Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

This research aims to analyze the impact of the United States policy of pressure and sanctions on changing Iran's conduct. Since the Islamic Revolution of Iran in 1979, the US has continuously pursued various policies towards Iran, aiming to change the regime by force or isolate it politically and economically. The main research question lies in the following: To what extent does the US pressure policy and its sanctions affect the conduct Iran?. This research discusses that the more there are economic and political alternatives to Iran, the more it will be challenging the US demands. Moreover, the more the US pursues a negotiating policy based on mutual interests, the more Iran will positively respond to American demands.

This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.