In this study predication of crop coefficient (Kc) values through growing season for cucumber plant was conducted. A field experiment was carried out at AL Yusufiyah Township, in the Governorate of Baghdad, (latitude: 33°09' N, longitude: 44°24' E, and altitude: 34 m) in medium loam soil. The plant was cultivated inside the greenhouse under subsurface trickle irrigation system with soil water retention technology (SWRT) during the growing season 2017. Crop coefficient values were guessed from the direct method of measurements of daily crop evapotranspiration, while reference evapotranspiration was obtained from Agricultural Meteorology Project - Station of Baghdad - Abu-Ghraib. The obtained results were showed that crop coefficient values for initial, mid and late of season growing stages were: 0.1, 1.29, and 0.9, respectively. Comparison with other local work was showed similar values of Kc. Although the type of irrigation and utilizing new techniques of saving the applied water which reduced the ETc value by about 132 % comparing with other, the reference evapotranspiration value was plays an effecting role in calculating the Kc values.
The aim of this research is to estimate the area unit function of productivity for the potato crop in Anbar province for the autumn season (2008 / 2009) Anbar province has been chosen as an applied model for the study due to its well known in cultivating potato crop , and the data were collected through a random sample about (10%) from the study society with a (150) farmers, The results indicated that the double logarithmic formula was the best representative of the relationship between crop productivity and independent variables (quantity of potato tubers , quantity of herbicides stuffs, quantity of fertilizer , hours of mechanical labour
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In this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of specific time points (m)،since the frequent measurements within the subjects are almost connected an
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Non uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at
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This article studies the nonlocal inverse boundary value problem for a rectangular domain, a second-order, elliptic equation and a two-dimensional equation. The main objective of the article is to find the unidentified coefficient and provide a solution to the problem. The two-dimensional second-order, convection equation is solved directly using the finite difference method (FDM). However, the inverse problem was successfully solved the MATLAB subroutine lsqnonlin from the optimization toolbox after reformulating it as a nonlinear regularized least-square optimization problem with a simple bound on the unknown quantity. Considering that the problem under study is often ill-posed and that even a small error in the input data can hav
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Abstract
Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.