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13,117 results for “Maps”
A Systematic Mapping Study on Software Testing forSystems-of-Systems
<p>Vídeo de apresentação do estudo : A Systematic Mapping Study on Software Testing forSystems-of-Systems para o SAST 2020</p>
Do we use FLOSS in Software Engineering Education? Mapping the Profiles and Practices of Higher Education Teachers from Brazi
<p>Context:Software Engineering (SE) is a key topic in undergraduate computing-related courses that provides the basic knowledge and skills necessary for professional practice in the software industry. Teaching SE principles, concepts and practices and relating them to real-world scenarios are challenging tasks, and the adoption of Free/Libre/Open Source Software (FLOSS) projects can help to face these challenges. On the other hand, using FLOSS projects as a didactic resource may introduce additional challenges to professors that are not familiar with the FLOSS ecosystem. Objective: This research aims to identify and map the profiles of professors of SE courses in Brazil, as well as to present the pedagogical practices used in the experience with FLOSS projects in Software Engineering Education (SEE). Method: We performed a survey with higher education professors in Brazil, used K-modes algorithm to identify clusters and Decision Tree algorithm to identify characteristics that determine the use of FLOSS projects in a sample of professors who had not used this approach in the classroom.Results:The results of the research revealed characteristics of professors who use, or not,FLOSS projects in SEE, of professors grouped in the two clusters generated by the application of the K-modes algorithm, of professors grouped by the application of the Decision Tree algorithm,in addition to presenting similar characteristics the pedagogical practices evidenced by each group of SE professors.</p>
Data from: European map of groundwater pH and calcium.
<p>Description of the files:</p> <p><strong>ADDITIONAL_RAW_DATA_E-Ukraine_Ca</strong>: Complementary data with Ca measurements compiled from Eastern Ukraine (Excel)</p> <p><strong>ADDITIONAL_RAW_DATA_E-Ukraine_pH</strong>: Complementary data with pH measurements compiled from Eastern Ukraine (Excel)</p> <p><strong>Ca_imp_RAW_DATA_used_for_modelling</strong>: Calcium-imputed data used for spatial modelling (Excel)</p> <p><strong>detailed_maps-panels_Ca_pH</strong>: Final map outputs with details, by European zones (JPEG)</p> <p><strong>pH_RAW_DATA_used_for_modelling</strong>: Coordinates and pH values used for modeling (Excel)</p> <p><strong>Raster_data_for_GIS</strong>: Model outputs for GIS (ASCII with ArcGIS project and legends)</p> <p><strong>sites_ca_GIS_points</strong>: Point data with Calcium measurements used for modelling (shapefile)</p> <p><strong>sites_pH_GIS_points</strong>: Point data with pH measurements used for modelling (shapefile)</p>
The utility of the Laplace effect size prior distribution in Bayesian fine-mapping studies
<p>Data needed to reproduce the figures and tables in the paper entitled 'The utility of the Laplace effect size prior distribution in Bayesian fine-mapping studies' submitted for publication.</p>
Map of geographic distribution of library holdings of al-Muqtabas
<p>Map of the geographic distribution of library holdings of the Arabic periodical "al-Muqtabas" published by Muḥammad Kurd ʿAlī in Cairo and Damascus between 1906 and 1918. The map was drawn with R and is based on queries to Worldcat (worldcat.org) and the Arabic Union Catalogue (aruc.org).</p>
Map 1 from: Syahida-Emiza S, Sam YY, Siti-Munirah MY (2020) Two new species of Codonoboea (Gesneriaceae) from Kenaboi State Park, Peninsular Malaysia. PhytoKeys 165: 51-62. https://doi.org/10.3897/phytokeys.165.56955
Map 1 Distribution of Codonoboea kenaboiensis (circle) and Codonoboea ruthiae (triangle) in Peninsular Malaysia.
Global color maps of dwarf planet (1) Ceres from Dawn Framing Camera images
<p>These are global maps of dwarf planet (1) Ceres described in "Resolved spectrophotometric properties of the Ceres surface from Dawn Framing Camera images" by <a href="http://dx.doi.org/10.1016/j.icarus.2017.01.026">Schröder <em>et al</em>., Icarus 288 (2017) 201-225</a> (<a href="https://arxiv.org/abs/1701.08550">arXiv</a>). Global color maps created from these data files are shown in Fig. 7 of that paper.</p> <p>These files contain global maps of the photometrically corrected reflectance of the Ceres surface, with one map for each of the 7 narrow-band filter of the Dawn framing camera (FC2). Photometrically corrected reflectance means observed reflectance divided by model reflectance, and the global average of the photometrically corrected reflectance is unity by definition. The model is the Akimov photometric model with parameters valid for global average Ceres and an upper limit of 80° for the photometric angles. The model reflectance was calculated with surface topography derived from a global shape model. Global maps were created as the median of projected individual images of the photometrically corrected reflectance. The IMG and FITS files contain the data in floating point format. The PNG files are provided for visual reference.</p>
Figs 1–5. Map and locality. 1 in Exceptional diversity of Tischeriidae (Lepidoptera) from a single tropical forest site in Belize, Central America
Figs 1–5. Map and locality. 1. Las Cuevas, Belize, Central America, 16°43′53″ N, 88°59′11″ W (Map base courtesy of T. Patterson, USA). 2–3. Road to Las Cuevas Research Station, located in the heart of the Chiquibul Forest in the Maya Mountains of Belize. 4. The site of Las Cuevas Research Station (formerly Las Cuevas Biological Station), shortly after its establishment by the Forest Department of Belize and the Natural History Museum, London in 1994 (courtesy of NHMUK). 5. Habitat, moist tropical forest (at right, collector Simon R. Hill, 1998).
Mapping the age of ice of Gauligletscher combining surface radionuclide contamination and ice flow modeling: Radionuclide data
<p>The data corresponds to 239-Pu and 236-U concentrations of 220 samples of ice collected along 5 flowlines at the surface of Gauligletscher in July 2019. Details about the data sampling and analysis can be found in the paper "Mapping the age of ice of Gauligletscher combining surface radionuclide contamination and ice flow modeling", by G. Jouvet, S. Röllin, H. Sahli, J. Corcho, L. Gnägi, L. Compagno, D. Sidler, M. Schwikowski, A. Bauder, and M. Funk. The Cryosphere, 2020.</p>
High-resolution soil erodibility map of Brazil
<p>This dataset provides high-resolution (250 m cell size) spatially explicit soil erodibility map across Brazil. The content is described below:</p> <ul> <li>K-factor_nomo.zip => soil erodibility estimated by the algebraic solution of USLE nomograph [t ha h ha<sup>-1</sup> MJ<sup>-1</sup> mm<sup>-1</sup>]</li> <li>K-factor_EPIC.zip => soil erodibility estimated by the EPIC Model [t ha h ha<sup>-1</sup> MJ<sup>-1</sup> mm<sup>-1</sup>]</li> <li>structure-code.zip => USLE structure code assigned to Brazilian soil groups.</li> <li>permeability.zip => USLE permeability code.</li> </ul> <p>Contact for further information: rachgodoi@gmail.com</p>
Software Engineering Meets Deep Learning: A Mapping Study
<p>Dataset used in the paper "Software Engineering Meets Deep Learning: A Mapping Study"</p>
Map 2 from: Yan W, Shi H, Liang H (2020) First discovery of the genus Himalopenetretus (Coleoptera, Carabidae, Patrobini) in China, with description of a new species. ZooKeys 997: 145-154. https://doi.org/10.3897/zookeys.997.58125
Map 2 Distribution map for Himalopenetretus species: H. burangensis sp. nov. (red); H. franzi (blue); H. falciger (magenta).
FIG. 6. — A in The zoomorphic representations of the Pîrî Reis map (1513)
FIG. 6. — A Reeves' muntjac (Muntiacus reevesi Ogilby, 1839), a species of Middle and Far Eastern cervid of the genus Muntiacus Rafinesque, 1815, which might be the inspiration for the mythical yael. (Drawing: Cecilia Veracini).
FIG. 5 in The zoomorphic representations of the Pîrî Reis map (1513)
FIG. 5. — "The shādawār that makes sweet music" according to a Persian miniature. Shiraz c. 1440 (from Robinson 1980, modified).
FIG. 4. — A in The zoomorphic representations of the Pîrî Reis map (1513)
FIG. 4. — A, Dog-headed creatures; B, less-headed creatures. From the Marvels of Things Created by al-Qazwīnī (1283). This is the oldest known textual witness to the original work. (Source: Library of Congress, World Digital Library).
