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10th International Conference on Artificial Intelligence and Robotics, QICAR 2024

作者： Safari, Rahebeh Mojtahedi Rahmani, Amir Masoud Alizaeh, Sasan H. Department of Computer and Information Technology Engineering Qazvin Branch Islamic Azad University Qazvin Iran Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan Tehran Iran

ISBN: (纸本)9798350348873

At present, the prediction of user retweeting behavior plays a significant role in perceiving the underlying mechanism of information diffusion in the microblogging network. The problem of retweeting behavior prediction is usually considered as a classification task hence, the effort for the classification of the time-series data in the microblogging network has gained spacious attention. It is challenging to improve the classification accuracy of retweeting behavior prediction models, because the applied classifications still lack a tailored method. To address this, we present a retweeting behavior prediction model based on Dynamic Naïve Bayes classifier that is an appropriate classifier dealing with time-series data classification. In fact, we apply a time discretization approach and incorporate user individual, social and temporal features into our proposed prediction model to estimate accurately user retweeting behavior in the microblogging network over time. The real Twitter(X) microblogging dataset is used to evaluate the performance of the proposed model in the user retweeting prediction. The experimental results show that our proposed classifier due to its simple structure can avoid overfitting problem, and outperforms in compared to other baseline methods. ©2024 IEEE.

关键词： Classification (of information)

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Optimizing Battery Management Systems For Electric Vehicles: Current Trends And Future Directions 5

Optimizing Battery Management Systems For Electric Vehicles:...

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5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Prakash, V.S. Muthu, Annamalai Anandan, B. Velmurugan, V. Raja, T. Alex Stanley Purushothaman, V. Kristu Jayanti College Department of Computer Science Bengaluru India University of Technology and Applied Science Electrical Section Engineering Department Nizwa Oman Siddharth Institute of Engineering & Technology Department of Mechanical Engineering Andhrapradesh Puttur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Avadi Tamil Nadu Chennai India Bannari Amman Institute of Technology Department of Electrical and Electronics Engineering Sathyamangalam India Chennai Institute of Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350376685

The rapid global shift towards electric vehicles (EVs) marks a transformative era in transportation, driven by the imperative to reduce carbon emissions and reliance on fossil fuels. Central to the performance and longevity of EVs are Battery Management Systems (BMS), which optimize battery usage, enhance safety, and extend operational life. This comprehensive review explores current trends and future directions in BMS optimization, focusing on key technological advancements and their implications for electric mobility. Battery Management Systems (BMS) serve as critical components in electric vehicles, orchestrating the efficient operation of battery packs through real-time monitoring, state-of-charge (SoC) estimation, thermal management, and fault diagnosis. These systems not only ensure optimal performance but also safeguard against potential hazards, thereby enhancing vehicle reliability and user confidence. Current advancements in BMS technology emphasize enhanced accuracy in SoC estimation, leveraging sophisticated algorithms and sensor integration to provide precise information on battery charge levels. Coupled with innovative thermal management strategies, which include active cooling and heating systems, BMS can mitigate thermal stress and optimize battery performance across diverse environmental conditions. By synthesizing technological advancements, emerging trends, and potential challenges, it offers valuable insights for researchers, engineers, and policymakers aiming to advance the efficiency, reliability, and sustainability of electric mobility solutions worldwide. © 2024 IEEE.

关键词： State of charge

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Real-time multi-GPU-based 8KVR stitching and streaming on 5G MEC/Cloud environments

Real-time multi-GPU-based 8KVR stitching and streaming on 5G...

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作者： Lee, HeeKyung Um, Gi-Mun Lim, Seong Yong Seo, Jeongil Gwak, Moonsung Immersive Media Research Section Electronics and Telecommunications Research Institute Daejeon Korea Republic of Electrical Engineering and Computer Science Ulsan National Institute of Science and Technology Ulsan Korea Republic of

In this study, we propose a multi-GPU-based 8KVR stitching system that operates in real time on both local and cloud machine environments. The proposed system first obtains multiple 4 K video inputs, decodes them, and generates a stitched 8KVR video stream in real time. The generated 8KVR video stream can be downloaded and rendered omnidirectionally in player apps on smartphones, tablets, and head-mounted displays. To speed up processing, we adopt group-of-pictures-based distributed decoding/encoding and buffering with the NV12 format, along with multi-GPU-based parallel processing. Furthermore, we develop several algorithms such as equirectangular projection-based color correction, real-time CG overlay, and object motion-based seam estimation and correction, to improve the stitching quality. From experiments in both local and cloud machine environments, we confirm the feasibility of the proposed 8KVR stitching system with stitching speed of up to 83.7 fps for six-channel and 62.7 fps for eight-channel inputs. In addition, in an 8KVR live streaming test on the 5G MEC/cloud, the proposed system achieves stable performances with 8 K@30 fps in both indoor and outdoor environments, even during motion. 1225-6463/$ © 2021 ETRI

关键词： Graphics processing unit

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Bayesian regularization knack-based intelligent networks for thermo-physical analysis of 3D MHD nanofluidic flow model over an exponential stretching surface

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European Physical Journal Plus 2023年第1期138卷 2页

作者： Awan, Saeed Ehsan Awais, Muhammad Raja, Muhammad Asif Zahoor Rehman, Saeed ur Shu, Chi-Min Department of Electrical and Computer Engineering COMSATS University Islamabad Attock Campus Attock 43600 Pakistan Department of Mathematics COMSATS University Islamabad Attock Campus Attock 43600 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan

Artificial intelligence (AI) knacks are exploited broadly by the research community in the field of engineering and technology to enhance efficacy of the outputs for rapid development of business and society. Therefore, it looks promising to explore or investigate in the novel AI-based integrated numerical computing to study the solution dynamic of computational fluid mechanics problem of utmost significance. Boundary layer methodology is invoked for the mathematical modeling of fluidic system to study the heat and mass transport improvement of nanofluid with base water 3D-MHD flow model with an exponentially stretched surface involving three types of nanoparticles Fe₃O₄ (magnetite), Ag (silver) and C₁₄₀H₄₂O₂₀ (graphene oxide). The representative 3D PDEs for nanofluidic system are converted into equivalent nonlinear ODE-based system via suitable similarity transformation. The results of the three nanofluidic models are calculated by applying Adams numerical technique for influential outcomes of aggressing parameters including Hartmann number M, wall stretching ratio P, thermal radiation R_d and heat source/sink hs to observe the effecting profiles of temperature and velocity fields. The obtained numerical data are utilized for Bayesian regularization knack-based intelligent computing method to construct the networks for approximate solution dynamic of nanofluidic models. The worth and value of designed Bayesian regularization knack-based networks (BRKNs) is established by regression index measurements, error histogram studies and convergence curves with negligible level of mean square error (E-12 to E-10) for the exhaustive simulations. Graphical Abstract: [Figure not available: see fulltext.]. © 2023, The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature.

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Revolutionizing Recruitment Management: Optimizing Advanced Digital Solutions for Manpower Planning in Higher Education

Revolutionizing Recruitment Management: Optimizing Advanced ...

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IEEE Conference on Systems, Process & Control (ICSPC)

作者： Ahmad Mukafi Andrian Nor Kamaliah Khamis Ahgalya Subbiah Halimatuz Zuhriyah Safira Faizah Faculty of Information Sciences and Engineering Management and Science University Section 13 Shah Alam Selangor Department Informatics Engineering Faculty Engineering and Computer Science Jakarta Global University Depok Indonesia

ISBN: (数字)9798350391398

ISBN: (纸本)9798350391404

Effective manpower planning is crucial for any organization, including universities, as it directly influences performance, productivity, and overall success. Inefficient recruitment processes can lead to increased costs, higher turnover rates, and suboptimal utilization of human resources, negatively impacting the institution's ability to achieve its goals and maintain a competitive advantage. The objective of this study is to develop a comprehensive digital solution to streamline and enhance recruitment and manpower planning processes, replacing traditional manual methods. This paper presents the Recruitment and Manpower Planning System, an innovative web-based platform designed using Extreme Programming (XP) methodologies. The system integrates modern programming tools such as Visual Studio Code, Laragon, Laravel 9, and MySQL, and utilizes Unified Modelling Language (UML) for precise system design. A mixed-methods approach, incorporating quantitative data from structured questionnaires administered to 500 users, informed the system's design. Data analysis indicates a 40% reduction in recruitment time, a 35% increase in successful job placements, and a 90% user satisfaction rate. Rigorous testing phases ensured system accuracy and quality. This digital solution not only optimizes recruitment processes but also provides a robust prototype for future advancements in manpower planning systems.

关键词： Productivity Visualization Unified modeling language Prototypes Organizations Labor resources System analysis and design Programming profession Recruitment Testing

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Sign language mobile apps: a systematic review of current app evaluation progress and solution framework

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Evolving Systems 2024年第2期15卷 669-686页

作者： David, Dianes Alamoodi, A.H. Albahri, O.S. Garfan, Salem Albahri, A.S. Zaidan, B.B. Chen, Juliana Perak Malaysia Baghdad Iraq Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunrlin Douliou64002 Taiwan Discipline of Nutrition and Dietetics Susan Wakil School of Nursing and Midwifery Faculty of Medicine and Health The University of Sydney CamperdownNSW2006 Australia Department of Computer Science and Information Technology La Trobe University MelbourneVIC Australia Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Charles Perkins Centre The University of Sydney CamperdownNSW2006 Australia

Mobile apps for sign language are a fascinating area of research that merits a lot of attention. These apps are widely used due to their affordability and usability. Nevertheless, the quality of these apps needs to be evaluated if they are to have a significant influence. The outcomes of app quality assessment can also stimulate app development efforts and improvements to their functionality and accuracy. Therefore, to gain more in depth understanding, four academic databases (science Direct, IEEE, Association for Computing Machinery, and Web of science) were searched as part of a systematic literature review. The review highlighted that sign language apps require further development to support users in achieving the greatest possible usage and learning experience. We present a solution framework based on a quality assessment criterion for sign language mobile apps that could be adopted by academics and developers. Alternative identification, criteria, and development are the three primary aspects of the framework. The results demonstrate that the new assessment approach can establish a detailed set of criteria for sign language mobile app development. Future academics could gain a thorough understanding of mobile app development criteria from this study. The results are advantageous and open up a new field where researchers and developers could collaborate on sign language mobile app development. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Audition

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Development of an Artificial Intelligence Device Management System Using Over-the-Air Technology

Development of an Artificial Intelligence Device Management ...

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International Conference on Ubiquitous and Future Networks, ICUFN

作者： Jinhong Kim Yun Won Choi Jang Woon Baek Kwang-Ju Kim Dongkyun Kim Electronics and Telecommunications Research Institute (ETRI) AI Infrastructure Research Section School of Computer Science and Engineering Kungpook National University

ISBN: (数字)9798350385298

ISBN: (纸本)9798350385304

This paper describes the development of an artificial intelligence(AI) device management system that utilizes over-the-air(OTA) updates to efficiently manage AI devices and the services they provide. By employing wireless communication such as short-range wireless communications or mobile telecommunications, the developed system monitors and manages the status of AI devices and update the learning model operating on the devices. In this way, the developed system enhances the performance of services provided by AI devices and ensures their stable operation.

关键词： Performance evaluation Wireless networks Data models Software Telecommunications Software reliability Artificial intelligence

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AI-Enabled Predictive Maintenance for Industrial Equipment in the Era of IoT 9

AI-Enabled Predictive Maintenance for Industrial Equipment i...

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9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Subbiah, Muthu Raman Devi, Kabirdoss Dhanamalar, M. Shareef, Ashraf Mohammed Ai-Shaikhli, Taha Raad Nidamanuri, Sudheer University of Technology And Applied Sciences Mie Section Department of Engineering Muscat Oman School of Management Studies Vels Institute-of Science Technology And Advanced Studies Chennai Tamil Nadu Pallavaram600117 India Kristu Jayanti College Department of Computer Science Karnataka Bengaluru India College of Pharmacy National University of Science And Technology DhiQar Iraq AL-Nisour University College Department of Medical Laboratories Technology Baghdad Iraq Madanapalle Institute of Technology And Science Computer Science And Technology Andhra Pradesh Madanapalle517325 India

ISBN: (纸本)9798350365092

Modern digital technology breakthroughs include machine learning. It's used in medical, image processing, manufacturing, aviation, autonomics, and more. Our main goal is to find an automated system that can accurately rate production machines at any given moment. The critical energy meter characteristics needed to create power reports in automation system to solve production difficulties at defined intervals were also not captured. We apply machine learning to estimate manufacturing machine accuracy in this study. We employed supervised machine learning of binary decision tree using CART method and power report, obtained data using RS232 to RS485 convertor through Modbus communication protocol, to overcome these challenges. This study presents issue formulation, energy meter data analysis and retrieval, and ML approaches used to estimate production machine accuracy. After retrieving the parameters, we provide power reports for each machine and a graphical warning of deteriorating performance. © 2024 IEEE.

关键词： Internet of things

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TRISAT-R: FLIGHT EXPERIENCE IN MEO

TRISAT-R: FLIGHT EXPERIENCE IN MEO

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2024 Small Satellites Systems and Services Symposium, 4S 2024

作者： Gonzales, Lorenzo Benamar, Kenza Santin, Giovanni Danzeca, Salvatore Kramberger, Iztok Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor2000 Slovenia Noordwijk2200 AG Netherlands Noordwijk2200 AG Netherlands Section Leader BE-CEM-EPR CERN Esplanade des Particules 1 Geneva 231211 Switzerland

ISBN: (纸本)9781510688940

This paper highlights the technical achievements and presents the in-flight experience of one of the first successful 3U nanosatellite mission in medium earth orbit (MEO) in Europe, TRISAT-R. TRISAT-R is an institutional non-commercial nanosatellite mission primed by the University of Maribor under the contract with ESA and in cooperation with CERN and Slovenian company SkyLabs. The primary mission objective is measurement of ionizing radiation and characterization of the space environment, consolidating the environmental models by comparing the simulated high energy particles particle environment with the measured data in orbit. The radiation measurements are conducted with several scientific payloads to monitor the Single Event Effects and Total Ionizing Dose. The secondary mission objectives are several In-Orbit demonstrations to show new solutions for nanosatellite component miniaturization, testing new design concepts, and demonstrating new Radiation Hardened by Design mitigation techniques for protection of high-performance and high-density electronic components, and targeting the upcoming era of Artificial Intelligence in space applications. Additionally, the satellite was equipped with two highly miniaturized experimental COTS cameras capturing the black Sun effect, which is a consequence of pixel spillover due to Sun’s energy saturation. These cameras captured a view of the Earth from MEO orbit by the 3U nanosatellite. © 2025 The Authors.

关键词： Radiation hardening

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DAS benchmarking methodology based on FWZIC II and FDOSM II to support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12747-12774页

作者： Mahmoud, U.S. Albahri, A.S. AlSattar, H.A. Zaidan, A.A. Talal, M. Mohammed, R.T. Albahri, O.S. Zaidan, B.B. Alamoodi, A.H. Qahtan, Sarah Baghdad Iraq Baghdad Iraq Baghdad Iraq Department of Computing FSKIK Universiti Pendidikan Sultan Idris Tanjung Malim35900 Malaysia Faculty of Engineering and IT British University in Dubia Dubai United Arab Emirates Parit Raja Johor Batu Pahat86400 Malaysia Department of Computer Science Faculty of Science Komar University of Science and Technology Sulaymaniyah Iraq Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan College of Health and Medical Technology Middle Technical University Baghdad Iraq Department of Business Administration College of Administrative Science The University of Mashreq Baghdad Iraq

This study proposed a novel methodology of data acquisition systems (DASs) benchmarking based on fuzzy-weighted zero-inconsistency (FWZIC II) and fuzzy decision by opinion score method (FDOSM II), which are applied in an intuitionistic fuzzy set (IFS) context and account for hesitation when benchmarking DASs, to support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles. The proposed methodology comprises two consecutive phases. The first phase involves constructing a decision matrix based on the intersection of the DAS alternatives and criteria. The second phase (development phase) proposes the formulation of a novel FWZIC II to weight the criteria and the formulation of a novel FDOSM II to benchmark DASs. Fourteen DASs were benchmarked based on the 15 DAS criteria, which included seven sub-criteria for ‘comprehensive complexity assessment’ and eight sub-criteria for ‘design and implementation’, which had a significant effect on the DAS design when implemented by industrial communities. A systematic ranking and sensitivity analysis were conducted to demonstrate that the benchmarking results were subject to systematic ranking, as indicated by the high correlations across all described scenarios of changing criteria weight values. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Benchmarking

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