Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

Introduction: Different surgical techniques used for closure of various oral defects. While each one of these techniques has its limitation; the buccal pad of fat used in last quarter of last century as pedicle or free graft in reconstruction of small to medium, congenital and acquired defects showed good potentials for success. The present study used the BPF as pedicled flap to reconstruct intra oral defects. The study aimed to evaluate of the success of buccal pad of fat pedicled flap in the reconstruction of intra oral defects. Outlining its indications, limitations and complications. Materials and Methods: The study included 19 patients (17 males and 2 females) with age range between (1- 70 years), all patients were treated with pedic

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Iraqi kaolin was used for the preparation and characterization of NaY zeolite for biodiesel production via esterification reaction. Oleic acid was used usually as a typical simulated feedstock of high acid number for the esterification reaction.

   The chemical composition for the prepared Nay zeolite is as following:  (Ca₂.6Na₁.K_0.1)(Al₆.3Si₁₇.₇)O₄₈.16H₂O, the silica to alumina ratio in the prepared catalyst was found equal to 2.6 and Na₂O content was 12.26 wt. %, with relative crystallinity equal to 147.4 % obtained by the X-ray diffraction. The surface area result shows that the prepared catalyst has 330 m²

This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

Expansive soil is one of the most serious problems that face engineers during the execution of any infrastructure projects. Soil stabilization using chemical admixture is one of the most traditional and widespread methods of soil improvement. Nevertheless, soil improvement on site is one of the most economical solutions for many engineering applications. Using construction and demolishing waste in soil stabilization is still under research., The aim of this study is to identify the effect of using concrete demolishing waste (CDW) in soil stabilization. Serious tests were conducted to investigate the changes in the geotechnical properties of the natural soil stabilized with CDW. From the results, it is concluded that the

Ultraviolet spectrophotometric studies for antibiotic (amino glycoside) derivatives including, Neomycin, Streptomycin, Gentamycin and Kanamycin with special reagents, which are benzoyl chloride; benzene sulfonyl chloride, toluenesulfonyl chloride and phthalic anhydride were made. Amino glycosides derivatives were followed through measurements of the ultraviolet absorbance (A) from which the absorptivity (ε) of the complexes was deduced and molar absorbances using Ultraviolet for products and calculate the number of reagents molecule that combine to amino glycosides.