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Proceedings of the 3rd International Conference on Computing Advancements

作者： Sumit Kumar Kar Fariya Sultana Prity Nafiz Fahad Mohammad Mahmudul Hasan Md Kishor Morol Md Abdullah Al Jubair Department of Electrical and Computer Engineering North South University Dhaka Bangladesh Department of Computer Science American International University-Bangladesh Dhaka Bangladesh Faculty of Information Science and Technology Multimedia University Melaka Malaysia Department of Computing and Information Science Cornell University New York USA

ISBN: (纸本)9798400713828

This paper describes an innovative mobile phone application, named Rokkha that allows users to send location to predefined contacts by SMS to improve personal safety without internet connectivity. It discusses the development of the application, highlighting its offline functionality, intuitive interface, and the potential implications for emergency response systems. The literature review reveals the fact that in many of the existing emergency applications, connectivity with data is essential. Rokkha addresses this gap by providing a reliable alternative for location sharing during emergencies, particularly in areas with limited or no internet access. This paper aims to cover the designing considerations, implementation challenges and greater impact of using Rokkha in terms of reduced essential response time and assistance in crisis.

关键词： Disaster Preparedness

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An improved genetic algorithm with variable neighbourhood search for flexible job-shop scheduling problem

An improved genetic algorithm with variable neighbourhood se...

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第43届中国控制会议

作者： Zerui Jia Chengyong Si Jianqiang Shen Lei Wang School of Optica-Electrical and Computer Engineering University of Shanghai for Science and Technology Sino-German College University of Shanghai for Science and Technology College of Electronics and Information Engineering Tongji University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The Flexible Job Shop Scheduling Problem(FJSP), a classical NP-hard problem, requires the solution of two aspects of the complex problem, the first is to assign each operation to an available machine, and the second is to sequence each *** this paper, we propose an improved genetic algorithm with variable neighbourhood search(IGA-VNS), which improves the stability of the algorithm by using an improved elite pool strategy and a hybrid selection strategy, and the variable neighbourhood search algorithm(VNS), it improves the local search ability of the algorithm and makes the search process more *** proved the effectiveness of the algorithm.

关键词： Flexible Job Shop Scheduling Problem Genetic algorithm Improved operator Variable neighbourhood search

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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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Dual-Stage Interleaved On-board Charger for Electric Vehicle using Snow Geese Algorithm 4

Dual-Stage Interleaved On-board Charger for Electric Vehicle...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Chandrashekhar, A. Mallikarjuna, B. Thiyagesan, M. Umasankar, L. Ezhil, G. Devi, Rukmani Icfai Foundation for Higher Education Faculty of Science and Technology Department of Mechanical Engineering Telangana Hyderabad501203 India Rns Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru560098 India R.M.K Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai601206 India S. A. Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai600077 India Bannari Amman Institute of Technology Department of English Tamil Nadu Sathyamangalam638401 India Saveetha College of Liberal Arts and Sciences Simats Deemed to Be University Department of Computer Science Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331523923

The growing demand for electric vehicles (EVs) has highlighted the need for efficient and reliable on-board chargers (OBCs) to reduce charging time and enhance battery life. Nevertheless, there are some issues in classic OBC designs: harmonic distortion may become too large, electromagnetic interference increases, and thermal management is not proper;all of which directly affects other elements of the system. As an optimization approach to enhance the performance of the dual-stage interleaved on-board charger (OBC) for electric vehicles (EVs), this work introduces the Snow Geese Algorithm (SGA). The objective of the proposed method is to enhance charging efficiency and minimize cost. The proposed SGA is used to optimize the dual-stage interleaved converter, focusing on reliable performance and effective operation within EV charging systems. The suggested approach is then put into practice on the MATLAB platform and contrasted with a number of current techniques, including Artificial Bee Colony (ABC), Simulated Annealing (SA), Multi-objective Genetic Algorithm (MOGA), and Particle Swarm Optimization (PSO). The proposed SGO method for dual-stage interleaved EV chargers achieves a cost of 1,050.80 and an efficiency of 97.2 %, demonstrating its effectiveness in reducing expenses while maximizing optimization performance in charging systems. © 2025 IEEE.

关键词： Simulated annealing

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Towards Content-Optimized Selection of Video Spatiotemporal Resolution for HTTP Adaptive Video Streaming

Towards Content-Optimized Selection of Video Spatiotemporal ...

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International Symposium on Electronics in Marine (ELMAR)

作者： Renato Kuna Jelena Šuljug Snježana Rimac-Drlje Faculty of Electrical Engineering Computer Sciences and Information Technology Osijek J. J. Strossmayer University of Osijek Osijek

ISBN: (数字)9798350375428

ISBN: (纸本)9798350375435

In adaptive video streaming systems, selecting optimal spatial and temporal resolutions for a given bitrate is crucial when encoding various video representations on the server side. Previous research has primarily focused on adjusting spatial resolution, leaving optimization in the time-space domain as an open research question. The research aims to identify the optimal spatiotemporal resolution for a given bitrate, contingent on the complexity of the video sequence. Given the extensive requirements of such research, this paper presents preliminary findings based on five sequences of differing complexity. For low-complexity sequences, the optimal approach is to first reduce the temporal resolution from 120 fps to 25 fps, followed by a reduction in spatial resolution. Conversely, for sequences with medium and high complexity, it is preferable to decrease the spatial resolution first and then the temporal resolution. The appropriate bitrates for these resolution adjustments are also influenced by the complexity of the video signal. The encoded sequences, along with their objective and subjective quality evaluations will serve as a foundation for future AI-based modeling efforts.

关键词： Adaptive systems Bit rate Video sequences Streaming media Complexity theory Quality assessment Spatiotemporal phenomena Spatial resolution Signal resolution Optimization

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Efficient Road Status Monitoring in Vehicular Ad-Hoc Networks: An Optimization Framework

Efficient Road Status Monitoring in Vehicular Ad-Hoc Network...

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information technology (ACIT)

作者： Ghassan Samara Hussain Mohammed Turki Mahmoud Odeh Anas Al-Oraiqat Mohammad Aljaidi Raed Alazaidah Mohammad Rasmi Al-Mousa Ahmed BaniMustafa Mohammad Kanan Department of Computer Science Faculty of IT Zarqa University Zarqa Jordan Faculty of Information Technology Zarqa University Faculty of Information Technology Zarqa University Zarqa Jordan Computer Information Science Dept. Higher Colleges of Technology Abu Dhabi UAE Department of Industrial Engineering University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

The number of cars on the road in the world is currently increasing. With the widespread usage of vehicles, a slew of issues inevitably arises. The damage of the road can be annoying to the drivers, and congestion in traffic can waste both fuel and time. It's worth noting that one of the primary causes of car damage and aging is the state of the road surface. Driving comfort and vehicle controllability can be harmed by poor road conditions. As a result, the system of monitoring road status is crucial to reducing congestion in traffic, reducing accident rates, and protecting cars from hazardous road conditions. This paper proposes using a framework based on cloud-fog network architecture, The fog computing network architecture is a dispersed network that may process data at the fog layer to minimize cloud computing's computational load. In addition, using small and large threshold values ( ), Main Authority (MA) deals with the major conditions, and the Sub Authority (SA) deals with the minor conditions.

关键词： Cloud computing Roads Vehicular ad hoc networks Network architecture Throughput Delays Servers Automobiles Monitoring Edge computing

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Diagnosing Diabetes Disease Based on Machine Learning Techniques 1

Diagnosing Diabetes Disease Based on Machine Learning Techni...

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1st International Conference on Logistics, ICL 2024

作者： Mostafa, Salama A. Al-Dayyeni, Wisam Subhi Alsaeedi, Mokhalad Abdulameer Kadhim Hassan, Mustafa Hamid Jaber, Mustafa Musa Farooq, Umar Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor86400 Malaysia School of Information Technologies and Engineering ADA University BakuAZ1008 Azerbaijan Bilad Alrafidain University College Department of Computer Eng. Tech. Ba'aqubah Diyala32001 Iraq College of Information Technology Imam Ja'afar Al-Sadiq University Department of Computer Technical Engineering Al-Muthanna66002 Iraq Al-Farahidi University Department of Medical Instruments Engineering Techniques Baghdad10021 Iraq School of Information Technology UNITAR International University Kelana Jaya Petaling JayaSelangor Petaling Jaya47301 Malaysia

ISBN: (纸本)9798331518844

Machine learning has been popular in medicine for offering methods and assessing disease data. Gradually, machine learning algorithms are becoming critical in attaining early disease diagnosis. Standard datasets of different types of diseases have been utilized in medical research and applications, including liver disease, diabetes, chronic kidney disease, heart disease, breast cancer, brain tumors, and many more. This research reviewed numerous machine learning algorithms for diabetes illness prediction. Subsequently, four machine learning classification algorithms of k-Nearest Neighbor (k-NN), Decision Tree (DT), Random Forest (RF), and XgBoost (XB) are selected to find the best model that performs the diabetes diagnosis. The Pima Indians Diabetes Database (PIDD) dataset is used for testing the models, which includes 768 instances and 10 features, and the class has labels of 0 that indicate negative diabetes or 1 that indicates positive diabetes. Precision, accuracy, and recall criteria are used to evaluate the performance of the algorithms. The experimental results show that the XB is the most suitable algorithm for building a diabetes diagnostic model. The XB model has the highest accuracy of 83.72% in the data split of 70% training and 30% testing. It has achieved an average accuracy of 81.20% as compared with the k-NN (74.02%), DT (77.71%), and RF (77.16%). © 2024 IEEE.

