In light of today's business world, who faces challenges and intense competition as a result of the rapid evolution of technical and informational, organizations had to respond to variables through the adoption of modern management techniques that reduce the effects of risks and activating the role of the internal control system in order to contribute to the early detection of risks and reduce the negative results expected .The research is to address the problem faced by organizations which still follow the traditional methods in the control activities, and the lack of knowledge of the management and their staff of the importance of the existence of risk management and internal control system takes into account these risks, and the limit

Objective: to assess the risk factors of coronary artery disease patients.
Methodology: A non-probability (purposive) sample of (100) patients. The study population consisted of
a sample of adults from both genders whose ages were 30 years and more, and was newly diagnosed as
having CAD by coronary angiography in the cardiac catheterization unit of An Nasiriyah heart center.
Results: The result of the study showed that the most common modifiable risk factors were low HDL-C
levels (58%), smoking (53%), hypertension (46%), diabetes mellitus (34%), obesity (30%), high
triglycerides (19%), hypercholesterolemia (17%), and high LDLC (14%). All these factors were positively
and significantly associated with the development

The research aims to identify the reality of the management strategy followed in the treatment of solid waste in the city of Baquba, and what strategies are used to treat solid waste, and the extent of the application of these strategies, through personal interviews with leading cadres in the Directorate of Baquba Municipality, their assistants and heads of departments, they numbered (55) Individuals. The descriptive method was adopted through a questionnaire prepared to measure the extent of the implementation of the strategy of solid waste management in the city of Baquba and using statistical tools including (arithmetic mean, standard deviation, relative importance, the gap). The research reac

Two field experimسents were conducted in one of the fields of the Agriculture Division of Ain Al-Tamr /Holy Karbala Governorate at two sites of different textures during the agricultural season 2020/2021. The first site has sandy loam texture (gypsum soils). The second site has loamy sand texture (calcareous soils). The factors of the study included: The first factor included two types of soil, gypsum and calcareous soil. The second factor is the tillage systems (no-tillage, spring spike harrows, disc harrows, and mold board plow). The experiment was designed in the two study sites according to the RCBD with three replications. The Valley type center pivot irrigation system was evaluated before planting, three speeds, 30, 50 and 100% of th

Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Acinetobacter baumannii received attention for its multi-drug resistant associated with many severe infections and outbreaks in clinical environment. The aims of the study are to investigate the antibiotic susceptibility profile of clinically isolated A. baumannii, biofilm production, and the efficiency of Low Frequency Ultrasound (LFU) and honey to attenuate biofilm production. A total of 100 samples were taken from different sources from Baghdad hospitals. The susceptibility patterns revealed the percentage of pan drug resistant (PDR) isolates were 1.5 %, 72.7 % were extended drug resistant (XDR), 16.7 % were multidrug resistant (MDR), and 9.1 % were non MDR and sensitive to most antibiotics used. The ability to form