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36th International Conference on Electrical Drives and Power Electronics, EDPE 2023

作者： Korkosz, Mariusz Krzywdzinska-Kornak, Krystyna Parfianowicz, Kamil Prokop, Jan Shchur, Ihor Rzeszow University of Technology Faculty of Electrical and Computer Engineering Rzeszow Poland Lviv Polytechnic National University Department of Electric Mechatronics and Computerized Electromechanical Systems Lviv Ukraine

ISBN: (纸本)9798350322750

The paper concerns the analyzis of the characteristics of a brushless permanent magnet motor for critical drive. To increase the level of redundancy, a multichannel power supply is provided for the analyzed motor. At the motor design stage, a provision was made for dual-channel or single-channel operation with balanced magnetic pull, or quadchannel, triple-channel, dual-channel, and single-channel operation with the possibility of unbalanced magnetic pull appearing. The results of numerical tests of the analyzed structure are included. Selected tests were carried out under laboratory conditions to verify the design assumptions. The prototype design was shown to tolerate single-channel operation with balanced magnetic pull, enabling continuous operation. In the case of single-channel operation with unbalanced magnetic pull, it is only possible to operate within a limited time range while maintaining the required output power. © 2023 IEEE.

关键词： Permanent magnets

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Learning of Multimodal Point Descriptors in Radar and LIDAR Point Clouds

Learning of Multimodal Point Descriptors in Radar and LIDAR ...

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International Conference on Multisensor Fusion and Integration for Intelligent systems (MFI)

作者： Jan M. Rottter Simon Cohrs Holger Blume Bernardo Wagner Realtime Systems Group of the Faculty of Electrical Engineering and Computer Science Leibniz University of Hannover Hannover Germany Institute of Microelectronic Systems of the Faculty of Electrical Engineering and Computer Science Leibniz University of Hannover Hannover Germany

ISBN: (数字)9798350368031

ISBN: (纸本)9798350368048

Registration of point clouds is a fundamental task in robotic SLAM pipelines. Typically this task is performed only on point clouds of the same sensor or at least the same sensing modality. However, robots designed for challenging environments are often equipped with redundant sensors for the same task where some sensors are more accurate and others are more robust against disturbing environmental conditions. Being able to register the data across the modalities is an important step to more fault-tolerant localization and mapping. We therefore propose a learning framework, which describes the points in the point cloud invariant of their modality. This description is then used in a transformer-like model to find point matches for the registration process. We demonstrate our results using a scanning lidar and radar sensor on our own and publicly available datasets.

关键词： Point cloud compression Location awareness Laser radar Simultaneous localization and mapping Pipelines Robot sensing systems Transformers Sensors Registers Intelligent systems

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UWB Channel Modeling and Simulation with Continuous Frequency Response

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China Communications 2022年第11期19卷 88-98页

作者： Kai Mao Qiuming Zhu Xijuan Ye Ruirui Feng Fuqiao Duan Yang Miao Maozhong Song The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space College of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China The Radio Systems Faculty of Electrical Engineering Computer Science and Mathematics(EEMCS)University of Twentethe Netherlands

Ultra-wideband(UWB)technology is a prospective technology for high-rate transmission and accurate localization in the future communication ***-of-art channel modeling approaches usually divide the UWB channel into several sub-band channels and model them *** considering frequency-dependent channel parameters,a novel analytical UWB channel model with continuous frequency response is *** composite effect of all frequency components within the UWB channel on the channel impulse response(CIR)of delay domain is derived based on the continuous channel transfer function(CTF)of frequency *** this basis,a closed-form simulation model for UWB channels and geometry-based parameter calculation method are developed,which can guarantee the continuity of channel characteristics on the frequency domain and greatly reduce the simulation ***,the proposed method is applied to generate UWB channel with 2 GHz bandwidth at sub-6GHz and millimeter wave(mmWave)bands,*** channel measurements are also carried out to validate the proposed *** simulated CIR and power gain are shown to be in good agreement with the measurement ***,the comparison results of power gain and Doppler power spectral density(DPSD)show that the proposed UWB channel model Received:Apr.23,2022 Revised:Jun.09,2022 Editor:Wei Fan achieves a good balance between the simulation accuracy and efficiency.

关键词： ultra-wideband(UWB)channel continuous frequency response frequency-dependent channel parameters simulation model channel measurement

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Optimal Deep Convolutional Neural Network for Vehicle Detection in Remote Sensing Images

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computers, Materials & Continua 2023年第2期74卷 3117-3131页

作者： Saeed Masoud Alshahrani Saud S.Alotaibi Shaha Al-Otaibi Mohamed Mousa Anwer Mustafa Hilal Amgad Atta Abdelmageed Abdelwahed Motwakel Mohamed I.Eldesouki Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Object detection(OD)in remote sensing images(RSI)acts as a vital part in numerous civilian and military application areas,like urban planning,geographic information system(GIS),and search and rescue *** recognition from RSIs remained a challenging process because of the difficulty of background data and the redundancy of recognition *** latest advancements in deep learning(DL)approaches permit the design of effectual OD *** study develops an Artificial Ecosystem Optimizer with Deep Convolutional Neural Network for Vehicle Detection(AEODCNN-VD)model on Remote Sensing *** proposed AEODCNN-VD model focuses on the identification of vehicles accurately and *** detect vehicles,the presented AEODCNN-VD model employs single shot detector(SSD)with Inception network as a baseline *** addition,Multiway Feature Pyramid Network(MFPN)is used for handling objects of varying sizes in *** features from the Inception model are passed into theMFPNformultiway andmultiscale feature ***,the fused features are passed into bounding box and class prediction *** enhancing the detection efficiency of the AEODCNN-VD approach,AEO based hyperparameter optimizer is used,which is stimulated by the energy transfer strategies such as production,consumption,and decomposition in an *** performance validation of the presentedmethod on benchmark datasets showed promising performance over recent DL models.

关键词： Object detection remote sensing vehicle detection artificial ecosystem optimizer convolutional neural network

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An Improved Multi-Objective Particle Swarm Optimization Routing on MANET

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computer systems Science & engineering 2023年第2期44卷 1187-1200页

作者： G.Rajeshkumar M.Vinoth Kumar K.Sailaja Kumar Surbhi Bhatia Arwa Mashat Pankaj Dadheech Department of Computer Science and Engineering Erode Sengunthar Engineering CollegePerunduraiErode638057Tamil NaduIndia Department of Information Science and Engineering Dayananda Sagar Academy of Technology and ManagementBangalore560082India Department of Master of Computer Applications M.S.Ramaiah Institute of TechnologyBangalore560054India Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversityRiyadh11533Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityRabigh21911Saudi Arabia Department of Computer Science and Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipur302017RajasthanIndia

A Mobile Ad hoc Network(MANET)is a group of low-power con-sumption of wireless mobile nodes that conﬁgure a wireless network without the assistance of any existing infrastructure/centralized *** primary aim of MANETs is to extendﬂexibility into the self-directed,mobile,and wireless domain,in which a cluster of autonomous nodes forms a MANET routing *** Intrusion Detection System(IDS)is a tool that examines a network for mal-icious behavior/policy violations.A network monitoring system is often used to report/gather any suspicious attacks/*** IDS is a software program or hardware system that monitors network/security trafﬁc for malicious attacks,sending out alerts whenever it detects malicious *** impact of Dynamic Source Routing(DSR)in MANETs challenging blackhole attack is investigated in this research *** Cluster Trust Adaptive Acknowledgement(CTAA)method is used to identify unauthorised and malfunctioning nodes in a MANET *** system is active and provides successful delivery of a data packet,which implements Kalman Filters(KF)to anticipate node ***,KF is used to eliminate synchronisation errors that arise during the sending and receiving *** order to provide an energy-efﬁcient solution and to minimize network trafﬁc,route optimization in MANET by using Multi-Objective Particle Swarm Optimization(MOPSO)technique to determine the optimal num-ber of clustered MANET along with energy dissipation in *** to the researchﬁndings,the proposed CTAA-MPSO achieves a Packet Delivery Ratio(PDR)of 3.3%.In MANET,the PDR of CTAA-MPSO improves CTAA-PSO by 3.5%at 30%malware.

关键词： MANET intrusion detection system cluster kalmanﬁlter dynamic source routing multi-objective particle swarm optimization packet delivery ratio

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Applying Apache Spark on Streaming Big Data for Health Status Prediction

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computers, Materials & Continua 2022年第2期70卷 3511-3527页

作者： Ahmed Ismail Ebada Ibrahim Elhenawy Chang-Won Jeong Yunyoung Nam Hazem Elbakry Samir Abdelrazek Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computers and InformationEl-Zagazig UniversityZagazigSharqiyah44519Egypt Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Big data applications in healthcare have provided a variety of solutions to reduce costs,errors,and *** work aims to develop a real-time system based on big medical data processing in the cloud for the prediction of health *** the proposed scalable system,medical parameters are sent to Apache Spark to extract attributes from data and apply the proposed machine learning *** this way,healthcare risks can be predicted and sent as alerts and recommendations to users and healthcare *** proposed work also aims to provide an effective recommendation system by using streaming medical data,historical data on a user’s profile,and a knowledge database to make themost appropriate real-time recommendations and alerts based on the sensor’s *** proposed scalable system works by tweeting the health status attributes of *** cloud profile receives the streaming healthcare data in real time by extracting the health attributes via a machine learning prediction algorithm to predict the users’health ***,their status can be sent on demand to healthcare ***,machine learning algorithms can be applied to stream health care data from wearables and provide users with insights into their health *** algorithms can help healthcare providers and individuals focus on health risks and health status changes and consequently improve the quality of life.

关键词： Big data streaming processing healthcare data machine learning IoT data processing Apache Spark

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Parameters Extraction of Photovoltaic Cell Using Particle Swarm Optimization 4th

Parameters Extraction of Photovoltaic Cell Using Particle Sw...

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4th International Conference on Electronic engineering and Renewable Energy systems, ICEERE 2024

作者： Chermite, Charaf Douiri, Moulay Rachid Elamri, Oumaymah Control and Computer Science for Intelligent Systems and Green Energy Department of Applied Physics Faculty of Science and Technology Cadi Ayyad University Marrakech Morocco LAMIGEP EMSI of Marrakech Systems and Applications Engineering Laboratory National School of Applied Sciences Cadi Ayyad University Marrakech Marrakesh Morocco

ISBN: (纸本)9789819799749

Extracting parameters accurately and effectively from solar photovoltaic (PV) models is crucial for detailed simulation, evaluation, and management of PV systems. Although there has been an increase in the development of analytical, numerical, and metaheuristic methods targeting this task, accurately determining these parameters continues to be a significant challenge. This study focuses on applying Particle Swarm Optimization (PSO) for the extraction of key parameters of RTC France solar cells, a critical step towards enhancing PV system efficiency and reliability. Additionally, the PSO's performance is evaluated against other metaheuristic algorithms including Enhanced Chaotic JAYA (CJAYA), Performance-Guided JAYA (PGJAYA), and Enhanced Gradient-Based Optimizer (EGBO), underscoring the effectiveness of the proposed PSO-based approach. Utilizing MATLAB-SIMULINK, comprehensive analysis and results are presented, shedding light on the efficacy of PSO in addressing the intricacies of parameter extraction in PV systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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A Review of Evaluation Metrics Algorithmic Used in Scholarly Research Recommender System

A Review of Evaluation Metrics Algorithmic Used in Scholarly...

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International Multidisciplinary Information Technology and engineering Conference (IMITEC)

作者： Gerald Ovono Travos Zuva Temidayo Otunniyi Department of Computer Faculty of Applied and Computer Sciences South Africa Department of Process Control and Computer Systems Faculty of Engineering and Technology VaalUniversity of Technology South Africa

ISBN: (数字)9798350387988

ISBN: (纸本)9798350387995

The exponential growth of academic publications has made scholarly research recommender systems indispensable tools for researchers. These systems rely on diverse evaluation metrics to assess their effectiveness and relevance. This paper provides a comprehensive review and analysis of these metrics, categorizing them into accuracy, ranking, diversity, user-centric, coverage, temporal, and computational metrics. By employing a mixed-methods approach, combining systematic literature review and empirical analysis, we identify the prevalence and application of these metrics across various scholarly domains such as literature, conferences, and reviewers. Our findings highlight the widespread use of traditional metrics like precision, recall, and Fl-score, while emphasizing the growing importance of novel metrics such as unexpectedness and serendipity, especially in literature and conference recommendations. We also underscore the domain-specific nature of metric selection, with user-centric evaluations more prominent in literature recommendations, and ranking-focused metrics dominant in conference and reviewer recommendations. Furthermore, the study reveals a significant gap in the use of temporal and computational metrics, suggesting key areas for future research. This review offers valuable insights for researchers and practitioners, guiding them in metric selection and highlighting potential directions for enhancing the effectiveness, adaptability, and user satisfaction of scholarly recommender systems.

关键词： Measurement Accuracy Diversity reception Solids Information technology Recommender systems Systematic literature review

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Alita, Debby Ahmad, Imam Jafar Rumandan, Rhaishudin Erkamim, Moh Widyasmoro Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Institut Agama Islam Negeri Ambon Islamic Education Management Study Program Ambon Indonesia Universitas Tunas Pembangunan Smart City Information Systems Study Program Surakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data. © 2024 IEEE.

关键词： Classification Data Mining Decision Tree Stunting

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Development of an Active Contour Method Based on Contrast Features to Detect Keratitis in the Cornea

Development of an Active Contour Method Based on Contrast Fe...

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International Conference on Informatics and Computing (ICIC)

作者： Wahyu Saptha Negoro Sumijan Saiful Bukhori Faculty of Engineering and Computer Science Universitas Potensi Utama Medan Indonesia Faculty of Engineering and Computer Science Universitas of UPI YPTK Padang Indonesia Faculty of Computer Science Information Systems Universitas of Jember Jember Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Digital Image Processing (DIP) is a scientific discipline with techniques for processing images using computers. The digital image is expressed in a two-dimensional matrix. The research object is keratitis on the cornea. The keratitis image was obtained using a slit lamp photo at Rs. Padang Aye Center (PAC), based on the results ofthe diagnosis by looking at the development of the infiltrate or also called hypopyon, by measuring the ulcer borders horizontally and vertically with the aim of evaluating improvements that respond to treatment. The clinical results obtained cannot determine the extent and circumference of the keratitis layer area that responds to keratitis as a whole. The images used were 206 slit lamp images of keratitis. This research provides knowledge in the form of contrast values in the Active Contour method, resulting in an update called Contras Adjustment (CA)/CAimg, in correctly segmenting keratitis objects and providing measurements of the area and circumference of the keratitis area. The results of this study were from 206 slit lamp images, 195 slit lamp images of keratitis that detected keratitis correctly and 11 slit lamp images of keratitis that could not be detected, resulting in an accuracy of $\mathbf{9 5 \%}$.

关键词： Accuracy Cornea Digital images Picture archiving and communication systems Personnel MATLAB Informatics Standards Active contours Testing

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