Outputs (94)

Challenges of delivering a graduate apprenticeship. (2019)
Conference Proceeding
YOUNG, T. and ZARB, M. 2019. Challenges of delivering a graduate apprenticeship. In Proceedings of the 24th Innovation and technology in computer science education annual conference (ITiCSE 2019), 15-17 July 2019, Aberdeen, UK. New York: ACM Press [online], page 327. Available from: https://doi.org/10.1145/3304221.3325566

Graduate Apprenticeship degree programmes look to overcome the segregation of learning and working, by integrating traditional education into the context of the work environment. This poster abstract showcases a number of actions that were put into p... Read More about Challenges of delivering a graduate apprenticeship..

An efficient face recognition system using local binary pattern. (2019)
Journal Article
VISHAL, P., SNIGDHA, L.K. and BANO, S. 2019. An efficient face recognition system using local binary pattern. International journal of recent technology and engineering [online], 8(1S4), article number A11680681S419, pages 912-914. Available from: https://www.ijrte.org/portfolio-item/A11680681S419/

Facial recognition is a critical and prominent aspect of current research into image processing and computer vision, with particular applications including confront location, confront acknowledgement and outward appearance investigation. A basic adva... Read More about An efficient face recognition system using local binary pattern..

Representation and learning schemes for argument stance mining. (2019)
Thesis
CLOS, J. 2019. Representation and learning schemes for argument stance mining. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Argumentation is a key part of human interaction. Used introspectively, it searches for the truth, by laying down argument for and against positions. As a mediation tool, it can be used to search for compromise between multiple human agents. For this... Read More about Representation and learning schemes for argument stance mining..

A normative decision-making model for cyber security. (2019)
Journal Article
M'MANGA, A., FAILY, S., MCALANEY, J., WILLIAMS, C., KADOBAYASHI, Y. and MIYAMOTO, D. 2019. A normative decision-making model for cyber security. Information and computer security [online], 27(5), pages 636-646. Available from: https://doi.org/10.1108/ICS-01-2019-0021

The purpose of this paper is to investigate security decision-making during risk and uncertain conditions, and to propose a normative model capable of tracing the decision rationale. The proposed risk rationalisation model is grounded in literature a... Read More about A normative decision-making model for cyber security..

Hierarchical approach to classify food scenes in egocentric photo-streams. (2019)
Journal Article
MARTINEZ, E.T., LEYVA-VALLINA, M., SARKER, M.M.K., PUIG, D., PETKOV, N. and RADEVA, P. 2020. Hierarchical approach to classify food scenes in egocentric photo-streams. IEEE journal of biomedical and health informatics [online], 24(3), pages 866-877. Available from: https://doi.org/10.1109/JBHI.2019.2922390

Recent studies have shown that the environment where people eat can affect their nutritional behavior. In this paper, we provide automatic tools for personalized analysis of a person's health habits by the examination of daily recorded egocentric pho... Read More about Hierarchical approach to classify food scenes in egocentric photo-streams..

Multi-label classification via incremental clustering on an evolving data stream. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LUONG, A.V., LIEW, A. W.-C., LIANG, T. and MCCALL, J. 2019. Multi-label classification via incremental clustering on an evolving data stream. Pattern recognition [online], 95, pages 96-113. Available from: https://doi.org/10.1016/j.patcog.2019.06.001

With the advancement of storage and processing technology, an enormous amount of data is collected on a daily basis in many applications. Nowadays, advanced data analytics have been used to mine the collected data for useful information and make pred... Read More about Multi-label classification via incremental clustering on an evolving data stream..

Inclusive design for immersive spaces. (2019)
Journal Article
CRABB, M., CLARKE, D., ALWAER, H., HERON, M. and LAING, R. 2019. Inclusive design for immersive spaces. Design journal [online], 22(Sup 1: running with scissors: proceedings from 13th European Academy of Design international conference (EAD 2019), 10-12 April 2019, Dundee, UK), pages 2105-2118. Available from: https://doi.org/10.1080/14606925.2019.1594934

It is vital when creating learning environments that attention is paid towards individuals using a given space, activities that they will carry out, and the available equipment that will facilitate this. It is also important that these spaces are cre... Read More about Inclusive design for immersive spaces..

Aspect-based sentiment analysis for social recommender systems. (2019)
Thesis
CHEN, Y.Y. 2019. Aspect-based sentiment analysis for social recommender systems. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Social recommender systems harness knowledge from social content, experiences and interactions to provide recommendations to users. The retrieval and ranking of products, using similarity knowledge, is central to the recommendation architecture. To e... Read More about Aspect-based sentiment analysis for social recommender systems..

Ontology driven information retrieval. (2019)
Thesis
NKISI-ORJI, I. 2019. Ontology driven information retrieval. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Ontology-driven information retrieval deals with the use of entities specified in domain ontologies to enhance search and browse. The entities or concepts of lightweight ontological resources are traditionally used to index resources in specialised d... Read More about Ontology driven information retrieval..

Video tampering localisation using features learned from authentic content. (2019)
Journal Article
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2020. Video tampering localisation using features learned from authentic content. Neural computing and applications [online], 32(16): special issue on Real-world optimization problems and meta-heuristics and selected papers from the 19th Engineering applications of neural networks conference 2018 (EANN 2018), 3-5 September 2018, Bristol UK , pages 12243-12257. Available from: https://doi.org/10.1007/s00521-019-04272-z

Video tampering detection remains an open problem in the field of digital media forensics. As video manipulation techniques advance, it becomes easier for tamperers to create convincing forgeries that can fool human eyes. Deep learning methods have a... Read More about Video tampering localisation using features learned from authentic content..