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Outputs (4095)

Visualization beyond the desktop--the Next Big Thing. (2014)
Journal Article
Roberts, J. C., Ritsos, P. D., Badam, S. K., Brodbeck, D., Kennedy, J., & Elmqvist, N. (2014). Visualization beyond the desktop--the Next Big Thing. IEEE Computer Graphics and Applications, 34(6), 26-34. https://doi.org/10.1109/MCG.2014.82

Visualization is coming of age. With visual depictions being seamlessly integrated into documents, and data visualization techniques being used to understand increasingly large and complex datasets, the term "visualization"' is becoming used in every... Read More about Visualization beyond the desktop--the Next Big Thing..

Behaviour reflects personality: detecting co-residence attacks on Xen-based cloud environments (2014)
Journal Article
Pitropakis, N., Pikrakis, A., & Lambrinoudakis, C. (2015). Behaviour reflects personality: detecting co-residence attacks on Xen-based cloud environments. International Journal of Information Security, 14(4), 299-305. https://doi.org/10.1007/s10207-014-0255-8

Cloud computing is gradually becoming the most popular option of Information Technology infrastructures. However, an important issue that has emerged through that revolution is the preservation of an adequate level of security for the infrastructure... Read More about Behaviour reflects personality: detecting co-residence attacks on Xen-based cloud environments.

Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features (2014)
Journal Article
Xia, Y., Cambria, E., Hussain, A., & Zhao, H. (2015). Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features. Cognitive Computation, 7(3), 369-380. https://doi.org/10.1007/s12559-014-9298-4

Contextual polarity ambiguity is an important problem in sentiment analysis. Many opinion keywords carry varying polarities in different contexts, posing huge challenges for sentiment analysis research. Previous work on contextual polarity disambigua... Read More about Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features.

Large-scale SDN experiments in federated environments (2014)
Presentation / Conference Contribution
Carrozzo, G., Monno, R., Belter, B., Krzywania, R., Pentikousis, K., Broadbent, M., Kudoh, T., Takefusa, A., Vieo-Oton, A., Fernandez, C., & et al. (2014, June). Large-scale SDN experiments in federated environments. Presented at 2014 International Conference on Smart Communications in Network Technologies (SaCoNeT), Vilanova i la Geltru, Spain

International cooperation on Software-Defined Networking (SDN), crossing the boundaries of Europe, the Americas and Asia, builds a strong foundation for pursuing experimental research through advanced programmable network testbeds. The EU-Japan joint... Read More about Large-scale SDN experiments in federated environments.

Feature selection Inspired classifier ensemble reduction. (2014)
Journal Article
Diao, R., Chao, F., Peng, T., Snooke, N., & Shen, Q. (2014). Feature selection Inspired classifier ensemble reduction. IEEE Transactions on Cybernetics, 44, 1259-1268. https://doi.org/10.1109/TCYB.2013.2281820

Classifier ensembles constitute one of the main research directions in machine learning and data mining. The use of multiple classifiers generally allows better predictive performance than that achievable with a single model. Several approaches exist... Read More about Feature selection Inspired classifier ensemble reduction..

Error analysis of estimators that use combinations of stochastic sampling strategies for direct illumination (2014)
Journal Article
Subr, K., Nowrouzezahrai, D., Jarosz, W., Kautz, J., & Mitchell, K. (2014). Error analysis of estimators that use combinations of stochastic sampling strategies for direct illumination. Computer Graphics Forum, 33(4), 93-102. https://doi.org/10.1111/cgf.12416

We present a theoretical analysis of error of combinations of Monte Carlo estimators used in image synthesis. Importance sampling and multiple importance sampling are popular variance-reduction strategies. Unfortunately, neither strategy improves the... Read More about Error analysis of estimators that use combinations of stochastic sampling strategies for direct illumination.

What’s in it for me? Making the case for paid student placements in computer science. (2014)
Presentation / Conference Contribution
Smith, S., & Smith, C. F. (2014, July). What’s in it for me? Making the case for paid student placements in computer science. Paper presented at STEM 2014

Recognising the need for skilled computer science graduates, the university funding body in Scotland, the Scottish Funding Council (SFC) is supporting a Scotland-wide student placement project, e-Placement Scotland, to create 750 new paid student pla... Read More about What’s in it for me? Making the case for paid student placements in computer science..

An improved immune inspired hyper-heuristic for combinatorial optimisation problems. (2014)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2014, July). An improved immune inspired hyper-heuristic for combinatorial optimisation problems

The meta-dynamics of an immune-inspired optimisation sys- tem NELLI are considered. NELLI has previously shown to exhibit good performance when applied to a large set of optimisation problems by sustaining a network of novel heuristics. We address th... Read More about An improved immune inspired hyper-heuristic for combinatorial optimisation problems..

A real-world employee scheduling and routing application. (2014)
Presentation / Conference Contribution
Hart, E., Sim, K., & Urquhart, N. B. (2014, July). A real-world employee scheduling and routing application. Presented at GECCO 2014

We describe a hyper-heuristic application developed for a client to find quick, acceptable solutions to Workforce Schedul- ing and Routing problems. An interactive fitness function controlled by the user enables five different objectives to be weight... Read More about A real-world employee scheduling and routing application..