Nor Ridzuan Daud

Contact positions estimation of sensing structure using adaptive neuro-fuzzy inference system

Purpose – Tactile sensing is the process of determining physical properties and events through contact with objects in the world. The purpose of this paper is to establish a novel design of an adaptive neuro-fuzzy inference system (ANFIS) for estimation of contact position of a new tactile sensing structure. Design/methodology/approach – The major task is to investigate implementations of carbon-black-filled silicone rubber for tactile sensation; the silicone rubber is electrically conductive and its resistance changes by loading or unloading strains. Findings – The sensor-elements for the tactile sensing structure were made by press-curing from carbon-black-filled silicone rubber. The experimental results can be used as training and checking data for the ANFIS network. Originality/value – This system is capable to find any change of contact positions and thus indicates state of the current contact location of the tactile sensing structure. The behavior of the use silicone rubber shows strong non-linearit...

Human Readable Rule Induction in Medical Data Mining

In general, the human-readable rule refers to data shown in a format easily read by most humans—normally this is in the form of IF…THEN rules. This is the most convenient way for physicians to express their knowledge in medical diagnosis. In particular, if learned diagnostic rules can be presented in such a form, physicians are much more likely to trust and believe the consequent diagnoses. This paper investigates the performances of existing state-of-the-art classification algorithms, mainly rule induction and tree algorithms, on benchmark problems in medical data mining. The findings indicate that certain algorithms are better for generating rules that are both accurate and short; these algorithms are recommended for further research towards the goal of improved accuracy and readability in medical data mining.