The Ratawi Oil Field (ROF) is one of Iraq's most important oil fields because of its significant economic oil reserves. The major oil reserves of ROF are in the Mishrif Formation. The main objective of this paper is to assess the petrophysical properties, lithology identification, and hydrocarbon potential of the Mishrif Formation using interpreting data from five open-hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. Understanding reservoir properties allows for a more accurate assessment of recoverable oil reserves. The rock type (limestone) and permeability variations help tailor oil extraction methods, extraction methods and improving recovery techniques. The petrophysical properties were calculated using Interactive Petroph

Bioremoval of chromium from wastewater of tannery factory in Iraq was studied. The bacteria Proteus vulgaris 7E showed an enhanced capability in biosorping chromium when its concentration increased in the solution, reaching a maximum of 476,7 mg/ ml out of 492 mg/ ml under optimum conditions at pH 6 and 50°C at one hour contact time and biomass of 1 mg/ml. The present results showed that dead cells of P. vulgaris 7E biosorbed 87.41 mg/ml of chromium in comparison with91.18 mg/ml of chromium biosorbed by living cells, this indicates the insignificant effect of physiological state of cells. It was found that the above biosorption is physico-chemical process depends upon electrostatic attraction forces. The results has illustrated that the

Began the process of re-engineering processes in the private sector as a way to assist organizations in re-thinking how to run the business in order to improve production processes and reduce operational cost, to get to compete on a global level. That was a major restructuring by further evolution in the use of technology to support innovative operations.

 Entered the technology in all areas of life and different regulations, This led to use as a change in all aspects The companies achieved success and progress today through the use of resources so as to ensure the wishes of the customers and their needs, and the requirements of the market primarily, Which is reflected on the basis of building strate

 The deficit budget, one of the results of increased public spending for their revenues due to the economic pressures imposed by the interest of the economies of those countries from the need to increase government spending in order to revitalize the national economy and accelerate economic growth rates and provide employment to the growing levels of unemployment in those countries opportunities and what is required to address the current debt crisis (borrowing), which has become a big burden on the governments and the need to move towards the application of austerity spending and tax increases, which inevitably forced those countries will be reflected reduced spending on basic aspects of life and their peoples, particularly earners

The aim of this paper is adopted to give an approximate solution for advection dispersion equation of time fractional order derivative by using the Chebyshev wavelets-Galerkin Method . The Chebyshev wavelet and Galerkin method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are described based on the Caputo sense. Illustrative examples are included to demonstrate the validity and applicability of the proposed technique.

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

لقد كان حرص المؤلف على إصدار هذا الكتاب نابعا ً من قناعة تامة بأن مجال التقويم والقياس بحاجة إلى كتاب علمي حديث يتناول عرض أدوات الاختبار والقياس والمتمثلة بالصدق والثبات ويتسم بالوضوح في التعبير عن المفاهيم والمصطلحات والأنواع لكل منها ليكون وسيلة مبسطة بأيدي الأساتذة والباحثين وطلبتي الدراسات العليا الماجستير والدكتوراه لإستخراج صدق وثبات الاختبارات والمقاييس بطرق إحصائية متقدمة من خلال إستخدام البرنا

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob