This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB )  to find the optimal solution

The linear segment with parabolic blend (LSPB) trajectory deviates from the specified waypoints. It is restricted to that the acceleration must be sufficiently high. In this work, it is proposed to engage modified LSPB trajectory with particle swarm optimization (PSO) so as to create through points on the trajectory. The assumption of normal LSPB method that parabolic part is centered in time around waypoints is replaced by proposed coefficients for calculating the time duration of the linear part. These coefficients are functions of velocities between through points. The velocities are obtained by PSO so as to force the LSPB trajectory passing exactly through the specified path points. Also, relations for velocity correction and exact v

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

Czerwi’nski et al. introduced Lucky labeling in 2009 and Akbari et al and A.Nellai Murugan et al studied it further. Czerwi’nski defined Lucky Number of graph as follows: A labeling of vertices of a graph G is called a Lucky labeling if  for every pair of adjacent vertices u and v in G where . A graph G may admit any number of lucky labelings. The least integer k for which a graph G has a lucky labeling from the set 1, 2, k is the lucky number of G denoted by η(G). This paper aims to determine the lucky number of Complete graph K_n, Complete bipartite graph K_m,n and Complete tripartite graph K_l,m,n. It has also been studied how the lucky number changes whi

Estimation of the names and verbs of some letters to consider the grammatical industry

The research included an introduction, and three functions
of the Prophet (peace and blessings of Allaah be upon him), a
machine and a companion, and a conclusion , the first function,
which is zakaah, and began with it because it is the basis of every
work, no work is accepted by Allaah except what was sincere to
him, as well as sincere intention, because accepting works is
entrusted with the

      This research is based on  interaction of two most important variables to the business organizations in the current era ,  these two variables are (marketing orientation and quality of service),  this research is trying to urge the service organizations to reconsider the mechanisms adopted in the formulation of its plans, It was the application of research in Korek Telecom and Asia Cell Telecom as a sector of service active and important in the business sector in Iraq, the information was obtained through the design of the Likert questionnaire , it was distributed (92) questionnaire , (50) for the company Korek Telecom and (42) of the Asia-Cell and represent research population sample

Differences in transversal sections and activities of geomorphological operations led to forming geomorphological shapes as river turns and river isles in watercourse in the area of study. The study showed three river turns that are Sindia turn with length 4723m, turn wave 3599 average width 267.6, Zanbour turn length 11374m, turn wave 7110 average width 307.5m,and Dojama turn with length 5876m, turn wave 4982m average width 313.4m. This difference is caused by the activity of erosion and sedimentation that led to the appearance of the length rivers turn.
The study showed that the turn of Dojama is the only corresponding turn, whereas the phenomena of corresponding never appeared in other turns in the area of study. The study also sho

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.