This research aims at studying and analyzing the creative research thinking of the educational staffs in private universities and colleges, and also the role of incentives, in its materialistic and moral sides in the development of such thinking and the pack of restraints which cause decline in interest level of the scientificresearch, and its weak role in the development of universities in Iraq, despite the interest of the Ministry of Higher Education and Scientific Research in Iraq in scientific research as part ofits academic and humanitarian targets.Based on study and analysis, and the using if some of statistical methods such as the Alpha Chronobaghcoefficient and the (T. Test)(F. Test),the research reached a number of conclusions.

Purpose: The concept of complete street is one of the modern trends concerned with diversifying means of transportation and reducing the disadvantages of mechanical transportation modes. This paper discusses the role of complete streets can play in developing the urban environment in the Alyarmok District of Baghdad.   Method/design/approach: The linear regression method used to analyze the opinions of 100 respondents surveyed in the study area in order to find the relationship between the urban environment and the complete street elements.   Theoretical framework: The Modern trends in urban planning aim to find alternatives to the policies of traditional transportation planning that focus on vehicular mobi

Background: In the past, an association between Tuberculosis (TB) and Diabetes Mellitus (DM) was widely accepted, today the potential public health and clinical importance of this relationship seems to be largely ignored. The national clinical and policy guidance in the UK on the central of TB, for example, does not consider the relationship with DM.Objectives: To determine the risk of association between diabetes mellitus and pulmonary TB.Methods: A retrospective study conducted in Ibn Zuhr hospital for chest diseases from Jan 2008 – sep 2010 , included in the study 402 patients with TB divided into diabetic & non diabetic, 96 (23.8%) were diabetic while other 306 were TB not diabetic.Results: Risk of TB among DM patients were cle

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri