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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Xuehua, Zhu Bashah, Nor Shahniza Kamal Guangxi Vocational and Technical College Faculty of Big Data Nanning China College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9798350369106

The increasing number of patients in hospitals, the need for telehealth among the elderly, and the impact of the pandemic highlight the need for telemedicine services. Among them, the telemedicine consultation system (TCS) is the medium for doctors to communicate with patients in the telemedicine system. However, due to the problem of safety technology, it has not been widely applied. This literature review conducts a comprehensive search using keywords in authoritative index databases such as SCI and Scopus, aiming to find out the existing security problems and solutions of TCS, and establish security technology evaluation criteria for TCS in identity authentication, system authorization, data privacy protection and data transmission security. At the same time, a TCS technology evaluation criteria model is established to classify the security level of the system. © 2024 IEEE.

关键词： Telemedicine

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Anomaly detection in ECG using recurrent networks optimized by modified metaheuristic algorithm 31

Anomaly detection in ECG using recurrent networks optimized ...

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31st Telecommunications Forum, TELFOR 2023

作者： Jovanovic, Luka Bacanin, Nebojsa Zivkovic, Miodrag Antonijevic, Milos Petrovic, Aleksandar Zivkovic, Tamara Singidunum University Faculty of Tehnical Sciences Belgrade Serbia Singidunum University Faculty of Informatics and Computing Belgrade Serbia University of Belgrade School of Electrical Engineering Belgrade Serbia

ISBN: (纸本)9798350303131

Cardiovascular disorders, a leading cause of death, demand urgent research attention. Early detection systems hold the potential to improve patient outcomes by enabling timely interventions and lifestyle adjustments. Recent advancements in artificial intelligence algorithms show promise in addressing complex challenges. This study investigates the application of Recurrent Neural Networks (RNNs) optimized with metaheuristic algorithms for anomaly detection in electrocardiogram (ECG) signals. We conducted a comparative analysis of state-of-the-art metaheuristic algorithms to determine their effectiveness in selecting optimal hyperparameters for RNN models, achieving acceptable accuracy levels. Notably, the relatively new crayfish optimization algorithm (COA) is included in the comparative analysis and has exhibited the best overall performance, demonstrating its potential for enhancing cardiovascular disorder detection. © 2023 IEEE.

关键词： Electrocardiograms

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Interaction Design for Mobile Gaming Development: A Systematic Literature Review

Interaction Design for Mobile Gaming Development: A Systemat...

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2024 IEEE International Conference on computing, ICOCO 2024

作者： Lau, Hui Sheng Lim, Tek Yong Luo, Zhiqiang Faculty of Computing and Informatics Multimedia University 63100 Selangor Cyberjaya Malaysia School of Design Foshan University 18 Jiang Wan Yi Lu Foshan528000 China

ISBN: (数字)9798331530303

ISBN: (纸本)9798331530303

Mobile gaming is an area of digital entertainment that provides platforms for social engagement, education, fun, and cognitive development. The success of mobile games is influenced by interaction design, which encompasses the user interface, usability, and user experience. This systematic review examines recent developments in interaction design approaches, usability principles, and factors affecting the uptake of interaction design in mobile gaming. Thirty primary studies, published between 2020 and 2024, were examined. In addition, the findings show that user-centered design is the most common approach, which emphasizes user participation throughout the design process. User control and freedom are highlighted as critical usability principles that emphasize the importance of users in controlling their actions and learning at their own pace. Technological factors are important for the adoption of an interaction design in mobile gaming. ©2024 IEEE.

关键词： Game design

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Viola–Jones Method for Robot Vision Purpose: A Software Technical Review 2nd

Viola–Jones Method for Robot Vision Purpose: A Software Tec...

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2nd International Congress of Electrical and Computer Engineering, ICECENG 2023

作者： Khong, Wei Leong Moung, Ervin Gubin Chong, Chee Siang School of Engineering Monash University Malaysia Selangor Bandar Sunway Malaysia Research Group Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Kota Kinabalu Malaysia

ISBN: (纸本)9783031527593

Viola–Jones (VJ) algorithm holds a prominent and undeniable position in the computer vision field. Despite not being the most recent technology, it aids research to achieve advanced levels. Researchers can practically implement the built-in detector to establish various esteemed inventions. The well-known image processing software MATLAB and iOS also offer the VJ-based functions, ‘***’ and ‘CIDetector’ in their platforms. However, it may be difficult for researchers outside the machine-learning field to choose suitable detectors. Therefore, this study intends to present the process for creating the detectors and explore the fundamental concept of a VJ detector. The software technical performances of these methods in processing 12 images with 155 faces are reviewed. This study found that the self-trained VJ detector has the most reliable accuracy since it achieved a 0.994 detection rate and precision of 1. Yet, it used the longest execution time and only be the best option if the execution time was not a significant factor. Overall, the CIDetector has the best performance in computation efficiency. It has a 0.776 detection rate and 0.833 precision. Nevertheless, it might be unable to detect small faces or faces with occluded eyes. If the user does not want any faces to be undetected, the ‘***’ is a better option as it has a 0.999 detection rate and 0.815 precision. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： MATLAB

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Exploring the Potential of Generative Adversarial Networks for Synthetic Medical Data Generation 31

Exploring the Potential of Generative Adversarial Networks f...

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31st Telecommunications Forum, TELFOR 2023

作者： Jovanovic, Luka Petrovic, Aleksandar Zivkovic, Tamara Antonijevic, Milos Bacanin, Nebojsa Zivkovic, Miodrag Singidunum University Faculty of Tehnical Sciences Belgrade Serbia Singidunum University Faculty of Informatics and Computing Belgrade Serbia University of Belgrade School of Electrical Engineering Belgrade Serbia

ISBN: (纸本)9798350303131

Proper artificial intelligence (AI) and machine learning (ML) model implementation and training are highly reliant on quality input data. However, the high costs of clinical studies and increasing privacy concerns limit the availability of medical data to researchers. This work explores the potential of applying generative adversarial networks (GAN) for generating synthetic medical data based on publicly available real-world datasets. Synthetic data is generated based on real-world observations and used to train several contemporary ML and AI models. These models are subjected to comparison with models trained on real data. Both trained models are evaluated under identical conditions on real-world testing data. These well-known, high-quality datasets are explored in this study covering diabetes and heart disease. While models trained on synthetic data show a slight decrease in objective performance, they still demonstrate viably accurate outcomes. This suggests that the introduced approach presents a potential stepping stone towards improvising data availability for researchers while respecting patients' best interests and patient privacy. © 2023 IEEE.

关键词： Generative adversarial networks

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Developing Engagement in the Learning Management System Supported by Learning Analytics

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Computer Systems Science & Engineering 2022年第7期42卷 335-350页

作者： Suraya Hamid Shahrul Nizam Ismail Muzaffar Hamzah Asad W.Malik Department of Information System Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Department of Computing School of Electrical Engineering and Computer Science(SEECS)National University of Sciences and Technology(NUST)IslamabadPakistan

Learning analytics is an emerging technique of analysing student par-ticipation and *** recent COVID-19 pandemic has signiﬁcantly increased the role of learning management systems(LMSs).LMSs previously only complemented face-to-face teaching,something which has not been possible between 2019 to *** date,the existing body of literature on LMSs has not analysed learning in the context of the pandemic,where an LMS serves as the only interface between students and ***,productive results will remain elusive if the key factors that contribute towards engaging students in learning are notﬁrst identiﬁ***,this study aimed to perform an exten-sive literature review with which to design and develop a student engagement model for holistic involvement in an *** required data was collected from an LMS that is currently utilised by a local Malaysian *** model was validated by a panel of experts as well as discussions with *** is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.

关键词： Engagement analysis learning analytics learning management system student engagement

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The synergy of Linear Regression, Fuzzy Functional Dependencies and Linguistic Summaries: A Case of Heat Islands in Bratislava 29

The synergy of Linear Regression, Fuzzy Functional Dependenc...

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29th International Conference on Information, Communication and Automation Technologies, ICAT 2023

作者： Minarikova, Erika Vuceticc, Miljan Hudec, Miroslav University of Economics in Bratislava Faculty of Economic Informatics Bratislava Slovakia Vlatacom Institute of High Technology Artificial Intelligence Department Belgrade Serbia Singidunum University Faculty of Informatics and Computing Belgrade Serbia VSB-Technical University of Ostrava Faculty of Economics Ostrava Czech Republic

ISBN: (纸本)9798350399837

The last decade has witnessed a rapid development of computational intelligence models in many scientific and industry fields. One of challenges is the lack of interpretability and explainability of the mechanism underlying the models. In this paper, we propose a methodology for evaluating and explaining influences by linear regression and by fuzzy logic techniques, which have been shown as promising approaches for the explainable computational intelligence. Precisely, fuzzy functional dependencies are able to verify regression result and explain intensities linguistically, whereas linguistic summaries can reveal intensities of relations among the subdomains of considered features. The proposed synergy is experimentally evaluated on the problem of explaining the influence of geographical features on the urban heat islands in the Bratislava downtown. Urban planning and development should consider environmental aspects. Thus, a support which is validated by three diverse approaches is more reliable. © 2023 IEEE.

关键词： Smart city

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The Integration of Deep Learning Techniques and Big Data Analytics for Improved Breast Cancer Diagnosis and Treatment: A Systematic Review

The Integration of Deep Learning Techniques and Big Data Ana...

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Information and Communication Technology for Development for Africa (ICT4DA), International Conference on

作者： Hambisa Mitiku Gebre Getachew Mamo Wegari Department of Information Science Faculty of Computing and Informatics Jimma University Jimma Ethiopia Department of Information Technology Faculty of Computing and Informatics Jimma University Jimma Ethiopia

ISBN: (数字)9798331527792

ISBN: (纸本)9798331527808

Background:- Breast cancer is one of the most common and lethal diseases in the world. Traditional breast cancer diagnostic and prognosis procedures usually involve significant human talent and can be time-consuming and subjective, leading to potential errors and treatment delays. Two recent technical advancements, deep learning, and big data analytics are promising to improve breast cancer diagnosis and therapy. As a result, this systematic review aims to examine specific papers that describe deep learning techniques and big data analytics in the context of breast cancer diagnosis and ***: Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), peer-reviewed articles published in the English language from January 2020 to August 2023 were selected from electronic databases such as PubMed, ACM, Digital Library, and Science Direct, as well as citations and manual searches. This review paper takes into account papers about deep learning algorithms, big data analytics, the efficacy of deep learning and big data analytics, as well as the problems and limitations of merging deep learning methods with big data analytics. Articles that were not original or in English were not ***: - Ten articles were identified for this review. The finding showed that deep-learning techniques play a great role in analyzing vast datasets to identify malignant cells or tumors, aiding radiologists in accurate diagnoses and improving patient outcomes. Big data analytics in breast cancer diagnosis and treatment can improve accuracy, efficiency, and patient-centered care. Deep learning techniques are utilized with big data, enhancing screening test accuracy and guiding diagnostic procedures, especially for image-based scanning that leads to early breast cancer identification, improving patient outcomes, and potentially enhancing diagnostics. Obtaining huge volumes of high-quality data for training deep learning models is a challenge and limita

关键词： Deep learning Training Accuracy Merging Medical treatment Manuals Big Data Breast cancer Prognostics and health management Tumors

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Well-founded Semantics for Recursive SHACL 4

Well-founded Semantics for Recursive SHACL

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4th International Workshop on the Resurgence of Datalog in Academia and Industry, Datalog-2.0 2022

作者： Chmurovic, Adrian Šimkus, Mantas Faculty of Informatics TU Wien Austria Department of Computing Science Umeå University Sweden

W3C has recently introduced SHACL as a new standard for integrity constraints on RDF graphs. Unfortunately, the standard defines the semantics of non-recursive constraints only, which has spurred recent research efforts into finding a suitable, mathematically crisp semantics for constraints with cyclic dependencies. To this end, Corman et al. [1] introduced a semantics related to supported models known in logic programming, while Andresel et al. [2] presented a semantics based on stable models known in Answer Set Programming (ASP). In this paper, we argue that recursive SHACL can be naturally equipped with a semantics inspired in the well-founded semantics for (recursive) DATALOG queries with default negation. This semantics is not only intuitive, but it is also computationally tractable, unlike the previous proposals. To draw a connection with the classic definition of well-founded semantics in logic programming, we provide a simple translation of recursive SHACL under the well-founded semantics into propositional logic programs under the well-founded semantics. This translation is not only of theoretical interest: It can be efficiently implemented using the functionality of standard RDF triple stores (specifically, by issuing a small number of SPARQL queries), followed by an efficient evaluation using an existing engine for computing the well-founded model of a propositional logic program. © 2022 Copyright for this paper by its authors.

关键词： Semantics

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Cybersecurity and Smart Cities: Current Status and Future

Cybersecurity and Smart Cities: Current Status and Future

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2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology, ICES and T 2023

作者： Habib, Muhammad Yasir Qureshi, Haseeb Ahmad Khan, Shujahat Ali Mansoor, Zara Chishti, Abdul Rehman The Islamia University of Bahawalpur Faculty of Engineering Dept. of Electronic Engineering Pakistan Bournemouth University Faculty of Computing Dept. of Computing and Informatics Bournemouth United Kingdom Charles Darwin University College of Engineering IT and Environment Darwin Australia

ISBN: (纸本)9781665455602

A Smart city implements the latest IoT and information and communication technologies (ICT) to improve the quality of urban city administrations, decrease expenditures, asset management and interconnect citizens of a Smart city. Smart cities offer numerous advantages like improved energy productivity, management, healthcare facilities, efficient transport systems, proper waste and water management, and individual security. Nonetheless, this reliance on ICT and IoT technologies makes a Smart city prone to digital cyber assaults. These technologies are vulnerable to many security issues like Information theft, Eaves-dropping attack, Denial of service, Communication delays, Data manipulation, IoT security attacks, Communication interception, Jamming, Sensor failure, insecure API, and Remote exploitation. This research study intends to address opinions on cybersecurity technologies, vulnerabilities, and cybercrime awareness based on the systematic literature review 'PRISMA Model' as our research method and help researchers and practitioners to look for innovative Smart City solutions. Our research endeavors to momentarily depict the central ideas of digital security and protection issues related to Smart city areas and uncover digital cyber-Attacks that focus on Smart city communities in the literature. In brief, the focus of this research is to explore and review the aspects of Smart city cybersecurity issues, Smart city vulnerabilities related to information security, and provide a comprehensive research framework that will help the researchers and practitioners explore this area of research. © 2023 IEEE.

关键词： Cybersecurity

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