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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jiaxiong Fang Juan Liu Hua Chen Wei Liu Ye Tian Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China School of Electronic Engineering and Computer Science Queen Mary University of London London UK

Based on the exact source-sensor spatial geometry, a three-dimensional (3-D) spatial-temporal localization algorithm for multiple near-field (NF) sources is proposed without adopting the Fresnel approximation, which simplifies the spatial phase difference by Taylors polynomial. In addition, considering the propagation attenuation which varies from different sensors, the spatial and temporal information can be exploited to construct a third-order parallel factor (PARAFAC) data model and the array manifold matrices can be extracted by trilinear decomposition; then, estimation of the unambiguous range and angle parameters of the NF sources is achieved from the spatial amplitude-phase factors by the least squares method. The obtained 3-D parameters associated with each source require no additional pairing process, as also demonstrated by simulation results.

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Deterministic Networking (DetNet): Architecture, Protocols, and Advanced Applications

Deterministic Networking (DetNet): Architecture, Protocols, ...

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International Conference on Mechatronics (ICOM)

作者： Zeinab E. Ahmed Aisha A. Hashim Rashid A. Saeed Mamoon M. Saeed Department of Computer Engineering University of Gezira Sudan Department of Electrical and Computer Engineering International Islamic University Malaysia Malaysia School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

This paper provides a thorough overview of Deterministic Networking (DetN et), focusing on establishing predictable data routes in Layer 2 and Layer 3 networks to address network issues like congestion, latency, and packet loss. It discusses DetNet's principles, architecture, and Operations, Administration, and Maintenance (OAM) protocols, crucial for fault detection and network monitoring. DetN et ensures bounded latency and minimal data loss, catering to industries' need for reliable flows over multi-hop paths. It integrates Time Sensitive Networking (TSN) and MPLS, using Resource Allocation (RA), Service Protection (SP), and Explicit Routing (ER) as core technologies, within a structured architecture of controller, application, and network planes. OAM is pivotal for efficient DetN et management, offering tools for fault detection, continuity checks, and maintenance activities to maintain Service Level Objectives (SLOs). The paper delves into advanced DetN et applications, highlighting enhanced protocols, health care frameworks, service function chain management, and industrial networking solutions, emphasizing their potential to improve reliability and network efficiency across diverse applications.

关键词： Industries Multiprotocol label switching Job shop scheduling Service function chaining Fault detection Packet loss Medical services

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Enhancing Smart City Mobility Using Software Defined Networks

Enhancing Smart City Mobility Using Software Defined Network...

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International Conference on Mechatronics (ICOM)

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

Smart cities face challenges in mobility management, such as scalability, latency, resource allocation, security, and energy efficiency, which traditional methods struggle to address effectively. Software Defined Networking (SDN) is a rapidly evolving field that provides centralized control and programmability of network devices. SDN-based MM can advance sustainable urban development by centralizing control, adapting to changes, optimizing resource allocation, reducing energy consumption, and improving urban mobility. This paper investigates SDN's role in enhancing urban sustainability and analyzes its implications for sustainable cities. The paper categorizes the use of SDN technology to improve various aspects of smart cities into three categories: Emergency Services and Traffic Management, Security and DDoS Defense, and Network Performance. Results showed a 20% reduction in average travel times and a 33% improvement in emergency response times. Future research should focus on advanced real-time traffic management algorithms, integrating emerging technologies like 6G, and artificial intelligence to improve SDN-based systems' scalability and efficiency in smart cities.

关键词： Energy consumption Smart cities Scalability Transforms Emergency services Energy efficiency Security

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A multi-Layer CNN-GRUSKIP model based on transformer for spatial − TEMPORAL traffic flow prediction

arXiv

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arXiv 2025年

作者： Ata, Karimeh Ibrahim Mohammad Hassan, Mohd Khair Ismaeel, Ayad Ghany Al-Haddad, Syed Abdul Rahman Alquthami, Thamer Alani, Sameer Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia UPM Serdang Selangor Darul Ehsan43400 Malaysia Department of Computer and Communication Systems Engineering Universiti Putra Malasia Selangor Seri Kembangan43400 Malaysia Electrical and Computer Engineering Department King Abdulaziz University Jeddah21589 Saudi Arabia Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Computer Center University of Anbar Iraq

Traffic flow prediction remains a cornerstone for intelligent transportation systems (ITS), influencing both route optimization and environmental efforts. While Recurrent Neural Networks (RNN) and traditional Convolutional Neural Networks (CNN) offer some insights into the spatial–temporal dynamics of traffic data, they’re often limited when navigating sparse and extended spatial–temporal patterns. In response, the CNN-GRUSKIP model emerges as a pioneering approach. Notably, it integrates the GRU-SKIP mechanism, a hybrid model that leverages the Gate Recurrent Unit’s (GRU) capabilities to process sequences with the’SKIP’ feature’s ability to bypass and connect longer temporal dependencies, making it especially potent for traffic flow predictions with erratic and extended patterns. Another distinctive aspect is its non-standard 6-layer CNN, meticulously designed for in-depth spatiotemporal correlation extraction. The model comprises (1) the specialized CNN feature extraction, (2) the GRU-SKIP enhanced long-temporal module adept at capturing extended patterns, (3) a transformer module employing encoder-decoder and multi-attention mechanisms to hone prediction accuracy and trim model complexity, and (4) a bespoke prediction module. When tested against real-world datasets from California’s Caltrans Performance Measurement System (PeMS), specifically PeMS districts 4 and 8, the CNN-GRUSKIP consistently outperformed established models such as ARIMA, Graph Wave Net, HA, LSTM, STGCN, and APTN. With its potent predictive prowess and adaptive architecture, the CNN-GRUSKIP model stands to redefine ITS applications, especially where nuanced traffic dynamics are in play. © 2025, CC0.

关键词： Convolutional neural networks

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Modelling of PV Plant for Supplying of Medium Sized Enterprises

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

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International Symposium on Electrical Apparatus and Technologies (SIELA)

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

ISBN: (数字)9798350382365

ISBN: (纸本)9798350382372

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.

关键词： Photovoltaic systems Meters Green energy Electricity Production Distribution networks Supercapacitors

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Hybrid Multi-Strategy Aquila Optimization with Deep Learning Driven Crop Type Classification on Hyperspectral Images

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computer Systems Science & engineering 2023年第10期47卷 375-391页

作者： Sultan Alahmari Saud Yonbawi Suneetha Racharla ELaxmi Lydia Mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa King Abdulaziz City for Science and Technology P.O Box 6086Riyadh 11442Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of AIML Aditya Engineering CollegeSurempallemAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed *** spatial information and spectral signatures of hyperspectral images(HSIs)present greater potential for detecting and classifying fine *** accurate classification of crop kinds utilizing hyperspectral remote sensing imaging(RSI)has become an indispensable application in the agricultural *** is significant for the prediction and growth monitoring of crop *** the deep learning(DL)techniques,Convolution Neural Network(CNN)was the best method for classifying HSI for their incredible local contextual modeling ability,enabling spectral and spatial feature *** article designs a Hybrid Multi-Strategy Aquila Optimization with a Deep Learning-Driven Crop Type Classification(HMAODL-CTC)algorithm *** proposed HMAODL-CTC model mainly intends to categorize different types of crops on *** accomplish this,the presented HMAODL-CTC model initially carries out image preprocessing to improve image *** addition,the presented HMAODL-CTC model develops dilated convolutional neural network(CNN)for feature *** hyperparameter tuning of the dilated CNN model,the HMAO algorithm is ***,the presented HMAODL-CTC model uses an extreme learning machine(ELM)model for crop type classification.A comprehensive set of simulations were performed to illustrate the enhanced performance of the presented HMAODL-CTC *** comparison studies reported the improved performance of the presented HMAODL-CTC algorithm over other compared methods.

关键词： Crop type classification hyperspectral images agricultural monitoring deep learning metaheuristics

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Harmonic Analysis of SEPIC DC-DC Converter

Harmonic Analysis of SEPIC DC-DC Converter

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Junior Conference on Lighting (Lighting)

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

ISBN: (数字)9798350352757

ISBN: (纸本)9798350352764

In the presented work, a harmonic analysis has been implemented to determine the resonance occurrence node of the Sepic DC-DC converter. The simulation studies were implemented in MATLAB/Simulink. Two cases of transistor conduction are presented. The differential equations for describing the processes in the converter are presented. State space matrices are used to implement harmonic analysis. Simulation studies are obtained and comments are made on the advantages and disadvantages of the methods used.

关键词： Lighting Differential equations DC-DC power converters Harmonic analysis Resonance Transistors Matrix converters

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Harmonic Analysis of Cûk DC-DC Converter

Harmonic Analysis of Cûk DC-DC Converter

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International Symposium on Electrical Apparatus and Technologies (SIELA)

ISBN: (数字)9798350382365

ISBN: (纸本)9798350382372

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.

关键词： Smart cities Simulation RLC circuits DC-DC power converters Harmonic analysis Resonance Power electronics

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

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

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Junior Conference on Lighting (Lighting)

ISBN: (数字)9798350352757

ISBN: (纸本)9798350352764

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.

关键词： Strips Voltage fluctuations Simulation Lighting DC-DC power converters Light emitting diodes Stability analysis

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Towards Holistic Crime Management Through Descriptive Analysis and Predictive Forecasting

Towards Holistic Crime Management Through Descriptive Analys...

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Advancements in Computing (ICAC), International Conference on

作者： Tinaya Wijethunge Sampath Edirisinghe Mansik Jeon Jeehyun Kim Ruchire Wijesinghe Bhagya Silva Department of Computer Engineering Faculty of Engineering Nugegoda Sri Lanka Daegu Republic of Korea Department of Electrical and Electronic Engineering Faculty of Engineering Malabe Sri Lanka Center for Excellence in Informatics Electronics Transmission (CIET) Malabe Sri Lanka Department of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Throughout the evolution of humankind, devising effective crime prevention strategies has been a concern in fostering safer communities. Although achieving a zero-crime rate is not possible yet, using data management methods can contribute to preventing and minimizing crimes. This article presents an integrated approach to proactive crime prevention. Data insights derived from analysis and visualization provide a comprehensive overview of historical trends and scenarios, aiding understanding of past and present situations. The forecasting of crime rates extends this comprehension to the future, spotlighting the severity of the potential threat to the safety of the community. Three distinct prediction models are presented to predict the occurrence of violent/non-violent crimes, the most probable crime type, and the most probable crime location in a spatial-temporal context, facilitating optimal resource allocation of police patrolling. Combining these three analytical components, an application is designed to present this holistic solution for effective crime prevention, with a 73% accuracy in predicting violent crimes. To achieve higher accuracy in predicting the most probable crime types and locations, it is essential to go beyond spatiotemporal context and augment data on other factors that affect the occurrence of crimes.

关键词： Adaptation models Accuracy Uncertainty Prevention and mitigation Computational modeling Predictive models Data models Spatiotemporal phenomena Forecasting Meteorology

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