Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

This paper aims to identify the approaches used in assessment the credit applications by Iraqi banks, as well as which approach is most used. It also attempted to link these approaches with reduction of credit default and banks’ efficiency particularly for the Gulf Commercial Bank. The paper found that the Gulf Bank widely relies on the method of Judgment Approach for assessment the credit applications in order to select the best of them with low risk of default. In addition, the paper found that the method of Judgment Approach was very important for the Gulf Bank and it driven in reduction the ratio of credit default as percentage of total credit. However, it is important to say that the adoption of statistical approaches for

One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried

دُرِست العوامل المؤثرة في عدد ساعات تجهيز الكهرباء في مدينة بغداد، وتكونت عينة الدراسة من (365) مشاهدة يومية لعام 2018، وتمثلت بستة متغيرات استعملت في الدراسة. كان الهدف الرئيس هو دراسة العلاقة بين هذه المتغيرات، وتقدير تأثيرات المتغيرات التنبؤية في المتغير التابع (عدد ساعات تجهيز الكهرباء في مدينة بغداد). ولتحقيق ذلك استعملت نمذجة المعادلات الهيكلية/ تحليل المسار وبرنامج AMOS

The research aims to measure the impact of the quality of the audit on the Earnings Quality, for a sample of private joint stock companies listed on the Iraq Stock Exchange, as the research sample included (14) private and listed joint stock companies in issuing their financial statements for the period from (2010-2018), as well as companies The audit offices in charge of auditing these companies, which number (18) companies or an audit office, and the research relied on two main models for measurement, as the first model reflects the assumed relationship between independent variables represented in the characteristics of external audit quality and measuring the extent of its impact on the dependent variable represented in the Ea

Background: To evaluate the bony supports of the teeth adjacent to the area of cleft in patient with unilateral cleft lip and palate and to compare these measurements with the measurements of the same teeth in non-cleft side by using CBCT. Materials and methods: The CBCT scans of 30 patients having cleft lip( unilateral) and palate(unilateral), were analyzed and the measurements of the alveolar bony support for teeth that are adjacent to the cleft area were measured with those teeth located on opposite side (non- clef) side. For each tooth, the measurements will taken for the distance between the( cementoenamel junction) (CEJ) and the bony crest (AC) at the( buccal area) was measured and the thickness of the buccal plate At zero, one, tw

Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-

Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit.  The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al-Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor