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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Sadullaeva, Shakhlo Azimbaevna Anarova, Shahzoda Amanbayevna Khaydarov, Abdugaffor Fayzullayeva, Zarnigor Nazirova, Dilorom Mirkhodzhaeva, Nazhiba departament Intellegent systems Joint Belarusian-Uzbek Intersectoral Institute of Applied Technical Qualifications Tashkent Uzbekistan Department of Convergence of Digital Technologies Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis National University of Uzbekistan Tashkent Uzbekistan Department of Informatics Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis NUUz Tashkent Uzbekistan

ISBN: (纸本)9798400716928

Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are nonlinear, degenerate, and have properties that are absent in linear theory and therefore make them quite difficult for both analytical and numerical analysis of the solution. For this reason, great attention is paid to the research of nonlinear mathematical models, the construction of efficient numerical solution schemes and algorithms, and the creation of software using the capabilities of computer technologies. In this article, the mathematical model of the diffusion process in a two-component nonlinear medium under the influence of time-dependent convective transfer and damping is studied. The calculation scheme, algorithm, and software for nonlinear problems were developed. Based on a study of the qualitative properties of a nonlinear mathematical model of a reaction-diffusion system, computer modeling of reaction-diffusion processes was carried out. The developed computational schemes, algorithms, and software packages for solving systems of parabolic equations with double nonlinearity provide high productivity in studying the theory and processes of numerical solutions of such problems. © 2024 ACM.

关键词： Nonlinear equations

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Live Migration of Virtual Machines Using a Mamdani Fuzzy Inference System

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computers, Materials & Continua 2022年第5期71卷 3019-3033页

作者： Tahir Alyas Iqra Javed Abdallah Namoun Ali Tufail Sami Alshmrany Nadia Tabassum Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Computer Science Virtual University of PakistanLahore54000Pakistan

Efforts were exerted to enhance the live virtual machines(VMs)migration,including performance improvements of the live migration of services to the *** VMs empower the cloud users to store relevant data and ***,the utilization of servers has increased significantly because of the virtualization of computer systems,leading to a rise in power consumption and storage requirements by data centers,and thereby the running *** center migration technologies are used to reduce risk,minimize downtime,and streamline and accelerate the data center move ***,several parameters,such as non-network overheads and downtime adjustment,may impact the live migration time and server downtime to a large *** virtualizing the network resources,the infrastructure as a service(IaaS)can be used dynamically to allocate the bandwidth to services and monitor the network flow *** to the large amount of filthy retransmission,existing live migration systems still suffer from extensive downtime and significant performance degradation in crossdata-center *** study aims to minimize the energy consumption by restricting the VMs migration and switching off the guests depending on a threshold,thereby boosting the residual network bandwidth in the data center with a minimal breach of the service level agreement(SLA).In this research,we analyzed and evaluated the findings observed through simulating different parameters,like availability,downtime,and outage of VMs in data center *** new paradigm is composed of two forms of detection strategies in the live migration approach from the source host to the destination source machine.

关键词： Cloud computing IaaS data centre storage performance analysis live migration

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An Architecture Supporting Intelligent Mobile Healthcare Using Human-computer Interaction HCI Principles

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computer systems science & Engineering 2022年第2期40卷 557-569页

作者： Mesfer Alrizq Shauban Ali Solangi Abdullah Alghamdi Muhammad Ali Nizamani Muhammad Ali Memon Mohammed Hamdi College of Computer Science and Information Systems Najran UniversityNajranSaudi Arabia Faculty of Engineering&Technology University of SindhJamshoro78060Pakistan

Recent advancements in the Internet of Things IoT and cloud computing have paved the way for mobile Healthcare(mHealthcare)services.A patient within the hospital is monitored by several ***,upon leaving the hospital,the patient can be remotely monitored whether directly using body wearable sensors or using a smartphone equipped with sensors to monitor different user-health *** raises potential challenges for intelligent monitoring of patient's *** this paper,an improved architecture for smart mHealthcare is proposed that is supported by HCI design *** HCI also provides the support for the User-Centric Design(UCD)for smart mHealthcare ***,the HCI along with IoT's(Internet of Things)5-layered architecture has the potential of improving User Experience(UX)in mHealthcare design and help saving *** intelligent mHealthcare system is supported by the IoT sensing and communication layers and health care providers are supported by the application layer for the medical,behavioral,and health-related *** care providers and users are further supported by an intelligent layer performing critical situation assessment and performing a multi-modal communication using an intelligent *** HCI design focuses on the ease-of-use,including user experience and safety,alarms,and error-resistant displays of the end-user,and improves user's experience and user satisfaction.

关键词： Human computer interaction mhealthcare user-centric design sensor network nternet-of-things

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The Impact of Augmentation and SMOTE Implementation on the Classification Models Performance: A Case Study on Student Academic Performance Dataset 9th

The Impact of Augmentation and SMOTE Implementation on the C...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Sano, Albert Verasius Dian Bhatti, Faqir M. Miranda, Eka Aryuni, Mediana Zakiyyah, Alfi Yusrotis Bernando, Charles Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Riphah Institute of Computing and Applied Sciences Riphah Intternational University Raiwind Lahore Pakistan Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Mathematics Department School of computer Science Bina Nusantara University Jakarta11480 Indonesia

This study aims to find out the impact of data augmentation and Synthetic Minority Over-sampling Techniques (SMOTE) implementation on the classification models performance using small and imbalanced dataset of student academic performance. The design of this study involved a comprehensive experiment by comparing four scenarios: 1) comparing classification models without both data augmentation and SMOTE, 2) models with data augmentation, 3) models with SMOTE, and 4) models with both data augmentation and SMOTE. The model's performances were each measured based on standard evaluation metrices such as accuracy, precision, recall, F1-score. To test the results validity, there were three classification algorithms implemented and evaluated for each scenario, that is, Random Forest, XGBoost, and AdaBoost. The finding of this study highlights the significant impact of data augmentation and SMOTE to the increase of classification models performance, particularly over the small and imbalanced dataset. Results showed that the implementation of both techniques simultaneously brought about the most significant increase in the evaluation metrices compared to the implementation of both techniques separately. The originality of this study lies in its comprehensive approach in comparing the effectiveness of data augmentation and SMOTE, as well as the use of student academic performance dataset, which is, a real case in the context of artificial intelligence. This finding gives a valuable insight to the researchers and practitioners in choosing appropriate techniques to handle small and imbalanced class datasets. This study is expected to make an important contribution to the more effective development of classification methodology in various domains. © 2024 The Authors.

关键词： Data accuracy

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Performance Framework for Virtual Machine Migration in Cloud Computing

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computers, Materials & Continua 2023年第3期74卷 6289-6305页

作者： Tahir Alyas Taher M.Ghazal Badria Sulaiman Alfurhood Munir Ahmad Ossma Ali Thawabeh Khalid Alissa Qaiser Abbas Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Information Technology Skyline University CollegeUniversity City SharjahSharjah1797UAE Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebansaan Malaysia(UKM)Bangi43600SelangorMalaysia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Dean of Student Affairs Skyline University CollegeUniversity City SharjahSharjah1797UAE Networks and Communications Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Faculty of Computer and Information Systems Islamic University Madinah Madinah42351Saudi Arabia

In the cloud environment,the transfer of data from one cloud server to another cloud server is called *** can be delivered in various ways,from one data centre to *** research aims to increase the migration performance of the virtual machine(VM)in the cloud *** allow cloud customers to store essential data and ***,server usage has grown dramatically due to the virtualization of computer systems,resulting in higher data centre power consumption,storage needs,and operating *** VMs on one data centre manage share resources like central processing unit(CPU)cache,network bandwidth,memory,and application ***-cloud,VMmigration addresses the performance degradation due to cloud server configuration,unbalanced traffic load,resource load management,and fault situations during data *** speed is influenced by the size of the VM,the dirty rate of the running application,and the latency ofmigration *** a result,evaluating VM migration performance while considering all of these factors becomes a difficult *** effort of this research is to assess migration problems on *** simulation results in Matlab show that if the VMsize grows,themigration time of VMs and the downtime can be impacted by three orders *** dirty page rate decreases,themigration time and the downtime grow,and the latency time decreases as network bandwidth increases during the migration time and post-migration overhead calculation when the VMtransfer is *** the simulated cases of VMs migration were performed in a fuzzy inference system with performance graphs.

