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23rd International Symposium on Electrical Apparatus and Technologies, SIELA 2024

作者： Vacheva, Gergana Stanchev, Plamen Hinov, Nikolay Technical University of Sofia Faculty of Electronic Engineering and Technologies Departement of Power Electronics Sofia Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Departement of Information Technology in Industry Sofia Bulgaria

ISBN: (纸本)9798350382365

In the present paper, a harmonic analysis of a Cuk DC-DC converter is realized. A simulation model was implemented in MATLAB/Simulink. The converter is described using differential equations that are represented in state space. Two scenario of on and off transistor are considered. Simulation results are shown, where it can be observed in which case resonance occurs, which significantly influences the design of the circuit. Main advantages and disadvantages of the selected topology are described. © 2024 IEEE.

关键词： Cuk converter

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Modelling of PV Plant for Supplying of Medium Sized Enterprises 23

Modelling of PV Plant for Supplying of Medium Sized Enterpri...

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23rd International Symposium on Electrical Apparatus and Technologies, SIELA 2024

作者： Vacheva, Gergana Borisov, Andrei Hinov, Nikolay Stanchev, Plamen Faculty of Electronic Engineering and Technologies Technical University of Sofia Departement of Power Electronics Sofia Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Departement of Information Technology in Industry Sofia Bulgaria

ISBN: (纸本)9798350382365

In current research a photovoltaic plant for supplying medium sized enterprises is studied. In the presented manuscript the main advantages of the proposed system and disadvantages of connecting photovoltaic systems to the distribution network are discussed. Also, the parameters and external influences on the power plant are presented. Data from smart meters for electricity production for a period of 1 year were used. © 2024 IEEE.

关键词： DC distribution systems

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LTSpice Based Stability Analysis of DC-DC Converter for LED Drivers 9

LTSpice Based Stability Analysis of DC-DC Converter for LED ...

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9th Junior Conference on Lighting, Lighting 2024

ISBN: (纸本)9798350352757

This article presents a stability analysis of a boost DC-DC converter for powering an LED strip. A model of a DC converter is presented and the principle of operation is described. LTSpice software was used to implement the mathematical model. LED strip data provided by the manufacturer is used. Simulation results of the realized studies by Fourier transformation are presented. Investigating the influence of transient in LED drivers is useful in order to ensure the stability of the manufactured device under various external influences. © 2024 IEEE.

关键词： Light emitting diodes

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Guest Editorial International Flexible electronics Technology Conference (IFETC) 2022 Special section of Selected Extended Papers

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible electronics 2023年第4期2卷 283-284页

作者： Guo, Xiaojun Ng, Tse Nga Petti, Luisa Yu, Jun Susthitha Menon, P. Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China University of California at San Diego Department of Electrical and Computer Engineering San DiegoCA92093 United States Free University of Bozen & Bolzano Faculty of Engineering Bolzano39100 Italy Shandong University School of Information Science and Engineering Qingdao266237 China Bangi43600 Malaysia

Flexible electronics is being continuously challenged by the growing demands for systems with better quality, lower cost, greener manufacturing, and mechanical flexibility. It goes beyond displays and wearable systems for all pervasive human–machine–environment interfaces. Therefore, the materials and manufacturing techniques at all levels have become increasingly critical for the electronics community to connect device technologies, manufacturing, and circuits and systems. The International Flexible electronics Technology Conference (IFETC), fully sponsored by the IEEE Electron Devices Society, is a premier conference for the flexible electronics community held annually in different locations around the globe that have become the hot beds for dissemination of designs, manufacturing techniques, and applications of semiconductor devices, circuits, and systems. The annual conference provides a forum for the flexible electronics communities to discuss and collaborate on a broad range of topical areas going beyond displays and wearable systems for an all-pervasive humanmachine-environment.

关键词： Special issues and sections Flexible electronics Meetings

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Sentiment Analysis using Machine Learning and Deep Learning Models

Sentiment Analysis using Machine Learning and Deep Learning ...

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2024 IEEE International Conference on Machine Learning and Applied Network Technologies, ICMLANT 2024

作者： Vu, Hoang-Dieu Pham, Quang-Tu Solanki, Vijender Kumar Hoang, Trong-Minh Tran, Duc-Tan Faculty of Electrical and Electronic Engineering Phenikaa University Hanoi Viet Nam Department of Computer Science and Enginnering Stanley College Of Engineering & Technology For Women TG Hyderabad India Posts and Telecommunications Institute of Technology Hanoi Viet Nam

ISBN: (纸本)9798350389180

This study investigates sentiment analysis methodologies using two distinct datasets: the IMDb Movie Reviews corpus and a novel Financial Sentiment dataset. Employing a comprehensive approach, the research integrates traditional Machine Learning algorithms and Deep Learning models to analyze and interpret sentiments. The preprocessing phase incorporates techniques such as punctuation removal, text lowercasing, and specialized considerations for financial symbols. Machine Learning models, including Logistic Regression and Random Forest, are applied to the IMDb dataset, with Naive Bayes demonstrating superior performance at 89% accuracy. The Deep Learning model achieves 82% accuracy on the testing set. In the Financial Sentiment dataset, Naive Bayes emerges as the optimal model, despite reduced overall performance due to dataset limitations and imbalance. This research contributes valuable insights into sentiment analysis methodologies, offering a nuanced understanding of model performance across diverse datasets and enhancing our comprehension of sentiment classification in various contexts. © 2024 IEEE.

