All Outputs (9)

A fast community detection method in bipartite networks by distance dynamics (2017)
Journal Article
Sun, H., Ch'ng, E., Yong, X., Garibaldi, J. M., See, S., & Chen, D. (2018). A fast community detection method in bipartite networks by distance dynamics. Physica A: Statistical Mechanics and its Applications, 496, https://doi.org/10.1016/j.physa.2017.12.099

Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extens... Read More about A fast community detection method in bipartite networks by distance dynamics.

Positive mood on the day of influenza vaccination predicts vaccine effectiveness: A prospective observational cohort study (2017)
Journal Article
Ayling, K., Fairclough, L., Tighe, P., Todd, I., Halliday, V., Garibaldi, J., …Vedhara, K. (2018). Positive mood on the day of influenza vaccination predicts vaccine effectiveness: A prospective observational cohort study. Brain, Behavior, and Immunity, 67, 314-323. https://doi.org/10.1016/j.bbi.2017.09.008

© 2017 Influenza vaccination is estimated to only be effective in 17–53% of older adults. Multiple patient behaviors and psychological factors have been shown to act as ‘immune modulators’ sufficient to influence vaccination outcomes. However, the re... Read More about Positive mood on the day of influenza vaccination predicts vaccine effectiveness: A prospective observational cohort study.

An improved game-theoretic approach to uncover overlapping communities (2017)
Journal Article
Sun, H., Ch'ng, E., Yong, X., Garibaldi, J. M., See, S., & Chen, D. (2017). An improved game-theoretic approach to uncover overlapping communities. International Journal of Modern Physics C, 28(8), Article 1750112. https://doi.org/10.1142/S0129183117501121

How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered whe... Read More about An improved game-theoretic approach to uncover overlapping communities.

An Immune-Inspired Technique to Identify Heavy Goods Vehicles Incident Hot Spots (2017)
Journal Article
Figueredo, G. P., Triguero, I., Mesgarpour, M., Maciel Guerra, A., Garibaldi, J. M., & John, R. (2017). An Immune-Inspired Technique to Identify Heavy Goods Vehicles Incident Hot Spots. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(4), 248-258. https://doi.org/10.1109/TETCI.2017.2721960

We report on the adaptation of an immune-inspired instance selection technique to solve a real-world big data problem of determining vehicle incident hot spots. The technique, which is inspired by the Immune System self-regulation mechanism, was orig... Read More about An Immune-Inspired Technique to Identify Heavy Goods Vehicles Incident Hot Spots.

A signalome screening approach in the autoinflammatory disease TNF receptor associated periodic syndrome (TRAPS) highlights the anti-inflammatory properties of drugs for repurposing (2017)
Journal Article
Figueredo, G., Todd, I., Negm, O. H., Reps, J., Radford, P., Figueredo, G. P., …Tighe, P. J. (2017). A signalome screening approach in the autoinflammatory disease TNF receptor associated periodic syndrome (TRAPS) highlights the anti-inflammatory properties of drugs for repurposing. Pharmacological Research, 125, 188-200. https://doi.org/10.1016/j.phrs.2017.08.012

© 2017 Elsevier Ltd TNF receptor associated periodic syndrome (TRAPS) is an autoinflammatory disease caused by mutations in TNF Receptor 1 (TNFR1). Current therapies for TRAPS are limited and do not target the pro-inflammatory signalling pathways tha... Read More about A signalome screening approach in the autoinflammatory disease TNF receptor associated periodic syndrome (TRAPS) highlights the anti-inflammatory properties of drugs for repurposing.

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., Xia, J., Garibaldi, J. M., Groumpos, P. P., & Wang, R. (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.