Two groups of fourth-grade children were selected from a population sample (N=926) to be either poor oral comprehenders (poor oral comprehension but normal word decoding) or poor decoders (poor decoding but normal oral comprehension). By examining both groups in the same study with varied cognitive and literacy predictors, and examining them both retrospectively and prospectively, we could asse...

In this paper I will introduce the trapezoidal intuitionistic fuzzy numbers (IF numbers) and will prove some operations for them. Also I am going to propose a new ordering method for IF numbers in which I will consider two characteristic values of membership and non-membership functions for an IF number. These values are defined by the integral of the inverse fuzzy membership and non-membership...

BACKGROUND Determination of drug safety and tolerability is usually based on the frequency of certain key adverse events (AEs) rather than the frequency of all-grade toxicities. We assessed the reporting of key AEs in oncology randomized, controlled trials (RCTs) and compared that with the expectations of the European Organization for Research and Treatment of Cancer (EORTC) membership. MATER...

This paper proposes a framework of multisource geo-knowledge discovery with association rules. Taking into account spatial data exist semantic fuzziness, and the conversion between qualitative concept and quantitative description is uncertain, in our study, conceptual partition algorithm and membership grade judgment algorithm based on cloud model was used. Meanwhile, there are many correlation...

The type-2 fuzzy sets was introduced by L. Zadeh as an extension of ordinary fuzzy sets. So the concept of type-2 fuzzy sets is also extended from type-1 fuzzy sets. If A is a type-1 fuzzy set and membership grade of x ∈ X in A is μA(x), which is a crisp number in [0, 1]. A type-2 fuzzy set in X is Ã, and the membership grade of x ∈ X in à is μÃ(x), which is a type-1 fuzzy set in [0, 1]. The el...

A pattern-recognition method for flatness defect based on CMAC neural network is proposed, and a flatness fuzzy controller based on the pattern-recognition results is designed in this paper. Pattern-recognition and controller are designed into a single unit, in which CMAC recognizes the membership grade relative to six basic modes of common flatness defect and realizes the seeking function of t...

Fuzzy segmentation is a technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership in an object (which is believed to be contained in the image). In an earlier work, the first two authors extended this concept by presenting and illustrating an algorithm which simultaneously assigns to each element in an image a grade of membe...