Organizational learning is one of the most important means of human resource development in organizations, but most of the organizations, especially public ones do not realize the importance of organizational learning enough, and estimated his role accurately in building intellectual capital, the resource competitive importantly for organizations of the third millennium and who suffers is other end of lack of understanding of its meaning and how to prove its presence and measured in public organizations, so there is the need for this research, which aims to investigate the effect of organizational learning its processes (knowledge acquisition, Information transfer, Interpreting the information, Organizational me

Resulted in scientific and technological developments to the emergence of changes in the educational process and methods of teaching modern formats commensurate with the level of mental retardation. Which called for educational institutions, including the University of Baghdad / College of Fine Arts to urge and guide researchers to study and follow-up of recent developments in the educational process in order to develop in the fine arts in general and technical education in particular being play an important role in achieving educational goals. The educational methods of modern educational require effort-intensive and advanced for the development of technical skills among students, and thus worked researcher to employ computer technology

Despite the significant increase in public spending in Iraq, it was not directed toward the important sectors that have an important role in correcting the productive structure. Rather, most of the public expenditure was going to cover the required imports, or to face shocks, whether security or health, and this caused a continuous decrease in the volume of Iraq's exports of goods and services, as the aim of the study was to review the importance of public debt and its impact on the trade balance, as well as to know the economic policies that can contribute to strengthening the trade balance, as the study proved through the (ARDL) model that there is a direct relationship between the domestic debt and the net trade balance, and an invers

ABSTRACT:

              Interest rates are one of the important aspects that affect the banking business directly, which is characterized by unstable dynamic dynamics, which must be viewed on a daily and continuous basis through the macroeconomic view, which directly affects the bank’s income realized from loans as interest received or interest paid on its deposits as an expense. Hence the earnings per share. The relationship between interest rates and between net income and earnings per share was measured and a correlation was found between them, and then the effect between them was measured using regression equations and they were applied and th

فعالية الوثب العالي تمتاز بالتكرار والممارسة لمراحل التسلسل الحركي بالتكرارات الصحيحة المصحوبة بالتغذية الراجعة من اجل الوصول إلى اداء افضل, ومن خلال عمل الباحثتان كونها تدريسية لمادة الساحة والميدان لاحظت ضعفا في مستوى الأداء الفني عند الطالبات في ضبط مراحل التسلسل الحركي الكامل لفعالية الوثب العالي ، لذا ارتأت الباحثتان اعداد تمرينات خاصة باستخدام أساليب التنافس حمل المتعلم على مضاعفة جهده لينافس ذاته

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

This study deals with the absence of state control over the whole of the Syrian geography in creating an environment conducive to the emergence of a new force represented by armed groups and organizations that point to fundamental changes in the conflict and to transform competition for control over the land into a struggle for influence. Which in itself represents the prospects of change in the Syrian scene, and that understanding their interests requires shedding light on the extent of the continuation of this competition and the conflict on land and expansion at the expense of the other, and thus contribute to complicate the Syrian scene, especially after attempts to bite Of land and annexation to each party's areas of influence, espe

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

The purpose of this study is to investigate the effect of credit risk indicators on the Arab Gulf countries' banks Profitability over the period of 2015 to 2017.  The banking credit risk was calculated using non-performing loans ratio affecting banks profitability indicators like net income and by using fixed effect and random effect model analyses, the study found that increasing in non-performing loans ratio will decrease the net income in gulf banks, the study also found that personal loans represent the largest share of loans granted in gulf banks. Also, the study recommends the importance of developing the capabilities of credit departments in commercial banks in dealing with bad loans, and studying the financial statem

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A