The aim of this study is to know the effect of different percentages of chitosan added to drinking water on the weight and quality of quail meat, physical anatomy in terms of (the body of the long carcass, the girth of the chest, the length of the thigh bones, the thigh racket, the fullness of the chest), chemical analysis (protein, moisture, fat and ash) and sensory evaluation of quail meat. It was purchased 320 Iraqi-origin birds of quail and one day old. Chicks were randomly distributed to three equal groups' treatments and treated with chitosan and added to the drinking water: the first treatment (0.1 gm./L water only as a control treatment), the second treatment (0.2 gm./L of chitosan was added to the drinking water) and the

Some degree of noise is always present in any electronic device that
transmits or receives a signal . For televisions, this signal i has been to s the
broadcast data transmitted over cable-or received at the antenna; for digital
cameras, the signal is the light which hits the camera sensor. At any case, noise
is unavoidable. In this paper, an electronic noise has been generate on
TV-satellite images by using variable resistors connected to the transmitting cable
. The contrast of edges has been determined. This method has been applied by
capturing images from TV-satellite images (Al-arabiya channel) channel with
different resistors. The results show that when increasing resistance always
produced higher noise f

             The centers of cities and historical quarter are exposed to a severe threat to the values of the physical and legal urban environment as a result of the value deterioration and the emergence, emergence and spread of new values on the intellectual and urban context, which generates the loss of the urban environment for its spatio-temporal continuity, flexibility, adaptation and continuity, and thus urban obsolescence, Hence the problem of the research in “the lack of comprehensiveness of studies on the phenomenon of urban obsolescence and its impact on the decline in the values of the quality of the built environment in historic

High temperature superconductor with nominal composition Bi1.6Pb0.4Sr1.8Ba0.2Ca2 Cu3O10+? was prepared by solid state reaction method. Two sets of samples have been prepared .The first one was quenched in air; the second set was quenched in liquid nitrogen. X-ray diffraction analyses showed an orthorhombic structure with two phases, high –Tc phase (2223) and low-Tc phase (2212) in addition to that impure phase was found. It has been observed that quenched in air samples display a sharp superconducting transition and a higher-Tc phase than that of the quenched in liquid nitrogen samples.

The ratio of draft tube to reactor diameters is of decisive importance for the operation behavior of air lift loop reactors. The influence of draft tube geometry was investigated with respect to oxygen mass transfer and mixing time. The diameter ratio was varied between 0.33 and 0.80. The measurements were performed in two loop reactors with liquid capacities of 11.775 and 26.49 liters using aqueous with solutions of different coalescence behavior. The results show that there is no single diameter ratio which would produce most favorable conditions for the two process parameters. With respect to the more important requirements of aerobic cultures, i.e high oxygen mass transfer and efficient mixing, a diameter ratio between 0.5 and 0.6 is

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

In this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class