Recently, the development and application of the hydrological models based on Geographical Information System (GIS) has increased around the world. One of the most important applications of GIS is mapping the Curve Number (CN) of a catchment. In this research, three softwares, such as an ArcView GIS 9.3 with ArcInfo, Arc Hydro Tool and Geospatial Hydrologic Modeling Extension (Hec-GeoHMS) model for ArcView GIS 9.3, were used to calculate CN of (19210 ha) Salt Creek watershed (SC) which is located in Osage County, Oklahoma, USA. Multi layers were combined and examined using the Environmental Systems Research Institute (ESRI) ArcMap 2009. These layers are soil layer (Soil Survey Geographic SSURGO), 30 m x 30 m resolution of Digital Elevation Model (DEM), land use layer (LU), “Look–Up tables” and other layers resulted from running the software. Curve Number which expresses a catchment’s response to a storm event has been estimated in this study to each land parcel based on LU layer and soil layer within each parcel. The results showed that a CN of 100 (dark Blue) means surface water. The high curve numbers (100 -81) (Blue and light Blue) corresponding to urbanized areas means high runoff and low infiltration; whereas low curve numbers (77- 58) (Brown and light Brown) corresponding to the forested area means low runoff and high infiltration. Four classes of land cover have been identified; these are surface water, medium residential, forest and agriculture.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreVisualization of subsurface geology is mainly considered as the framework of the required structure to provide distribution of petrophysical properties. The geological model helps to understand the behavior of the fluid flow in the porous media that is affected by heterogeneity of the reservoir and helps in calculating the initial oil in place as well as selecting accurate new well location. In this study, a geological model is built for Qaiyarah field, tertiary reservoir, relying on well data from 48 wells, including the location of wells, formation tops and contour map. The structural model is constructed for the tertiary reservoir, which is an asymmetrical anticline consisting of two domes separated by a saddle. It is found that
... Show MoreBrain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining
... Show MoreCoaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi
... Show MoreThe theme of this Study presents analysis and discuss to the "Share the framework for assessing inflation," a practical study in a sample of joint stock companies listed on the Iraq Stock Exchange for the years (2009-2013). To determine the extent of the disparity between the nominal value of shares (Nominal Value) before deducting inflation and the real value (Real Value) per share, after deducting inflation in the case of zero growth. The study relied on annual reports of the companies of the research sample of the Iraq Stock Exchange, as well as the Iraqi Securities Commission. Besides the annual reports issued by the Ministry of Planning, as well as annual reports and statistical bulletin issued by the Central Bank of Iraq. It is fra
... Show MoreThe study of topography most important studies and depth of any literary or artistic text and occupy the thinking of many who work in art at generally. There is hardly any film scenario from description in general of the indispensable elements of the composition and place one. So the place starts form since the scriptwriter begins to view the result of the description begins to feature the emergence of there are simple operations in the scenario soon to receive growth as a final achievement in the film. The description of the place begins to take on an allegorical character as a language version in the script, soon translated into another language, the language of the picture. Which in turn complement the creative ring of cinematic art a
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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