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21 results for “triangulation”
Regular full triangulations of the 3-dilated 3-simplex
<p>This dataset contains the 21 125 102 regular full triangulations of the 3-dilated 3-simplex, computed by mptopcom. The data is given up to symmetry, i.e. we have one triangulation from every orbit. The file `3d3.dat` is the input file for mptopcom, which was called with the `--regular` and `--full` flags. The output is in the file `3d3_regular_full.result.xz`.</p>
Regular unimodular triangulations of the 3-dilated 3-simplex
<p>This dataset contains the 14 373 645 regular unimodular triangulations of the 3-dilated 3-simplex, computed by mptopcom. The data is given up to symmetry, i.e. we have one triangulation from every orbit. The file `3d3.dat` is the input file for mptopcom, which was called with the `--regular` and `--full` flags. This output was then filtered by a perl script to receive the unimodular triangulations only. The output is in the file `3d3_regular_unimodular.result.xz`.</p>
Regular triangulations of the Hypersimplex(3,6)
<p>This dataset contains the 42 489 025 regular triangulations of the Hypersimplex(3,6) computed with mptopcom. The triangulations were computed up to symmetry and the result contains one representative from every orbit. The dataset is structured as follows:</p> <ul> <li>`hypersimplex_3_6.dat` contains the input points and the group acting.</li> <li>`hypersimplex_3_6.result.*.xz` contains the output from mptopcom.</li> <li>`hypersimplex_3_6.job.auto` is the cluster script used to produce these triangulations.</li> <li>`hypersimplex_3_6.checkp.*` are the checkpoints between the different result files.</li> </ul> <p>Since the computation was too large, it had to split up into four parts.</p>
Regular triangulations of the Hypersimplex(2,7)
<p>This dataset contains the 30 485 496 regular triangulations of the Hypersimplex(2,7) computed with mptopcom. The triangulations were computed up to symmetry and the result contains one representative from every orbit. The dataset is structured as follows:</p> <ul> <li>`hypersimplex_2_7.dat` contains the input points and the group acting.</li> <li>`hypersimplex_2_7_reg.result.*.xz` contains the output from mptopcom.</li> </ul> <p>Since the computation was too large, it had to split up into eleven parts.</p>
Repository of Thoracolumbar Spine Triangulated Meshes
<p><em><strong>Repository of Thoracolumbar Spine Triangulated Meshes:</strong></em></p> <ul> <li>42 stereolithography (stl) files (.stl extension) representing patient-specific thoracolumbar spine triangulated meshes ("<a href="../record/7715658/files/42%20Patient-Specific%20stl%20files.rar?download=1">42 Patient-Specific stl files.rar</a>"), including point coordinates and triangulated mesh connectivity IDs. These stl files are reconstructed using sterEOS software (IRCCS, Milan), thanks to non-operated bi-planar images. Each stl file includes triangulated meshes of vertebras, pelvis, sacrum, and the femoral head. The stl files can be opened by many image viewers, 3D modelling, and CAD programs, like: Microsoft 3D Viewer (windows), and MeshLab (multiplatform). Data can be filtered, visualized, and downloaded using the data visualisation platform (<a href="https://thc.spineview.upf.edu/">https://thc.spineview.upf.edu</a>/).</li> <li>16807 stl files representing the thoracolumbar spine triangulated models ("<a href="../api/files/a36be640-9968-46cc-a0f5-b4aa610dfcfa/stl.part01.rar?versionId=9aa98aa1-9e2d-4638-809e-2358f406de2d">stl.part01.rar</a>" to "<a href="../api/files/a36be640-9968-46cc-a0f5-b4aa610dfcfa/stl.part09.rar?versionId=f9cb0431-4db1-4dd0-9313-6c782c626280">stl.part09.rar</a>"), including point coordinates and triangulated mesh connectivity IDs. These stl files are sampled by combining the first 5 shape modes of the SSM, in which each shape mode is discretized into 7 Standard Deviations (SD): -3, -2, -1, 0, 1, 2, 3. Each stl file includes triangulated meshes of vertebras, pelvis, sacrum, and the femoral head. The stl files can be opened by many image viewers, 3D modelling, and CAD programs, like: Microsoft 3D Viewer (windows), and MeshLab (multiplatform). Data can be filtered, visualized, and downloaded using the data visualisation platform (<a href="https://thc.spineview.upf.edu/">https://thc.spineview.upf.edu</a>/).</li> <li>An excel file "<a href="../records/8108354/files/Descriptive_List.xlsx?download=1">Descriptive_List.xlsx</a>" reporting measured spinopelvic parameters for 42 patient-specific triangulated models, and virtual cohort 16807 triangulated models. Spinopelvic parameters are: Pelvic-Incidence (PI), Pelvic Tilt (PT), Sacral Slope (SS), Lumbar Lordosis (LL), LL-PI, Global Tilt (GT), Relative Pelvic Version (RPV), Relative Lumbar Lordosis (RLL), Lumbar Distribution Index (LDI), Relative Spinopelvic Alignment (RSA), T1 pelvic Angle (TPA), and scoliosis cobb angle. Global Alignment and Proportion (GAP) score is further measured as a complementary assessment. The Excel file has two sheets: sheet1 for 16807 virtual cohort, and sheet2 for 42 patient-specific models. Model ID in the excel file is correspondent to the model's name in both virtual cohort and patient-specific models. Model number in "Descriptive_List.xlsx" is correspondent to the same model number in 42 and 16807 FE input files, respectively (42 FE input files (DOI: <a href="../records/10994164">10.5281/zenodo.10994164</a>), 16807 virtual FE input files (DOI: <a href="https://doi.org/10.5281/zenodo.8107354">10.5281/zenodo.8107354</a>)).</li> </ul> <p>Developed by: Morteza Rasouligandomani (Ph.D. in biomedical engineering, Pompeu Fabra university, BCN Med-Tech group, DTIC department, Barcelona, Spain).</p> <p>Email contact: jerome.noailly@upf.edu</p>
Data and results for "A corpus-based study to triangulating experimental evidence regarding verb-noun association for action verbs"
<p>This repository provides spreadsheets containing the results of corpus-based and experimental studies for my undergraduate thesis titled "A corpus-based study to triangulating experimental evidence regarding verb-noun association for action verbs" (supervised by Gede Primahadi Wijaya Rajeg, PhD [main] and Ketut Santi Indriani, M.Hum. [associate]) in the Bachelor of English Literature (BoEL) program, Faculty of Humanities, Udayana University. The thesis explores convergences/divergences between different methods and data types for a set of verb-noun collocations for several action verbs and their synonyms. The description of the dataset is as follows:</p> <ol> <li>"data-raw": A raw dataset containing the results of an experiment conducted using Gorilla Experiment Builder. This consists of responses regarding verb-noun collocation co-occurrences from 17 participants into one. Link to Gorilla Experiment: (https://app.gorilla.sc/openmaterials/622948).</li> <li>"Corpus Analysis Results": A compiled data containing search results of frequencies found in the Corpus of Contemporary American English (COCA). The frequencies were compiled into tables for the five main verbs showing the number of co-occurrences of specific verb-noun collocations.</li> <li>"Experiment Results (1)": A compiled data containing the experiment results calculated as a total, showing the number of co-occurrences of specific verb-noun collocations across five verbs from the participant responses.</li> </ol> <p>The thesis is part of the pedagogical outcome of the <a title="CompLexico" href="https://www.cirhss.org/complexico/" target="_blank" rel="noopener"><em>CompLexico</em></a> research group at <a title="CIRHSS" href="https://www.cirhss.org/" target="_blank" rel="noopener"><em>CIRHSS</em></a>, and the Psycholinguistics course I took with I Made Sena Darmasetiyawan, PhD at BoEL, both in the Faculty of Humanities, Udayana University.</p>
Laser triangulation measurement for AFP monitoring
<p>This data set was acquired in the context of EU project ZAero. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 721362. Project duration: 2016/10/01 - 2019/09/30. This data set contains a HDF5 file with data used for evaluation in a SAMPE 2019 conference paper [1].</p> <p>The main data in this package is contained in a HDF5 file: zaeroFTD1.h5. There are two entries in this file:<br> /raw: contains the raw laser range data as acuqired during AFP lay-up<br> /seg: contains the manually defined segmentation that corresponds to the laser range data</p> <p>The data was acquired for preliminary test runs for AFP monitoring in the ZAero project. It contains different regions that correspond to the following labels (as defined in /seg):<br> 1 ... gap<br> 2 ... regular tow<br> 3 ... overlap<br> 4 ... fuzzball</p> <p>This data is mainly intended for testing of algorithms that perform defect detection on laser range images of AFP data.</p> <p>For more information about the HDF5 format, please visit the HDF5 Group website:<br> https://www.hdfgroup.org/solutions/hdf5/</p> <p>An example for loading and visualizing the data in Python comes with this data set:<br> readDataExample.py</p> <p>=====================================<br> REFERENCES<br> =====================================</p> <p>[1]<br> @inproceedings{Zambal2019_SAMPE}<br> author = {Sebastian Zambal and Christoph Heindl and Christian Eitzinger},<br> title = {Machine Learning for CFRP Quality Control},<br> booktitle = {Conference of the Society for the Advancement of Material and Process Engineering (SAMPE), Nantes, France},<br> year = {2019}<br> }</p> <p>[2]<br> @inproceedings{Zambal2019_QCAV,<br> author = {Sebastian Zambal and Christoph Heindl and Christian Eitzinger and Josef Scharinger},<br> title = {End-to-End Defect Detection in Automated Fiber Placement Based on Artifcially Generated Data},<br> booktitle = {Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111721G},<br> doi = {DOI: 10.1117/12.2521739},<br> year = {2019}<br> }</p> <p> </p>
Fig 3 in New data on the Paleocene monotreme Monotrematum sudamericanum, and the convergent evolution of triangulate molars
Fig 3. Schematic occlusal view of two left lower molars (m1–m2) of an ornithorhynchid monotreme (Obdurodon dicksoni) (A), and a pre−tribosphenic peramuran (Peramus sp.) (B). Note the difference between the "gaps" in A and the "embrasures" in B. In the former the intermolar contact results by mesial and distal cingulids. Not to scale.
Fig. 2 in New data on the Paleocene monotreme Monotrematum sudamericanum, and the convergent evolution of triangulate molars
Fig. 2. Schematic occlusal view of the advanced ornithorhynchid Obdurodon dicksoni; RM2 (A), Rm1 (B). The only know m1 of Monotrematum sudamericanum is incomplete (Fig. 1D). As both genera show similar crown pattern, we figure here the homologous teeth of O. dicksoni. Not to scale.
Fig. 1 in New data on the Paleocene monotreme Monotrematum sudamericanum, and the convergent evolution of triangulate molars
Fig. 1. Monotrematum sudamericanum RM2 (MPEF−PV 1634) in occlusal (A) and posterior (B) views. C. Base of crown showing fragment of roots. Rm1(MPEF−PV 1635); occlusal view (D), posterior view (E). F. Base of crown showing fragmentary roots. Not to scale.
Fig. 4. Monotrematum sudamericanum. A in New data on the Paleocene monotreme Monotrematum sudamericanum, and the convergent evolution of triangulate molars
Fig. 4. Monotrematum sudamericanum. A. Stereopair of RM2, occlusal view. B. Stereopair of Rm1, occlusal view. Anterior is up in A and B.