关键词： Adversarial machine learning

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Effects of Torso Inhomogeneities on Spontaneous PVC Localization in Potential and Dipole-Based Methods 14

Effects of Torso Inhomogeneities on Spontaneous PVC Localiza...

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14th International Conference on Measurement, MEASUREMENT 2023

作者： Rasoolzadeh, Nika Ondrusova, Beata Dogrusoz, Yesim Serinagaoglu Svehlikov, Jana Middle East Technical University Institute of Applied Mathematics Ankara Turkey Middle East Technical University Electrical-Electronics Engineering Dept Ankara Turkey Slovak Academy of Sciences Institute of Measurement Science Bratislava Slovakia Stu Faculty of Electrical Engineering and Information Technology Bratislava Slovakia

ISBN: (纸本)9788097262976

The use of electrocardiographic imaging for the localization of the undesired premature ventricular contraction needs a torso volume conductor definition. This study aims to investigate the specific effect of lung and blood cavity inhomogeneities on the performance of inverse localization. Two source models were assumed for the inverse solution applied to clinical data;potential on the closed epicardial-endocardial surface and a single dipole. The results showed that the potential-based solution performed better if the presence of at least blood cavities was assumed, while the dipole-based solution was not significantly influenced by the presence of inhomogeneities. The importance of the inhomogeneities in the torso model for the inverse solution also depends on the used model of the equivalent heart generator. © 2023 Institute of Measurement science, Slovak Academy o.

关键词： Electrocardiographic Imaging (ECGI) Premature Ventricular Contraction (PVC) Torso Inhomogeneities

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Modeling Intra- and Inter-Modal Correlations for Incomplete Multi-Modal 3D Shape Clustering

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IEEE Transactions on Multimedia 2025年

作者： Qin, Tianyi Peng, Bo Lei, Jianjun Yao, Yuxuan Huang, Qingming Tianjin University School of Electrical and Information Engineering Tianjin300072 China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing101408 China

The investigation for incomplete multi-modal 3D shape clustering is evolving as a promising task for the field of recognizing massive unlabeled 3D shapes. As two widely adopted 3D shape modalities, point clouds and multiple views not only exhibit rich intra-modal correlations but also encompass complementary structures and appearances of 3D shapes. By effectively modeling the intra-modal and inter-modal correlations, this paper proposes a novel incomplete multi-modal 3D shape clustering method to reveal the underlying clustering associations from incomplete multi-modal 3D shapes. In detail, a similarity-transferred feature prediction module is presented to recover the features of missing instances within one modality with the assistance of similarity exploring from another modality. Then, an intra-to-inter progressive feature fusion module is designed to mine the correlations within the modality as well as between different modalities, thereby obtaining comprehensive 3D shape features for clustering. Extensive experiments on two public 3D shape datasets have demonstrated that the proposed method has achieved promising clustering results under different missing rates. © 1999-2012 IEEE.

关键词： 3D modeling

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Unit Commitment and Load Dispatch Problems Considering Inertial Response of Dispatchable Generators

Unit Commitment and Load Dispatch Problems Considering Inert...

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2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Shigenobu, Ryuto Ito, Yuhi Ito, Masakazu Takano, Hirotaka Orihara, Dai Goda, Tadahiro Taoka, Hisao University of Fukui Faculty of Engineering Dept. of Electrical Electronic and Computer Engineering Fukui Japan Gifu University Faculty of Engineering Dept. of Electrical Electronic and Computer Engineering Gifu Japan Fukushima Renewable Energy Institute Aist National Institute of Advanced Industrial Science and Technology Fukushima Japan

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

The growth in penetration of renewable energy sources leads to reduction in the number of grid-tied dis-patchable synchronous generators. Since the contributions of non-dispatchable, renewable energy-based generators to both grid inertia and grid frequency controllability are significantly small, it becomes important to secure sufficient operational margins in the operation scheduling phase. This paper presents a framework that integrates constraints for the inertial response and the primary frequency control to the unit commitment and economic load dispatch (UC-ELD) problem. The authors' proposal contributes cooperative operations of dispatchable and non-dispatchable generators in the levels of inertial and primary responses although the UC-ELD is a framework for operations in longer period. Through numerical simulations and discussion on their results, the validity of the authors' proposal is verified. © 2022 IEEE.

关键词： Renewable energy resources

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