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All Outputs (241)

Fuzzy C-means-based scenario bundling for stochastic service network design (2018)
Conference Proceeding
Jiang, X., Bai, R., Landa-Silva, D., & Aickelin, U. (2018). Fuzzy C-means-based scenario bundling for stochastic service network design. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (1-8). https://doi.org/10.1109/SSCI.2017.8280905

Stochastic service network designs with uncertain demand represented by a set of scenarios can be modelled as a large-scale two-stage stochastic mixed-integer program (SMIP). The progressive hedging algorithm (PHA) is a decomposition method for solvi... Read More about Fuzzy C-means-based scenario bundling for stochastic service network design.

A Method for Evaluating Options for Motif Detection in Electricity Meter Data (2018)
Journal Article
Dent, I., Craig, T., Aickelin, U., & Rodden, T. (2018). A Method for Evaluating Options for Motif Detection in Electricity Meter Data. International Journal of Data Science, 16(1), 1-28. https://doi.org/10.6339/jds.201801_16%281%29.0001

Investigation of household electricity usage patterns, and matching the patterns to behaviours, is an important area of research given the centrality of such patterns in addressing the needs of the electricity industry. Additional knowledge of househ... Read More about A Method for Evaluating Options for Motif Detection in Electricity Meter Data.

Using simulation to incorporate dynamic criteria into multiple criteria decision making (2017)
Journal Article
Aickelin, U., Reps, J. M., Siebers, P., & Li, P. (2018). Using simulation to incorporate dynamic criteria into multiple criteria decision making. Journal of the Operational Research Society, 69(7), 1021-1032. https://doi.org/10.1080/01605682.2017.1410010

In this paper we present a case study demonstrating how dynamic and uncertain criteria can be incorporated into a multi-criteria analysis with the help of discrete event simulation. The simulation guided multi-criteria analysis can include both monet... Read More about Using simulation to incorporate dynamic criteria into multiple criteria decision making.

THCluster: herb supplements categorization for precision traditional Chinese medicine (2017)
Conference Proceeding
Ruan, C., Wang, Y., Zhang, Y., Ma, J., Chen, H., Aickelin, U., …Zhang, T. (2017). THCluster: herb supplements categorization for precision traditional Chinese medicine.

There has been a continuing demand for traditional and complementary medicine worldwide. A fundamental and important topic in Traditional Chinese Medicine (TCM) is to optimize the prescription and to detect herb regularities from TCM data. In this pa... Read More about THCluster: herb supplements categorization for precision traditional Chinese medicine.

Novel similarity measure for interval-valued data based on overlapping ratio (2017)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017). Novel similarity measure for interval-valued data based on overlapping ratio. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015623

In computing the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal similarities for substantially different pairs... Read More about Novel similarity measure for interval-valued data based on overlapping ratio.

Measuring behavioural change of players in public goods game (2017)
Book Chapter
Fattah, P., Aickelin, U., & Wagner, C. (2017). Measuring behavioural change of players in public goods game. In P. Fattah, U. Aickelin, & C. Wagner (Eds.), Measuring Behavioural Change of Players in Public Goods Game. Springer

In the public goods game, players can be classified into different types according to their participation in the game. It is an important issue for economists to be able to measure players’ strategy changes over time which can be considered as concep... Read More about Measuring behavioural change of players in public goods game.

CRNN: A Joint Neural Network for Redundancy Detection (2017)
Conference Proceeding
Fu, X., Ch’ng, E., Aickelin, U., & See, S. (2017). CRNN: A Joint Neural Network for Redundancy Detection. In 2017 IEEE International Conference on Smart Computing (SMARTCOMP) (1-8). https://doi.org/10.1109/SMARTCOMP.2017.7946996

This paper proposes a novel framework for detecting redundancy in supervised sentence categorisation. Unlike traditional singleton neural network, our model incorporates character-aware convolutional neural network (Char-CNN) with character-aware rec... Read More about CRNN: A Joint Neural Network for Redundancy Detection.

Robust datamining (2017)
Conference Proceeding
Uwe, A. (2017). Robust datamining.

Our long-term research goal is to develop datamining methodologies that are robust to changes in data and uncertainty. By robust we mean solutions remain ‘optimal’ when things change or are easily repaired. Broadly, this robustness can be achieved in... Read More about Robust datamining.

Measuring agreement on linguistic expressions in medical treatment scenarios (2016)
Conference Proceeding
Navarro, J., Wagner, C., Aickelin, U., Green, L., & Ashford, R. (2016). Measuring agreement on linguistic expressions in medical treatment scenarios. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI) (1-8). https://doi.org/10.1109/SSCI.2016.7849895

Quality of life assessment represents a key process of deciding treatment success and viability. As such, patients’ perceptions of their functional status and well-being are important inputs for impairment assessment. Given that patient completed que... Read More about Measuring agreement on linguistic expressions in medical treatment scenarios.

Exploring differences in interpretation of words essential in medical expert-patient communication (2016)
Conference Proceeding
Navarro, J., Wagner, C., Aickelin, U., Green, L., & Robert, A. (2016). Exploring differences in interpretation of words essential in medical expert-patient communication. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

In the context of cancer treatment and surgery, quality of life assessment is a crucial part of determining treatment success and viability. In order to assess it, patient-completed questionnaires which employ words to capture aspects of patients’ we... Read More about Exploring differences in interpretation of words essential in medical expert-patient communication.

Measuring player’s behaviour change over time in public goods game (2016)
Conference Proceeding
Fattah, P., Aickelin, U., & Wagner, C. (2016). Measuring player’s behaviour change over time in public goods game.

An important issue in public goods game is whether player's behaviour changes over time, and if so, how significant it is. In this game players can be classified into different groups according to the level of their participation in the public good.... Read More about Measuring player’s behaviour change over time in public goods game.

Modelling cyber-security experts' decision making processes using aggregation operators (2016)
Journal Article
Miller, S., Wagner, C., Aickelin, U., & Garibaldi, J. M. (2016). Modelling cyber-security experts' decision making processes using aggregation operators. Computers and Security, 62, 229-245. https://doi.org/10.1016/j.cose.2016.08.001

An important role carried out by cyber-security experts is the assessment of proposed computer systems, during their design stage. This task is fraught with difficulties and uncertainty, making the knowledge provided by human experts essential for su... Read More about Modelling cyber-security experts' decision making processes using aggregation operators.

Optimising rule-based classification in temporal data (2016)
Journal Article
Fattah, P., Aickelin, U., & Wagner, C. (2016). Optimising rule-based classification in temporal data. Zanco Journal of Pure and Applied Sciences, 28(2),

This study optimises manually derived rule-based expert system classification of objects according to changes in their properties over time. One of the key challenges that this study tries to address is how to classify objects that exhibit changes in... Read More about Optimising rule-based classification in temporal data.

An improved system for sentence-level novelty detection in textual streams (2016)
Conference Proceeding
Fu, X., Ch'ng, E., & Aickelin, U. (in press). An improved system for sentence-level novelty detection in textual streams. . https://doi.org/10.1049/cp.2015.0250

Novelty detection in news events has long been a difficult problem. A number of models performed well on specific data streams but certain issues are far from being solved, particularly in large data streams from the WWW where unpredictability of new... Read More about An improved system for sentence-level novelty detection in textual streams.

Simulating user learning in authoritative technology adoption: an agent based model for council-led smart meter deployment planning in the UK (2016)
Journal Article
Zhang, T., Siebers, P., & Aickelin, U. (2016). Simulating user learning in authoritative technology adoption: an agent based model for council-led smart meter deployment planning in the UK. Technological Forecasting and Social Change, 106, https://doi.org/10.1016/j.techfore.2016.02.009

How do technology users effectively transit from having zero knowledge about a technology to making the best use of it after an authoritative technology adoption? This post-adoption user learning has received little research attention in technology m... Read More about Simulating user learning in authoritative technology adoption: an agent based model for council-led smart meter deployment planning in the UK.

Supervised anomaly detection in uncertain pseudoperiodic data streams (2016)
Journal Article
Ma, J., Sun, L., Wang, H., Zhang, Y., & Aickelin, U. (2016). Supervised anomaly detection in uncertain pseudoperiodic data streams. ACM Transactions on Internet Technology, 16(1), https://doi.org/10.1145/2806890

Uncertain data streams have been widely generated in many Web applications. The uncertainty in data streams makes anomaly detection from sensor data streams far more challenging. In this paper, we present a novel framework that supports anomaly detec... Read More about Supervised anomaly detection in uncertain pseudoperiodic data streams.

Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation (2015)
Conference Proceeding
Navarro, J., Wagner, C., & Aickelin, U. (2015). Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation.

Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, i.e. classifiers which can be introspective, understood, validated and augmented by human experts by relying on fuzzy-set based rules.... Read More about Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation.

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining (2015)
Journal Article
Reps, J. M., Aickelin, U., & Hubbard, R. B. (2016). Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. Computers in Biology and Medicine, 69, https://doi.org/10.1016/j.compbiomed.2015.11.014

Purpose: To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. Methods: We co... Read More about Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework (2015)
Conference Proceeding
Figueredo, G. P., Wagner, C., Garibaldi, J. M., & Aickelin, U. (2015). Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework. . https://doi.org/10.1109/Trustcom.2015.571

In this position paper, we present ideas about creating a next generation framework towards an adaptive interface for data communication and visualisation systems. Our objective is to develop a system that accepts large data sets as inputs and provid... Read More about Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework.

A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations (2015)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Gibson, J. E., & Hubbard, R. B. (2015). A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations. Journal of Biomedical Informatics, 56, https://doi.org/10.1016/j.jbi.2015.06.011

Big longitudinal observational medical data potentially hold a wealth of information and have been recognised as potential sources for gaining new drug safety knowledge. Unfortunately there are many complexities and underlying issues when analysing l... Read More about A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations.