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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Wismantoro, Yohan Westri Kekalih Susilowati, M.G. Himawan, Heribertus Dian Nuswantoro University Faculty of Economics and Business Semarang Indonesia Soegijapranata Catholic University Faculty of Economics and Business Semarang Indonesia Dian Nuswantoro University Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350339215

Virtual Reality Technology for tourism (VR Tourism) can be a means to boost tourist visits. However, this opinion is still controversial. VR Tourism, as a VR technology, provides a pleasant experience for its users and is supposed to encourage people to visit a tourist site. As a result, evaluating VR tourism's effectiveness in mood management becomes critical. This study develops a research model on how Mood Management Theory (MMT) influences visit intentions. This study uses an experimental approach by providing an experience using VR Tourism Making Batik with natural dyes. The data were analyzed using a path analysis approach processed using SmartPLS 3.0. The findings indicate that Entertainment Experience, Education Experience, Esthetic Experience, and favourably impact the perception of positive mood enhancement. However, the intention to visit does not display any significant association with the perception of positive mood improvement. © 2023 IEEE.

关键词： Virtual reality

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Leveraging Social Learning for Improved Cybersecurity Maturity: A Case Study Using the NIST Framework

Leveraging Social Learning for Improved Cybersecurity Maturi...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Marcel Meyliana Hendric Spits Warnars, Harco Leslie Nugraha Mursitama, Tirta BINUS Graduate Program Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Krida Wacana Christian University Information Systems Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta Indonesia BINUS Business School Bina Nusantara University Management Department Jakarta Indonesia

ISBN: (纸本)9798350379839

This research shows that social learning can be used to increase an organization's cybersecurity maturity level. Using a literature study and case study approach. Literature studies are used to identify social learning's key success factors (KSF) and challenges in general. Then, the case study was performed in the context of assessing the maturity level of information security using the NIST Cybersecurity framework at ABC Software House, a small-scale software development company in Indonesia. Assessment activities are performed through FGDs which then also identify the most relevant social learning' KSF to increase the organization's information security maturity level. Next, referring to the selected KSF, a process of identifying and mapping social learning' challenges was carried out. The integration of social learning can help organizations gain better focus and understanding in nontechnical contexts to increase their maturity level. This research highlights that integrating social learning with the NIST cybersecurity framework can provide organizations with better focus and perspective for formulating non-technical solutions. This study also enriches the existing literature on social learning in cybersecurity and offers practical insights for organizations looking to improve their cybersecurity resilience. © 2024 IEEE.

关键词： case study cybersecurity maturity level NIST social learning

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TinyML-Based Gait Recognition for User Detection on an STM32L4 IoT Node 9

TinyML-Based Gait Recognition for User Detection on an STM32...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Hassan, Hateem Abdullah, M. Hussain, Muhammad Zunnurain Hasan, Muhammad Zulkifl Mustafa, Muzzamil Khalid, Aqsa Awan, Rimsha Hussain, Usman Khan, Zohaib Ahmed Javaid, Arslan University Lahore Department of Computer Engineering Information Technology Punjab Pakistan Bahria University Lahore Campus Dept. of Computer Science Pakistan University of Central Punjab Lahore Pakistan Faculty of Information Technology Department of Computer Science Pakistan National College of Business Administration And Economics Department of Computer Science Lahore Pakistan Information Technology University Lahore Pakistan University of Home Economics Pakistan

ISBN: (纸本)9798350394474

Gait recognition stands out as a robust biometric tool for discerning users. Yet, adapting it to devices with limited resources, such as the STM32L4 microcontroller, demands cutting-edge strategies. This research unveils an innovative TinyML methodology, leveraging a specially-designed Convolutional Neural Network (CNN). Notably, our bespoke CNN model showcased a remarkable 97.3% accuracy in pinpointing users on the STM32L4 system. © 2024 IEEE.

关键词： Convolutional neural networks

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Digital Learning Ecosystem: Online Concept for Engineering Education 65

Digital Learning Ecosystem: Online Concept for Engineering E...

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65th IEEE Annual International Scientific Conference on Power and Electrical Engineering of Riga Technical University, RTUCON 2024

作者： Zabasta, Anatolijs Kazymyr, Volodymyr Kunicina, Nadezhda Velihorskyi, Oleksandr Riga Technical University Faculty of Computer Science Information Technology and Energy Riga Latvia Chernihiv Polytechnic National University Information and Computer Systems Department Chernihiv Ukraine Chernihiv Polytechnic National University Radio Engineering and Embedded Systems Department Chernihiv Ukraine

ISBN: (纸本)9798350365771

This article examines the development of a Digital Learning Ecosystem (DLE) for engineering education, supported by online learning, within the framework of Erasmus+ international educational projects. We hypothesize that a DLE can address the challenges posed by rapid technological changes associated with Industry 4.0 and digital transformation, thus transforming engineering education to meet modern industry needs. Building on the earlier Erasmus+ CybPhys project, which established a Sharing Modelling and Simulation Environment (SMSE) for digitalizing online technical courses, the DIGITRANS project aims to enhance this architecture to include remote laboratories through the Sharing Remote Experiment Environment (SREE) platform. The project involves acquiring hardware and open-source software for SREE and establishing two physical remote laboratories. A study conducted in spring 2023, using the Technology Acceptance Model framework, indicated positive student perceptions of SMSE, with students believing it would enhance learning outcomes and expressing intentions to use the platform frequently. The efficacy of the DLE in addressing technological advancement challenges will be further evaluated through post-ante assessments and feedback from prospective employers and stakeholders, focusing on the implementation of industry recommendations and the correlation between pre- and post-implementation survey responses from industry and academic experts. © 2024 IEEE.

关键词： Open source software

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Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

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computer Modeling in Engineering & sciences 2024年第9期140卷 2795-2823页

作者： Naif Alotaibi A.S.Al-Moisheer Ibrahim Elbatal Mohammed Elgarhy Ehab M.Almetwally Department of Mathematics and Statistics Faculty of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Mathematics College of ScienceJouf UniversityP.O.Box 848Sakaka72351Saudi Arabia Mathematics and Computer Science Department Faculty of ScienceBeni-Suef UniversityBeni-Suef62521Egypt Department of Basic Sciences Higher Institute of Administrative SciencesBelbeisEgypt Faculty of Business Administration Delta University for Science and TechnologyGamasa11152Egypt

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(SGLE)*** SGLE distribution utilizes the sine transformation to enhance its *** updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability *** suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique *** model includes many well-known lifespan distributions as separate *** suggested model is accompanied with a range of statistical *** model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored *** order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing *** relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

关键词： Sine G family generalized linear failure rate progressively censored data moments maximum likelihood estimation Bayesian estimation simulation

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Experiences in PCB manufacturing with ultra-lowcost and home-made CNC machine 16

Experiences in PCB manufacturing with ultra-lowcost and home...

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Avila, Bernardo Yaser LeON Vazquez, Carlos Alberto GarcIA Baluja, Osmel PERez Dominguez, Luis Alberto Quintero Cotfas, Daniel Tudor Cotfas, Petru Adrian Transilvania University of Braşov Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers Braşov Romania University of Sancti Spiritus 'José Martí Pérez' Faculty of Business and Technical Sciences Department of Computer Engineering Sancti Spiritus Cuba

ISBN: (纸本)9798350371154

In the context of printed circuit board (PCB) manufacturing, accessibility and affordability are pivotal, especially for individuals and institutions with limited financial resources. The advent of ultra-low-cost and homemade computer numerical control (CNC) machines offers a promising solution to address these concerns. However, the plethora of online resources often presents solutions fraught with practical challenges. This paper delves into firsthand experiences in utilizing such technologies, navigating the delicate balance between cost-effectiveness and functionality in prototyping. By examining the inherent obstacles, it aims to offer valuable insights for those seeking to achieve PCB manufacturing goals with minimal resources. © 2024 IEEE.

关键词： Cost effectiveness

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Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

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computer Modeling in Engineering & sciences 2024年第4期139卷 801-816页

作者： D.Dorathy Prema Kavitha L.Francis Raj Sandeep Kautish Abdulaziz S.Almazyad Karam M.Sallam Ali Wagdy Mohamed Department of Mathematics Voorhees CollegeVelloreTamil NaduIndia Chandigarh Group of Colleges JhanjeriMohaliPunjabIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Science and Technology School of IT and SystemsUniversity of CanberraCanberraAustralia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan

The intuitive fuzzy set has found important application in decision-making and machine *** enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images *** image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye *** degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal *** proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between *** methodology was used to clarify the input images and make them adequate for the process of glaucoma *** objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were *** the peak regions were identified,the recurrence relationships among those peaks were then *** partitioning was done due to varying degrees of similar and dissimilar concentrations in the *** and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and *** distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.

关键词： Convolutional Neural Network(CNN) glaucomatous eyes fuzzy difference equation intuitive fuzzy sets image segmentation retinal images

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Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

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computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

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The Intensive Model Design using FL for Smart HC System Design 4

The Intensive Model Design using FL for Smart HC System Desi...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Raman, Ramakrishnan Verma, Apurv Kumar, Vikram Rastogi, Shailesh Pillai, Biju G. Meenakshi, R. India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India Srv Media Pvt. Limited India India Sri Balaji University Faculty of Management It & Business Analytics Pune India Chennai Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350360165

Using cutting-edge technology like wearables, internet access of Things, and smartphones, smart healthcare has become a crucial component of health policy services. This revolutionary method enables seamless connection and ongoing information access between patients, medical equipment, the facilities, allowing for intelligent responses to a variety of demands within the medical ecosystem. No matter when or where they are, patients may get urgent assistance, diagnostic services, and monitoring via the digital platform of the Smart Health care Management systems (SHMS). This research emphasizes innovation with direct healthcare services and suggests the use of the Smart the management of healthcare Examination using Fuzzy Decision-Taking (SHME-FDM) technique to measure the effectiveness of technology integration. Furthermore, the Fuzzy Asymmetric Hierarchy Process-Technique for Orders of Preference by The sameness to Ideal Solution (Fuzzy AHP-TOPSIS) is used to evaluate the privacy protection and healthcare data inside the SHMS. In order to make predictions about healthcare, the research uses a fuzzy-based neural network. Through experimental analysis, reliability, accuracy, and error rates are evaluated. Notably, a security risk analysis highlights the proposed fuzzy model's potential for protecting healthcare data by demonstrating its improved risk assessment performance when compared to current methods. © 2024 IEEE.

关键词： Risk assessment

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Enhancing School and College Attendance Using Advanced Technology 3

Enhancing School and College Attendance Using Advanced Techn...

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3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Budiarto, Mukti Audiah, Sipah Astuti, Eka Dian Sanjaya, Yulia Putri Ayu Firli, M. Zaki University of Raharja Faculty of Informatics Engineering Tangerang Indonesia Cai Sejahtera Indonesia Faculty of Digital Business Tangerang Indonesia Asosiasi Dosen Indonesia Faculty of Digital Business Tangerang Indonesia Alfabet Inkubator Indonesia Faculty of Retail Management Tangerang Indonesia Rey Faculty of Computer Systems Tangerang Indonesia

ISBN: (纸本)9798350367492

In today digital era traditional manual attendance systems in educational institutions are both inefficient and outdated. This study assesses the impact of implementing technology-driven attendance systems developed using the Waterfall Model, which promises to revolutionize educational settings by enhancing operational efficiency and reducing administrative burdens. The research involved deploying automated attendance software across various institutions and comparing its efficacy with traditional methods in terms of time efficiency, accuracy, and cost. The results indicate that technology-based systems significantly reduce the time and effort required for attendance recording, minimize manual errors, and offer real-time data that helps quickly identify attendance patterns and issues. These improvements lead to enhanced student engagement and accountability. Moreover the transition to automated systems results in considerable administrative cost savings by decreasing reliance on extensive paperwork, thereby allowing for a better allocation of resources towards improving the educational experience. Ultimately, the study confirms that adopting modern attendance monitoring technologies not only streamlines processes but also enhances the educational framework, making institutions more efficient and responsive. This shift benefits administrative and educational outcomes and sets a robust foundation for future educational practices, highlighting the critical role of technology in advancing educational environments. © 2024 IEEE.

关键词： Educational technology

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