In this paper was discussed the process of compounding two distributions using new compounding procedure which is connect a number of life time distributions ( continuous distribution ) where is the number of these distributions represent random variable distributed according to one of the discrete random distributions . Based on this procedure have been compounding zero – truncated poisson distribution with weibell distribution to produce new life time distribution having three parameter , Advantage of that failure rate function having many cases ( increasing , dicreasing , unimodal , bathtube) , and study the resulting distribution properties such as : expectation , variance , comulative function , reliability function and fa

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

Background: Multiple sclerosis (MS) is one of the increasing prevalent neurologic disorders. Epidemiologic and family studies implicate genetic and environmental factors in determining
susceptibility to MS. The exact effect of the former is intended for investigation in our study.
Objectives: The objective of the study is to compare the demographic features, clinical presenting features, and clinical course between familial and sporadic cases of MS.
Materials and Methods: this is a retrospective cohort study conducted in Multiple Sclerosis Center in the Medical City in Baghdad. The records of the MS center in Baghdad Teaching Hospital were surveyed, and data from 13 patients with positive family history of MS

Background: Multiple sclerosis (MS) is one of the increasing prevalent neurologic disorders. Epidemiologic and family studies implicate genetic and environmental factors in determining
susceptibility to MS. The exact effect of the former is intended for investigation in our study.
Objectives: The objective of the study is to compare the demographic features, clinical presenting features, and clinical course between familial and sporadic cases of MS.
Materials and Methods: this is a retrospective cohort study conducted in Multiple Sclerosis Center in the Medical City in Baghdad. The records of the MS center in Baghdad Teaching Hospital were surveyed, and data from 13 patients with positive family history of MS

The purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift

New mode for the on-line determination of oxonium ion in different strong acids using CFIA via the use of homemade linear array Ayah 5Sx4-ST- 5D solar CFI analyser

In this paper, a new high-performance lossy compression technique based on DCT is proposed. The image is partitioned into blocks of a size of NxN (where N is multiple of 2), each block is categorized whether it is high frequency (uncorrelated block) or low frequency (correlated block) according to its spatial details, this done by calculating the energy of block by taking the absolute sum of differential pulse code modulation (DPCM) differences between pixels to determine the level of correlation by using a specified threshold value. The image blocks will be scanned and converted into 1D vectors using horizontal scan order. Then, 1D-DCT is applied for each vector to produce transform coefficients. The transformed coefficients will be qua

A numerical and experimentally investigation for two types of winglets (spiroid and blended), which are used to reduce the induced drag caused by the trailing vortices were presented and discussed in this work. The SOLIDWORK 2016 was used to model a rectangular wing geometry of NACA2415 cross-sectional airfoil with blended and spiroid airfoils (2415 and 0012). The steady, incompressible N.S equations with standard (