Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

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.

The paper is devoted to solve nth order linear delay integro-differential equations of convolution type (DIDE's-CT) using collocation method with the aid of B-spline functions. A new algorithm with the aid of Matlab language is derived to treat numerically three types (retarded, neutral and mixed) of nth order linear DIDE's-CT using B-spline functions and Weddle rule for calculating the required integrals for these equations. Comparison between approximated and exact results has been given in test examples with suitable graphing for every example for solving three types of linear DIDE's-CT of different orders for conciliated the accuracy of the results of the proposed method.

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

Abstract:

               The research aims to achieve defining the concept of environmental quality and associated costs. Studying the impact of environmental quality costs on the performance of economic units. Measuring the relationship between environmental quality and environmental performance of the units. Where the research problem is represented in the weak awareness of some economic units of the importance of environmental quality costs and their impact on evaluating environmental performance, and this leads to neglecting environmental considerations and not improving environmental performance effectively, which negatively affects the en

Abstract The strategic performance of the United States depends on dealing with the Middle East countries and its variants on several bases and motives that enabled them to achieve American hegemony and invest its interests at the expense of the region countries. Within this performance, the administration of the United State President Donald Trump presented the Strategic Document on December 18, 2017, which focused on the principle of "America First", to determine the direction of future US strategic performance in the formulation of means of cooperation and intersections or hostility in addition to interests and threats.The future vision of the Arab region and the Middle East as a whole, this strategy is based on the fact that

The aim of the research to measure the correlation relationship between modern manufacturing systems and process design and measure the effect by adopting the regression; the research consists of two main variables, which are modern manufacturing systems and process design; it was applied in the production lines of the General Company for Construction Industries, There is a sample of managers, engineers, technicians, administrators, and some workers were selected to fill the special questionnaire with (70) forms which distributed and (65) were approved suitable for use, For data analysis the correlation coefficient was adopted to measure the relationship and regression analysis to find out the effect, Using (SPSS), So the first h