A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Background: Hyperfunction of the muscles of the upper lip is considered as the most common cause of excessive gingival display (EGD). The aim of this study was to demonstrate the effectiveness of botulinum toxin (BT) injection as a conservative treatment for EGD due to muscular hyperfunction and to compare the outcome of 2 injection methods. Material and methods: This study included 40 participants who were randomly assigned into 2 groups of 20 each, The first group received 2.5IU BT injection at 1 point per side (2-points group), while the second group received a total of 5 IU of BT at 2 points per side (4-points group). The outcome variables were the reduction in the central and lateral gingival display expressed as the difference between

Objective : Alzheimer’s disease (AD) continues to be a major challenge because handling high-dimensional data is time-consuming and expensive due to its complexity. A large feature space often increases computational costs and reduces model interpretability. This study addresses this problem by evaluating and comparing multiple feature selection techniques to identify the most informative biomarkers for AD diagnosis.

Methods : Our study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to implement and test three feature selection a

t-Self-Compacting Concrete (SCC) reduces environmental noise and has more workability. This research presents an investigation of the behavior of SCC under mechanical loading (impact loading). Two types of cement have been used to produce SCC mixtures, Ordinary Portland Cement (OPC) and Portland Limestone Cement (PLC), which reduces the emission of carbon dioxide during the manufacturing process. The mixes were reinforced with Carbon Fiber Reinforced Polymer (CFRP) which is usually used to improve the seismic performance of masonry walls, to replace lost steel reinforcements, or to increase column strength and ductility. Workability tests were carried out for fresh SCC. Prepared concrete slabs of 500×500×50mm were tested for lo

The efforts embedded in this paper have been devoted to designing, preparing, and testing warm mix asphalt (WMA) mixtures and comparing their behavior against traditional hot mix asphalt mixtures. For WMA preparation, the Sasobit wax additive has been added to a 40/50 asphalt binder with a concentration of 3%. An experimental evaluation has been performed by conducting the Marshall together with volumetric properties, indirect tensile strength, and wheel tracking tests to acquire the tensile strength ratio (TSR), retained stability index (RSI), and rut depth. It was found that the gained benefit of reduction in mixing and compaction temperatures was reversely associated with a noticeable decline in Marshall properties and moisture s

This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values