Muhaini Othman

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The paper presents a novel method and system for personalised (individualised) modelling of spatio/ spectro-temporal data (SSTD) and prediction of events. A novel evolving spiking neural network reservoir system (eSNNr) is proposed for the purpose. The system consists of spike-time encoding module of continuous value input information into spike trains; a(More)
The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing(More)
OBJECTIVES Lung exposures including cigarette smoking and silica exposure are associated with the risk of rheumatoid arthritis (RA). We investigated the association between textile dust exposure and the risk of RA in the Malaysian population, with a focus on women who rarely smoke. METHODS Data from the Malaysian Epidemiological Investigation of(More)
Early event prediction challenges most of existing modeling methods especially when dealing with complex spatio-temporal data. In this paper we propose a new method for predictive data modelling based on a new development of the recently proposed NeuCube spiking neural network architecture, called here NeuCube<sup>(ST)</sup>. The NeuCube uses a Spiking(More)
This paper discusses the proposed model of the collaborative virtual learning system for the introductory computer programming course which uses one of the collaborative learning techniques known as the “Think-Pair-Share”. The main objective of this study is to design a model for an online learning system that facilitates the collaborative learning(More)
This paper is a continuation of previous published work by the same authors on Personalized Modelling and Evolving Spiking Neural Network Reservoir architecture (PMeSNNr). The focus is on improvement of predictive modeling methods for the stroke occurrences case study utilizing an enhanced NeuCube architecture. The adaptability of the new architecture leads(More)
The increment of spatial-temporal data (STD) collected in many domain areas, including bioinformatics, engineering, medicine, environment, telecommunication, computer vision and many more has leads towards the emergent of information technology initiatives that facilitate the knowledge acquisition, organization and dissemination among research community.(More)
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