The study was reflection of the impact of the widespread use of polymer Novolak composite reinforced Glass fiber and Asbestos fiber once again with weight fraction 60% on the physical properties, which included (Hardness, Compressive deformation, compressive modulus of elasticity, Flexural modulus of elasticity, Resilience modulus, the maximum of Flexural strength, Flexural strain energy and Shear strength inner layers); it is known how much important the media as a source of bacterial contamination, which contributes directly or indirectly in the process of aging of these materials. These Novolak composite reinforced, prepared by weight fraction of (10%) and (14%) of the Hexamethylene-tetraamine (HMTA) hardener material. It showed the results of the comparison, the composite prepared to offer bacterial media, negatively effect on Hardness, Compressive strengths, Flexural strength and Flexural strain stored energy The research also concluded clear results, which is that there is the possibility to delay the aging process of the presence of bacterial circles, using glass fibers in the polymer Novolak composite reinforced, more than it is the use of asbestos fiber. And increase the weight fraction of hardener material to be 14%, coefficient of resilience reversal less than it is in the rest of the models, which leads to raise the value of the work done at the end of proportionality.
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Under-reamed piles defined by having one or more bulbs have the potential for sizeable major sides over conventional straight-sided piles, most of the studies on under-reamed piles have been conducted on the experimental side, while theoretical studies, such as the finite element method, have been mainly confined to conventional straight-sided piles. On the other hand, although several laboratory and experimental studies have been conducted to study the behavior of under-reamed piles, few numerical studies have been carried out to simulate the piles' performance. In addition, there is no research to compare and evaluate the behavior of these piles under dynamic loading. Therefore, this study aimed to numerically investigate bearing capaci
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It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlighting the diff
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Finite Element Approach is employed in this research work to solve the governing differential equations related to seepage via its foundation's dam structure. The primary focus for this reason is the discretization of domain into finite elements through the placement of imaginary nodal points and the discretization of governing equations into an equation system; An equation for each nodal point or part, and unknown variables are solved. The SEEP / W software (program) is a sub-program of the Geo-Studio software, which is used by porous soil media to compensate for the problems of seepage. To achieve the research goals, a study was carried out on Hemrin dam, which located in the Diyala River 100 km northeast of Baghdad, Iraq. Thus, o
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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
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Objective: The study aim to evaluate secondary schools students' exposure to risk factors in Al-Najaf City. Methodology: Descriptive study conducted in Al- Najaf City/Iraq on students at secondary schools, those aged (12-24) years old, for the period from the 13ed of November 2015 and up to 4ed of August 2015. The sample included secondary school from those schools . Data is collected through a constructed questionnaire, reliability and students (intermediate and secondary) (540) student; (270) male and (270) females who are selected randomly content validity process has been determined for the instrument. Dat