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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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Autonomous Deployment of a Robust computer Vision Framework for Real-Time Car Counting on Paraguayan Highways 10

Autonomous Deployment of a Robust Computer Vision Framework ...

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10th International Conference on Applied System Innovation, ICASI 2024

作者： Frachi, Maximiliano Pfannl Ruan, Shanq-Jang Chen, Chih-Lun Department of Information Engineering Taiwan-Paraguay Polytechnic University Department of Electronic and Computer Engineering National Taiwan University of Science and Technology No. 43 Section 4 Keelung Rd Da an District Taipei City 106 Taipei Taiwan

ISBN: (纸本)9798350394924

Our research utilizes a custom YOLOv8 model trained with transfer learning on a representative augmented dataset tailored to accurately represent Paraguay's traffic situations. We employ multiple Gaussian Mixture Models (GMMs) for foreground object detection, incorporating motion and spatial cues. Innovative shadow removal techniques ensure robust mask extraction from highway video frames. Finally, virtual lines help determine the direction and number of cars crossing. © 2024 IEEE.

关键词： computer vision

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Landscape of sign language research based on smartphone apps: coherent literature analysis, motivations, open challenges, recommendations and future directions for app assessment

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Universal Access in the Information Society 2024年第2期23卷 687-702页

作者： David, Dianes Alamoodi, A.H. Albahri, O.S. Zaidan, B.B. Zaidan, A.A. Garfan, Salem Ismail, Amelia Ritahani Albahri, A.S. Alsinglawi, Belal Malik, R.Q. Perak Malaysia Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Faculty of Engineering and IT The British University in Dubai Dubai United Arab Emirates International Islamic University Malaysia Kuala Lumpur Malaysia Baghdad Iraq School of Computer Data and Mathematical Sciences Western Sydney University Sydney Australia Medical Intrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq Computer Techniques Engineering Department Mazaya University College Thi-Qar Nassiriya Iraq

Numerous nations have prioritised the inclusion of citizens with disabilities, such as hearing loss, in all aspects of social life. Sign language is used by this population, yet they still have trouble communicating with others. Many sign language apps are being created to help bridge the communication gap as a result of technology advances enabled by the widespread use of smartphones. These apps are widely used because they are accessible and inexpensive. The services and capabilities they offer and the quality of their content, however, differ greatly. Evaluation of the quality of the content provided by these applications is necessary if they are to have any kind of real effect. A thorough evaluation like this will inspire developers to work hard on new apps, which will lead to improved software development and experience overall. This research used a systematic literature review (SLR) method, which is recognised in gaining a broad understanding of the study whilst offering additional information for future investigations. SLR was adopted in this research for smartphone-based sign language apps to understand the area and main discussion aspects utilised in the assessment. These studies were reviewed on the basis of related work analysis, main issues, discussions and methodological aspects. Results revealed that the evaluation of sign language mobile apps is scarce. Thus, we proposed a future direction for the quality assessment of these apps. The findings will benefit normal-hearing and hearing-impaired users and open up a new area where researchers and developers could work together on sign language mobile apps. The results will help hearing and non-hearing users and will pave the way for future collaboration between academicians and app developers in the field of sign language technology. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Smartphones

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A Review of Mooring Monitoring Methods for Anomalies Detection in Thin Mooring Lines: Challenges and Future Realms 4

A Review of Mooring Monitoring Methods for Anomalies Detecti...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Hashmani, Manzoor Ahmed Khatri, Tarwan Kumar Koh, Tieng Wei Rahim, Lukman Ab. Taib, Hasmi Abdullah, Nasir Department of Computer and Information Sciences Perak Seri Iskandar Malaysia Perak Malaysia Floating Production Facilities Project Delivery & Technology Division Civil and Structural Section Engineering Department Kuala Lumpur Malaysia Metocean Engineering Kuala Limpur Malaysia

ISBN: (纸本)9798350395914

Mooring systems originate in the form of polyester ropes, chains, and steel wire that are employed for the purpose of offshore station keeping and have been shaped in bulk based on the defined criteria of the mooring design principles. But, still, there have been many incidents, including financial losses, loss of human life, injuries of crew members during onboard mooring operations, catastrophic failure, and more due to the failure in mooring lines during offshore mooring operations, which reveals that there is a strong need to improve the reliability of the mooring systems and a way for the betterment of mooring integrity management, inspection, and monitoring of mooring systems that may aid in bettering the reliability. In this paper, an extensive review is conducted to examine conventional mooring monitoring methods with challenges and future directions for anomaly detection in mooring lines. Additionally, this research study also focuses on furnishing insights into the strengths, limitations, and effectiveness of conventional mooring monitoring techniques that have been employed to detect the failure in mooring lines and dig into the new research advancement and emerging trends that extend the potential solution for the bettering of mooring monitoring in the detection of anomalies in mooring lines by assuring the reliability, safety, scalability, and optimality in the performance of marine structures and offshore mooring operations. © 2024 IEEE.

关键词： Mooring

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Measuring the social influence for retweet behavior prediction in microblogging network 11

Measuring the social influence for retweet behavior predicti...

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11th International Symposium on Telecommunication, IST 2024

作者： Safari, Rahebeh Mojtahedi Rahmani, Amir Masoud Alizaeh, Sasan H. Islamic Azad University Lahijan Branch Department of Computer Engineering Lahijan Iran National Yunlin University of Science and Technology Future Technology Research Center 123 University Road Section3 Douliou Yunlin64002 Taiwan Faculty of Information Technology Tehran Iran

ISBN: (纸本)9798350356250

Nowadays, retweeting behavior is considered a substantial behavior to analyze information diffusion in the microblogging network. To understand the underlying mechanism of information diffusion and analyze the evolution of the diffusion corresponding to a given original microblog, user retweeting behavior prediction has recently gained considerable attention. In this paper firstly, we introduce the most influential factors which affect user retweeting behavior and propose an effective measurement based on the random walk model to measure the social influence. Secondly, by incorporating our defined influential factors into a logistic regression classifier model, we predict the future activated user set concerning the diffusion of a given original microblog at the next time point. Unlike other comparative models, our prediction model can illustrate the evolution of diffusion and predict the retweeting behavior of all potential users through the diffusion of any original microblog in the microblogging network. Finally, based on the real Twitter microblogging dataset, the experimental results show by the contribution of our defined influential factors and presenting an effective measure of the social influence factor, we can obtain more accurate predictions in comparison to other baseline methods. © 2024 IEEE.

关键词： Prediction models

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Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks

arXiv

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arXiv 2025年

作者： Orfanoudakis, Stavros Palensky, Peter Vergara, Pedro P. Section Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands

Maintaining grid stability amid widespread electric vehicle (EV) adoption is vital for sustainable transportation. Traditional optimization methods and Reinforcement Learning (RL) approaches often struggle with the high dimensionality and dynamic nature of real-time EV charging, leading to sub-optimal solutions. To address these challenges, this study demonstrates that combining Large Language Models (LLMs), for sequence modeling, with Graph Neural Networks (GNNs), for relational information extraction, not only outperforms conventional EV smart charging methods, but also paves the way for entirely new research directions and innovative solutions. © 2025, CC BY.

关键词： Charging stations

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IT-Security Risk Based Approach for Secure Operation of Distributed Data Platforms in Supply Chains

IT-Security Risk Based Approach for Secure Operation of Dist...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Voß, Marvin Kallisch, Jonas Runge, Maxim Theus, Tobias Niemann, Karl-Heinz Wunck, Christoph Faculty I - Electrical Engineering and Information Technology University of Applied Sciences and Arts Hannover Germany Department of Engineering Section Electrical Engineering and Computer Science University of Applied Sciences Leer Emden Germany Faculty of Mathematics Informatics and Statistics Ludwig Maximilian University Munich Germany

ISBN: (纸本)9798350386097

This paper presents the development of a secure data platform designed to enhance operational efficiency and to facilitate cross-company collaboration within the manufacturing supply chain. The platform is designed to ease secure information exchange while maintaining the sovereignty of each participant, leveraging standardized security features and advanced technologies such as federated learning. Security measures are based on a comprehensive risk analysis, which methodically identifies, assesses, and mitigates potential threats. Moreover, federated learning models that are not transparent are utilized. This allows data owners to maintain control over sensitive information within the consortium. The described approach markedly enhances both security and operational collaboration across the industry, representing a crucial stride towards more integrated and efficient supply chain management in manufacturing. © 2024 IEEE.

关键词： Risk analysis

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Novel Design of Grey Wolf Optimization Heuristics for High Resolution Direction of Arrival Estimation in Acoustic Plane Waves

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Wireless Personal Communications 2023年第4期128卷 2507-2529页

作者： Ahmed, Nauman Wang, Huigang Raja, Muhammad Asif Zahoor Ali, Wasiq Kashif, Muhammad Zaman, Fawad School of Marine Science and Technology Northwestern Polytechnical University Xi’an China Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan COMSATS University Islamabad Attock Campus Attock Pakistan Department of Electrical and Computer Engineering COMSATS University Islamabad Islamabad Pakistan

High resolution direction of arrival estimation for closely spaced target in low signal to noise ration (SNR) is an active research area in underwater acoustic and SONAR signal processing The resolution performance of classical/traditional subspace based algorithms including MUSIC and ESPRIT procedures degraded under sever scenarios of low signal to noise ratio (SNR), less number of samples/snapshots and short distant targets. In this work, optimization courage of swarming intelligence of grey wolf optimization (GWO) is carried out for viable DOA estimation in the challenging instances of worst underwater scenarios using a uniform linear array (ULA). The high resolution DOA for short distant emitters is achieved using less number of samples vitally with GWO by inspecting the global minima of the highly nonlinear objective model of ULA having multi local minimas. The performance is analyzed for different number of targets employing estimation accuracy, resolution certainty, variability analysis, frequency distribution of RMSE, robustness against different SNR of additive-white Gaussian measurement noise and comparative studies with MUSIC and Particle Swarm Optimization PSO with the validation strength of Cramer Rao bound reveals the valuation of the scheme. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Direction of arrival

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Green Leaf Disease Detection Using Raspberry Pi and Random Forest Machine Learning Algorithm: An Automated Approach for Precision Agriculture 10

Green Leaf Disease Detection Using Raspberry Pi and Random F...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Ranganathan, Chitra Sabapathy Basha, Amjath Ali Jakul Vijayalakshmi, A. Mohankumar, N. Sujatha, S. Sasikala, C. Mphasis Corporation Tamil Nadu Chennai India University of Technology and Applied Sciences Computer Engineering Electrical and Electronic Section Department of Engineering Ibra Oman Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Maharashtra Nagpur India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India Sri Sai Ranganathan Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350363104

Farm production and food security are affected by green leaf diseases. Modern disease detection technologies may discover plant health issues early. This work uses Raspberry Pi, a cheap and flexible single-board computer, along the advanced Random Forest machine learning technique to identify a green leaf disease. To identify crop diseases, the study uses automated, non-invasive technologies. From labeled images of good and sickly leaves, the algorithm extracts color histograms and texture, and form. It feeds a Random Forest classifier these properties for classifying data with high dimensions. Several green leaf diseased plant species were examined. This method detected plant health concerns with high precision. Movement and low cost make the Raspberry Pi ideal for remote and resource-limited agriculture, increasing farming accuracy. Helping farmers and users identify and develop green leaf diseases improves efficient farming. This methodology has the potential to improve crop management, optimize pesticide usage, and increase agricultural productivity. These results might contribute to the development of advanced automatic disease detection techniques to address green leaf diseases in modern agriculture. © 2024 IEEE.

关键词： computer Vision Green Leaf Plant Disease Detection Precision Agriculture raspberry pi

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Network Performance Analysis Of SCTP Protocol In Multihoming Transmission Through 5G Network

Network Performance Analysis Of SCTP Protocol In Multihoming...

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Visualization, Informatics and technology Conference (IVIT), International

作者： Shahidatul Arfah Baharudin Nurul Iman Muhammad Taufik Sri Banu Munisamy Adidah Lajis Computer Engineering Technology Section Universiti Kuala Lumpur MIIT Kuala Lumpur Malaysia

ISBN: (数字)9798350354447

ISBN: (纸本)9798350354454

The research presents that the Stream Control Transmission Protocol (SCTP) provides a very interesting alternative to classical TCP and UDP, especially in multihoming settings. We therefore specifically sought to test SCTP's performance in multihoming scenarios within 5G networks and compare its reliability to TCP and UDP under various Network Address Translation (NAT) settings through complete simulations. We took care to focus on the important performance metrics of throughput, latency, packet loss, and connection stability. The ability of multihoming with SCTP, where a single SCTP endpoint can support several IP addresses, was also tested. In the context that devices will be able to have more than one network interface, this feature is welcomed in 5G networks. An empirical investigation revealed that in NAT settings, while TCP and UDP see higher packet loss and more delay, SCTP maintains a more reliable connection. The as much as needed ultra-reliable and low-latency communications transport protocol for 5G must be very stable. For example, applications such as online gaming, video conferencing, and major IoT operations will be relying on this new network. This paper has specifically emphasized the potential that SCTP's multihoming feature and improved performance metrics hold for 5G networks. This means that SCTP should be recommended to increase network stability and enhance performance, based on the results presented here that have indicated its great potential. Further research will be done on enhancing SCTP for specific 5G use cases under different deployment scenarios and investigating its integration with promising new technologies like edge computing and network slicing.

关键词： TCP Transport protocols Visualization 5G mobile communication Packet loss Stability analysis Reliability Thermal stability Network address translation Videoconferences

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