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Reconstruction of Three-Dimensional Object from Two-Dimensional Images by Utilizing Distance Regularized Level Algorithm and Mesh Object Generation
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Three-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and constructed a low-cost three-dimensional object scanner. We have proposed a 3D canal reconstruction system (ear or nose) based on using 2D images for reconstruction 3D object. A low-cost EndoScope with a proposed program based upon utilized the segmentation algorithm type “Distance Regularized Level” to segment active edges from images then generate mesh object in order to generate 3D structure for small canals or cracks. The results show good accuracy of the reconstructed object in both details and their measurements which are related to the success in the reconstruction of algorithm that yields good three-dimensional meshes object.

 

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Study the Efficiency of Two Concentrations from Algae Cladophora glomerata Extract on the Giardia lamblia parasite
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Giardia lamblia parasite was isolated from the diarrhea samples of patients with Giardiasis dysentery and was developed in HSP media, four mice groups have been used to find in vivo efficacy of two concentrations (128,256) mg/ml of chlorophorm extracts from Cladophora glomerata algae against Giardia lamblia parasite  as compared with (Flagyl) by measuring several biochemical markers as ( GPT and GOT) enzymes ,sodium ,potassium and iron concentration as well as counting the number of parasitic cysts in each mice groups. The results demonstrate that levels of GPTA GOT enzymes have been decreased in mice treated with algal extract. As for the concentration of the Sodium, Potassium and Iron increased in mice treat

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Genetic Algorithm Based PID Controller Design for a Precise Tracking of Two-Axis Piezoelectric Micropositioning Stage
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 In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th

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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Measurement of the distance to the central stars of Nebulae by using Expansion methods with Alladin Sky Atlas
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Abstract<p>The usual methods of distance determination in Astronomy parallax and Spectroscopic with Expansion Methods are seldom applicable to Nebulae. In this work determination of the distances to individual Nebulae are calculated and discussed. The distances of Nebulae to the Earth are calculated. The accuracy of the distance is tested by using Aladin sky Atlas, and comparing Nebulae properties were derived from these distance made with statistical distance determination. The results showed that angular Expansions may occur in a part of the nebulae that is moving at a velocity different than the observed velocity. Also the results of the comparison of our spectroscopic distances with the trig</p> ... Show More
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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Creating a Conductive Surface of the PMMA by Laser Cladding with DWCNT and MWCNTS
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This work studied the electrical and thermal surface conductivity enhancement of polymethylmethacrylate (PMMA) clouded by double-walled carbon nanotubes (DWCNTs) and multi-walled carbon nanotube (MWCNTs) by using pulsed Nd:YAG laser. Variable input factors are considered as the laser energy (or the relevant power), pulse duration and pulse repetition rate. Results indicated that the DWCNTs increased the PMMA’s surface electrical conductivity from 10-15 S/m to 0.813×103 S/m while the MWCNTs raised it to 0.14×103 S/m. Hence, the DWCNTs achieved an increase of almost 6 times than that for the MWCNTs. Moreover, the former increased the thermal conductivity of the surface by 8 times and the later by 5 times.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of South Asian Federation Of Obstetrics And Gynaecology
Effect of Leptin Level in Pregnancy Complicated by Preeclampsia and Pregnancy Outcome
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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Fri Sep 01 2023
Journal Name
Civil Engineering Journal
Fundamental Challenges and Management Opportunities in Post Disaster Reconstruction Project
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The study examines the root causes of delays that the project manager is unable to resolve or how the decision-maker can identify the best opportunities to get over these obstacles by considering the project constraints defined as the project triangle (cost, time, and quality) in post-disaster reconstruction projects to review the real challenges to overcome these obstacles. The methodology relied on the exploratory description and qualitative data examined. 43 valid questionnaires were distributed to qualified experienced engineers. A list of 49 factors causes was collected from previous international and local studies. A Relative Important Index (RII) is adapted to determine the level of importance of each sub-criterion in the fou

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Recycling of Chicken Egg Shells into Nanopowder: Synthesis, and its Properties
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Increase in unconventional resources of calcium (Ca+2) for fowls, aquaculture and native animals was improved. This work was planned to define the most polymorph of calcium carbonate (CaCO3) that take place in the two types of chicken eggshells (local and imported type). In this research, the comparative analysis of calcium carbonate (CaCO3) content was approved for nominated eggshells of native strain and imported chicken via Field Emission Scanning Electron Microscope (FESEM), Transmission Electron Microscope (TEM), Fourier-Transform Infrared Spectroscopy (FTIR) and Powder X-Ray Diffraction (PXRD) analysis. The results demonstrate that native and imported chicken eggshells comprise calcite morph that ha

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