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2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Shiny, X.S. Asha Ravikumar, D. Chinnasamy, A. Hemavathi, S. Department of Computer Science and Engineering Telangana Hyderabad India Kings Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Chennai India Sri Sairam Engineering College Department of Computer Science Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665456302

Regular cities can be transformed into intelligent structures by leveraging information and communication technologies. Innovative city development could be significantly impacted by the Internet of Things paradigm, commonly called cloud computing. All urban locations have a lot of traffic. In this study, Internet-of- Things (IoT) based system is proposed for health care services to organize and to establish the traffic signaling and pick up a route under which road congestion can be administrated. Vehicle accident contraventions are identified by the traffic officers using an online service that is hierarchically carefully monitored or constrained. However, the suggested approach is generic and may be utilized in any major metropolis without losing its generality. Traffic lights linked to cameras in metropolitan areas can be upgraded by connecting to IoT. During a pandemic, this approach is precious. The police can easily regulate traffic from their homes using their cell phones and identify defaulters. The suggested technique aids in the separation of ambulance and rescue engines from ordinary traffic. © 2023 IEEE.

关键词： Internet of things

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Exploring Advancements in 6G Wireless Networks for the Future of High-Speed Connectivity 2

Exploring Advancements in 6G Wireless Networks for the Futur...

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2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Suresh, J. Kumari, V Sheeja Pillai, N. Muthuvairavan Jayarin, P. Jesu David, D. Beulah Care College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Thandalam Tamil Nadu Chennai India R.M.D Engineering College Department of Computer Science and Business Systems Tamil Nadu India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Information Technology ThandalamTamil Nadu Chennai India

ISBN: (纸本)9798350364699

High-speed connectivity technologies that aim to be faster and more secure have been explored so that there will be a change of the very nature of wireless communication. This article presents advances concerning the high-speed connection component of the sixth-generation wireless networks, which is simply denoted as 6G. Different performance parameters of 6G are compared with 4G (LTE) and 5G (5G) through multiplicity of research analyses done across disciplines. Our findings suggested that 6G networks are incredibly dynamic and will change how the internet is used. These SixG networks are due to accompany massive data transmission rates of 100 Gbps, five times higher than 5G's 20 Gbps. Latency also approaches same level as 6G where on average 1 millisecond is noticed compared to 5G's 10 and 4G's 50. Server speed and its response time in milliseconds will expose room for a number of real-time applications from only augmented reality imaging to the world of driverless automobiles and interactive games. Our study outlines the major consequences of the coming health shift. 4G allowed only for slow/limited improvements in healthcare whereas the 5G made telemedicine possible. On the other hand, 6G reportedly offers "precision remote surgery", allowing surgeons to be located remotely of a patient while still performing a high precision surgery. Attitude of people becomes completely unaware when they are briefed about concepts of latest generation known as 6G. Before studying about 6G, the number of those are eagerly delighted are 20%, having no idea on how it will be is 50%, while the other 30% are skeptics. Meanwhile, once people are better cognizant of 6G, fanatics raise up from 60 percent and sceptics drop till 10 percent. The significant shift is a reflection of 6G technology in the stakeholders' mind. © 2024 IEEE.

关键词： 5G mobile communication systems

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Scanning the Issue - May 2025

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IEEE Transactions on Intelligent Transportation systems 2025年第5期26卷 5627-5648页

作者： Simona Sacone Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genova Genova Italy

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Challenges in Cyber Physical Social systems and Internet of Things 5

Challenges in Cyber Physical Social Systems and Internet of ...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Revathi, S. Raja, J. Mohanraj, M. Malathi, K. Mallala, Balasubbareddy Vidhya, R.G. B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Sri Eshwar college of engineering Department of Computer Science and Business Systems Coimbatore India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Hkbk College of Engineering Department of Ece Bangalore India

ISBN: (纸本)9798331504403

This research analyses the complex dynamics of Cyber-Physical-Social systems (CPSS), encompassing cyber-physical systems, cybersecurity, the Internet of Things (IoT), and social media. By exploring the interactions among these elements, this study analyses the vulnerabilities, risks, and potential benefits within the CPSS framework. This research study analyses the evolving landscape of cybersecurity by considering various aspects such as data integrity, privacy in the IoT era, and the influence of social media on user behaviour and influence dynamics. The study also introduces innovative strategies to enhance CPSS resilience, including methods to mitigate cyber threats and enhance overall system integrity. Additionally, we investigate how social media shapes CPSS behaviours, offering valuable insights into influence dynamics. This research advances the comprehensive understanding of CPSS to support future studies and advancements in the protection and improvement of interconnected systems. © 2024 IEEE.

