A new, simple and sensitive method was used forevaluation of propranolol withphosphotungstic acidto prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between propranolol and phosphotungstic acid in an aqueous medium to obtain a yellow precipitate. Optimum parameters was studied to increase the sensitivity for developed method. A linear range for calibration graph was 0.007-13 mmol/L for cell A and 5-15 mmol/L for cell B, and LOD 207.4792 ng/160 µL and 1.2449 µg/160 µL respectively to cell A and cell B with correlation coefficient (r) 0.9988 for cell A, 0.9996 for cell B, RSD% was lower than 1%, (n=8) for the

This study's objective is to assess how well UV spectrophotometry can be used in conjunction with multivariate calibration based on partial least squares (PLS) regression for concurrent quantitative analysis of antibacterial mixture (Levofloxacin (LIV), Metronidazole (MET), Rifampicin (RIF) and Sulfamethoxazole (SUL)) in their artificial mixtures and pharmaceutical formulations. The experimental calibration and validation matrixes were created using 42 and 39 samples, respectively. The concentration range taken into account was 0-17 μg/mL for all components. The calibration standards' absorbance measurements were made between 210 and 350 nm, with intervals of 0.2 nm. The associated parameters were examined in order to develop the optimal c

AS Muhsen, International Journal of Psychosocial Rehabilitation (1475-7192), 2020 - Cited by 1

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulati

   There is no doubt that the project control function is very important for administration, so the project Management depends on to monitor and control the project. The project control integrated to the planning which is the base of the administration functions; planning, organizing, directing, and controlling. Without project control cannot be insure to fulfill the plan of the project by the budget and specified time. The project management apply many methods of control to achieve the goals of project which are cost, time, and required specifications. Earned Value Management one of control methods that used in the project by international companies.

Earned Value Method is used in the project o

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that