The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

This search is field research, which aims to explore the trends of students in media department toward specialized Satellite Channels and identify the knowledge capacity and its role in the development of their knowledge’s, represented by watching those channels as well as media students' habits exposed by those channels. As to the public is a key element in the process and substantive communication, the Sociological studies information on that article information is not complete its work, but that he was receiving from before receiving, and send every piece of information content in order to achieve a certain goal, therefore, is the future of receiving such information in order to achieve a particular goal, which is

At a time when any tourist in the world wants a trip to reload his energy and enjoy peace and quiet and engage in adventures in a safe environment, terrorism comes to disturb him on that journey through operations aimed at the tourist and entertainment destinations, such as shops, restaurants, cafes and hotels Is the orbit of research) for many reasons. The security measures taken by hotels play an important and fundamental role in preventing or limiting these terrorist operations. At the same time, while some hotel administrations are constantly seeking to improve these measures to preserve the safety of their guests and visitors, In spite of the high number of attacks on hotels since 2001 and today. This research is intended to highlight

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

Of non-Muslim minorities In the Muslim community

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −