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The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project. (2020)
Conference Proceeding
IACOB, C. and FAILY, S. 2020. The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project. In Proceedings of the 51st ACM technical symposium on computer science education (SIGCSE 2020), 11-14 March 2020, Portland, USA. New York: ACM [online], pages 128-134. Available from: https://doi.org/10.1145/3328778.3366835

Mentorship schemes in software engineering education usually involve professional software engineers guiding and advising teams of undergraduate students working collaboratively to develop a software system. With or without mentorship, teams run the... Read More about The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project..

Identifying safety and human factors issues in rail using IRIS and CAIRIS. (2020)
Conference Proceeding
ALTAF, A., FAILY, S., DOGAN, H., MYLONAS, A. and THRON, E. 2020. Identifying safety and human factors issues in rail using IRIS and CAIRIS. In Katsikas, S., Cuppens, F., Cuppens, N., Lambrinoudakis, C., Kalloniatis, C., Mylopoulos, J., Antón, A., Gritzalis, S., Pallas, F., Pohle, J., Sasse, A., Meng, W., Furnell, S. and Garcia-Alfaro, J. (eds.) Computer security: ESORICS 2019 international workshops, CyberICPS, SECPRE, SPOSE and ADIoT: revised selected papers from the 5th Workshop on security of industrial control systems and cyber-physical systems (CyberICPS 2019), co-located with the 24th European symposium on research in computer security (ESORICS 2019), 26-27 September 2019, Luxembourg City, Luxembourg. Lecture notes in computer science, 11980. Cham: Springer [online], pages 98-107. Available from: https://doi.org/10.1007/978-3-030-42048-2_7

Security, safety and human factors engineering techniques are largely disconnected although the concepts are interlinked. We present a tool-supported approach based on the Integrating Requirements and Information Security (IRIS) framework using Compu... Read More about Identifying safety and human factors issues in rail using IRIS and CAIRIS..

Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform. (2020)
Conference Proceeding
TSOHOU, A., MAGKOS, M., MOURATIDIS, H., CHRYSOLORAS, G., PIRAS, L., PAVLIDIS, M., DEBUSSCHE, J., ROTOLONI, M. and GALLEGO-NICASIO CRESPO, B. 2019. Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform. In Katsikas, S., Cuppens, F., Cuppens, N. et.al (eds.) Computer security: revised and selected papers of 24th European symposium on research in computer security international workshops 2019 (ESORICS 2019), co-located with 5th Security of industrial control systems and cyber-physical systems international workshops (CyberICPS 2019), 3rd Security and privacy requirements engineering international workshops (SECPRE 2019), 1st Security, privacy organizations and systems engineering international workshops (SPOSE 2019) and 2nd Attacks and defences for Internet-of-Things international workshops (ADIoT 2019), 26-27 September 2019, Luxembourg City, Luxembourg. Lecture notes in computer science, 11980. Cham: Springer [online], pages 204- 223. Available from: https://doi.org/10.1007/978-3-030-42048-2_14

GDPR entered into force in May 2018 for enhancing user data protection. Even though GDPR leads towards a radical change with many advantages for the data subjects it turned out to be a significant challenge. Organizations need to make long and comple... Read More about Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform..

A knowledge-light approach to personalised and open-ended human activity recognition. (2020)
Journal Article
WIJEKOON, A., WIRATUNGA, N., SANI, S. and COOPER, K. 2020. A knowledge-light approach to personalised and open-ended human activity recognition. Knowledge-based systems [online], 192, article ID 105651. Available from: https://doi.org/10.1016/j.knosys.2020.105651

Human Activity Recognition (HAR) is a core component of clinical decision support systems that rely on activity monitoring for self-management of chronic conditions such as Musculoskeletal Disorders. Deployment success of such applications in part de... Read More about A knowledge-light approach to personalised and open-ended human activity recognition..

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..

Varietal classification of rice seeds using RGB and hyperspectral images. (2020)
Journal Article
FABIYI, S.D., VU, H., TACHTATZIS, C., MURRAY, P., HARLE, D., DAO, T.K., ANDONOVIC, I., REN, J. and MARSHALL, S. 2020. Varietal classification of rice seeds using RGB and hyperspectral images. IEEE access [online], 8, pages 22493-22505. Available from: https://doi.org/10.1109/ACCESS.2020.2969847

Inspection of rice seeds is a crucial task for plant nurseries and farmers since it ensures seed quality when growing seedlings. Conventionally, this process is performed by expert inspectors who manually screen large samples of rice seeds to identif... Read More about Varietal classification of rice seeds using RGB and hyperspectral images..

MIMN-DPP: maximum-information and minimum-noise determinantal point processes for unsupervised hyperspectral band selection. (2020)
Journal Article
CHEN, W., YANG, Z., REN, J., CAO, J., CAI, N., ZHAO, H. and YUEN, P. 2020. MIMN-DPP: maximum-information and minimum-noise determinantal point processes for unsupervised hyperspectral band selection. Pattern recognition [online], 102, article 107213. Available from: https://doi.org/10.1016/j.patcog.2020.107213

Band selection plays an important role in hyperspectral imaging for reducing the data and improving the efficiency of data acquisition and analysis whilst significantly lowering the cost of the imaging system. Without the category labels, it is chall... Read More about MIMN-DPP: maximum-information and minimum-noise determinantal point processes for unsupervised hyperspectral band selection..

Human activity recognition with deep metric learners. (2020)
Conference Proceeding
MARTIN, K., WIJEKOON, A. and WIRATUNGA, N. 2019. Human activity recognition with deep metric learners. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19), 8-12 September 2019, Otzenhausen, Germany. CEUR Workshop Proceedings, 2567. Aachen: CEUR-WS [online], pages 8-17. Available from: http://ceur-ws.org/Vol-2567/paper1.pdf

Establishing a strong foundation for similarity-based return is a top priority in Case-Based Reasoning (CBR) systems. Deep Metric Learners (DMLs) are a group of neural network architectures which learn to optimise case representations for similarity-... Read More about Human activity recognition with deep metric learners..

Automatic extraction of water inundation areas using Sentinel-1 data for large plain areas. (2020)
Journal Article
HU, S., QIN, J., REN, J., ZHAO, H., REN, J., and HONG, H. 2020. Automatic extraction of water inundation areas using sentinel-1 data for large plain areas. Remote sensing [online], 12(2), article 243. Available from: https://doi.org/10.3390/rs12020243

Accurately quantifying water inundation dynamics in terms of both spatial distributions and temporal variability is essential for water resources management. Currently, the water map is usually derived from synthetic aperture radar (SAR) data with th... Read More about Automatic extraction of water inundation areas using Sentinel-1 data for large plain areas..