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

作者： Arifin, Fikri Firas Tajul Idrus, Zanariah Halim, Shamimi A. Ahmarofi, Ahmad Afif Ahmad, Khairul Adilah Shah Alam College of Computing Informatics and Mathematics Selangor Shah Alam Malaysia Kedah Branch College of Computing Informatics and Mathematics Merbok Kedah Malaysia

ISBN: (纸本)9798350315516

Water quality is crucial as it directly affects the ecosystem and human health. However, current water quality classification methods are inefficient because they do not compare prediction accuracy between machine learning methods. In this regard, the objective of this study is to classify water quality based on the proposed machine learning tools. To fulfill that, a preliminary study was conducted by collecting related information in the research domain through articles, electronic books, and online databases. The data collection for the prototype's dataset was obtained from an electronic book published by the Pakistan Council of Research in Water Resources 2021. Subsequently, the data pre-processing phase was conducted by using WEKA software which includes the crucial steps to transform the data into a cleaner format and make the model more accurate. The model for each technique was developed using Python in Jupyter Notebook. The results of the accuracy score for each model were also conducted in this phase. The findings of this research show that the Decision Tree model performs excellently with an accuracy of 97.37% compared to the Support Vector Machine and K-Nearest Neighbour models, with an accuracy of 95.69% and 74.72%, respectively. Consequently, implementing a multi-class classification system can help future researchers classify more accurately and reduce the misclassification of water quality. © 2023 IEEE.

关键词： Decision trees

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A Foresight Course Framework for Undergraduates Designing Human-Centric Solutions 10

A Foresight Course Framework for Undergraduates Designing Hu...

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10th International HCI and UX Conference in Indonesia, CHIuXiD 2024

作者： Harun, Afdallyna Fathiyah Universiti Teknologi Mara College of Computing Informatics and Mathematics School of Computing Sciences Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9798350380439

The growing complexity of global challenges that advocate human values necessitates a shift towards future oriented, human-centric design approaches. Such thinking is embedded in a foresight-driven coursework, part of the Bachelor of Information Technology (Hons) offered in Universiti Teknologi MARA. It trains students to anticipate future trends and co-create innovative, resilient and sustainable solutions. In this paper we elaborate how foresight methodology, when integrated with participatory design approach, can result in powerful human-centric solutions that are future-proof. Through future tools such as horizon scanning, the seven questions technique, issues paper, driver mapping, futures wheel, SWOT analysis, prototyping and road mapping, students engage with stakeholder to address present and future challenges, equipping them to design adaptable, human-centric technological solutions. © 2024 IEEE.

关键词： Students

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A Web-based Management System for Diagnostic Laboratory with Business Process Re-Engineering and Data Analytics 14

A Web-based Management System for Diagnostic Laboratory with...

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14th International Conference on System Engineering and Technology, ICSET 2024

作者： Leynes, Jhun-Jhun P. Amorado, Ryndel V. Batangas State University College of Informatics and Computing Sciences TNEU Alangilan Campus Batangas City Philippines Batangas State University College of Informatics and Computing Sciences TNEU Lipa Campus Lipa City Philippines

ISBN: (纸本)9798331504526

Management information systems are a challenge for many small businesses. With fast-changing technology, data management has become an integral part of business processes, especially in the healthcare industry. This study uses Business Process Re-Engineering (BPR) and Data Analytics for a Diagnostic Laboratory to improve its operational efficiency through a web-based management system. The obsolete system, consisting of eight modules, is replaced with a sophisticated system involving twenty-one modules. The goal is to evaluate the impact of technology on business operations and user satisfaction. The results indicate that the most recent technology enables board members to monitor corporate performance from any location using various web browsers. The database securely saves and categorizes all operational data. Transactions, test results, and reports are instantly created in PDF format. Subsequently, the gathered information is utilized by means of descriptive and prescriptive analysis. The system acceptance is also assessed using a questionnaire that adheres to the ISO 25010 standards. With an optimal score of 5.0, the results showed a weighted average of 4.79 ('Strongly Agree'), which is significantly higher than the prior system average of 3.69 ('Agree'). The conclusions emphasize that the system has a crucial role in remote management, efficient database management, improved operational efficiency, and reduced turnaround time. Recommendations encompass the integration of digital payment methods for transactions and advocating the established system as a benchmark for other diagnostic laboratories in the health industry. This research has a significant impact on the improvement of diagnostic laboratory management systems. © 2024 IEEE.

关键词： Web browsers

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Fault Management Cyber-Physical Systems in Virtual Storage Model

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Computers, Materials & Continua 2022年第2期70卷 3781-3801页

作者： Kailash Kumar Ahmad Abdullah Aljabr College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Kingdom of Saudi Arabia

On average,every two years,the amount of data existing globally *** development will be affected and improved by Cyber-Physical Systems(CPS).The number of problems remained even though developments helped Information Technology experts extract better value from their storage *** of poor interoperability between different vendors and devices,countless numbers of Storage Area Networks were *** setup used for data storage includes a complex and rigid arrangement of routers,switch,hosts/servers,storage *** have evaluated the performance of routing protocol Transmission Control Protocol(TCP)and Fibre Channel Protocol(FCP)under different network scenario by Network Simulator(NS)-3 *** simulated the Node Failure and NetworkCongestion issuewithDoS attacks and a counter effect on the Packet Distribution Ratio and End-to-End Delay efficiency metrics with different nodes and speed of node *** study is performed for the Simple NetworkManagement Protocol(SNMP)on FCP *** results proved that the proposed method isolates the malicious and congested nodes and improves the Network’s performance.

关键词： CPS data storage virtualization TCP FCP

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Deep Learning Food Detection and Calories Counter

Deep Learning Food Detection and Calories Counter

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2023 IEEE International Conference on computing, ICOCO 2023

作者： Ibrahim, Shafaf Arif Aiman Wan Hasnan, Wan Muhamad Md Ghani, Nor Azura Fariza Abu Samah, Khyrina Airin Abu Mangshor, Nur Nabilah Ahmad Fadzil, Ahmad Firdaus Janor, Roziah Mohd School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi Mara Shah Alam Malaysia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi Mara Melaka Branch Jasin Malaysia

ISBN: (纸本)9798350302684

Monitoring and managing dietary intake plays a vital role in maintaining a healthy lifestyle. However, accurately tracking food consumption and estimating calorie intake can be challenging. This paper presents a deep learning-based approach of You Only Look Once version 4 (YOLOv4) model for food detection and calorie counting. Leveraging the power of deep neural networks, the proposed study automatically detects and classifies food items from images and provides real-time estimation of their calorie content. Seven classes of food which are fried noodles, fried rice, kaya toast, nasi lemak, roti canai, fried chicken, and fried egg were addressed, by training the model on a diverse and well-annotated food dataset. We also tackle the issue of calorie estimation. Experimental evaluations of the proposed YOLOv4 for food detection demonstrates 96.07% of accuracy. Thus, it could be deduced that the proposed deep learning-based food detection and calorie counter have the potential to significantly improve dietary monitoring and contribute to the promotion of healthier eating habits. © 2023 IEEE.

关键词： Deep neural networks

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Automatic Malicious URL Detection with User Notification using Well-known API 22

Automatic Malicious URL Detection with User Notification usi...

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22nd IEEE Student Conference on Research and Development, SCOReD 2024

作者： Zulkipli, Nurul Huda Nik Fuzi, Mohd Faris Mohd Salni, Muhammad Khairul Ariffin Universiti Teknologi MARA College of Computing Informatics and Mathematics Melaka Malaysia Perlis Malaysia

ISBN: (纸本)9798331510077

This study an innovative automatic malicious URL detection and user notification app using a well-known API. With approximately 3.8 billion users in April 2020, the background study underscores the significant risks posed by deceptive URLs, such as phishing attacks. The problem statement highlights the key challenges: the surge in mobile device usage, the increasing number of suspicious URLs, user awareness gaps, and the limitations of current URL scanners in providing actionable responses. To address these issues, the study introduces a novel approach by designing, developing, and testing an app that detects malicious URLs and allow users to ignore, quarantine, or block these threats. The methods involve leveraging APIs, such as VirusTotal and ***, alongside rigorous validity and functionality tests. Key results demonstrate the app's effectiveness in real-time threat detection and user guidance. The app's unique feature set, including user-friendly notifications and customizable threat responses, set it apart from any existing solutions. The conclusion affirms the app's potential to significantly enhance mobile security, offering a safer digital experience for users. This innovative solution addresses current limitations and provides a proactive approach to mobile security, ensuring users to be better protected against evolving cyber threats. © 2024 IEEE.

关键词： Phishing

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STATE:Learning structure and texture representations for novel view synthesis

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Computational Visual Media 2023年第4期9卷 767-786页

作者： Xinyi Jing Qiao Feng Yu-Kun Lai Jinsong Zhang Yuanqiang Yu Kun Li College of Intelligence and Computing Tianjin UniversityTianjin 300350China School of Computer Science and Informatics Cardiff UniversityCardiff CF244AGUK

Novel viewpoint image synthesis is very challenging,especially from sparse views,due to large changes in viewpoint and *** image-based methods fail to generate reasonable results for invisible regions,while geometry-based methods have difficulties in synthesizing detailed *** this paper,we propose STATE,an end-to-end deep neural network,for sparse view synthesis by learning structure and texture *** is encoded as a hybrid feature field to predict reasonable structures for invisible regions while maintaining original structures for visible regions,and texture is encoded as a deformed feature map to preserve detailed *** propose a hierarchical fusion scheme with intra-branch and inter-branch aggregation,in which spatio-view attention allows multi-view fusion at the feature level to adaptively select important information by regressing pixel-wise or voxel-wise confidence *** decoding the aggregated features,STATE is able to generate realistic images with reasonable structures and detailed *** results demonstrate that our method achieves qualitatively and quantitatively better results than state-of-the-art *** method also enables texture and structure editing applications benefiting from implicit disentanglement of structure and *** code is available at http://***/faculty/likun/projects/STATE.

关键词： novel view synthesis sparse views spatioview attention structure representation texture representation

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Performance Analysis of Lightweight Vision Transformers and Deep Convolutional Neural Networks in Detecting Brain Tumors in MRI Scans: An Empirical Approach 8

Performance Analysis of Lightweight Vision Transformers and ...

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8th International Conference on Biomedical Imaging, Signal Processing, ICBSP 2023

作者： Montalbo, Francis Jesmar P. Hernandez, Lovely Rose T. Palad, Lanie P. Castillo, Ria C. Alon, Alvin S. De Ocampo, Anton Louise P. College of Informatics and Computing Sciences Batangas State University Philippines

ISBN: (纸本)9798400716584

Vision transformer models began gaining recognition alongside NLP. However, their performance compared to Convolutional Neural Network (CNN) models in this domain still requires more significant investigations. Hence, this article comprehensively analyzes their impact and effectiveness against CNN models in medical imaging. We conducted experiments using ViT, MobileViT, and Swin transformers against a pure CNN ConvNeXt trained on Magnetic Resonance Image (MRI) scans. While our findings show promising advancements in imaging with transformers, we observed challenges in their scalability and deployment due to their cost and complexity. We also noticed that they require more medical data, specifically higher-quality MRI scans, when considering better reliability. Nonetheless, comparing their performance in terms of accuracy, even with such limitations, these visual transformer models have shown better detection and diagnosis of brain tumors in MRI scans compared to pure CNN models selected in this study. © 2023 ACM.

关键词： Biomedical engineering

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E-CommerceShield: A Framework for Enhanced Security in E-Commerce with Awareness, DNS Matching, and Blockchain Integration 30

E-CommerceShield: A Framework for Enhanced Security in E-Com...

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30th IEEE International Conference on Telecommunications, ICT 2024

作者： Belghith, Aymen College of Informatics and Computing Saudi Electronic University Computer Science Department Saudi Arabia

ISBN: (纸本)9798350356694

Security attacks on e-commerce platforms are increasingly prevalent, posing significant risks to both users and organizations. These attacks aim to cause financial harm or disrupt e-commerce services, highlighting the critical need for robust security measures. This study investigates key security attacks targeting e-commerce platforms and evaluates the efficacy of various attack detection methods. Through a comprehensive literature review and descriptive analysis, the study identifies financial frauds, phishing, and Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks as the major threats to e-commerce systems. Furthermore, the study examines different detection methods, revealing that blockchain-based security systems emerge as the most effective solution against a range of identified security attacks. Building upon these findings, this paper proposes a novel framework, dubbed e-CommerceShield, which integrates user awareness, DNS matching, and blockchain technology to enhance security in e-commerce environments. The framework prioritizes proactive security measures, empowers users with awareness and education, and leverages advanced technologies to detect and prevent security threats effectively. By adopting the e-CommerceShield framework, e-commerce platforms can fortify their security posture and safeguard the integrity of online transactions, thereby fostering trust and confidence among users in the digital marketplace. © 2024 IEEE.

关键词： Blockchain

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A Taxonomy of Factors that Influence the Multiple-Cloud computing Utilization 13

A Taxonomy of Factors that Influence the Multiple-Cloud Comp...

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13th International Conference on Computer Technologies and Development, TechDev 2024

作者： Al-Qahtani, Hassan Saad Saudi Electronic University College of Computing and Informatics Department of Information Technology Saudi Arabia

ISBN: (纸本)9798331539771

There are various factors that associated with the architecture of Multiple-Cloud computing, which have negative impact that reduce the utilization of MCC. Our study is proposing a comprehensive taxonomy of these factors. The proposed classification will help to apply efficient solutions/approaches that prevent, avoid, or reduce the negative impact of these factors;and enhance dealing with these factors. This study identifies and categorize the factors into five primary dimensions: operational factors, data privacy and integrity factors, performance factors, and law and legislations factors. © 2024 IEEE.

关键词： Cloud computing architecture

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