Solving problems via artificial intelligence techniques has widely prevailed in different aspects. Implementing artificial intelligence optimization algorithms for NP-hard problems is still challenging. In this manuscript, we work on implementing the Naked Mole-Rat Algorithm (NMRA) to solve the n-queens problems and overcome the challenge of applying NMRA to a discrete space set. An improvement of NMRA is applied using the aspect of local search in the Variable Neighborhood Search algorithm (VNS) with 2-opt and 3-opt. Introducing the Naked Mole Rat algorithm based on variable neighborhood search (NMRAVNS) to solve N-queens problems with different sizes. Finding the best solution or set of solutions within a plausible amount of t

In this work, plasma parameters such as, the electron temperature )Te(, electron density ne, plasma frequency )fp(, Debye length )λD(
and Debye number )ND), have been studied using optical emission spectroscopy technique. The spectrum of plasma with different values of energy, Pb doped CuO at different percentage (X=0.6, 0.7, 0.8) were recorded. The spectroscopic study for these mixing under vacuum with pressure down to P=2.5×10-2 mbar. The results of electron temperature for X=0.6 range (1.072-1.166) eV, for X=0.7 the Te range (1.024-0.855) eV and X=0.8 the Te is (1.033-0.921) eV. Optical properties of CuO:Pb thin films were determined through the optical transmission method using ultraviolet visible spectrophotometer within the ra

 The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.                                                          

Among the problems that appear as a result of the use of some statistical methods I

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

    The digital world has been witnessing a fast progress in technology, which led to an enormous increase in using digital devices, such as cell phones, laptops, and digital cameras. Thus, photographs and videos function as the primary sources of legal proof in courtrooms concerning any incident or crime. It has become important to prove the trustworthiness of digital multimedia. Inter-frame video forgery one of common types of video manipulation performed in temporal domain. It deals with inter-frame video forgery detection that involves frame deletion, insertion, duplication, and shuffling. Deep Learning (DL) techniques have been proven effective in analysis and processing of visual media. Dealing with video data needs to handle th

Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve