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Reliable Phase Selection Method for Transmission Systems Based on Relative Angles Between Sequence Voltages

Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1431-1444页

作者： Abdallah A.Aboelnaga Maher A.Azzouz the Department of Electrical and Computer Engineer ing University of WindsorWindsorON N9B 3P4Canada Electrical Power and Machines Department Faculty of EngineeringAin Shams UniversityCairo 11566Egypt the Electrical Engineering Department Qatar UniversityDohaQatar

Fault currents emanating from inverter-based resources(IBRs)are controlled to follow specific references to support the power grid during ***,these fault currents differ from the typical fault currents fed by synchronous generators,resulting in an improper operation of conventional phase selection methods(PSMs).In this paper,the relative angles between sequence voltages measured at the relay location are determined analytically in two stages:(1)a short-circuit analysis is performed at the fault location to determine the relative angles between sequence voltages;and(2)an analysis of the impact of transmission line on the phase difference between the sequence voltages of relay and fault is conducted for different IBR ***,new PSM zones based on relative angles between sequence voltages are devised to facilitate accurate PSM regardless of the fault currents,resistances,or locations of *** time-domain simulations confirm the accuracy of the proposed PSM with different fault locations,resistances,types,and currents.

关键词： Fault resilience fault type identification phase selection method inverter-based resource control function renewable energy source sequence voltage

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Comparative Analysis of Spatial Human Mobility Parameters in 15 Most Populous U.S. Metropolitan Statistical Areas

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IAENG International Journal of Applied Mathematics 2024年第6期54卷 997-1012页

作者： Matloub, Zaid Kostanic, Ivica Senior Data Engineer at Better World Analytics MelbourneFL United States Department of Electrical Engineering and Computer Science Florida Institute of Technology MelbourneFL United States

This research paper presents the results of two studies investigating human mobility patterns in the 15 largest Metropolitan Statistical Areas (MSAs) in the United States. It studied 14 daily mobility parameters aggregated at the MSA level, derived from four primary mobility parameters: Number of Visited Locations (N_LOC), Number of Unique Visited Locations (N_ULOC), Radius of Gyration (R_GYR), and Distance Traveled (D_TRAV) over a 30-day period. The first study was conducted on data from two large MSAs, one coastal and one inland (Boston and Atlanta, respectively). The aim was to examine associations between daily values of mobility parameters aggregated at the MSA level and identify those carrying similar or identical information. Results of factor analysis showed that these could be adequately described by two independent factors, pointing to one or two of the mobility parameters as sufficient to represent the whole set in analyses based on associations. These could either be D_TRAV, as it had high loadings on both factors, or N_LOC and R_GYR due to their high loadings on the two extracted factors. The second study was conducted on daily mobility datasets from the 15 MSAs. The aim was to compare daily mobility patterns of these MSAs and group them based on their mobility pattern similarities. Factor analysis of the aggregated mean daily distances (D_TRAV) across different MSAs over the studied period classified them into two distinct groups: one predominantly composed of inland MSAs and the other primarily of coastal MSAs. Strong weekly cycle trends emerged in these groups. Specifically, individuals from the inland MSA group tended to travel the furthest on Fridays and the least on Sundays, whereas those from the coastal MSA group traveled the most on Saturdays and the least on Mondays. This weekly pattern was robust, with 7-day lag autocorrelations of mean daily parameter values ranging between 0.81 to 0.99, excluding the mean daily N_LOC. These findings offer a

关键词： Big data

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An improved pulse coupled neural networks model for semantic IoT

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Digital Communications and Networks 2024年第3期10卷 557-567页

作者： Rong Ma Zhen Zhang Yide Ma Xiping Hu Edith C.H.Ngai Victor C.M.Leung School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China School of Medical Technology Beijing Institute of TechnologyBeijing100081China Department of Electrical and Electronic Engineer The University of Hong KongHong Kong 999077China College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and Computer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PCNN are determined by trial and error,which limits its *** overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this *** IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation *** IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

关键词： Internet of things(IoT) Semantic information Real-time application Improved pulse coupled neural network Image segmentation

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Model predictive control switching strategy for safe small satellite cluster formation flight

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Aerospace Systems 2023年第4期6卷 559-579页

作者： Smith, Tyson Akagi, John Droge, Greg GN &C Engineer Space Dynamics Laboratory LoganUT84341 United States Electrical and Computer Engineering Department Utah State University LoganUT84322 United States

