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Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification (2023)
Journal Article
Prasad Yadav, D., Kumar, D., Singh Jalal, A., Kumar, A., Bhatia Khan, S., Gadekallu, T. R., …Malibari, A. A. (2023). Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification. Canadian Journal of Remote Sensing, 49(1), https://doi.org/10.1080/07038992.2023.2248270

Hyperspectral image classification is vital for various remote sensing applications; however, it remains challenging due to the complex and high-dimensional nature of hyperspectral data. This paper introduces a novel approach to address this challeng... Read More about Spectral–Spatial Features Exploitation Using Lightweight HResNeXt Model for Hyperspectral Image Classification.

Detection of Alzheimer’s Disease Based on Cloud-Based Deep Learning Paradigm (2023)
Journal Article
Pruthviraja, D., Nagaraju, S. C., Mudligiriyappa, N., Raisinghani, M. S., Khan, S. B., Alkhaldi, N. A., & Malibari, A. A. (in press). Detection of Alzheimer’s Disease Based on Cloud-Based Deep Learning Paradigm. Diagnostics, 13(16), 2687. https://doi.org/10.3390/diagnostics13162687

Deep learning is playing a major role in identifying complicated structure, and it outperforms in term of training and classification tasks in comparison to traditional algorithms. In this work, a local cloud-based solution is developed for classific... Read More about Detection of Alzheimer’s Disease Based on Cloud-Based Deep Learning Paradigm.

An Approach to Binary Classification of Alzheimer’s Disease Using LSTM (2023)
Journal Article
Salehi, W., Baglat, P., Gupta, G., Khan, S. B., Almusharraf, A., Alqahtani, A., & Kumar, A. (in press). An Approach to Binary Classification of Alzheimer’s Disease Using LSTM. Bioengineering, 10(8), 950. https://doi.org/10.3390/bioengineering10080950

In this study, we use LSTM (Long-Short-Term-Memory) networks to evaluate Magnetic Resonance Imaging (MRI) data to overcome the shortcomings of conventional Alzheimer’s disease (AD) detection techniques. Our method offers greater reliability and accur... Read More about An Approach to Binary Classification of Alzheimer’s Disease Using LSTM.

A Cluster-Based Energy-Efficient Secure Optimal Path-Routing Protocol for Wireless Body-Area Sensor Networks (2023)
Journal Article
Dass, R., Narayanan, M., Ananthakrishnan, G., Kathirvel Murugan, T., Nallakaruppan, M. K., Somayaji, S. R. K., …Almusharraf, A. (in press). A Cluster-Based Energy-Efficient Secure Optimal Path-Routing Protocol for Wireless Body-Area Sensor Networks. Sensors, 23(14), 6274. https://doi.org/10.3390/s23146274

Recently, research into Wireless Body-Area Sensor Networks (WBASN) or Wireless Body-Area Networks (WBAN) has gained much importance in medical applications, and now plays a significant role in patient monitoring. Among the various operations, routing... Read More about A Cluster-Based Energy-Efficient Secure Optimal Path-Routing Protocol for Wireless Body-Area Sensor Networks.

Deep Belief Networks (DBN) with IoT-Based Alzheimer’s Disease Detection and Classification (2023)
Journal Article
Alqahtani, N., Alam, S., Aqeel, I., Shuaib, M., Mohsen Khormi, I., Khan, S. B., & Malibari, A. A. (in press). Deep Belief Networks (DBN) with IoT-Based Alzheimer’s Disease Detection and Classification. Applied Sciences, 13(13), 7833. https://doi.org/10.3390/app13137833

Dementias that develop in older people test the limits of modern medicine. As far as dementia in older people goes, Alzheimer’s disease (AD) is by far the most prevalent form. For over fifty years, medical and exclusion criteria were used to diagnose... Read More about Deep Belief Networks (DBN) with IoT-Based Alzheimer’s Disease Detection and Classification.

Sentiment Analysis of Semantically Interoperable Social Media Platforms Using Computational Intelligence Techniques (2023)
Journal Article
Alqahtani, A., Khan, S. B., Alqahtani, J., AlYami, S., & Alfayez, F. (in press). Sentiment Analysis of Semantically Interoperable Social Media Platforms Using Computational Intelligence Techniques. Applied Sciences, 13(13), 7599. https://doi.org/10.3390/app13137599

Competitive intelligence in social media analytics has significantly influenced behavioral finance worldwide in recent years; it is continuously emerging with a high growth rate of unpredicted variables per week. Several surveys in this large field h... Read More about Sentiment Analysis of Semantically Interoperable Social Media Platforms Using Computational Intelligence Techniques.

An Informed Decision Support Framework from a Strategic Perspective in the Health Sector (2023)
Journal Article
Alojail, M., Alturki, M., & Bhatia Khan, S. (in press). An Informed Decision Support Framework from a Strategic Perspective in the Health Sector. Information, 14(7), 363. https://doi.org/10.3390/info14070363

This paper introduces an informed decision support framework (IDSF) from a strategic perspective in the health sector, focusing on Saudi Arabia. The study addresses the existing challenges and gaps in decision-making processes within Saudi organizati... Read More about An Informed Decision Support Framework from a Strategic Perspective in the Health Sector.

Development of a cloud-assisted classification technique for the preservation of secure data storage in smart cities (2023)
Journal Article
Kumar, A., Khan, S. B., Pandey, S. K., Shankar, A., Maple, C., Mashat, A., & Malibari, A. A. (in press). Development of a cloud-assisted classification technique for the preservation of secure data storage in smart cities. #Journal not on list, 12(1), 92. https://doi.org/10.1186/s13677-023-00469-9

Cloud computing is the most recent smart city advancement, made possible by the increasing volume of heterogeneous data produced by apps. More storage capacity and processing power are required to process this volume of data. Data analytics is used t... Read More about Development of a cloud-assisted classification technique for the preservation of secure data storage in smart cities.

Machine Learning-Driven Ubiquitous Mobile Edge Computing as a Solution to Network Challenges in Next-Generation IoT (2023)
Journal Article
Al Moteri, M., Khan, S. B., & Alojail, M. (in press). Machine Learning-Driven Ubiquitous Mobile Edge Computing as a Solution to Network Challenges in Next-Generation IoT. Systems, 11(6), 308. https://doi.org/10.3390/systems11060308

Ubiquitous mobile edge computing (MEC) using the internet of things (IoT) is a promising technology for providing low-latency and high-throughput services to end-users. Resource allocation and quality of service (QoS) optimization are critical challe... Read More about Machine Learning-Driven Ubiquitous Mobile Edge Computing as a Solution to Network Challenges in Next-Generation IoT.

Fusion of Graph and Tabular Deep Learning Models for Predicting Chronic Kidney Disease (2023)
Journal Article
Rao, P. K., Chatterjee, S., Nagaraju, K., Khan, S. B., Almusharraf, A., & Alharbi, A. I. (in press). Fusion of Graph and Tabular Deep Learning Models for Predicting Chronic Kidney Disease. Diagnostics, 13(12), 1981. https://doi.org/10.3390/diagnostics13121981

Chronic Kidney Disease (CKD) represents a considerable global health challenge, emphasizing the need for precise and prompt prediction of disease progression to enable early intervention and enhance patient outcomes. As per this study, we introduce a... Read More about Fusion of Graph and Tabular Deep Learning Models for Predicting Chronic Kidney Disease.

Load Balancing Using Artificial Intelligence for Cloud-Enabled Internet of Everything in Healthcare Domain (2023)
Journal Article
Aqeel, I., Khormi, I. M., Khan, S. B., Shuaib, M., Almusharraf, A., Alam, S., & Alkhaldi, N. A. (in press). Load Balancing Using Artificial Intelligence for Cloud-Enabled Internet of Everything in Healthcare Domain. Sensors, 23(11), 5349. https://doi.org/10.3390/s23115349

The emergence of the Internet of Things (IoT) and its subsequent evolution into the Internet of Everything (IoE) is a result of the rapid growth of information and communication technologies (ICT). However, implementing these technologies comes with... Read More about Load Balancing Using Artificial Intelligence for Cloud-Enabled Internet of Everything in Healthcare Domain.

Design and Development of IoT and Deep Ensemble Learning Based Model for Disease Monitoring and Prediction (2023)
Journal Article
Venkatachala Appa Swamy, M., Periyasamy, J., Thangavel, M., Khan, S. B., Almusharraf, A., Santhanam, P., …Elsisi, M. (in press). Design and Development of IoT and Deep Ensemble Learning Based Model for Disease Monitoring and Prediction. Diagnostics, 13(11), 1942. https://doi.org/10.3390/diagnostics13111942

With the rapidly increasing reliance on advances in IoT, we persist towards pushing technology to new heights. From ordering food online to gene editing-based personalized healthcare, disruptive technologies like ML and AI continue to grow beyond our... Read More about Design and Development of IoT and Deep Ensemble Learning Based Model for Disease Monitoring and Prediction.

Sustainable Irrigation Requirement Prediction Using Internet of Things and Transfer Learning (2023)
Journal Article
Blessy, A., Kumar, A., Quadir Md, A., Alharbi, A. I., Almusharraf, A., Khan, S. B., …Md, A. Q. (2023). Sustainable Irrigation Requirement Prediction Using Internet of Things and Transfer Learning. Sustainability, 15(10), 8260. https://doi.org/10.3390/su15108260

Irrigation systems are a crucial research area because it is essential to conserve fresh water and utilize it wisely. As a part of this study, the reliability of predicting the usage of water in the present and future is investigated in order to deve... Read More about Sustainable Irrigation Requirement Prediction Using Internet of Things and Transfer Learning.