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Healthcare organisations using the European Foundation for Quality Management (EFQM) Excellence Model for self-assessment have found an opportunity to work more effectively and a powerful driver for improvement. Nevertheless, when these organisations address self-assessment processes for the first time the initial effort needed presents many difficulties. The aim of this paper is to offer a consensus...
The problem of controlling the induction motor π-model with magnetic saturation is considered using an adaptive controller with stator current and rotor speed measurement. The new in this paper that in the previous work, only the rotor resistance and load torque can be adapted using the controller but in this work, using artificial intelligent technique, an adaptation of the stator resistance variation...
In this paper a new application of fuzzy logic to predict the performance of Titanium Aluminum Nitride (TiAlN) sputtering coating process is presented. Titanium Aluminum Nitride (TiAlN) coated material is widely used as a cutting tool in machining due to its excellent properties such as hardness, roughness and wear. A fuzzy logic model was proposed to predict the coating roughness with respect to...
Wind energy is becoming one of the most important and promising areas of renewable energy. During the past few years, wind energy generation underwent strong improvements in several fields including power electronics, mechanics, wind dynamics, etc. However, there is a high need to develop more intelligent control mechanisms that can handle the various sources of uncertainties encountered in wind turbines...
Autonomous steering control is the principal task in the development of an intelligent transportation system. This research paper proposes a novel approach for vision based intelligent control of unmanned vehicles. The paper addresses the problems of accurate and efficient intelligent vehicle control by incorporating a well known evolutionary algorithm cAnt-Miner. The uniqueness of the proposed algorithm...
Fuzzy C-means (FCM) and Rough K-means (RKM) algorithms are two popular soft clustering algorithms that allow for overlapping clusters. The overlapping clusters can be useful in applications where restrictions imposed by crisp clustering that force assignment of every object to a unique cluster may not be practical. Likewise RKM and FCM, interval set representation of clusters would also generate overlapping...
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