The aim of the current research is to identify the level of organizational culture among the headmasters and teachers of intermediate and secondary schools in Arar city. It also aims to identify the effect of job variables, qualifications, educational stage, and years of experience on the level of organizational culture and its domains. The research sample consisted of 62 participants divided into 7 headmasters and 55 teachers. The researcher used the questionnaire of the organizational culture. The researcher used also statistical methods such as mean, standard deviation, t-test, and One way ANOVA. The results revealed that the level of organizational culture and its four domains were high, and there was no effect of the variables (teac

Background: Economic Globalization affects work condition by increasing work stress. Chronic work stress ended with burnout syndrome.

Objectives: To estimate the prevalence of burnout syndrome and the association of job title, and violence with it among physicians in Baghdad, and to assess the burnout syndrome at patient and work levels by structured interviews.

Subjects and Methods: A cross section study was conducted on Physicians in Baghdad. Sampling was a multistage, stratified sampling to control the confounders in the design phase. A mixed qualitative and quantitative

Background: Economic Globalization affects work condition by increasing work stress. Chronic work stress ended with burnout syndrome. Objectives: To estimate the prevalence of burnout syndrome and the association of job title, and violence with it among physicians in Baghdad, and to assess the burnout syndrome at patient and work levels by structured interviews. Subjects and Methods: A cross section study was conducted on Physicians in Baghdad. Sampling was a multistage, stratified sampling to control the confounders in the design phase. A mixed qualitative and quantitative approach (triangulation) was used. Quantitative method used self-administered questionnaires of Maslach Burn out Inventory. Qualitative approach used an open-end

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Two field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

In this study, the radon gas concentration as well as the annual effective dose in leaves of the Malvasylvestris (Khabbaz) plant used in the traditional treatment and as food in Iraq, for this, it is necessary to evaluate the concentrations radon gas, which were measured using solid state nuclear track detectors (SSNTDs) CR-39 technique.  The  concentration and annual effective dose in samples were collected from Baghdad city ranged from minimum to maximum value 15.815 , 0.498 , 54.445 , 1.717  respectively, while the values of  concentration and annual effective dose in a sample collected from Karbala are 15.297 ,0.482 . These values of  concentration and annual effective dose less were compared with th