Outputs (151)

Critically introducing an online peer review CampusMoodle Audit Tool (CMAT) project. (2020)
Presentation / Conference Contribution
WORK, F., LUDERS, S., GOODHAND, K. and EBOH, W. 2020. Critically introducing an online peer review CampusMoodle Audit Tool (CMAT) project. In Gómez Chova, L., López Martínez, A. and Candel Torres, I. (eds.) Proceedings of the 12th International conference on education and new learning technologies 2020 (EDULEARN20), 6-7 July 2020, [virtual event]. Valencia: IATED [online], pages 525-534. Available from: https://doi.org/10.21125/edulearn.2020.0223

This study critically introduces a CampusMoodle Audit Tool (CMAT) online peer–mentoring project. In this presentation, we share lessons and findings from research on a CMAT project for sharing best practice in Scotland. The rationale for the research... Read More about Critically introducing an online peer review CampusMoodle Audit Tool (CMAT) project..

Wifi-based human activity recognition using Raspberry Pi. (2020)
Presentation / Conference Contribution
FORBES, G., MASSIE, S. and CRAW, S. 2020. Wifi-based human activity recognition using Raspberry Pi. In Alamaniotis, M. and Pan, S. (eds.) Proceedings of Institute of Electrical and Electronics Engineers (IEEE) 32nd Tools with artificial intelligence international conference 2020 (ICTAI 2020), 9-11 Nov 2020, [virtual event]. Piscataway: IEEE [online], pages 722-730. Available from: https://doi.org/10.1109/ICTAI50040.2020.00115

Ambient, non-intrusive approaches to smart home health monitoring, while limited in capability, are preferred by residents. More intrusive methods of sensing, such as video and wearables, can offer richer data but at the cost of lower resident uptake... Read More about Wifi-based human activity recognition using Raspberry Pi..

An IoT based industry 4.0 architecture for integration of design and manufacturing systems. (2020)
Presentation / Conference Contribution
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 event], 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..

Maddie is online: an educational video cartoon series on digital literacy and resilience for children. (2020)
Journal Article
MARTZOUKOU, K. 2022. Maddie is online: an educational video cartoon series on digital literacy and resilience for children. Journal of research in innovative teaching and learning [online], 15(1), pages 64-82. Available from: https://doi.org/10.1108/jrit-06-2020-0031

Purpose – This paper examines children’s development of digital literacy, resilience and citizenship in the online environment, addressing active engagement, and participation via cartoon videos. Previous research has emphasised the positive role of... Read More about Maddie is online: an educational video cartoon series on digital literacy and resilience for children..

Building a virtual degree show: Gray's School of Art. [Film] (2020)
Digital Artefact
KELLIE, C. 2020. Building a virtual degree show: Gray's School of Art. [Film]. Hosted on YouTube [online]. Available from: https://www.youtube.com/watch?v=eWfCebO5AVA

In 2020, the COVID-19 pandemic necessitated the adaptation of Gray's School of Art annual degree show into a digital format. This short film uses interviews with staff, students and other key stakeholders who lived through that experience to explore... Read More about Building a virtual degree show: Gray's School of Art. [Film].

Case-based approach to automated natural language generation for obituaries. (2020)
Presentation / Conference Contribution
UPADHYAY, A., MASSIE, S. and CLOGHER, S. 2020. Case-based approach to automated natural language generation for obituaries. In Watson, I. and Weber, R. (eds.) Case-based reasoning research and development: proceedings of the 28th International conference on case-based reasoning research and development (ICCBR 2020), 8-12 June 2020, Salamanca, Spain [virtual conference]. Lecture notes in computer science, 12311. Cham: Springer [online], pages 279-294. Available from: https://doi.org/10.1007/978-3-030-58342-2_18

Automated generation of human readable text from structured information is challenging because grammatical rules are complex making good quality outputs difficult to achieve. Textual Case-Based Reasoning provides one approach in which the text from p... Read More about Case-based approach to automated natural language generation for obituaries..