This paper presents the development and analysis of a spacecraft formation flying architecture. The desired state of each spacecraft is maintained using a model predictive control-based control framework that is based on the Hill–Clohessy–Wiltshire equations and a polytope boundary constraint as a switching surface. This framework can be used to maintain the desired cluster formation while also guaranteeing internal cluster flight. The polytope boundaries are designed, such that no two agents have overlapping regions, allowing the vehicles to execute avoidance strategies without continually maintaining the trajectories of other agents. The model predictive control framework combined with the convex polytope boundary enables a scalable method that can support clusters of satellites to coordinate to safely achieve mission objectives while minimizing fuel usage. As part of the implementation of this control scheme, the authors created two spacecraft formation flying control approaches. The first approach uses fewer, large maneuvers to control a spacecraft to the center of a keep-in-volume. The second approach allows the spacecraft to perform many small maneuvers to stay just inside the boundary of the keep-in-volume. This paper compares the fuel cost savings of these two approaches. The results presented in this paper demonstrate that the first approach produces the lower total fuel usage, but if a lower amount of fuel per maneuver is required, then the second approach should be used. This work also compares the computation requirements and fuel usage for L 1 , L 2 , and L ∞ norms formulations of the framework, the L 1 and L 2 norms require the least amount of fuel usage, while the L 2 requires the least amount of computation time. © 2023, Shanghai Jiao Tong University.

关键词： Spacecraft

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Design and Model of On-Chip Metalens for Silicon Photonics Convolutional Neural Network

Design and Model of On-Chip Metalens for Silicon Photonics C...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Peserico, Nicola Yang, Hangbo Ma, Xiaoxuan Li, Shurui George, Jonathan K. Gupta, Puneet Wong, Chee Wei Sorger, Volker J. Department of Electrical & Computer Engineer. George Washington University WashingtonDC20052 United States Department of Electrical & Computer Engineering University of California Los AngelesCA90095 United States

Convolution Neural Networks are one of the most diffuse Neural Networks. Here, we present a Silicon photonic CNN chip that leverages hardware complexity by exploiting Fourier fight properties to perform convolution op... 详细信息

ISBN: (纸本)9781957171258

关键词： Silicon photonics

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PWM based Software defined radio Modeling 20

PWM based Software defined radio Modeling

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20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Sakr, Ahmed Hussein, Aziza I. Fahmy, Ghazal A. Abdelghany, Mahmoud A. Research Engineer Minia Egypt Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia National Telecommunications Institute Electronics Department Cairo Egypt Minia University Electrical Engineering Department Minia Egypt

ISBN: (纸本)9798350332568

Modern wireless networks are allocated in different frequency bands and have different specifications. However, many wireless devices are required to support different standards which is the case for mobile devices and IoT. For example, a modern mobile device usually supports 5G or 4G besides older generations back to 2G, Wi-Fi standards 802.11 a/b/g/n/ac and Bluetooth with its different versions. To support all these standards, an increasing complexity is added to the design of RF front-end that should be more flexible and more ***-defined-radio SDR aims to achieve a flexible front-end that is fully programmable and flexible in order to support more standards in different frequency bands and with different specifications. It takes advantage of the increasing enhancements in IC fabrication processes which enables performing signal processing in digital domain with high speed and accuracy more than what analog signal processing can *** this work, a review of traditional receivers as well as multistandard receivers and SDRs are performed, then an SDR based on Pulse-width-modulation PWM RF-to-digital receiver is demonstrated. The chosen PWM based SDR is modeled using MATLAB Simulink. © 2023 IEEE.

关键词： MATLAB

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Research on CANOpen Communication protocal for Electric Vehicle On-board Chargers

Research on CANOpen Communication protocal for Electric Vehi...

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2023 IET International Conference on engineering Technologies and Applications, ICETA 2023

作者： Wu, Ping-Tsang Chuang, Ching-Chun Hong, Min-Rui Wang, Shu-Po Wu, Jun-Yi Department of Computer Science & Information Engineering National Formosa University Taiwan Department of Electrical Engineering National Kaohsiung University of Science and Technology Taiwan Department of Vehicle Engineer National Formosa University Taiwan

ISBN: (纸本)9781839539848

This research focuses on utilizing the CANOpen communication protocol for operating and programming onboard vehicle chargers. With its benefits of high efficiency, reliability, and flexibility, CANOpen is widely adopted in the automobile industry. First of all, the research focused on analysing the fundamental principles and structure of the CANOpen communication protocol. Secondly, we will delve even further into the application of EV chargers during the setup and activation stage. By utilizing CANOpen communication, the onboard charger establishes a seamless and efficient connection with the electric vehicle's central control unit. This connection facilitates essential functions such as the management of charging initiation and termination, precise adjustment of the charging power output, and the comprehensive monitoring of the entire charging process. The experimental results demonstrate the stability and reliability of the vehicle charger when controlled through the CANOpen communication. © The Institution of engineering & Technology 2023.

