The materials of soil were affected by multi reasons; such as human activities, floods, tidal waves, ... etc. The change of the soil contents could be measured through different indexes; such as electric conductivities, salinity, concentration of the heavy elements, and concentration of essential elements ... etc. The land cover is affected by natural influences, like tidal energy, which plays a negative role in the salinization of land adjacent to the coasts, causing a problem for soils in all its details represented in changing of the dissolved elements in soil. One of the most important natural factors that cause soil salinity is human activity in all its forms, and one of the most important causes of salinity is the phenomenon o

Abstract : Silicone elastomer is widely used as the material of choice for fabricating maxillofacial prosthesis. However, silicone properties are far from ideal; low tear strength, low tensile strength and insufficient elasticity are the most undesirable properties. The purpose of this study was to evaluate the effect of addition of nano SiO2filler on tear strength, tensile strength, elongation at break, hardness and color of Cosmesil M-511 HTV maxillofacial silicone elastomer. Nano SiO2was added to the silicone base in concentrations of 4%, 5% and 6% by weight. Silicone with 0% nano filler served as a control. Tear test was done according to ISO 34-1. Tensile and elongation test was done according to ISO 37. Shore A hardness test was done

The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

Abstract

  The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable.                                                                                  &nb

The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

structural and electrical of CuIn (Sex Te1-x)2