All Outputs (119)

Similarity-based non-singleton fuzzy logic control for improved performance in UAVs (2017)
Presentation / Conference Contribution
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (2017). Similarity-based non-singleton fuzzy logic control for improved performance in UAVs. In Proceedings - 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015440

© 2017 IEEE. As non-singleton fuzzy logic controllers (NSFLCs) are capable of capturing input uncertainties, they have been effectively used to control and navigate unmanned aerial vehicles (UAVs) recently. To further enhance the capability to handle... Read More about Similarity-based non-singleton fuzzy logic control for improved performance in UAVs.

A Direct Approach for Determining the Switch Points in the Karnik–Mendel Algorithm (2017)
Journal Article
Chen, C., John, R., Twycross, J., & Garibaldi, J. M. (2018). A Direct Approach for Determining the Switch Points in the Karnik–Mendel Algorithm. IEEE Transactions on Fuzzy Systems, 26(2), 1079-1085. https://doi.org/10.1109/tfuzz.2017.2699168

The Karnik-Mendel algorithm is used to compute the centroid of interval type-2 fuzzy sets, determining the switch points needed for the lower and upper bounds of the centroid, through an iterative process. It is commonly acknowledged that there is n... Read More about A Direct Approach for Determining the Switch Points in the Karnik–Mendel Algorithm.

Can machine-learning improve cardiovascular risk prediction using routine clinical data (2017)
Journal Article
Weng, S. F., Reps, J. M., Kai, J., Garibaldi, J. M., & Quereshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data. PLoS ONE, 12(4), Article e0174944. https://doi.org/10.1371/journal.pone.0174944

Background
Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiti... Read More about Can machine-learning improve cardiovascular risk prediction using routine clinical data.

A new accuracy measure based on bounded relative error for time series forecasting (2017)
Journal Article
Chen, C., Twycross, J., & Garibaldi, J. M. (2017). A new accuracy measure based on bounded relative error for time series forecasting. PLoS ONE, 12(3), Article e0174202. https://doi.org/10.1371/journal.pone.0174202

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising c... Read More about A new accuracy measure based on bounded relative error for time series forecasting.

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets (2017)
Journal Article
Zhang, J.-H., Xia, J.-J., Garibaldi, J. M., Groumpos, P. P., & Wang, R.-B. (2017). Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets. Computer Methods and Programs in Biomedicine, 144, https://doi.org/10.1016/j.cmpb.2017.03.016

Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must b... Read More about Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.

Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts (2016)
Presentation / Conference Contribution
Soria, D., & Garibaldi, J. M. (2016). Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts.

Recent studies in breast cancer domains have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a variety of unsupervised learning techniques. Consensus among the clustering algorithms has been used to categ... Read More about Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts.

A similarity-based inference engine for non-singleton fuzzy logic systems (2016)
Presentation / Conference Contribution
Wagner, C., Pourabdollah, A., McCulloch, J., John, R., & Garibaldi, J. M. (2016). A similarity-based inference engine for non-singleton fuzzy logic systems. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (316-323). https://doi.org/10.1109/FUZZ-IEEE.2016.7737703

In non-singleton fuzzy logic systems (NSFLSs) input uncertainties are modelled with input fuzzy sets in order to capture input uncertainty such as sensor noise. The performance of NSFLSs in handling such uncertainties depends both on the actual input... Read More about A similarity-based inference engine for non-singleton fuzzy logic systems.

A comparative study on the control of Quadcopter UAVs by using singleton and non-singleton fuzzy logic controllers (2016)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
Figueredo, G. P., Wagner, C., Garibaldi, J. M., & Aickelin, U. (2015, August). Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework. Presented at Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015, Helsinki, Finland

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)
Presentation / Conference Contribution
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.-O., 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.