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2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023

作者： Sharma, Harsh Jindal, Harsh Sehgal, Abhinav Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh Group of Colleges Landran Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350380880

Data mining can be defined as a process of extracting and discovering required data or patterns from big data sets, sorting them through large data sets and finding relationships that can help solve business problems through data analysis to predict the desired outcomes. Gregory Piatetsky-Shapiro coined the term 'knowledge discovery in databases' for the first workshop on the same topic (KDD-1989) and this term became more popular in AI and machine learning community. This paper gives a lightning overview of data mining and its relation to statistics discusses the emerging applications and techniques of the data mining that has been adapted by some of the healthcare organizations to predict and analyse the heart related disease and businesses for the efficient and predictable outcome. This paper also describes how to apply the different data mining techniques such as prediction, classification, regression, clustering, and association mining onto the patterns for the future excellent results. The term 'data mining' is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself. © 2023 IEEE.

关键词： Data mining

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EcoRoute: Ecosystem of Electric Vehicle by Optimizing Route for Long-Distance Travel 3

EcoRoute: Ecosystem of Electric Vehicle by Optimizing Route ...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Sharma, Harsh Jindal, Harsh Sehgal, Abhinav Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh Group of Colleges Department of Computer Science and Engineering Landran Mohali India

ISBN: (纸本)9798350302288

Electric vehicle (EV) owners in India are facing dissatisfaction due to the limited availability and reliability of charging infrastructure. One of the main concerns is the inadequate range of EVs, which creates difficulties for long-distance travel. For instance, if a user needs to travel inter-statefor 1000 km but their EV's range is limited to 350 km, they need to stop multiple times at charging stations to complete the trip. Unlike traditional petrol or gasoline-based cars, EVs require a considerable amount of recharge, meaning users must manuallyplan their charging stops and search for available charging stations. This problem statement highlights the challenge of ensuring that EVs are viable and convenient for long-distance travel in India, where the availability and accessibility of charging infrastructure remain a significant concern. These issues can be resolved by eliminating human intervention in the route planning process of any trip. To minimize human interference an algorithm is required that can generate a route plan for long-distance travel based on the real-time stats of the electric vehicle. Various parameters need to be considered to optimize the travel route, and to minimize the overall travel time by reducing the total charging time in between. © 2023 IEEE.

关键词： Travel time

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Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones

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Journal of Electronic science and Technology 2024年第4期22卷 19-36页

作者： Didar Yedilkhan Abzal E.Kyzyrkanov Zarina A.Kutpanova Shadi Aljawarneh Sabyrzhan K.Atanov Department of Computer Engineering Astana IT UniversityAstana010000Kazakhstan Department of Computer and Software Engineering L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Automation and Control Systems L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Software Engineering Jordan University of Science and TechnologyIrbid22110Jordan

The growing field of urban monitoring has increasingly recognized the potential of utilizing autonomous technologies,particularly in drone *** deployment of intelligent drone swarms offers promising solutions for enhancing the efficiency and scope of urban condition *** this context,this paper introduces an innovative algorithm designed to navigate a swarm of drones through urban landscapes for monitoring *** primary challenge addressed by the algorithm is coordinating drone movements from one location to another while circumventing obstacles,such as *** algorithm incorporates three key components to optimize the obstacle detection,navigation,and energy efficiency within a drone ***,the algorithm utilizes a method to calculate the position of a virtual leader,acting as a navigational beacon to influence the overall direction of the ***,the algorithm identifies observers within the swarm based on the current *** further refine obstacle avoidance,the third component involves the calculation of angular velocity using fuzzy *** approach considers the proximity of detected obstacles through operational rangefinders and the target’s location,allowing for a nuanced and adaptable computation of angular *** integration of fuzzy logic enables the drone swarm to adapt to diverse urban conditions dynamically,ensuring practical obstacle *** proposed algorithm demonstrates enhanced performance in the obstacle detection and navigation accuracy through comprehensive *** results suggest that the intelligent obstacle avoidance algorithm holds promise for the safe and efficient deployment of autonomous mobile drones in urban monitoring applications.

关键词： Drone swarms Fuzzy logic Intelligent solution Smart city Urban monitoring

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Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

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computers, Materials & Continua 2024年第9期80卷 4475-4496页

作者： Xiwang Guo Liangbo Zhou Zhiwei Zhang Liang Qi Jiacun Wang Shujin Qin Jinrui Cao College of Information and Control Engineering Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Research Center of the Economic and Social Development of Henan East Provincial Joint Shangqiu Normal UniversityShangqiu476000China Department of Computer Science New Jersey City UniversityJersey CityNJ 07305USA

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle *** on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is *** enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular *** established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,*** a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

关键词： Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm

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Utilization of genetic algorithm in tuning the hyper-parameters of hybrid NN-based side-slip angle estimators

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Neural Computing and Applications 2024年第30期36卷 19055-19074页

作者： Essa, Mohamed G. Elias, Catherine M. Shehata, Omar M. Research Group Cairo Egypt Mechatronics Department Faculty of Engineering and Materials Science German University in Cairo Cairo Egypt Computer Science Department Faculty of Media Engineering and Technology German University in Cairo Cairo Egypt Mechatronics Department Faculty of Engineering Ain Shams University Cairo Cairo Egypt

