Abstract
Objective: To assess pregnant women Knowledge toward Urinary Tract Infection at Kirkuk City.

Methodology: A descriptive and analytical study was conducted from 1st of November 2013 and up to the 19 th of August 2014 in five typical primary health care centers at Kirkuk City. A Probability (randomly sample) was used to select the sample of 180 women aged (15-44) years. A questionnaire format was used as a tool for data collection , content validity of the questionnaire achieved through reviewing it by (24) experts in numerous scientific fields and reliability of the questionnaire was determined through a pilot study. Descriptive and inferential statistics were used to analyze the data.

Resul

Abstract

Objective(s): To evaluate the level of Psychological Empowerment among Nurses as perceived by their Point of View, and identify the differences in nurses' Psychological Empowerment with regard to age, gender, graduation level, and years of work employment. 

Methodology: A descriptive analytic design was conducted on nurses in Psycho-social health Units in Primary Health Care Centers in Kirkuk Governorate, to achieve the objectives of the study. A convenient (non-probability) sample of 84 nurses was selected. The data collected through self-report method for the period from 25^th August to 10^th October 2022. The questionnaire was adopted

The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.