Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

TEOS aerogel a is the most commonly used. a Aerogel has attracted increasing attention from both academic and industries due to its extraordinary performance and potentials. We have systematically studied the relationship between the densification temperature of the synthesis environment of silica aerogels on their resulting morphological, optical and thermal properties. SEM and BET measurements were employed as structural probes to ascertain the structural differences. Lee's disc apparatus was used for determining the thermal conductivity coefficient. There is a systematic correlation between the annealing temperature and the aerogel surface area, porosity, as well as pore size. The implemented autoclave was able to produce aerogel mono

The main aims of this research is to find the stabilizer groups of a cubic curves over a finite field of order , studying the properties of their groups and then constructing the arcs of degree  which are embedding in a cubic curves of even size which are considering as the arcs of degree . Also drawing all these arcs.

The reform process is a dynamic process going on, especially the administrative and financial reform, which contributes to the work and directing operations towards success and continuous development, which requires determining the validity and the responsibility and the rights and duties of all officials in the school settings (within the formations educational institutions) for the purpose of reducing the administrative and financial corruption, and then ensure management efficient and effective way by taking advantage of the physical, financial and human resources available to achieve the greatest benefit at the lowest cost to the fact that the follow-up performance on an ongoing basis in accordance with the specific of powers

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust