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Integrating Blockchain Technology with PKI for Secure and Interoperable Communication in 5G and Beyond Vehicular Networks

Integrating Blockchain Technology with PKI for Secure and In...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Fetulhak Abdurahman Shewajo Abdelwahab Boualouache Sidi Mohammed Senouci Ines El-Korbi Bouziane Brik Kinde Anlay Fante DRIVE Lab University of Burgundy Nevers France Faculty of Electrical and Computer Engineering Jimma Institute of Technology Jimma University Jimma FSTM University of Luxembourg Luxembourg Computer Science Department College of Computing and Informatics Sharjah University Sharjah UAE

Security and privacy are crucial in V2X networks due to sensitive user information. Public Key Infrastructure (PKI) is widely used in C-ITS to ensure security and privacy. However, the practical implementation of PKI faces challenges in achieving seamless communication across diverse ITS projects worldwide. The absence of interoperability between PKI systems and unre-solved issues in existing PKI standards hinder global adoption. Despite available security standardizations using centralized PKI technology for V2X, a universally adopted PKI-based security architecture is necessary. Furthermore, the progress made in 5G V2X technology has demonstrated significant potential for revolutionizing V2X communication in the future. Enhancing the level of trust through integration of the 5G Core Network (5GC) into the PKI security mechanism can lead to more secure and efficient V2X communication. To address these challenges, we propose a blockchain-based architecture that integrates the 5GC network with the PKI infrastructure, aiming to enhance privacy and security in 5G V2X communication. Our solution is designed to be distributed and interoperable, aligned with existing ETSI ITS PKI standard. By utilizing Hyperledger Fabric (HLF) platform, a permissioned blockchain framework, we present the architecture and conduct a comprehensive security analysis to ensure compliance with security and privacy requirements of V2X communications.

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Roman Senkerik Aleksander Byrski Hubert Guzowski Peter Janku Tomas Kadavy Zuzana Kominkova Oplatkova Radek Matusu Michal Pluhacek Libor Pekar Maciej Smolka Adam Viktorin Department of Informatics and Artificial Intelligence A.I. Lab Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Institute of Computer Science AGH University of Science and Technology Krakow Poland

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics.

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Calorie Burn Estimator on Stationary Bike using Human Body Pose Detector

Calorie Burn Estimator on Stationary Bike using Human Body P...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Iwap Saputra Batan Eko Mulyanto Yuniarno Mauridhi Hery Purnomo Ahmad Ramadhani Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

During the pandemic, we must maintain our body’s immunity at best. Outdoor activities have been closed; therefore, there are limitations to activities that can be done. A solution to staying healthy during the pandemic is indoor exercise. One type of indoor exercise is regularly riding stationary bikes. We maintain the body’s fitness and burn calories by riding stationary bikes. However, some stationary bikes could not show accurate calories burned; they calculated it only based on speed, resistance, and duration, so people with different weights seem to burn the same amount of calories. Therefore, this paper proposed an additional parameter essential in calorie burning: body weight. We used the human body pose estimator to detect the activity of riding the stationary bike and calculated it by adding the person’s weight. The result shows a difference between the estimated calorie burned and the data directly from the stationary bike. The difference is between 0.0225 to 2.8775. The heavier the person, the more differences in the calories burned. The proposed method helped prove that a person’s weight affects the calories burned while doing an activity, especially riding a stationary bike.

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VLM-Enabled Network Experimentation: Case Study of Chanel Capacity in System Limited by η-μ Fading

VLM-Enabled Network Experimentation: Case Study of Chanel Ca...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Dejan Milić Nenad Petrović Milan Jović Radiša Stefanović Mejdin Saliji Elida Suljović Faculty of Electronic Engineering University of Niš Niš Serbia Applied Engineering Sciences Academy of Vocational Studies Polytechnic Belgrade Serbia Faculty of Mathematics and Natural Sciences Cyril and Methodius University Skopje Republic of North Macedonia Informatics and Computer Science Technical School in Novi Pazar Novi Pazar Serbia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

In this paper, a micro-MRC receiver with L branches operating in a correlated gamma-shadowed η-μ fading channel is considered. For such a system, the channel capacity (CC) is determined based on the maximum signal-to-noise ratio (SNR) at the L branches at the input of the MRC receiver. The results are presented graphically to illustrate the impact of different system parameters on performance and the improvements that result from the advantages of combined diversity. Additionally, we introduce the application of Large Language Models (LLMs) to make network experimentation more practical, using the previously presented expression as a case study. Moreover, a Vision Language Model (VLM) aided method aiming to make model-driven network design and experimentation more convenient is introduced and evaluated for the previously considered case study

关键词： Fading channels Wireless communication Visualization Channel capacity System performance Scalability Large language models Receivers Signal to noise ratio

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Traffic Classification based on Incremental Learning Algorithms for the Software-Defined Networks

Traffic Classification based on Incremental Learning Algorit...

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2022 International Conference on Frontiers of Information Technology, FIT 2022

作者： Eldhai, Arwa M. Hamdan, Mosab Khan, Suleman Hamzah, Muzaffar Marsono, M.N. University of Science and Technology Faculty of Engineering Khartoum11115 Sudan Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Kota Kinabalu88450 Malaysia University of São Paulo Department of Computer Science São Paulo05508-090 Brazil University of Central Lancashire School of Psychology and Computer Science PrestonPR1 2HE United Kingdom Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor81310 Malaysia

ISBN: (纸本)9798350345933

A new era of network administration has been ushered in by recent developments in software-defined networks (SDN) and traffic classification (TC) using machine learning (ML) techniques. All network devices are centrally managed and accessible through the SDN, which can simplify the TC process. The traditional data mining/ML approach that uses TC assumes that all of the task's data is always accessible and can be viewed simultaneously without processing time and memory restrictions. Therefore, these approaches are not effective in the case of stream learning since, in more realistic settings, the data is not available all at once and has a distinct distribution. Consequently, incremental learning algorithms (ILAs) can handle online data mining. This study's primary goal is to contrast various ILA approaches to enhance SDN's TC performance. In this study, we propose four ILAs: the self- adjusting memory coupled with the k Nearest Neighbor (kNN) classifier (SAMKNNC), the very fast decision rules classifier (VFDRC), the extremely fast decision tree classifier (EFDTC), and the streaming random patches ensemble classifier (SRPC). Both real and synthetic datasets are used for validation. Experimental findings reveal that the proposed techniques perform better in SDN traffic classification since they can effectively identify drift and use less memory and time. © 2022 IEEE.

关键词： Learning algorithms

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Analysis of Virtual Reality Based on the Internet of Things on Human Psychology ‘Internet of Thoughts’ (IoThs) for Rich Content Extraction Applied Natural Language Processing and Deep Learning 1

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20th International Conference on Smart Living and Public Health, ICOST 2023

作者： Mah, Pascal Muam Skalna, Iwona Pelech-Pilichowski, Tomasz Derlecki, Tomasz Nasr, Mahmoud Munyeshuri, Eric Amuzang, Gilly Njoh Itoe, Micheal Blake Somaah Tah, Ning Frida Department of Technical Informatics and Telecommunications AGH University of Science and Technology Krakow Poland Department of Business Informatics and Management Engineering AGH University of Science and Technology Krakow Poland Institute of Computer Science AGH University of Science and Technology Krakow Poland Department of Economics and Management Industry AGH University of Science and Technology Krakow Poland Department of Biomedical Engineering AGH University of Science and Technology Krakow Poland Department of Engineering Mathematics and Physics Faculty of Engineering and Technology Future University Cairo Egypt Department of Production Engineering and Logistics Enterprise Silesian University of Technology Gliwice Poland Department of Logistics Management Silesian University of Technology Gliwice Poland

ISBN: (数字)9783031439506

ISBN: (纸本)9783031439490

In the past decade, a lot of challenges to access, assess, and to acquire the needed technological opportunities to teach computers what naturally comes from the human brain and to understand how we naturally react when we rely on technology. The ability to document human thoughts, reactions and behavior to computers has led to the coming of NLP, AI, Dl, & ML. Aim to understand the influence of IoT on humans with the use of DL to achieve content correctness and accuracy with virtual technology. Studies show that the way we think, react, and do the things we think "Internet of thoughts" reflect our personality. The way we think determines the way we react and the way we do things are based on how we think. Technology advancement has reinforced a lot of changes in humans which makes humans vulnerable to personal content exposure misappropriation due to the continuously changing nature of humanity and language. The study uses NLP, DL and behavior-oriented drive and influential function and results show that IoT based on VR influences human psychology "Internet of Thoughts". © 2023, The Author(s).

关键词： Internet of things

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Markov Chain-Based Model of Blockchain Radio Access Networks 29

Markov Chain-Based Model of Blockchain Radio Access Networks

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Kouvakis, Vasileios Trevlakis, Stylianos E. Boulogeorgos, Alexandros-Apostolos A. Liu, Hongwu Tsiftsis, Theodoros A. Dobre, Octavia A. University of Western Macedonia Department of Electrical and Computer Engineering Kozani50100 Greece School of Information Science and Electrical Engineering Shandong Jiaotong University Jinan250357 China University of Thessaly Department of Informatics & Telecommunications Lamia35100 Greece InnoCube P.C. Department of Research and Development 17th Noemvriou 79 Thessaloniki55535 Greece Memorial University Faculty of Engineering and Applied Science St. John'sNLA1B 3X9 Canada

ISBN: (纸本)9798350377644

Security has always been a priority, for re- searchers, service providers and network operators when it comes to radio access networks (RAN). One wireless access approach that has captured attention is blockchain enabled RAN (B-RAN) due to its secure nature. This research introduces a framework that integrates blockchain technology into RAN while also addressing the limitations of state-of-the-art models. The proposed framework utilizes queuing and Markov chain theory to model the aspects of B-RAN. An extensive evaluation of the models performance is provided, including an analysis of timing factors and a focused assessment of its security as- pects. The results demonstrate reduced latency and comparable security making the presented framework suitable for diverse application scenarios. © 2024 IEEE.

