The governmental projects are considers the prevailing in Iraq, as most of the projects implemented by the Government, the major role played by governmental projects in the provision of services to citizens and improve the economic situation in the country in general, in addition to the huge number of these projects implemented by the governmental organizations and the large failure rates of it , and because of the fact that these projects are stumbled  before they reach the stage of failure, The aim of this research to identify the main factors for the stumble projects in addition to identifying the most influential factor on the causes and consequences of it , like (cost overruns , time overruns , delay and scope

In this paper, An application of non-additive measures for re-evaluating the degree of importance of some student failure reasons has been discussed. We apply non-additive fuzzy integral model (Sugeno, Shilkret and Choquet) integrals for some expected factors which effect student examination performance for different students' cases.

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

: Cigarette smoking is a lifestyle behavior that causes significant adverse health effects. Cigarette smoke contains chemicals, many of which are lead to the production of reactive oxygen species (ROS), which can lead to apoptosis and autophagy. To estimate the association of Cigarette smoking with the autophagy and immunity, technology of real time polymerase chain reaction (RTPCR) for gene expression of (LC3A, LC3B, LC3C, myd88) was used. Enzyme-linked immunosorbent assay (ELISA) technique was utilized to measurement the amount of TNF-α protein. The ratios of LC3A/LC3B and LC3B/LC3C were calculated to estimate the autophagy flux. The results indicate the expression of LC3B, LC3C and Myd88 genes in smokers is increased significantly (p

To determine the association between cigarette smoking and oxidative stress, a study was conducted in the period from January 2020 to April 2021, at College of Medicine, Al-Nahrain University, Baghdad, Iraq. The Enzyme-linked immunosorbent assay (ELISA) technique was utilized for measurement the antioxidant enzymes including: Glutathione superoxide (GPX) and catalase (CAT) and the biomarker of lipid peroxidation Malondialdehyde (MDA). Also, the gene expression of Nrf2 and HO-1were determined by using RT-PCR technique. The results indicate lower level of both GPX and CAT (p ≤ 0.001) in smokers compared with non-smokers. While the result of MDA indicate higher level in smokers (p≤0.001) compared with nonsmokers. The Nrf2 and HO-1 gene exp