Crude oil still affects many countries because it is one of the essential fuel sources. It makes life more manageable in modern communities and cannot be overstated because it is easy to use and find. However, the pollution caused by its use in industries such as mining, transportation, and the oil and gas business, especially soil pollution, cannot be ignored. Soil pollution is an issue in most communities because it influences people and ecology. Accidental infusions and spills of ore oils are prevalent occurrences leading to the entire or fractional exchange of the soil pore fluid by oil-contaminated soils that have affected the geotechnical engineering properties. The liquid limitations for polluted soil grades silty loam and sa

In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

Porosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is sol

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

A comparative study was carried out to evaluate alkaloid antibacterial activity which was extracted from the root bark Punica granatum L. by liquid membrane techniques (SA) and organic solvent traditional techniques (SB). The screening of the antimicrobial activity was conducted by agar well diffusion method against Staphylococcus aureus, Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis at three concentration levels (5, 10 and 15 mg/ml). Alkaloid extracts were analyzed by a high performance liquid chromatography (HPLC) method. Among the tested extractions, SB showed the highest antibacterial activity against all five bacterial strains, especially at 15 mg/ml concentration. However, all the B type solution

The tagged research (realism in the Paintings of Iraqi Kurdistan artists, “a study of expression methods”) dealt with realism in an objective way, as well as the complexity of its concepts through its formations and formations. On realism and its historical dimension in concept and meaning, as for the second chapter, the research was focused on the methods of expression in painting, while the third chapter was concerned with the procedural applications of realistic methods of expression in the drawings of Iraqi Kurdistan, and according to these axes and to achieve the goal of the research, a number of Among the results are:
1- Realism documented the life of the Kurdish society in line with the developments of the era, as the sty

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s