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A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms

computers, Materials & Continua 2022年第7期72卷 365-380页

作者： Mahmoud Ragab Ali Altalbe Abdullah Saad Al-Malaise ALGhamdi SAbdel-khalek Rashid A.Saeed Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Center of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Mathematics Faculty of ScienceTaif UniversityTaifSaudi Arabia Department of Mathematics Faculty of ScienceSohag UniversitySohagEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

The smart city comprises various interlinked elements which communicate data and offers urban life to *** Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and *** improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with *** addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV ***,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)*** design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.

关键词： Drones smart city swarm intelligence route selection internet of drones networking

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A Systemic Big Data Framework for the Charging Pile Business 22

A Systemic Big Data Framework for the Charging Pile Business

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Proceedings of the 7th International Conference on information systems engineering

作者： Licheng Xu Shuai Xie Department of Software Engineering Universiti Malaya Malaysia Faculty of Computer Science and Information Technology Universiti Malaya Malaysia

ISBN: (纸本)9781450397889

There are some problems in the electric vehicle (EV) charging pile industry, such as the unreasonable location of charging station construction, low utilization rate of charging piles, and imprecise marketing strategies, which may elicit a negative response from EV users, cause colossal waste of resources and hinder the development of EVs. Based on the relevant charging pile data to be analyzed, this paper combines big data-related technologies to propose a big data framework for analyzing the charging pile data to solve the common charging service problems from a systemic perspective. The purpose of the framework is to provide decision-making reference information for charging pile operators, charging pile application operators and charging service marketers to improve the charging pile business more effectively. The framework is demonstrated by functional structure and technical structure.

关键词： Charging pile data Big Data framework Decision-making reference Charging business improvement

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Blockchain-Powered e-Wallet: Enhancing Security and Fraud Detection in Online Payments 1

Blockchain-Powered e-Wallet: Enhancing Security and Fraud De...

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1st International Conference on Cryptography and information Security, VCRIS 2024

作者： Bui-Huu, Dong Le-Nhat, Tan Nguyen-An, Khuong Ho Chi Minh University of Banking Faculty of Management Information Systems Department of Computer Science Ho Chi Minh City Viet Nam Fulbright Vietnam University Undergraduate Faculty Ho Chi Minh city Viet Nam Faculty of Computer Science and Engineering Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9798331529949

Cashless payment has been emphasized in many countries, especially since the outbreak of the COVID-19 pandemic. Various payment methods have emerged, among which electronic wallets (e-wallets) have become a popular online payment method due to their convenience, flexibility, and time and cost savings for users. However, alongside the growth in the number and value of transactions, e-wallets face challenges from increasingly sophisticated and complex security threats, fraud, and forgery, originating both internally and externally, causing severe financial losses and diminishing customer trust. To ensure the safety of e-wallet, we propose an architecture developed based on the permissioned blockchain platform-Hyperledger Fabric, following a microservice model with high-performance APIs that can be easily integrated into e-wallet systems at an optimal cost without requiring complex infrastructure investments. Thanks to blockchain's immutable, transparent, and decentralized storage nature, this solution effectively monitors and supports real-time fraud detection and forgery prevention, ensuring the safety, security, and integrity of users' online payment transactions. Furthermore, this solution also provides users with immediate notifications via Email or SMS when an attack or fraud is detected on the e-wallet. © 2024 IEEE.

关键词： Blockchain

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An Optimal Text Watermarking Method for Sensitive Detecting of Illegal Tampering Attacks

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computers, Materials & Continua 2022年第3期70卷 5583-5600页

作者： Anwer Mustafa Hilal Fahd N.Al-Wesabi Mohammed Alamgeer Manar Ahmed Hamza Mohammad Mahzari Murad A.Almekhlafi Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of English College of Science&HumanitiesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Faculty of Engineering Department of Electrical EngineeringCommunication EngineeringSana’a UniversityYemen

Due to the rapid increase in the exchange of text information via internet networks,the security and authenticity of digital content have become a major research *** main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital *** this paper,an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on theArabic text transmitted online via an Internet *** this purpose,the accuracy of tampering detection and watermark robustness has been improved of the proposed method as compared with the existing *** the proposed method,both embedding and extracting of the watermark are logically implemented,which causes no change in the digital *** is achieved by using the third level and alphanumeric strategy of the Markov model as a text analysis technique for analyzing the Arabic contents to obtain its features which are considered as the digital *** digital watermark will be used later to detecting any tampering of illegal attack on the received Arabic *** extensive set of experiments using four data sets of varying lengths proves the effectiveness of our approach in terms of detection accuracy,robustness,and effectiveness under multiple random locations of the common tampering attacks.

关键词： Text analysis text-watermarking tampering detection text authentication

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Exploring the Impact of Random Distribution Choices on Particle Swarm Optimization: An Initial Analysis 27

Exploring the Impact of Random Distribution Choices on Parti...

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27th International Conference on Knowledge Based and Intelligent information and engineering Sytems, KES 2023

作者： Kolodziejczyk, Joanna Tarasenko, Yuliia Sulikowski, Piotr Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland Department of Information Systems Engineering Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

Particle Swarm Optimization (PSO) is a robust stochastic optimization algorithm for solving complex and constrained optimization problems. This paper aims to systematically investigate the influence of diverse random number distributions on the learning parameters of PSO and evaluate the algorithm's sensitivity based on these parameters. To this end, several exhaustive numerical experiments were conducted on several test functions, including asymmetric Sphere, Easom, and Csendes. Initially, appropriate random distributions were identified for the learning parameters and proceeded to compare these distributions using all potential combinations. The sensitivity of PSO to these parameters was evaluated using the mean best score, the relative proximity of the best particle to the theoretical optimum, and the average objective function evaluations. The most significant contribution of this research lies in the insights derived from the experimental data. The discovery was that highly skewed and long-tailed distributions such as Chi, Chi-square, Lomax, and Exponential often underperform. On the other hand, distributions that are bounded proportionally to the problem domain consistently surpass the performance of the standard uniform distribution. These findings significantly enhance the understanding of PSO algorithms and provide valuable guidelines for their practical deployment. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Particle Swarm Optimization random number distribution stochastic optimization

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Syllabus Design and Planning with Artificial Intelligence and the Potential of Generative AI 24

Syllabus Design and Planning with Artificial Intelligence an...

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24th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2024

作者： Kozhanov, Murat Mosavi, Amir Amirov, Azamat Kaibassova, Dinara Poser, Valeria Shakhatova, Aliya Lira, La Eigner, Gyorgy Department of Information and Computing Systems Abylkas Sagninov Karaganda Technical University Karaganda Kazakhstan Obuda University Budapest Hungary Ludovika University of Public Service Budapest Hungary Department of Computer Engineering Astana IT University Astana Kazakhstan John von Neumann Faculty of Informatics Obuda University Budapest Hungary Department of Information Systems L.N.Gumilyov Eurasian National University Astana Kazakhstan

ISBN: (纸本)9798350353433

This article introduces a methodology to identify the fundamental studies carried out using artificial intelligence for syllabus design and planning. A taxonomy of the most relevant studies is presented based on the method and applications. The main studies in the field are reviewed and their contributions are emphasized. The meta-analysis of the results presents the extent and applicability of artificial intelligence in syllabus design and planning. The result shows the essential role of machine learning in the development and improving the process of syllabus design and planning. © 2024 IEEE.

关键词： Adversarial machine learning

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Towards Modeling Functional Requirements From Tacit Knowledge

Towards Modeling Functional Requirements From Tacit Knowledg...

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computer Science, computer engineering, & Applied Computing (CSCE), Congress in

作者： Rameen Jafar Maram Fahaad Almufareh Sundas Ashraf Bushra Khan Wasi Haider Butt Mamoona Humayun Department of Computer and Software Engineering National University of Sciences and Technology Pakistan Department of Information Systems College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia

Requirements Elicitation is the process of identifying system needs by talking with stakeholders who have a direct or indirect effect on the requirements. Requirements may be derived from several sources and are one of the most important phases of requirement engineering. We need to perform different elicitation techniques to find out the user's needs. Pre-requirements tracing is the process of determining the origins of a specific demand. Typically, certain needs arise that have no apparent source, but stakeholders will testify to their importance. Such criteria, however, are most likely dependent on tacit or tacit-like information entrenched in the issue domain. Tacit knowledge is one of the most common challenges for requirement analysts. This study contributes to constructing a systematic literature review for exploring multiple ways to model functional requirements using tacit knowledge. We have identified and analyzed 10 studies. In these research papers, different authors have discussed different methods to gather functional requirements from tacit knowledge.

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Towards a Deep Learning Pain-Level Detection Deployment at UAE for Patient-Centric-Pain Management and Diagnosis Support: Framework and Performance Evaluation

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Procedia computer science 2023年 220卷 339-347页

作者： Leila Ismail Muhammad Danish Waseem Clouds and Distributed Computing and Systems (CLOUDS) Lab School of Computing and Information Systems Faculty of Engineering and Information Technology The University of Melbourne Australia. Intelligent Distributed Computing and Systems (INDUCE) Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University UAE. National Water and Energy Center United Arab Emirates University UAE.

The outbreak of the COVID-19 pandemic revealed the criticality of timely intervention in a situation exacerbated by a shortage in medical staff and equipment. Pain-level screening is the initial step toward identifying the severity of patient conditions. Automatic recognition of state and feelings help in identifying patient symptoms to take immediate adequate action and providing a patient-centric medical plan tailored to a patient's state. In this paper, we propose a framework for pain-level detection for deployment in the United Arab Emirates and assess its performance using the most used approaches in the literature. Our results show that a deployment of a pain-level deep learning detection framework is promising in identifying the pain level accurately.

关键词： computer Vision Deep Learning Image Processing Machine Learning Pain Detection Patient-Centric Smart healthcare eHealth

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Remote Patient Monitoring systems Network Adaptation Scenarios

Remote Patient Monitoring Systems Network Adaptation Scenari...

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2022 IEEE International Conference on Current Development in engineering and Technology, CCET 2022

作者： Khujamatov, Halimjon Akhmedov, Nurshod Lazarev, Amir Arsheen, Sobiya Tashkent University of Information Technologies Dean of the Faculty of Computer Engineering Tashkent Uzbekistan Tashkent University of Information Technologies Data Transmission Networks and Systems Department Tashkent Uzbekistan Maulana Azad National Urdu University Department of Computer Science and Information Technology India

ISBN: (纸本)9781665454155

This article is devoted to the actual topic of studying scenarios for adapting a network infrastructure to a network of remote patient monitoring systems (PCMS). The paper presents an overview and analysis of scenarios for adapting the network infrastructure of monitoring systems. The stages of scenario execution have been studied and simulation models of the RPMS network infrastructure have been developed that implement various adaptation scenarios. A comparative analysis of adaptation scenarios was carried out according to several criteria, such as the speed of request delivery, delivery time, and network load. Simulation models built in the Anylogic environment, a powerful simulator of mass service system, showed the effectiveness of the mesh topology in relation to the ad-hoc topology according to several criteria. The theoretical significance of the work lies in carrying out analytical work on scenarios for adapting the network infrastructure of the RPMS, as well as in studying the network architecture. The practical significance of the work lies in the development of a simulation model that allows you to explore scenarios for adapting the network architecture. © 2022 IEEE.

关键词： Network architecture

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Smart Home User Interface: Development and Comparison

Smart Home User Interface: Development and Comparison

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International Conference on Industrial engineering, Applications and Manufacturing (ICIEAM)

作者： R. Faizrakhmanov A. Platunov M. Bahrami Cyberphysical Systems Laboratory Innopolis University Kazan Russian Faculty of Software Engineering and Computer Systems ITMO University Saint-Petesburg Russia

The active development of the Internet of Things (IoT) in recent years has increased people’s need for control smart devices for home. At the same time, the complexity of these devices is growing. Therefore, Smart Home systems require a simple and convenient interface for control. However, methods for evaluating and comparing interfaces are not clear. In this paper, we described a method to comparing and evaluating different types of Smart Home interfaces. In addition, we evaluate results experimentally. For this comparison, we used a popular Smart Home control software on the market. The results showed that Smart Home graphical user interfaces are more convenient than a messenger or voice. Voice interface is suitable for controlling a Smart Home but is not informative enough in feedback. On the other hand, the familiar interface of the messenger turned out to be the least convenient. This study will help both researchers and practitioners evaluate and choose the right Smart Home interface.

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