The study included adding antimony oxide to mixtures of coating metal surfaces (Enameling), after it was selected ceramic materials used in the coating metal pieces of the type of steel and cast iron in two layers. The first is called a ground coat and the second is a cover coat.
Ceramic materials layer for ground coat have been melted down in
platinum crucible at a temperature of 1200oC to prepare the glass
mixture (Frit). It was coated on metals at a temperature of 780oC for
two minutes, while the second layer was prepared glass mixture
(Frit) at a temperature of 1200oC, but was coated at a temperature of
760oC for two minutes.
Underwent tests crystalline state of powders (Frits) and enameled samples using X-ray diffraction technique and found that the process of powders and ground coat layer is random, while the cover layer included having developed a silicon oxide and titanium oxide phases. It was measured density, coating thickness and Knoop hardness for each layer. As well as practical tests conducted dipping enameled samples in diluted and concentrated sulfuric acid, as well as diluted and concentrated hydrochloric acid for three days at a temperature of 100oC. The samples showed good resistance against these acids. The addition of antimony oxide reduced the presence of bubbles in the coated cast iron and enhancement physical and mechanical properties.
A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a
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