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

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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

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

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

The experiment was conducted at the plant tissue culture laboratory of the Department of Horticulture and Garden Engineering College of Agricultural Engineering Sciences, University of Baghdad, in order to study the effect of some growth regulators on propagation an stimulation production of volatile oil compounds of rosemary plant Rosmarinus officinlis using two vegetative parts (apical and lateral buds). Factorial experiment was implemented in completely randomized design with twenty replications. The results indicated that culturing the apical meristem on the medium Murashige and Skoog (MS) media with 0.5 mg.l-1 (BA) with 0.1 mg.l-1 of NAA gave the highest response rate of 100%. As for the doubling stage, the levels of BAA and IAA (Indol