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4,107 results for “pointing”
FR073, Middle Woodland, Snyders point
Snyders Point Middle Woodland Catalog #: P651? Uploaded by Gwyneth Harris Suggested Data Citation: Thompson, Christine, Erin Powers, Gwyneth Harris, and Kevin C. Nolan, 2021. FRHS_FR073, 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
2005.002.007 Bag 5a Point 447 - shaded version
From the Connecticut State Museum of Natural History's Caldwell Collection of Neolithic Mali Points, Bag 5a, Point 447. Max height 32.19mm. Max width 15.99mm. GSD 0.012 mm/pix, RMS reprojection error 0.530063 pix. Source: Objaverse 1.0 / Sketchfab
Marion Point, SJ13_19
Marion style biface, North Florida, Archaic (6200-5200 ya) Part of the Coontie Island Collection, SJ13_19 Model by Emily Jane Murray This model was made using RealityCapture software by Capturing Reality Source: Objaverse 1.0 / Sketchfab
Three-Point Correlation Multipoles with AP
<p>This repository contains the backbones for the computation of 3PCF theoretical predictions.</p> <p>See attached code</p> <p> </p>
Coastal bluff point clouds derived from SfM near Elwha River mouth, Washington from 2016-04-18 to 2020-05-08
<p>Point Clouds of an approximately 2.0 km alongshore reach of seaward-facing coastal bluff faces on the Strait of Juan de Fuca, Washington State, were derived using structure-from-motion (SfM) photogrammetry from digital photos collected at least quarterly between 2016 and 2022. The point clouds were derived to assess spatial and temporal patterns of erosion on the bluff face and deposition at the base of the bluff. Photos from Miller, et al. (2022) were aligned using a modified USGS published workflow (Over, et al., 2022) with Agisoft Metashape Professional 1.8.5. Photos were aligned within a single chunk in a 4D approach described by Wernette, et al. (2022), and the sparse point cloud was filtered by reconstruction uncertainty (Ru) and projection accuracy (Pa). Dense point clouds were generated independently for each survey date by disabling all cameras except for a single photo date and then generating the dense cloud. This was repeated for each of the 30 photo survey dates, resulting in 30 dense point clouds (one point cloud per photo survey date).</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S240422ed
<p>Attached in a .json file is the completed pointing information for 55 observation(s) for the EM counterpart search associated with the gravitational wave event S240422ed. These observations were taken on the ZTF, and WINTER instruments.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S240422ed
<p>Attached in a .json file is the completed pointing information for 24 observation(s) for the EM counterpart search associated with the gravitational wave event S240422ed. These observations were taken on the MLS10KCCD-CSS instrument.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S240422ed
<p>Attached in a .json file is the completed pointing information for 306 observation(s) for the EM counterpart search associated with the gravitational wave event S240422ed. These observations were taken on the Sinistro, and MuSCAT instruments.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event MS240429t
Attached in a .json file is the completed pointing information for 2 observation(s) for the EM counterpart search associated with the gravitational wave event MS240429t. These observations were taken on the DLT40 instrument.
Data from : Measuring nearshore waves at break point in 4D with Stereo-GoPro photogrammetry
<p>This dataset was collected with a stereophotogrammetric method, using a cost-effective stereo system composed of two GoProTM (Hero 7) video cameras.</p> <p>The result is a geotiff DEM time series, with a resolution of 0.2 m, focusing on close-range measurements of nearshore waves at break point.</p> <p>Data collected in the framework of the WEST project (Natural Breaking WavEs and Sediment Transport during beach recovery - ANR-20-CE01-009) granted by the Agence Nationale pour la Recherche (ANR).</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event MS181101ab
Attached in a .json file is the completed pointing information for 25 observation(s) for the EM counterpart search associated with the gravitational wave event MS181101ab. These observations were taken on the DECam, ZTF, and DLT40 instruments.
Lake Superior bluff toes and crests from Wisconsin Point to Bark Point, 2009 and 2019
<p>This repository contains shapefiles of bluff toe and crest points delineated from LiDAR data collected in the years 2009 and 2019 for the Wisconsin Lake Superior coast from Wisconsin Point to Bark Point. The shapefiles have a horizontal coordinate reference system of EPSG:32615 and their names describe the year and feature they represent. Additional details regarding the creation of these points can found in the accompanying publication (https://doi.org/10.1016/j.jglr.2024.102366).</p>
Data from: Sea ice choke points reduce the length of the shipping season in the Northwest Passage
<p>Arctic sea ice has shifted from a perennial (older, thicker ice) to a seasonal (younger, thinner) ice regime, leading to the increasingly common belief that shipping through Canada's Northwest Passage is becoming more viable. Here, we use the Risk Index Outcome values derived from the Polar Operational Limit Assessment Risk Indexing System and analyze recent changes to shipping season lengths along individual sections of the Northwest Passage routes from 2007 to 2021. Results show that multi-year ice flushed southward from high-latitude regions maintains the so-called choke points along certain route sections, reducing overall shipping season length. There is considerable spatiotemporal variability in shipping season lengths along the southern and northern routes. Specifically, parts of the northern route exhibit a decrease of up to 14 weeks over the 15 years. The variability of shipping season and, in particular, the shortening of the season will impact not only international shipping but also resupply and the cost of food in many Arctic communities, which require a prompt policy response.</p>
Light holographic dilatons near critical points — data release
<p>This dataset consists of .csv files containing all of the data used to make the plots appearing in the article <a href="https://arxiv.org/abs/2406.04974" target="_blank" rel="noopener">Light holographic dilatons near critical points</a>. There are also Mathematica and Jupyter Notebooks which may be used to reproduce the plots.</p>
Avian Point Count Surveys from Yáláƛi (Goose Island) Archipelago, British Columbia, Canada in 2011
<p>This file contains some data used in the article, "<em>Comparing historical and contemporary observations of avian fauna across 75 years on the Yáláƛi (Goose Island) Archipelago, British Columbia, Canada</em>" by Obrist et al. currently in peer-review as a Nature Note at Ecology and Evolution. A DOI to the article will be added upon publication. Specifically, these data refer to the <u>2011 Surveys by Simon Fraser University (SFU) Researchers. </u></p> <ul> <li>Avian point count surveys were conducted in 2011 at 50 locations across the six main islands of Yáláƛi, the Goose Island Archipelago (i.e., Goose, Gosling, Gull, Duck, Snipe, and Swan Island).</li> <li>Locations were chosen to replicate surveys within the four main habitat types outlined by Charles J. Guiguet (1953) (i.e., climax forest, ecotone, muskeg, meadow).</li> <li>Points were surveyed three times during the breeding season, between May 12th and June 2nd, 2011.</li> <li>The date, survey number, start time, point ID, temperature, and weather were recorded for each point count.</li> <li>A single observer recorded all birds seen and heard within a 100 m radius of each point for 10 minutes, separating all observations into minute-long intervals.</li> <li>The distance between the observer (point) and bird was estimated for each observation.</li> <li>Point counts were conducted within five hours of sunrise.</li> <li>Protocols based on Huff et al. (2000) </li> </ul> <p>Please see the article at DOI for a more comprehensive description of the data collection and processing. </p> <p> </p> <p> </p> <p> </p> <p> </p> <p><span><strong>File: GooseIslandBirds_Data.xlsx</strong></span></p> <p>This excel file contains the following sheets: </p> <p>1.) Relative Abundance Comparisons: The comparisons of totals between 2011 survey data and data collected by Charles Guiguet (1953). </p> <p>2.) Point Count Summaries: Shows the way the 2011 totals in Sheet 1 (Relative Abundance Comparisons) was calculated, showing the total abundance for each species for each of the 3 visits, and the total from the Casual Observations sheet. </p> <p>3.) Raw Point Counts</p> <p>4.) Casual Observations <strong>(Caution: observations beyond line 457 are considered duplicates of individuals already accounted for on point counts).</strong></p> <p>5.) Locations</p> <p>6.) Metadata <strong>(READ FIRST)</strong></p>
Innovative 3D Cone Point Cloud Fitting via Landweber Iteration
<p>Cone surface fitting is essential in various fields, including computer graphics, computer vision, and robotics. However, factors such as noise, initial parameter selection, and the varying distribution of point clouds can significantly impact fitting accuracy and stability. To address these challenges, we propose a novel optimization method based on Landweber iteration. This method solves an objective function that includes the cone vertex. Initially, Landweber iteration is used to calculate high-precision initial values for the conical surface by leveraging all point cloud data. Subsequently, the RANSAC algorithm filters the point cloud data based on these initial values, eliminating points that do not meet the distance threshold. Finally, an error equation is formulated, and the cone surface parameters are further refined using an optimization algorithm based on Landweber iteration. Simulation experiments validate the feasibility and robustness of our approach, demonstrating superior accuracy and stability in 3D cone surface fitting.</p>
Figure 6 in The Paleocene cephalopod fauna from Pebble Point, Victoria (Australia) - fulcrum between two Eras
Figure 6. Nautilus praepompilius from Pebble Point, AM C 143662. Scale bar = 10 mm.
Figure 1 in The Paleocene cephalopod fauna from Pebble Point, Victoria (Australia) - fulcrum between two Eras
Figure 1. Map showing the location of sampling from Pebble Point Formation outcrop.
Supporting dataset with respect to Raman spectroscopic analysis of Palaeogene charcoals from Malcolm's Point, Isle of Mull, Scotland.
<p>Raman spectroscopic data (raw and processed) for Palaeogene charcoal samples A1, A2, B, and A1 thin section (A1-TS), including application of FWHMRa geothermometry as per <strong>Theurer et al. (2022)</strong>. Spectral data collected and processed in <em>Renishaw</em> WiRE 3.4 software. Those data presented in sheet 'HDHG Method 3' refer to spectral data processed in MATLAB, implementing 'peak-fit' and secondary deconvolution codes, as per <strong>O'Haver (2015, 2022)</strong> and <strong>Schito et al. (2020, 2022)</strong>, respectively.</p> <p><strong>O'Haver, T. (2015)</strong>. A Pragmatic Introduction to Signal Processing [Online]. Retrieved from https://terpconnect.umd.edu/~toh/spectrum/CurveFittingC.html</p> <p><strong>O'Haver, T. (2022)</strong>. peakfit.m [Code]. <em>MATLAB Central File Exchange</em>. Retrieved from https://www.mathworks.com/matlabcentral/fileexchange/23611-peakfit-m</p> <p><strong>Schito, A. & Corrado, S. (2020)</strong>. An automatic approach for characterization of the thermal maturity of dispersed organic matter Raman spectra at low diagenetic stages. <em>Journal of the Geological Society of London - Special Publications</em>. 484, 107–119. doi: 10.1144/SP484.5</p> <p><strong>Schito, A., Pensa, A., Corrado, S., Vona, A., Trolese, M., Morgavi, D., <em>et al. </em>(2022)</strong>. Calibrating carbonization temperatures of wood fragments embedded within pyroclastic density currents through Raman spectroscopy. <em>Minerals</em>, 12, 203. doi: 10.3390/min12020203</p> <p><strong>Theurer, T., Naszarkowski, N., Muirhead, D. K., Jolley, D. & Mauquoy, D. (2022)</strong>. Assessing modern Calluna heathland fire temperatures using Raman spectroscopy: Implications for past regimes and geothermometry. <em>Frontiers in Earth Science</em>, 10, 827933. doi: 10.3389/feart.2022.827933</p>
Missing the (tipping) point: the effect of information about climate tipping points on public risk perceptions in Norway [Dataset]
<p>This is all the data used for the redaction of the research paper "Missing the (tipping) point: the effect of information about climate tipping points on public risk perceptions in Norway".</p> <p> </p> <p>The dataset is contained in Excel files (.xlsx) and code for statistical analysis can be found in R files (.R)</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.