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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

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Role of Quantum Computation (QC) in Addressing Computational Challenges of electrical Systems: A Review

Role of Quantum Computation (QC) in Addressing Computational...

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international conference on Power Energy, Environment and Intelligent control (PEEIC)

作者： Rahul Mishra Centre for Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

Quantum mechanics (QM) forms the basis for quantum computation (QC), a paradigm that provides distinctive problem-solving abilities. Although quantum computing (QC) has demonstrated potential in theoretical physics and computer science, its practical applications, particularly in power systems, have not been thoroughly studied. The objective of this work is to highlight the use of quantum computing (QC) as a solution for addressing the rising computational difficulties in power systems. The text provides an introduction to the historical history and essential concepts of QC, and then explores its modern applications in solving intricate power system problems. The aforementioned subjects comprise the study of alternating current (AC) and direct current (DC)” power flow, contingency analysis, state estimation, modeling of electromagnetic transients, fault diagnostics, unit commitment, and challenges related to facility location-allocation.” Despite the existing limits of noisy intermediate-scale quantum (NISQ) devices, the potential of quantum computing to address significant power system concerns on a wide scale holds promise, mostly driven by anticipated advancements in technology and increased research endeavors.

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Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing

Continual Learning for Robust Gate Detection under Dynamic L...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Zhongzheng Qiao Xuan Huy Pham Savitha Ramasamy Xudong Jiang Erdal Kayacan Andriy Sarabakha ERI@N Interdisciplinary Graduate Programme Nanyang Technological University Singapore Department of Electrical and Computer Engineering Aarhus University Aarhus Denmark Institute of Infocomm Research (I2R) Agency for Science Technology and Research (A*STAR) Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore Automatic Control Group (RAT) Paderborn University Paderborn Germany

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements, as exemplified in the context of autonomous drone racing. This study introduces a perception technique for detecting drone racing gates under illumination variations, which is common during high-speed drone flights. The proposed technique relies upon a lightweight neural network backbone augmented with capabilities for continual learning. The envisaged approach amalgamates predictions of the gates' positional coordinates, distance, and orientation, encapsulating them into a cohesive pose tuple. A comprehensive number of tests serve to underscore the efficacy of this approach in confronting diverse and challenging scenarios, specifically those involving variable lighting conditions. The proposed methodology exhibits notable robustness in the face of illumination variations, thereby substantiating its effectiveness.

关键词： Continuing education Robot kinematics Neural networks Lighting Logic gates Robustness Real-time systems

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Improved Dynamic Response of Boost LLC AC-DC Converter with Voltage Regulation

Improved Dynamic Response of Boost LLC AC-DC Converter with ...

引用

2021 IEEE international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSES 2021

作者： Rameshbabu, A. Sundarrajan, G.T. Sundarsingh, Jebaseelan S D Dilleswararao, A. Paul Glady, J Barnabas Sunil Kumar, J.V. Sathyabama Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9781665435215

This paper shows a high gain idea for Industrial application to straight forwardly incorporate Boost LLC converter. Here the simulation was developedforFOPID for Boost LLC converter in DC loads system with Power Factor Correction (PFC). This work recommends FOPID to control and improve time domain response in voltage Regulation. The output of Boost LLC converter is measured by using closed loop arrangement. The locked PI FOPID configured Boost LLC converter arrangements are simulated and outcomes are compared. The outcome of signifies of Boost LLC-FOPID provides a better answer than the Boost LLC-PI controller arrangement. The Boost LLC-FOPID controlled high gain arrangement has better result parameter like reduced steady-state error, rise time, peak time, settling time. © 2021 IEEE.

关键词： controllers

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Design and Implementation of a Damping controller in Microgrids

Design and Implementation of a Damping Controller in Microgr...

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Evolutionary Algorithms and Soft computing Techniques (EASCT), international conference on

作者： Harshini Panda Pradeep Kumar Sivakumar Electrical and Electronics Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

The power generation and distribution sectors observe high-level penetration of Renewable Energy Sources (RESs) and Distributed Generators (DGs) due to several factors such as perpetual energy demand, nature of sources and load. Nevertheless, more specifically, the direct current (DC) micro grid is getting more attention over the conventional alternating current (AC) Micro rid for several benefits; for example, higher efficiency and reliability. This research work focus on three aspects the first one to design phase shift full bridge DC-DC converter with and discuss with various optimization techniques for implementing the Micro Grid. The second aspects to validate to implemented the Enthalpy Sigmoid Neuro-Fuzzy crowbar control using DFIG for power oscillation damping. The third aspects to analysis and implementation of a damping controller with renewable energy sources. The advantages and disadvantages of different protection and planning approaches are explained in detail. The effectiveness for the proposed strategy is proved.

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Enhancing Smart Grid Security with Machine Learning: A Comparative Study of Supervised and Unsupervised Techniques

Enhancing Smart Grid Security with Machine Learning: A Compa...

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international conference on New Trends in computing sciences (ICTCS)

作者： Abdirizak Abdullahi Khalif Abubakar Abdi Warsame Jafar Ismail Mohamed Hafso Mohamed Mohamoud Abdinasir Hirsi Lukman Audah Mohamed Osman Omar Abdiaziz Mohamed Abdirahman Mohamed Elmi Ahmed AI and Network Security (AiNetSec) Research Lab (Virtual Lab) Bosaso Somalia Faculty of Engineering Jamhuriya University of Science and Technology Mogadishu Somalia Faculty of Electrical & Electronics Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Faculty of Technology and Business Management UTHM University Parit Raja Malaysia

ISBN: (数字)9798331523411

ISBN: (纸本)9798331523428

The smart grid enables the collection of enormous quantities of high-dimensional, multi-type data on the operation of the electric power grid by integrating modern metering infrastructure, control technologies, and communication technologies. Smart utilities are more vulnerable to cyber-attacks because of their dependence on advanced information and communication technology. Cybersecurity in smart grids has been the focus of numerous studies. This study provides a comprehensive and unique examination of the potential of machine learning to secure a smart grid infrastructure by evaluating supervised and unsupervised machine learning models. This study emphasizes the prospective application and limitations of these models. It evaluates the most recent approaches and considers performance metrics such as computing complexity and accuracy. This study also identifies critical research issues and future approaches for cybersecurity threat identification in smart grids. The three primary sections of this article are a taxonomy of machine learning techniques, a review of related studies, and a concise summary of the results and their significance.

关键词： Reviews Computational modeling Prevention and mitigation Taxonomy Machine learning Smart grids Power systems Protection Standards Resilience

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automatic Emotion Recognition System: A cross Culture Study between Tamil and Russian Speaking Children

Automatic Emotion Recognition System: A cross Culture Study ...

引用

Advanced Research in computing (ICARC), international conference on

作者： Ruban Nersisson Prithiraj Bhuyan A. Mary Mekala Elena Lyakso School of Electrical Engineering Vellore Institute of Technology Vellore India School of Computer Science and Engineering Vellore Institute of Technology Vellore India The Child Speech Research Group St. Petersburg State University Russia

Speech based communication contains both linguistic and paralinguistic information. It conveys emotions not only through its verbal communication, but also through voice characteristics such as pitch, volume, and stress. The objective of this study is to convey the child’s emotion to a caretaker. To achieve this, a cross-cultural study of four emotions "joy - neutral (calm state) - sadness - anger" in children aged 8-12 years is considered. The data collection is carried out in multiple modes like acting speech in Russian and spontaneous and acting speech in Tamil language. SVM and MLP classitiers were used by the Russian specialist to train and validate speech data of both languages. The accuracy achieved by the Russian team is 84.1% and the Indian specialists used CNN and obtained the training and validation accuracy of 90% and >68% over 75 Epoch and used 7-layer CNN and obtained the training and validation accuracy of 95% and > 65% over 50 Epoch. The goal of the study is to see how well Russian and Indian specialists can recognise the emotional condition of Russian and Indian children based on their speech, and the results are correlated with computer-based emotion classification algorithms with various machine learning and deep net architectures.

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Bug Triaging: Right Developer Recommendation for Bug Resolution Using Data Mining Technique 6th

Bug Triaging: Right Developer Recommendation for Bug Resolut...

引用

6th international conference on Emerging Research in computing, Information, Communication and Applications, ERCICA 2020

作者： Chaitra, B.H. Swarnalatha, K.S. Department of Information Science and Engineering NITTE Meenakshi Institute of Technology Bengaluru India

ISBN: (纸本)9789811613418

Most of the open-source projects consist of open-source bug repositories. Users report the bugs frequently to these open-source bug repositories. The bugs are typically non-technical and cannot be assigned to the correct class. Triaging these bugs is extremely time-consuming. Developers are expected to be expertise in specific areas. For example, some developers are experts of GUI and while others in Java applications. Assigning a particular bug to respective developer could save time and would help the developers according to their requirements. However, assigning correct bug to respective developer is quite difficult for triager without knowing the actual class, to which the bug belongs. Bugs are inevitable and bug triaging is a challenging, time-consuming, tedious and expensive task, particularly the software bugs. Larger software projects include more of incoming bug reports than in smaller projects. Triaging these bug reports is a tough and time consuming. Part of the bug triaging process is assigning a newly arrived bug report to a developer who can successfully resolve the bug. automatic assignment of the bug to the right developer based on the developer’s experience and skills for the bug fixation is achieved. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data mining

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Memristive Circuit Design of Operant Conditioning with Bridging

Memristive Circuit Design of Operant Conditioning with Bridg...

引用

Memristive computing and Applications (ICMCA), IEEE international conference on

作者： Yu Zhai Yi Yue Rui Duan Bairen Chen Junwei Sun Yanfeng Wang School of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou China School of Information and Communication Zhengzhou Electric Power College Zhengzhou China

Most of the previous operant conditioning neural network circuits only consider the basic theory and ignore the effect of additional stimuli on operant conditioning, such as bridging stimulus. In this paper, a memristor-based operant conditioning circuit with bridging is designed. The designed circuit is mainly composed of delay module, voltage control module and experience module. The various processes of operant conditioning are taken into account. The designed circuit realizes the feedback learning, experience memory, experience-based decision making and bridging functions in operant conditioning. The effect of the length of the bridging stimulus on operant conditioning is also taken into account. The study of operant conditioning with bridging can provide a reference for the study of more intelligent brain-like systems.

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Social Media Event Summarization using Neural Networks

Social Media Event Summarization using Neural Networks

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Smart Technologies in computing, electrical and Electronics (ICSTCEE), international conference on

作者： Sucharitha Yadala Anitha Gurram Yamunadevi S Veeresh U S Bhargavi Latha TN Chitti Computer Science and Engineering VNR Vignana Jyothi Institute of Engineering & Technology Hyderabad India Computer Science and Engineering CMR Institute of Technology Hyderabad India Computer Science and Engineering Panimalar Engineering College Tamilnadu India School of Computer Science and Engineering REVA University Bengaluru Karnataka India Kalasalingam Academy of Research and Education Krishnankoil India

Micro blogging sites have become extremely popular, with a huge number of tweets being posted daily on a broad assortment of subjects. Recent studies have exposed that a significant part of these tweets are regarding “events”, and the discovery of new events in the tweet-stream has pulled in a lot of attention. In the Natural Language Processing (NLP) field, automatic text summarization is viewed as an extremely tricky problem. The content substance on the internet, specifically, is rising at an outstanding level. The capacity to decode through such immense volumes of data, to facilitate mine the require knowledge, is a foremost undertaking and needs an automatic system to serve with the present warehouse of data. A decent text summarization framework should comprehend the entire content, reorganize information, and create coherent, useful and amazingly tiny summaries to pass on the significant information of the innovative content. In this article, an inventive content summarization framework has been built, which combines RNN with LSTM and encoder-decoder structure. Our framework is assessed on the LCSTS dataset, which is an excellent corpus of Chinese short content summarization dataset created from “SinaWeibo”. Empirical outcomes exhibit the adequacy of the proposed framework, which outperforms all the existing approaches. Particularly, the proposed framework enhances the semantic consistency by 5% in terms of human assessment.

关键词： Social networking (online) Semantics Neural networks Blogs Natural language processing Data mining

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The Technical Research of In Situ Diagnoses of Engine Start electrical control System 2

The Technical Research of In Situ Diagnoses of Engine Start ...

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2nd IEEE international conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021

作者： Meng, Fei Wang, Fawei Ji, Tian Zhou, Mingqiu School of Aeronautical Maintenance NCO Air Force Engineering University Xingyang China

ISBN: (纸本)9781665428767

It is always a puzzle reflected by the user that the high failure rate of a certain engine start system with shortage of maintenance methods. Based on the analysis of logic control relationship and requirements of electrical parameters measurement of engine start electrical control system, the rule database and fact database based on fault model are constructed by using FMEA. And the methods are achieved by using of PCI bus control, data acquisition and processing, Windows software programming in order to diagnose and measure the logical relationship of engine start system and typical electrical parameters in situ automatically. Eventually the automatic test platform is running fast and convenient, accurate and reliable, which can provide support for fault diagnosis and intelligent maintenance decisions. © 2021 IEEE.

关键词： Data acquisition

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