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Hyper-heuristics: a survey of the state of the art (2013)
Journal Article
Burke, E., Gendreau, M., Hyde, M., Kendall, G., Ocha, G., Özcan, E., & Qu, R. (2013). Hyper-heuristics: a survey of the state of the art. Journal of the Operational Research Society, 64, https://doi.org/10.1057/jors.2013.71

Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the goal of automating the design of heuristic methods to solve hard computational search problems. An underlying strategic research challenge is to develop more g... Read More about Hyper-heuristics: a survey of the state of the art.

Indoors and outdoors: designing mobile experiences for Cité de l’espace (2013)
Book Chapter
Rennick-Egglestone, S., Roussou, M., Brundell, P., Chaffardon, C., Kourtis, V., Koleva, B., & Benford, S. (2013). Indoors and outdoors: designing mobile experiences for Cité de l’espace. In Proceedings of NODEM 2013. NODEM

The CHESS project has been working with Cité de l’espace, a space technology centre, to explore the use of tablets and mobile phones to deliver visitor experiences that integrate across multiple experiences. In this paper, we articulate three key cha... Read More about Indoors and outdoors: designing mobile experiences for Cité de l’espace.

Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology (2013)
Journal Article
Swan, A. L., Mobasheri, A., Allaway, D., Liddell, S., & Bacardit, J. (2013). Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology. OMICS, 17(12), https://doi.org/10.1089/omi.2013.0017

Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, i... Read More about Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology.

Usability of Geographic Information: current challenges and future directions (2013)
Journal Article
Brown, M., Sharples, S., Harding, J., Parker, C., Bearman, N., Maguire, M., …Jackson, M. (2013). Usability of Geographic Information: current challenges and future directions. Applied Ergonomics, 44(6), https://doi.org/10.1016/j.apergo.2012.10.013

The use of Geographic Information or GI, has grown rapidly in recent years. Previous research has identified the importance of usability and user centred design in enabling the proliferation and exploitation of GI. However, the design and developme... Read More about Usability of Geographic Information: current challenges and future directions.

Aircraft taxi time prediction: comparisons and insights (2013)
Journal Article
Ravizza, S., Chen, J., Atkin, J. A., Stewart, P., & Burke, E. K. (2014). Aircraft taxi time prediction: comparisons and insights. Applied Soft Computing, 14(C), https://doi.org/10.1016/j.asoc.2013.10.004

The predicted growth in air transportation and the ambitious goal of the European Commission to have on-time performance of flights within 1 min makes efficient and predictable ground operations at airports indispensable. Accurately predicting taxi t... Read More about Aircraft taxi time prediction: comparisons and insights.

Reputation aware obfuscation for mobile opportunistic networks (2013)
Journal Article
Radenkovic, M., Benslimane, A., & McAuley, D. (2015). Reputation aware obfuscation for mobile opportunistic networks. IEEE Transactions on Parallel and Distributed Systems, 26(1), 230-240. https://doi.org/10.1109/TPDS.2013.265

© 2013 IEEE. Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large nu... Read More about Reputation aware obfuscation for mobile opportunistic networks.

Automatic generation of statistical pose and shape models for articulated joints (2013)
Journal Article
Chen, X., Graham, J., Hutchinson, C., & Muir, L. (2013). Automatic generation of statistical pose and shape models for articulated joints. IEEE Transactions on Medical Imaging, 33(2), https://doi.org/10.1109/TMI.2013.2285503

Statistical analysis of motion patterns of body joints is potentially useful for detecting and quantifying pathologies. However, building a statistical motion model across different subjects remains a challenging task, especially for a complex joint... Read More about Automatic generation of statistical pose and shape models for articulated joints.

Face hallucination based on sparse local-pixel structure (2013)
Journal Article
Li, Y., Cai, C., Qiu, G., & Lam, K.-M. (2014). Face hallucination based on sparse local-pixel structure. Pattern Recognition, 47(3), 1261-1270. https://doi.org/10.1016/j.patcog.2013.09.012

In this paper, we propose a face-hallucination method, namely face hallucination based on sparse local-pixel structure. In our framework, a high resolution (HR) face is estimated from a single frame low resolution (LR) face with the help of the facia... Read More about Face hallucination based on sparse local-pixel structure.

Grammatical evolution hyper-heuristic for combinatorial optimization problems (2013)
Journal Article
Sabar, N., Ayob, M., Kendall, G., & Qu, R. (2013). Grammatical evolution hyper-heuristic for combinatorial optimization problems. IEEE Transactions on Evolutionary Computation, 17(6), https://doi.org/10.1109/TEVC.2013.2281527

Designing generic problem solvers that perform well across a diverse set of problems is a challenging task. In this work, we propose a hyper-heuristic framework to automatically generate an effective and generic solution method by utilizing grammatic... Read More about Grammatical evolution hyper-heuristic for combinatorial optimization problems.