Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

The waste material problem in today's world has become a major topic affecting all sectors of human life. Researchers are interested in providing solutions for each kind of waste material. Waste glass is one of the waste materials whose amounts increase daily. This article deals with two types of modified cement mortar with glass granular in the masonry wall to find their effect on the wall's property (direct tensile, flexural, and compressive bond strength). Seven different mixes were prepared according to the used glass granular ratio (three mixes contained white glass with 15, 20, and 25% while three of them contained green glass granular 5, 10, and 15%, and the last mix was a controlled mix which contains no glass gr

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

The research aims to identify the bedroom furniture designs for children who are in ages range between (4-6) years and the rate of employing them in developing their aesthetic sense. To achieve this objective, the researchers developed the two research tools represented by a analysis-description form of bedroom furniture designs included a number of domains that were represented in the shapes, colors, and sizes of the furniture, as well as the availability of the safety factor, ease of use, cleaning and movement. As for the aesthetic sense scale included (30) paragraphs and alternatives (always, sometimes, never), they were distributed among a representative sample of (170) mothers of children were chosen randomly from (17) kindergartens

     University Campuses, as any lively physical entity, is subject to continuous variation due to . growth, development and change. This reality covers the existing or futuristic additives or  additions, consecutively these changes may have a strong sensation of disorientation as a result of formatic changes in buildings, or in movement paths. And it epitomized the research problem to "the need for knowledge to clarify the impact of intellectual and executive policy in achieving coherence, functional and space organization of the elements of the university urban environment and in the stages of future growth and change,"  the search targeted "to highlight the study of constraction politics on campus Bmqomad

DBNRSK Sayed, Journal of Strategic Research in Social Science (JoSReSS), 2020