-This paper introduces a new image thresholding method based on minimizing the measures of fuzziness of an input image. The membership function in the thresholding method is used to denote the characteristic relationship between a pixel and its belonging region (the object or the background). In addition, based on the measure of fuzziness, a fuzzy range is defined to find the adequate threshold...

Due to the existing of various kinds of uncertainties, predicting structural performance is always a great challenge in practical applications. The reliability of structure under the probabilistic uncertainty has been well studied in the past decade. However, the randomness is not the only attribute of reality. This paper attempts to investigate approach for the structural reliability analysis ...

The clinical decision is supposed to be based on evidence. In fact, what counts as evidence is far from being established. Some definition of ‘‘proof’’ is needed to distinguish between scientific medicine and charlatanism. My thesis is that unfortunately a clear-cut boundary between evidence and lack of evidence cannot be found, for several reasons that I summarise in the paper. Evidence in med...

Within the framework of fuzzy logic for pattern recognition, we propose a neural network based membership function procedure. The estimate is obtained as the output of a multilayer network trained to minimize a fuzziness measure of the concept to be learnt. This method is shown to be able to deal with probabilistic, resolutional and fuzzy uncertainty. Fuzziness estimation is also made possible ...

In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for termina...

This paper presents an approach to texture segmen tation by thresholding based on compactness measures of fuzzy sets to determine thresholds of an ill-defined image. The extension of fuzziness in the texture feature space provides more meaningful results than by considering fuzziness in gray scale domain. The effectiveness of the algorithm is demonstrated by comparison with other traditional no...

High-stakes (dangerous, catastrophic) risks take on a wider profile as progress unfolds. What are the impacts of technological and social change on the risk landscape? Due to the complexities and dynamics involved, we can only answer these questions approximately. By using the concept of fuzziness, we can formalize our imprecision about high-stakes risk, and therefore place their management on ...

In this paper, several portfolio selection problems with normal mixture distributions including fuzziness are proposed. Until now, many researchers have proposed portfolio models based on the stochastic approach, and there are some models considering both random and ambiguous conditions, particularly using fuzzy random or random fuzzy variables. However, the model including normal mixture distr...