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

We have studied some types of ideals in a KU-semigroup by using the concept of a bipolar fuzzy set. Bipolar fuzzy S-ideals and bipolar fuzzy k-ideals are introduced, and some properties are investigated. Also, some relations between a bipolar fuzzy k-ideal and k-ideal are discussed. Moreover, a bipolar fuzzy k-ideal under homomorphism and the product of two bipolar fuzzy k-ideals are studied.

 

    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 research deals with the role of quantitative (indirect) tools of monetary policy that used by the Central Bank of Iraq in order to control and manage the size of the money supply that intermediate goal through which monetary policy is able to achieve its final goals, foremost among which is to reduce inflation and raise the value of the local currency in front of foreign currency rates. The research is based on a major hypothesis stating that quantitative tools have a direct and strong influence on the money supply, especially under the circumstances of the shift towards a market economy. There has been a branching relationship with this statistically significant relationship between the money supply and the quantitative tools used

Abstract :

       The research aims to diagnose some of the negative phenomena
 ( Counterfiting , Pettifogging , Embezzlement ) that have been detected over the past ( 2010 – 2014 ), a fixed-term part of the national strategy for the fight against corruption launched by the Joint Council for the fight against corruption in Iraq and measuring the application of government control according to the American standard GAO standards and identifying the potential for the application of those standards gap. It has been collecting data and information of special issues of corruption reports and meeting with (42) employees and the use of a checklist has been prepared for thi

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In this paper, Min-Max composition fuzzy relation equation are studied. This study is a generalization of the works of Ohsato and Sekigushi. The conditions for the existence of solutions are studied, then the resolution of equations is discussed.

In this paper, we apply the notion of a bipolar fuzzy n-fold KU-ideal of KU- algebras. We introduce the concept of a bipolar fuzzy n-fold KU-ideal and investigate several properties. Also, we give relations between a bipolar fuzzy n- fold KU-ideal and n-fold KU-ideal. The image and the pre-image of bipolar fuzzy n-fold KU-ideals in KU-algebras are defined and how the image and the pre- image of bipolar fuzzy n-fold KU-ideals in KU-algebras become bipolar fuzzy n- fold KU-ideals are studied. Moreover, the product of bipolar fuzzy n-fold KU- ideals in Cartesian product KU-algebras is given.