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Evaluation of Manifold Dual Contouring Algorithms Based on k-d tree and Octree Data Structures

Informatica (Slovenia) 2024年第3期48卷 399-418页

作者： Ramaijane, Thabang Hlomani, Hlomani Zlotnikova, Irina Maupong, Thabiso Department of Computing and Informatics School of Pure and Applied Sciences Botswana International University of Science and Technology Botswana Botswana

This study evaluated the performance and efficiency of manifold dual contouring algorithms using k-d trees and octrees, therefore, addressing a critical gap in comparative analysis of these data structures. Despite the popularity of k-d trees and octrees in isosurface extraction, their performance has not been empirically compared. This research specifically focuses on visualization quality, performance metrics, and efficiency across various simplification error thresholds. A comprehensive comparative analysis was conducted to identify the conditions under which each data structure is most suitable. Both algorithms employed the manifold vertex clustering scheme for dual contouring of isosurfaces. The methodology involved evaluating visual output, build time, extraction time, and efficiency based on triangle counts during the simplification process. Computational experiments demonstrated that the octree-based algorithm is superior for rendering large models, producing an average of 20% more visual detail due to a higher triangle count. In contrast, the k-d tree-based algorithm showed a 40% reduction in build time and a 35% reduction in extraction time, making it more efficient for processing large implicit models by reducing geometric complexity. These findings provide metrics to assist researchers and practitioners in selecting the most suitable adaptive data structure for achieving optimal simplification results in manifold dual contouring algorithm implementations. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Trees (mathematics)

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Classification Framework for Autoimmune Liver Disease using Machine Learning and Deep Learning Techniques 5

Classification Framework for Autoimmune Liver Disease using ...

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5th technology Innovation Management and Engineering Science International Conference, TIMES-iCON 2024

作者： George, E. Ben Rosline, G. Jeba Varghese, Abraham Rajesh, Gnana D. Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Muscat Oman Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Al Mussanah Oman

ISBN: (纸本)9798350362602

—Autoimmune diseases affect people of all ages, genders, and ethnic backgrounds, making it one of the most widespread health issues we face today. These disorders occur when the immune system mistakenly targets healthy cells within the body and causing a wide range of potentially life-threatening diseases. There are over 80 recognized autoimmune disorders, including type-1 diabetes, rheumatoid arthritis, Graves' disease, alopecia, celiac disease, and autoimmune liver disease(AiLD). Autoimmune liver disease is one such chronic disorder characterized by liver inflammation and damage. If not detected on time and untreated within the given time, it might lead to liver cirrhosis or liver cancer. Identifying and treating autoimmune liver disease is a complex and time consuming process which involves symptom analysis, laboratory tests, and clinical assessments. Detecting the disease can be more challenging because many symptoms of autoimmune liver diseases overlap with those of other autoimmune conditions. As a result, there is a need for an optimized, accurate, efficient, and cost-effective methodology to identify the disease without extensive and invasive procedures such as organ transplants. This paper introduces an innovative approach that employs the power of supervised machine learning and deep learning techniques to predict the onset of autoimmune liver diseases in advance. The machine learning model is constructed using a comprehensive dataset comprising the complete medical history of patients, physical examination records, histopathology and genetic data. Along with the machine learning model, the deep learning model is also developed for liver MRI images of various patients to make accurate prediction. This system provides a second opinion for medical professionals that may avoid the need for extensive and invasive medical procedures, including biopsies, and ultimately improve patient care and outcomes. ©2024 IEEE.

关键词： Autoimmune Liver Disease Classification Deep Learning Machine Learning

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A Study for Smart Technologies for Autism Spectrum Disorders Children in Oman to Facilitate Interactive Communication 2

A Study for Smart Technologies for Autism Spectrum Disorders...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Alghafri, Manal Al-Zeid, Shima Al Mamari, Misoon College of Computing and Information Sciences University of Technology and Applied Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

The study investigates the use of smart technologies in Oman to improve communication skills and social interactions among children with autism spectrum disorders (ASD). The Sultanate of Oman is focusing on fostering an inclusive environment through technological innovation and inclusive education. The study concludes that smart technology interventions can significantly improve communication abilities and social interactions, promoting a more inclusive society for ASD children. © 2024 IEEE.

关键词： ASD Autism spectrum disorder

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Exploring the Influence of Social Media on Omani Culture, Identity and its Impact on Youth Behavior 2

Exploring the Influence of Social Media on Omani Culture, Id...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Al Shiadi, Hawa Zaid Al Mamari, Abir Nasser Al Farsi, Shatha Mohammed College of Computing and Information Sciences University of Technology and Applied Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

The purpose of this study was to comprehend how social media affects Omani youth and what that means for maintaining their nationality and identity. Expanding school curricula to highlight the importance of Omani culture, finding strategies for parents to support their children in preserving Omani identity and culture, and increasing public awareness of the risks connected with social media platforms were the objectives. The study employed a survey research methodology, gathering data via the administration of questionnaires. A representative sample of young Omani people was chosen using voluntary response samples and convenience sampling. Social network analysis and content analysis are examples of data analysis. A number of ethical factors were taken into account, including security, privacy, secrecy, data integrity, and informed permission. The results indicated that there were no statistically significant differences between the means of the data sets, indicating that the central tendency of the data sets was statistically similar. The research concluded that social media plays an important role in shaping cultural perceptions, identity formation, and behavioral patterns among Omani youth, and strategies should be developed to harness its positive aspects while mitigating its negative effects. The result tendency of the data sets was statistically similar, according to the results, which showed that there were no statistically significant discrepancies between the means of the data sets. According to the study's findings, social media has a significant impact on how Omani young perceives culture, construct identities, and behave. As a result, measures for maximizing social media's beneficial benefits while reducing its negative ones should be devised. © 2024 IEEE.

关键词： Data integrity

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A Study on the Importance of Cybersecurity and its Significance in Omani Society 2

A Study on the Importance of Cybersecurity and its Significa...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Mohammed, Aisha Abdullah Al Ghaithi, Hamda Khamis Al Salty, Rawya Khamis University of Technology and Applied Sciences College of Computing and Information Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

This study investigates the critical role of cybersecurity in Omani society, analyzing its significance in safeguarding digital assets and maintaining societal well-being. By examining the current cybersecurity landscape in Oman, including challenges and vulnerabilities, the study highlights the pressing need for robust cybersecurity measures. Additionally, it explores the implications of cyber threats on various sectors, such as government, finance, healthcare, and education, underscoring the far-reaching consequences of inadequate cybersecurity practices. Furthermore, the study assesses existing cybersecurity initiatives and policies in Oman and identifies areas for improvement to enhance overall cyber resilience. Through empirical research and data analysis, this study contributes valuable insights into the importance of cybersecurity in protecting national interests, promoting economic growth, and preserving social stability in Oman. © 2024 IEEE.

关键词： Cybersecurity

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The Smart Assistive technology in Education for Students with Disabilities in Oman 2

The Smart Assistive Technology in Education for Students wit...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Albalushi, Laryam Nasser Almamari, Hind Maktoom University of Technology and Applied Sciences College of Computing and Information Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

The research in Oman assessed smart assistive technology's impact on students with disabilities, focusing on academic improvement and user satisfaction. Using a mixedmethods approach, it found significant gains in student engagement and academic outcomes. Recommendations include expanding assistive tools and training educators. Limitations were a small sample size and uneven tech access. The study concluded that such technology greatly enhances inclusive education in Oman. © 2024 IEEE.

关键词： Assistive technology

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Explore Enhanced Communication and Decision Making between Government and Citizens of Oman Using Digital Technologies 2

Explore Enhanced Communication and Decision Making between G...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Anwar, Naira Hassan Al Naabi, Muneera Saif Al-Badi, Mashaal Atiyaq College of Computing and Information Sciences University of Technology and Applied Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

This study explores how digital technology can enhance communication and decision-making between the Omani government and its citizens. In our digital age, effective communication and collaboration are crucial. The research examines how tools like mobile apps, social media, and e-government services can improve information sharing and decision-making. The paper begins by highlighting the importance of citizen participation and transparency in Oman's Vision 2040. It then presents the hypothesis: digital technology positively impacts citizen engagement, communication quality, transparency, trust, and decision-making. The study reviews the relevance, scope, and limitations, emphasizing the need for digital tools to enhance communication in Oman. It aims to evaluate how well these technologies bridge communication gaps and overcome challenges. The methodology combines qualitative and quantitative approaches, gathering data from government officials, citizens, and experts. The findings and recommendations aim to guide policymakers in developing effective digital initiatives to boost governance and public involvement in Oman. © 2024 IEEE.

关键词： Citizen Participation Digital Technologies E-Government Government-Citizen Communication Oman Vision 2040

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Revolution in the Effectiveness of Artificial Intelligence (AI) on Educational Resourcing for Student in Oman to Enhanced Learning Opportunities 2

Revolution in the Effectiveness of Artificial Intelligence (...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Al Jabri, Jaber Saleh Al Saadi, Saif Awadh College of Computing and Information Sciences University of Technology and Applied Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

This research investigates the potential of Artificial Intelligence (AI) to improve educational resourcing in Oman. This research addresses the prevalent issues of inefficiency and inequity in Omani educational resourcing, by proposing hypothesis that AI integration can lead to more efficient resource allocation and enhanced educational outcomes. The study aims to explore this hypothesis through a comprehensive review of existing literature. The ultimate goal is to empower individuals, enhance educational opportunities, and promote innovation and growth within Oman. Literature review provide us a comprehensive understanding of the current state of research area and identifies gaps and opportunities, to enhance our research and contribute to the advancement of knowledge in the field. Analysis of Variance or ANOVA resulted in accepting the null hypothesis. This indicates no statistically significant differences in agreement levels between groups regarding AI and educational resourcing. However, the overall research suggests potential benefits of AI in this area. Future studies could explore implementation strategies, user needs, and the impact of AI on specific educational outcomes in Oman, while also considering the country's unique cultural context and educational needs. © 2024 IEEE.

关键词： Federated learning

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A Study on the Development and Evaluation of Smart Home System Using IoT and AI Technologies in Oman 2

A Study on the Development and Evaluation of Smart Home Syst...

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2nd International Conference on computing and Data Analytics, ICCDA 2024

作者： Ahamed, Junath Naseer Ashraf, Mohammed Juma, Ahmed College of Computing and Information Sciences University of Technology and Applied Sciences Department of Information Technology Ibri Oman

ISBN: (纸本)9798331542573

Smart homes, leveraging Internet of Things (IoT) and Artificial Intelligence (AI) technologies, are gaining popularity worldwide. However, their implementation in specific regions, such as Oman, remains underexplored. This research addresses this gap by investigating the development and evaluation of a smart home system tailored to Oman's unique context. Our study aims to enhance home automation, energy efficiency, and overall quality of life for Omani residents. We propose hypotheses related to the impact of IoT and AI integration, economic prospects, and localized design strategies. The study's significance lies in its potential to inform decisionmakers, urban planners, and technology suppliers regarding the adoption and use of smart home technologies in Oman. © 2024 IEEE.

关键词： Smart homes

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Posture Monitoring and Classification for Health Care of Bedridden Patients Using IoT and AI Algorithms 10

Posture Monitoring and Classification for Health Care of Bed...

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10th International Conference on Engineering and Emerging Technologies, ICEET 2024

作者： Cheriyan, Sunitha Sakthivel, Sudha Regula, Thirupathi Kiran Kumar, S.G. Riyami, Said Al College of Computing and Information Sciences University of Technology and Applied Sciences Department of It Muscat Oman

ISBN: (纸本)9798331532895

Posture monitoring has become a crucial area of research and application, particularly considering the increasing concerns about musculoskeletal disorders and their association with prolonged lying and poor ergonomic practices. To solve the crucial problem of bedridden patient care, this study investigates the categorization of lying postures using four different deep learning models: The models used are Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), VGG16, and ResNe$t$50. Due to bedridden patients' difficulty in developing pressure ulcers, respiratory disorders, and other complications, the classification of laying positions which includes supine, prone, and lateral is essential. Some possible assistive devices that can inform caregivers or initiate some techniques to improve the patient's comfort and eliminate adverse effects of immobility can benefit from the identification of some postures in real-time. The models were trained using both balanced and unbalanced data sets from a set of labeled images covering different laying postures. Their performance was then determined by criteria including accuracy, RMSE, Kappa, recall, and precision. As for the performance, the proposed VGG model achieved better classification accuracy compared to the CNN, RNN, and ResNet models. In light of enhancing patient care as well as monitoring within the health care facilities, it is suggested from our result that these models could suggest potential solutions to posture identification for bedridden patients. By illustrating how AI posture classification systems can be implemented in IoT-based applications, the study also shows how future healthcare delivery can be improved and the problems caused by long periods of inactivity can be prevented. © 2024 IEEE.

关键词： Convolutional neural networks

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