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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Rama, P. Pandiaraj, A. Angayarkanni, V. Prakash, Y. Jagadeesh, S. SRM Institute of Science and Technology Computing Technologies College of Engineering and Technology Faculty of Engineering and Technology SRM Nagar TN Kattankulathur603203 India SRM Institute of Science and Technology Computing Technologies College of Engineering and Technology SRM Nagar TN Kattankulathur603203 India

ISBN: (纸本)9798350370249

This paper introduces IR-GAN (Image Restoration Generative Adversarial Network), a groundbreaking tool accessible on GitHub, designed to elevate image quality and rejuvenate damaged or low-resolution photographs. Leveraging the power of generative facial priors, IR-GAN adeptly transforms aged images, effectively reducing blurriness and revitalizing historical snapshots with remarkable precision. At the heart of IR-GAN lies its pre-trained Generative Adversarial Network (GAN) model, meticulously crafted to intelligently fill in missing or damaged areas within images by discerning intricate patterns present in the dataset. This innovative approach enables IR-GAN to seamlessly replace distorted or blurred segments with visually coherent elements, preserving the authenticity and essence of the original photographs. Through the integration of advanced image processing techniques and state-of-the-art deep learning methodologies, IR-GAN emerges as a promising solution for digital restoration and preservation endeavours. Its ability to breathe new life into old photographs while maintaining their historical significance holds immense value for archivists, historians, and enthusiasts alike. Experimental results presented in this paper underscore IR-GAN's efficacy in the transformative process of old photographs into visually appealing images. The showcased capabilities of IR-GAN align with the burgeoning demand for sophisticated image enhancement tools within the realm of image processing, paving the way for future advancements in digital restoration and preservation technologies. © 2024 IEEE.

关键词： Generative adversarial networks

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Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2103-2127页

作者： Othman S.Al-Heety Zahriladha Zakaria Ahmed Abu-Khadrah Mahamod Ismail Sarmad Nozad Mahmood Mohammed Mudhafar Shakir Hussein Alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITS) traffic control vehicular communication kalman filtering smart city Internet of Things

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Multi-lingual news stack based ensemble classification for deep news feed analysis

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Neural computing and Applications 2025年 1-12页

作者： Sakthivel, Rakesh Kumar Nagasubramanian, Gayathri Sankayya, Muthuramalingam Kadry, Seifedine Rocha, Alvaro Karnataka Bengaluru India Department of Information Technology Thiagarajar College of Engineering Madurai India Faculty of Applied Computing and Technology Noroff University College Kristiansand Norway Alvaro Rocha ISEG University of Lisbon Lisbon Portugal

Analyzing and extracting effective words of news feeds are critical tasks. News making sources may feed their news articles in different manners based on their own perspective. In this situation, finding likelihood samples from the vast news feeds is an essential task. Moreover, acquiring optimal word deviations, news varieties, sentiment metrics, and multi-lingual analysis are major tasks of this proposed system. To achieve this massive news feed analysis task, the proposed system uses specially designed multi-classifier units and news stack manipulation procedures. The proposed system integrates different classifiers and dynamic news stacks to handle datasets of multi-lingual attributes. The results show that the proposed method performs with better accuracy rate than existing techniques. This gives 10 to 15% higher accuracy rate than existing works. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Data accuracy

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Broker-Less OPC UA PubSub Communication Model Performance Analysis 30

Broker-Less OPC UA PubSub Communication Model Performance An...

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30th IEEE International Conference on Telecommunications, ICT 2024

作者： Homay, Aydin Chrysoulas, Christos Watt, Tess Wollschlaege, Martin De Sousa, Mario Maglaras, Leandros Technische Universität Dresden Faculty of Computer Science Dresden Germany School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom University of Porto Faculty of Engineering Porto Portugal

ISBN: (纸本)9798350356694

The advent of Industrial Internet of Things (IIoT) has accelerated the adoption of OPC UA (Object Linking and Embedding for Process Control Unified Architecture) PubSub communication models, enabling efficient data exchange in industrial automation systems. This study delves into the performance analysis of a broker-less OPC UA PubSub communication model, a paradigm gaining prominence for its potential to streamline communication in distributed systems. Our methodology involves the establishment of a representative test environment, configuration of OPC UA PubSub components without an intermediary broker, and the design of diverse test scenarios. The results of this performance analysis not only reveal the inherent capabilities of the broker-less OPC UA PubSub communication model but also identify potential bottlenecks and areas for optimization. This research advances our understanding of broker-less OPC UA PubSub communication models, offering empirical evidence of their performance in diverse scenarios. © 2024 IEEE.

