Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results.

Christie, Lee A.; Brownlee, Alexander E.I.; Woodward, John R.

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..

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..

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..

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..

Opinion context extraction for aspect sentiment analysis. (2018)
Conference Proceeding
BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and LUHAR, R. 2018. Opinion context extraction for aspect sentiment analysis. In Proceedings of the 12th Association for the Advancement of Artificial Intelligence (AAAI) international conference on web and social media (ICWSM 2018), 25-28 June 2018, Palo Alto, USA. Palo Alto: AAAI Press [online], pages 564-567. Available from: https://www.aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17859

Sentiment analysis is the computational study of opinionated text and is becoming increasing important to online commercial applications. However, the majority of current approaches determine sentiment by attempting to detect the overall polarity of... Read More about Opinion context extraction for aspect sentiment analysis..

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 about New trends on digitisation of complex engineering drawings..

Towards situational awareness of botnet activity in the Internet of Things (2018)
Conference Proceeding
MCDERMOTT, C.D., PETROVSKI, A.V. and MAJDANI, F. 2018. Towards situational awareness of botnet activity in the Internet of Things. In Proceedings of the 2018 International conference on cyber situational awareness, data analytics and assessment (Cyber SA 2018): cyber situation awareness as a tool for analysis and insight, 11-12 June 2018, Glasgow, UK. Piscataway: IEEE [online], article number 8551408. Available from: https://doi.org/10.1109/CyberSA.2018.8551408

An IoT botnet detection model is designed to detect anomalous attack traffic utilised by the mirai botnet malware. The model uses a novel application of Deep Bidirectional Long Short Term Memory based Recurrent Neural Network (BLSTMRNN), in conjuncti... Read More about Towards situational awareness of botnet activity in the Internet of Things.

Effective and efficient estimation of distribution algorithms for permutation and scheduling problems. (2018)
Thesis
AYODELE, M. 2018. Effective and efficient estimation of distribution algorithms for permutation and scheduling problems. Robert Gordon University, PhD thesis.

Estimation of Distribution Algorithm (EDA) is a branch of evolutionary computation that learn a probabilistic model of good solutions. Probabilistic models are used to represent relationships between solution variables which may give useful, human-un... Read More about Effective and efficient estimation of distribution algorithms for permutation and scheduling problems..

Deep learning based approaches for imitation learning. (2018)
Thesis
HUSSEIN, A. 2018. Deep learning based approaches for imitation learning. Robert Gordon University, PhD thesis.

Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as well as rising demand for int... Read More about Deep learning based approaches for imitation learning..

Knowledge driven approaches to e-learning recommendation. (2018)
Thesis
MBIPOM, B. 2018. Knowledge driven approaches to e-learning recommendation. Robert Gordon University, PhD thesis.

Learners often have difficulty finding and retrieving relevant learning materials to support their learning goals because of two main challenges. The vocabulary learners use to describe their goals is different from that used by domain experts in tea... Read More about Knowledge driven approaches to e-learning recommendation..

Evaluating the effect of locking on multitenancy isolation for components of cloud-hosted services. (2018)
Journal Article
OCHEI, L.C. and EJIOFOR, C.I. 2018. Evaluating the effect of locking on multitenancy isolation for components of cloud-hosted services. Advances in science, technology and engineering systems journal [online], 3(3), pages 92-99. Available from: https://doi.org/10.25046/aj030312

Multitenancy isolation is a way of ensuring that the performance, stored data volume and access privileges required by one tenant and/or component does not affect other tenants and/or components. One of the conditions that can influence the varying d... Read More about Evaluating the effect of locking on multitenancy isolation for components of cloud-hosted services..

Non-traditional skills in undergraduate medical education: the development of a teaching programme. (2018)
Journal Article
BRADY, C. and ZARB, M. 2018. Non-traditional skills in undergraduate medical education: the development of a teaching programme. Scottish medical journal [online], 63(3), pages 80-81. Available from: https://doi.org/10.1177/0036933018776837

As a junior doctor in what is an increasingly struggling healthcare system, I am concerned to see that many of my junior and senior colleagues have opted not to continue onto the next stage of training. Whilst entrepreneurship, leadership and managem... Read More about Non-traditional skills in undergraduate medical education: the development of a teaching programme..

Coherent narrow-band light source for miniature endoscopes. (2018)
Journal Article
CHEN, Z.-Y., GOGOI, A., LEE, S.-Y., TSAI-LIN, Y., YI, P.-W.Y., LU, M.-K., HSIEH, C.-C., REN, J., MARSHALL, S. and KAO, F.-J. 2019. Coherent narrow-band light source for miniature endoscopes. IEEE journal of selected topics in quantum electronics [online], 25(1), article 7100707. Available from: https://doi.org/10.1109/JSTQE.2018.2836959

In this work, we report the successful implementation of a coherent narrow-band light source for miniature endoscopy applications. An RGB laser module that provides much higher luminosity than traditional incoherent white light sources is used for il... Read More about Coherent narrow-band light source for miniature endoscopes..

Sparse representation-based augmented multinomial logistic extreme learning machine with weighted composite features for spectral–spatial classification of hyperspectral images. (2018)
Journal Article
CAO, F., YANG, Z., REN, J., LING, W.-K., ZHAO, H., SUN, M. and BENEDIKTSSON, J.A. 2018. Sparse representation-based augmented multinomial logistic extreme learning machine with weighted composite features for spectral–spatial classification of hyperspectral images. IEEE transactions on geoscience and remote sensing [online], 56(11), pages 6263-6279. Available from: https://doi.org/10.1109/tgrs.2018.2828601

Although extreme learning machine (ELM) has successfully been applied to a number of pattern recognition problems, only with the original ELM it can hardly yield high accuracy for the classification of hyperspectral images (HSIs) due to two main draw... Read More about Sparse representation-based augmented multinomial logistic extreme learning machine with weighted composite features for spectral–spatial classification of hyperspectral images..

W3C accessibility guidelines for mobile games. (2018)
Journal Article
WILSON, A. and CRABB, M. 2018. W3C accessibility guidelines for mobile games. Computer games journal [online], 7(2), pages 49-61. Available from: https://doi.org/10.1007/s40869-018-0058-7

In the past decade, video games have become one of the fastest growing forms or entertainment around the world. In particular, mobile gaming has continued to evolve, becoming increasingly popular for billions of people worldwide. An ongoing issue wit... Read More about W3C accessibility guidelines for mobile games..

Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results. (2018)
Report
CHRISTIE, L.A., BROWNLEE, A.E.I. and WOODWARD, J.R. 2018. Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results. Stirling: University of Stirling [online]. Available from: http://hdl.handle.net/1893/26956

Benchmarks are important to demonstrate the utility of optimisation algorithms, but there is controversy about the practice of benchmarking; we could select instances that present our algorithm favourably, and dismiss those on which our algorithm und... Read More about Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results..

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