In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has

Background:No previous Iraqi study was done on the estimation of post mortem interval (PMI) from the medico-legal point of view; depending on the biochemical changes of vitreous humor.Objectives:To find out the relationship between some biochemical changes in vitreous humor and post mortem interval.To find out a new formula for estimation of PMI from some biochemical changes in vitreous humor.Method:The study was conducted on one hundred twenty two cases referred to the medico-legal institute in Sulaimani province during the period between 1st of February and 30th of July 2012.Complete classical autopsy was performed for each case and vitreous humor was collected at autopsy from the posterior chamber of the eye and the samples after coll

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

CD63 is -one of the tetraspanin family proteins, which are regarded as: hallmark exosomal markers because it is absent from other types of vesicles. It is expressed in the cell membrane of cancer cells, and cytoplasm of stromal cells. Objective: To assess CD63 expression in gastric cancer (GC) patients, and detected if it could be used as a predictive marker. Furthermore, the current study aimed to find the correlation between CD63 expression and clinicopathological parameters as: gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade and stages of GC (TNM). The current study is a retrospective study in the period time from (2018 to-2020); 50 randomly patients formalin-fixed paraffin embedded blocks (FFPE)

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

 

The Field Programmable Gate Array (FPGA) approach is the most recent category, which takes the place in the implementation of most of the Digital Signal Processing (DSP) applications. It had proved the capability to handle such problems and supports all the necessary needs like scalability, speed, size, cost, and efficiency.

In this paper a new proposed circuit design is implemented for the evaluation of the coefficients of the two-dimensional Wavelet Transform (WT) and Wavelet Packet Transform (WPT) using FPGA is provided.

In this implementation the evaluations of the WT & WPT coefficients are depending upon filter tree decomposition using the 2-D discrete convolution algorithm. This implementation w

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con