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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Srivastav, Adarsh Indira, G. Tiwaskar, Shweta A. Garg, Avni Singh, Shweta Das, Sunanda Vivekananda Global University Department of Computer Science & Engineering Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350319125

textual content Mining is the process of extracting meaningful information from large volumes of unstructured text. it's far a form of synthetic intelligence used to investigate and interpret files along with consumer feedback, emails, transcripts, net logs, surveys, and on line documents. Its intention is to discover hidden shape, patterns, institutions, and correlations in textual facts in order to draw inferences and broaden new insights. textual content Mining allows a deeper level of intelligence and selection-making by means of uncovering which means from unstructured textual facts. by means of utilising present day statistical strategies and herbal Language Processing (NLP), text Mining can produce automatic fashions that interpret and translate textual content into intelligent information which can be used to make correct predictions and provide actionable insights. textual content Mining is also being used to find out new trends, categorize client sentiment, locate correlations in purchaser comments, and section document collections. eventually, text Mining is being used to assist automate selection-making by automating workflows, processing massive volumes of text in a fragment of time, and providing deep insights into patron conversations. © 2023 IEEE.

关键词： Automating Categorize Collections Conversations Insights

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Characterization and Control of a Superconducting Homopolar Motor with Cryogenic GaN Inverter for Electric Aircrafts

Characterization and Control of a Superconducting Homopolar ...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Gliese, Felix Pearce, Matthew G. S. Wadsworth, Aaron Siamaki, Mohammad Storey, James Lumsden, Grant Thrimawithana, Duleepa J. Badcock, Rod Roth-Stielow, Joerg Neuburger, Martin Esslingen University Faculty of Mobility and Technology Germany The University of Auckland Dept. of Electrical Computer and Software Engineering New Zealand OpenStar Technologies New Zealand Victoria University of Wellington Robinson Research Institute New Zealand University of Stuttgart Institute for Power Electronics and Electrical Drives Germany

ISBN: (纸本)9798350376067

In the quest for a zero-emissions future, the aviation sector is facing the challenge of reducing its carbon footprint. This paper presents a characterization of a superconducting homopolar motor designed to meet the stringent power and efficiency requirements of all-electric aircraft. The control system, which features field-oriented control and a multi-layer architecture, ensures precise operation of the motor under various load conditions. The motor uses a stationary cryogenic superconducting DC coil to generate the rotor's magnetic field. Utilizing superconducting materials helps produce the high power densities critical for aviation. The characterization of the key parameters of the motor, such as inductances, stator resistance and flux, are presented. A description of the cryogenic GaN power electronic inverter power stage immersed in liquid nitrogen is provided. This design enables future integration next to the motor, and improved power density and efficiency. This paper outlines the design, implementation, and initial testing of the superconducting homopolar motor and its power electronics, highlighting its potential for electric propulsion in aviation by providing a viable solution for long-range flights. © 2024 IEEE.

关键词： Gallium nitride

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Efficient COVID-19 super pixel segmentation algorithm using MCFO-based SLIC

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Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9217-9232页

作者： Faragallah, Osama S. El-Hoseny, Heba M. El-Sayed, Hala S. Department of Information Technology College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Computer Science The Higher Future Institute for Specialized Technological Studies El Shorouk Egypt Department of Electrical Engineering Faculty of Engineering Menoufia University Shebin El-Kom32511 Egypt

In computer vision segmentation field, super pixel identity has become an important index in the recently segmentation algorithms especially in medical images. Simple Linear Iterative Clustering (SLIC) algorithm is one of the most popular super pixel methods as it has a great robustness, less sensitive to the image type and benefit to the boundary recall in different kinds of image processing. Recently, COVID-19 severity increased with the lack of an effective treatment or vaccine. As the Corona virus spreads in an unknown manner, th-ere is a strong need for segmenting the lungs infected regions for fast tracking and early detection, no matter how small. This may consider difficult to be achieved with traditional segmentation techniques. From this perspective, this paper presents an efficient modified central force optimization (MCFO)-based SLIC segmentation algorithm to discuss chest CT images for detecting the positive COVID-19 cases. The proposed MCFO-based SLIC segmentation algorithm performance is evaluated and compared with the thresholding segmentation algorithm using different evaluation metrics such as accuracy, boundary recall, F-measure, similarity index, MCC, Dice, and Jaccard. The outcomes demonstrated that the proposed MCFO-based SLIC segmentation algorithm has achieved better detection for the small infected regions in CT lung scans than the thresholding segmentation. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： COVID-19

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Optimal Almost-Balanced Sequences

arXiv

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arXiv 2024年

作者： Bar-Lev, Daniella Kobovich, Adir Leitersdorf, Orian Yaakobi, Eitan Faculty of Computer Science Technion Israel Institute of Technology Haifa3200003 Israel Faculty of Electrical and Computer Engineering Technion Israel Institute of Technology Haifa3200003 Israel

This paper presents a novel approach to address the constrained coding challenge of generating almost-balanced sequences. While strictly balanced sequences have been well studied in the past, the problem of designing efficient algorithms with small redundancy, preferably constant or even a single bit, for almost balanced sequences has remained unsolved. A sequence is Ε(n)-almost balanced if its Hamming weight is between 0.5n ± Ε(n). It is known that for any algorithm with a constant number of bits, Ε(n) has to be in the order of Θ(√n), with O(n) average time complexity. However, prior solutions with a single redundancy bit required Ε(n) to be a linear shift from n/2. Employing an iterative method and arithmetic coding, our emphasis lies in constructing almost balanced codes with a single redundancy bit. Notably, our method surpasses previous approaches by achieving the optimal balanced order of Θ(√n). Additionally, we extend our method to the non-binary case, considering q-ary almost polarity-balanced sequences for even q, and almost symbol-balanced for q = 4. Our work marks the first asymptotically optimal solutions for almost-balanced sequences, for both, binary and non-binary alphabet. © 2024, CC BY-NC-ND.

关键词： Redundancy

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Heterodyne quantum light detection using free electrons

Heterodyne quantum light detection using free electrons

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Malka, Salomon Abu-El-Hija, Mohamad Gorlach, Alexey Karnieli, Aviv Kaminer, Ido Solid State Institute Faculty of Electrical & Computer Engineering Technion -Israel Institute of Technology Israel Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv69978 Israel

We show that free electrons can be used for heterodyne light detection and are sensitive to quantum-optical properties of light, including off-diagonal elements of the photonic density matrix. © Optica Publishing... 详细信息

ISBN: (纸本)9781957171258

关键词： Optical properties

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Self-Supervise Reinforcement Learning Method for Vacant Parking Space Detection Based on Task Consistency and Corrupted Rewards

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IEEE Transactions on Intelligent Transportation Systems 2024年第2期25卷 1346-1363页

作者： Nguyen, Manh-Hung Chao, Tzu-Yin Hsiao, Ching-Chun Li, Yung-Hui Huang, Ching-Chun Hcm University of Technology and Education Faculty of Electrical Electronic Engineering Ho Chi Minh City700000 Viet Nam National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300093 Taiwan Hon Hai Research Institute Ai Research Center New Taipei City114699 Taiwan

This paper proposes a novel task-consistency learning method that enables us to train a vacant space detection network (target task) based on the logic consistency with the semantic outcomes from a flow-based motion behavior classifier (source task) in a parking lot. Note that the source task can introduce false detection during task-consistency learning, which implies noisy rewards or supervision. The target network can be trained in a reinforcement learning setting by appropriately designing the reward mechanism upon semantic consistency. We also introduce a novel symmetric constraint to detect corrupted samples and reduce the effect of noisy rewards. Unlike conventional corrupted learning methods that use only training losses to identify corrupted samples, our symmetric constraint also explores the relationship among training samples to improve performance. Compared with conventional supervised detection methods, the main contribution of our work is the ability to learn a vacant space detector via semantic consistency rather than supervised labels. The dynamic learning property allows the proposed detector to be easily deployed and updated in various lots without heavy human loads. Experiments demonstrate that our noisy task consistency mechanism can be successfully applied to train a vacant space detector from scratch. © 2000-2011 IEEE.

关键词： Semantics

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SiamCircle: Trajectory Representation Learning in Free Settings 23rd

SiamCircle: Trajectory Representation Learning in Free Sett...

