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

This is a research that deals with one of the topics of Arabic grammar, namely, the plural noun, and it is not hidden from the students the importance of grammatical topics in preserving the tongue from melody, and what it has of fundamental importance in knowing the graphic miracles of the Qur’an, and I called this research:

(plural noun in Arabic a grammatical study)

This study Arabic dialect prevailing in the province of Khuzestan [southwest Islamic Republic of Iran] as one of the Arabic dialects abundant qualities and characteristics of linguistic entrenched in the foot, which includes among Tithe thousands composed of vocabulary and structures and phrases classical that live up to the pre-Islamic era, if what Tasha researcher and reflect accurately the find of a large number of phrases and vocabulary and acoustic properties by nature accent, and formal, and nature of the synthetic, and characteristics semantic and contextual in this dialect studied without being something of them heavy on the tongue and without displays her tune or Tasha or distortion and so on all of which constitute a catalyst i

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

Abstract:

               The aim of the research is to evaluate the practice of banking departments for strategic foresight represented by its dimensions (environmental scanning, future vision, scenarios, reconfiguration) and its relationship to the organizational brilliance represented by dimensions (brilliance of leadership, brilliance of service and innovation, brilliance of knowledge, brilliance of employees), as the research was applied in A number of private Iraqi commercial banks represented by (Baghdad, Iraqi Investment, Iraqi Middle East Investment, Commercial Gulf, Ashur International Investment, Al Mansour Investment, Via Iraq Invest

Abstract

The experiment has been carried out in the Syrian National Commission of Biotechnology, during the growing season 2018/2019, to study the effect of abiotic stresses (salinity and osmotic stresses) on the activity of some antioxidant enzymes and biochemical traits in Catharanthus roseus. The experiment has been laid according to (CRD) with three replications. The seeds have been sterilized by NaOCl solution (0.5% v/v), then planted on MS medium. Plantlets have been moved to MS medium enriched with NAA (1 mg.L^-1) and BA (2 mg.L^-1). The callus has been initiated from leaves using MS medium containing NAA (1 mg L^-1) and KIN (2 mg.L^-1). After 60 days, callus

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

The study aimed at the following:

    Identify the differences in average scores core  thinking skills kindergarten children by variable sex (male - female), and by variable age (5.6 - 5.11).

To achieve this researcher adopted a standardized test of core thinking skills for the kindergarten children, which was built and standardization by the researcher Meyada Asaad Mussa 2012 . applied test on a sample of (814) ) boys and girls who were randomly chosen form,  from directorates of Baghdad Education Adoption of the proportional distribution.