The aim of this research is to know how business organizations achieve competitive advantage ,and make it sustainable through constructing a green strategy ( friend to environment) which is reflected on sustaining their competitive advantages .The problem of this study is presented through trying to answer many thoughtful questions, the most important of them are: 

1-Can business organizations today make green strategies supporting their competitive advantage?

2-Is there a framework or mechanism could be depended on by business organizations to manage strategic risks of losing their competit

 In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

    يعد الدين من أكثر المتغيرات تأثيرا في سلوك البشر بصورة عامة ، وفي شخصياتهم وصحتهم النفسية بصورة خاصة .

    ولأحداث الحياة والأزمات والشدائد تأثيرها الكبير في هذا المتغير وفي مدى تمسك الناس بقيمهم الدينية .

    وفي العراق ، لا تخفى علينا المآسي والأزمات والشدائد التي مر ويمر بها البلد مما قد يزعزع ثقة الناس بمعتقداتهم وقيمهم ، ومن جانب آخر فان دخول المحت

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

The correct and sincere process of socialization is working on appropriate social climate in
which this process is the provision, and the climate is achieved in the presence of a positive
environment free of negatives and contradictions, but when there is a socialization processes
inadequate and contradictory was not based on the principles of punishment and reward nor a
balance between methods soft and intensity of treatment and interaction with small and
adolescent does not require intensive social care formulas do not create the conditions
essential items required by the successful and effective socialization, the young and the young
people who are going through in such Altanisah and educational operations will be