Freedom of opinion and expression occupy the first place among the concerns of countries and international organizations. And it is also the basis of contemporary freedom because it is the foundation for achieving freedom in other fields such as politics, economics, education, etc.. The constitutions of the state have ensured that almost the entire freedom to express an opinion in all its forms either orally or writing or images of expressions, but these freedoms are identified within the law. Most countries announced their commitment to the international conventions and texts issued by international and regional organization like the Universal Declaration of Human Rights in 1948, and the International Covenant on Civil and Political Rig

In this work, electrochemical process was presented to polymerized eugenol on Gr.2 and Gr.5 titanium alloys before and after treated by Micro Arc Oxidation (MAO), where Gr.2 is commercial pure titanium and Gr.5 is Ti-6Al-4V dental alloys. The deposited layers were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The adhesion strength of polymeric thin-film was estimation by using pull-off adhesion test and the result was the adhesion strength of PE was (1.23 MPa) on Gr.2 before MAO and increase to (1.98 MPa) on Gr.2 after MAO treatment. The corrosion behavior of Gr.2 and Gr.5 alloy in artificial saliva environment at

Total no. of patient (100) stool samples were collected, during the period from February to the end of May of 2008, for children under two years old suffering from non-bloody and bloody diarrhea at (Children Welfare Teaching Hospital) in Baghdad. The study evaluates the relationship between etiological agent of diarrhea and sex, age group, type of feeding, presence of blood in stool of the patients. All samples were examined microscopically to identify parasitic agent and serological test for Rotavirus to identify viral infection, also biochemical and serological tested for specimen's culture on different culture media and antibiotic sensitivity test. Results show from 100 cases 64] represents the etiological agent of diarrhea and

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

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

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