In this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most

The agricultural sector suffers from many risks and natural disasters, such as droughts and heavy rains that cause floods, as well as hail and agricultural pests, etc., that threaten agricultural activity and reduce it, which leads to the failure of farmers and peasants for fear of being subjected to continuous losses. Nevertheless, we notice almost complete reluctance to move towards agricultural insurance, due to the dependence of farmers on the government, which adopts the principle of compensation instead of agricultural insurance when natural disasters happen despite the difficulties and financial hardship as well as the suspicion of corruption that haunt the compensation process and this represents the most important problem for resea

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

Objective: study aims to identify the diabetes type2 clients self management skills toward dietary pattern
, and find out the relationship between variables which are (Age, gender, educational level, duration of DM
diagnosis, and monthly income) with diabetes type 2 clients self management skills toward dietary pattern
Methodology: descriptive study was carried out through the present investigation from January 2nd
2011to September 2nd 2011 in order to achieve the objectives of the present study. A non probability
(purposive) sample, (200) cases which consists of clients who were attending Al-Nasiriyha diabetic center.
Including (118) males and (82) females. The data were collected by utilization of the study instrument

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

 An accurate and sensitive spectrophotometric method has been developed for the determination of carbamazepine (CRN.) in pure and dosage forms. The method is based on the oxidation of 2,4-dinitrophenylhydrazine (2,4-DNPHz) by potassium periodate than coupling with carbamazepine (CRN.) in alkaline medium to form a stable yellowish brown colored water-soluble dye with a maximum absorption at 485 nm. The variables that affect the completion of reaction have been carefully optimized. Beer’s law is obeyed over the concentration range of     (4-50 μg.mL-1) with molar absorptivity of (6.7335×103 L.mol-1.cm1). The limit of detection was (0.1052 μg.mL-1) and Sandell’s sensitivity value was 0.0350 μg.cm-2.

A new, simple and sensitive spectrophotometric method was described for the determination of famotidine (FAM) as a pure material and in pharmaceutical formulation. This method was based on diazotization and coupling reaction between famotidine and diazotized solution of metochlopramide hydrochloride (DMPH) in the presence of phosphate buffer solution to give a compound of azo dye having orange color soluble in water with high absorptivity at a wave length of 478 nm. The data shows that FAM and DMPH combine in the molar ratio of 1:1 at PH 7.0 .The method obeys Beer's law over concentration range of 1-40 ?g.ml-1 of famotidine with a correlation coefficient of 0.9955 and a detection limit of 0.10 ?g.ml-1. The apparent molar absorptivity re