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Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.

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Publication Date
Tue Oct 30 2018
Journal Name
Journal Of Engineering
Active Vibration Control of Cantilever Beam by Using Optimal LQR Controller
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Many of mechanical systems are exposed to undesired vibrations, so designing an active vibration control (AVC) system is important in engineering decisions to reduce this vibration. Smart structure technology is used for vibration reduction. Therefore, the cantilever beam is embedded by a piezoelectric (PZT) as an actuator. The optimal LQR controller is designed that reduce the vibration of the smart beam by using a PZT element.  

In this study the main part is to change the length of the aluminum cantilever beam, so keep the control gains, the excitation, the actuation voltage, and mechanical properties of the aluminum beam for each length of the smart cantilever beam and observe the behavior and effec

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Effecting of pH Parameter on Simulated Wastewater Treatment Using Electrocoagulation Method
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The aim of the present research is to investigate the effecting of pH parameter on the feasibility of lead removal from simulated wastewater using an electrochemical system. Electrocoagulation method is one of electrochemical technology which is used widely to treat industrial wastewater. Parameters affecting this operation, such as initial metal concentration, applied current, stirrer speed, and contact time of electroprocessing were taken as 155ppm, 1.5 Ampere, 150 rpm, 60 minutes respectively. While pH of the simulated wastewater was in the range of  2 to 12 in the experiments. It was found from the results that pH is an important parameter affecting lead removal operation. The best value of pH parameter is appro

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Nondestructive Evaluation of Coatings Delamination Using Microwave Time Domain Reflectometry Technique
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
Wastewater Bio-solids Management for Fertilizer Quality Using Co- composting Process
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Co-composting process can be acquired by combining organic fraction of municipal solid waste (OFMSW) with sewage sludge (SS) and mature compost (MC) as enhancement and bulking agent to overcome the problems of municipal solid waste and wastewater treatment plants besides the finally produced fertilizer usage for agriculture and horticulture. The effects of different mixture ratios of (OFMSW), (SS) and (MC) on the performance of composting process were investigated in this study. Piles of about 10 kg were prepared by mixing OFMSW, SS and MC in three different ratios (w/w) [OFMSW: SS: MC= 3:1:1, 3:2:1, and 3:3:1]. Results showed that the pile [3:1:1] was most beneficial to composting. The final compost products contained a

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
Thermal Buckling of Angle-Ply Laminated Plates Using New Displacement Function
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ABSTRACT

Critical buckling temperature of angle-ply laminated plate is developed using a higher-order displacement field. This displacement field used by Mantari et al based on a constant ‘‘m’’, which is determined to give results closest to the three dimensions elasticity (3-D) theory. Equations of motion based on higher-order theory angle ply plates are derived through Hamilton, s principle, and solved using Navier-type solution to obtain critical buckling temperature for simply supported laminated plates. Changing (α2/ α1) ratios, number of layers, aspect ratios, E1/E2 ratios for thick and thin plates and their effect on thermal

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Publication Date
Wed May 17 2023
Journal Name
Journal Of Engineering
Multicomponent Biosorption of Heavy Metals Using Fluidized Bed of Algal Biomass
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This paper aims to study the biosorption for removal of lead, cadmium, copper and arsenic ions using algae as a biosorbent. A series of experiments were carried out to obtain the breakthrough data in a fluidized bed reactor. The minimum fluidization velocities of beds were found to be 2.27 and 3.64 mm/s for mish sizes of 0.4-0.6 and 0.6-1 mm diameters, respectively. An ideal plug flow model has been adopted to characterize the fluidized bed reactor. This model has been solved numerically using MATLAB version 6.5. The results showed a well fitting with the experimental data. Different operating conditions were varied: static bed height, superficial velocity and particle diameter. The breakthrough curves were plotted for each metal. Pb2+ s

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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology &amp; Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improvement Marshall Properties of Hot Mix Asphalt Concrete Using Polyphosphoric Acid
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Modified asphalt is considered one of the alternatives to address the problems of deficiencies in traditional asphalt concrete, as modified asphalt addresses many of the issues that appear on the pavement layers in asphalt concrete, resulting from heavy traffic and vehicles loaded with loads that exceed the design loads and the large fluctuations in the daily and seasonal temperatures of asphalt concrete. The current study examined the role of polyphosphoric acid (PPA) as a modified material for virgin asphalt when it was added in different proportions (1%, 2%, 3%, 4%) of the asphalt weight. The experimental program includes the volumetric characteristics associated with the Marshall test, the physical properties, and th

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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Experimental and Numerical Analysis of Expanded Pipe using Rigid Conical Shape
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The experimental and numerical analysis was performed on pipes suffering large plastic deformation through expanding them using rigid conical shaped mandrels, with three different cone angles (15◦, 25◦, 35◦) and diameters (15, 17, 20) mm. The experimental test for the strain results investigated the expanded areas. A numerical solution of the pipes expansion process was also investigated using the commercial finite element software ANSYS. The strains were measured for each case experimentally by stamping the mesh on the pipe after expanding, then compared with Ansys results. No cracks were generated during the process with the selected angles. It can be concluded that the strain decreased with greater angles of con

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