Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin’s method), The nonparametric model is estimated by using kernel smoothing (Nadaraya Watson), K-Nearest Neighbor smoothing and Median smoothing. The Flower Pollination algorithms were employed and structured in building the ecological model and estimating the semi-parametric regression function with measurement errors in the explanatory and dependent variables, then compare the models to choose the best model used in the environmental scope measurement errors, where the comparison between the models is done using the mean square error (MSE).
Transportation and distribution are the most important elements in the work system for any company, which are of great importance in the success of the chain work. Al-Rabee factory is one of the largest ice cream factories in Iraq and it is considered one of the most productive and diversified factories with products where its products cover most areas of the capital Baghdad, however, it lacks a distribution system based on scientific and mathematical methods to work in the transportation and distribution processes, moreover, these processes need a set of important data that cannot in any way be separated from the reality of fuzziness industrial environment in Iraq, which led to use the fuzzy sets theory to reduce the levels of uncertainty.
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Let R be a Г-ring, and σ, τ be two automorphisms of R. An additive mapping d from a Γ-ring R into itself is called a (σ,τ)-derivation on R if d(aαb) = d(a)α σ(b) + τ(a)αd(b), holds for all a,b ∈R and α∈Γ. d is called strong commutativity preserving (SCP) on R if [d(a), d(b)]α = [a,b]α(σ,τ) holds for all a,b∈R and α∈Γ. In this paper, we investigate the commutativity of R by the strong commutativity preserving (σ,τ)-derivation d satisfied some properties, when R is prime and semi prime Г-ring.
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The Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.
The objective of this work was to study the effect of oral administration of Cyperus esculentus (CE) and its alcoholic extract on sperm function parameters in prepubertal mice as a model for human .The animals were divided into three groups each contains 6 animals .Group 1 was treated with 150 mg/ kg body weight /day of crude CE, group 2 was treated with same dose of alcohol extract of CE and group 3 regarded as control throughout six weeks period. The results showed a significant (p> 0.05) increase in the mean of sperm concentration ,sperm motility percent and progressive sperm motility between treated groups and control . There was no differences among groups in the mean of sperm normal morphology and sperm viability . No significa
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
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A simple analytical method was used in the present work for the simultaneous quantification of Ciprofloxacin and Isoniazid in pharmaceutical preparations. UV-Visible spectrophotometry has been applied to quantify these compounds in pure and mixture solutions using the first-order derivative method. The method depends on the first derivative spectrophotometry using zero-cross, peak to baseline, peak to peak and peak area measurements. Good linearity was shown in the concentration range of 2 to 24 μg∙mL-1 for Ciprofloxacin and 2 to 22 μg∙mL-1 for Isoniazid in the mixture, and the correlation coefficients were 0.9990 and 0.9989 respectively using peak area mode. The limits of detection (LOD) and limits of quantification (LOQ) wer
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