The purpose of this paper is to shed light on the concept of fuzzy logic ,its application in linguistics ,especially in language teaching and the fuzziness of some lexical items in English.
Fuzziness means that the semantic boundaries of some lexical items are indefinite and ideterminate.Fuzzy logic provides a very precise approach for dealing with this indeterminacy and uncertainty which grows (among other reasons) out of human behavior and the effect of society.
The concept of fuzzy logic has emerged in the development of the theory of fuzzy set by Lotfi Zadeh(a professor of computer science at the university of California) in 1965.It can be thought of as the application side of the fuzzy set theory. In linguistics, few scholars have dealt with this phenomenon, among them, Lakoff (1972), Labov (1973), and Aitchison (1994). Consequently, very little literature is available on this concept in linguistics. The researcher has to collect bits of information scattered in various fields of knowledge.
The paper is of three sections: section one surveys briefly some of the semantic terms which are closely related to lexical fuzziness, since it is a problem of meaning by nature, like denotation versus connotation and intension versus extension. Section two is of two main parts. The first explores in detail the emergence of fuzzy logic, shedding light on its development and the criticism to it. The second part is devoted to lexical fuzziness, trying to discover its characteristics, the reasons behind its existence in languages, its relation to other similar concepts like vagueness, its application in teaching a second language and some other related titles.
In this paper the research introduces a new definition of a fuzzy normed space then the related concepts such as fuzzy continuous, convergence of sequence of fuzzy points and Cauchy sequence of fuzzy points are discussed in details.
This paper introduce two types of edge degrees (line degree and near line degree) and total edge degrees (total line degree and total near line degree) of an edge in a fuzzy semigraph, where a fuzzy semigraph is defined as (V, σ, μ, η) defined on a semigraph G* in which σ : V → [0, 1], μ : VxV → [0, 1] and η : X → [0, 1] satisfy the conditions that for all the vertices u, v in the vertex set, μ(u, v) ≤ σ(u) ᴧ σ(v) and η(e) = μ(u1, u2) ᴧ μ(u2, u3) ᴧ … ᴧ μ(un-1, un) ≤ σ(u1) ᴧ σ(un), if e = (u1, u2, …, un), n ≥ 2 is an edge in the semigraph G
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Fuzzy orbit topological space is a new structure very recently given by [1]. This new space is based on the notion of open fuzzy orbit sets. The aim of this paper is to provide applications of open fuzzy orbit sets. We introduce the notions of fuzzy orbit irresolute mappings and fuzzy orbit open (resp. irresolute open) mappings and studied some of their properties. .
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A fuzzy logic approach (FLA) application in the process of stud arc welding environment was implemented under the condition of fuzziness input data. This paper is composed of the background of FLA, related research work review and points for developing in stud welding manufacturing. Then, it investigates thecase of developingstud arc welding process on the controversial certaintyof available equipment and human skills.Five parameters (welding time, sheet thickness, type of coating, welding current and stud shape) were studied.A pair of parameter was selected asiteration whichis welding current and welding time and used fo
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Abstract of the research:
This research sheds light on an important phenomenon in our Arabic language, which is linguistic sediments, and by which we mean a group of vocabulary that falls out of use and that native speakers no longer use it, and at the same time it happens that few individuals preserve the phenomenon and use it in their lives, and it is one of the most important phenomena that It should be undertaken and studied by researchers; Because it is at the heart of our huge linguistic heritage, as colloquial Arabic dialects retain a lot of linguistic sediments, and we usually find them at all levels of language: phonetic, banking, grammatical and semantic. In the
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Cluster analysis (clustering) is mainly concerned with dividing a number of data elements into clusters. The paper applies this method to create a gathering of symmetrical government agencies with the aim to classify them and understand how far they are close to each other in terms of administrative and financial corruption by means of five variables representing the prevalent administrative and financial corruption in the state institutions. Cluster analysis has been applied to each of these variables to understand the extent to which these agencies are close to other in each of the cases related to the administrative and financial corruption.
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