关键词： Adversarial machine learning

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Free-electron crystals for enhanced X-ray radiation

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Light(Science & Applications) 2024年第7期13卷 1299-1309页

作者： Lee Wei Wesley Wong Xihang Shi Aviv Karnieli Jeremy Lim Suraj Kumar Sergio Carbajo Ido Kaminer Liang Jie Wong School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore. Solid State Institute and Faculty of Electrical and Computer Engineering Technion–Israel Institute of TechnologyHaifa 3200003Israel. School of Electrical Engineering Fleischman Faculty of EngineeringTel Aviv UniversityTel Aviv 69978Israel Department of Applied Physics Stanford UniversityStanfordCA 94305USA. Science Mathematics and TechnologySingapore University of Technology and Design8 Somapah RoadSingapore 487372Singapore. Electrical and Computer Engineering Department UCLA420 WestwoodLos AngelesCA 90095USA. Physics and Astronomy Department UCLA475 Portola PlazaLos AngelesCA 90095USA. SLAC National Accelerator Laboratory Stanford University2575 Sand Hill RoadMenlo ParkCA 94025USA

Bremsstrahlung—the spontaneous emission of broadband radiation from free electrons that are deflected by atomic nuclei—contributes to the majority of X-rays emitted from X-ray tubes and used in applications ranging from medical imaging to semiconductor chip ***,we show that the bremsstrahlung intensity can be enhanced significantly—by more than three orders of magnitude—through shaping the electron wavefunction to periodically overlap with atoms in crystalline ***,we show how to shape the bremsstrahlung X-ray emission pattern into arbitrary angular emission profiles for purposes such as unidirectionality and ***,we find that these enhancements and shaped emission profiles cannot be attributed solely to the spatial overlap between the electron probability distribution and the atomic centers,as predicted by the paraxial and nonrecoil theory for free electron light *** work highlights an unprecedented regime of free electron light emission where electron waveshaping provides multi-dimensional control over practical radiation processes like *** results pave the way towards greater versatility in table-top X-ray sources and improved fundamental understanding of quantum electron-light interactions.

关键词： overlap attributed arbitrary

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Transformer-based Text Classification on Unified Bangla Multi-class Emotion Corpus 25

Transformer-based Text Classification on Unified Bangla Mult...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Sourav, Md Sakib Ullah Mahmud, Mohammad Sultan Zheng, Hua Aljaidi, Mohammad Talukder, Md. Simul Hasan Bin Sulaiman, Rejwan Nur, Abdullah Hafez Al-Qerem, Ahmad Shandong University of Finance and Economics School of Management Science and Engineering Jinan China Shenzhen University College of Computer Science and Software Engineering Senzhen China Software Engineering Institute of Guangzhou Department of Software Engineering Guangzhou510990 China Zarqa University Department of Computer Science Zarqa Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Dhaka University of Engineering and Technology Department of Electrical and Electronic Engineering Dhaka Bangladesh Northumbria University Newcastle Tayne School of Computer Science & Technology Northumbria United Kingdom International Islamic University Chittagong Department of Electronic and Telecommunication Engineering Chittagong Bangladesh Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan

ISBN: (纸本)9798331540012

Due to its importance in studying people's thoughts on various Web 2.0 services, emotion classification is a critical undertaking. Most existing research is focused on the English language, with little work on low-resource languages. Though sentiment analysis, particularly emotion classification in English, has received increasing attention in recent years, little study has been done in the context of Bangla, one of the world's most widely spoken languages. In this research, we propose a complete set of approaches for identifying and extracting emotions from Bangla texts. We provide a Bangla emotion classifier for six classes, i.e., anger, disgust, fear, joy, sadness, and surprise, from Bangla words using transformer-based models, which exhibit phenomenal results in recent days, especially for high-resource languages. The Unified Bangla Multi-class Emotion Corpus (UBMEC) is used to assess the performance of our models. UBMEC is created by combining two previously released manually labelled datasets of Bangla comments on six emotion classes with fresh manually labelled Bangla comments created by us. The corpus dataset and code we used in this work are publicly available. © 2024 IEEE.

关键词： Classification (of information)

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Proactive Production Forecasting to Support Offshore Wind Development

Proactive Production Forecasting to Support Offshore Wind De...

