The study was aimed to evaluate the marketing efficiency of dry Onion crop in Salah al-Deen, as estimate the impact of some quality and quantity factors in the efficiency of marketing process of crop using Tobit regression model. The average marketing efficiency of the research sample was 71.3686%. The marketing margins differed according to the marketing channel followed in marketing the crop. The qualitative and quantitative variables in the model are productivity, family size, distance from the market, educational level. The estimated model revealed that a variable productivity is the most important and influential in marketing efficiency, followed by the variable of the distance between the farm and the market, then the variable

The study was aimed to evaluate the marketing efficiency of dry Onion crop in Salah al-Deen, as estimate the impact of some quality and quantity factors in the efficiency of marketing process of crop using Tobit regression model. The average marketing efficiency of the research sample was 71.3686%. The marketing margins differed according to the marketing channel followed in marketing the crop. The qualitative and quantitative variables in the model are productivity, family size, distance from the market, educational level. The estimated model revealed that a variable productivity is the most important and influential in marketing efficiency, followed by the variable of the distance between the farm and the market, then the variable

The theory of probabilistic programming  may be conceived in several different ways. As a method of programming it analyses the implications of probabilistic variations in the parameter space of linear or nonlinear programming model. The generating mechanism of such probabilistic variations in the economic models may be due to incomplete information about changes in demand, pro­duction and technology, specification errors about the econometric relations presumed for different economic agents, uncertainty of various sorts and the consequences of imperfect aggregation or disaggregating of economic variables. In this Research we discuss the probabilistic programming problem when the coefficient b_i is random variable

In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g

Background: Dimensional changes of acrylic denture bases after polymerization results in need for further adjustments or even ends with technical failure of the finished dentures. The purpose of this study was to estimate the linear dimensional changes for different palatal depths when using multiple investment materials and polymerization techniques. Materials and methods: Ninety upper complete denture bases were constructed for this study. They were divided into two main groups according to the polymerization methods: conventional water bath and experimental autoclave (short and long cycles). Each main group was further subdivided into three subgroups according to the palatal depth (shallow, medium and deep). Furthermore, for each palatal

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

This work is devoted to study the properties of the ground states such as the root-mean square ( ) proton, charge, neutron and matter radii, nuclear density distributions and elastic electron scattering charge form factors for Carbon Isotopes (9C, 12C, 13C, 15C, 16C, 17C, 19C and 22C). The calculations are based on two approaches; the first is by applying the transformed harmonic-oscillator (THO) wavefunctions in local scale transformation (LST) to all nuclear subshells for only 9C, 12C, 13C and 22C. In the second approach, the 9C, 15C, 16C, 17C and 19C isotopes are studied by dividing the whole nuclear system into two parts; the first is the compact core part and the second is the halo part. The core and halo parts are studied using the

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival