A data-driven decision support tool for offshore oil and gas decommissioning. (2021)
Journal Article
VUTTIPITTAYAMONGKOL, P., TUNG, A. and ELYAN, E. 2021. A data-driven decision support tool for offshore oil and gas decommissioning. IEEE access [online], 9, pages 137063-137082. Available from: https://doi.org/10.1109/ACCESS.2021.3117891

A growing number of oil and gas offshore infrastructures across the globe are approaching the end of their operational life. It is a major challenge for the industry to plan and make a decision on the decommissioning as the processes are resource exh... Read More about A data-driven decision support tool for offshore oil and gas decommissioning..

Harris Tweed: a glocal case study. (2021)
Journal Article
CROSS, K., STEED, J. and JIANG, Y. 2021. Harris Tweed: a global case study. Fashion, style and popular culture [online], 8(4), pages 475-494. Available from: https://doi.org/10.1386/fspc_00102_1

Fast and effectively disposable fashion has seen clothing reduced to transient items, worn for a short period of time then discarded. This has pushed down prices, moving textile and clothing production to low-cost labour countries and decimating the... Read More about Harris Tweed: a glocal case study..

Artificial intelligence surgery: how do we get to autonomous actions in surgery? (2021)
Journal Article
GUMBS, A.A., FRIGERIO, I., SPOLVERATO, G., CRONER, R., ILLANES, A., CHOUILLARD, E. and ELYAN, E. 2021. Artificial intelligence surgery: how do we get to autonomous actions in surgery? Sensors [online], 21(16), article 5526. Available from: https://doi.org/10.3390/s21165526

Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intel... Read More about Artificial intelligence surgery: how do we get to autonomous actions in surgery?.

Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. (2021)
Journal Article
ACEVES-MARTINS, A., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(3), pages 544-560. Available from: https://doi.org/10.1093/nutrit/nuab041

Context: Prevalence of overweight and obesity has been rising in the past 3 decades among Mexican children and adolescents. Objective: To systematically review experimental studies evaluating interventions to treat obesity in Mexican children and ado... Read More about Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis..

A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods. (2021)
Journal Article
ABDULLAKUTTY, F., ELYAN, E. and JOHNSTON, P. 2021. A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods. Information fusion [online], 75, pages 55-69. Available from: https://doi.org/10.1016/j.inffus.2021.04.015

Face Recognition is considered one of the most common biometric solutions these days and is widely used across a range of devices for various security purposes. The performance of FR systems has improved by orders of magnitude over the past decade. T... Read More about A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods..

Burst detection-based selective classifier resetting. (2021)
Journal Article
WARES, S., ISAACS, J. and ELYAN, E. 2021. Burst detection-based selective classifier resetting. Journal of information and knowledge management [online], 20(2), article 2150027. Available from: https://doi.org/10.1142/S0219649221500271

Concept drift detection algorithms have historically been faithful to the aged architecture of forcefully resetting the base classifiers for each detected drift. This approach prevents underlying classifiers becoming outdated as the distribution of a... Read More about Burst detection-based selective classifier resetting..

Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. (2021)
Journal Article
MEDINA, E.C.G., ESPITIA, V.M.V., SILVA, D.C., DE LAS CUEVAS, S.F.R., HIRATA, M.P., CHEN, A.Z., GONZÁLEZ, J.A.G., BUSTAMANTE-BELLO, R. and MORENO-GARCÍA, C.F. 2021. Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. Applied sciences [online], 11(7), article 2925. Available from: https://doi.org/10.3390/app11072925

Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional... Read More about Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems..

An IoT based industry 4.0 architecture for integration of design and manufacturing systems. (2020)
Journal Article
ANBALAGAN, A. and MORENO-GARCIA, C.F. 2021. An IoT based industry 4.0 architecture for integration of design and manufacturing systems. Materials today: proceedings [online], 46(17): proceedings of 3rd International conference on materials, manufacturing and modelling 2021 (ICMMM 2021), 19-21 March 2021, [virtual conference], pages 7135-7142. Available from: https://doi.org/10.1016/j.matpr.2020.11.196

This paper proposes an Internet of Things (IoT) based 5-stage Industry 4.0 architecture to integrate the design and manufacturing systems in a Cyber Physical Environment (CPE). It considers the transfer of design and manufacturing systems data throug... Read More about An IoT based industry 4.0 architecture for integration of design and manufacturing systems..

On the class overlap problem in imbalanced data classification. (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P., ELYAN, E. and PETROVSKI, A. 2021. On the class overlap problem in imbalanced data classification. Knowledge-based systems [online], 212, article number 106631. Available from: https://doi.org/10.1016/j.knosys.2020.106631

Class imbalance is an active research area in the machine learning community. However, existing and recent literature showed that class overlap had a higher negative impact on the performance of learning algorithms. This paper provides detailed criti... Read More about On the class overlap problem in imbalanced data classification..

Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.” (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.”. International journal of neural systems [online], 30(9), article ID 2075002. Available from: https://doi.org/10.1142/s0129065720750027

In the paper 'Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson's Disease', the authors introduced two new methods that address the class overlap problem in imbalanced datasets. The... Read More about Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.”.

CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification. (2020)
Journal Article
ELYAN, E., MORENO-GARCIA, C.F. and JAYNE, C. 2021. CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification. Neural computing and applications [online], 33(7), pages 2839-2851. Available from: https://doi.org/10.1007/s00521-020-05130-z

Class-imbalanced datasets are common across several domains such as health, banking, security, and others. The dominance of majority class instances (negative class) often results in biased learning models, and therefore, classifying such datasets re... Read More about CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification..

Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease. (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease. International journal of neural systems [online], 30(8), article ID 2050043. Available from: https://doi.org/10.1142/S0129065720500434

Classification of imbalanced datasets has attracted substantial research interest over the past decades. Imbalanced datasets are common in several domains such as health, finance, security and others. A wide range of solutions to handle imbalanced da... Read More about Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease..

Deep learning for symbols detection and classification in engineering drawings. (2020)
Journal Article
ELYAN, E., JAMIESON, L. and ALI-GOMBE, A. 2020. Deep learning for symbols detection and classification in engineering drawings. Neural networks [online], 129, pages 91-102. Available from: https://doi.org/10.1016/j.neunet.2020.05.025

Engineering drawings are commonly used in different industries such as Oil and Gas, construction, and other types of engineering. Digitising these drawings is becoming increasingly important. This is mainly due to the need to improve business practic... Read More about Deep learning for symbols detection and classification in engineering drawings..

Privacy, security, legal and technology acceptance elicited and consolidated requirements for a GDPR compliance platform (2020)
Journal Article
TSOHOU, A., MAGKOS, E., MOURATIDIS, H., CHRYSOLORAS, G., PIRAS, L., PAVLIDIS, M., DEBUSSCHE, J., ROTOLONI, M. and CRESPO, B. G.-N. 2020. Privacy, security, legal and technology acceptance elicited and consolidated requirements for a GDPR compliance platform. Information and computer security [online], 28(4), pages 531-553. Available from: https://doi.org/10.1108/ICS-01-2020-0002

Purpose– General data protection regulation (GDPR) entered into force in May 2018 for enhancing personal data protection. Even though GDPR leads toward many advantages for the data subjects it turned out to be a significant challenge. Organizations n... Read More about Privacy, security, legal and technology acceptance elicited and consolidated requirements for a GDPR compliance platform.

A simple encoder scheme for distributed residual video coding. (2020)
Journal Article
HU, C., ZHAO, Y., YU, L., JIANG, Y. and XIONG, Y. 2020. A simple encoder scheme for distributed residual video coding. Multimedia tools and applications [online], 79(27-28), pages 20061-20078. Available from: https://doi.org/10.1007/s11042-020-08811-y

Rate-Distortion (RD) performance of Distributed Video Coding (DVC) is considerably less than that of conventional predictive video coding. In order to reduce the performance gap, many methods and techniques have been proposed to improve the coding ef... Read More about A simple encoder scheme for distributed residual video coding..

Reducing human effort in engineering drawing validation. (2020)
Journal Article
RICA, E., MORENO-GARCÍA, C.F., ÁLVAREZ, S. and SERRATOS, F. 2020. Reducing human effort in engineering drawing validation. Computers in industry [online], 117, article ID 103198. Available from: https://doi.org/10.1016/j.compind.2020.103198

Oil & Gas facilities are extremely huge and have complex industrial structures that are documented using thousands of printed sheets. During the last years, it has been a tendency to migrate these paper sheets towards a digital environment, with the... Read More about Reducing human effort in engineering drawing validation..

The effects of measurement error and testing frequency on the fitness-fatigue model applied to resistance training: a simulation approach. (2019)
Journal Article
STEPHENS HEMINGWAY, B.H., BURGESS, K.E., ELYAN, E. and SWINTON, P.A. 2020. The effects of measurement error and testing frequency on the fitness-fatigue model applied to resistance training: a simulation approach. International journal of sports science and coaching [online], 15(1), pages 60-71. Available from: https://doi.org/10.1177/1747954119887721

This study investigated the effects of measurement error and testing frequency on prediction accuracy of the standard fitness-fatigue model. A simulation-based approach was used to systematically assess measurement error and frequency inputs commonly... Read More about The effects of measurement error and testing frequency on the fitness-fatigue model applied to resistance training: a simulation approach..

Data stream mining: methods and challenges for handling concept drift. (2019)
Journal Article
WARES, S., ISAACS, J. and ELYAN, E. 2019. Data stream mining: methods and challenges for handling concept drift. SN applied sciences [online], 1(11), article ID 1412. Available from: https://doi.org/10.1007/s42452-019-1433-0

Mining and analysing streaming data is crucial for many applications, and this area of research has gained extensive attention over the past decade. However, there are several inherent problems that continue to challenge the hardware and the state-of... Read More about Data stream mining: methods and challenges for handling concept drift..

室内3D点云模型的门窗检测. (2019)
Journal Article
SHEN, L., LI, G., XIAN, C., JIANG, Y. and XIONG, Y. 2019. 室内3D点云模型的门窗检测. Jisuanji fuzhu sheji yu tuxingxue xuebao/Journal of computer-aided design and computer graphics [online], 31(9), pages 1494-1501. Available from: https://doi.org/10.3724/SP.J.1089.2019.17575

This paper proposes a 3D-2D-3D algorithm for doors and windows detection in 3D indoor environment of point cloud data. Firstly, by setting up a virtual camera in the middle of this 3D environment, a set of pictures are taken from different angles by... Read More about 室内3D点云模型的门窗检测..

Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. (2019)
Journal Article
WANG, C., HOU, J., MILLER, D., BROWN, I. and JIANG, Y. 2019. Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. International journal of disaster risk reduction [online], 39, article ID 101139. Available from: https://doi.org/10.1016/j.ijdrr.2019.101139

The Sponge City concept has been promoted as a major programme of work to address increasing flood risk in urban areas, in combination with wider benefits for water resources and urban renewal. However, realization of the concept requires collaborati... Read More about Flood risk management in sponge cities: the role of integrated simulation and 3D visualization..