Performance measures are a central component of management control system, making good planning and control decisions requires information about how different subunits of organizations have performed. To be effective, performance measures (both financial and nonfinancial) must also motivate managers and employees at all levels of organization to strive to achieve organization goals.

To give aclear picture about performance must be used compound measure, that was best than single measure.

Altman model can be used as a compound performance measure that measures the performance by tied a sum of variables, due to make weight for every variable to reach for performance.

In this research, one of the nonlinear regression models is studied, which is BoxBOD, which is characterized by nonlinear parameters, as the difficulty of this model lies in estimating its parameters for being nonlinear, as its parameters were estimated by some traditional methods, namely the method of non-linear least squares and the greatest possible method and one of the methods of artificial intelligence, it is a genetic algorithm, as this algorithm was based on two types of functions, one of which is the function of the sum of squares of error and the second is the function of possibility. For comparison between the methods used in the research, the comparison scale was based on the average error squares, and for the purpose of data ge

The primary purpose of this paper is to introduce the, N-coprobabilistic normed space, coprobabilistic dual space of N-coprobabilistic normed space and give some facts that are related of them.

ان التقدم والحداثة التي تم ادخالها على النظام التعليمي والتربوي اثر بشكل كبير في العمليات التعليمية وطريقة عرض الموضوع وشرحه على الطلبة حيث اصبح الاعتماد الكبير في عملية التعلم هو كيفية التفاعل بين المتعلم والمادة المراد تعلمها واتاحة الفرصة الكافية للمتعلم للتعلم وإعطاءه الحرية والثقة بالنفس بغية تحقيق الهدف من التعلم .  وهنا تكمن مشكلة البحث  من خلال عمل الباحثة كتدريسية في كلية التربية البدنية وعلو

  Let R be an associative ring with identity and M a non – zero unitary R-module.In this paper we introduce the definition of purely co-Hopfian module, where an R-module M is said to be purely co-Hopfian if for any monomorphism f Ë› End (M), Imf is pure in M and we give  some properties of this kind of modules.

he concept of small monoform module was introduced by Hadi and Marhun, where a module U is called small monoform if for each non-zero submodule V of U and for every non-zero homomorphism f ∈ Hom R (V, U), implies that ker f is small submodule of V. In this paper the author dualizes this concept; she calls it co-small monoform module. Many fundamental properties of co-small monoform module are given. Partial characterization of co-small monoform module is established. Also, the author dualizes the concept of small quasi-Dedekind modules which given by Hadi and Ghawi. She show that co-small monoform is contained properly in the class of the dual of small quasi-Dedekind modules. Furthermore, some subclasses of co-small monoform are investiga

During this research accomplish some chemical modifications on the Poly for new modified polymers with Kimaaaúah qualities, physical and unexpected new applications that the first of these chemical modifications that was completed is the introduction of a poly styrene butadiene swash and then this group

تكمن أهمية البحث من الاستفادة من تمرينات الخاصة بمساعدة استعمال أي جهاز تدريبي مثل استعمال جهاز (Vertimax) فإِنَّ هذهِ التدريبات تساعد في تطوير التحمل الخاص وفقًا لما يتطور من قدرات بدنية باستعمال هذا الجهاز، ومن هنا برزت مشكلة البحث انه من المهم  للاعب ان يعمل على الروافع الجسم للحصول على اداء افضل في عملية الرمي والحصول على افضل انجاز لهذة الفعالية باستعمال جهاز تدريبي جديد حيث يسلط مقاومات متعددة في ان وا

In linear regression, an outlier is an observation with large residual.  In other words, it is an observation whose dependent-variable value is unusual given its values on the predictor variables. An outlier observation may indicate a data entry error or other problem.

An observation with an extreme value on a predictor variable is a point with high leverage. Leverage is a measure of how far an independent variable deviates from its mean. These leverage points can have an effect on the estimate of regression coefficients.

Robust estimation for regression parameters deals with cases that have very high leverage, and cases that are outliers. Robust estimation is essentially a