Binary mixtures of three heavy oil-stocks had been subjected to density measurments. The data had been aquired on the volumetric behaviour of these systems. The heavy oil-stocks used were of good varity, namely 40 stock , 60 stock, and 150 stock, 40 stock is the lightest one with the API gravity 33.7 while 60 stock is middle type and 150 stock is heavy one, with API gravity 27.7 and 23.8 respectively. Stocks with Kerosene or Xylene for non-ideal mixtures for which excess volume can be positive or  negative. Mixture of heavy-oil stocks with paraffinic spike (Kerosene) show negative excess volume. While, aromatic rings results a lower positive excess volume, as shown in Xylene when blending with 40 stock and 60 stock but a negati

The research aim is to identify the concept of fair value and its measurement approaches, shed light on the concept of fraud and its forms, motives, as well as how to identify fraud under the fair value method.

I have been using the program package SSPS statistical in the calculation of the research variables, and the research sample was a group of university professors and auditors working in the federal board of Supreme Audit. 

 The researcher has reached some conclusions, the most important; the lack of conclusive evidence about management's intent in adopting the use of fair value raises several doubts about the credibility of the statements prepared in under the fa

      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

The aim of this study is to use style programming goal and technical programming goal fuzzy to study assessing need annual accurately and correctly depending on the data and information about the quantity the actual use of medicines and medical supplies in all hospitals and health institutions during a certain period where they were taking the company public for the marketing of medicines and medical supplies sample for research. Programming model was built goal to this problem, which included (15) variable decision, (19) constraint and two objectives:

1 - rational exchange of budget allocated for medicines and supplies.
2 - ensure that the needs of patients of medicines and supplies needed to improve

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