Background: Job satisfaction remains as an important concern for both employer and employee. A high-quality teaching staff is the cornerstone of a successful educational system. One step in developing a high quality faculty understands the factors associated with teaching quality and retention. One of these factors is job satisfaction, which has been studied widely by organizational researchers.Objectives: To evaluate the extent of job satisfaction of teaching staff working at AL-Kindy College of medicine and to identify some work-related factors associated with job satisfaction.Methods: A cross- sectional study was carried out. A convenient sample of 50 teaching staff, who had a teaching job at different scientific departments at AL-Kindy college of Medicine. The data was collected using a questionnaire form which includes information under three main headings: information related to the socio-demographic characteristic; the work motivators and the work environmentsResults: the study shows that 60% of the academic staff were generally satisfied with their job, the general satisfaction were more among those with age more than 50 years, males, singles, those with no children, and those living near their work place with the following percentage 68, 78, 87, 87 and 87, respectively. It also revealed that positive criticism, promotion, training, growth in work, increase income, new responsibilities, were the most motivators to work.Conclusions: Most of the academic staff were generally satisfied with their job. Most of the academic staff were satisfied to the studied work motivator and environment factors.
Physically based modeling approach has been widely developed in recent years for the simulation of dam failure process due to the lack of field data. This paper provides and describes a physically-based model depending on dimensional analysis and hydraulic simulation methods for estimating the maximum water level and the wave propagation time from breaching of field test dams. The field physical model has been constructed in Dabbah city to represent the collapse of the Roseires dam in Sudan. Five cases of a dam failure were studied to simulate water flood conditions by changing initial water height in the reservoir (0.8, 1.0, 1.2, 1.4 and 1.5 m respectively).The physical model working under five cases, case 5 had the greatest influence of t
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re
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This paper presents a stylistic analysis of two poems of well-known poets of the English literature, namely; E.E. Cummings and the Irish noble laureate Seamus Heaney. The researcher's attempt here is to approach Cummings’s poem “maggie and milly and molly and may” and Heaney’s “A Kite for Aibhín” from the stylistics’ point of view. The paper also analyzes the poems using the tools of linguistics with a view to make their meaning explicit.
It is worth noting that stylistics as a scientific discipline is really beneficial to those who are teaching and studyi
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Objective: Determine the effectiveness of the Nutrition Education Program upon the pregnant mothers'
nutritional knowledge.
Methodology: ٨ quazi-experimental study was carried out to determine the effectiveness of the nutrition
education program upon the pregnant mother's nutritional knowledge. A non-probability "purposive sample" of
(60) pregnant mother was selected from Al-bayaa' Primary Health Care Center in Baghdad City. These mothers
were divided into two equal groups; study group and control group. A questionnaire was developed as a tool of
data collection for the purpose of the study. A pilot study and follow-up was carried out to test the reliability and
validity of the questionnaire for the period of Octobe
Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio
In the present work advanced oxidation process, photo-Fenton (UV/H2O2/Fe+2) system, for the treatment of wastewater contaminated with oil was investigated. The reaction was influenced by the input concentration of hydrogen peroxide H2O2, the initial amount of the iron catalyst Fe+2, pH, temperature and the concentration of oil in the wastewater. The removal efficiency for the system UV/ H2O2/Fe+2 at the optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=3, temperature =30o C) for 1000mg/L load was found to be 72%.
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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