In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.
Total Electron Content measurements derived from Athens station ionograms (ITEC),
located near Iraq, during the ascending phase of solar cycle 24 (July 2009- April 2010),
according to availability of data, are compared with the latest version of the International
Reference Ionosphere model, IRI-2012 (IRI TEC), using two options (NeQuick, IRI01-
Corr) for topside electron density.
The results obtained from both (ITEC and IRI TEC) techniques were similar, where
correlation coefficients between them are very high. Generally, the IRI predictions
overestimate the ITEC values.
The current search aims to identify First: To measure the level of authoritarian personality among the students of the sample as a whole. Second: Measurement of differences in the level of authoritarian personality among students in the middle school according to the following variables 0.Science (literary, scientific) 8. Sex (male - female) Third: the level of control site level among the students of the sample as a whole. Ra'aa: Measurement of differences in the level of the control site among junior students according to the following variables 0.Science (literary, scientific) 8. Sex (male - female) Fifth: Explain the relationship between the authoritarian personality and the locus of control among the students of the research sample.
... Show MoreIn 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
... Show MoreString matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-co
... Show MoreThe continuous increases in the size of current telecommunication infrastructures have led to the many challenges that existing algorithms face in underlying optimization. The unrealistic assumptions and low efficiency of the traditional algorithms make them unable to solve large real-life problems at reasonable times.
The use of approximate optimization techniques, such as adaptive metaheuristic algorithms, has become more prevalent in a diverse research area. In this paper, we proposed the use of a self-adaptive differential evolution (jDE) algorithm to solve the radio network planning (RNP) problem in the context of the upcoming generation 5G. The experimental results prove the jDE with best vecto
The rapid and enormous growth of the Internet of Things, as well as its widespread adoption, has resulted in the production of massive quantities of data that must be processed and sent to the cloud, but the delay in processing the data and the time it takes to send it to the cloud has resulted in the emergence of fog, a new generation of cloud in which the fog serves as an extension of cloud services at the edge of the network, reducing latency and traffic. The distribution of computational resources to minimize makespan and running costs is one of the disadvantages of fog computing. This paper provides a new approach for improving the task scheduling problem in a Cloud-Fog environme
One of the most important elements of achieving food security is livestock, which is an essential element in the agricultural sector, and is one of the state support sectors. Animal production (sheep) ranked an important position in this sector due to the economic advantages that are available when rearing. Moreover, the success and development of sheep breeding depend on several factors, including financial return and achieving profitability. The study aims to identify the phenomenon size of random slaughter as a problem, which spread in Baghdad and its causes and the factors that influencing its development. As well as, the possibility of applying the idea of amobile slaughterhouse to reduce this phenomen
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