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 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.
Background: Diabetic patients have been reported to be more susceptible to gingivitis and periodontitis than healthy subjects. Many intracellular enzymes like (alkaline phosphatase- (ALP), aspartate aminotransferase- (AST) and alanine aminotransferase- (ALT) that are released outside cells into the gingival crevicular fluid (GCF) and saliva after destruction of periodontal tissue during periodontitis. This study was conducted to determine the periodontal health status and the levels of salivary enzymes (ALP, AST and ALT) of the study and control groups and to correlate the levels of these enzymes with clinical periodontal parameters in each study group. Subjects, Materials and Methods: One hundred subjects were enrolled in the study, with a
... Show MoreThis 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
... Show MoreObjective: The study aims to assess the knowledge and practices of mothers with hemophilia children type - A - ,
socio-economic status and association between mother demographic information with their knowledge and practices
toward their children in Azadi Teaching Hospital in Kirkuk.
Methodology: Descriptive study no probability (purposive) sample. Selected Fifty-five of mothers having hemophilia
children, started from November 2012 to May 2013. Study was carried out in the Azadi teaching hospital in
Kirkuk. By using questionnaire which consists from five parts include demographic characteristics for mother and
children, socio-economic, Knowledge and practices data gathered, by direct interview with the mothers in the
The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
... Show More