Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

In this study, a new theoretical method for the estimation of absorption and fluorescence spectra is accomplished. These estimations were established following experimental measurements of absorption and fluorescence spectra for the solutions of fluorescein laser dye mixed with titanium dioxide (TiO2) nanoparticles
in distilled water. The used concentration of fluorescein dye was 1x10-5 M, whereas the masses of titanium dioxide nanoparticles were 0.0003g, 0.0005g, 0.001g and 0.002g. An absorption spectra improvement was observed upon raising the mass of TiO2 nanoparticles, which specifies that doping the fluorescein dye with TiO2 nanoparticles have an essential influence on the dye absorption spectra. On the other side, all fluorescen

The research is summarized in the construction of a mathematical model using the most common methods in the science of Operations Research, which are the models of transportation and linear programming to find the best solution to the problem of the high cost of hajj in Iraq, and this is done by reaching the optimum number of pilgrims traveling through both land ports and the number Ideal for passengers traveling through airports by Iraqi Airways, instead of relying on the personal experience of the decision-maker in Hajj and Umrah Authority by identifying the best port for pilgrim's travel, which can tolerate right or wrong, has been based on scientific methods of Operations Research, the researcher built two mathematical models

This research aims at building a proposed training program according to the self-regulated strategies for the mathematics teachers and to identify the effect of this program on relational Mathematics of teachers. The sample of the research was (60) Math teachers; (30) teachers as experimental group and (30) teachers as control group. The results of the current research reacheded that the proposed training program according to some self-managed learning strategies, meets the needs of trainees with remarkable effectiveness to improve the level of their teaching performance to achieve the desired goals. Training teacher according to self-managed learning strategies is effective in bringing about the transition of training to their students

Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear (with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.

Background: One of the recommended methods for reducing aerosol contamination during the daily regular usage of high-speed turbine and ultrasonic scaling is the use of preprocedural mouth rinse. Several agents have been investigated as a preprocedural mouth rinse. Chlorhexidine significantly reduce the viable microbial content of aerosol when used as a preprocedural rinse. Studies have shown that cetylpridinum chloride (CPC) mouthwash is equally effective as chlorhexidine in reducing plaque and gingivitis. This study compared the effect of 0.07% CPC to 0.2% chlorhexidine gluconate (CHX) as preprocedural mouth rinses in reducing the aerosol contamination by high-speed turbine. Materials and Methods: 36 patients were divided into three gro