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All Outputs (37)

Understanding mass participatory pervasive computing systems for environmental campaigns (2013)
Journal Article
Chamberlain, A., Paxton, M., Glover, K., Flintham, M., Price, D., Benford, S., …Greenhalgh, C. (2014). Understanding mass participatory pervasive computing systems for environmental campaigns. Personal and Ubiquitous Computing, 18(7), https://doi.org/10.1007/s00779-013-0756-x

Participate was a 3-year collaboration between industry and academia to explore how mobile, Web and broadcast technologies could combine to deliver environ- mental campaigns. In a series of pilot projects, schools used mobile sensors to enhance scien... Read More about Understanding mass participatory pervasive computing systems for environmental campaigns.

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.

Comparison of algorithms that detect drug side effects using electronic healthcare databases (2013)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2013). Comparison of algorithms that detect drug side effects using electronic healthcare databases. Soft Computing, 17(12), https://doi.org/10.1007/s00500-013-1097-4

The electronic healthcare databases are starting to become more readily available and are thought to have excellent potential for generating adverse drug reaction signals. The Health Improvement Network (THIN) database is an electronic healthcare dat... Read More about Comparison of algorithms that detect drug side effects using electronic healthcare databases.

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.

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. (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.

A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery (2013)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2014). A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE Journal of Biomedical and Health Informatics, 18(2), 537-547. https://doi.org/10.1109/JBHI.2013.2281505

Drugs are frequently prescribed to patients with the aim of improving each patient's medical state, but an unfortunate consequence of most prescription drugs is the occurrence of undesirable side effects. Side effects that occur in more than one in a... Read More about A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery.

A novel approach to independent taxi scheduling problem based on stable matching (2013)
Journal Article
Bai, R., Li, J., Atkin, J. A., & Kendall, G. (2014). A novel approach to independent taxi scheduling problem based on stable matching. Journal of the Operational Research Society, 65(10), https://doi.org/10.1057/jors.2013.96

This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the stre... Read More about A novel approach to independent taxi scheduling problem based on stable matching.

Extraversion differentiates between model-based and model-free strategies in a reinforcement learning task (2013)
Journal Article
Skatova, A., Chan, P. A., & Daw, N. (2013). Extraversion differentiates between model-based and model-free strategies in a reinforcement learning task. Frontiers in Human Neuroscience, 7, Article 525. https://doi.org/10.3389/fnhum.2013.00525

Prominent computational models describe a neural mechanism for learning from reward prediction errors, and it has been suggested that variations in this mechanism are reflected in personality factors such as trait extraversion. However, although trai... Read More about Extraversion differentiates between model-based and model-free strategies in a reinforcement learning task.

Efficient Location Privacy-Aware Forwarding in Opportunistic Mobile Networks (2013)
Journal Article
Zakhary, S., Radenkovic, M., & Benslimane, A. (2014). Efficient Location Privacy-Aware Forwarding in Opportunistic Mobile Networks. IEEE Transactions on Vehicular Technology, 63(2), 893-906. https://doi.org/10.1109/TVT.2013.2279671

This paper proposes a novel fully distributed and collaborative k-anonymity protocol (LPAF) to protect users’ location information and ensure better privacy while forwarding queries/replies to/from untrusted location-based service (LBS) over opportun... Read More about Efficient Location Privacy-Aware Forwarding in Opportunistic Mobile Networks.

A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means (2013)
Journal Article
Lai, D. T. C., Garibaldi, J. M., Soria, D., & Roadknight, C. M. (2014). A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means. Central European Journal of Operations Research, 22(3), 475-499. https://doi.org/10.1007/s10100-013-0318-3

Previously, a semi-manual method was used to identify six novel and clinically useful classes in the Nottingham Tenovus Breast Cancer dataset. 663 out of 1,076 patients were classified. The objectives of our work is three folds. Firstly, our primary... Read More about A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means.

A path-oriented encoding evolutionary algorithm for network coding resource minimization (2013)
Journal Article
Xing, H., Qu, R., Kendall, G., & Bai, R. (2014). A path-oriented encoding evolutionary algorithm for network coding resource minimization. Journal of the Operational Research Society, 65(8), https://doi.org/10.1057/jors.2013.79

Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computation... Read More about A path-oriented encoding evolutionary algorithm for network coding resource minimization.

A quantifier-based fuzzy classification system for breast cancer patients (2013)
Journal Article
Soria, D., Garibaldi, J. M., Green, A. R., Powe, D. G., Nolan, C. C., Lemetre, C., …Ellis, I. O. (2013). A quantifier-based fuzzy classification system for breast cancer patients. Artificial Intelligence in Medicine, 58(3), https://doi.org/10.1016/j.artmed.2013.04.006

Objectives:Recent studies of breast cancer data have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a range of different clustering techniques. Consensus between unsupervised classification algorithms ha... Read More about A quantifier-based fuzzy classification system for breast cancer patients.

A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems (2013)
Journal Article
Xu, Y., Qu, R., & Li, R. (2013). A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems. Annals of Operations Research, 260(1), https://doi.org/10.1007/s10479-013-1322-7

This paper presents a new hybrid evolutionary algorithm to solve multi-objective multicast routing problems in telecommunication networks. The algorithm combines simulated annealing based strategies and a genetic local search, aiming at a more flexib... Read More about A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems.