Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

The capital banking foundation stone upon which the bank in the practice of business activities, the more capital a good financial adequacy of the increased bank's ability to grant credit and expand the various activities and provide a safety element for depositors and other sources of funding to achieve profits and increase the trading volume of the shares, causing the rise the rate of return for the shares of banks and have the Central Bank as head of the banking system by issuing instructions capital increase banking, according to the requirements of economic development and increase gross domestic product by supporting investment projects that are financed through banks, the research aims to show the extent of the banks commitment to

The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that

In this paper, An application of non-additive measures for re-evaluating the degree of importance of some student failure reasons has been discussed. We apply non-additive fuzzy integral model (Sugeno, Shilkret and Choquet) integrals for some expected factors which effect student examination performance for different students' cases.

The study aims to identify the impact of electronic games on increasing the dropout rate among students in the basic stage in Jordan from their teachers’ point of view. The study adopted a descriptive survey method. Its community consisted of all fe(male) teachers of the basic stage in public and private schools, (First Amman, Irbid, and special education in Zarqa and Amman). The electronic questionnaire was used as a tool for the study. The results have shown that the effect of electronic games on increasing the dropout rate among students in the basic stage in Jordan was high. Besides, there are statistically significant differences due to the gender variable for males. There are statistically significant differences due to the varia