This paper presents a clustering approach for grouping components of similar reusability using an already worked out fuzzy data set [2]. Research has shown that, component based systems development concept benefits the object oriented software development. A Component based system achieves flexibility by clearly separating the stable parts of systems from the specification of their composition. Many software systems contain many similar or even identical components and these components are developed from scratch over and over again which require extra effort. So to minimize the extra effort in developing these components, it is more beneficial to reuse the existing components. To reuse components effectively in Component Based Software Development, it is required to quantify the reusability of components. However it is difficult to use clustering approach to predict reusability. This paper discusses a technique to cluster components of similar reusability together for the purpose of minimizing the efforts of the developer using agglomerative hierarchical clustering. Components attribute affecting the reusability are classified into rules using fuzzy system and are then taken as the inputs to the proposed clustering model.
Medical diagnosis is basically a pattern classification phenomena: based on some input provided by a patient, an expert gives a conclusion on the basis of its knowledge, which is normally stored in a binary form, and finally the result is calculated i.e. either the patient suffering from a certain disease or not. There are a number of properties in fuzzy set theory has a number of facilities that make it suitable for medical diagnosis. The results and findings from the study had shown that the technique of fuzzy logic can contribute a reliable result in order to notify the disease. Human subject has been used to test the system. In this paper we have proposed a system for medical diagnosis which is a generated using Fuzzy Logic Toolbox in MATLAB. Specifically, it focuses on medical diagnosis.
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