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bsj-3009
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 Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Thu Jul 09 2020
Journal Name
Agrosystems, Geosciences & Environment
Yield and quality of three potato cultivars under series of nitrogen rates
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Undesirable growth of potato (Solanum tuberosum L.) crop under an excessive N fertilizer application is the main obstacle presently. This research was conducted to investigate the response of different potato cultivars; Russet Burbank, Shepody, and Superior, and its qualitative characteristics under a series of N rates. Six rates of N fertilization (0–280 kg ha−1) were applied on 11 sites in a randomized complete block design, with four replications. Sites with ≥30 g kg−1 of soil organic matter (OM) produced total tuber yield, marketable yield, and tuber weight per plant 39.5, 45.2, and 54.9%, respectively, higher than sites with ≤30 g kg−1 of OM. Tubers specific gravity increased by 0.18% in the sites with ≥30 g kg−1 of OM.

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Re-engineering management processes and its impact on the strategic decision-making process Field study on the College of Education / University of Mustansiriya / Iraq
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The aim of the research is to identify both the re-engineering of management processes and the strategic decision-making process in the research community and determine the nature of the correlation between the two variables and know the relationship between them to achieve the research goal. The researcher used a descriptive and analytical method. The research community consists of a group of professors and staff of the College of Education affiliated to the University of Mustansiriya in Baghdad, which their number were (45),  the researcher has distributed the forms to all members of the sample,  only (3) forms were excluded for invalidity and thus the number of forms approved in the analysis were (42) forms. The rese

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Publication Date
Sun Sep 03 2023
Journal Name
مجلة درااست دولية
بناء الدولة في الفكر السياسي لجون راولز
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تعد مسالة بناء الدولة احدة المواضيع المهمة في حقل الدراسات السياسية والتي تعكس مظهراً متعدد الابعاد لمبدأ الثقة المنشود بين الحاكم والمحكوم، فمنذ أمد طويل تحاول الدول تحقيق تنميتها السياسية والبحث عن مقومات ترشيد سياسي لقدراتها المؤسساتية والوظيفية بهدف تعزيز اسس التكامل والاندماج بين المجتمع السياسي والمجتمع المدني. عليه انطلق جون راولز في مفهومه لبناء الدولة المعاصرة من بناء المجتمع العادل، فالعدالة ه

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Investigating the Aerodynamic Surface Roughness Length over Baghdad City Utilizing Remote Sensing and GIS Techniques
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This study calculated the surface roughness length (Zo), zero-displacement length (Zd) and height of the roughness elements (ZH) using GIS applications. The practical benefit of this study is to classify the development of Baghdad, choose the appropriate places for installing wind turbines, improve urban planning, find rates of turbulence, pollution and others. The surface roughness length (Zo) of Baghdad city was estimated based on the data of the wind speed obtained from an automatic weather station installed at Al-Mustansiriyah University, the data of the satellite images digital elevation model (DEM), and the digital surface model (DSM), utilizing Remote Sensing Techniques. The study area w

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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model
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In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Tolerance and its impact on building society
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Tolerance and its impact on building society

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Mental-math level of intermediate school students
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The study seeks to explore the mental-math level among intermediate-school students. To this end, the researcher raised a question. What the level of mental math among students in the intermediate stage? Total of (576) male and female students were chosen from different schools at Al-karkh side \ general directorate of Baghdad education. So as to answer research question and hypothesis, a questionnaire of (30) items designed by the authors was administered to the study sample. T-test was used to analyze the collected data at the level of significance (0.05). Expectancy means (15) showed significant difference comparing to the achieved mean (10, 10) on mental-math test. The study concluded with students has a low level of mental math. The

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Publication Date
Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improving the Network Lifetime in Wireless Sensor Network for Internet of Thing Applications
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Mobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kern

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