video Conferencing Using External Vi...

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2024 International Conference on Computer, Electronics, Electrical engineering and their Applications, IC2E3 2024

作者： Davey, Vrishab Prasanth Akilandeswari, A. Kumar, Rohit Byadgi, Chandrashekhar S Kalaiyarasan, S. Sandhia, G.K. Guleria, Mandeep Vijeth, B. School of Computing SRM Institute of Science and Technology KTR India National Institute of Technology Dept. of Electrical Engineering Uttarakhand India Samsung R and D Bangalore India

ISBN: (纸本)9798350388534

Video conferencing and other forms of live communication methods enjoy widespread popularity. However, the absence of interpersonal, psychological, or tactile feedback diminishes engagement compared to in-person communication. A notable challenge arising from the distance between the webcam and display of the device lies in the absence of contact of eye during live video conferences. Addressing this issue involves manipulating video frames to alter the direction of the gaze, creating the illusion of sustained eye contact. This research introduces a technique for preserving eye contact, entailing the rotation of a user's eyeball prior to transmitting the frame of video to the distant place. The implementation leverages WebRTC and TFLite within a application optimized for mobile devices. Convolutional neural networks based on warping play a pivotal role in superimposing the corrected eye onto the detected eye position during the eye position correction process. The employed loss functions contribute to maintaining the geometry of the eye structures while mitigating color shifts around the borders of the eye regions. The technology's real-time eye gaze rectification capability on consumer-oriented mobile devices is demonstrated, highlighting its remarkable speed and resolution. This approach to gaze correction, achieved through postprocessing, proves to be a practical solution for addressing the challenge of lost contact of eye during real time video communication. The model's integration into an application facilitates its implementation. © 2024 IEEE.

关键词： Video conferencing

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Human Activity Recognition Using Rotation Invariant Radial Fourier Profile Features 3

Human Activity Recognition Using Rotation Invariant Radial F...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Kamble, Milind Bichkar, Rajankumar G. H. Raisoni College of Engineering and Management Dept. of E&tc Pune India Vidya Pratishthan's Kamalnayan Bajaj Institute of Engineering and Technology Maharashtra Baramati India

ISBN: (纸本)9798350375190

Human activity recognition (HAR) in video datasets is crucial for various applications, yet challenges persist in accurately identifying activities among diverse view and camera angles. Existing methods often struggle with rotational variations, leading to decreased recognition accuracy and performance gaps in real-world scenarios. To address this issue, this study proposes using Radial Fourier Profile (RFP) features extracted via 2D Fast Fourier Transform (FFT). RFP features inherently possess rotation invariance, offering a solution to the challenges posed by varying viewing conditions. The effectiveness of the proposed RFP feature extraction technique is evaluated using K-Nearest Neighbour (KNN) and Random Forest classifiers on UCF and HMDB datasets, representing diverse human activities and environmental conditions. Statistical tests, including ANOVA, are employed to assess the rotation invariance of RFP features. Results indicate significant improvements in activity recognition accuracy across various orientations, demonstrating the robustness of the proposed system. © 2024 IEEE.

关键词： Fast Fourier transforms

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Introduction of Grid Forming Converters in the European Grid Codes 58

Introduction of Grid Forming Converters in the European Grid...

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58th International Universities Power engineering Conference, UPEC 2023

作者： Malamaki, Kyriaki-Nefeli D. Tampakis, Dimitrios Demoulias, Charis S. Aristotle University of Thessaloniki Dept. of Electrical and Computer Engineering Thessaloniki Greece Independent Power Transmission Operator Research Technology & Development Dept. Athens Greece

ISBN: (纸本)9798350316834

The increased penetration of Converter-Interfaced Distributed Renewable Energy Sources (CI-DRES) and the simultaneous decommitment of fuel-driven Synchronous Generators (SGs) has revealed problems related to the robustness and stability of the electric grid, which in turn lead to displacement of SG support functions -e.g., inertia, fault-current contribution- and Ancillary Services (AS), e.g., reactive power and primary frequency regulation. The advanced controllability of Voltage Source Converters (VSCs) and the use of Energy Storage systems can be exploited to boost the functionalities of CI-DRES beyond their current operation, i.e., uncontrolled power provision. Within the H2020 project EASY-RES such VSC has been developed. In this paper, suggestions for the modification of European grid codes are presented, so that such units are integrated in distribution networks (DNs) to provide existing and new AS and achieve 100% RES penetration. In this way, DNs can be transformed into active DNs with dynamic capabilities like dynamic Virtual Power Plants. Finally, suggestions are presented for: the introduction of new grid codes with respect to AS measurement and quantification;specifications on ICT systems within DNs;the development of a CI-DRES registry with all their steady-state and dynamic properties. © 2023 IEEE.

