KE Sharquie, AA Al-Nuaimy, FA Al-Shimary, Saudi medical journal, 2005 - Cited by 20

A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus

Labrotary experiment was conducted to study the effect of different levels of nematode population densities of Meloidogyne spp on seed germination percentage and seedling characteristics of Vigna sinensis, Ahelmoschus esculentus, Cicer arietinum, Helianthus annuus and Rap-hanus sativus. Four different levels of nematode populat-ion densities ranged from 1 to 4 prepared from radish in-fected roots and used as inoculating agent to infect all seed types in the experiment Seed germination percentage of Vigna sinensis and Ablemoschus eseulentus were highly reduced (at 0.01 level of significance) with increased nematode population level from 1 to 4. Seedling length of the remaining seed types were significantly reduced (at 0.01 level of signif

A field experiment was conducted in Al-Yusufiya district - Al-Mahmoudiya district, Baghdad province during the winter season 2021, to study improving the efficiency and management of water use and the productivity of lettuce under different irrigation systems. The Nested-Factorial Experiments design was used, where the main plots include the first factor, irrigation levels (I1) 50%, (I2) 75%, (I3) 100, (I4) 125%, (I5) 150% ETpan. After depleting 35% of the available water and in terms of climatic data from the American Evaporative Basin, Class A. Then the main factor is divided into three replicates, and the coefficients of the second factor are distributed randomly within each replicate, which includes the irrigation system: surface drip i

This paper presents the Taguchi approach for optimization of hardness for  shape memory alloy (Cu-Al-Ni) . The influence of  powder metallurgy parameters on hardness has been investigated. Taguchi technique and ANOVA were used for analysis. Nine experimental runs based on Taguchi’s L9 orthogonal array were performed (OA),for two parameters was study (Pressure and sintering temperature) for three different levels (300 ,500 and 700) MPa ,(700 ,800 and  900)^oC respectively . Main effect, signal-to-noise (S/N) ratio was study, and analysis of variance (ANOVA) using  to investigate the micro-hardness characteristics of the shape memory alloy .after application the result of study shown the hei

In this work, the effects of solvent properties on the characteristics of absorption and fluorescence for two laser dyes was studied. Dyes used in this work include Coumarin 5400 and DCM, while the solvents include ethanol, methanol, acetone, propanol and chloroform. Coumarin 5400 dye shows sharp fluorescence peaks in the green band of visible region while the DCM dye shows relatively wide band within 590-630 nm. Therefore, the selection of any dye for random gain medium applications should be performed after determining the most appropriate solvent as the optimum fluorescence characteristics are obtained.

This study includes adding chemicals to gypseous soil to improve its collapse characteristics. The collapse behavior of gypseous soil brought from the north of Iraq (Salah El-Deen governorate) with a gypsum content of 59% was investigated using five types of additions (cement dust, powder sodium meta-silicate, powder activated carbon, sodium silicate solution, and granular activated carbon). The soil was mixed by weight with cement dust (10, 20, and 30%), powder sodium meta-silicate (6%), powder activated carbon (10%), sodium silicate solution (3, 6, and 9%), and granular activated carbon (5, 10, and 15%). The collapse potential is reduced by 86, 71, 43, 37, and 35% when 30% cement dust, 6% powder sodium meta-silicate, 10% powder activated

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h