This paper studies the investment project evaluation under the condition of uncertainty. Evaluation of investment project under risk and uncertainty is possible to be carried out through application of various methods and techniques. The best known methods are : Risk-adjusted discount rate , certainty equivalent method , Sensitivity analysis and Simulation method The objective of this study is using the sensitivity analysis in evaluation Glass Bottles project  in Anbar province under the condition of risk and uncertainty.

After applying sensitivity analysis we found that the glass bottles project  sensitive to the following factors (cash flow, the cost of investment, and the pro

The importance of studying the political trends of caricature in Al-Sharq Al-Awsat Newspaper comes from the importance of this magical and satirical journalistic art, as it addresses various trends with satirical criticism that exposes the negative sides and affects the reader’s consciousness in a way or another by contributing to the public opinion about these issues and topics that affect people's lives and their future. Therefore, this art is no less important than the other arts, on the contrary, it complements the other arts and also contributes to the importance of Journalism. Also, the choice of Al-Sharq Al-Awsat Newspaper as being one of the most widely circulated and prominent Arab newspapers, t

The research aims to detect the problems of educational reality faced by university professors and identify statistically significant differences in the academic problems of university instructors. It has adopted an analytical descriptive research approach to achieve research objectives and identifies the study community with professors of public and private universities. A random sample of 250 instructors was selected for the purpose of applying the questionnaire to them, knowing the academic problems encountered in the course of their work at universities, and adopting appropriate statistical means to process and analyze the data. The research concluded with a set of results, including that all fields (infrastructure, admission of

The molluscum contagiosum virus (MCV) is a dermatotropic poxvirus. The causative agent of molluscum contagiosum (MC) is nonlethal, common and worldwide. Additionally, little inflammation is associated with MC papules. The present study aims to evaluate the immune status of MC patients by measuring the level of immunoglobulins IgG and IgM by using the radial immune diffusion assay (RIA) and the level of interleukin 18 receptor 1 (IL-18R1) by the Enzyme-linked immunosorbent assay (ELISA).The study is conducted during November 2013 to April, 2014 in outpatient clinic of Baquba Teaching Hospital. There are 75 patients, diagnosed with clinical lesions of MCV on different areas of the body, whose age is ranged between 2-50 years including 40(53.

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

     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