The main objective of the present work is to find a method increases the efficiency of the airfoil that is used for blade in wind turbine, wing in aircraft, propeller and helicopter (like NACA 4412). By overcoming the separation of flow at high angle of attacks, a slotted airfoil had been used and solved numerically through connecting the pressure side in the bottom surface with the suction side in the top surface of the airfoil to energize the separated flow. Slot exit, width and slope were considered as a parameters of slot configuration to determine the effective design of consideration. Reynolds number was taken as [1.6 x106 ] and the angle of attacks were ranged from (0o - 20o ). The numerical solution with Ansys Fluent commercial program had been used to solve a fully turbulent N.S. equations with κ-ω SST turbulence model. The method of changing variables with best one among them was adopted to find the design of the slot. The results of flow field and airfoil characteristics for solid and slotted airfoil were described and illustrated in the present work which showed that the airfoil produces higher lift coefficient value and lower drag coefficient as compared with solid airfoil. Moreover, it delays stalling angle of attack to 19o . The slotted airfoil shows an increasing in maximum lift to drag ratio up to 110% at angle of attack 18o . The most effective slot is found at 60% chord, slope 65o and width 1% chord.
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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This researchs the preparation of particulate polymer composites from Alkyd resin and Iraqi Burn Kaolin which were added as (20%,30%,40%,50%)and comparing with the polymer. It studied Thermal conductivity and Dielectric strength for both of the Alkyd resin and the Composite Material. The result showed an increase in Dielectric strength after adding the Iraqi Burn Kaolin , also the Thermal conductivity was increased by adding the Iraqi Burn Kaolin .
A concept of indoor solar illumination is described and simulated. The solar illumination system is composed of a tracking primary reflector, a selective secondary reflector, a visible light guide and a scattering solid glass tube fixture. Each part of the solar illumination system is optically suited and compatible with other parts to realize high efficiency. The simulation is conducted for Baghdad city for a library hall. Two major days over a year are chosen to investigate the illumination system for acceptable visible light level for reading hall. The two days are: summer solstice day and winter solstice day at 8:00 AM and 12:00 PM for each. Research results showed that the design of the solar system is achieved on the base of minimu
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To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.
E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.
A total of 63 patients with periodontitis (case) and 35
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This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s
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Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
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