This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

The study found a number of results. The most prominent were the low married during the years of the study in 1997-2012. The study also showed the level of administrative units that the percentage of widows and single rise in urban and rural decline. This is due to the different nature of urban and rural society of the behavior and social habits and traditions.As the proportion of divorced and unmarried are decreased in urban and increase proportion in the countryside, and this is due to the influence of the rural population in the urban centers. As well as the study showed that there was a significant effect of the economic and social factors and other factors on marital status on its parts in the study area.

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

This study aimed to evaluate oral health (OH) and periodontal diseases (PD) awareness in the Iraqi population.

The study of sex Structure and age characteristics of an important element of the
follow-up changes between different population groups, which are connected to a large degree
the demographic, social and economic characteristics, particularly since each population
group varying characteristics in terms of age, sex entail social, demographic, cultural and
economic implications, and from that the researcher has taken from Structure of sex and age
for population in the district of Tuz Khurmatu for (1997-2012 ) the subject of consideration
and maintain compared to see the contrast between them. Qualitative Research for installation
and the age of the urban and rural areas has touched the judiciary, as well as its respects

In this paper a prey - predator model with harvesting on predator species with infectious disease in prey population only has been proposed and analyzed. Further, in this model, Holling type-IV functional response for the predation of susceptible prey and Lotka-Volterra functional response for the predation of infected prey as well as linear incidence rate for describing the transition of disease are used. Our aim is to study the effect of harvesting and disease on the dynamics of this model.

Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.

             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o