关键词： Electric power distribution

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Combined Diffusion Adaptation on Adaptive Leaky Criterion and Orthogonal Gradient Algorithm 20

Combined Diffusion Adaptation on Adaptive Leaky Criterion an...

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20th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information technology, ECTI-CON 2023

作者： Sitjongsataporn, Suchada Nurarak, Piyaporn Faculty of Engineering and Technology Mahanakorn University of Technology Dept. of Electronic Engineering Bangkok Thailand Sukhothai Thammathirat Open University School of Science and Technology 9/9 Chaengwattana Rd. Nonthaburi11120 Thailand

ISBN: (纸本)9798350310467

This paper presents a combined diffusion policy on the orthogonal gradient-based algorithm using adaptive averaging leaky criterion. A mixed-node criterion is described by orthogonal projection matrix of its own tap-weight vector, while information of other connected nodes are undisturbed. An adaptive leaky algorithm is applied for fast convergence with low complexity. By minimising a mixed-node cost function, the distributed estimation is verified in terms of adapt-then-combine strategy over the distributed network. Statistical experimental results on system identification examine that a proposed algorithm can provide promising results in form of mean square error criterion. © 2023 IEEE.

关键词： Adaptive algorithms

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Segmentation of Brain MRI Images using Deep Learning 1

Segmentation of Brain MRI Images using Deep Learning

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1st International Conference on Recent Trends in Microelectronics, Automation, Computing and Communications systems, ICMACC 2022

作者： Choudhary, Santosh Kumar Lekha Chittajallu, Yesu Nirmala Anisha, Javvaji Meka, Sai Teja Ravipati, Bhuvaneswar Vnr Vignana Jyothi Institute of Engineering and Technology Dept. of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9781665496049

Brain injury is the greatest cause of death worldwide, according to a WHO (World Health Organization) research. Deep Learning is one of the most often used algorithms for segmentation of the brain, and also it can be used in conjunction with MRI (magnetic resonance imaging), CT, PTE, and other modalities. Many anatomical properties, such as shape, size, and also the structure of the labels of distinct organs of humans, are not relevant to the suggested framework. When compared to state-of-the-art procedures, the developed frame may be studied using various functions such as classification and enhancement of image, and it also helps to improve the level of prediction. We should have a basic understanding of the organs before beginning an in-dept. inspection. Using CNN (Convolution Neural Network) which is also known as ACNN (Anatomically Constrained Neural Networks), the algorithm that is proposed, leverages semantic segmentation notions. Throughout brain imaging, this approach will develop and partition parts of the organ. To classify portions of an organ, various existing algorithms (such as NN, SVM, and KNN) are utilized, however, these methods fail if the input image is noisy. The method we proposed will segment the organ from brain images with the highest accuracy (CDR: Correct Detection Rate) and the highest indication of similarity. Through objective analysis and purpose, we have shown that our approach is more effective than existing strategies. © 2022 IEEE.

关键词： Magnetic resonance imaging

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Scanning Electron Diffraction: To Precess or not to Precess?

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 2101-2102页

作者： Bergh, Tina Holmestad, Randi Christiansen, Emil F. Thronsen, Elisabeth Nordahl, Gregory Nord, Magnus van Helvoort, Antonius T J Dept. of Chemical Engineering NTNU Trondheim Norway Dept. of Physics Norwegian University of Science and Technology (NTNU) Trondheim Norway Materials and Nanotechnology SINTEF Industry Trondheim Norway

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Real-Time Electric Shock Safety Diagnosis system for Switchgear Based on Capacitance and Relative Leakage Distribution Analysis Algorithm

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Transactions of the Korean Institute of Electrical Engineers 2025年第5期74卷 977-982页

作者： Yoo, Seungcheol Kim, Kangmin Jeong, JunHo So, Yoonsub Park, Young Yoon, YongHo Choi, Wonseok Dept. of Electrical Engineering Hanbat National University Korea Republic of SM ELECTRONICS Co. Ltd Korea Republic of Dept. of Electrical System Engineering Hanbat National University Korea Republic of Department of Electrical Engineering Gwangju University Korea Republic of

In this paper describes the distribution panel real-time electrocution safety diagnosis system technology based on the capacitance and relative leakage distribution analysis algorithm, and applies the safety technology to prevent electrocution accidents caused by leakage current such as faulty ground facilities and connection status. A distribution panel capacitance detection module and a facility multi-point leakage detection module were developed. Through this, a technology to prevent electrocution accidents by monitoring the capacitance and leakage current of the distribution facility is secured, and it is expected that by applying a technology to detect abnormal conditions by analyzing the capacitance and leakage current signals inside the distribution panel, the cost required for regular inspection in the power facility system can be reduced and electric accidents can be prevented. Copyright © The Korean Institute of Electrical Engineers.

关键词： Electric accidents

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