This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of the regression, as recorded as the best value to validate the performance, was 58.11 in the second period. The importance of fruit circumference is attributed to the sorting and grading of fruits, especially in packing boxes and marketing. Keywords: Automated grading and sorting, traditional grading and sorting, image processing, computer vision, Artificial neural networks
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The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.
In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes
... Show MoreA survey statistician for cholera in Iraq for 1980 and until 2003 show that cholera is endemic in Iraq and that the highest number of casualties recorded in the years 1998-1999 and increasing spread of the disease during the wars in hot climates, wet a study bacteriological used where circles selective and tests Alkouhaoah examinations serological system
2,2'-(1-(3,4-bis(carboxydichloromethoxy)-5-oxo-2,5-dihydrofuran-2-yl)ethane-1,2-diyl)bis(oxy)bis(2,2-dichloroacetic acid) a derivative of L-ascorbic acid was prepared by reaction of L-ascorbic acid with trichloroacetic acid (1:4) ratio, in the presence of potassium hydroxide. A series of new metal complexes of this ligand were prepared by a reaction with the chlorides of Cd(II), Co(II), Ni(II), Cu(II) and Zn(II). The new ligand and its complexes were identified by C.H.N., IR, UV-visible spectra, Thermogravimetric analysis (TGA), as well as 1H, 13C-NMR and Mass spectra for ligand L. The complexes were also identified by molar conductance, atomic absorption, magnetic susceptibility and X-ray diffraction for Cu (II) complex. FT-IR spectra
... Show MoreComplexes of (Co2+, Ni2+, Cu2+, Zn2+, Cd2+ and Hg2+) with the ligand Ethyl cyano (2-methyl carboxylate phenyl azo acetate) (ECA) have been prepared and characterized by FTIR, (UV-Visible), Atomic absorption spectroscopy, Molar conductivity measurements and magnetic moments measurements. The following general formula has been suggested for the prepared complexes [M(ECA)2]Cl2 where M = (Co2+, Ni2+, Cu2+ ,Zn2+, Cd2+, Hg2+) and the geometry is octahedral.
In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.