关键词： Electronic data interchange

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Novel Approach for Enhancing Mental Well-Being Through Machine Learning Techniques 5

Novel Approach for Enhancing Mental Well-Being Through Machi...

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5th International Conference on Advancements in computing, ICAC 2023

作者： Roshani, O.V.D.E. Ayuwardhana, H.M.K.J.J. Rodrigo, P.H.M.S. Hewageegana, R.U. Fernando, Harinda De Silva, Dilshan I. Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

Frequently, individuals undergo specific episodes of mental health challenges throughout their lifetime. But the COVID pandemic has triggered a surge in mental health disorders arising from isolation, monotonous routines, demanding workloads, financial disparities, and disruptions to daily schedules. Furthermore, the global pandemic has induced constant anxiety and stress. Beyond the pandemic, the competition and intense pressure of the modern world impact mental health. Access to advanced mental health solutions and the necessary familiarity remain limited for most of the population. Given the integration of technology into daily life, diverse remedies, including mobile and web applications, have emerged to tackle the escalating challenge of mental health disorders. This study proposes an accessible and cost-effective approach that employs machine learning to detect stress levels and discern user emotions from journal entries and facial expressions while integrating self-journaling, video recommendations, and visual content generation to stimulate positive emotions and relieve stress. © 2023 IEEE.

关键词： Cost effectiveness

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Information Flow and Laplacian Dynamics on Local Optima Networks 13

Information Flow and Laplacian Dynamics on Local Optima Netw...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Richter, Hendrik Thomson, Sarah L. Htwk Leipzig University of Applied Sciences Faculty of Engineering Leipzig Germany School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom

ISBN: (纸本)9798350308365

We propose a new way of looking at local optima networks (LONs). LONs represent fitness landscapes;the nodes are local optima, and the edges are search transitions between them. Many metrics computed on LONs have been proposed and shown to be linked to metaheuristic search difficulty. These have typically considered LONs as describing static structures. In contrast to this, Laplacian dynamics (LD) is an approach to consider the information flow across a network as a dynamical process. We adapt and apply LD to the context of LONs. As a testbed, we consider instances from the quadratic assignment problem (QAP) library. Metrics related to LD are proposed and these are compared with existing LON metrics. The results show that certain LD metrics are strong predictors of metaheuristic performance for iterated local search and tabu search. © 2024 IEEE.

关键词： Tabu search

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IoT Revolutionizing Healthcare: A Survey of Smart Healthcare System Architectures

IoT Revolutionizing Healthcare: A Survey of Smart Healthcare...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Delsi Robinsha, S. Amutha, B. Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Chengalpattu District Tamilnadu Kattankulathur603 203 India

ISBN: (纸本)9798350305708

The Internet of Things (IoT) has had a profound impact on the healthcare sector by paving the way for the creation of smart healthcare systems that improve patient monitoring, diagnosis, and individualized care. The purpose of this study is to provide a review of the state of the art in IoT-based healthcare system architectures. In this study, we take a look at the current state of the art of Internet of Things (IoT) technologies, protocols, and communication models used in healthcare settings. The survey digs into the roles and interconnections of key components and layers of IoT architecture, such as sensor nodes, gateways, cloud platforms, and data analytics, in a smart healthcare ecosystem. Furthermore, it investigates the potential for incorporating wearable devices, medical sensors, and other smart healthcare gadgets that enable real - time data gathering and transmission. In addition, the paper explores the dangers and vulnerabilities inherent in IoT - based healthcare systems, as well as the current solutions available for addressing these issues and safeguarding sensitive patient data. The challenges of interoperability and standardization are also explored in order to guarantee the smooth integration and communication of various healthcare equipment and systems. Using examples like remote patient monitoring, chronic illness management, fall detection, and elderly care, the survey emphasizes the beneficial effects of IoT on patient outcomes and healthcare efficiency. © 2023 IEEE.

关键词： Global System for Mobile Communication (GSM) Healthcare Industry Intelligent Healthcare Systems Internet of Things (IoT) Remote Patient Monitoring

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An Automated Real-Time Face Mask Detection System Using Transfer Learning with Faster-RCNN in the Era of the COVID-19 Pandemic

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Computers, Materials & Continua 2022年第5期71卷 4151-4166页

作者： Maha Farouk S.Sabir Irfan Mehmood Wafaa Adnan Alsaggaf Enas Fawai Khairullah Samar Alhuraiji Ahmed S.Alghamdi Ahmed A.Abd El-Latif Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversitySaudi Arabia Centre for Visual Computing Faculty of Engineering and InformaticsUniversity of BradfordBradfordU.K Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahP.O.Box 23713Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of Mathematics and Computer Science Faculty of ScienceMenoufia University32511Egypt

