Since there is no market for bond issuance by companies in the Iraqi market and the difficulty of borrowing, companies must resort to proprietary financing to finance their investments. However, in the framework of the literature of financial management, the type of financing used by the company sends signals to investors and therefore reflected on the market value. Therefore, the problem of the study revolves around the variables of the study (Equity financing within the framework the signal theory, price of common stock in the Iraqi market).     

The study aims to verify the impact of the capital increase through the issuance of new stock on the price of

The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.

The purchase of a home and access to housing is one of the most important requirements for the life of the individual and the stability of living and the development of the prices of houses in general and in Baghdad in particular affected by several factors, including the basic area of the house, the age of the house, the neighborhood in which the housing is available and the basic services, Where the statistical model SSM model was used to model house prices over a period of time from 2000 to 2018 and forecast until 2025 The research is concerned with enhancing the importance of this model and describing it as a standard and important compared to the models used in the analysis of time series after obtaining the

Abstract The Object of the study aims to identify the effectiveness of using the 7E’s learning cycle to learn movement chains on uneven bars, for this purpose, we used the method SPSS. On a sample composed (20) students on collage of physical education at the university of Baghdad Chosen as two groups experimental and control group (10) student for each group, and for data collection, we used SPSS After collecting the results and having treated them statistically, we conclude the use 7E’s learning cycle has achieved remarkable positive progress, but it has diverged between to methods, On this basis, the study recommended the necessity of applying 7E’s learning cycle strategy in learning the movement chain on uneven bar

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F