All Outputs (86)

Improving human activity recognition with neural translator models. (2018)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N. and SANI, S. 2018. Improving human activity recognition with neural translator models. In Minor, M. (ed.) Workshop proceedings for the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 96-100. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=96

Multiple sensor modalities provide more accurate Human Activity Recognition (HAR) compared to using a single modality, yet the latter is more convenient and less intrusive. It is advantages to create a model which learns from all available sensors; a... Read More about Improving human activity recognition with neural translator models..

Reasoning with multi-modal sensor streams for m-health applications. (2018)
Conference Proceeding
WIJEKOON, A. 2018. Reasoning with multi-modal sensor streams for m-health applications. In Minor, M. (ed.) Workshop proceedings for the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 234-238. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=234

Musculoskeletal Disorders have a long term impact on individuals as well as on the community. They require self-management, typically in the form of maintaining an active lifestyle that adheres to prescribed exercises regimes. In the recent past m-he... Read More about Reasoning with multi-modal sensor streams for m-health applications..

Explainability through transparency and user control: a case-based recommender for engineering workers. (2018)
Presentation / Conference
MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2018. Explainability through transparency and user control: a case-based recommender for engineering workers. In Minor, M. (ed.) Workshop proceedings for the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 22-31. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=22

Within the service providing industries, field engineers can struggle to access tasks which are suited to their individual skills and experience. There is potential for a recommender system to improve access to information while being on site. Howeve... Read More about Explainability through transparency and user control: a case-based recommender for engineering workers..

Study of similarity metrics for matching network-based personalised human activity recognition. (2018)
Presentation / Conference
SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2018. Study of similarity metrics for matching network-based personalised human activity recognition. In Minor, M. (ed.) Workshop proceedings for the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden, pages 91-95. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=91

Personalised Human Activity Recognition (HAR) models trained using data from the target user (subject-dependent) have been shown to be superior to non personalised models that are trained on data from a general population (subject-independent). Howev... Read More about Study of similarity metrics for matching network-based personalised human activity recognition..

Generic application of deep learning framework for real-time engineering data analysis. (2018)
Conference Proceeding
MAJDANI, F., PETROVSKI, A. and PETROVSKI, S. 2018. Generic application of deep learning framework for real-time engineering data analysis. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489356. Available from: https://doi.org/10.1109/IJCNN.2018.8489356

The need for computer-assisted real-time anomaly detection in engineering data used for condition monitoring is apparent in various applications, including the oil and gas, automotive industries and many other engineering domains. To reduce the relia... Read More about Generic application of deep learning framework for real-time engineering data analysis..

Iterated racing algorithm for simulation-optimisation of maintenance planning. (2018)
Conference Proceeding
LACROIX, B., MCCALL, J. and LONCHAMPT, J. 2018. Iterated racing algorithm for simulation-optimisation of maintenance planning. In Proceedings of the 2018 IEEE congress on evolutionary computation (CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8477843. Available from: https://doi.org/10.1109/CEC.2018.8477843

The purpose of this paper is two fold. First, we present a set of benchmark problems for maintenance optimisation called VMELight. This model allows the user to define the number of components in the system to maintain and a number of customisable pa... Read More about Iterated racing algorithm for simulation-optimisation of maintenance planning..

Symbols classification in engineering drawings. (2018)
Conference Proceeding
ELYAN, E., MORENO GARCIA, C. and JAYNE, C. 2018. Symbols classification in engineering drawings. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489087. Available from: https://doi.org/10.1109/IJCNN.2018.8489087

Technical drawings are commonly used across different industries such as Oil and Gas, construction, mechanical and other types of engineering. In recent years, the digitization of these drawings is becoming increasingly important. In this paper, we p... Read More about Symbols classification in engineering drawings..

Spatial effects of video compression on classification in convolutional neural networks. (2018)
Conference Proceeding
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Spatial effects of video compression on classification in convolutional neural networks. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489370. Available from: https://doi.org/10.1109/IJCNN.2018.8489370

A collection of Computer Vision application reuse pre-learned features to analyse video frame-by-frame. Those features are classically learned by Convolutional Neural Networks (CNN) trained on high quality images. However, available video content is... Read More about Spatial effects of video compression on classification in convolutional neural networks..

Few-shot classifier GAN. (2018)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., SAVOYE, Y. and JAYNE, C. 2018. Few-shot classifier GAN. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489387. Available from: https://doi.org/10.1109/IJCNN.2018.8489387

Fine-grained image classification with a few-shot classifier is a highly challenging open problem at the core of a numerous data labeling applications. In this paper, we present Few-shot Classifier Generative Adversarial Network as an approach for fe... Read More about Few-shot classifier GAN..

Botnet detection in the Internet of Things using deep learning approaches. (2018)
Conference Proceeding
MCDERMOTT, C.D., MAJDANI, F. and PETROVSKI, A.V. 2018. Botnet detection in the Internet of Things using deep learning approaches. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489489. Available from: https://doi.org/10.1109/IJCNN.2018.8489489

The recent growth of the Internet of Things (IoT) has resulted in a rise in IoT based DDoS attacks. This paper presents a solution to the detection of botnet activity within consumer IoT devices and networks. A novel application of Deep Learning is u... Read More about Botnet detection in the Internet of Things using deep learning approaches..

Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. (2018)
Conference Proceeding
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2018. Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. In Proceedings of the 2018 IEEE international conference on fuzzy systems (FUZZ-IEEE 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article ID 8491628. Available from: https://doi.org/10.1109/FUZZ-IEEE.2018.8491628

To manage uncertainty in reservoir development projects, the Value of Information is one of the main factors on which the decision is based to determine whether it is necessary to acquire additional data. However, subsurface data is not always precis... Read More about Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry..

Performance analysis of GA and PBIL variants for real-world location-allocation problems. (2018)
Conference Proceeding
ANKRAH, R., REGNIER-COUDERT, O., MCCALL, J., CONWAY, A. and HARDWICK, A. 2018. Performance analysis of GA and PBIL variants for real-world location-allocation problems. In Proceedings of the 2018 IEEE congress on evolutionary computation (CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8477727. Available from: https://doi.org/10.1109/CEC.2018.8477727

The Uncapacitated Location-Allocation problem (ULAP) is a major optimisation problem concerning the determination of the optimal location of facilities and the allocation of demand to them. In this paper, we present two novel problem variants of Non-... Read More about Performance analysis of GA and PBIL variants for real-world location-allocation problems..

An international investigation into student concerns regarding transition into higher education computing. (2018)
Conference Proceeding
ZARB, M., ALSHAIGY, B., BOUVIER, D., GLASSEY, R., HUGHES, J. and RIEDESEL, C. 2018. An international investigation into student concerns regarding transition into higher education computing. In Proceedings companion of the 23rd Association for Computing Machinery (ACM) Innovation and technology in computer science education conference 2018 (ITiCSE 2018), 02-04 July 2018, Larnaca, Cyprus. New York: ACM [online], pages 107-129. Available from: https://doi.org/10.1145/3293881.3295780

The experience of transitioning into and starting higher education is very much an individual one, with some applicants viewing the prospect of higher education as an unknown entity. For those who are first in their family or community to consider hi... Read More about An international investigation into student concerns regarding transition into higher education computing..

Investigating benchmark correlations when comparing algorithms with parameter tuning. (2018)
Conference Proceeding
CHRISTIE, L.A., BROWNLEE, A.E.I. and WOODWARD, J.R. 2018. Investigating benchmark correlations when comparing algorithms with parameter tuning. In Aguirre, H.E. (ed.) Proceedings of the 2018 Genetic and evolutionary computation conference companion (GECCO'18 companion), 15-19 July 2018, Kyoto, Japan. New York: Association for Computing Machinery [online], pages 209-210. Available from: https://doi.org/10.1145/3205651.3205747

Benchmarks are important for comparing performance of optimisation algorithms, but we can select instances that present our algorithm favourably, and dismiss those on which our algorithm under-performs. Also related are automated design of algorithms... Read More about Investigating benchmark correlations when comparing algorithms with parameter tuning..

Evolutionary computation for optimal component deployment with multitenancy isolation in cloud-hosted applications. (2018)
Conference Proceeding
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2018. Evolutionary computation for optimal component deployment with multitenancy isolation in cloud-hosted applications. In Proceedings of the 2018 IEEE international symposium on innovations in intelligent systems and applications (INISTA 2018), 3-5 July 2018, Thessaloniki, Greece. New York: IEEE [online], article ID 8466315. Available from: https://doi.org/10.1109/INISTA.2018.8466315

A multitenant cloud-application that is designed to use several components needs to implement the required degree of isolation between the components when the workload changes. The highest degree of isolation results in high resource consumption and... Read More about Evolutionary computation for optimal component deployment with multitenancy isolation in cloud-hosted applications..