Today,due to the pandemic of COVID-19 the entire world is facing a serious health *** to the World Health Organization(WHO),people in public places should wear a face mask to control the rapid transmission of *** governmental bodies of different countries imposed that wearing a face mask is compulsory in public ***,it is very difficult to manually monitor people in overcrowded *** research focuses on providing a solution to enforce one of the important preventative measures of COVID-19 in public places,by presenting an automated system that automatically localizes masked and unmasked human faces within an image or video of an area which assist in this outbreak of *** paper demonstrates a transfer learning approach with the Faster-RCNN model to detect faces that are masked or *** proposed framework is built by fine-tuning the state-of-the-art deep learning model,Faster-RCNN,and has been validated on a publicly available dataset named Face Mask Dataset(FMD)and achieving the highest average precision(AP)of 81%and highest average Recall(AR)of 84%.This shows the strong robustness and capabilities of the Faster-RCNN model to detect individuals with masked and un-masked ***,this work applies to real-time and can be implemented in any public service area.

关键词： COIVD-19 deep learning faster-RCNN object detection transfer learning face mask

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Survey and Tutorial on Hybrid Human-Artificial Intelligence

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Tsinghua Science and Technology 2023年第3期28卷 486-499页

作者： Feifei Shi Fang Zhou Hong Liu Liming Chen Huansheng Ning School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Computer Science and Software Engineering East China Normal UniversityShanghai 200062China Faculty of Computing Ulster UniversityNewtownabbey BT370QBUK

The growing computing power,easy acquisition of large-scale data,and constantly improved algorithms have led to a new wave of artificial intelligence(AI)applications,which change the ways we live,manufacture,and do *** with this development,a rising concern is the relationship between AI and human intelligence,namely,whether AI systems may one day overtake,manipulate,or replace *** this paper,we introduce a novel concept named hybrid human-artificial intelligence(H-AI),which fuses human abilities and AI capabilities into a unified *** presents a challenging yet promising research direction that prompts secure and trusted AI innovations while keeping humans in the loop for effective *** scientifically define the concept of H-AI and propose an evolution road map for the development of AI toward *** then examine the key underpinning techniques of H-AI,such as user profile modeling,cognitive computing,and human-in-the-loop machine ***,we discuss H-AI’s potential applications in the area of smart homes,intelligent medicine,smart transportation,and smart ***,we conduct a critical analysis of current challenges and open gaps in H-AI,upon which we elaborate on future research issues and directions.

关键词： hybrid human-artificial intelligence(H-AI) Internet of Things(IoT) artificial intelligence(AI)

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AFuNet: an attention-based fusion network to classify texts in a resource-constrained language

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Neural computing and Applications 2025年第9期37卷 6725-6748页

作者： Hossain, Md. Rajib Hoque, Mohammed Moshiul Dewan, M. Ali Akber Hoque, Enamul Siddique, Nazmul Department of Computer Science & Engineering Chittagong University of Engineering & Technology Chittagong4349 Bangladesh School of Computing and Information Systems Faculty of Science and Technology Athabasca University AthabascaABT9S 3A3 Canada School of Information Technology York University TorontoONM3J 1P3 Canada School of Computing Engineering and Intelligent Systems Ulster University Coleraine United Kingdom

In the era of widespread Internet use and extensive social media interaction, the digital realm is accumulating vast amounts of unstructured text data. This unstructured data often contain undesirable information, necessitating time-consuming manual classification efforts. An intelligent text classification system capable of automatically categorizing digitized texts based on semantic meaning is crucial. However, this task is particularly challenging for low-resource languages like Bengali due to a shortage of annotated corpora, issues with out-of-vocabulary words, lack of domain-specific hyperparameter tuning, limited ability to extract generalized text features, and class imbalances within the corpus. AFuNet: an attention-based fusion network to classify texts in a resource-constrained language. AFuNet undergoes a comprehensive four-phase experimental process, including baseline model evaluation and hyperparameter tuning, late fusion and model selection, attention-based early fusion and model identification, and an ablation study with impact analysis. Fine-tuned based on five Bengali text classification corpora, AFuNet achieves impressive accuracies: 96.60 ± 0.2 (BTCC11), 85.37 ± 0.2 (OSBC), 97.35 ± 0.2 (BARD), 93.74 ± 0.2 (IndicNLP), and 96.51 ± 0.2 (ProthomAlo). In comparison with previous state-of-the-art models on these corpora, AFuNet demonstrates significant accuracy improvements ranging from 0.54% to 4.49%, showcasing its effectiveness in advancing text classification capabilities for the Bengali language. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Semantics

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