ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, auto

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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

This study seeks to shed light on the aspects of visual pollution and its impact on the aesthetics of the town of Al-Eizariya known to suffer from the phenomenon. In order to identify the real causes of the problem which develops in various forms and patterns, threatening not only the aesthetic appearance of the towns, but also causes the emergence of new problems and phenomena that will have negative repercussions on the population. The researcher uses the analytical descriptive method to analyze the phenomenon of visual pollution in terms of reality, development, manifestations and spread and uses photos which document the visual pollution and its impact on the aesthetics of the known. The study concluded the existence of a strong rela

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The researcher attempts to examine Barman model in acquiring the historical concepts among fourth-grade students at literary classrooms. To this end, the researcher held the null hypothesis, there is no significant difference between the experimental groups who was taught based on Barman model and the control group that taught based on the traditional method in acquiring the historical concepts on the post-test. To testify the effectiveness of Barman model, the researcher administered a questionnaire included (60) items on bunch of female-students who were selected from al-khamaeal preparatory school in al-hurriyah district in Baghdad. The author utilized different statistical tools to analyze the collected data.    &