An international investigation into student concerns regarding transition into higher education. (2018)
Conference Proceeding
ZARB, M., ABANDOH-SAM, J.A., ALSHAIGY, B., BOUVIER, D., GLASSEY, R., HUGHES, J. and RIEDESEL, C. 2018. An international investigation into student concerns regarding transition into higher education. In Proceedings of the 23rd Annual Association for Computing Machinery (ACM) conference on innovation and technology in computer science education (ITiCSE 2018), 2-4 July 2018, Larnaca, Cyprus. New York: ACM [online], pages 344-345. Available from: https://doi.org/10.1145/3197091.3205842

The experience of transitioning into and starting higher education is a very individual one, with some applicants viewing the prospect of higher education as an unknown entity; for those who are first in their family or community to consider higher e... Read More about An international investigation into student concerns regarding transition into higher education..

Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines. (2018)
Conference Proceeding
FREZZA, S., DANIELS, M., PEARS, A., CAJANDER, A., KANN, V., KAPOOR, A., MCDERMOTT, R., PETERS, A.-K., SABIN, M. and WALLACE, C. 2018. Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines. In Rossling, G. and Scharlau, B. (eds.) Proceedings companion of the 23rd Innovation and technology in computer science education annual conference 2018 (ITiCSE 2018), 02-04 July 2018, Larcana, Cyprus. New York: ACM [online], pages 148-174. Available from: https://doi.org/10.1145/3293881.3295782

How might the content and outcomes of tertiary education programmes be described and analysed in order to understand how they are structured and function? To address this question we develop a framework for modelling graduate competencies linked to t... Read More about Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines..

Two enhancements for improving the convergence speed of a robust multi-objective coevolutionary algorithm. (2018)
Conference Proceeding
ZAVOIANU, A.-C., SAMINGER-PLATZ, S., LUGHOFER, E. and AMRHEIN, W. 2018. Two enhancements for improving the convergence speed of a robust multi-objective coevolutionary algorithm. In Aguirre, H. (ed.) Proceedings of the 2018 Genetic and evolutionary computation conference (GECCO'18), 15-19 July 2018, Kyoto, Japan. New York: Association for Computing Machinery [online], pages 793-800. Available from: https://doi.org/10.1145/3205455.3205549

We describe two enhancements that significantly improve the rapid convergence behavior of DECM02 - a previously proposed robust coevolutionary algorithm that integrates three different multi-objective space exploration paradigms: differential evoluti... Read More about Two enhancements for improving the convergence speed of a robust multi-objective coevolutionary algorithm..

Digital interpretation of sensor-equipment diagrams. (2018)
Conference Proceeding
MORENO-GARCÍA, C.F. 2018. Digital interpretation of sensor-equipment diagrams. In Martin, K., Wiratunga, N. and Smith, L.S. (eds.) Proceedings of the 2018 Scottish Informatics and Computer Science Alliance (SCISA) workshop on reasoning, learning and explainability (ReaLX 2018), 27 June 2018, Aberdeen, UK. CEUR workshop proceedings, 2151. Aachen: CEUR-WS [online], session 2, paper 1. Available from: http://ceur-ws.org/Vol-2151/Paper_s2.pdf

A sensor-equipment diagram is a type of engineering drawing used in the industrial practice that depicts the interconnectivity between a group of sensors and a portion of an Oil & Gas facility. The interpretation of these documents is not a straightf... Read More about Digital interpretation of sensor-equipment diagrams..

Zero-shot learning with matching networks for open-ended human activity recognition. (2018)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N. and SANI, S. 2018. Zero-shot learning with matching networks for open-ended human activity recognition. In Martin, K., Wiratunga, N. and Smith, L.S. (eds.) Proceedings of the 2018 Scottish Informatics and Computer Science Alliance (SCISA) workshop on reasoning, learning and explainability (ReaLX 2018), 27 June 2018, Aberdeen, UK. CEUR workshop proceedings, 2151. Aachen: CEUR-WS [online], session 2, paper 4. Available from: http://ceur-ws.org/Vol-2151/Paper_S9.pdf

A real-world solution for Human Activity Recognition (HAR) should cover a variety of activities. However training a model to cover each and every possible activity is not practical. Instead we need a solution that can adapt its learning to unseen act... Read More about Zero-shot learning with matching networks for open-ended human activity recognition..