Input dataset for gap filling and land-cover mapping using eumap Library - 2000 to 2020
<p>Benchmark dataset containing slope, elevation, Landsat temporal composites and night light raster layers, and the training samples (<a href="https://land.copernicus.eu/imagery-in-situ/lucas">LUCAS</a> and <a href="https://land.copernicus.eu/pan-european/corine-land-cover">CORINE</a> samples compilation) to map the land-cover in different areas of the European Union-EU.</p> <p>The slope and elevation refers to <a href="https://zenodo.org/record/4057883#.X3MJ0Nkmz0q">Digital Terrain Model for Continental Europe</a>, and the night light images are from <a href="https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/VNP46A1/">VNP46A1 product (VIIRS/NPP Daily Gridded Day Night Band 500m)</a>. The temporal composites were based on <a href="https://glad.geog.umd.edu/ard/glad-landsat-ard">GLAD Landsat ARD</a>, considering the 4 seasons and 3 percentiles per season (25, 50 and 75), for 6 spectral (blue, green, red, NIR, SWIR1, SWIR2) and 1 thermal band, resulting at end in 88 Landsat composites per year. The images for each season were selected using the same calendar dates for all period:</p> <ul> <li>Winter: December 2 of previous year until March 20 of current year</li> <li>Spring: March 21 until June 24 of current year</li> <li>Summer: June 25 until September 12 of current year</li> <li>Fall: September 13 until December 1 of current year</li> </ul> <p>The temporal composites were generated to <a href="https://roda.sentinel-hub.com/sentinel-s2-l2a/readme.html">Sentinel-2 L2A</a> for 2018, 2019 and 2020, using the same approach (4 seasons x 3 percentiles x 6 spectral bands).</p> <p>The benchmark areas were selected according to the EU tiling system, which consists of 7,042 regular tiles with 30 x 30 km. The dataset uses the ETRS89-extended / LAEA Europe as spatial reference system (<a href="https://epsg.io/3035">EPSG:3035</a>), and all the raster layers have 1,000 x 1,000 pixels and 30m of spatial resolution.</p> <p>For all the EU the training samples will have 32 land-cover classes, varying according to the benchmark area:</p> <ul> <li>111: Urban fabric</li> <li>122: Road and rail networks and associated land</li> <li>123: Port areas</li> <li>124: Airports</li> <li>131: Mineral extraction sites</li> <li>132: Dump sites</li> <li>133: Construction sites</li> <li>141: Green urban areas</li> <li>211: Non-irrigated arable land</li> <li>212: Permanently irrigated arable land</li> <li>213: Rice fields</li> <li>221: Vineyards</li> <li>222: Fruit trees and berry plantations</li> <li>223: Olive groves</li> <li>231: Pastures</li> <li>311: Broad-leaved forest</li> <li>312: Coniferous forest</li> <li>321: Natural grasslands</li> <li>322: Moors and heathland</li> <li>323: Sclerophyllous vegetation</li> <li>324: Transitional woodland-shrub</li> <li>331: Beaches, dunes, sands</li> <li>332: Bare rocks</li> <li>333: Sparsely vegetated areas</li> <li>334: Burnt areas</li> <li>335: Glaciers and perpetual snow</li> <li>411: Inland wetlands</li> <li>421: Maritime wetlands</li> <li>511: Water courses</li> <li>512: Water bodies</li> <li>521: Coastal lagoons</li> <li>522: Estuaries</li> <li>523: Sea and ocean</li> </ul> <p>The gap filling validation data was generated by creating a mask of all nodata pixels (gaps) for each temporal composite, and then transposing that mask. All valid pixels covered by the transposed nodata mask are considered validation pixels. This method was chosen to retain the diversity of spatiotemporal nodata patterns that occur in the data. Each gap filling validation file contains 3 directory:</p> <ul> <li>raw: original temporal composite</li> <li>validation: transposed data</li> <li>filled_tmwm8: the best gap filling method that was tested</li> </ul> <p>See the <a href="https://gitlab.com/geoharmonizer_inea/eumap">eumap library</a> for more information about the gapfiling approach and land-cover mapping using this dataset.</p>
Open Street Map: mapping e cartografia collaborativa in condizioni di emergenza
<p>In questo minicorso, facente parte della collezione <a href="https://www.youtube.com/playlist?list=PLXBZ0jvtlWH6qL7SOKOddJ_7MioDid_Oo">acasaconSE</a> organizzato dalla associazione <a href="http://www.successionecologica.it/">Successione Ecologica</a>, si parla di cos'è <a href="http://www.openstreetmap.org">Open Street Map</a> e come, in condizioni di emergenza (pandemie, tsunami, terremoti, siccità etc.), la cartografia colalborativa possa essere sia di supporto alle attività di soccorso che alla vita quotidiana dei singoli cittadini. In particolare, l'outline del minicorso è:<br> 1) Open Street Map: perché "insieme è meglio" e come contribuire<br> 2) Esempio di applicazione in condizioni di emergenza (il progetto HOT e il caso COVID-19)<br> 3) il civic hacking e le comunità informali</p> <p>Buona visione! </p>
Map 18 from: Caterino MS, Tishechkin AK (2020) Recognition and revision of the Phelister blairi group (Histeridae, Histerinae, Exosternini). ZooKeys 1001: 1-154. https://doi.org/10.3897/zookeys.1001.58447
Map 18 Collecting records for Phelister incertus (black triangles), P. okeefei (white circle), P. blairoides (white squares), and P. pirana (star).
Map 17 from: Caterino MS, Tishechkin AK (2020) Recognition and revision of the Phelister blairi group (Histeridae, Histerinae, Exosternini). ZooKeys 1001: 1-154. https://doi.org/10.3897/zookeys.1001.58447
Map 17 Collecting records for Phelister curvipes (upright black triangle), P. vilavelha (black hexagon), P. rio (white circle), P. semotus (stars), P. uncinatus (black squares), and P. inscriptus (inverted white triangles).
Map 13 from: Caterino MS, Tishechkin AK (2020) Recognition and revision of the Phelister blairi group (Histeridae, Histerinae, Exosternini). ZooKeys 1001: 1-154. https://doi.org/10.3897/zookeys.1001.58447
Map 13 Collecting records for Phelister amazoniae (white circles), P. arcuatus (black squares), and P. praecisus (stars).
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.