The Banking Supervision of the most important functions of the Central Bank of Iraq, which he intended to have a strong banking system and a sound and competitive, and exercised control over the banks by inspection bodies to ensure their compliance with the laws, regulations and orders and instructions and the safety of their financial positions.

The research was aimed to release the concept of banking inspection, compliance and problems and obstacles faced by the inspectors, and monitors compliance and down to make recommendations.

Has been reached on a set of theoretical and practical conclusions, including: -

1-confirmed the statistical analysis of the answers to the research sample the importance of the role o

Transgenic plants offer advantages for the manufacture of recombinant proteins with terminal
mannose residues on their glycan chains. So plants are chosen as source of pharmaceutical products and for
the development of alternative expression systems to produce recombinant lysosomal enzymes. In the
present study the sequence of the natural cDNA encoding for the human lysosomal enzyme
glucocerebrosidase (GCD) was modified to enhance its expression in soybean plants. The glucocerebrosidase
gene signal peptide was substituted with that signal peptide for the Arabidopsis thaliana basic endochitinase
gene to support the co-translational translocation into the endoplasmic reticulum (ER), and the storage
vacuol

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

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

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

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Low-temperature stratification, high-volumetric storage capacity, and less-complicated material processing make phase-changing materials (PCMs) very suitable candidates for solar energy storage applications. However, their poor heat diffusivities and suboptimal containment designs severely limit their decent storage capabilities. In these systems, the arrangement of tubes conveying the heat transport fluid (HTF) plays a crucial role in heat communication between the PCM and HTF during phase transition. This study investigates a helical coil tube-and-shell thermal storage system integrated with a novel central return tube to enhance heat transfer effectiveness. Three-dimensional computational fluid dynamics simulations compare the proposed d