Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear (with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.

This work generalizes Park and Jung's results by introducing the concept of generalized permuting 3-derivation on Lie ideal.

In this paper, we study the concepts of generalized reverse derivation, Jordan
generalized reverse derivation and Jordan generalized triple reverse derivation on -
ring M. The aim of this paper is to prove that every Jordan generalized reverse
derivation of -ring M is generalized reverse derivation of M.

In this research, a new application has been developed for games by using the generalization of the separation axioms in topology, in particular regular, Sg-regular and SSg- regular spaces. The games under study consist of two players and the victory of the second player depends on the strategy and choice of the first player. Many regularity, Sg, SSg regularity theorems have been proven using this type of game, and many results and illustrative examples have been presented

In this study, we introduce and study the concepts of generalized ( , )-reverse derivation, Jordan generalized ( , )-reverse derivation, and Jordan generalized triple ( , )-reverse derivation from Γ-semiring S into ΓS-module X.  The most important findings of this paper are as follows:

If S is Γ-semiring and X is ΓS-module, then every Jordan generalized ( , )- reverse derivations from S into X associated with Jordan ( , )-reverse derivation d from S into X is ( , )-reverse derivation from S into X.

The concepts of generalized higher derivations, Jordan generalized higher derivations, and Jordan generalized triple higher derivations on Γ-ring M into ΓM-modules X are presented. We prove that every Jordan generalized higher derivation of Γ-ring M into 2-torsion free ΓM-module X, such that aαbβc=aβbαc, for all a, b, c M and α,βΓ, is Jordan generalized triple higher derivation of M into X.

Undoubtedly, Road Traffic Accidents (RTAs) are a major dilemma in term of mortality and morbidity facing the road users as well as the traffic and road authorities. Since 2002, the population in Iraq has increased by 49 percent and the number of vehicles by three folds. Consequently, these increases were unfortunately combined with rising the RTAs number, mortality and morbidity. Alongside the humanitarian tragedies, every year, there are considerable economic losses in Iraq lost due to the epidemic of RTAs. Given the necessity of understanding the contributory factors related to RTAs for the implementation by traffic and road authorities to improve the road safety, the necessity have been a rise for this research which focuses into

Undoubtedly, Road Traffic Accidents (RTAs) are a major dilemma in term of mortality and morbidity facing the road users as well as the traffic and road authorities. Since 2002, the population in Iraq has increased by 49 percent and the number of vehicles by three folds. Consequently, these increases were unfortunately combined with rising the RTAs number, mortality and morbidity. Alongside the humanitarian tragedies, every year, there are considerable economic losses in Iraq lost due to the epidemic of RTAs. Given the necessity of understanding the contributory factors related to RTAs for the implementation by traffic and road authorities to improve the road safety, the necessity have been a rise for

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina