Skip to main content

Research Repository

Advanced Search

All Outputs (1084)

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 about Autonomous supervision and optimization of product quality in a multi-stage manufacturing process based on self-adaptive prediction models..

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 about Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks..

Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. (2019)
Journal Article
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2019. Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. Journal of cloud computing [online], 8, article 1. Available from: https://doi.org/10.1186/s13677-018-0124-5

One of the challenges of deploying multitenant cloud-hosted services that are designed to use (or be integrated with) several components is how to implement the required degree of isolation between the components when there is a change in the workloa... Read More about Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation..

Ontology alignment based on word embedding and random forest classification. (2019)
Conference Proceeding
NKISI-ORJI, I., WIRATUNGA, N., MASSIE, S., HUI, K.-Y. and HEAVEN, R. 2019. Ontology alignment based on word embedding and random forest classification. In Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. and Ifrim, G. (eds.) Machine learning and knowledge discovery in databases: proceedings of the 2018 European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD 2018), 10-14 September 2018, Dublin, Ireland. Lecture notes in computer science, 11051. Cham: Springer [online], part I, pages 557-572. Available from: https://doi.org/10.1007/978-3-030-10925-7_34

Ontology alignment is crucial for integrating heterogeneous data sources and forms an important component for realising the goals of the semantic web. Accordingly, several ontology alignment techniques have been proposed and used for discovering corr... Read More about Ontology alignment based on word embedding and random forest classification..

Privacy risk assessment in context: a meta-model based on contextual integrity. (2019)
Journal Article
HENRIKSEN-BULMER, J., FAILY, S. and JEARY, S. 2019. Privacy risk assessment in context: a meta-model based on contextual integrity. Computers and security [online], 82, pages 270-283. Available from: https://doi.org/10.1016/j.cose.2019.01.003

Publishing data in open format is a growing trend, particularly for public bodies who have a legal obligation to make data available as open data. We look at the privacy implications of publishing open data and, in particular, how organisations can m... Read More about Privacy risk assessment in context: a meta-model based on contextual integrity..

'If your mother says she loves you, check it out': citizens' approaches to evaluating the credibility of information provided online by political actors in Scotland. (2019)
Presentation / Conference
BAXTER, G. and MARCELLA, R. 2019. 'If your mother says she loves you, check it out': citizens' approaches to evaluating the credibility of information provided online by political actors in Scotland. Presented at the 2019 Media, Communication and Cultural Studies Association annual conference (MeCCSA 2019), 9-11 January 2019, Stirling, UK.

This paper provided an overview of developments in online information credibility evaluation over the previous 25 years, relating these to the results of two studies conducted by the authors in 2017: 1) an online survey of the general public (n = 538... Read More about 'If your mother says she loves you, check it out': citizens' approaches to evaluating the credibility of information provided online by political actors in Scotland..

Searching for global employability: can students capitalize on enabling learning environments? (2019)
Journal Article
ISOMÖTTÖNEN, V., DANIELS, M., CAJANDER, A., PEARS, A. and MCDERMOT, R. 2019. Searching for global employability: can students capitalize on enabling learning environments? ACM transactions on computing education, 19(2), article ID 11. Available from: https://doi.org/10.1145/3277568

Literature on global employability signifies “enabling” learning environments where students encounter ill-formed and open-ended problems and are required to adapt and be creative. Varying forms of “projects,” co-located and distributed, have populat... Read More about Searching for global employability: can students capitalize on enabling learning environments?.

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 about Multi-label classification via label correlation and first order feature dependance in a data stream..

Designing usable and secure software with IRIS and CAIRIS. (2018)
Book
FAILY, S. 2018. Designing usable and secure software with IRIS and CAIRIS. Cham: Springer [online]. Available from: https://doi.org/10.1007/978-3-319-75493-2

Everyone expects the products and services they use to be secure, but 'building security in' at the earliest stages of a system's design also means designing for use as well. Software that is unusable to end-users and unwieldy to developers and admin... Read More about Designing usable and secure software with IRIS and CAIRIS..

Rationalising decision-making about risk: a normative approach. (2018)
Conference Proceeding
M'MANGA, A., FAILY, S., MCALANEY, J. and WILLIAMS, C. 2018. Rationalising decision-making about risk: a normative approach. In Clarke, N.L. and Furnell, S.M. (eds.) Proceedings of the 12th International symposium on human aspects of information security and assurance (HAISA 2018), 29-31 August 2018, Dundee, UK. Plymouth: University of Plymouth, pages 263-271. Hosted on the CSCAN Archive [online]. Available from: https://www.cscan.org/?page=openaccess&eid=20&id=395

Techniques for determining and applying security decisions typically follow risk-based analytical approaches where alternative options are put forward and weighed in accordance to risk severity metrics based on goals and context. The reasoning or val... Read More about Rationalising decision-making about risk: a normative approach..

Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. (2018)
Journal Article
OCHEI, L.C., BASS, J.M. and PETROVSKI, A. 2018. Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. Journal of cloud computing [online], 7, article ID 22. Available from: https://doi.org/10.1186/s13677-018-0121-8

A challenge, when implementing multi-tenancy in a cloud-hosted software service, is how to ensure that the performance and resource consumption of one tenant does not adversely affect other tenants. Software designers and architects must achieve an o... Read More about Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis..

X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks. (2018)
Journal Article
AL-KADRI, M.O., AIJAZ, A. and NALLANATHAN, A. 2019. X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks. IEEE wireless communications [online], 26(2), pages 70-77. Available from: https://doi.org/10.1109/MWC.2017.1700243

The recent developments in self-interference (SI) cancellation techniques have led to the practical realization of FD radios that can perform simultaneous transmission and reception. FD technology is attractive for various legacy communications stand... Read More about X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks..

Feature trade-off analysis for reconnaissance detection. (2018)
Book Chapter
KALUTARAGE, H.K. and SHAIKH, S.A. 2018. Feature trade-off analysis for reconnaissance detection. In Heard, N., Adams, N., Rubin-Delanchy, P. and Turcotte, M. (eds.) Data science for cyber security. Security science and technology, 3. London: World Scientific [online], chapter 5, pages 95-126. Available from: https://doi.org/10.1142/9781786345646_005

An effective cyber early warning system (CEWS) should pick up threat activity at an early stage, with an emphasis on establishing hypotheses and predictions as well as generating alerts on (unclassified) situations based on preliminary indications. T... Read More about Feature trade-off analysis for reconnaissance detection..

Real-time relative permeability prediction using deep learning. (2018)
Journal Article
ARIGBE, O.D., OYENEYIN, M.B., ARANA, I. and GHAZI, M.D. 2019. Real-time relative permeability prediction using deep learning. Journal of petroleum exploration and production technologies [online], 9(2), pages 1271-1284. Available from: https://doi.org/10.1007/s13202-018-0578-5

A review of the existing two and three phase relative permeability correlations shows a lot of pitfalls and restrictions imposed by (a) their assumptions (b) generalization ability and (c) difficulty with updating in real time for different reservoir... Read More about Real-time relative permeability prediction using deep learning..

Risk information recommendation for engineering workers. (2018)
Conference Proceeding
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..

Informed pair selection for self-paced metric learning in Siamese neural networks. (2018)
Conference Proceeding
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..

GramError: a quality metric for machine generated songs. (2018)
Conference Proceeding
DAVIES, C., WIRATUNGA, N. and MARTIN, K. 2018. GramError: a quality metric for machine generated songs. 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 184-190. Available from: https://doi.org/10.1007/978-3-030-04191-5_16

This paper explores whether a simple grammar-based metric can accurately predict human opinion of machine-generated song lyrics quality. The proposed metric considers the percentage of words written in natural English and the number of grammatical er... Read More about GramError: a quality metric for machine generated songs..

A holistic metric approach to solving the dynamic location-allocation problem. (2018)
Conference Proceeding
ANKRAH, R., LACROIX, B., MCCALL, J., HARDWICK, A. and CONWAY, A. 2018. A holistic metric approach to solving the dynamic location-allocation problem. 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 artificial intelligence, 11311. Cham: Springer [online], pages 433-439. Available from: https://doi.org/10.1007/978-3-030-04191-5_35

In this paper, we introduce a dynamic variant of the Location-Allocation problem: Dynamic Location-Allocation Problem (DULAP). DULAP involves the location of facilities to service a set of customer demands over a defined horizon. To evaluate a soluti... Read More about A holistic metric approach to solving the dynamic location-allocation problem..

Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge. (2018)
Conference Proceeding
BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and LUHAR, R. 2018. Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge. 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 artificial intelligence, 11311. Cham: Springer [online], pages 357-371. Available from: https://doi.org/10.1007/978-3-030-04191-5_30

Aspect-level sentiment analysis of customer feedback data when done accurately can be leveraged to understand strong and weak performance points of businesses and services and also formulate critical action steps to improve their performance. In this... Read More about Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge..

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 about Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP)..