关键词： Markov chains

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A Study on Medicinal Plant Leaf Recognition Using Artificial Intelligence 3

A Study on Medicinal Plant Leaf Recognition Using Artificial...

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3rd International Conference on informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Ayumi, Vina Ermatita, Ermatita Abdiansah, Abdiansah Noprisson, Handrie Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Universitas Mercu Buana Faculty of Computer Science Jakarta Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Medicinal plant recognition manually takes a lot of time and money. Moreover, to reduce these resources, some researchers propose to implement artificial intelligence technology. This paper aims are to conduct a systematic literature review of medicinal plant leaf recognition published in the last two years (2019-2020) from IEEE, Springer and Science Direct. We obtained 15 studies in the field of medicinal plant leaf recognition using artificial intelligence. The dataset used for medicinal plant leaf recognition is mostly used private dataset, however, there are public dataset named Leaf, Flavia, Swedish dataset. We also found robust method that can be used for medicinal plant leaf recognition is Multichannel Modified Local Gradient Pattern (MCMLGP) and Gray Level Co-Occurrence Matrix (GLCM) as feature extraction;and Convolutional Neural Network (CNN), Multi-Layer Perceptron trained with Backpropagation algorithm (MLP-BP), Support Vector Machine (SVM), and Transfer Learning (VGG19) as classifier. © 2021 IEEE.

关键词： Image processing

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Analysis of the Best Employee Selection Decision Support System Using Analytical Hierarchy Process (AHP) 1

Analysis of the Best Employee Selection Decision Support Sys...

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1st International Conference on Innovation and Application of Science and Technology, ICIASTECH 2019

作者： Lia Hananto, April Priyatna, Bayu Fauzi, Ahmad Yuniar Rahman, Aviv Pangestika, Yulia Tukino Faculty of Computing Universiti Teknologi Malaysia Skudai Johor Malaysia Faculty of Technology and Computer Science Universitas Buana Perjuangan Karawang Indonesia Department of Informatics Engineering Universitas Widyagama Malang Indonesia Faculty of Postgraduate Management Computer Indonesia of University Indonesia

The award is given by the company to the best employees always to provide the best performance for companies that carry out duties and obligations in the company. How to give rewards to employees not only for how long they have been working at the company but about the results achieved. The gift can be in the form of salary or inventory from the company. So employees have great loyalty to the company. Decision making to determine the company can do the best employee by assessing the performance that has been done by employees at a specific time. Performance evaluation of Hon Chuan Company is influenced by several criteria, namely discipline, innovation, and responsibility. The support system for the best employee selection method uses the Analytical Hierarchy Process (AHP) method. The decision-making system is carried out to assess choices based on predetermined criteria. AHP method is applied to choose the best prospective employees. The calculation of the AHP method gives the results of the order of importance of criteria, namely discipline level (0.5584), responsibility (0.3196), and innovation (0.1220) and the best employee selection results obtained by Hendra (0.189), Vienna (0.189), Yin (0.145), Paul (0.109), Kandi (0.108), Kusworo (0.101), Bayu (0.088), and Ade Muhidin (0.072). © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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COVID19 Impact on Medical Clinics, Analysing and Devising a Safety Software Model for Clinics 4

COVID19 Impact on Medical Clinics, Analysing and Devising a ...

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4th International Conference on Computing, Electronics and Communications engineering, iCCECE 2021

作者： Fetaji, Majlinda Fetaji, Bekim Aliu, Azir Snopce, Halil Zeqiri, Izet Ebibi, Mirlanda Ali, Maaruf South East European University Faculty of Computer Sciences Tetovo Macedonia Mother Teresa University Faculty of Informatics Skopje Macedonia Faculty of Economy South East European University Tetovo Albania Epoka University Department of Computer Engineering Tirana Albania

ISBN: (纸本)9781665449113

The focus of this research is on investigating and identifying what constitutes a safe software model of a medical clinic that will enable and enhance its protection for healthcare providers and its patients by devising a model of a software system. There is a gap in the published research regarding the understanding of impacting factors of COVID19 in the safe functioning of a medical clinic. This Case Study investigated several impacting factors. The aims of this research project are: increasing the safety effectiveness of both the hospital personnel and patients. Next, to solve the problems with tracking the illnesses of patients, a more rigorous database indexing system was implemented with data provenance. With this technique in the database, it kept track of illnesses (when, why, in whom did it appear or any kind of other developments), login details (when, who is logged in, logged out), which is more important especially for medical systems. Also, which doctors interacted with the patients (what drug have been administered, their performance, percentage of efficacy, successfully or unsuccessfully) and other data mining information. Because this project is envisioned to be continually supported, it should evolve and deal with the problems encountered in modern hospitals. The system has been evaluated on its functionalities and the safety usability, on two groups of users: Those with a computer science background and those from a different field. Afterwards regression analyses were used to determine the impact. The research study contributed with identified impacting factors for such systems, analyses of the improvement in conceptual increase of safety and usability. Insights and recommendations are provided. © 2021 IEEE.

关键词： COVID-19

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