We extend type-1 fuzzy contingency table to type-2 in order to analyze inexact information. We apply the type-2 fuzzy contingency table to needs analysis for students learning media lectures in university and show its effectiveness from some data.

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Diagnosis is essential for patient treatment. The diagnosis has two objectives: deciding on the disease or syndrome and classifying its grade, in which some fuzziness of diagnosis is imbedded. The purpose of this paper is to examine the relationship between the decision of disease or syndrome and the classification of grades. To clarify the fuzziness of diagnosis, we analyzed clinical data on patients with Carpal Tunnel Syndrome (CTS) using multivariate analysis. From the analytical results, we propose a new diagnostic logic with two diagnostic layers: A first layer for the detection about CTS by the clinical indicators such as Ring finger sensory splitting and Phalen’s test, and a second layer for the classification of CTS by indicators of Thenar muscle atrophy and Pinch disturbance.

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In most industrial projects, costs and completion dates are difficult to predict. More efficient project management is needed in order to maintain schedules and reduce cost. Narrowing down requirements to applicable specifications and unifying or cutting tasks in projects are effective means to shorten schedules and reduce costs. This paper aims to prioritize requirements using cost share rates from linguistic analysis and artificial neural networks. At the conclusion, this paper shows the potential to prioritize requirements and to reduce costs by limiting requirements. In the future, this method would be able to help unify or cut tasks in system development projects in order to shorten schedule and reduce costs.

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