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Employment aesthetic of digital technology for color in the film novelist: نجيـــــب أصليـــــوة حيــــــــــــــدو
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Find all boils down to is marked with (recruitment aesthetic of digital technology for (color) in the film novelist) And the relationship between the aesthetic employment of digital technology for (color) and its impacts on the level of artistic creativity through digital technology and its impacts on the technical and completed the final film in the film.Search and distributed at five chapters The first chapter discusses the methodological framework of the research, which included the research problem and is as follows:What is the digital technology to enrich color in the context in the film narrative to reflect the dramatic effect?And the importance of research and its objectives, including:1 - Employment aesthetic of digital technology for (color) in the film narrative.2 - the relationship of digital technology to embody film processors.And the limits of research and definition of key terms that came in the research.And the second chapter, a theoretical framework and previous studies. The distribution of the theoretical framework on three topics, The first section contains a historical extrapolation of the path of evolution for (color) in the cinema and the developments of digital technologies for (color) in the picture film.The second topic dealt with technical and aesthetics of film creativity.The third topic addressed the role of technology in the directorial processors, and ideas in the text of the films through incorporation of these processors and the various levels.In the third chapter, which has been allocated to research procedures, which included the research methodology, and appointed are:Lord of the Rings Part III - Return of the King, in 2003 .And the research community and his tool and the unit of analysis and the analysis steps and then the fourth quarter Filmed analysis of the sample.The fifth chapter Consisted the results, including:1 - The color of the digital technology has the ability to achieve shades of color in the display image of the film more than the normal film.As well as the conclusions reached by the researcher, including:1 - Whenever you add aesthetic techniques developed image with high accuracy and be more convincing.Well as the recommendations and proposals. It must for this type of research to contain the sources support the process of scientific research

 

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Publication Date
Sun Nov 01 2020
Journal Name
Solid State Technology
Forecasting Crop Coefficient Values for Cucumber Plant (Cucumis sativus)
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Publication Date
Sun Jan 01 2017
Journal Name
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Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

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Podophyllin 25% as alternative effective topical therapy for keratoacanthoma
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Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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