All Outputs (17)

CEANet: an end-to-end transformer based static-mobile points alignment approach. (2025)
Journal Article
YESIPOV, V., MEKALA, M.S., EDGE, P. and ELYAN, E. 2025. CEANet: an end-to-end transformer based static-mobile points alignment approach. Signal, image and video processing [online], 19(8), article number 596. Available from: https://doi.org/10.1007/s11760-025-04258-6

Correspondence-based Point Cloud Registration (PCR) is crucial for 3D visualization applications, especially in change detection. Most PCR models depend on precise initialization using a set of closest points to establish correspondences, a method th... Read More about CEANet: an end-to-end transformer based static-mobile points alignment approach..

Predicting student next-term performance in degree programs using AI-based approach: a case study from Ghana. (2025)
Journal Article
DIEKUU, J.-B., MEKALA, M.S., ABONIE, U.S., ISAACS, J. and ELYAN, E. 2025. Predicting student next-term performance in degree programs using AI-based approach: a case study from Ghana. Cogent education [online], 12(1), article number 2481000. Available from: https://doi.org/10.1080/2331186X.2025.2481000

Student performance can fluctuate over time due to various factors (e.g. previous assignment grades, social life and economic conditions). Temporal dynamics, such as semester-to-semester variations, and changes in students' academic achievements, beh... Read More about Predicting student next-term performance in degree programs using AI-based approach: a case study from Ghana..

A latency-efficient integration of channel attention for ConvNets. (2025)
Journal Article
PARK, W., CHOI, Y., MEKALA, M.S., CHOI, G.S., YOO, K.-Y. and JUNG, H.-Y. 2025. A latency-efficient integration of channel attention for ConvNets. Computers, maerials and continua [online], 82(3), pages 3965-3981. Available from: https://doi.org/10.32604/cmc.2025.059966

Designing fast and accurate neural networks is becoming essential in various vision tasks. Recently, the use of attention mechanisms has increased, aimed at enhancing the vision task performance by selectively focusing on relevant parts of the input.... Read More about A latency-efficient integration of channel attention for ConvNets..

A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. (2024)
Journal Article
SHANKAR, A., RIZWAN, P., MEKALA, M.S., ELYAN, E., GANDOMI, A.H., MAPLE, C. and RODRIGUES, J.J.P.C. 2024. A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. IEEE journal of biomedical and health informatics [online], Early Access. Available from: https://doi.org/10.1109/JBHI.2024.3400878

In recent times, there has been a notable rise in the utilization of Internet of Medical Things (IoMT) frameworks particularly those based on edge computing, to enhance remote monitoring in healthcare applications. Most existing models in this field... Read More about A multimodel-based screening framework for C-19 using deep learning-inspired data fusion..

C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics. (2023)
Journal Article
SRIVASTAVA, G., MEKALA, M.S., HAJAR, M.S. and KALUTARAGE, H. 2024. C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics. IEEE transactions on consumer electronics [online], 70(1), pages 1556-1565. Available from: https://doi.org/10.1109/TCE.2023.3342635

The Medical Internet of Things (MIoT) facilitates extensive connections between cyber and physical "things" allowing for effective data fusion and remote patient diagnosis and monitoring. However, there is a risk of incorrect diagnosis when data is t... Read More about C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics..

Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. (2023)
Presentation / Conference Contribution
MEKALA, M.S., EYAD, E. and SRIVASTAVA, G. 2023. Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. In Proceedings of the 10th IEEE (Institute of Electrical and Electronics Engineers) Data science and advanced analytics international conference 2023 (DSAA 2023), 9-13 October 2023, Thessaloniki, Greece. Piscataway: IEEE [online], 10302554. Available from: https://doi.org/10.1109/DSAA60987.2023.10302554

Sharing up-to-date information about the surrounding measured by On-Board Units (OBUs) and Roadside Units (RSUs) is crucial in accomplishing traffic efficiency and pedestrians safety towards Intelligent Transportation Systems (ITS). Transferring meas... Read More about Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems..

ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT. (2023)
Journal Article
MEKALA, M.S., DHIMAN, G., PARK, J.H., JUNG, H.-Y. and VIRIYASITAVAT, W. 2024. ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT. IEEE transactions on industrial informatics [online], 20(3), pages 4347-4359. Available from: https://doi.org/10.1109/TII.2023.3315744

Most computation-intensive industry applications and servers encounter service-reliability challenges due to the limited resource capability of the edge. Achieving quality data fusion and accurate service reliability with optimized service-x executio... Read More about ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT..

RLIS: resource limited improved security beyond fifth generation networks using deep learning algorithms. (2023)
Journal Article
SELVARAJAN, S., MANOHARAN, H., KHADIDOS, A.O., SHANKAR, A., MEKALA, M.S. and KHADIDOS, A.O. 2023. RLIS: resource limited improved security beyond fifth generation networks using deep learning algorithms. IEEE open journal of the Communications Society [online], 4, pages 2383-2396. Available from: https://doi.org/10.1109/OJCOMS.2023.3318860

This study explores the feasibility of allocating finite resources beyond fifth generation networks for extended reality applications through the implementation of enhanced security measures via offloading analysis (RLIS). The quantification of resou... Read More about RLIS: resource limited improved security beyond fifth generation networks using deep learning algorithms..

A quantum-inspired sensor consolidation measurement approach for cyber-physical systems. (2023)
Journal Article
MEKALA, M.S., SRIVASTAVA, G., GANDOMI, A.H., PARK, J.H. and JUNG, H.-Y. 2024. A quantum-inspired sensor consolidation measurement approach for cyber-physical systems. IEEE transactions on network science and engineering [online], 11(1), pages 511-524. Available from: https://doi.org/10.1109/TNSE.2023.3301402

Cyber-Physical System (CPS) devices interconnect to grab data over a common platform from industrial applications. Maintaining immense data and making instant decision analysis by selecting a feasible node to meet latency constraints is challenging.... Read More about A quantum-inspired sensor consolidation measurement approach for cyber-physical systems..

