The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg

This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.

The rapid success and the field dilation of Daish organization in both Iraq and Syria make academic institutes and research centers to pay attention to its propaganda means to gain its public opinion, and to further investigation about new methods employed by this organization to disseminate its messages to the public, particularly young people in large areas of the world. This organization uses traditional propaganda techniques on psychological war and its levels, social network sites and platforms that are distributed online. This study seeks to expose more persuasive methods used by the organization to gain multiple classes of society and to disseminate its extremist ideological thoughts. It also studies the psychological operation an

      This paper deals with estimation of the reliability system in the stress- strength model of the shape parameter for the power distribution. The proposed approach has been including different estimations methods such as Maximum likelihood method, Shrinkage estimation methods, least square method and Moment method. Comparisons process had been carried out between the various employed estimation methods with using the mean square error criteria via Matlab software package.

In this paper was discussed the process of compounding two distributions using new compounding procedure which is connect a number of life time distributions ( continuous distribution ) where is the number of these distributions represent random variable distributed according to one of the discrete random distributions . Based on this procedure have been compounding zero – truncated poisson distribution with weibell distribution to produce new life time distribution having three parameter , Advantage of that failure rate function having many cases ( increasing , dicreasing , unimodal , bathtube) , and study the resulting distribution properties such as : expectation , variance , comulative function , reliability function and fa

In this paper, the effective computational method (ECM) based on the standard monomial polynomial has been implemented to solve the nonlinear Jeffery-Hamel flow problem. Moreover, novel effective computational methods have been developed and suggested in this study by suitable base functions, namely Chebyshev, Bernstein, Legendre, and Hermite polynomials. The utilization of the base functions converts the nonlinear problem to a nonlinear algebraic system of equations, which is then resolved using the Mathematica^®12 program. The development of effective computational methods (D-ECM) has been applied to solve the nonlinear Jeffery-Hamel flow problem, then a comparison between the methods has been shown. Furthermore, the maximum

The phytoremediation technique has become very efficient for treating soil contaminated with heavy metals. In this study, a pot experiment was conducted where the Dodonaea plant (known as hops) was grown, and soil previously contaminated with metals (Zn, Ni, Cd) was added at concentrations 100, 50, 0 mg·kg-1 for Ni and Zn, and at concentrations of 0, 5, 10 mg·kg-1 for cadmium. Irrigation was done within the limits of the field capacity of the soil. Cadmium, nickel and zinc was estimated in the soil to find out the capacity of plants to the absorption of heavy and contaminated metals by using bioconcentration factors (BCFs), bioaccumulation coefficient (BAC) and translocation factor (TF). Additionally, BCF values of both Ni and Zn were l

The current study is the identification and isolation dermatophyte species in clinical isolates by both Sabouraud’s Dextrose Agar (SDA) and on Dermatophyte Test Medium (DTM). Clinical specimens of hair, nails and skin scales were collected from patients with dermatophytosis and submitted to direct microscopic examination after immersion in 20% of potassium hydroxide solution. The clinical specimens were cultured on SDA containing chloramphenicol and cycloheximide, and on DTM. Tinea corporis showed the highest prevalent dermatophyte infection among patients (26.7%), followed by Tinea pedis (23.3%), whereas Tinea manuum exhibited the lowest fungal infection (6.7 %). Rural areas revealed the highest prevalence of dermatophyte in

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system