All Outputs (11)

Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review (2023)
Journal Article
Rashid, A., Al-Obeidat, F., Kanthimathinathan, H. K., Benakatti, G., Hafez, W., Ramaiah, R., Brierley, J., Hanisch, B., Khilnani, P., Koutentis, C., Brusletto, B. S., Toufiq, M., Hussain, Z., Vyas, H., Malik, Z. A., Schumacher, M., Malik, R. A., Deshpande, S., Quraishi, N., Kadwa, R., …Hussain, A. (2024). Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review. Informatics in Medicine Unlocked, 44, Article 101419. https://doi.org/10.1016/j.imu.2023.101419

Sepsis continues to be recognized as a significant global health challenge across all ages and is characterized by a complex pathophysiology. In this scoping review, PRISMA-ScR guidelines were adhered to, and a transcriptomic methodology was adopted,... Read More about Advancing sepsis clinical research: harnessing transcriptomics for an omics-based strategy - a comprehensive scoping review.

Potential of Satellite-Airborne Sensing Technologies for Agriculture 4.0 and Climate-Resilient: A Review (2023)
Journal Article
Hazmy, A. I., Hawbani, A., Wang, X., Al-Dubai, A., Ghannami, A., Yahya, A. A., Zhao, L., & Alsamhi, S. H. (2024). Potential of Satellite-Airborne Sensing Technologies for Agriculture 4.0 and Climate-Resilient: A Review. IEEE Sensors Journal, 24(4), 4161-4180. https://doi.org/10.1109/jsen.2023.3343428

Agriculture 4.0 offers the potential to revolutionize the agriculture sector through improved productivity and efficiency. However, adopting Agriculture 4.0 requires a period of transition and effort. Satellite-Airborne sensing technologies may becom... Read More about Potential of Satellite-Airborne Sensing Technologies for Agriculture 4.0 and Climate-Resilient: A Review.

Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities (2023)
Journal Article
Tallat,, R., Hawbani, A., Wang, X., Al-Dubai, A., Zhao, L., Liu, Z., Min, G., Zomaya, A., & Alsamhi, S. (2024). Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities. Communications Surveys and Tutorials, IEEE Communications Society, 26(2), 1080 - 1126. https://doi.org/10.1109/comst.2023.3329472

This century has been a major avenue for revolutionary changes in technology and industry. Industries have transitioned towards intelligent automation, relying less on human intervention, resulting in the fourth industrial revolution, Industry 4.0. T... Read More about Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities.

Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes (2023)
Journal Article
Rashid, A., Al-Obeida, F., Hafez, W., Benakatti, G., Malik, R. A., Koutentis, C., Sharief, J., Brierley, J., Quraishi, N., Malik, Z. A., Anwary, A., Alkhzaimi, H., Zaki, S. A., Khilnani, P., Kadwa, R., Phatak, R., Schumacher, M., Shaikh, G., Al-Dubai, A., & Hussain, A. (2024). Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes. Shock, 61(1), 4-18. https://doi.org/10.1097/shk.0000000000002227

Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of Machine Learning (ML) techniques to bridge the gap between clinical data and gene expression information to bette... Read More about Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes.

A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing (2023)
Journal Article
Zhao, L., Zhao, Z., Zhang, E., Hawbani, A., Al-Dubai, A., Tan, Z., & Hussain, A. (2023). A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing. IEEE Journal on Selected Areas in Communications, 41(11), 3386-3400. https://doi.org/10.1109/jsac.2023.3310062

Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge Computing (MEC) to road scenarios. In VEC, task offloading can enable vehicles to offload the computing tasks to nearby Roadside Units (RSUs) that deploy computing capabili... Read More about A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing.

Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method (2023)
Journal Article
Li, Z., Zhao, L., Min, G., Al-Dubai, A. Y., Hawbani, A., Zomaya, A. Y., & Luo, C. (2023). Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method. IEEE Transactions on Intelligent Transportation Systems, 24(12), 14022 - 14036. https://doi.org/10.1109/tits.2023.3300082

Greedy routing efficiently achieves routing solutions for vehicular networks due to its simplicity and reliability. However, the existing greedy routing schemes have mainly considered simple routing metrics only, e.g., distance based on the local vie... Read More about Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method.

A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation? (2023)
Journal Article
Rashid, A., Brusletto, B. S., Al-Obeidat, F., Toufiq, M., Benakatti, G., Brierley, J., Malik, Z. A., Hussain, Z., Alkhazaimi, H., Sharief, J., Kadwa, R., Sarpal, A., Chaussabel, D., Malik, R. A., Quraishi, N., Khilnani, P., Zaki, S. A., Nadeem, R., Shaikh, G., Al-Dubai, A., …Hussain, A. (2023). A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?. Shock, 60(4), 503-516. https://doi.org/10.1097/shk.0000000000002192

This study investigated the temporal dynamics of childhood sepsis by analyzing gene expression changes associated with proinflammatory processes. Five datasets, including four meningococcal sepsis shock (MSS) datasets (two temporal and two longitudin... Read More about A Transcriptomic Appreciation of Childhood Meningococcal and Polymicrobial Sepsis from a Pro-Inflammatory and Trajectorial Perspective, a Role for Vascular Endothelial Growth Factor A and B Modulation?.

ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology (2023)
Journal Article
Naji, A., Hawbani, A., Wang, X., Al-Gunid, H. M., Al-Dhabi, Y., Al-Dubai, A., Hussain, A., Zhao, L., & Alsamhi, S. H. (2024). ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology. IEEE Transactions on Sustainable Computing, 9(1), 31 - 45. https://doi.org/10.1109/tsusc.2023.3296607

Wireless Power Transfer (WPT) is a promising technology that can potentially mitigate the energy provisioning problem for sensor networks. In order to efficiently replenish energy for these battery-powered devices, designing appropriate scheduling an... Read More about ESPP: Efficient Sector-based Charging Scheduling and Path Planning for WRSNs with Hexagonal Topology.

MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing (2023)
Journal Article
Zhao, L., Zhang, E., Wan, S., Hawbani, A., Al-Dubai, A. Y., Min, G., & Zomaya, A. Y. (2024). MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing. IEEE Transactions on Mobile Computing, 23(5), 4259 - 4272. https://doi.org/10.1109/tmc.2023.3289611

Vehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing (MEC) in road scenarios. One key technology of VEC is task offloading, which allows vehicles to send their computation tasks to the surrounding Roadside Units (RSUs... Read More about MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing.

Application of a gene modular approach for clinical phenotype genotype association and sepsis prediction using machine learning in meningococcal sepsis (2023)
Journal Article
Rashid, A., Anwary, A. R., Al-Obeidat, F., Brierley, J., Uddin, M., Alkhzaimi, H., Sarpal, A., Toufiq, M., Malik, Z. A., Kadwa, R., Khilnani, P., Guftar Shaikh, M., Benakatti, G., Sharief, J., Ahmed Zaki, S., Zeyada, A., Al-Dubai, A., Hafez, W., & Hussain, A. (2023). Application of a gene modular approach for clinical phenotype genotype association and sepsis prediction using machine learning in meningococcal sepsis. Informatics in Medicine Unlocked, 41, Article 101293. https://doi.org/10.1016/j.imu.2023.101293

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The... Read More about Application of a gene modular approach for clinical phenotype genotype association and sepsis prediction using machine learning in meningococcal sepsis.

A Novel Federated Learning Scheme for Generative Adversarial Networks (2023)
Journal Article
Zhang, J., Zhao, L., Yu, K., Min, G., Al-Dubai, A., & Zomya, A. (2024). A Novel Federated Learning Scheme for Generative Adversarial Networks. IEEE Transactions on Mobile Computing, 23(5), 3633-3649. https://doi.org/10.1109/tmc.2023.3278668

Generative adversarial networks (GANs) have been advancing and gaining tremendous interests from both academia and industry. With the development of wireless technologies, a huge amount of data generated at the network edge provides an unprecedented... Read More about A Novel Federated Learning Scheme for Generative Adversarial Networks.