A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new approach for deriving the conventional estimator for the ridge parameter proposed by Hoerl and Kennard (1970) as well as  Bayesian estimator  are presented. A numerical example is studied in order to   compare the performance of these estimators.

     University Campuses, as any lively physical entity, is subject to continuous variation due to . growth, development and change. This reality covers the existing or futuristic additives or  additions, consecutively these changes may have a strong sensation of disorientation as a result of formatic changes in buildings, or in movement paths. And it epitomized the research problem to "the need for knowledge to clarify the impact of intellectual and executive policy in achieving coherence, functional and space organization of the elements of the university urban environment and in the stages of future growth and change,"  the search targeted "to highlight the study of constraction politics on campus Bmqomad

AZ Khalaf, M kassim Haidir, LK Jasim, Iraqi Journal of Science, 2012

Controlling cost in construction projects is an essential issue. This study investigates the most critical problems that cause weakness in cost control in Iraqi construction projects. The quantitative technique was used by conducting a survey directed to professionals who work on construction projects. One hundred and sixty-four questionnaire forms were distributed to private sector companies, government companies, and government institutions, and the responses were subjected to the required statistical analysis. The results indicate that the most influential factors are the weakness in keeping up with the use of modern concepts, methods, and technologies, the delay in receiving the amounts due for work done from the owner, fluctuat

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

    When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona