The aim of this study was to identify the rate of return of the stock through the financial information disclosed by the financial statements of companies both services and insurance included in Iraqi market for securities . The study used a descriptive statistical methods and the correlation matrix for the independent factors , in addition to a regression model for data analysis and hypothesis . Model included a number of independent variables , which was measured in the size of company (sales or revenue) , and the leverage , in addition to the structure of assets and the book value of owners' equity in the company , as well as the general price index .Based on the data of (11)companies and for three years, showed the result
... Show MoreThe research aimed to identify the level of reality of administrative values of sports activities in the Faculties of the university of Baghdad from the point of view of the leaders and those related to the divisions and units of student's activities and the case study method was adopted from the descriptive approach.
An experiment was conducted to study the effect of the sprayer type according to the source of power and the size of the spray nozzle concerning the quality of the spray produced and fuel consumption.Two types of sprayers were used: a conventional boom sprayer (S1) and a modified (electrified) boom sprayer (S2), along with three sizes of the XR TeeJet 110 spray nozzle (N). The following technical performance indicators were examined: Density of coverage (drops/cm2) using ImageJ software, a 600dpi business card scanner, specifically the ScanShell 800N by CSSN, Inc, and water-sensitive paper (WSP), rate of spray nozzles discharge (ml/min), and fuel consumption (liters/hectare) using a c
The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg
... Show MoreSignification with its different aspects constitutes various aesthetic pictures for human and nature creations over different periods of time. It was a focal around which logical thinking loops on the interpretation level of the signification movement according to its structural context expresses its hidden entities with which a human being deals according to two symmetrical levels while interpreting to attain meaning. Sense was the first passing window for the picture of signification which thought deals with. While trying to decode it and because art in general and theatre in particular are considered as the basis of creating signification through its visual and aural elements, so it was necessary to consider one of the elements of cre
... Show MoreThe aim of the present work, was measuring of uranium concentrations in 25 soil samples from five locations of Al-Kut city. The samples taken from different depths ranged from soil surface to 60cm step 15 cm, for this measurement of uranium concentrations .The most widely used technique SSNTDs was chosen to be the measurement technique. Results showed that the higher concentrations were in Hai Al- Kafaat which recorded 1.49 ± 0.054 ppm . The uranium content in soil samples were less than permissible limit of UNSCEAR(11.7ppm).
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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