A dynamic analysis method has been developed to investigate and characterize embedded delamination on the dynamic response of composite laminated structures. A nonlinear finite element model for geometrically large amplitude free vibration intact plate and delamination plate analysis is presented using higher order shear deformation theory where the nonlinearity was introduced  in the Green-Lagrange sense. The governing equation of the vibrated plate were derived using the Variational approach. The effect of different orthotropicity ratio, boundary condition and delamination size on the non-dimenational fundamental frequency and frequency ratios of plate for different stacking sequences are studied. Finally th

The important of present study is to design rehabilitation program by using hypermedia for some injuries of smooth tissues in shoulder joint.   This joint is most important to help badminton players in achieving their daily and sport tasks due to upper limp movements depend on health and active of this joint. Experimental approach with a manner of equal single station was used in present study and study simple consisted of 6 badminton players from Babylon and Al-Mahaweel clubs who have less sharp tissue smooth injury such (muscles, ligaments, pocket). We used (SPSS) to analyses pre, medal, post-tests data. In conclusion, hypermedia is positive benefit to rehabilitee of injuries of smooth tissues in shoulder joint for badminton pla

The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

The research aims to demonstrate the impact of tax techniques on the quality of services provided to income taxpayers by studying the correlational and influencing relationships between the exploited variable (tax techniques) and the dependent variable (the quality of services provided to income taxpayers), and in line with the research objectives, the main hypothesis of the research was formulated (there is a relationship Significance between tax techniques and the quality of services provided to income taxpayers) a number of sub-hypotheses emerged from this hypothesis that were stated in the research methodology, and a number of conclusions were reached, the most important of which were (through the use of the correlation coeff

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

Biomarkers such as Interleukin-6 (IL-6), Procalcitonin (PCT), C-reactive protein (CRP) and Neutrophil-Lymphocyte Ratio (NLR) have a role in the pathogenesis of severe coronavirus disease 2019 (COVID-19). The aim of this study was to explore the differences between serum levels of such biomarkers in severe and non-severe COVID-19 cases and compare them with normal people and to evaluate the sociodemographic variables and chronic diseases effect on the severity of COVID-19. The study included 160 subjects, divided into two groups, a case group of 80 patients, and a control group of 80 normal persons. The case group was divided into two subgroups: 40 severe COVID-19 patients and 40 patients with non-severe disease. Blood IL-6 was asses

significant bits either in the spatial domain or frequency domain sequentially or pseudo
randomly through the cover media (Based on this fact) statistical Steganalysis use different
techniques to detect the hidden message, A proposed method is suggested of a stenographic
scheme a hidden message is embedded through the second least significant bits in the
frequency domain of the cover media to avoid detection of the hidden message through the
known statistical Steganalysis techniques.