Background: Polycystic ovary syndrome (PCOS) has an unknown and complex etiology. It affects 5–10% of women in the reproductive age. Patients are known to have increased ovarian androgen production that is associated with decreased menses, hirsutism, and acne. Urinary tract stones (UTS) are a multifactorial disorder, with age and sex being known risk factors. Many PCOS patients are obese, and links between nephrolithiasis and obesity have been shown previously. Objectives: To identify the relation between PCOS and UTS considering the patients' body mass index (BMI). Methods: This is a cross-sectional study that enrolled 407 women aged 18-40 who attended the gynecology and obstetrics clinic at Al-Elwiya Maternity Teaching Hospital.

Background: Diabetes is defined by the World Health Organization as a metabolic disorder characterized by chronic hyperglycemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action, or both. Families are co-regulating systems in which the stresses and strains of one family member affect the well-being of another member of the family. Caregivers of children with chronic illness report experiencing more parental stress than parents of healthy children.

Objective: A descriptive cross-sectional study had been conducted in four centers of endocrine diseases in Baghdad city and data was collected by using self-administered questionnaire regarding qua

The design and implementation of an active router architecture that enables flexible network programmability based on so-called "user components" will be presents. This active router is designed to provide maximum flexibility for the development of future network functionality and services. The designed router concentrated mainly on the use of Windows Operating System, enhancing the Active Network Encapsulating Protocol (ANEP). Enhancing ANEP gains a service composition scheme which enables flexible programmability through integration of user components into the router's data path. Also an extended program that creates and then injects data packets into the network stack of the testing machine will be proposed, we will call this program

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

ان تقدير مسؤولية المحاسب في تصميم نظام المعلومات المحاسبي من منظور تاريخي سبقت استخدام الحاسوب كأداة معلوماتية للاعمال، لما له من رؤيا بالتطورات الرئيسية لنظام المعلومات والتي اهمها تحديد متطلبات مستخدمي المعلومات وتعيين مضمون وشكل مخرجات النظام من التقارير وتحديد مصادر البيانات وانتقاء القواعد المحاسبية الملائمة فضلاً عن الرقابة الضرورية لتكامل وفاعلية النظام.

ان النظم المحاسبية التقليدية غالبا

يرجع تاريخ الاصلاحات الادارية إلى سبعينات القرن الماضي  ،ولاسيما الندوة التي عقدت لبحث العوامل المؤثرة في انخفاض الانتاجية عام 1976، وعملية ترشيق الاجهزة الادارية للدولة عام 1987.

            ان بحثنا الموسوم (نظام المعلومات المحاسبية ودوره في عملية اتخاذ القرارات) يتم عرضه في فرعين مترابطين، هما:

• المحاسبة نظام معلومات.
• الادارة صانعة للقرار.<

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da