Assessing the clinicians’ pathway to embed artificial intelligence for assisted diagnostics of fracture detection. (2020)
Presentation / Conference Contribution
MORENO-GARCÍA, C.F., DANG, T., MARTIN, K., PATEL, M., THOMPSON, A., LEISHMAN, L. and WIRATUNGA, N. 2020. Assessing the clinicians’ pathway to embed artificial intelligence for assisted diagnostics of fracture detection. In Bach, K., Bunescu, R., Marling, C. and Wiratunga, N. (eds.) Knowledge discovery in healthcare data 2020: proceedings of the 5th Knowledge discovery in healthcare data international workshop 2020 (KDH 2020), co-located with 24th European Artificial intelligence conference (ECAI 2020), 29-30 August 2020, [virtual conference]. CEUR workshop proceedings, 2675. Aachen: CEUR-WS [online], pages 63-70. Available from: http://ceur-ws.org/Vol-2675/paper10.pdf

Fracture detection has been a long-standingparadigm on the medical imaging community. Many algo-rithms and systems have been presented to accurately detectand classify images in terms of the presence and absence offractures in different parts of the... Read More about Assessing the clinicians’ pathway to embed artificial intelligence for assisted diagnostics of fracture detection..

The folklore-centric gaze: a relational approach to landscape, folklore and tourism. (2020)
Journal Article
IRONSIDE, R. and MASSIE, S. 2020. The folklore-centric gaze: a relational approach to landscape, folklore and tourism. Time and mind [online], 13(3), pages 227-244. Available from: https://doi.org/10.1080/1751696X.2020.1809862

Supernatural folktales have a long oral tradition in Scotland, embedded in local communities and the landscapes of the region. Recently, these folktales have been utilised by destinations as a form of place-making, and a driver for increasing tourist... Read More about The folklore-centric gaze: a relational approach to landscape, folklore and tourism..

WEC: weighted ensemble of text classifiers. (2020)
Presentation / Conference Contribution
UPADHYAY, A., NGUYEN, T.T., MASSIE, S. and MCCALL, J. 2020. WEC: weighted ensemble of text classifiers. In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2020), part of the 2020 (IEEE) World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 International joint conference on neural networks (IJCNN 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 19-24 July 2020, Glasgow, UK [virtual conference]. Piscataway: IEEE [online], article ID 9185641. Available from: https://doi.org/10.1109/CEC48606.2020.9185641

Text classification is one of the most important tasks in the field of Natural Language Processing. There are many approaches that focus on two main aspects: generating an effective representation; and selecting and refining algorithms to build the c... Read More about WEC: weighted ensemble of text classifiers..

Locality sensitive batch selection for triplet networks. (2020)
Presentation / Conference Contribution
MARTIN, K., WIRATUNGA, N. and SANI, S. 2020. Locality sensitive batch selection for triplet networks. In Proceedings of the 2020 Institute of Electrical and Electronics Engineers (IEEE) International joint conference on neural networks (IEEE IJCNN 2020), part of the 2020 IEEE World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 IEEE congress on evolutionary computation (IEEE CEC 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 19-24 July 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9207538. Available from: https://doi.org/10.1109/IJCNN48605.2020.9207538

Triplet networks are deep metric learners which learn to optimise a feature space using similarity knowledge gained from training on triplets of data simultaneously. The architecture relies on the triplet loss function to optimise its weights based u... Read More about Locality sensitive batch selection for triplet networks..

Representing temporal dependencies in smart home activity recognition for health monitoring. (2020)
Presentation / Conference Contribution
FORBES, G., MASSIE, S., CRAW, S., FRASER, L. and HAMILTON, G. 2020. Representing temporal dependencies in smart home activity recognition for health monitoring. In Proceedings of the 2020 Institute of Electrical and Electronics Engineers (IEEE) International joint conference on neural networks (IEEE IJCNN 2020), part of the 2020 IEEE World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 IEEE congress on evolutionary computation (IEEE CEC 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 19-24 July 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9207480. Available from: https://doi.org/10.1109/IJCNN48605.2020.9207480

Long term health conditions, such as fall risk, are traditionally diagnosed through testing performed in hospital environments. Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which m... Read More about Representing temporal dependencies in smart home activity recognition for health monitoring..

Representing temporal dependencies in human activity recognition. (2020)
Presentation / Conference Contribution
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..

Human activity recognition with deep metric learners. (2020)
Presentation / Conference Contribution
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..

The disrupted workplace: are the digital and group skills needs of employers being addressed by universities? (2019)
Presentation / Conference Contribution
BREMNER, P.A.M. and LAING, A. 2019. The disrupted workplace: are the digital and group skills needs of employers being addressed by universities? Journal of learning development in higher education [online], 16: special issue of articles from the 2019 Association for Learning Development in Higher Education conference (ALDINHE 2019), 15-17 April 2019, Exeter, UK, article 535. Available from: https://journal.aldinhe.ac.uk/index.php/jldhe/article/view/535

Upskilling moves quickly in today’s ‘disrupted’ workplace, and skill sets need to change to meet the needs of the digital economy (Gray, 2016), sometimes referred to as the fourth industrial revolution (4IR). Using a mixed methods approach and drawin... Read More about The disrupted workplace: are the digital and group skills needs of employers being addressed by universities?.

Developing a catalogue of explainability methods to support expert and non-expert users. (2019)
Presentation / Conference Contribution
MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2019. Developing a catalogue of explainability methods to support expert and non-expert users. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXVI: proceedings of the 39th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) international Artificial intelligence conference 2019 (AI 2019), 17-19 December 2019, Cambridge, UK. Lecture notes in computer science, 11927. Cham: Springer [online], pages 309-324. Available from: https://doi.org/10.1007/978-3-030-34885-4_24

Organisations face growing legal requirements and ethical responsibilities to ensure that decisions made by their intelligent systems are explainable. However, provisioning of an explanation is often application dependent, causing an extended design... Read More about Developing a catalogue of explainability methods to support expert and non-expert users..

Towards a conversational agent for threat detection in the internet of things. (2019)
Presentation / Conference Contribution
MCDERMOTT, C.D., JEANNELLE, B. and ISAACS, J.P. 2019. Towards a conversational agent for threat detection in the internet of things. In Proceedings of the 2019 International Cyber science on cyber situational awareness, data analytics and assessment (Cyber SA): pioneering research and innovation in cyber situational awareness, 3-4 June 2019, Oxford, UK. Piscataway: IEEE [online], chapter 6. Available from: https://doi.org/10.1109/CyberSA.2019.8899580

A conversational agent to detect anomalous traffic in consumer IoT networks is presented. The agent accepts two inputs in the form of user speech received by Amazon Alexa enabled devices, and classified IDS logs stored in a DynamoDB Table. Aural anal... Read More about Towards a conversational agent for threat detection in the internet of things..

Fall prediction using behavioural modelling from sensor data in smart homes. (2019)
Journal Article
FORBES, G., MASSIE, S. and CRAW, S. 2020. Fall prediction using behavioural modelling from sensor data in smart homes. Artificial intelligence review [online], 53(2), pages 1071-1091. Available from: https://doi.org/10.1007/s10462-019-09687-7

The number of methods for identifying potential fall risk is growing as the rate of elderly fallers continues to rise in the UK. Assessments for identifying risk of falling are usually performed in hospitals and other laboratory environments, however... Read More about Fall prediction using behavioural modelling from sensor data in smart homes..

Informed pair selection for self-paced metric learning in Siamese neural networks. (2018)
Presentation / Conference Contribution
MARTIN, K., WIRATUNGA, N., MASSIE, S. and CLOS, J. 2018. Informed pair selection for self-paced metric learning in Siamese neural networks. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXV: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in computer science, 11311. Cham: Springer [online], pages 34-49. Available from: https://doi.org/10.1007/978-3-030-04191-5_3

Siamese Neural Networks (SNNs) are deep metric learners that use paired instance comparisons to learn similarity. The neural feature maps learnt in this way provide useful representations for classification tasks. Learning in SNNs is not reliant on e... Read More about Informed pair selection for self-paced metric learning in Siamese neural networks..

Risk information recommendation for engineering workers. (2018)
Presentation / Conference Contribution
MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2018. Risk information recommendation for engineering workers. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXV: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in computer science, 11311. Cham: Springer [online], pages 311-325. Available from: https://doi.org/10.1007/978-3-030-04191-5_27

Within any sufficiently expertise-reliant and work-driven domain there is a requirement to understand the similarities between specific work tasks. Though mechanisms to develop similarity models for these areas do exist, in practice they have been cr... Read More about Risk information recommendation for engineering workers..

Personalised human activity recognition using matching networks. (2018)
Presentation / Conference Contribution
SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2018. Personalised human activity recognition using matching networks. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 339-353. Available from: https://doi.org/10.1007/978-3-030-01081-2_23

Human Activity Recognition (HAR) is typically modelled as a classification task where sensor data associated with activity labels are used to train a classifier to recognise future occurrences of these activities. An important consideration when trai... Read More about Personalised human activity recognition using matching networks..