The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

The research seeks to highlight the importance of digital finance in banking by providing financial and banking services and its role in improving the access of financial services to customers at the farthest possible point by using modern technology to finance their needs by granting them cash credits through electronic payment tools to facilitate them and shorten time and effort as well as Low cost, and this cannot be achieved without concerted efforts and the provision of basic infrastructure that includes connecting the Internet to all targeted areas, whether cities or rural areas, as well as distributing the largest possible number of ATMs and sending specialized teams to those areas that develop in customers the culture of digital

Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

In this work the concept of semi-generalized regular topological space was introduced and studied via semi generalized open sets. Many properties and results was investigated and studied, also it was shown that the quotient space of semi-generalized regular topological space is not, in general semi-generalizedspace.

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

We discussed the proper preparation, directing, and implementation of physical education lessons, and clarification of the duties that fall upon the physical education teacher in addition to his physical and skill duties, which is the duty of the physical education lesson. The problem of the research lies in the fact that interactive harmonic exercises are not implemented accurately by physical education teachers because they require great experience, exceptional efforts, and accuracy in performance. The research aims to identify the level of some physical and motor abilities and intelligence among students aged (9-10) years, and to know the effect of some harmonic exercises. Interactivity at the level of some physical and motor abi

In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has