The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

The derivatives formed after the successive acetylation, esterification and nitration reactions to cholic, deoxycholic, and taurocholic acids were identified to be of the following general strucure: Colt, Where RI=NO3, OH, 0=, or CH3COO. R2=H, NO3, OH, 0-=, or CH3COO. R3=H, NO3,01-1, 0=, or CH3COO. R4=OH, NH(CH2)2S03Na, NH(CH2)2S03H, or OMe. By using U.V-visible and I.R spectrophotometry . The number of hydroxyl groups was determined, purity was checked from T.L.C, Most of these derivatives will find pharmaceutical application.

Recently the use of nanofluids represents very important materials. They are used in different branches like medicine, engineering, power, heat transfer, etc. The stability of nanofluids is an important factor to improve the performance of nanofluids with good results. In this research two types of nanoparticles, TiO₂ (titanium oxide) and γ-Al₂O₃ (gamma aluminum oxide) were used with base fluid water. Two-step method were used to prepare the nanofluids. One concentration 0.003 vol. %, the nanoparticles were examined. Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and X-ray diffraction (XRD) were used to accomplish these tests. The stability of the two types of nanofluids is measured by

In this research we assumed that the number of emissions by time (𝑡) of radiation particles is distributed poisson distribution with parameter (𝑡), where  < 0 is the intensity of radiation. We conclude that the time of the first emission is distributed exponentially with parameter 𝜃, while the time of the k-th emission (𝑘 = 2,3,4, … . . ) is gamma distributed with parameters (𝑘, 𝜃), we used a real data to show that the Bayes estimator 𝜃 ∗ for 𝜃 is more efficient than 𝜃̂, the maximum likelihood estimator for 𝜃 by using the derived variances of both estimators as a statistical indicator for efficiency

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Abstract: New copper(II) complexes with mixed ligand benziloxime (BOxH) and furfural-dehydeazine (FA) using classical (with and without solvent) and microwave heating methods have been prepared. The resulting complexes have been characterized using physico-chemical techniques. The study suggested that the ligands formed neutral complexes had general formulas [Cu(FA)(BOXH)(Ac)2] and [Cu(FA)(BOX)(OH)] in neutral (or acidic) and basic medium, respectively. Accordingly, hexa-coordinated mono-nuclear complexes have been investigated by this study and having distorted octahedral geometry. The effect of laser have been studied on solid ligands and solid complexes, no effect have been observed on most compounds through the results of melting poin