3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration. (2023)
Journal Article
ZHANG, H., MEKALA, M.S., YANG, D., ISAACS, J., NAIN, Z., PARK, J.H. and JUNG, H.-Y. 2023. 3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration. IEEE transactions on vehicular technology [online], 72(12), pages 15268-15279. Available from: https://doi.org/10.1109/TVT.2023.3291650

The use of edge computing for 3D perception has garnered interest in intelligent transportation systems (ITS) due to its potential to enhance Vehicle-to-Everything (V2X) orchestration through real-time traffic monitoring. The ability to accurately me... Read More about 3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration..

Efficient LiDAR-trajectory affinity model for autonomous vehicle orchestration. (2023)
Journal Article
MEKALA, M.S., DHIMAN, G., VIRIYASITAVAT, W., PARK, J.H. and JUNG, H.-Y. 2024. Efficient LiDAR-trajectory affinity model for autonomous vehicle orchestration. IEEE transactions on intelligent transportation systems [online], 25(3), pages 2708-2718. Available from: https://doi.org/10.1109/TITS.2023.3242900

Computation and memory resource management strategies are the backbone of continuous object tracking in intelligent vehicle orchestration. Multi-object tracking generates enormous measurements of targets and extended object positions using light dete... Read More about Efficient LiDAR-trajectory affinity model for autonomous vehicle orchestration..

An effective communication and computation model based on a hybridgraph-deeplearning approach for SIoT. (2022)
Journal Article
MEKALA, M.S., SRIVASTAVA, G., PARK, J.H. and JUNG, H.-Y. 2022. An effective communication and computation model based on a hybridgraph-deeplearning approach for SIoT. Digital communications and networks [online], 8(6), pages 900-910. Available from: https://doi.org/10.1016/j.dcan.2022.07.004

Social Edge Service (SES) is an emerging mechanism in the Social Internet of Things (SIoT) orchestration for effective user-centric reliable communication and computation. The services are affected by active and/or passive attacks such as replay atta... Read More about An effective communication and computation model based on a hybridgraph-deeplearning approach for SIoT..

A DRL-based service offloading approach using DAG for edge computational orchestration. (2022)
Journal Article
MEKALA, M.S., DHIMAN, G., SRIVASTAV, G., NAIN, Z., ZHANG, H., VIRIYASITAVAT, W. and VARMA, G.P.S. 2024. A DRL-based service offloading approach using DAG for edge computational orchestration. IEEE transactions on computational social systems [online], 11(3), pages 3070-3078. Available from: https://doi.org/10.1109/tcss.2022.31616273070-3078

Edge infrastructure and Industry 4.0 required services are offered by edge-servers (ESs) with different computation capabilities to run social application's workload based on a leased-price method. The usage of Social Internet of Things (SIoT) applic... Read More about A DRL-based service offloading approach using DAG for edge computational orchestration..

DAWM: cost-aware asset claim analysis approach on big data analytic computation model for cloud data centre. (2021)
Journal Article
MEKALA, M.S., PATAN, R., ISLAM, S.H., SAMANTA, D., MALLAH, G.A. and CHAUDHRY, S.A. 2021. DAWM: cost-aware asset claim analysis approach on big data analytic computation model for cloud data centre. Security and communication networks [online], 2021: security, trust and privacy for cloud, fog and Internet of Things, article ID 6688162. Available from: https://doi.org/10.1155/2021/6688162

The heterogeneous resource-required application tasks increase the cloud service provider (CSP) energy cost and revenue by providing demand resources. Enhancing CSP profit and preserving energy cost is a challenging task. Most of the existing approac... Read More about DAWM: cost-aware asset claim analysis approach on big data analytic computation model for cloud data centre..

Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT). (2021)
Journal Article
MEKALA, M.S., RIZWAN, P. and KHAN, M.S. 2023. Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT). IEEE Internet of Things journal [online], 10(3), pages 2121-2130. Available from: https://doi.org/10.1109/JIOT.2021.3073600

Continues field monitoring and searching sensor data remains an imminent element emphasizes the influence of the Internet of Things (IoT). Most of the existing systems are concede spatial coordinates or semantic keywords to retrieve the entail data,... Read More about Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT)..

Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical systems. (2020)
Journal Article
MEKALA, M.S., JOLFAEI, A., SRIVASTAVA, G., ZHENG, X., ANVARI-MOGHADDAM, A. and VISWANATHAN, P. 2022. Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical systems. IEEE transactions on emerging topics in computational intelligence [online], 6(2), pages 245-254. Available from: https://doi.org/10.1109/tetci.2020.3044082

In cyber-physical systems, it is advantageous to leverage cloud with edge resources to distribute the workload for processing and computing user data at the point of generation. Services offered by cloud are not flexible enough against variations in... Read More about Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical systems..

Efficient task optimization algorithm for green computing in cloud. (2020)
Journal Article
G, T., CH, D.C., VARMA, G.P.S. and MEKALA, M.S. 2023. Efficient task optimization algorithm for green computing in cloud. Internet technology letters [online] 6(1): ubiquitous clouds and social Internet of Things, article e254. Available from: https://doi.org/10.1002/itl2.254

Cloud infrastructure assets are accessed by all hooked heterogeneous network servers and applications to maintain entail reliability towards global subscribers with high performance and low cost is a tedious challenging task. Most of the extant techn... Read More about Efficient task optimization algorithm for green computing in cloud..