The -mixing of  - transition in Er 168 populated in  Er(n,n ) Er 168 168  reaction is calculated in the present work by using a2- ratio method. This method has used in previou studies [4, 5, 6, 7] in case that the second transition is pure or for that transition which can be considered as pure only, but in one work we applied this method for two cases, in the first one for pure transition and in the 2nd one for non pure transitions. We take into accunt the experimental a2- coefficient for previous works and -values for one transition only [1]. The results obtained are, in general, in agood agreement within associated errors, with those reported previously [1], the discrepancies that occur are due to in

This paper presents a hierarchical two-stage outdoor scene classification method using multi-classes of Support Vector Machine (SVM). In this proposed method, the gist feature of all the images in the database is extracted first to obtain the feature vectors. The image of database is classified into eight outdoor scenes classes, four manmade scenes and four natural scenes. Second, a hierarchical classification is applied, where the first stage classifies all manmade scene classes against all natural scene classes, while the second stage of a hierarchical classification classifies the outputs of first stage into either one of the four manmade scene classes or natural scene classes. Binary SVM and multi-classes SVMs are employed in the fir

The current research aims at:
Students know the level of the fourth phase of the Arabic language
departments in colleges of education in the discovery of the basic error of
grammar by answering the following questions: 

1. What level of students in the fourth stage of the Arabic language
departments in colleges of education in the discovery of the basic grammar
error?
2. Is there a statistically significant difference between male and female
students in the discovery of the wrong grammar?
3. What proposals to address the weakness of students in the grammar error
detection from the viewpoint of the teaching staff and Altdriciat?
Determined by the current search by:
1. Students in the fourth st

Massive multiple-input multiple-output (massive-MIMO) is considered as the key technology to meet the huge demands of data rates in the future wireless communications networks. However, for massive-MIMO systems to realize their maximum potential gain, sufficiently accurate downlink (DL) channel state information (CSI) with low overhead to meet the short coherence time (CT) is required. Therefore, this article aims to overcome the technical challenge of DL CSI estimation in a frequency-division-duplex (FDD) massive-MIMO with short CT considering five different physical correlation models. To this end, the statistical structure of the massive-MIMO channel, which is captured by the physical correlation is exploited to find sufficiently

   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.

Analysis of Covariance consider to be quite important procedure to reduce the effect of some independents factors before going through the experiment.

By this procedure we can compare variances causes from the difference between treatments and error term variance of they are equals or less than consider to be not significant, otherwise if is significant.

We carry on with this comparison until we find the greatest covser for the significant variance flam the treatments.

There are methods can be used like least significant difference method, Duncan method and Turkeys' w-procedure and Student Newman.

Key Word: Analysis of variatio

We have provided in this research model multi assignment  with  fuzzy function goal has been to build programming model is correct Integer Programming fogging  after removing the case from the objective function data and convert it to real data .Pascal triangular graded mean using Pascal way to the center of the triangular.

The data processing to get rid of the case fogging which is surrounded by using an Excel 2007 either model multi assignment  has been used program LNDO to reach the optimal solution, which represents less than what can be from time to accomplish a number of tasks by the number of employees on the specific amount of the Internet, also included a search on some of the

Interleukin-1 β (IL-1 β) is considered to be one of the most important mediators in the pathogenesis of inflammatory diseases, particularly in neurodegenerative diseases such as multiple sclerosis (MS). MS is a chronic inflammatory disease characterized with demyelination in central nervous system (CNS). There was believe that single nucleotide polymorphisms (SNPs) in IL-1β gene can alter the structure and function of the IL-1β and consequently may have play role in MS disease. In this this study the IL-1β gene polymorphism (rs16944, rs1143634) and their association with MS in Iraqi patients were investigated. Two SNPs including IL-1β-511 (rs16944) in promoter and IL-1B+3962 (rs1143634) in encoding region, were studied using Polyme

During recent years, there has been an increasing interest in the investigation of the cytokines roles in pathogenesis of cancer, thus the study aimed at evaluating the level of tumor necrosis factor-alpha(TNF-?) in sera of Iraqi multiple myeloma (MM) patients. Beta 2-microglobulion (?2-m) was assessed to determine if there was any association between this cytokine and the level of ?2- m, as the latter is related to the stage of the disease. In addition, the age and gender were also taken into consideration. Furthermore, we investigated the relationship between IgG and TNF-? in sera of patients. 49 Iraqi patients (27 males and 22 females).The patients were also divided into two groups: the first group included (17) patients who were

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c