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23rd International Symposium on Intelligent Data Analysis, IDA 2025

作者： Nasri, Maedeh Baratchi, Mitra Koutamanis, Alexander Rieffe, Carolien Department of Developmental Psychology Leiden University Leiden Netherlands Leiden Institute of Advanced Computer Science Leiden University Leiden Netherlands Faculty of Architecture and the Built Environment Delft University of Technology Delft Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands Department of Psychology and Human Development Institute of Education UCL London United Kingdom

ISBN: (纸本)9783031913976

Trajectory representation learning (TRL) is an intermediate step in handling trajectory data to realize various downstream machine-learning tasks. While most previous TRL research focuses on modeling structured movements in large-scale urban spaces (e.g., cars or pedestrians on streets), this paper focuses on a more challenging scenario of modeling free movement in small-scale social spaces (e.g., children playing in a schoolyard). We present a TRL model, SiamCircle, to process raw trajectories without additional feature extraction to prevent information loss. SiamCircle adopts a Siamese network with Circle Loss to learn trajectory embeddings. Furthermore, SiamCircle employs a data augmentation process to enable self-supervised learning and enrich the input data to address the limited access to high-quality data and ground truth. We evaluate the performance of SiamCircle in downstream tasks using trajectory ranking and clustering performance via seven evaluation metrics collectively. Using an ablation study, we explored the impact of different loss functions on the model’s performance. Accordingly, we selected a 2-D convolutional design with Circle Loss as the best-performing model. In a comparative study, we compared our model against three other baselines. We observed up to 19% improvements in trajectory ranking tasks and achieved the highest average rank in supervised clustering tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Sorting

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Bamboo Forest Growth Optimization Algorithm for Night Image Enhancement 15th

Bamboo Forest Growth Optimization Algorithm for Night Image...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Shi, Hao-Jie Pan, Jeng-Shyang Chu, Shu-Chuan Kong, Lingping Snášel, Václav College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

ISBN: (纸本)9789819700677

The Bamboo Forest Growth Optimization(BFGO) algorithm is an algorithm proposed by the growth law of bamboo forest, which has the advantages of fast convergence and not easily falling into local optimum. In this paper we have experimented the BFGO with several other population intelligence optimization algorithms on 23 benchmark test functions and proved its superiority. Also we apply the bamboo forest optimization algorithm to nighttime image enhancement in this paper, and the algorithm achieves better results on this application. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Ontology-Based Crime News Semantic Retrieval System

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computers, Materials & Continua 2023年第10期77卷 601-614页

作者： Fiaz Majeed Afzaal Ahmad Muhammad Awais Hassan Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Information Technology University of GujratGujrat50700Pakistan Department of Computer Science University of Engineering&TechnologyLahore54890Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular *** news exists on the Internet in unstructured formats such as books,websites,documents,and *** such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement ***-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant *** are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given ***,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the *** ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal *** semantic system retrieves information in view of the similarity of the semantics among indexed data and user *** this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two *** the first experiment,we implemented a keyword-based textual IR systemusing Apache *** the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL *** keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.

关键词： Web 3.0 crime ontology semantic web knowledge representation

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Design of optimal hybrid power system to provide reliable supply to rural areas of Ethiopia using MATLAB and Homer

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Renewables: Wind, Water, and Solar 2021年第1期8卷 1-7页

作者： Nebey, Abraham Hizkiel Faculty of Electrical and Computer Engineering Bahir Dar University Institute of Technology Bahir Dar Ethiopia

Integrating different energy resources, like solar PV, wind, and hydro is used to ensure reliable power to the rural community loads. Hybrid power system offers sufficient power supply for the rural villages by providing alternative supply for intermittent nature of renewable energy resource. Hence, intermittency of renewable energy resources is a challenge to electrify the rural community in a sustainable manner with the above sources. Thus, efficient resources management is a reasonable choice for intermittent renewable energy resources. The majority of rural villages in Ethiopia are suffering from lack of electricity. This causes deforestation, travel for long distance to fetch water, and no good social services, like clinic and schools, sufficiently. Therefore, the objective of this study was to maximize reliability of power supply by renewable energy sources. Data on wind speed and solar radiation are obtained from the NASA surface meteorological agency. While hydro data are obtained from physical measurements. Different configuration options are considered by Homer software to find the optimal configuration of hybrid system. The optimal configuration system is selected and hybrid components are sized. The optimal hybrid system consists of solar PV, wind, and hydro to supply a community load with a share of 13%, 52%, and 35% respectively. The fuzzy logic controller is designed to manage the intermittent nature of energies. Hence, the demand and energy sources are unpredictable;intelligent control system is important to manage the system accordingly. The control system is designed in MATALAB software. The result obtained from resource combination shows demand and supply are balanced. From the Twelve probabilistic combinations of demand and energy sources, one of the combinations shows that when 7.5 kW is demanded, the power generated/output from hybrid system is 10 kW which is greater than demand. To satisfy 7.5 kW demand control system takes 4.25 kW, 2.75 kW, a

关键词： Hybrid systems

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