Update to Dartmouth Isochrones Triangulation
<p>This file supersedes older dartmouth.tri uploads; for use with the "isochrones" python package, which should download this automatically.</p>
FR044, Late Woodland, Maidson Triangule Points
Maidson Triangule Points Late Woodland Catalog #:P656 Uploaded by Gwyneth Harris Suggested Data Citation: Thompson, Christine, Erin Powers, Gwyneth Harris, and Kevin C. Nolan, 2021. FRHS_FR044, 3D Model .ply file. Digital Exhibit of Fort Recovery Historical Society's Precontact Collection, Fort Recovery Historical Society and Applied Anthropology Laboratories, Ball State University. Source: Objaverse 1.0 / Sketchfab
Low-poly Stone summit sign, triangulation pillar
Stones like this with year cross carving on it was used to mark summits in Czechoslovakia. This stone was playsed in 1937 year. Cross on top is a compass rose it used to display the orientation of the cardinal directions. Source: Objaverse 1.0 / Sketchfab
Triangulated surface geometry of the upper lumbar and lower thoracic spine
<p>Triangulated surface geometry of the upper lumbar and lower thoracic spine, stored as <a href="https://www.loc.gov/preservation/digital/formats/fdd/fdd000504.shtml">STL</a>.</p> <p>The dataset is used to develop the SODALITE virtual clinical trial use-case. It contains a triangulated iso-surface of a part of the lumbar spine. The geometry starts caudal at L2 which is only partially contained and ends cranial at T9 which also only partially contained. The triangulation is extracted from the coresponding <a href="https://doi.org/10.5281/zenodo.3959070">volume dataset</a>.</p> <p>The datasets content is illustrated by the attached png image which shows a shaded surface rendering of the dataset.</p> <pre><code>Format : STL Header : BINARY Byte Order : LittleEndian Grid Type : Unstructured # Nodes : 346051 # Elements : 692244 Data-Type : Uint32, Float32, Uint16 </code></pre> <p> </p>
Using Delaunay triangulation to sample whole-specimen color from digital images
<p>1. Color variation is one of the most obvious examples of variation in nature, but biologically meaningful quantification and interpretation of variation in color and complex patterns is challenging. Many current methods for assessing variation in color patterns classify color patterns using categorical measures, provide aggregate measures that ignore spatial pattern, or both, losing potentially important aspects of color pattern.</p> <p>2. Here, we present Colormesh, a novel method for analyzing complex color patterns that offers unique capabilities. Our approach is based on unsupervised color quantification combined with geometric morphometrics to identify regions of putative spatial homology across samples, from histology sections to whole organisms. Colormesh quantifies color at individual sampling points across the whole sample.</p> <p>3. We demonstrate the utility of Colormesh using digital images of Trinidadian guppies (Poecilia reticulata), for which the evolution of color has been frequently studied. Guppies have repeatedly evolved in response to ecological differences between up- and downstream locations in Trinidadian rivers, resulting in extensive parallel evolution of many phenotypes. Previous studies have, for example, compared the area and quantity of discrete color (e.g., area of orange, number of black spots) between these up- and downstream locations neglecting spatial placement of these areas. Using the Colormesh pipeline, we show that patterns of whole-animal color variation do not match expectations suggested by previous work.</p> <p>4. Colormesh can be deployed to address a much wider range of questions about color pattern variation than previous approaches. Colormesh is thus especially suited for analyses that seek to identify the biologically important aspects of color pattern when there are multiple competing hypotheses, or even no a priori hypotheses at all.</p>
Triangulation Bulls Eye and Stone Direct Targeting Pcnl
ClinicalTrials.gov study NCT04846699. IPD Sharing: NO. Countries: 1. Publications: 3.
Using Delaunay triangulation to sample whole-specimen color from digital images
Open the record for dataset details and reuse information.
Enhancing Regional Quasi-Geoid Refinement Precision: An Analytical Approach Employing ADS80 Tri-linear Array Stereoscopic Imagery for Aerial Triangulation Densification and GNSS Gravity-Potential Leveling
Open the record for dataset details and reuse information.
Prospective Multicenter Study With the Endomina® Triangulation Platform
ClinicalTrials.gov study NCT05677464. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
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