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Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification (2022)
Journal Article
Jin, J., Zhang, Q., He, J., & Yu, H. (2022). Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification. Electronics, 11(23), Article 3969. https://doi.org/10.3390/electronics11233969

Deep neural networks have proven to be effective in solving computer vision and natural language processing problems. To fully leverage its power, manually designed network templates, i.e., Residual Networks, are introduced to deal with various visio... Read More about Quantum Dynamic Optimization Algorithm for Neural Architecture Search on Image Classification.

Assessment of symmetries and asymmetries on barriers to circular economy adoption in the construction industry towards zero waste: A survey of international experts (2022)
Journal Article
Oluleye, B. I., Chan, D. W., Olawumi, T. O., & Saka, A. B. (2023). Assessment of symmetries and asymmetries on barriers to circular economy adoption in the construction industry towards zero waste: A survey of international experts. Building and Environment, 228, Article 109885. https://doi.org/10.1016/j.buildenv.2022.109885

This study evaluates simultaneously the symmetries and asymmetries on the classification of barriers to circular economy (CE) adoption in the building construction industry (BCI) of developing and developed economies. This is crucial because the vagu... Read More about Assessment of symmetries and asymmetries on barriers to circular economy adoption in the construction industry towards zero waste: A survey of international experts.

Fusing external knowledge resources for natural language understanding techniques: A survey (2022)
Journal Article
Wang, Y., Wang, W., Chen, Q., Huang, K., Nguyen, A., De, S., & Hussain, A. (2023). Fusing external knowledge resources for natural language understanding techniques: A survey. Information Fusion, 92, 190-204. https://doi.org/10.1016/j.inffus.2022.11.025

Knowledge resources, e.g. knowledge graphs, which formally represent essential semantics and information for logic inference and reasoning, can compensate for the unawareness nature of many natural language processing techniques based on deep neural... Read More about Fusing external knowledge resources for natural language understanding techniques: A survey.

Internet of drones security: taxonomies, open issues, and future directions (2022)
Journal Article
Derhab, A., Cheikhrouhou, O., Allouch, A., Koubaa, A., Qureshi, B., Ferrag, M. A., Maglaras, L., & Khan, F. A. (2023). Internet of drones security: taxonomies, open issues, and future directions. Vehicular Communications, 39, Article 100552. https://doi.org/10.1016/j.vehcom.2022.100552

Unmanned Aerial Vehicles (UAVs), also known as drones, have recently become one of the most important technological breakthroughs. They have opened the horizon for a vast array of applications and paved the way for a diversity of innovative solutions... Read More about Internet of drones security: taxonomies, open issues, and future directions.

Universally Hard Hamiltonian Cycle Problem Instances (2022)
Presentation / Conference Contribution
Sleegers, J., Thomson, S. L., & van den Berg, D. (2022, November). Universally Hard Hamiltonian Cycle Problem Instances. Presented at ECTA 2022 : 14th International Conference on Evolutionary Computation Theory and Applications, Valletta, Malta

In 2021, evolutionary algorithms found the hardest-known yes and no instances for the Hamiltonian cycle problem. These instances, which show regularity patterns, require a very high number of recursions for the best exact backtracking algorithm (Vand... Read More about Universally Hard Hamiltonian Cycle Problem Instances.

Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images (2022)
Journal Article
Liu, Y., Shen, J., Yang, L., Yu, H., & Bian, G. (2023). Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images. Computers in Biology and Medicine, 152, Article 106341. https://doi.org/10.1016/j.compbiomed.2022.106341

Accurate segmentation of retinal vessels from fundus images is fundamental for the diagnosis of numerous diseases of eye, and an automated vessel segmentation method can effectively help clinicians to make accurate diagnosis for the patients and prov... Read More about Wave-Net: A lightweight deep network for retinal vessel segmentation from fundus images.

Assessment of Ambient Air Quality in Hulu Langat District, Selangor, Malaysia (2022)
Presentation / Conference Contribution
Mohd Saudi, A., Abdullah, A., Shafii, N., Khairuddin, M., Ismail, M., Mejía, P., Kadir, K., Saudi, M., Kamarudin, M., Muhammad-Sukki, F., Ali, M., & Bani, N. (2022, November). Assessment of Ambient Air Quality in Hulu Langat District, Selangor, Malaysia. Presented at The 3rd International Conference on Medical Science Technology, Online

Air pollution is one of the most pressing environmental issues in the world. The district of Hulu Langat, bordering the capital city of Kuala Lumpur, is the focus area of the surrounding population. The district experienced a decline in air quality i... Read More about Assessment of Ambient Air Quality in Hulu Langat District, Selangor, Malaysia.

Decarbonising the Transport Industry (2022)
Presentation / Conference Contribution
Muhammad Sukki, F. (2022, November). Decarbonising the Transport Industry. Presented at Research Seminar, Edinburgh Napier University

The electric vehicles (EVs) sales in Scotland increased by 97% in 2020, but Scotland still lags behinds when compared to other locations in the UK. One of the reasons for the slow rollout is limited charging infrastructure to power the EVs especially... Read More about Decarbonising the Transport Industry.

Low‐gain integral control for a class of discrete‐time Lur'e systems with applications to sampled‐data control (2022)
Journal Article
Guiver, C., Rebarber, R., & Townley, S. (2023). Low‐gain integral control for a class of discrete‐time Lur'e systems with applications to sampled‐data control. International Journal of Robust and Nonlinear Control, 33(3), 1410-1437. https://doi.org/10.1002/rnc.6455

We study low-gain (P)roportional (I)ntegral control of multivariate discrete-time, forced Lur’e systems to solve the output-tracking problem for constant reference signals. We formulate an incremental sector condition which is sufficient for a usual... Read More about Low‐gain integral control for a class of discrete‐time Lur'e systems with applications to sampled‐data control.