Muhaini Othman

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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)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t The paper presents a novel method and system for personalised(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)
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)
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)
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