关键词： Cyber-Physical systems Cyber-Physical-Social systems (CPSS) Cybersecurity Internet of Things (IoT) Social Media

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Automatic Learning for Commercial Registration Renewal - The Case of Camara de Comercio of Barranquilla-Colombia

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IEEE engineering Management Review 2023年第1期51卷 26-40页

作者： Rios-Henao, Cristian Ariza-Colpas, Paola Patricia De-La-Hoz-Franco, Emiro Aziz, Shariq Butt Melo, Marlon Alberto Pineres Perez-Coronell, Leidy Universidad de la Costa Cuc Department of Computer Science and Electronics Barranquilla08002 Colombia University of South Asia Department of Computer Science Lahore54000 Pakistan Universidad Del Norte Department of Systems Engineering Barranquilla081001 Colombia Universidad Simón Bolívar Facultad de Ingenierías Barranquilla08002 Colombia

This article shows the implementation of a prediction model of the payment behavior of the renewal concept of companies registered in the commercial registry of the Barranquilla Chamber of Commerce using machine learning techniques in a multilevel classification scenario, where it will offer the organization a tool that allows it to know in advance the behavior of the payment of the renewal of a company in such a way that it is able to design strategies to increase the success indicators in terms of the number of registration renewals, mercantile, and of the income collected for this concept. © 1973-2011 IEEE.

关键词： Behavioral research

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Investigating Routing Protocol Attacks on Low Power and Lossy IoT Networks

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SN computer science 2024年第4期5卷 393页

作者： Kiran, Usha Maurya, Poonam Sharma, Himanshu Department of Computer Science Indian Institute of Technology Bhilai Bhilai India Department of Electronics Systems Aalborg University Aalborg Denmark Department of Electronics and Communication Noida Institute of Engineering and Technology Greater Noida India

Internet-of-things (IoT) networks are distinguished by nodes with limited computational power and storage capacity, making Low Power and Lossy Networks (LLNs) protocols essential for effective communication in resource-constrained environments. One such protocol is the Routing Protocol for Low-Power and Lossy networks (RPL), which establishes and manages routes in RPL-based networks. RPL contributes to optimized routing and reduced network overhead in LLNs. However, the RPL-based protocol is susceptible to various internal and external vulnerabilities that require thorough exploration and mitigation. Experimental results illustrate the impact of several RPL attacks, including the DODAG Information Solicitation (DIS) attack, version number attack, decreased rank attack, and worst parent selection (WPS) attack. For simulation purposes, we employed the Contiki Cooja network simulator. Further, we conduct a comparative analysis of these RPL-based attacks, revealing that the WPS attack has a significant impact on the network performance compared to other attacks mentioned in the paper. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Decreased rank attack DIS attack Intrusion detection system RPL attacks Version number attack WPS attack

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Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video

Disentangling Spatio-Temporal Knowledge for Weakly Supervise...

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2025 IEEE/CVF Winter Conference on Applications of computer Vision, WACV 2025

作者： Liao, Guiqiu Jogan, Matjaz Koushik, Sai Eaton, Eric Hashimoto, Daniel A. University of Pennsylvania Pcaso Laboratory Department of Surgery United States University of Pennsylvania Department of Electrical and Systems Engineering United States University of Pennsylvania Department of Computer and Information Science United States

ISBN: (纸本)9798331510831

Weakly supervised video object segmentation (WSVOS) enables the identification of segmentation maps without requiring extensive annotations of object masks, relying instead on coarse video labels indicating object presence. WSVOS in surgical videos is, however, more challenging due to the complex interaction of multiple transient objects, such as surgical tools moving in and out of the surgical field. In this scenario, state-of-the-art WSVOS methods struggle to learn accurate segmentation maps. We address this problem by introducing ViDeo Spatio-Temporal disentanglement Networks (VDST-Net), a framework to disentangle complex spatio-temporal object interactions using semi-decoupled knowledge distillation to predict high-quality class activation maps (CAMs). A teacher network is designed to help a temporal-reasoning student network resolve activation conflicts, as the student leverages temporal dependencies when specifics about object location and timing in the video are not provided. We demonstrate the efficacy of our framework on a challenging surgical video dataset where objects are, on average, present in less than 60% of annotated frames, and compare our method to state-of-the-art methods on surgical data and on a public dataset commonly used to benchmark WSVOS. Our method outperforms state-of-the-art techniques and generates accurate segmentation masks under video-level weak supervision. Our code is available at: https://***/PCASOlab/VDST-net. © 2025 IEEE.

关键词： Image segmentation

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Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

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computers, Materials & Continua 2022年第9期72卷 4249-4265页

作者： Muhammad Irfan Ali Raza Faisal Althobiani Nasir Ayub Muhammad Idrees Zain Ali Kashif Rizwan Abdullah Saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Saifur Rahman Omar Alshorman Samar Alqhtani Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Campus22060Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Federal Urdu University of ArtsScience and TechnologyIslamabad44000Pakistan School of Electrical Engineering and Computer Science National University of Science and TechnologyIslamabad44000Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia

In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial ***,electricity demand and price forecasting play a significant role and can help in terms of reliability and *** to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG *** this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as *** minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant *** this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the ***,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test *** evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark *** proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.

关键词： Smart grid deep neural networks consumer demand big data analytics load forecasting price forecasting

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UAV -Based Object Tracking Using Siamese Networks and Kalman Filtering

UAV -Based Object Tracking Using Siamese Networks and Kalman...

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2025 International Conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Ramanan, S.V. Rajasekar, M. Shanmugapriya, G. Sujitha, R. Akshya, J. Choudhry, Mani Deepak P Pg Institute of Technology Department of Electronics and Communication Engineering Coimbatore India Vsb college of Engineering Department of Computer Science and Engineering Technical Campus Coimbatore India Dr.N G.P Institute of Technology Department of Computer Science and Business Systems Coimbatore India Christ The King Engineering College Department of Information Technology Coimbatore India Srm Institute of Science and Technology Department of Computational Intelligence Chennai India Srm Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798331509828

The ability to match features and keep track of objects in changing dynamic environments is still an important problem, particularly due to varying noise levels, diverse datasets, and high dimensional feature spaces. Euclidean Distance and Cosine Similarity based matching are existing methods that commonly do not generalize well, particularly in the case of cross domain scenarios, where noise and motion dynamics are powerful factors to limit the accuracy of tracking. However, Deep Metric Learning approaches can extract robust features at the cost of computational efficiency and are unsuitable for real-time applications. This research proposes a Siamese Network framework to solve these problems by using robust feature matching and multi-object tracking. Based on that, the proposed framework uses a dual-branch network architecture in which feature embeddings extracted from paired inputs are mapped through the same shared latent space. Furthermore, the adaptive learning rate leads to efficient convergence during the training. Experimental results show that the Siamese Network not only achieves better accuracy than the existing methods and the more such as Deep Metric Learning but also performs significantly more efficient computation. With an accuracy of 90.2 % at a precision of 88.5%, the framework's inference time is much faster than that of Deep Metric Learning at 2.0ms. Furthermore, the proposed method performs well on the generalization over datasets with a 15% improvement of cross-domain matching accuracy on Euclidean Distance. By striking this balance between accuracy, efficiency and adaptability, it shows its suitability for dynamic and noisy environments for real-time tracking. The proposed method fills existing gaps and achieves a new state of the art for feature matching and tracking performance. © 2025 IEEE.

关键词： Object tracking

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Evaluating the Impact on Usability and Acceptance of ECAs in m-Health Applications for Older Adults 11

Evaluating the Impact on Usability and Acceptance of ECAs in...

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11th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Gilaberte, Raquel Lacuesta Bagdasari, Eva Cerezo Navarro-Alamán, Javier EUPT Universidad de Zaragoza Spain EINA Universidad de Zaragoza Spain Department of Computer Science and Engineering of Systems EUPT Universidad de Zaragoza Spain

ISBN: (纸本)9789897587436

In the context of m-health applications, developing user-friendly interfaces to improve usability and acceptance by older adults has become a prominent research topic. The use of embodied conversational agents (ECAs) seems promising as they allow interacting through natural verbal and nonverbal communication. However, analyses about the design and acceptance of embodied conversational agents embedded in m-health applications for older adults are needed. In this paper, we present a study carried out to analyse the usability and acceptance of ECAs interfaces in m-health applications, compared to traditional tactile text interfaces. The study carried out has involved 23 users over 65 years old with promising results. The ECA interface was positively assessed and its acceptance increased compared to the traditional one, but although the feelings arisen are positive, users still claim for less complexity and a more careful design. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Avatars ECAs m-Health Older Adults

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