In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distr

This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.

Objectives:  The study aims to identify the effects of an educational program on patients’ knowledge about vascular access care and to find out the relationship between patients knowledge scores and their selected demographic variable.                                                                                  &

This study focuses on the biodegradation of oxymatrine insecticide by some soil fungi isolated from four agriculture stations. The results showed that the highest degradation rate 94.66% was recorded by Ulocladium sp. at 10 days and A. niger recorded the lowest degradation rate 45.86%, while at 20 days Ulocladium sp. also showed the highest degradation rate 94.98% and the lowest degradation rate reached to 82.49% with A.niger. The mix (Exerohilum sp.+Ulocladium sp.) recorded the highest degradation rate of oxymatrine insecticide 90.22%, 88.51%, 85.34%  at 4, 8 and 12 ppm.The use of mixed isolates enhanced the biodegradation process. There is no study of oxymatrine biodegradation

The aim of the research is to identify the percentage of success and failure of some compound offensive skills in joiner basketball. It was evident that development only occurred though the mastery of the basic single offence skills as well as the ability to perform compound skills accurately and consistently. Not paying enough attention to compound skills leads evidentially to weakness in the athlete's level that in turn leads to mistakes in performance. Six joiner games of the best four teams in Baghdad were filmed and analyzed. The results of analyzing the compound offence skills were as follows:  There was some weakness in the athletes' ability in using compound offence skills specially receiving, dribbling and following through that

Abstract:

           The great importance that distinguish these factorial experiments made ​​them subject a desirable for use and application in many fields, particularly in the field of agriculture, which is considered the broad area for experimental designs applications.

            And the second case for the factorial  experiment, which faces researchers have great difficulty in dealing with the case unbalance we mean that frequencies treatments factorial  are not equal meaning (that is allocated a number unequal of blocks or units experimental per tre

     استهدف البحث فصل بروتينات مصل دم كل من الحمامة الفاختة (Streptopelia decaocto) والحمامة المطوقة (Streptopelia senegalensis) بطريقة الترحيل الكهربائي كطريقة تصنيفية مابين النوعين . تم جمع 23 حمامة فاختة (13 ذكر و10 إناث) و 15 حمامة ضاحكة (8 ذكر و5 إناث) من مناطق مختلفة من مدينة بغداد ، وتم سحب0.1 مل من الدم من الوريد الموجود

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.