Outputs (1084)

Confidence in prediction: an approach for dynamic weighted ensemble. (2020)
Conference Proceeding
DO D.T., NGUYEN T.T., NGUYEN T.T., LUONG A.V., LIEW A.W.-C. and MCCALL J. 2020. Confidence in prediction: an approach for dynamic weighted ensemble. In Nguyen N., Jearanaitanakij K., Selamat A., Trawiński B. and Chittayasothorn S. (eds.) Intelligent information and database systems: proceedings of the 12th Asian intelligent information and database systems conference (ACIIDS 2020), 23-26 March 2020, Phuket, Thailand. Lecture Notes in Computer Science, 12033. Cham: Springer [online], part 1, pages 358-370. Available from: https://doi.org/10.1007/978-3-030-41964-6_31

Combining classifiers in an ensemble is beneficial in achieving better prediction than using a single classifier. Furthermore, each classifier can be associated with a weight in the aggregation to boost the performance of the ensemble system. In this... Read More about Confidence in prediction: an approach for dynamic weighted ensemble..

Employing multi-modal sensors for personalised smart home health monitoring. (2020)
Conference Proceeding
FORBES, G. 2019. Employing multi-modal sensors for personalised smart home health monitoring. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 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], paper 19, pages 185-190. Available from: http://ceur-ws.org/Vol-2567/paper19.pdf

As the prevalence of IoT sensor equipment in smart homes continues to rise, long term monitoring for personalised and more representative health tracking has become more accessible. The estimation of physiological health factors such as gait and hear... Read More about Employing multi-modal sensors for personalised smart home health monitoring..

Preface: case-based reasoning and deep learning. (2020)
Conference Proceeding
MARTIN, K., KAPETANAKIS, S., WIJEKOON, A., AMIN, K. and MASSIE, S. 2019. Preface: case-based reasoning and deep learning. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 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 6-7. Available from: http://ceur-ws.org/Vol-2567/cbr_dl_preface.pdf

Recent advances in deep learning (DL) have helped to usher in a new wave of confidence in the capability of artificial intelligence. Increasingly, we are seeing DL architectures out perform long established state-of-the-art algorithms in a numb... Read More about Preface: case-based reasoning and deep learning..

Representing temporal dependencies in human activity recognition. (2020)
Conference Proceeding
FORBES, G., MASSIE, S., CRAW, S., FRASER, L. and HAMILTON, G. 2019. Representing temporal dependencies in human activity recognition. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 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 29-38. Available from: http://ceur-ws.org/Vol-2567/paper3.pdf

Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A pro... Read More about Representing temporal dependencies in human activity recognition..

Weakly supervised conditional random fields model for semantic segmentation with image patches. (2020)
Journal Article
XU, X., XUE, Y., HAN, X., ZHANG, Z., XIE, J. and REN, J. 2020. Weakly supervised conditional random fields model for semantic segmentation with image patches. Applied sciences [online], 10(5), article 1679. Available from: https://doi.org/10.3390/app10051679

Image semantic segmentation (ISS) is used to segment an image into regions with differently labeled semantic category. Most of the existing ISS methods are based on fully supervised learning, which requires pixel-level labeling for training the model... Read More about Weakly supervised conditional random fields model for semantic segmentation with image patches..

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..