17 research outputs found

    Volumetric rendering techniques for scientific visualization

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    Ankara : The Department of Computer Engineering and The Graduate School of Engineering and Science of Bilkent University, 2014.Thesis (Ph.D.) -- Bilkent University, 2014.Includes bibliographical references leaves 80-86.Direct volume rendering is widely used in many applications where the inside of a transparent or a partially transparent material should be visualized. We have explored several aspects of the problem. First, we proposed a view-dependent selective refinement scheme in order to reduce the high computational requirements without affecting the image quality significantly. Then, we explored the parallel implementations of direct volume rendering: both on GPU and on multi-core systems. Finally, we used direct volume rendering approaches to create a tool, MaterialVis, to visualize amorphous and/or crystalline materials. Visualization of large volumetric datasets has always been an important problem. Due to the high computational requirements of volume-rendering techniques, achieving interactive rates is a real challenge. We present a selective refinement scheme that dynamically refines the mesh according to the camera parameters. This scheme automatically determines the impact of different parts of the mesh on the output image and refines the mesh accordingly, without needing any user input. The viewdependent refinement scheme uses a progressive mesh representation that is based on an edge collapse-based tetrahedral mesh simplification algorithm. We tested our view-dependent refinement framework on an existing state-of-the-art volume renderer. Thanks to low overhead dynamic view-dependent refinement, we achieve interactive frame rates for rendering common datasets at decent image resolutions. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multi-core parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm support progressive rendering. We compared the GPU implementation with the serial and multi-core implementations. We observed significant speed-ups, that, together with progressive rendering, enabling reaching interactive rates for large datasets. Visualization of materials is an indispensable part of their structural analysis. We developed a visualization tool for amorphous as well as crystalline structures, called MaterialVis. Unlike the existing tools, MaterialVis represents material structures as a volume and a surface manifold, in addition to plain atomic coordinates. Both amorphous and crystalline structures exhibit topological features as well as various defects. MaterialVis provides a wide range of functionality to visualize such topological structures and crystal defects interactively. Direct volume rendering techniques are used to visualize the volumetric features of materials, such as crystal defects, which are responsible for the distinct fingerprints of a specific sample. In addition, the tool provides surface visualization to extract hidden topological features within the material. Together with the rich set of parameters and options to control the visualization, MaterialVis allows users to visualize various aspects of materials very efficiently as generated by modern analytical techniques such as the Atom Probe Tomography.Okuyan, ErhanPh.D

    Pattern information extraction from crystal structures

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    Cataloged from PDF version of article.Determining crystal structure parameters of a material is a quite important issue in crystallography. Knowing the crystal structure parameters helps to understand physical behavior of material. For complex structures, particularly for materials which also contain local symmetry as well as global symmetry, obtaining crystal parameters can be quite hard. This work provides a tool that will extract crystal parameters such as primitive vectors, basis vectors and space group from atomic coordinates of crystal structures. A visualization tool for examining crystals is also provided. Accordingly, this work presents a useful tool that help crystallographers, chemists and material scientists to analyze crystal structures efficiently.Okuyan, ErhanM.S

    Awareness of Pregnant Women for COVID-19 Infection

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    Covid outbreak has been getting worse and spread affected all over the world. Pregnant patients are also vulnerable to respiratory diseases. We aimed to evaluate the awareness, emotional status, and behavior of pregnant during the COVID outbreak. This study's main benefit is to analyze the knowledge and understanding of pregnant women about the pandemic and draw attention to the prevention issues that need improvement. This research is a prospective observational study that 199 patients subjected to a questionnaire including 29 questions about patient characteristics, pregnancy information, knowledge about COVID19-infection, behavioral and emotional changes. 130 (65.3) of the patients stated an above-average knowledge level. Television was the most frequent information source (75.4%, n:150) and was the only information source for 90 (45.1%) of the patients. Sixty-nine patients used more than one information source. More than one prevention method uses by 149 (75%) of the patients. Washing hands (n:183, 92.0%) and cleaning the house (n:122, 61.3%) were the most preferred methods. Only 55 (27.6%) of the patients used a mask for prevention. 88(44.2%) of the patients stated that they preferred a shorter hospital stay, and 75 (37.7%) of the patients indicated that they postponed or avoided the pregnancy follow-up visits due to the COVID-19 issue. Pregnant women seem to be aware and stressed of COVID-19, but knowledge of what to do seems insufficient. Patients informed of risks of COVID infection, unplanned hospital admission, and chances of avoiding necessary visits and home birth demands

    Risk factors associated with adverse fetal outcomes in pregnancies affected by Coronavirus disease 2019 (COVID-19): a secondary analysis of the WAPM study on COVID-19.

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    Objectives To evaluate the strength of association between maternal and pregnancy characteristics and the risk of adverse perinatal outcomes in pregnancies with laboratory confirmed COVID-19. Methods Secondary analysis of a multinational, cohort study on all consecutive pregnant women with laboratory-confirmed COVID-19 from February 1, 2020 to April 30, 2020 from 73 centers from 22 different countries. A confirmed case of COVID-19 was defined as a positive result on real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of nasal and pharyngeal swab specimens. The primary outcome was a composite adverse fetal outcome, defined as the presence of either abortion (pregnancy loss before 22 weeks of gestations), stillbirth (intrauterine fetal death after 22 weeks of gestation), neonatal death (death of a live-born infant within the first 28 days of life), and perinatal death (either stillbirth or neonatal death). Logistic regression analysis was performed to evaluate parameters independently associated with the primary outcome. Logistic regression was reported as odds ratio (OR) with 95% confidence interval (CI). Results Mean gestational age at diagnosis was 30.6+/-9.5 weeks, with 8.0% of women being diagnosed in the first, 22.2% in the second and 69.8% in the third trimester of pregnancy. There were six miscarriage (2.3%), six intrauterine device (IUD) (2.3) and 5 (2.0%) neonatal deaths, with an overall rate of perinatal death of 4.2% (11/265), thus resulting into 17 cases experiencing and 226 not experiencing composite adverse fetal outcome. Neither stillbirths nor neonatal deaths had congenital anomalies found at antenatal or postnatal evaluation. Furthermore, none of the cases experiencing IUD had signs of impending demise at arterial or venous Doppler. Neonatal deaths were all considered as prematurity-related adverse events. Of the 250 live-born neonates, one (0.4%) was found positive at RT-PCR pharyngeal swabs performed after delivery. The mother was tested positive during the third trimester of pregnancy. The newborn was asymptomatic and had negative RT-PCR test after 14 days of life. At logistic regression analysis, gestational age at diagnosis (OR: 0.85, 95% CI 0.8-0.9 per week increase; pPeer reviewe

    Dynamic view-dependent visualization of unstructured tetrahedral volumetric meshes

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    Visualization of large volumetric datasets has always been an important problem. Due to the high computational requirements of volume-rendering techniques, achieving interactive rates is a real challenge. We present a selective refinement scheme that dynamically refines the mesh according to the camera parameters. This scheme automatically determines the impact of different parts of the mesh on the output image and refines the mesh accordingly, without needing any user input. The view-dependent refinement scheme uses a progressive mesh representation that is based on an edge collapse-based tetrahedral mesh simplification algorithm. We tested our view-dependent refinement framework on an existing state-of-the-art volume renderer. Thanks to low overhead dynamic view-dependent refinement, we achieve interactive frame rates for rendering common datasets at decent image resolutions
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