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International Conference on 6G Communications Networking and Signal Processing, SGCNSP 2023

作者： Kumari, K. Aruna Muvva, Vijaya Bhaskar Reddy Kumar, K. Sudheer Rai, B. Karunakara Shakir, Aboothar Mahmood Department of CSE SRKR Engineering College Bhimavaram Chinaamiram India Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences -Shinas Shinas Oman School of Computer Science and Artificial Intelligence SR University Warangal India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India The Islamic University Najaf Iraq

ISBN: (纸本)9789819778751

The resource allocation is focus on enhancing the service provider proceedings and obtaining customer satisfaction by Service Level Agreements (SLA). Cloud technology has significantly transformed the organizations to manage and allocate their resources. The cloud users are choosing sources of application distribution exclusive of cooperating Quality of Service (QoS) necessities. To overcome this issue, this paper proposed a Quasi-Opposition Learning based Aquila Optimizer (QOL-AO) for resource allocation in cloud. The virtualization supports to implement task using resource availability and reduces the response time. The QOL-AO employs the hunting approach for obtain the effective and efficient resource allocation in cloud. The Performance of QOL-AO is estimate through execution time, response time and energy consumption for various number of Virtual Machines (VMs). The QOL-AO attained less execution time of 18.568 ms and response time of 0.095 s than existing algorithms like Emperor Penguin Optimization (EPO) and Particle Swarm Optimization (PSO). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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

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

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computing and Data Analytics (ICCDA), International Conference on

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

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

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.

关键词： Data analysis Prototypes Smart homes Energy efficiency Internet of Things Cultural differences Artificial intelligence Socioeconomics Meteorology

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

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

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computing and Data Analytics (ICCDA), International Conference on

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

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

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.

关键词： Surveys Ethics Data privacy Data analysis Social networking (online) Data integrity Information age Cultural differences Stakeholders Security

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

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

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computing and Data Analytics (ICCDA), International Conference on

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

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

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.

关键词： Autism Technological innovation Data analysis Education Focusing

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The effect of deep learning methods on deepfake audio detection for digital investigation

The effect of deep learning methods on deepfake audio detect...

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2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022

作者： McUba, Mvelo Singh, Avinash Ikuesan, Richard Adeyemi Venter, Hein Department of Computer Science University of Pretoria Pretoria South Africa Computing and Applied Technology College of Technological Innovation Zayed University Abu Dhabi United Arab Emirates

Voice cloning methods have been used in a range of ways, from customized speech interfaces for marketing to video games. Current voice cloning systems are smart enough to learn speech characteristics from a few samples and produce perceptually unrecognizable speech. These systems pose new protection and privacy risks to voice-driven interfaces. Fake audio has been used for malicious purposes and is difficult to classify what is real and fake during a digital forensic investigation. This paper reviews the issue of deep-fake audio classification and evaluates the current methods of deep-fake audio detection for forensic investigation. Audio file features were extracted and visually presented using MFCC, Mel-spectrum, Chromagram, and spectrogram representations to further study the differences. Harnessing the different deep learning techniques from existing literature were compared using five iterative tests to determine the mean accuracy and the effects thereof. The results showed a Custom Architecture gave better results for the Chromagram, Spectrogram, and Me-Spectrum images and the VGG-16 architecture gave the best results for the MFCC image feature. This paper contributes to further assisting forensic investigators in differentiating between synthetic and real voices. © 2023 The Authors. Published by Elsevier B.V.

关键词： Cloning

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

Explore Enhanced Communication and Decision Making between G...

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computing and Data Analytics (ICCDA), International Conference on

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

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

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.

关键词： Bridges Data analysis Social networking (online) Decision making Information sharing Collaboration Information age Mobile applications Electronic government Systematic literature review

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Advancing Brain Image Segmentation: A Comprehensive Exploration of Enhanced VGG16 Architecture for Precise Neuroanatomical Mapping 2

Advancing Brain Image Segmentation: A Comprehensive Explorat...

