Indicative supervision represents the comparison between direct intervention (acquisition, nationalism) and participation through rules.

The last financial crisis reflected our needs for different approaches of supervision consist with our goals, but the crisis reveals also number of sounds requested and pressured toward direct control (Intervention via forces) through government acquisition and nationalization.

This study attempts to deal with crisis lessons, in the field of choice between indicative and direct supervision which government authorities used to reduce the bad effect on the monetary firms.

Iraqi banks suffered from high levels of direct co

The goal of this paper is to design a robust controller for controlling a pendulum
system. The control of nonlinear systems is a common problem that is facing the researchers in control systems design. The Sliding Mode Controller (SMC) is the best solution for controlling a nonlinear system. The classical SMC consists from two phases. The first phase is the reaching phase and the second is the sliding phase. The SMC suffers from the chattering phenomenon which is considered as a severe problem and undesirable property. It is a zigzag motion along the switching surface. In this paper, the chattering is reduced by using a saturation function instead of sign function. In spite of SMC is a good method for controlling a nonlinear system b

العقيدة الدينية وأثرها على منهج التفكير السياسي للولايات المتحدة الامريكية

المجال الحيوي للاقتصاد الايراني وانعكاساته على اقتصاديات دول الخليج العربي

The research aims to identify the correlation between self-reliance and human relationship of kindergartens’ teachers. Total of (120) kindergarten teachers at Baghdad city. To collect needed data, two scales were administered to the research sample consisted of (25) items of each scale with (five) alternatives. The results revealed that teachers have good level of self-reliance and human relationship. There is a positive correlation between self-reliance and human relationship.

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

أولاً: مشكلة البحث:

على الرغم من أن كل شخص هو كائن متفرد بحد ذاته ، إلا أن هناك تشابهات مشتركة بين كثير من الناس ، وتشكل هذه التشابهات أنماطآ شخصية يهدف علم النفس إلى دراستها وفهمها.

وقد حاول علماء النفس والمنظرون في مجال الشخصية بناء أنظمة نظرية لتغطية التباين الواسع بين الأفراد في السلوك ضمن المواقف المختلفة. وهدفت جهودهم إلى فهم الدافعية البشرية ، والسلوك عن طريق عملية النمو

In this paper, a modified derivation has been introduced to analyze the construction of C-space. The profit from using C-space is to make the process of path planning more safety and easer. After getting the C-space construction and map for two-link planar robot arm, which include all the possible situations of collision between robot parts and obstacle(s), the A* algorithm, which is usually used to find a heuristic path on Cartesian W-space, has been used to find a heuristic path on C-space map. Several modifications are needed to apply the methodology for a manipulator with degrees of freedom more than two. The results of C-space map, which are derived by the modified analysis, prove the accuracy of the overall C-space mapping and cons

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre