Research Repository

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Human activity recognition with deep metric learners. (2019)
Conference Proceeding
MARTIN, K., WIJEKOON, A. and WIRATUNGA, N. [2019]. Human activity recognition with deep metric learners. In Workshop proceedings of the 27th International conference on case-based reasoning (ICCBR 2019), 8-12 September 2019, Otzenhausen, Germany. CEUR workshop proceedings: CEUR-WS [online], (accepted).

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

Introducing the dynamic customer location-allocation problem. (2019)
Conference Proceeding
ANKRAH, R., LACROIX, B., MCCALL, J., HARDWICK, A. and CONWAY, A. 2019. Introducing the dynamic customer location-allocation problem. In Proceedings of the 2019 Institute of Electrical and Electronics Engineers (IEEE) Congress on evolutionary computation (IEEE CEC 2019), 10-13 June 2019, Wellington, NZ. Piscataway: IEEE [online], pages 3157-3164. Available from: https://doi.org/10.1109/CEC.2019.8790150.

In this paper, we introduce a new stochastic Location-Allocation Problem which assumes the movement of customers over time. We call this new problem Dynamic Customer Location-Allocation Problem (DC-LAP). The problem is based on the idea that customer... Read More

Comparative analysis of two asynchronous parallelization variants for a multi-objective coevolutionary solver. (2019)
Conference Proceeding
ZAVOIANU, A.-C., SAMINGER-PLATZ, S. and AMRHEIN, W. 2019. Comparative analysis of two asynchronous parallelization variants for a multi-objective coevolutionary solver. In Proceedings of the 2019 Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2019), 10-13 June 2019, Wellington, New Zealand. Piscataway: IEEE [online], (accepted).

We describe and compare two steady state asynchronous parallelization variants for DECMO2++, a recently proposed multi-objective coevolutionary solver that generally displays a robust run-time convergence behavior. The two asynchronous variants were... Read More

MFC-GAN: class-imbalanced dataset classification using multiple fake class generative adversarial network. (2019)
Journal Article
ALI-GOMBE, A. and ELYAN, E. 2019. MFC-GAN: class-imbalanced dataset classification using multiple fake class generative adversarial network. Neurocomputing [online], 361, pages 212-221. Available from: https://doi.org/10.1016/j.neucom.2019.06.043

Class-imbalanced datasets are common across different domains such as health, banking, security and others. With such datasets, the learning algorithms are often biased toward the majority class-instances. Data Augmentation is a common approach tha... Read More

Simultaneous meta-data and meta-classifier selection in multiple classifier system. (2019)
Conference Proceeding
NGUYEN, T.T., LUONG, A.V., NGUYEN, T.M.V., HA, T.S., LIEW, A.W.-C. and MCCALL, J. 2019. Simultaneous meta-data and meta-classifier selection in multiple classifier system. In López-Ibáñez, M. (ed.) Proceedings of the 2019 Genetic and evolutionary computation conference (GECCO ’19), 13-17 July 2019, Prague, Czech Republic. New York: ACM [online], pages 39-46. Available from: https://doi.org/10.1145/3321707.3321770

In ensemble systems, the predictions of base classifiers are aggregated by a combining algorithm (meta-classifier) to achieve better classification accuracy than using a single classifier. Experiments show that the performance of ensembles significan... Read More

Potential identification and industrial evaluation of an integrated design automation workflow. (2019)
Journal Article
ENTNER, D., PRANTE, T., VOSGIEN, T., ZAVOIANU, A.-C., SAMINGER-PLATZ, S., SCHWARZ, M. and FINK, K. 2019. Potential identification and industrial evaluation of an integrated design automation workflow. Journal of engineering, design and technology [online], Earlycite. Available from: https://doi.org/10.1108/jedt-06-2018-0096

Purpose - The paper aims to raise awareness in the industry of design automation tools, especially in early design phases, by demonstrating along a case study the seamless integration of a prototypically implemented optimization, supporting design sp... Read More

Learning to self-manage by intelligent monitoring, prediction and intervention. (2019)
Conference Proceeding
WIRATUNGA, N., CORSAR, D., MARTIN, K., WIJEKOON, A., ELYAN, E., COOPER, K., IBRAHIM, Z., CELIKTUTAN, O., DOBSON, R.J., ABD-ALHAMMED, R., QAHWAJI, R. and CHAUDHURI, R. 2019. Learning to self-manage by intelligent monitoring, prediction and intervention. Presented at the 4th International workshop on knowledge discovery in healthcare data (KDH 2019), co-located with the 28th International joint conference on artificial intelligence (IJCAI-19), 10-11 August 2019, Macao, China. CEUR workshop proceedings. Aachen: CEUR-WS [online], (accepted).

Despite the growing prevalence of multimorbidities, current digital self-management approaches still prioritise single conditions. The future of out-of-hospital care requires researchers to expand their horizons; integrated assistive technologies sho... Read More

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

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): proceedings of the 13th International conference of the European Academy of Design (EAD 2019): running with scissors, 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

Video tampering localisation using features learned from authentic content. (2019)
Journal Article
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2019. Video tampering localisation using features learned from authentic content. Neural computing and applications [online], Latest Articles. 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

A fuzzy inference system applied to value of information assessment for oil and gas industry. (2019)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2019. A fuzzy inference system applied to value of information assessment for oil and gas industry. Decision making: applications in management and engineering [online], Online First. Available from: https:// doi.org/10.31181/dmame1902001v

Value of information is a widely accepted methodology for evaluating the need to acquire new data in the oil and gas industry. In the conventional approach to estimating the value of information, the outcomes of a project assessment relate to the dec... Read More

Generalised median of graph correspondences. (2019)
Journal Article
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2019. Generalised median of graph correspondences. Pattern recognition letters [online], 125, pages 389-395. Available from: https://doi.org/10.1016/j.patrec.2019.05.015

A graph correspondence is defined as a function that maps the elements of two attributed graphs. Due to the increasing availability of methods to perform graph matching, numerous graph correspondences can be deducted for a pair of attributed graphs.... Read More

Fuzzy logic applied to value of information assessment in oil and gas projects. (2019)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. [2019]. Fuzzy logic applied to value of information assessment in oil and gas projects. Petroleum science [online], (accepted).

The concept of value of information (VOI) has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields. The classical approach to VOI assumes that the outcome of th... Read More

Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour. (2019)
Journal Article
YEBOAH, G., COTTRILL, C.D., NELSON, J.D., CORSAR, D., MARKOVIC, M. and EDWARDS, P. 2019. Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour. Public transport [online], 11(1), pages 135-158. Available from: https://doi.org/10.1007/s12469-019-00198-w

This paper investigates factors influencing public transport passengers’ pre-travel information-seeking behaviours in a British urban environment. Public transport traveller surveys were conducted to better understand the journey stages at which info... Read More

Minimality and simplicity of rules for the internet-of-things. (2019)
Conference Proceeding
PANARETOS, A., CORSAR, D. and VASCONCELOS, W.W. 2019. Minimality and simplicity of rules for the internet-of things. In Lujak, M. (ed.) Agreement technologies: revised selected papers from the 6th International conference on agreement technologies (AT 2018), 6-7 December 2018, Bergen, Norway. Lecture notes in computer science, 11327. Cham: Springer [online], pages 64-72. Available from: https://doi.org/10.1007/978-3-030-17294-7_5

Rule-based systems have been increasing in popularity in recent years. They allow for easier handling of both simple and complicated problems utilising a set of rules created in various ways (e.g., manually, or (semi-) automatically, via, say, machin... Read More

Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. (2019)
Journal Article
WANG, C., HOU, J., MILLER, D., BROWN, I. and JIANG, Y. 2019. Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. International journal of disaster risk reduction [online], In Press. Available from: https://doi.org/10.1016/j.ijdrr.2019.101139

The Sponge City concept has been promoted as a major programme of work to address increasing flood risk in urban areas, in combination with wider benefits for water resources and urban renewal. However, realization of the concept requires collaborati... Read More

A weighted multiple classifier framework based on random projection. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LIEW, A. W.-C. and BEZDEK, J.C. 2019. A weighted multiple classifier framework based on random projection. Information science [online], 490, pages 36-58. Available from: https://doi.org/10.1016/j.ins.2019.03.067

In this paper, we propose a weighted multiple classifier framework based on random projections. Similar to the mechanism of other homogeneous ensemble methods, the base classifiers in our approach are obtained by a learning algorithm on different tra... Read More

A review of digital video tampering: from simple editing to full synthesis. (2019)
Journal Article
JOHNSTON, P. and ELYAN, E. 2019. A review of digital video tampering: from simple editing to full synthesis. Digital investigation [online], 29, pages 67-81. Available from: https://doi.org/10.1016/j.diin.2019.03.006

Video tampering methods have witnessed considerable progress in recent years. This is partly due to the rapid development of advanced deep learning methods, and also due to the large volume of video footage that is now in the public domain. Historica... Read More

A lossless online Bayesian classifier. (2019)
Journal Article
NGUYEN, T.T.T., NGUYEN, T.T., SHARMA, R. and LIEW, A. W.-C. 2019. A lossless online Bayesian classifier. Information sciences [online], 489, pages 1-17. Available from: https://doi.org/10.1016/j.ins.2019.03.031

We are living in a world progressively driven by data. Besides the issue that big data cannot be entirely stored in the main memory as required by traditional offline learning methods, the problem of learning data that can only be collected over time... Read More

Fall prediction using behavioural modelling from sensor data in smart homes. (2019)
Journal Article
FORBES, G., MASSIE, S. and CRAW, S. 2019. Fall prediction using behavioural modelling from sensor data in smart homes. Artificial intelligence review [online], Online First. 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