Outputs (22)

An Exploration of Dropout with RNNs for Natural Language Inference (2018)
Presentation / Conference Contribution
Gajbhiye, A., Jaf, S., Al-Moubayed, N., McGough, A. S., & Bradley, S. (2018, December). An Exploration of Dropout with RNNs for Natural Language Inference. Presented at ICANN 2018: 27th International Conference on Artificial Neural Networks, Rhodes

Dropout is a crucial regularization technique for the Recurrent Neural Network (RNN) models of Natural Language Inference (NLI). However, dropout has not been evaluated for the effectiveness at different layers and dropout rates in NLI models. In thi... Read More about An Exploration of Dropout with RNNs for Natural Language Inference.

Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine (2017)
Book Chapter
Al Moubayed, N., Wall, D., & McGough, A. (2017). Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine. In T. Tryfonas (Ed.), Human aspects of information security, privacy and trust : 5th International Conference, HAS 2017, held as part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, proceedings (287-295). Springer Verlag. https://doi.org/10.1007/978-3-319-58460-7_19

Successful Cybersecurity depends on the processing of vast quantities of data from a diverse range of sources such as police reports, blogs, intelligence reports, security bulletins, and news sources. This results in large volumes of unstructured tex... Read More about Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine.

Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems (2017)
Presentation / Conference Contribution
McGough, A. S., Al Moubayed, N., & M, F. (2017). Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems. In Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion (ICPE '17 Companion), April 22 - 26, 2017, L’Aquila, Italy (55-60). https://doi.org/10.1145/3053600.3053612

When performing a trace-driven simulation of a High Throughput Computing system we are limited to the knowledge which should be available to the system at the current point within the simulation. However, the trace-log contains information we would n... Read More about Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems.

Efficient Comparison of Massive Graphs Through The Use Of 'Graph Fingerprints' (2016)
Presentation / Conference Contribution
Bonner, S., Brennan, J., Theodoropoulos, G., Kureshi, I., & McGough, A. (2016). Efficient Comparison of Massive Graphs Through The Use Of 'Graph Fingerprints'.

The problem of how to compare empirical graphs is an area of great interest within the field of network science. The ability to accurately but efficiently compare graphs has a significant impact in such areas as temporal graph evolution, anomaly dete... Read More about Efficient Comparison of Massive Graphs Through The Use Of 'Graph Fingerprints'.

SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder (2016)
Presentation / Conference Contribution
Al Moubayed, N., Breckon, T., Matthews, P., & McGough, A. (2016, August). SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder

In This paper we present a novel approach to spam filtering and demonstrate its applicability with respect to SMS messages. Our approach requires minimum features engineering and a small set of labelled data samples. Features are extracted using topi... Read More about SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder.

HTC-Sim: a trace-driven simulation framework for energy consumption in high-throughput computing systems (2016)
Journal Article
Forshaw, M., McGough, A. S., & Thomas, N. (2016). HTC-Sim: a trace-driven simulation framework for energy consumption in high-throughput computing systems. Concurrency and Computation: Practice and Experience, 28(12), 3260-3290. https://doi.org/10.1002/cpe.3804

High-throughput computing (HTC) is a powerful paradigm allowing vast quantities of independent work to be performed simultaneously across many loosely coupled computers. These systems often exploit the idle time available on computers provisioned for... Read More about HTC-Sim: a trace-driven simulation framework for energy consumption in high-throughput computing systems.

Detecting Insider Threats Using Ben-ware: Beneficial Intelligent Software for Identifying Anomalous Human Behaviour (2015)
Journal Article
McGough, A. S., Arief, B., Gamble, C., Wall, D., Brennan, J., Fitzgerald, J., …Ruck-Keene, E. (2015). Detecting Insider Threats Using Ben-ware: Beneficial Intelligent Software for Identifying Anomalous Human Behaviour. Journal of wireless mobile networks, ubiquitous computing and dependable applications, 6(4), 1-44

The insider threat problem is a significant and ever present issue faced by any organisation. While security mechanisms can be put in place to reduce the chances of external agents gaining access to a system, either to steal assets or alter records,... Read More about Detecting Insider Threats Using Ben-ware: Beneficial Intelligent Software for Identifying Anomalous Human Behaviour.

Data Quality Assessment and Anomaly Detection Via Map / Reduce and Linked Data: A Case Study in the Medical Domain (2015)
Presentation / Conference Contribution
Bonner, S., McGough, S., Kureshi, I., Brennan, J., Theodoropoulos, G., Moss, L., …Antoniou, G. (2015). Data Quality Assessment and Anomaly Detection Via Map / Reduce and Linked Data: A Case Study in the Medical Domain. In Proceedings, 2015 IEEE International Conference on Big Data : Oct 29-Nov 01, 2015, Santa Clara, CA, USA (737-746). https://doi.org/10.1109/bigdata.2015.7363818

Recent technological advances in modern healthcare have lead to the ability to collect a vast wealth of patient monitoring data. This data can be utilised for patient diagnosis but it also holds the potential for use within medical research. However,... Read More about Data Quality Assessment and Anomaly Detection Via Map / Reduce and Linked Data: A Case Study in the Medical Domain.

Energy-aware simulation of workflow execution in High Throughput Computing systems (2015)
Presentation / Conference Contribution
McGough, A. S., & Forshaw, M. (2015). Energy-aware simulation of workflow execution in High Throughput Computing systems. In Proceedings of the 19th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2015, 14-16 October 2015, Chengdu, China (25-32). https://doi.org/10.1109/ds-rt.2015.31

Workflows offer a great potential for enacting corelated jobs in an automated manner. This is especially desirable when workflows are large or there is a desire to run a workflow multiple times. Much research has been conducted in reducing the makesp... Read More about Energy-aware simulation of workflow execution in High Throughput Computing systems.

Flipping the priority: effects of prioritising HTC jobs on energy consumption in a multi-use cluster (2015)
Presentation / Conference Contribution
Forshaw, M., & McGough, A. S. (2015). Flipping the priority: effects of prioritising HTC jobs on energy consumption in a multi-use cluster. In Proceedings of the 8th International Conference on Simulation Tools and Techniques, SIMUTools '15, August 26-28, Athens, Greece (357-364). https://doi.org/10.4108/eai.24-8-2015.2261101

High Throughput Computing (HTC) through the use of vol- unteer computing provides a compelling opportunity to per- form large volumes of computation without the need to in- vest in computational resources. This relies on the good will of computer own... Read More about Flipping the priority: effects of prioritising HTC jobs on energy consumption in a multi-use cluster.