关键词： Latency cloud computing dirty page ratio storage migration performance

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Web Application to predict Skin Disease: An Approach Using Deep Learning Algorithm 6

Web Application to predict Skin Disease: An Approach Using D...

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6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Thayalan, Eelanila Arumugavel, Ayingaran Ganeshan, Sharujan Dalaxshan, Makenthiran Fernando, Harinda Rajapakse, Kaushalya Department of Information Technology Faculty of computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Faculty of computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350394634

The Disease Prediction System revolutionizes healthcare with advanced machine learning techniques for early detection of skin diseases, notably focusing on skin cancer. Through image processing and Transfer Learning, it excels in identifying potential malignancies, enabling timely interventions. Its capabilities extend to benign tumors and growth disorders, utilizing the ResNet50 Model for precise identification. Additionally, it predicts skin reactions associated with various dermatological conditions, such as Urticaria Hives and Warts, leveraging the efficientnetB0 Model. Integration of the VGG16 Model enhances diagnostic accuracy for inflammatory skin conditions. This holistic approach prioritizes patient-centric care, leveraging diverse datasets and intricate pattern recognition in medical images. The system's proactive nature embodies personalized solutions for early detection, timely intervention, and improved patient outcomes. Its versatility and accuracy underscore itstransformative potential in healthcare delivery. By harnessing diverse datasets and recognizing intricate patterns within medical images, it heralds a new era of personalized healthcare solutions. In essence, the Disease Prediction System exemplifies the transformative potential of machine learning in healthcare, ensuring the highest standards of diagnostic accuracy and efficacy, while prioritizing patient well-being and quality oflife. © 2024 IEEE.

关键词： Deep learning

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Real-Time Sensor Fault Tolerant Control of DC-DC Converters in DC Microgrids Using a Switching Unknown Input Observer

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IEEE Access 2025年 13卷 95837-95850页

作者： Ouahabi, Mohammed Said Benyounes, Abdelhafid Barkat, Said Ihammouchen, Syphax Rekioua, Toufik Rabehi, Abdelaziz El-Kenawy, El-Sayed M. Alharbi, Amal H. University of M’sila Electrical Engineering Laboratory Faculty of Technology M’sila28000 Algeria University of Bejaia Laboratoire de Technologie industrielle et de l’Information Bejaia06000 Algeria University of Djelfa Telecommunications and Smart Systems Laboratory PO Box 3117 Djelfa17000 Algeria PO Box 33349 Isa Town Bahrain Applied Science Private University Applied Science Research Center Amman Jordan Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Computer Sciences P.O. Box 84428 Riyadh11671 Saudi Arabia

DC Microgrids are rapidly developing, driven by the increasing integration of renewable sources and dynamic loads. Their growing adoption in critical applications raises the need for operational safety and reliability, particularly under fault conditions. This paper presents a sensor fault-tolerant control (FTC) for DC-DC power converters in DC Microgrids designed to maintain resilient and reliable operation. The proposed FTC leverages a single Switching Unknown Input Observer (SW-UIO) at the bottom control level to estimate arbitrary sensor faults with a high accuracy (0.3% fault estimation error), allowing a real-time identification and precise control reconfiguration to accommodate sensor faults with minimal computational burden. The approach is validated under diverse conditions, including time-varying loads, complete sensor failure, noise abnormality, and simultaneous faults/failure, achieving a consistent fault accommodation of 1μs from fault occurrence to compensation. Real-time simulation has been performed in the OPAL-RT environment to assess the efficacy and superiority of the proposed sensor fault tolerant strategy in comparison to reference FTC strategies. © 2013 IEEE.

关键词： Identification (control systems)

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A Proposed Framework for Cloud Immunization information System: Challenges and Opportunities 11th

A Proposed Framework for Cloud Immunization Information Syst...

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11th and 12th EAI International Conference on Big Data Technologies and Applications, BDTA 2021 and BDTA 2022

作者： Aladel, Lamia Sabry, Heba M. Department of Computers and Information Systems Sadat Academy Cairo Egypt Department of Computer Science Faculty of Computers and Information Sadat Academy Cairo Egypt

ISBN: (纸本)9783031336133

Immunization and vaccination do not exactly mean the same thing. The term "vaccination" refers to receiving a vaccine, which includes receiving the injection or oral dose. Immunization is the process of receiving the vaccine and developing an immunity to the disease after receiving it. By compiling immunization information into a single trustworthy source, Immunization information systems (IIS) assist healthcare professionals, families, and public health officials. The data can then be utilized to enhance vaccination rates, direct patient treatment, and ultimately lower the incidence of diseases that are preventable by vaccination. This paper seeks to identify the immunization information systems (IIS) concept its functions, clarify why it is important, propose a framework of cloud Immunization information systems, discuss the levels of this framework and its goals, challenges, and opportunities. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： information use

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Parameters Extraction of Photovoltaic Cell Using Particle Swarm Optimization 4th

Parameters Extraction of Photovoltaic Cell Using Particle Sw...

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4th International Conference on Electronic Engineering and Renewable Energy systems, ICEERE 2024

作者： Chermite, Charaf Douiri, Moulay Rachid Elamri, Oumaymah Control and Computer Science for Intelligent Systems and Green Energy Department of Applied Physics Faculty of Science and Technology Cadi Ayyad University Marrakech Morocco LAMIGEP EMSI of Marrakech Systems and Applications Engineering Laboratory National School of Applied Sciences Cadi Ayyad University Marrakech Marrakesh Morocco

ISBN: (纸本)9789819799749

Extracting parameters accurately and effectively from solar photovoltaic (PV) models is crucial for detailed simulation, evaluation, and management of PV systems. Although there has been an increase in the development of analytical, numerical, and metaheuristic methods targeting this task, accurately determining these parameters continues to be a significant challenge. This study focuses on applying Particle Swarm Optimization (PSO) for the extraction of key parameters of RTC France solar cells, a critical step towards enhancing PV system efficiency and reliability. Additionally, the PSO's performance is evaluated against other metaheuristic algorithms including Enhanced Chaotic JAYA (CJAYA), Performance-Guided JAYA (PGJAYA), and Enhanced Gradient-Based Optimizer (EGBO), underscoring the effectiveness of the proposed PSO-based approach. Utilizing MATLAB-SIMULINK, comprehensive analysis and results are presented, shedding light on the efficacy of PSO in addressing the intricacies of parameter extraction in PV systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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Blockchain and Quantum-based Collaborative Communication Framework for Telehealth

Blockchain and Quantum-based Collaborative Communication Fra...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Gajjar, Harshal Jivani, Dirgha Trivedi, Chinmay Gupta, Rajesh Jadav, Nilesh Kumar Tanwar, Sudeep Dutta, Ashit Kumar Rodrigues, Joel J.P.C. Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat India Department of Computer Science and Information Systems College of Applied Sciences AlMaarefa University Saudi Arabia Amazonas State University AM Manaus Brazil

ISBN: (纸本)9798350350548

This paper introduces a novel telehealth communication system, designed to enhance the security and integrity of medical data exchange. In the rapidly evolving digital healthcare landscape, the protection of sensitive patient information is paramount. To address this, our system uniquely combines quantum cryptography, specifically the BB84 protocol, with blockchain technology, offering a dual-layered security framework. The Quantum Layer, underpinned by the BB84 protocol, establishes quantum-secure communication channels, effectively encrypting data exchanges between patients, doctors, and hospitals. This layer guarantees that medical information remains confidential and safe from potential quantum-level eavesdropping threats. The subsequent Blockchain Layer further strengthens the system by storing these encrypted communications in an immutable blockchain ledger. This approach not only secures the data against unauthorized alterations but also provides a transparent and permanent record of all transactions, thereby enhancing the auditability of medical communications. © 2024 IEEE.

关键词： Electronic health record

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