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A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers (2016)
Conference Proceeding
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (in press). A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers.

Fuzzy logic controllers (FLCs) have extensively been used for the autonomous control and guidance of unmanned aerial vehicles (UAVs) due to their capability of handling uncertainties and delivering adequate control without the need for a precise, mat... Read More about A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers.

On Using Genetic Algorithm for Initialising Semi-supervised Fuzzy c-Means Clustering (2016)
Journal Article
Lai, D. T. C., & Garibaldi, J. M. (2017). On Using Genetic Algorithm for Initialising Semi-supervised Fuzzy c-Means Clustering. Advances in Intelligent Systems and Computing, 532, 3-14. https://doi.org/10.1007/978-3-319-48517-1_1

In a previous work, suitable initialisation techniques were incorporated with semi-supervised Fuzzy c-Means clustering (ssFCM) to improve clustering results on a trial and error basis. In this work, we present a single fully-automatic version of an e... Read More about On Using Genetic Algorithm for Initialising Semi-supervised Fuzzy c-Means Clustering.

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.

An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models (2016)
Conference Proceeding
Chen, C., John, R., Twycross, J., & Garibaldi, J. M. (2016). An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models.

In this paper, an extended ANFIS architecture is proposed. By incorporating an extra layer for the fuzzification process, the extended architecture is able to fit both type-1 and interval type-2 models. The learning properties of the proposed archite... Read More about An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models.

An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS (2016)
Conference Proceeding
Madi, E., Garibaldi, J. M., & Wagner, C. (2016). An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS.

Decision making is an important process for organizations. Common practice involves evaluation of prioritized alternatives based on a given set of criteria. These criteria conflict with each other and commonly no solution can satisfy all criteria sim... Read More about An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS.

KI67 and DLX2 predict increased risk of metastasis formation in prostate cancer: a targeted molecular approach (2016)
Journal Article
Green, W. J., Ball, G., Hulman, G., Johnson, C., Van Schalwyk, G., Ratan, H. L., …Powe, D. G. (in press). KI67 and DLX2 predict increased risk of metastasis formation in prostate cancer: a targeted molecular approach. British Journal of Cancer, https://doi.org/10.1038/bjc.2016.169

Background:There remains a need to identify and validate biomarkers for predicting prostate cancer (CaP) outcomes using robust and routinely available pathology techniques to identify men at most risk of premature death due to prostate cancer. Previo... Read More about KI67 and DLX2 predict increased risk of metastasis formation in prostate cancer: a targeted molecular approach.

Improved Uncertainty Capture for Nonsingleton Fuzzy Systems (2016)
Journal Article
Pourabdollah, A., Wagner, C., Aladi, J. H., & Garibaldi, J. M. (2016). Improved Uncertainty Capture for Nonsingleton Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 24(6), 1513-1524. https://doi.org/10.1109/TFUZZ.2016.2540065

© 2016 IEEE. In nonsingleton fuzzy logic systems (NSFLSs), input uncertainties are modeled with input fuzzy sets in order to capture input uncertainty (e.g., sensor noise). The performance of NSFLSs in handling such uncertainties depends on both the... Read More about Improved Uncertainty Capture for Nonsingleton Fuzzy Systems.

A multi-cycled sequential memetic computing approach for constrained optimisation (2016)
Journal Article
Sun, J., Garibaldi, J. M., Zhang, Y., & Al-Shawabkeh, A. (2016). A multi-cycled sequential memetic computing approach for constrained optimisation. Information Sciences, 340-341, 175-190. https://doi.org/10.1016/j.ins.2016.01.003

In this paper, we propose a multi-cycled sequential memetic computing structure for constrained optimisation. The structure is composed of multiple evolutionary cycles. At each cycle, an evolutionary algorithm is considered as an operator, and connec... Read More about A multi-cycled sequential memetic computing approach for constrained optimisation.

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 comparison between two types of Fuzzy TOPSIS method (2015)
Conference Proceeding
Madi, E., Garibaldi, J. M., & Wagner, C. (2015). A comparison between two types of Fuzzy TOPSIS method.

Multi Criteria Decision Making methods have been developed to solve complex real-world decision problems. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is currently one of the most popular methods and has been shown to p... Read More about A comparison between two types of Fuzzy TOPSIS method.

Automatic detection of protected health information from clinic narratives (2015)
Journal Article
Yang, H., & Garibaldi, J. M. (2015). Automatic detection of protected health information from clinic narratives. Journal of Biomedical Informatics, 58(Suppl.), S30-S38. https://doi.org/10.1016/j.jbi.2015.06.015

This paper presents a natural language processing (NLP) system that was designed to participate in the 2014 i2b2 de-identification challenge. The challenge task aims to identify and classify seven main Protected Health Information (PHI) categories an... Read More about Automatic detection of protected health information from clinic narratives.

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.

Juxtaposition of System Dynamics and Agent-Based Simulation for a Case Study in Immunosenescence (2015)
Journal Article
Figueredo, G. P., Siebers, P., Aickelin, U., Whitbrook, A., & Garibaldi, J. M. (2015). Juxtaposition of System Dynamics and Agent-Based Simulation for a Case Study in Immunosenescence. PLoS ONE, 10(3), Article e0118359. https://doi.org/10.1371/journal.pone.0118359

Advances in healthcare and in the quality of life significantly increase human life expectancy. With the aging of populations, new un-faced challenges are brought to science. The human body is naturally selected to be well-functioning until the age o... Read More about Juxtaposition of System Dynamics and Agent-Based Simulation for a Case Study in Immunosenescence.

Augmented Neural Networks for modelling consumer indebtness (2014)
Journal Article
Ladas, A., M. Garibaldi, J., Scarpel, R., & Aickelin, U. (2014). Augmented Neural Networks for modelling consumer indebtness. Proceedings of International Joint Conference on Neural Networks, 3086-3093. https://doi.org/10.1109/IJCNN.2014.6889760

Consumer Debt has risen to be an important problem of modern societies, generating a lot of research in order to understand the nature of consumer indebtness, which so far its modelling has been carried out by statistical models. In this work we show... Read More about Augmented Neural Networks for modelling consumer indebtness.

Tuning a multiple classifier system for side effect discovery using genetic algorithms (2014)
Conference Proceeding
Reps, J. M., Aickelin, U., & Garibaldi, J. M. (2014). Tuning a multiple classifier system for side effect discovery using genetic algorithms. In 2014 IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2014.6900328

In previous work, a novel supervised framework implementing a binary classifier was presented that obtained excellent results for side effect discovery. Interestingly, unique side effects were identified when different binary classifiers were used wi... Read More about Tuning a multiple classifier system for side effect discovery using genetic algorithms.

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer (2014)
Journal Article
Rakha, E., Soria, D., Green, A. R., Lemetre, C., Powe, D. G., Nolan, C. C., …Ellis, I. O. (2014). Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer. British Journal of Cancer, 110(7), https://doi.org/10.1038/bjc.2014.120

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. I... Read More about Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

From Interval-Valued Data to General Type-2 Fuzzy Sets (2014)
Journal Article
Wagner, C., Miller, S., Garibaldi, J. M., Anderson, D. T., & Havens, T. C. (2015). From Interval-Valued Data to General Type-2 Fuzzy Sets. IEEE Transactions on Fuzzy Systems, 23(2), 248-269. https://doi.org/10.1109/tfuzz.2014.2310734

In this paper, a new approach is presented to model interval-based data using fuzzy sets (FSs). Specifically, we show how both crisp and uncertain intervals (where there is uncertainty about the endpoints of intervals) collected from individual or mu... Read More about From Interval-Valued Data to General Type-2 Fuzzy Sets.

Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs (2014)
Journal Article
Reps, J., M. Garibaldi, J., Aickelin, U., Soria, D., E. Gibson, J., & B. Hubbard, R. (2014). Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs. Drug Safety, 37(3), 163-170. https://doi.org/10.1007/s40264-014-0137-z

Background: Children are frequently prescribed medication `o-label', meaning there has not been sucient testing of the medication to determine its safety or eectiveness. The main reason this safety knowledge is lacking is due to ethical restrictions... Read More about Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs.

A data mining framework to model consumer indebtedness with psychological factors (2014)
Conference Proceeding
Ladas, A., Ferguson, E., Garibaldi, J. M., & Aickelin, U. (2014). A data mining framework to model consumer indebtedness with psychological factors.

Modelling Consumer Indebtedness has proven to be a problem of complex nature. In this work we utilise Data Mining techniques and methods to explore the multifaceted aspect of Consumer Indebtedness by examining the contribution of Psychological Factor... Read More about A data mining framework to model consumer indebtedness with psychological factors.

Personalising mobile advertising based on users’ installed apps (2014)
Conference Proceeding
Reps, J., Aickelin, U., Garibaldi, J. M., & Damski, C. (2014). Personalising mobile advertising based on users’ installed apps.

Mobile advertising is a billion pound industry that is rapidly expanding. The success of an advert is measured based on how users interact with it. In this paper we investigate whether the application of unsupervised learning and association rule min... Read More about Personalising mobile advertising based on users’ installed apps.