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7th International Conference on Vocational Education and Electrical Engineering, ICVEE 2024

作者： Prasetya, Didik Dwi Muhtadi, Muis Azizah, Hanifah Nur Zain, Azlan Mohd State University of Malang Department of Electrical Engineering and Informatics Malang Indonesia Universiti Teknologi Malaysia Faculty of Computing Johor Bahru Malaysia

ISBN: (纸本)9798331505103

Concept maps are graphic representations of unique ideas widely used in learning. Concept mapping activities are often stored in an activity log which contains a record of data based on a particular time. The high activity of concept mapping can form extensive data collection and result in abundant information. An appropriate initial processing action is needed to process the concept mapping log data properly. This study aims to reduce the concept of map activity log data to obtain a reliable and noise-free dataset. This research begins with the data preprocessing stage, the initial technique in data mining that converts raw data into cleaner information and can be used for further processing. The preprocessing phase could be done using the data reduction method or adding a filter example to observe missing data on an attribute by eliminating missing observation data. The principal component analysis algorithm was used to normalize the data to become stable, neither too high nor too low. This study emphasizes that the extracted data could produce high accuracy and shorter processing time. © 2024 IEEE.

关键词： Data assimilation

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Unleashing the Potential of Blockchain and Internet of Things (IoT) Convergence: A Comprehensive Study 20

Unleashing the Potential of Blockchain and Internet of Thing...

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20th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2024

作者： Kadir, Khairunnisa A. Wahab, Nur Haliza Abdul Hartomom, Kristoko Dwi Harun, Siti Zaleha College Of Computing Informatics And Mathematics Pahang Branch Raub Campus Pahang Raub27600 Malaysia Universiti Teknologi Malaysia Faculty Of Computing Johor Skudai Malaysia Satya Wacana Christian University Faculty Of Technology Information Salatiga Indonesia

ISBN: (纸本)9798350382310

This comprehensive review explores the synergistic intersection of blockchain technology and the Internet of Things (IoT), revealing how the fusion of these two innovative technologies is revolutionizing both network security and applications. As the IoT ecosystem expands and becomes increasingly complex, the necessity for robust and efficient security measures escalates. Herein, we elucidate how Blockchain technology, renowned for its secure, decentralized nature, can play an instrumental role in safeguarding IoT devices and networks from potential threats and breaches. We conduct an in-depth exploration of the various Blockchain-enabled IoT applications, shedding light on examples that span numerous sectors such as healthcare, supply chain, smart homes, and more. These practical implementations exemplify the enhanced security, transparency, and improved efficiency that Blockchain can introduce to the IoT landscape. This review also identifies and discusses challenges faced when integrating Blockchain with IoT, such as scalability issues and energy consumption, providing suggestions for future research and developments in this area. As the digital age advances, the fusion of Blockchain and IoT holds immense potential not only to fortify security but also to redefine conventional application models. Our analysis presents a clear trajectory of progress and innovation, offering researchers, practitioners, and stakeholder's valuable insights into the future of Blockchain-enabled IoT. © 2024 IEEE.

关键词： Blockchain

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Cultural Heritage in The Digital Age: Evaluating User Experience in Virtual Reality Cultural Heritage Learning Application 27

Cultural Heritage in The Digital Age: Evaluating User Experi...

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27th International Conference on Advanced Communications Technology, ICACT 2025

作者： Afendi bin Abdul Ghani, Mohamad Shahfik Kiffli, Sudirman bin Kuan, Tenh Hock Shamsuddin, Syadiah Nor binti Wan Rahim, Normala binti Faculty of Creative Technology and Heritage Universiti Malaysia Kelantan Kelantan Bachok16300 Malaysia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Kuala Nerus21300 Malaysia

ISBN: (纸本)9791188428137

The Fourth Industrial Revolution (IR4.0) has transformed various sectors, including cultural heritage preservation, education, and tourism, through advanced technologies like virtual reality (VR). This study explores the intersection of technology and cultural heritage learning, highlighting the crucial role of user experience (UX) in VR applications. While VR holds significant potential for cultural heritage learning, existing research often emphasizes utility and usability over UX. To address this gap, the study evaluates the UX of VR applications designed for cultural heritage, specifically focusing on the Istana Jahar historical site. The objectives include assessing dimensions such as effectiveness, efficiency, attractiveness, satisfaction, emotion, engagement, attention, and perception. The research employs quantitative methods using the Design Science Research Methodology (DSRM) to guide the development and evaluation of the VR application. A cluster random sampling technique was used to recruit 113 students from Universiti Malaysia Kelantan (UMK), ensuring a representative sample with relevant educational backgrounds. Participants interacted with the VR application and completed a survey based on the developed conceptual framework. Findings indicate high mean scores across UX dimensions: Effectiveness (4.487), Efficiency (4.363), Attractiveness (4.528), Satisfaction (4.363), Emotion (4.401), Engagement (4.385), Attention (4.366), and Perception (4.416). These results demonstrate that the elements within the conceptual framework effectively enhance the UX in cultural heritage learning applications. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Virtual environments

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A Review of Deep Convolutional Neural Networks in Mobile Face Recognition

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第23期17卷 4-19页

作者： Chi, Jing On, Chin Kim Zhang, Haopeng Chai, Soo See Faculty of Computing and Informatics University Malaysia Sabah Sabah Malaysia School Information and Electrical Engineering Hebei University of Engineering Hebei China Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Sarawak Malaysia

With the emergence of deep learning, Convolutional Neural Network (CNN) models have been proposed to advance the progress of various applications, including face recognition, object detection, pattern recognition, and number plate recognition. The utilization of CNNs in these areas has considerably improved security and surveillance capabilities by providing automated recognition solutions, such as traffic surveillance, access control devices, biometric security systems, and attendance systems. However, there is still room for improvement in this field. This paper discusses several classic CNN models, such as LeNet-5, AlexNet, VGGNet, GoogLeNet, and ResNet, as well as lightweight models for mobile-based applications, such as MobileNet, ShuffleNet, and EfficientNet. Additionally, deep CNN-based face recognition models, such as DeepFace, DeepID, FaceNet, and SphereFace, are explored, along with their architectural characteristics, advantages, disadvantages, and recognition accuracy. The results indicate that many scholars are researching lightweight face recognition, but applying it to mobile devices is impractical due to high computational costs. Furthermore, noise label learning is not robust in actual scenarios, and unlabeled face learning is expensive in manual labeling. Finally, this paper concludes with a discussion of the current problems faced by face recognition technology and its potential future directions for development. © 2023 by the authors of this article. Published under CC-BY. All Rights Reserved.

关键词： Neural network models

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Utilizing Fine-Tuning ResNet-18 for Acute Leukemia Diagnosis from Blood Smear Images 2

Utilizing Fine-Tuning ResNet-18 for Acute Leukemia Diagnosis...

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2nd International Conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Sinaga, Triandes Candra, Ade Purnama, Bedy Universitas Sumatera Utara Faculty of Computer and Information Technology Medan Indonesia Telkom University Department of Informatics School of Computing Bandung Indonesia

ISBN: (纸本)9798350351613

This study explores fine-tuning ResNet-18 to enhance the accuracy of acute leukemia diagnosis from blood smear images. Early detection is crucial for patient outcomes, but the application of ResNet-18 in this context has been underutilized. We propose fine-tuning ResNet-18 to increase diagnostic precision using datasets from RSUP Haji Adam Malik Medan and Università degli Studi di Milano Statale. The model achieved 99.12% accuracy on validation and test datasets, with excellent precision, recall, F1-score, and AUCROC. Comparative analysis with non-fine-tuned ResNet-18, VGG-16, and MobileNetV2 demonstrated the superiority and stability of fine-tuning, highlighting its importance in improving diagnostic model reliability. © 2024 IEEE.

关键词： Diseases

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Financial Sustainability of Automotive Software Compliance and Industry Quality Standards 8th

Financial Sustainability of Automotive Software Compliance ...

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8th International Congress on Information and Communication Technology, ICICT 2023

作者： Dakić, Pavle Todorović, Vladimir Vranić, Valentino Faculty of Informatics and Computing Singidunum University Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia Faculty of Business Studies and Law MB University Belgrade Serbia

ISBN: (纸本)9789819930906

Achieving a high level of quality in the AV industry involves understanding the complexity of the production cycle with the constant challenges of applying appropriate standards. The need for compliance based on relevant certificates implies the creation of an environment of trust between manufacturers, component suppliers, and end customers. Research should sublimate the most current standards from various fields related to data protection, security, system sustainability, environmental management, financial sustainability, and business transparency. The success of a complex parts supply system is impossible without a stable approach to IT security. The control of production processes sometimes involves using non-standardized techniques, and one of the applicable ones is work-in-progress (WIP), which describes the use of partially finished raw materials in the stages of obtaining final products. Key points and the contribution of the current study are in getting a better overview of the situation within this area related to standards and the financial problems that can arise due to a lack of understanding of standards compliance. The main limitations within the study itself refer to the consideration of the theoretical foundations that should be used during future research related to the practical part during implementation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

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A Scalable and Lightweight Authentication Architecture for the Internet of Things (IoT) in Smart Home Applications 2

A Scalable and Lightweight Authentication Architecture for t...

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2nd Zimbabwe Conference on Information Communication and Technology, ZCICT 2023

作者： Gamundani, Attlee M. Phillips, Amelia Muyingi, Hippolyte N. Namibia University of Science and Technology Faculty of Computing & Informatics Cyber Security Department Windhoek Namibia University of the Cumberlands School of Computer and Information Sciences WilliamsburgKY United States Namibia University of Science and Technology Faculty of Computing & Informatics Windhoek Namibia

ISBN: (纸本)9798350318128

In the evolving landscape of smart home applications, ensuring robust and efficient authentication within the Internet of Things (IoT) environments is paramount. This paper presents a scalable, lightweight authentication architecture for IoT-driven smart homes. The proposed architecture, drawing inspiration from cloud computing mechanisms, introduces a trusted, smart home agent, integrating the Data-Information-Knowledge-Wisdom (DIKW) model to facilitate efficient and secure data exchange within smart homes. Our solution addresses the challenges of minimal computation and processing overheads, essential in resource-constrained IoT devices, and focuses on device-level authentication to reduce computational costs. A comparative analysis with existing models demonstrates the superiority of our architecture in terms of computational efficiency, making it an ideal candidate for scalable deployments. The architecture successfully navigates the complexities of ensuring secure communication among autonomous IoT devices, balancing the dual needs of computational efficiency and robust security, thereby promising resilience against common security threats in the smart home ecosystem. © 2023 IEEE.

关键词： Authentication

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E-mail Spam Classification Using Grasshopper Optimization Algorithm and Neural Networks

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Computers, Materials & Continua 2022年第6期71卷 4749-4766页

作者： Sanaa A.A.Ghaleb Mumtazimah Mohamad Syed Abdullah Fadzli Waheed A.H.M.Ghanem Faculty of Informatics and Computing Universiti Sultan Zainal AbidinKuala Terengganu22200Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia TerengganuKuala Terengganu21030Malaysia Faculty of Engineering University of AdenAdenYemen Faculty of Education(Aden-Saber) University of AdenAdenYemen

Spam has turned into a big predicament these days,due to the increase in the number of spam emails,as the recipient regularly receives piles of *** only is spam wasting users’time and *** addition,it limits the storage space of the email box as well as the disk ***,spam detection is a challenge for individuals and organizations *** advance spam email detection,this work proposes a new spam detection approach,using the grasshopper optimization algorithm(GOA)in training a multilayer perceptron(MLP)classifier for categorizing emails as ham and ***,MLP and GOA produce an artificial neural network(ANN)model,referred to(GOAMLP).Two corpora are applied Spam Base and UK-2011Web spam for this ***,the finding represents evidence that the proposed spam detection approach has achieved a better level in spam detection than the status of the art.

关键词： Grasshopper optimization algorithm multilayer perceptron artificial neural network spam detection approach

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Comparison of Dark Channel Prior and Contrast Limited Histogram Equalization for the Enhancement of Underwater Fish Image 4

Comparison of Dark Channel Prior and Contrast Limited Histog...

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4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022

作者： Ahmad Hijazi, Mohd Hanafi Mei, Leong Jing Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Malaysia

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

The application of artificial intelligence (AI) in aquaculture may improve the efficiency of fish farming management. Computer vision is one of the fields in AI beneficial for aquaculture. However, the underwater image quality is usually low due to light scattering through the water. Therefore, image enhancement is necessary before any further processing can be done. There are numerous image enhancement techniques for underwater images reported in the literature. In this paper, the comparison of the two most common image enhancement techniques for underwater images, the Dark Channel Prior (DCP) and Histogram Equalization (HE), is presented. The strength and weaknesses of each technique pertaining to the underwater images are also described. © 2022 IEEE.

关键词： Image enhancement

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Treat Assessment Framework in Analysing Network Threat Occurrence 8

Treat Assessment Framework in Analysing Network Threat Occur...

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8th IEEE International Conference on Recent Advances and Innovations in Engineering, ICRAIE 2023

作者： Awang, Norkhushaini Samy, Ganthan A-L Narayana Hassan, Noor Hafizah Binti Universiti Teknologi MARA College of Computing Informatics and Mathematics Selangor Malaysia Universiti Teknologi Malaysia Razak Faculty of Technology and Informatics Kuala Lumpur Malaysia

ISBN: (纸本)9798350315516

Threat assessment of network security assists in identifying potential risks and vulnerabilities. By understanding the threats, their potential impact, and the probability of their occurrence, organizations can proactively implement the necessary security controls and countermeasures to mitigate the risks. Using a mixed method methodology, this research implemented the semi-structured interview and experimental data collection to assess network threats, emphasizing the significance of a tailored framework for university networks. Semi-structured interviews were conducted with network security administrators, risk management experts, and network security experts. The process of experimental data collection involves gathering data from the university firewall during a specific time period in order to identify occurrences of potential threats. In addition, the developed threat assessment utilized machine learning methods to determine the occurrence of threats using a time series analysis algorithm. The findings contribute to developing a comprehensive threat assessment framework that supports decision-making processes for university network security. © 2023 IEEE.

关键词： Network security

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