This paper proposes a solution to enhance and compare different neural network (NN)-based side-slip angle estimators. The feed-forward neural networks (FFNNs), recurrent neural networks, long short-term memory units (LSTMs), and gated recurrent units are investigated. However, there is a lack in the selection criteria of the architectures’ hyper-parameters. Therefore, the genetic algorithm is integrated with the NN-based estimators to find the optimal hyper-parameters for the studied architectures. The tuned hyper-parameters in this work include the number of neurons, number of layers, activation function, optimizer type, and learning rate. The objective function of the optimization problem is minimizing the root-mean-square error (RMSE) on multiple testing data. The optimal models are further included in the design of a hybrid NN estimator with Kalman filter. In the hybrid estimators, the optimal NN estimators are used as virtual sensors to correct the prediction of the side-slip angle resulting from the mathematical lateral vehicle model. Eventually, the performance of the best selected model is evaluated in terms of different metrics;mean RMSE, mean error variance, mean training time, and mean estimation time. LSTMs are found to achieve the lowest mean RMSE while being tested on highly generalized data yielding the highest training and estimation time. However, FFNNs achieve the lowest RMSE while being tested on low generalized data and the lowest training and estimation time. Meanwhile, it is observed that the hybrid estimators achieved lower RMSE with great enhancement compared to the non-hybridized ones proving the effectiveness of the proposed approach and increasing the side-slip estimation generalization ability in unknown environments with high uncertainties, which are not covered by the training dataset for the NNs estimators. © The Author(s) 2024.

关键词： Kalman filters

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HoloStream: a GPU-powered high-speed user interface for holographic microscopy imaging

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Optics Express 2025年第7期33卷 15648-15660页

作者： Morales, Johan Obando-Vásquez, Sofia Doblas, Ana Trujillo, Carlos Applied Optics Group School of Applied Science and Engineering EAFIT University Medellin Colombia Optical Imaging Research Lab Electrical and Computer Engineering Department University of Massachusetts Dartmouth DartmouthMA United States

This paper presents HoloStream, a GPU-powered high-speed user interface designed for holographic microscopy imaging. The platform reconstructs quantitative phase images rapidly for off-axis digital holographic microscopy (DHM) systems operating in the telecentric regime. By optimizing critical computational procedures, the HoloStream app reconstructs phase maps of 1280 × 960 pixels up to 11 frames per second (FPS) in live visualization and 90 fps for pre-recorded holographic videos. This real-time phase compensation is performed by upgrading the semi-heuristic phase compensation (SHPC) algorithm through GPU acceleration via PyCUDA. The interface also offers a user-friendly experience with flexible control over acquisition modes, visualization formats, and 3D tracking functionalities. Experimental validation demonstrates the platform’s capability to achieve fast and accurate phase imaging for live microscopy applications. The HoloStream app advances DHM technology by combining high-speed processing with ease of use, making it suitable for a wide range of DHM imaging applications. © 2025 Optica Publishing group under the terms of the Optica Open Access Publishing Agreement.

关键词： computer graphics equipment

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X-ray Image Analysis for Aided Detection of COVID-19

X-ray Image Analysis for Aided Detection of COVID-19

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2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Sharma, Avinash Barua, Tarkeshwar Garg, Prachi Saxsena, Rini Goyel, Parul Singh Parmar, Vivek Chandigarh Group of Colleges Department of Computer Science and Engineering Chandigarh Engineering 140307 India Roorkee Institute of Technology Department of Computer Science and Engineering Roorkee India Mmec Department of Computer Science and Engineering Mullana India M. M. Engineering College Maharishi Markandeshwar Mullana Computer Science & Engineering Haryana Ambala1307 India Chitkara University Department of Cse India

ISBN: (纸本)9798331508432

The COVID-19 epiphytotic highlighted the necessity for speedy and accessible identification instruments. Chest X-rays offer a readily available and relatively inexpensive Tomography proficiency. This stuff explores the potential of X-ray image analysis using Profound learning algorithmic program for the aided detection of COVID-19 contagions. While chest X-rays and CT scans are valuable instruments for COVID-19 diagnosis, manual analysis is time-consuming and error-prone. Profound learning, a powerful subset of artificial intelligence[10], offers promising solutions for automated and accurate COVID-19 detection from these Tomography modalities. This stuff reviews key investigation findings on Profound learning-based classification of COVID-19 using chest X-rays and CT scans. We explore the current state-of-the-art advancements, discuss remaining challenges, and outline potential future directions in this crucial field. Containing COVID-19 relies heavily on isolating infected individuals and widespread inoculation. While RT-PCR tests remain the gold standard for diagnosis, delays in processing limit their effectiveness. Additionally, post-recovery positive tests raise concerns about accuracy [7]. Vaccines offer protection, but breakthrough contagions occur. Developing highly effective, long-lasting vaccines and achieving planetary immunization face significant logistical hurdles. Faster and more reliable identification instruments are crucial to complement these ongoing efforts. © 2024 IEEE.

关键词： Vaccines

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Energy Efficient Dual User Association for Large Scale IRS-Aided mmWave Communication Networks

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China Communications 2025年第1期22卷 182-195页

作者： Chen Guolin Deng Yiqin Huang Xiaoxia Fang Yuguang School of Electronics and Communication Engineering Sun Yat-sen UniversityShenzhen 518107China School of Control Science and Engineering Shandong UniversityJinan 250100China Department of Computer Science City University of Hong KongHong Kong 999077China

The deployment of multiple intelligent reflecting surfaces(IRSs)in blockage-prone millimeter wave(mmWave)communication networks have garnered considerable attention *** the remarkably low circuit power consumption per IRS element,the aggregate energy consumption becomes substantial if all elements of an IRS are turned on given a considerable number of IRSs,resulting in lower overall energy efficiency(EE).To tackle this challenge,we propose a flexible and efficient approach that individually controls the status of each IRS ***,the network EE is maximized by jointly optimizing the associations of base stations(BSs)and user equipments(UEs),transmit beamforming,phase shifts of IRS elements,and the associations of individual IRS elements and *** problem is efficiently addressed in two ***,the Gale-Shapley algorithm is applied for BS-UE association,followed by a block coordinate descent-based algorithm that iteratively solves the subproblems related to active beamforming,phase shifts,and element-UE *** reduce the tremendous dimensionality of optimization variables introduced by element-UE associations in large-scale IRS networks,we introduce an efficient algorithm to solve the associations between IRS elements and *** results show that the proposed elementwise control scheme improves EE by 34.24% compared to the network with IRS-all-on scheme.

关键词： energy efficiency intelligent reflecting surface,millimeter-wave communication

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Real-Time Multi-object Tracking Using YOLOv8 and SORT on a SoC FPGA 21st

Real-Time Multi-object Tracking Using YOLOv8 and SORT on a...

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21st International Symposium on Applied Reconfigurable Computing, ARC 2025

作者： Danilowicz, Michal Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031879944

Multi-object tracking (MOT) is one of the most important problems in computer vision and a key component of any vision-based perception system used in advanced autonomous mobile robotics. Therefore, its implementation on low-power and real-time embedded platforms is highly desirable. Modern MOT algorithms should be able to track objects of a given class (e.g. people or vehicles). In addition, the number of objects to be tracked is not known in advance, and they may appear and disappear at any time, as well as be obscured. For these reasons, the most popular and successful approaches have recently been based on the tracking paradigm. Therefore, the presence of a high quality object detector is essential, which in practice accounts for the vast majority of the computational and memory complexity of the whole MOT system. In this paper, we propose an FPGA (Field-Programmable Gate Array) implementation of an embedded MOT system based on a quantized YOLOv8 detector and the SORT (Simple Online Realtime Tracker) tracker. We use a modified version of the FINN framework to utilize external memory for model parameters and to support operations necessary required by YOLOv8. We discuss the evaluation of detection and tracking performance using the COCO and MOT15 datasets, where we achieve 0.21 mAP and 38.9 MOTA respectively. As the computational platform, we use an MPSoC system (Zynq UltraScale+ device from AMD/Xilinx) where the detector is deployed in reprogrammable logic and the tracking algorithm is implemented in the processor system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： System-on-chip

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From Exclusion to Inclusion: Digital Platforms as a Pathway for Hijra (Third Gender) Employment 24

From Exclusion to Inclusion: Digital Platforms as a Pathway ...

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2024 International Conference on Information and Communication Technologies and Development, ICTD 2024

作者： Fatema Lamia, Umme Ratul, Md. Alvi Islam Mrittika, Anika Priodorshinee Noor, Jannatun Department of Computer Science and Engineering Brac University Dhaka Bangladesh Research Group Brac University Dhaka Bangladesh

ISBN: (纸本)9798400710414

The Hijra community in Bangladesh continues to face discrimination in nearly every aspect of life, despite being officially recognized as a separate gender by the government. This recognition has yet to translate into tangible benefits, such as employment in the formal job sector. Past efforts have primarily focused on education, financial aid, and informal work opportunities. This study examines the potential and challenges of integrating Hijras into the formal job market, with a specific focus on developing and evaluating a tailored digital platform to enhance employment opportunities for Hijras in domestic and caregiving roles. Data was gathered through qualitative interviews with 46 Hijra individuals and an online survey of 136 general participants. By analyzing perspectives from both Hijras and the general public, we identified possible solutions for their inclusion in the formal workforce. The data was analyzed using qualitative methods, including open coding and thematic analysis. The study sheds light on the difficult realities faced by Hijras and presents a strategic intervention aimed at improving their socioeconomic standing and promoting inclusivity. The findings underscore the importance of comprehensive approaches, such as policy reforms and targeted support systems, to close the gap between legal recognition and actual societal acceptance. These efforts would create formal employment opportunities for Hijras, fostering a society where they are not only visible but also valued. Collaboration between the general public and the Hijra community is crucial, with NGOs and government agencies playing a key role in driving these initiatives. © 2024 Copyright held by the owner/author(s).

关键词： Hijra

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