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He was instrumental in setting up the Internet Commerce Security Laboratory with Westpac, IBM and the Victorian State Government as a joint industry-focused and data-driven laboratory on cyber security in the financial sector.
Professor Yearwood's work in data mining and computational intelligence has led to the development of new machine learning and hybrid learning algorithms for artificial neural networks, as well as new data and text mining and pattern recognition approaches.
His work in decision science has developed the use of argumentation structures for the modelling of knowledge and collaborative decision making in complex domains. He has published over journal and refereed conference papers including 2 books.
Defending unknown attacks on cyber-physical systems by semi-supervised approach and available unlabeled data. Heterogeneous cooperative co-evolution memetic differential evolution algorithms for big data optimisation problems.
Exponentially weighted control charts to monitor multivariate process variability for high dimensions. A parallel framework for software defect detection and metric selection on cloud computing. Kernel-based features for predicting population health indices from geocoded social media data.
Patchwork-based multilayer audio watermarking. Detection of ground parrot vocalisation: A multiple instance learning approach. A framework for software defect prediction and metric selection. Hybrids of support vector machine wrapper and filter based framework for malware detection. Protection of privacy in biometric data. Group decision making in health care: A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression.
Discriminative cues for different stages of smoking cessation in online community. Guidelines for developing and reporting machine learning predictive models in biomedical research: A hybrid feature binary options neural network yearwood medical with ensemble classification for imbalanced healthcare data: Constructing an inter-post similarity measure to differentiate the psychological stages in offensive chats.
A hybrid wrapper-filter approach to detect the source s of out-of-control signals in multivariate manufacturing process. Hybrid metaheuristic approaches to the expectation maximization for estimation of the hidden markov model for signal modeling. Analytics service oriented architecture for enterprise information systems. A new loss function for robust classification. A theoretical foundation of demand driven web services.
Attribute weighted Naive Bayes binary options neural network yearwood medical using a local optimization. A data mining application of the incidence semirings. A technique for ranking friendship closeness in social networking services. An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling. Illicit image detection using erotic pose estimation based on kinematic constraints. Application of rank correlation, clustering and classification in information security.
Derivative-free optimization and neural networks for robust regression. Improving classifications for cardiac autonomic neuropathy using multi-level ensemble classifiers and feature selection based on random forest. Performance evaluation of multivariate non-normal process using metaheuristic approaches.
Applications of machine learning for linguistic analysis of texts. Intelligent Techniques, Hershey, Pa. Machine learning algorithms for analysis of DNA data sets. Approaches for community decision making and collective reasoning: Profiling phishing activity based on hyperlinks extracted from phishing emails.
A novel approach to optimal pump scheduling in water distribution systems. Optimal rees matrix constructions for analysis of data. Empirical study of decision trees and ensemble classifiers for monitoring of diabetes patients in pervasive healthcare.
Empirical investigation of consensus clustering for large ECG data sets. Novel weighting in single hidden layer feedforward neural networks for data classification.
Using psycholinguistic features for profiling first language of authors. Detection of CAN by ensemble classifiers based on ripple down rules. Hybrid wrapper-filter approaches for input feature selection using maximum relevance-minimum redundancy and artificial neural network input gain measurement approximation ANNIGMA. Child face detection using age specific binary options neural network yearwood medical invariant geometric descriptor.
Real-time detection of children's skin on social networking sites using Markov random field modelling. Reinforcement learning approach to AIBO robot's decision making process in Robosoccer's goal keeper problem. Does the Delphi process lead binary options neural network yearwood medical increased accuracy in group-based judgmental forecasts or does it simply induce consensus amongst judgmental forecasters?
Optimization of matrix binary options neural network yearwood medical for classification systems. A reinforcement learning approach with spline-fit object tracking for AIBO robot's high level decision making.
Optimization of classifiers for data mining based on combinatorial semigroups. Internet security applications of the Munn rings. The impact of frame semantic annotation levels, frame-alignment techniques, and fusion methods on factoid answer processing. Narrative-based interactive learning environments from modelling reasoning. A hybrid neural learning algorithm using evolutionary learning and derivative free local search method. A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems.
New algorithms for multi-class cancer diagnosis using tumor gene expression signatures. Argumentation structures that integrate dialectical and non-dialectical reasoning. Retrieving cases for treatment advice in nursing using text representation and structured text retrieval. Enhancing and supporting deliberations within multidisciplinary binary options neural network yearwood medical teams - transfer in Intelligent software engineering techniques to monitor and improve the quality of software development and managing the productivity of the developers.
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Constructing an inter-post similarity measure to differentiate the psychological stages in offensive chats M Miah, J Yearwood, S KulkarniVol. Hybrid metaheuristic approaches to the expectation maximization for estimation of the hidden markov model for signal modeling S Huda, J Yearwood, R TogneriVol. A theoretical foundation of demand driven web services Z Sun, J Yearwoodpp. Improving classifications for cardiac autonomic neuropathy using multi-level ensemble classifiers and feature selection based on random forest A Kelarev, A Stranieri, J Yearwood, J Abawajy, H Jelinekpp.
Integrating online social networks with e-Commerce: Empirical study of decision trees and ensemble classifiers for monitoring of diabetes patients in pervasive healthcare A Kelarev, A Stranieri, J Yearwood, H Jelinekpp.
Novel weighting in single hidden layer feedforward neural networks for data classification S Seifollahi, J Yearwood, B OfoghiVol. Child face detection using age specific luminance invariant geometric descriptor M Islam, P Watters, J Yearwoodpp.
The impact of frame semantic annotation levels, frame-alignment techniques, and fusion methods on factoid answer processing B Ofoghi, J Yearwood, M LipingVol. Narrative-based interactive learning environments from modelling reasoning J Yearwood, A StranieriVol. A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems A Bagirov, J YearwoodVol. Retrieving cases for treatment advice in nursing using text representation and structured text retrieval J Yearwood, R WilkinsonVol.
Industry and Other Funding Intelligent software engineering techniques to monitor and improve the quality of software development and managing the productivity of the developers Dr Shamsul Huda, Prof John Yearwood, Prof Jemal Abawajy