Concentrated research topic in addressing variable vital to the work of offices of inspectors general, construction and scale effectiveness and efficiency is the organizational structure, which are important as is obvious to any researcher in the management and organization and this variable would affect the exercise task supervision and inspection of financial and administrative corruption and combat efficiently, Thus this effect will be placed in the fold ability to achieve goals. That the creation of the organizational structure and requirements to achieve harmony between its properties is creating step towards success. This research aims to analyze the characteristics and style o

          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

The fluctuation and expansion ratios have been studied for cylindrical gas-solid fluidized columns by using air as fluidizing medium and Paracetamol as the bed material. The variables were the column diameter (0.0762, 0.15, and 0.18 m), static bed height (0.05, 0.07, and 0.09 m), and air velocity to several times of minimum fluidization velocity. The results showed that both the fluctuation and expansion ratios had a direct relation with air velocity and an inverse one with column diameter and static bed height. A good agreement was between the experimental results and the calculated values by using the correlation equations from the literature.

Giardiasis is an infection caused by the protozoan flagellate parasite Giardia spp. in the intestine. G duodenalis, a species complex of diverse genotypes that tend to demonstrate host specificity, is responsible for most veterinary health related infections; production animals, companion animals, and wildlife can all be infected. Abdominal pain and diarrhea, typically accompanied by steatorrhea, are the most common symptoms of Giardiasis. Cysts or antigens in feces are commonly used to diagnose the disease. Treatment regimens vary and are dependent on the indication. Control methods must include hygiene measures. Despite direct evidence of Giardia sp transmission to humans via polluted water supplies, our analysis will focus on some r

The psychological burnout is considered one of dangerous phenomenon’s which appeared in the 70s of the 20th century and suffered by most of the society classes. It is a term which the wide uses and various meaning like emotional, mental, and physical exhaustion and chronic weak exhaustion. The presented research aims t identify the psychological burnout as for the Kindergarten teacher and the differences significance according to the variations (Kindergarten type: private or govern mental). The research sample contains 400 female teachers divided to 170 governmental Kindergarten teachers and 230 private Kindergarten teachers. The researcher prepared a measurement method to measure the psychological burnout for those teachers after

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number