As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

                           
 The Islamic religion approach Rabbani urges and seeks to bring happiness to people, as Allah says: ((We sent thee not all people glad tidings and a warner, but most people do not know)) Spa: State 28
   Islam looks at the concept of educational values ​​through positive behavior derived emerging through formal and informal education. The Islamic approach works on the basis of a systematic and clear rule in the form of an integrated system includes multiple areas. As the lead actor role as the desired position.
  Although 

The present study analyzes the violation of the strategies of conversation in two English plays namely Richard II and King Lear. The present study tries to achieve the following goals: 1. showing how the strategies of real conversation can be applied to conversation in plays. 2. analyzing how the characters communicate with each other to discover how Shakespeare violates the strategies of conversation in depicting his characters. The study has been conducted on the bases of the following hypotheses:

1. The strategies of conversation which are derived from the study of natural conversation can be applied to conversation in drama with some modification for dramatic purposes.

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

The cities are not yet a temporal status in the process of the human and civilization development. The cities consider as a life pattern, this mean that people cannot live without cities, which surround us. Several phenomena like globalization, revolution of information, technical development, increased of consumption, do not confirmed without the living in cities. The urbanization – in its simple meaning – means transferring from rural community to city community. In other word, it means that socioeconomic changes happened subject to the patterns and conditions of the urban life. Each government depend a certain policy, this policy contains set of plans and programs, that targeting to affect the population factors and the st

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models