In this work various correlation methods were employed to investigate the annual cross-correlation patterns among three different ionospheric parameters: Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). The annual predicted dataset for these parameters were generated using VOCAP and ASASPS models based on the monthly Sunspot Numbers (SSN) during two years of solar cycle 24, minimum 2009 and maximum 2014. The investigation was conducted for Thirty-two different transmitter/receiver stations distributed over Middle East. The locations were selected based on the geodesic parameters which were calculated for different path lengths (500, 1000, 1500, and 2000) km and bearings (N, NE, E, SE, S, SW, W, NW) using a Matlab program that was designed and implemented for this purpose. Depending on the investigation results of the cross-correlation, a third order polynomial equation provides a better representation of the correlation between the tested parameters. Also, the annual values of the HPF, OWF, and BUF parameters were predicted using the proposed mathematical correlation equations. These equations were confirmed by comparing their results with the observed datasets for the studied years. Several statistical methods were used to validate the presented data, all of which gave good results for all tested cases. Also, contour plot diagrams were used to visually illustrate the annual average distribution pattern of the tested ionospheric parameters for all geodetic factors for the minimum and maximum years of Solar Cycle 24.
After the spread of the function of the scenographer in the modern theater, his vision has become present in most of the theatrical works and because the director is the master of the work and the owner of the vision that appears in front of the audience, the overlap between the visions of each of them was required. This research is an attempt to detect the overlap and disengagement in the work of each of them.
The research is divided into a methodological framework that included the research problem, importance, limits, and purpose, and then the definition of terms. In the theoretical framework, the research dealt with two theoretical sections that pave the way for raising ideas related to this subject: the first section (scenography
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
... Show MoreThe Christian religion came in love and co-existence with all human beings, united in the minds of its people, including the great creation to form a strong unit of high ethics that contributes to the unity among the members of society and coexistence in security, peace and love of harmony.
This research aims to suggest formulas to estimate carry-over effects with two-period change-over design, and then, all other effects in the analysis of variance of this design, and find the efficiency of the two-period change-over design relative to another design (say, completely randomized design).
Hydroisomerization of Iraqi light naphtha was studied on prepared Ni-Pt/H-mordenite catalyst at a temperature range of 220-300°C, hydrogen to hydrocarbon molar ratio of 3.7, liquid hourly space velocity (LHSV) 1 hr-1 and at atmospheric pressure.
The result shows that the hydrisomerization of light naphtha increases with the increase in reaction temperature at constant LHSV. However, above 270 0C the isomers formation decreases and the reaction is shifted towards the hydrocracking reaction, a higher octane number of naphtha was formed at 270 °C.
Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE), Border
... Show MoreThe study addresses the problem of stagnation and declining economic growth rates in Arab countries since the eighties till today after the progress made by these countries in the sixties of the last century. The study reviews the e
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