Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

Background: With the increased in the demands of adult orthodontics, the challenge of direct bonding to non-enamel surface (zirconium) had been increased. The present study was carried out to compare the shear bond strength of three different brackets (stainless steel, sapphire and composite) bonded to zirconium surface and study the mode of bond failure. Materials and methods: The sample was comprised of 30 models (8mm *6mm*1.5mm) of full contour zirconium veneers. They were divided into three groups according to the brackets type; all samples were treated first by sandblast with aluminum oxide particle 50 µm then coated by z-prime plus primer. A central incisor bracket of each group was bonded to the prepared zirconium surface with lig

The N-[(2,3-dioxoindolin-1-yl)-N-methylbenzamide] was prepared by the reaction of acetanilide with isatin then in presence of added paraformaldehyde, the prepared ligand was identified by microelemental analysis, FT.IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following selected metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio, yielded a series of complexes of the general formula [M(L)2Cl2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). From the obtained data the octahed

Background/aim: The rising challenge of microbial resistance necessitates the development of novel therapeutic agents. This study aims to synthesize, characterize, and evaluate the antimicrobial potential of a new series of mixed-ligand metal complexes (ZnII, CuII, NiII, and MnII) derived from a p-hydroxybenzaldehyde-4-aminoantipyrine Schiff base and 2,2′-bipyridine, in addition to assessing the binding affinity and pharmacokinetic properties of the synthesized free Schiff base ligand through molecular docking and ADME profiling. Methods: The Schiff base ligand and its transition metal complexes were synthesized and subsequently characterized using single-crystal X-ray diffraction, elemental analysis, FTIR, UV–Vis spectroscopy, NMR, mag

synthesis and characterization of New schiff base Ligand Derived from 4-amino anti pyrine and it's complexes with some Metal lons and theirAntibacterial studies

This study designed to examine association between-174G/C polymorphism of interleukin-6 gene and phosphate, calcium, vitamin D₃, and parathyroid hormone levels in Iraqi patient with chronic kidney disease on maintenance hemodialysis. Seventy chronic renal failure patients (patients group) and 20 healthy subjects (control group) were genotyped for interleukin-6 polymorphism and genotyping was performed by conventional polymerase chain reaction-restriction fragment length polymorphism. No significant differences in phosphate levels were observed in patients and control with different interleukin-6 genotypes. Control had non-significant differences in calcium levels, while patients with GG and CG genotypes displayed significant e

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

Strategic Cost Management Tools Under Technological Development and Change in Customer Tastes Critical Studies