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

作者： Sheeja Kumari, V. Wilfred Blessing, N.R. Palarimath, Suresh Gunasekaran, Hemalatha Poorana Senthilkumar, S. Sutherlin Subitha, G. Saveetha School of Engineering Simats University Department of Computational Intelligence Chennai600 025 India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Dr. N. G. P Arts and Science College Department of Computer Applications Tamil Nadu Coimbatore India Stella Mary's College of Engineering Department of Computer Science and Engineering Tamil Nadu Kanyakumari India

ISBN: (纸本)9798331542573

This study introduces a novel approach to brain image segmentation by enhancing the VGG16 architecture. Neuroanatomical mapping is a critical aspect of understanding brain structures, and our research focuses on refining the VGG16 model to achieve more accurate segmentation results. We address the intricacies of brain image analysis, optimizing the architecture for the nuanced structures inherent in neuroimaging data. Our enhanced VGG16 model is thoroughly evaluated across diverse datasets, demonstrating superior performance compared to state-of-the-art segmentation methods. The framework proves robust and efficient in accurately delineating complex brain regions. We also delve into the interpretability of the segmentation results, shedding light on the learned features that contribute to the model's efficacy. The significance of our work extends beyond improved segmentation, offering valuable insights into the interpretability of deep learning models in neuroimaging. This research contributes to the broader field of biomedical image analysis and holds promise for applications in neuroscience and medical diagnostics. The proposed enhanced VGG16 framework emerges as a potent tool for advancing our understanding of brain structures and enhancing the capabilities of neuroimaging technologies. © 2024 IEEE.

关键词： Brain mapping

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

Revolution in the Effectiveness of Artificial Intelligence (...

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computing and Data Analytics (ICCDA), International Conference on

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

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

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.

关键词： Technological innovation Data analysis Education Learning (artificial intelligence) Resource management Stakeholders Cultural differences Artificial intelligence Analysis of variance Systematic literature review

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Optimal Deep Convolution Neural Network for Cervical Cancer Diagnosis Model

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Computers, Materials & Continua 2022年第2期70卷 3295-3309页

作者： Mohamed Ibrahim Waly Mohamed Yacin Sikkandar Mohamed Abdelkader Aboamer Seifedine Kadry Orawit Thinnukool Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Faculty of Applied Computing and Technology Noroff University CollegeKristiansand4608Norway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Biomedical imaging is an effective way of examining the internal organ of the human body and its *** important kind of biomedical image is Pap smear image that iswidely employed for cervical cancer *** cancer is a vital reason for increased women’s mortality *** screening of pap smear images is essential to assist the earlier identification and diagnostic process of cervical ***-aided systems for cancerous cell detection need to be developed using deep learning(DL)*** study introduces an intelligent deep convolutional neural network for cervical cancer detection and classification(IDCNN-CDC)model using biomedical pap smear *** proposed IDCNN-CDC model involves four major processes such as preprocessing,segmentation,feature extraction,and ***,the Gaussian filter(GF)technique is applied to enhance data through noise removal process in the Pap smear *** Tsallis entropy technique with the dragonfly optimization(TE-DFO)algorithm determines the segmentation of an image to identify the diseased portions *** cell images are fed into the DL based SqueezeNet model to extract deeplearned ***,the extracted features fromSqueezeNet are applied to the weighted extreme learning machine(ELM)classification model to detect and classify the cervix *** experimental validation,the Herlev database is *** database was developed at Herlev University Hospital(Denmark).The experimental outcomes make sure that higher performance of the proposed technique interms of sensitivity,specificity,accuracy,and F-Score.

关键词： Biomedical images deep learning cervical cancer pap smear images computer aided diagnosis herlev database

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

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

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International Conference on Engineering and Emerging Technologies (ICEET)

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

ISBN: (数字)9798331532895

ISBN: (纸本)9798331532901

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.

关键词： Recurrent neural networks Accuracy Ergonomics Prevention and mitigation Refining Medical services Transforms Real-time systems Convolutional neural networks Monitoring

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