关键词： Electric vehicles

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The New Frontier in Media: AI-Driven Content Creation for Ad-Supported TV using Generative Adversarial Network 7

The New Frontier in Media: AI-Driven Content Creation for Ad...

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7th International Conference of computer and Informatics engineering, IC2IE 2024

作者： Ramagundam, Shashishekhar Karne, Niharika Comcast Software Development and Engineering in Content Discovery and Ai United States Troy University Masters in Computer Science AL. Department of Computer Science Montgomery Campus United States Dt Amtrak Sr. Principal Systems Engineer in C and Rs Platform Services United States University of South Alabama Masters in Electrical Engineering Department of Electrical Engineering United States

ISBN: (纸本)9798331505530

The use of Artificial intelligence (AI) technology in the content creation to produce creative aspects like editing, audience analysis, creating ideas, writing copy, etc. The major aim is to streamline and automate the process of content creation and convert it into a more efficient and effective way. There is a lack of transparency in the AI content production process and hence it does not exactly mimic human activities, which includes fantasizing and picking up new abilities. AI content creation requires more creativity while investigating with a specific goal in mind. Although, AI faces many challenges since it constantly expands its base knowledge. One of the biggest ethical problems is the probability that AI content is used to deceive or influence people. Hence, to overcome these difficulties a machine learning-based Artificial Intelligent content creation framework is generated for content creation in Ad-supported TV. Here, an effective model Generative Adversarial Network (GAN) introduced to deliver enterprise data, customize descriptions, and adjust content based on consumer behaviors. This developed model produces material that is closely related to the preferences of the user. AI content creation increases efficiency and productivity by saving time and money. It also leads to the development of better content. Finally, the experimental analysis is performed to find the effectiveness of the developed deep learning-based AI content creation framework via various metrics. © 2024 IEEE.

关键词： Generative adversarial networks

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The Application of a Synonyms Dictionary Using Bi-LSTM in Bangla for Better Approximation 2

The Application of a Synonyms Dictionary Using Bi-LSTM in Ba...

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2nd International Conference on Information and Communication Technology for Sustainable Development, ICICT4SD 2023

作者： Hossain, M Iffat Saha, Utsha Billa, Arefa Software Engineer BJIT Ltd. Dhaka Bangladesh North Dakota State University Department of Computer Science Fargo United States Florida State University Department of Electrical and Computer Engineering Tallahassee United States

ISBN: (纸本)9798350358667

With the increasing internet usage, the volume of computerized data in Bangla is also growing exponentially. This vast repository of unstructured web data has various potential applications in Natural Language Processing (NLP). However, research in Bangla NLP faces significant challenges, including language complexity and limited availability of tools and datasets. These factors result in a lower accuracy rate when traditional methods used for English NLP are applied to Bangla. Specifically, the Bangla language has a rich lexicon of root words and characters, leading to an increase in out-of-vocabulary words when dealing with unseen texts. This paper proposes a novel method that employs a synonym dictionary to mitigate this problem. By converting unseen words into their synonyms that are recognized by the model, the method significantly reduces out-of-vocabulary errors. Our approach achieved an accuracy rate of 97.4%, compared to 95.3% without using the synonym dictionary, and had a loss value of 0.96. This methodology holds promise as an effective tool for solving classification problems in Bangla NLP. © 2023 IEEE.

关键词： Long short-term memory

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Attention Mechanism indicating Item Novelty for Sequential Recommendation 14

Attention Mechanism indicating Item Novelty for Sequential R...

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14th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022

作者： Wang, Li-Chia Ma, Hao-Shang Huang, Jen-Wei National Cheng Kung University Department of Electrical Engineering Tainan Taiwan Institute of Computer and Communication Engineer National Cheng Kung University Department of Electrical Engineering Tainan Taiwan

ISBN: (纸本)9781665456616

Most sequential recommendation systems, including those that employ a variety of features and state-of-the-art network models, tend to favor items that are the most popular or of greatest relevance to the historic behavior of the user. Recommendations made under these conditions tend to be repetitive;i.e., many options that might be of interest to users are entirely disregarded. This paper presents a novel algorithm that assigns a novelty score to potential recommendation items. We also present an architecture by which to incorporate this functionality in existing recommendation systems. In experiments, the proposed NASM system outperformed state-of-the-art sequential recommender systems, thereby verifying that the inclusion of novelty score can indeed improve recommendation performance. © 2022 IEEE.

关键词： Recommender systems

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