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2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Wilk, Patrick Fera, James Yang, Yujie Liu, Ting Li, Jie Rowan University Electrical and Computer Engieering Glassboro United States Xi'an Jiaotong University Faculty of Electronic and Information Engineering Xi'an China

ISBN: (纸本)9798350312492

This research explores a proactive production forecasting methodology to support the current offshore wind development in the U.S., highlighting the effectiveness of utilizing a well-trained long short-term memory (LSTM) machine learning model, which robustly captures intricate temporal patterns in historical wind speed trends, wind turbine power curves, forecasted offshore wind speeds, and wind turbine configuration parameters, thus offering a reliable foundation for effective power production predictions. Due to the underdevelopment of offshore wind in the U.S. and the lack of access to true offshore wind farm operational data, this study builds, trains, and tests a generalized model on four existing land-based operational wind farms, and then deploys the model on a New Jersey offshore wind farm that is now under development. Equipped with such a proactive production prediction tool, offshore wind developers and operators could pursue alternative profitable opportunities in the ISO/RTOs' wholesale electricity markets when state funding for renewable purchases, such as Offshore Renewable Energy Credits (ORECs) or power purchase agreements (PPAs), is not available. Accurate production forecasting can mitigate potential penalties for offshore wind power producers (WPPs) due to over and/or under commitment in the forward wholesale electricity markets and prove them to be as competitive in the markets as those traditionally predictable non-renewable resources. © 2023 IEEE.

关键词： Offshore wind farms

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Leveraging Outage probability in system limited by BX fading and Co-channel interference for ChatGPT-enabled QoS adaptation 31

Leveraging Outage probability in system limited by BX fading...

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31st Telecommunications Forum, TELFOR 2023

作者： Vujović, Vuk Milić, Dejan Petrović, Nenad Marković, Filip Suljović, Suad Stefanović, Radiša MB University Belgrade Computer Science and Informatics Information Technology Belgrade Serbia University of Niš Telecommunications Faculty of Electronic Engineering Niš Serbia University of Niš Computer Science and Informatics Faculty of Electronic Engineering Niš Serbia University of Priština Computer Science and Informatics Faculty of Technical Sciences Kosovska Mitrovica Serbia Computer Science and Informatics the Academy of Applied Technical Studies Belgrade Belgrade Serbia

ISBN: (纸本)9798350303131

In this paper, we performed an analysis of the outage probability (Pout) at the output of the receiver with selection combination (SC) with L branches of the wireless communication system in the presence of Beaulieu-Xie (BX) fading and BX co-channel interference (CCI). The mathematical form of the function for Pout as a normalized signal-to-interference ratio (SIR) was derived, based on which a graph was drawn for different values of fading and CCI parameters. The second part of the paper considers applying machine learning approach relying on ChatGPT with aim to enable fading type recognition based on Pout measurements, which can be further used in order to perform Quality of Service (QoS) adaptation by tuning receiver's parameters. © 2023 IEEE.

关键词： Quality of service

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Target tracking method of Siamese networks based on the broad learning system

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1043-1057页

作者： Dan Zhang C.L.Philip Chen Tieshan Li Yi Zuo Nguyen Quang Duy Navigation College Dalian Maritime UniversityDalianChina Innovation and Entrepreneurship Education College Dalian Minzu UniversityDalianChina Computer Science and Engineering College South China University of TechnologyGuangzhouChina Department of Computer and Information Science Faculty of Science and TechnologyUniversity of MacaoMacaoChina School of Automation Engineering University of Electronic Science and Technology of ChinaChengduChina Faculty of Navigation Vietnam Maritime UniversityHaiphongVietnam

Target tracking has a wide range of applications in intelligent transportation,real‐time monitoring,human‐computer interaction and other ***,in the tracking process,the target is prone to deformation,occlusion,loss,scale variation,background clutter,illumination variation,etc.,which bring great challenges to realize accurate and real‐time *** based on Siamese networks promotes the application of deep learning in the field of target tracking,ensuring both accuracy and real‐time ***,due to its offline training,it is difficult to deal with the fast motion,serious occlusion,loss and deformation of the target during ***,it is very helpful to improve the performance of the Siamese networks by learning new features of the target quickly and updating the target position in time *** broad learning system(BLS)has a simple network structure,high learning efficiency,and strong feature learning *** at the problems of Siamese networks and the characteristics of BLS,a target tracking method based on BLS is *** method combines offline training with fast online learning of new features,which not only adopts the powerful feature representation ability of deep learning,but also skillfully uses the BLS for re‐learning and re‐*** broad re‐learning information is used for re‐detection when the target tracking appears serious occlusion and so on,so as to change the selection of the Siamese networks search area,solve the problem that the search range cannot meet the fast motion of the target,and improve the *** results show that the proposed method achieves good results on three challenging datasets and improves the performance of the basic algorithm in difficult scenarios.

关键词： broad learning system siamese network target tracking

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