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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

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

Autonomous supervision and optimization of product quality in a multi-stage manufacturing process based on self-adaptive prediction models. (2019)
Journal Article
LUGHOFER, E., ZAVOIANU, A.-C., POLLAK, R., PRATAMA, M., MEYER-HEYE, P., ZÖRRER, H., EITZINGER, C. and RADAUER, T. 2019. Autonomous supervision and optimization of product quality in a multi-stage manufacturing process based on self-adaptive prediction models. Journal of process control [online], 76, pages 27-45. Available from: https://doi.org/10.1016/j.jprocont.2019.02.005

In modern manufacturing facilities, there are basically two essential phases for assuring high production quality with low (or even zero) defects and waste in order to save costs for companies. The first phase concerns the early recognition of potent... Read More

Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. (2019)
Journal Article
MCDERMOTT, C.D., ISAACS, J.P. and PETROVSKI, A.V. 2019. Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. Informatics [online], 6(1), article 8. Available from: https://doi.org/10.3390/informatics6010008

The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform large-scale attacks on the Intern... Read More

Multi-label classification via label correlation and first order feature dependance in a data stream. (2019)
Journal Article
NGUYEN, T.T., NGUYEN, T.T.T., LUONG, A.V., NGUYEN, Q.V.H., LIEW, A.W.-C. and STANTIC, B. 2019. Multi-label classification via label correlation and first order feature dependance in a data stream. Pattern recognition [online], 90, pages 35-51. Available from: https://doi.org/10.1016/j.patcog.2019.01.007

Many batch learning algorithms have been introduced for offline multi-label classification (MLC) over the years. However, the increasing data volume in many applications such as social networks, sensor networks, and traffic monitoring has posed many... Read More

Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). (2018)
Journal Article
ANI, M., OLUYEMI, G., PETROVSKI, A. and REZAEI-GOMARI, S. 2019. Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). Journal of petroleum science and engineering [online], 174, pages 833-843. Available from: https://doi.org/10.1016/j.petrol.2018.11.024

The selection of an optimal model from a set of multiple realizations for dynamic reservoir modelling and production forecasts has been a persistent issue for reservoir modelers and decision makers. Current evidence has shown that many presumably goo... Read More

Combining heterogeneous classifiers via granular prototypes. (2018)
Journal Article
NGUYEN, T.T., NGUYEN, M.P., PHAM, X.C., LIEW, A. W.-C. and PEDRYCZ, W. 2018. Combining heterogeneous classifiers via granular prototypes. Applied soft computing [online], 73, pages 795-815. Available from: https://doi.org/10.1016/j.asoc.2018.09.021

In this study, a novel framework to combine multiple classifiers in an ensemble system is introduced. Here we exploit the concept of information granule to construct granular prototypes for each class on the outputs of an ensemble of base classifiers... Read More

A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service. (2018)
Journal Article
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2018. A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service. International journal of cloud computing [online], 7(3-4), pages 248-281. Available from: https://doi.org/10.1504/IJCC.2018.095396

Multitenancy allows multiple tenants to access a single instance of a cloud offering. While several approaches exist for implementing multitenancy, little attention has been paid to implementing the required degree of isolation since there are varyin... Read More

New trends on digitisation of complex engineering drawings. (2018)
Journal Article
MORENO-GARCIA, C.F., ELYAN, E. and JAYNE, C. 2019. New trends on digitisation of complex engineering drawings. Neural computing and applications [online], 31(6): selected papers from the proceedings of the 18th Engineering applications of neural networks conference (EANN 2017), 25-27 August 2017, Athens, Greece, pages 1695-1712. Available from: https://doi.org/10.1007/s00521-018-3583-1

Engineering drawings are commonly used across different industries such as oil and gas, mechanical engineering and others. Digitising these drawings is becoming increasingly important. This is mainly due to the legacy of drawings and documents that m... Read More

Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. (2018)
Journal Article
CHEN, Y.Y., WIRATUNGA, N. and LOTHIAN, R. [2019]. Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. Online information review [online], (accepted).

Purpose - Recommender system approaches such as collaborative and content-based filtering rely on user ratings and product descriptions to recommend products. More recently, recommender system research has focused on exploiting knowledge from user-ge... Read More