All Outputs (58)

Multi-layer heterogeneous ensemble with classifier and feature selection. (2020)
Conference Proceeding
NGUYEN, T.T., VAN PHAM, N., DANG, M.T., LUONG, A.V., MCCALL, J. and LIEW, A.W.C. 2020. Multi-layer heterogeneous ensemble with classifier and feature selection. In GECCO '20: proceedings of the Genetic and evolutionary computation conference (GECCO 2020), 8-12 July 2020, Cancun, Mexico. New York: ACM [online], pages 725-733. Available from: https://doi.org/10.1145/3377930.3389832

Deep Neural Networks have achieved many successes when applying to visual, text, and speech information in various domains. The crucial reasons behind these successes are the multi-layer architecture and the in-model feature transformation of deep le... Read More about Multi-layer heterogeneous ensemble with classifier and feature selection..

The importance of embedding meta skills in computer science graduate apprenticeship programmes. (2020)
Conference Proceeding
YOUNG, T. 2020. The importance of embedding meta skills in computer science graduate apprenticeship programmes. In Proceedings of the 25th Association for Computing Machinery (ACM) Innovation and technology in computer science education conference 2020 (ITiCSE '20), 15-19 June 2020, Trondheim, Norway. New York: ACM [online], pages 589-590. Available from: https://doi.org/10.1145/3341525.3394010

The purpose of this proposal is to investigate the need for the increased focus on developing transferable and meta skills of Graduate Apprentice Computer Science students and how the advancements of technology can impact the need for this. The Fourt... Read More about The importance of embedding meta skills in computer science graduate apprenticeship programmes..

Through the lens: enhancing assessment with video-based presentation. (2020)
Conference Proceeding
ZARB, M. and BIRTLESKELMAN, J. 2020. Through the lens: enhancing assessment with video-based presentations. In Proceedings of the 25th Association for Computing Machinery (ACM) Innovation and technology in computer science education conference 2020 (ITiCSE '20), 15-19 June 2020, Trondheim, Norway. New York: ACM [online], pages 187-192. Available from: https://doi.org/10.1145/3341525.3387376

This paper discusses a video-based approach trialled within Robert Gordon University. Students are typically asked to formally deliver presentations (either individually, or in groups) for summative assessment. Timetabling issues, large student numbe... Read More about Through the lens: enhancing assessment with video-based presentation..

Overlap-based undersampling method for classification of imbalanced medical datasets. (2020)
Conference Proceeding
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Overlap-based undersampling method for classification of imbalanced medical datasets. In Maglogiannis, I., Iliadis, L. and Pimenidis, E. (eds.) Artificial intelligence applications and innovations: AIAI 2020; proceedings of 16th International Federation for Information Processing working group (IFIP WG) 12.5 International artificial intelligence applications and innovations, 5-7 June 2020, Halkidiki, Greece. IFIP advances in information and communication technology, 584. Cham: Springer [online], pages 358-369. Available from: https://doi.org/10.1007/978-3-030-49186-4_30

Early diagnosis of some life-threatening diseases such as cancers and heart is crucial for effective treatments. Supervised machine learning has proved to be a very useful tool to serve this purpose. Historical data of patients including clinical and... Read More about Overlap-based undersampling method for classification of imbalanced medical datasets..

Evaluating the transferability of personalised exercise recognition models. (2020)
Conference Proceeding
WIJEKOON, A. and WIRATUNGA, N. 2020. Evaluating the transferability of personalised exercise recognition models. In Iliadis, L., Angelov, P.P., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 21st Engineering applications of neural networks conference 2020 (EANN 2020): proceedings of the EANN 2020, 5-7 June 2020, Halkidiki, Greece. Proceedings of the International Neural Networks Society, 2. Cham: Springer [online], pages 32-44. Available from: https://doi.org/10.1007/978-3-030-48791-1_3

Exercise Recognition (ExR) is relevant in many high impact domains, from health care to recreational activities to sports sciences. Like Human Activity Recognition (HAR), ExR faces many challenges when deployed in the real-world. For instance, typica... Read More about Evaluating the transferability of personalised exercise recognition models..

Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks. (2020)
Conference Proceeding
ELYAN, E., MORENO-GARCÍA, C.F. and JOHNSTON, P. 2020. Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks. In Iliadis, L., Angelov, P.P., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 21st Engineering applications of neural networks conference 2020 (EANN 2020); proceedings of the EANN 2020, 5-7 June 2020, Halkidiki, Greece. Proceedings of the International Neural Networks Society, 2. Cham: Springer [online], pages 215-224. Available from: https://doi.org/10.1007/978-3-030-48791-1_16

Engineering drawings are common across different domains such as Oil & Gas, construction, mechanical and other domains. Automatic processing and analysis of these drawings is a challenging task. This is partly due to the complexity of these documents... Read More about Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks..

Predicting permeability based on core analysis. (2020)
Conference Proceeding
KONTOPOULOS, H., AHRIZ, H., ELYAN, E. and ARNOLD, R. 2020. Predicting permeability based on core analysis. In Iliadis, L., Angelov, P.P., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 21st Engineering applications of neural networks conference 2020 (EANN 2020); proceedings of the EANN 2020, 5-7 June 2020, Halkidiki, Greece. Proceedings of the International Neural Networks Society, vol 2. Cham: Springer [online], pages 143-154. Available from: https://doi.org/10.1007/978-3-030-48791-1_10

Knowledge of permeability, a measure of the ability of rocks to allow fluids to flow through them, is essential for building accurate models of oil and gas reservoirs. Permeability is best measured in the laboratory using special core analysis (SCAL)... Read More about Predicting permeability based on core analysis..

Towards a reliable face recognition system. (2020)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E. and ZWIEGELAAR, J. 2020. Towards a reliable face recognition system. In Iliadis, L., Angelov, P.P., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 21st Engineering applications of neural networks conference 2020 (EANN 2020); proceedings of the EANN 2020, 5-7 June 2020, Halkidiki, Greece. Proceedings of the International Neural Networks Society, 2. Cham: Springer [online], pages 304-316. Available from: https://doi.org/10.1007/978-3-030-48791-1_23

Face Recognition (FR) is an important area in computer vision with many applications such as security and automated border controls. The recent advancements in this domain have pushed the performance of models to human-level accuracy. However, the va... Read More about Towards a reliable face recognition system..

Learning to recognise exercises for the self-management of low back pain. (2020)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., COOPER, K. and BACH, K. 2020. Learning to recognise exercises for the self-management of low back pain. In Barták, R. and Bell, E. (eds.). Proceedings of the 33rd International Florida Artificial Intelligence Research Society (FLAIRS) 2020 conference (FLAIRS-33), 17-20 May 2020, Miami Beach, USA. Palo Alto: AAAI Press [online], pages 347-352. Available from: https://aaai.org/ocs/index.php/FLAIRS/FLAIRS20/paper/view/18460

Globally, Low back pain (LBP) is one of the top three contributors to years lived with disability. Self-management with an active lifestyle is the cornerstone for preventing and managing LBP. Digital interventions are introduced in the recent past to... Read More about Learning to recognise exercises for the self-management of low back pain..

On modeling the dynamic thermal behavior of electrical machines using genetic programming and artificial neural networks. (2020)
Conference Proceeding
ZAVOIANU, A.-C., KITZBERGER, M., BRAMERDORFER, G. and SAMINGER-PLATZ, S. 2020. On modeling the dynamic thermal behavior of electrical machines using genetic programming and artificial neural networks. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: EUROCAST 2019: revised selected papers from the proceedings of the 17th International conference on computer aided systems theory (EUROCAST 2019), 17-22 February 2019, Las Palmas de Gran Canaria, Spain. Lecture notes in computer science, 12013. Cham: Springer [online], part 1, pages 319-326. Available from: https://doi.org/10.1007/978-3-030-45093-9_39

We describe initial attempts to model the dynamic thermal behavior of electrical machines by evaluating the ability of linear and non-linear (regression) modeling techniques to replicate the performance of simulations carried out using a lumped param... Read More about On modeling the dynamic thermal behavior of electrical machines using genetic programming and artificial neural networks..

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..

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..

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..

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..

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..

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 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 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..