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On the elusivity of dynamic optimisation problems. (2023)
Journal Article
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2023. On the elusivity of dynamic optimisation problems. Swarm and evolutionary computation [online], In Press, article 101289. Available from: https://doi.org/10.1016/j.swevo.2023.101289

The field of dynamic optimisation continuously designs and compares algorithms with adaptation abilities that deal with changing problems during their search process. However, restarting the search algorithm after a detected change is sometimes a bet... Read More about On the elusivity of dynamic optimisation problems..

A PESTEL and SWOT impact analysis on renewable energy development in Togo. (2023)
Journal Article
KANSONGUE, N., NJUGUNA, J. and VERTIGANS, S. 2023. A PESTEL and SWOT impact analysis on renewable energy development in Togo. Frontiers in sustainability [online], 3, article 990173. Available from: https://doi.org/10.3389/frsus.2022.990173

Like most developing countries, Togo continues to rely on the use of traditional forms of biomass energy which causes tremendous socio-economic, environmental and health hazards. In addition, the imbalanced distribution and use of electricity, petrol... Read More about A PESTEL and SWOT impact analysis on renewable energy development in Togo..

PSSA: PCA-domain superpixelwise singular spectral analysis for unsupervised hyperspectral image classification. (2023)
Journal Article
LIU, Q., XUE, D., TANG, Y., ZHAO, Y., REN, J. and SUN, H. 2023. PSSA: PCA-domain superpixelwise singular spectral analysis for unsupervised hyperspectral image classification. Remote sensing [online], 15(4), article 890. Available from: https://doi.org/10.3390/rs15040890

Although supervised classification of hyperspectral images (HSI) has achieved success in remote sensing, its applications in real scenarios are often constrained, mainly due to the insufficiently available or lack of labelled data. As a result, unsup... Read More about PSSA: PCA-domain superpixelwise singular spectral analysis for unsupervised hyperspectral image classification..

Multiscale diff-changed feature fusion network for hyperspectral image change detection. (2023)
Journal Article
LUO, F., ZHOU, T., LIU, J., GUO, T., GONG, X. and REN, J. 2023. Multiscale diff-changed feature fusion network for hyperspectral image change detection. IEEE transactions on geoscience and remote sensing [online], 61, article 5502713. Available from: https://doi.org/10.1109/TGRS.2023.3241097

For hyperspectral images (HSI) change detection (CD), multi-scale features are usually used to construct the detection models. However, the existing studies only consider the multi-scale features containing changed and unchanged components, which is... Read More about Multiscale diff-changed feature fusion network for hyperspectral image change detection..

Stress analysis of pipe-in-pipe systems under free span for deep water pipeline applications. (2023)
Journal Article
MOHAMMED, A.I., JOHNSON, C., SPENCE, S., SKYES, P. and NJUGUNA, J. 2023. Stress analysis of pipe-in-pipe systems under free span for deep water pipeline applications. Petroleum and petrochemical engineering journal [online], Articles in Press. To be made available from: https://doi.org/10.23880/ppej-16000325

This study examined the phenomena of free span for a pipe -in- pipe (PIP) system for pipeline application. Two different span length of 8 and 30 meters are modelled and simulated using nonlinear stress analysis. The effect of pressure, temperature an... Read More about Stress analysis of pipe-in-pipe systems under free span for deep water pipeline applications..

Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation. (2023)
Journal Article
SUN, M., LI, P., REN, J. and WANG, Z. 2023. Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation. Cognitive computation [online], Online First. Available from: https://doi.org/10.1007/s12559-022-10094-4

Existing deep learning–based medical image segmentation methods have achieved gratifying progress, but they still suffer from the coarse boundaries with similar pixels of target. Because the boundary of medical images becomes blurred and the gradient... Read More about Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation..

LDDNet: a deep learning framework for the diagnosis of infectious lung diseases. (2023)
Journal Article
PODDER, P., RANI DAS, S., MONDAL, M.R.H., BHARATI, S., MALIHA, A., HASAN, M.J. and PILTAN, F. 2023. LDDNet: a deep learning framework for the diagnosis of infectious lung diseases. Sensors [online], 23(1), article 480. Available from: https://doi.org/10.3390/s23010480

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The pro... Read More about LDDNet: a deep learning framework for the diagnosis of infectious lung diseases..

On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems. (2022)
Conference Proceeding
HAN, K., CHRISTIE, L.A., ZAVOIANU, A.-C. and MCCALL, J. 2022. On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: Eurocast 2022; revised selected papers from the 18th International conference on computer aided systems theory (Eurocast 2022), 20-25 February 2022, Las Palmas, Spain. Lecture notes in computer science, 13789. Cham: Springer [online], pages 104-111. Available from: https://doi.org/10.1007/978-3-031-25312-6_12

While self-driving technology is still being perfected, public transport authorities are increasingly interested in the ability to model and optimise the benefits of adding connected and autonomous vehicles (CAVs) to existing multi-modal transport sy... Read More about On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems..

Lightweight interpolation-based surrogate modelling for multi-objective continuous optimisation. (2022)
Conference Proceeding
ZAVOIANU, A.-C., LACROIX, B. and MCCALL, J. 2022. Lightweight Interpolation-based surrogate modelling for multiobjective continuous optimisation. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: Eurocast 2022; revised selected papers from the 18th International conference on computer aided systems theory (Eurocast 2022), 20-25 February 2022, Las Palmas, Spain. Lecture notes in computer science, 13789. Cham: Springer [online], pages 53-60. Available from: https://doi.org/10.1007/978-3-031-25312-6_6

We propose two surrogate-based strategies for increasing the convergence speed of multi-objective evolutionary algorithms (MOEAs) by stimulating the creation of high-quality individuals early in the run. Both offspring generation strategies are desig... Read More about Lightweight interpolation-based surrogate modelling for multi-objective continuous optimisation..

Composite repair and remanufacturing. (2022)
Book Chapter
VON FREEDEN, J., DE WIT, J., CABA, S., KROLL, S., ZHAO, H., REN, J., YAN, Y., ARSHED, F., AHMAD, A. and XIROUCHAKIS, P. 2022. Composite repair and remanufacturing. In Colledani, M. and Turri, S. (eds.) Systemic circular economy solutions for fiber reinforced composites. Cham: Springer [online], pages 191-214. Available from: https://doi.org/10.1007/978-3-031-22352-5_10

For the reuse of components and structures made of fiber composite materials, a complete remanufacturing process chain is necessary to prepare the parts for a further life cycle. The first step is to dismantle the parts to be reused. Fiber composite... Read More about Composite repair and remanufacturing..

Efficient breast cancer classification network with dual squeeze and excitation in histopathological images. (2022)
Journal Article
SARKER, M.M.K., AKRAM, F., ALSHARID, M., SINGH, V.K., YASRAB, R. and ELYAN, E. 2023. Efficient breast cancer classification network with dual squeeze and excitation in histopathological images. Diagnostics [online], 13(1), article 103. Available from: https://doi.org/10.3390/diagnostics13010103

Medical image analysis methods for mammograms, ultrasound, and magnetic resonance imaging (MRI) cannot provide the underline features on the cellular level to understand the cancer microenvironment which makes them unsuitable for breast cancer subtyp... Read More about Efficient breast cancer classification network with dual squeeze and excitation in histopathological images..

Mobile Platform for livestock monitoring and inspection. (2022)
Conference Proceeding
FABIYI, S.D., REN, J., HAN, Y., ZHU, Q. and BARCLAY, D. 2022. Mobile platform for livestock monitoring and inspection. In Proceedings of the 3rd International informatics and software engineering conference 2022 (IISEC 2022), 15-16 December 2022, Ankara, Turkey. Piscataway: IEEE [online], article 9998279. Available from: https://doi.org/10.1109/iisec56263.2022.9998297

Livestock keepers acquire and manage information (e.g. identification numbers, images, etc.) about livestock to identify and keep track of livestock using systems with capabilities to extract such information. Examples of such systems are Radio Frequ... Read More about Mobile Platform for livestock monitoring and inspection..

An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification. (2022)
Journal Article
ZHAO, C., QIN, B., FENG, S., ZHU, W., ZHANG, L. and REN, J. 2022. An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5546216. Available from: https://doi.org/10.1109/TGRS.2022.3230378

Despite success in the same-scene hyperspectral image classification (HSIC), for the cross-scene classification, samples between source and target scenes are not drawn from the independent and identical distribution, resulting in significant performa... Read More about An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification..

Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation. (2022)
Conference Proceeding
DANG, T., NGUYEN, T.T., MCCALL, J. and LIEW, A.W.-C. 2022. Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation. In Ishibuchi, H., Kwoh, C.-K., Tan, A.-H., Srinivasan, D., Miao, C., Trivedi, A. and Crockett, K. (eds.) Proceedings of the 2022 IEEE Symposium series on computational intelligence (SSCI 2022), 4-7 December 2022, Singapore. Piscataway: IEEE [online], pages 269-276. Available from: https://doi.org/10.1109/SSCI51031.2022.10022114

Segmentation, a process of partitioning an image into multiple segments to locate objects and boundaries, is considered one of the most essential medical imaging process. In recent years, Deep Neural Networks (DNN) have achieved many notable successe... Read More about Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation..

Job assignment problem and traveling salesman problem: a linked optimisation problem. (2022)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2022. Job assignment problem and traveling salesman problem: a linked optimisation problem. In Bramer, M. and Stahl, F (eds.) Artificial intelligence XXXIX: proceedings of the 42nd SGAI (Specialist Group on Artificial Intelligence) Artificial intelligence international conference 2022 (AI 2022), 13-15 December 2022, Cambridge, UK. Lecture notes in computer science (LNCS), 13652. Cham: Springer [online], pages 19-33. Available from: https://doi.org/10.1007/978-3-031-21441-7_2

Linked decision-making in service management systems has attracted strong adoption of optimisation algorithms. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems. This paper, theref... Read More about Job assignment problem and traveling salesman problem: a linked optimisation problem..

Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures. (2022)
Journal Article
ZABALZA, J., MURRAY, P., MARSHALL, S., REN, J., BERNARD, R. and HEPWORTH, S. 2023. Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures. IEEE sensors journal [online], 23(1), pages 452-459. Available from: https://doi.org/10.1109/JSEN.2022.3221680

Traditionally, Special Nuclear Material (SNM) at Sellafield has been stored in multi-layered packages, consisting of metallic cans and an over-layer of plasticized Polyvinyl Chloride (PVC) as an intermediate layer when transitioning between areas of... Read More about Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures..

Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture. (2022)
Journal Article
HUANG, H., TANG, Y., TAN, Z., ZHUANG, J., HOU, C., CHEN, W. and REN, J. 2022. Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture. IEEE transactions on geoscience and remote sensing [online], 60, article number 4416013. Available from: https://doi.org/10.1109/TGRS.2022.3224580

Color calibration is a critical step for unmanned aerial vehicle (UAV) remote sensing, especially in precision agriculture, which relies mainly on correlating color changes to specific quality attributes, e.g. plant health, disease, and pest stresses... Read More about Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture..

Digital condition monitoring for wider blue economy. (2022)
Presentation / Conference
HASAN, M.J., YAN, Y. and REN, J. 2022. Digital condition monitoring for wider blue economy. Presented at the 12th Annual science meeting of the Marine Alliance for Science and Technology for Scotland (MASTS ASM 2022), 8-10 November 2022, Glasgow, UK.

In the process of decommissioning energy systems, condition monitoring is crucial. It can make the health status of offshore oil and gas installations, pipelines, wind farms etc. transparent to policymakers and stakeholders, and aid them in creating... Read More about Digital condition monitoring for wider blue economy..

A novel gradient-guided post-processing method for adaptive image steganography. (2022)
Journal Article
XIE, G., REN, J., MARSHALL, S., ZHAO, H. and LI, R. 2022. A novel gradient-guided post-processing method for adaptive image steganography. Signal processing [online], 203, article 108813. Available from: https://doi.org/10.1016/j.sigpro.2022.108813

Designing an effective cost function has always been the key in image steganography after the development of the near-optimal encoders. To learn the cost maps automatically, the Generative Adversarial Networks (GAN) are often trained from the given c... Read More about A novel gradient-guided post-processing method for adaptive image steganography..

Automated analysis of sleep study parameters using signal processing and artificial intelligence. (2022)
Journal Article
SOHAIB, M., GHAFFAR, A., SHIN, J., HASAN. M.J. and SULEMAN, M.T. 2022. Automated analysis of sleep study parameters using signal processing and artificial intelligence. International journal of environmental research and public health [online], 19(20), article number 13256. Available from: https://doi.org/10.3390/ijerph192013256

An automated sleep stage categorization can readily face noise-contaminated EEG recordings, just as other signal processing applications. Therefore, the denoising of the contaminated signals is inevitable to ensure a reliable analysis of the EEG sign... Read More about Automated analysis of sleep study parameters using signal processing and artificial intelligence..