Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

In this paper, a discussion of the principles of stereoscopy is presented, and the phases
of 3D image production of which is based on the Waterfall model. Also, the results are based
on one of the 3D technology which is Anaglyph and it's known to be of two colors (red and
cyan).
A 3D anaglyph image and visualization technologies will appear as a threedimensional
by using a classes (red/cyan) as considered part of other technologies used and
implemented for production of 3D videos (movies). And by using model to produce a
software to process anaglyph video, comes very important; for that, our proposed work is
implemented an anaglyph in Waterfall model to produced a 3D image which extracted from a
video.

Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had

Todays, World is faced an energy crisis because of a continuous increasing the consumption of fuels due to intension demand for all types of vehicles. This study is one of the efforts dealing with reduce the weight of vehicles by using a new material of sandwich steel, which consists of two skin steel sheets with core of a polymer material. Resistance spot welding (RSW) can be easily implemented on metals; however a cupper shunt tool was designed to perform the resistance welding of sandwich steel with DP800 cover sheets to resolve a non-conductivity problem of a polymer core. Numerical simulations with SORPAS^®3D were employed to test the weldability of this new material and supported by many practical experiments. In conclus

This work aims to detect the associations of C-peptide and the homeostasis model assessment of beta-cells function (HOMA2-B%) with inflammatory biomarkers in pregnant-women in comparison with non-pregnant women. Sera of 28 normal pregnant women at late pregnancy versus 27 matched age non-pregnant women (control), were used to estimate C-peptide, triiodothyronine (T3), and thyroxin (T4) by Enzyme-linked-immunosorbent assay (ELISA), fasting blood sugar (FBS) by automatic analyzer Biolis 24i, hematology-tests by hematology analyzer and the calculation of HOMA2-B% and homeostasis model assessment of insulin sensitivity (HOMA2-S%) by using C-peptide values instead of insulin. The comparisons, correlations, regression analysis tests were perfo

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

Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

          New nitrone and selenonitrone compounds were synthesized. The condensation method between N-(2-hydroxyethyl) hydroxylamine and substituted carbonyl compounds such as [benzil, 4, 4́-dichlorobenzil and  2,2́ -dinitrobenzil] afforded a variety of new nitrone compounds while the condensation between N-benzylhydroxylamine and substituted selenocarbonyl compounds such as [di(4-fluorobenzoyl) diselenide and (4-chlorobenzoyl selenonitrile] obtained selenonitrone compounds. The condensation of N-4-chlorophenylhydroxylamine with dibenzoyl diselenide obtained another type of selenonitrone compounds. The structures of the synthesized compounds were assigned based on spectroscopic data (FT-IR,

This study addresses quantum computers as one of the most significant contemporary technological transformations that promise to reshape the future of global computing. It aims to clarify the conceptual foundations of quantum computing and to identify the fundamental differences between quantum and classical computers in terms of processing mechanisms, computational speed, and the ability to solve highly complex problems. The study focuses on key concepts such as the qubit, superposition, and entanglement, highlighting their role in enabling computational capabilities that exceed the limits of classical computing. It also discusses the future applications of quantum computers in areas such as cryptography, artificial intelligence, big data