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BRAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 1. Example displaying two scatter plots with different characteristics and patterns
<p>In addition to this introductory section, the remainder of this paper is organized as follows. In Section 2, we present previous work related to our present study. In Section 3, we describe details regarding the methodology used in this study. In Section 4, we describe our experiments and results, then discuss our findings. Finally, we summarize the key content of our study in Section 5. </p>
Stable Modeling on Resource Usage Parameters of MapReduce Application-Figure 1. ACF and PACF plot of TeraSort application
<p>In Figure 1, the autocorrelation plots of all resource usage parameters reveal non- randomness because of the corresponding autocorrelations, denoted by the circle, violate the dashed lines (95% confidence boundary) and are statistically significant for lags up to 100. The filled triangle point-up in partial autocorrelation plots marks the largest partial autocorrelation of usage parameters as well as the corresponding lag number.</p>
Stable Modeling on Resource Usage Parameters of MapReduce Application-Figure 2. ACF plot of Residuals of Regression Model of Terasort
<p>, are uncorrelated. If the error term is uncorrelated, it proves that there exists strong randomness in residuals of the model and provides the evidence for the unbiased estimate for the true standard error. The autocorrelation plot is used to check this assumption. Figure 2 shows the autocorrelation plot of residuals of regression models of TeraSort application. In Figure 2, the horizontal axis represents lag time and the vertical axis indicates the autocorrelation between residual at time t and residual at other lag time. At lag 0, autocorrelation is always equal to 1 and represents time series itself. Most of the autocorrelation at other lag time fall into the 95% confidence interval, only few of them violate the dashed line. Such a shape of ACF plot proves that residuals are uncorrelated and respects to the independent assumption of the linear regression model residuals.</p>
Plots of Observations of CasA from LOFAR Station IE613 HBA against Frequency, Altitude and Azimuth
<p>A series of plots of the variation of linear polarisation channels and Stokes parameters of an observation of CasA on the 16th-17th March 2018 against frequency and local horizontal coordinates.</p>
Data, plotting scripts, and figures for "Computational study of the effects of density, fuel content, and moisture content on smoldering propagation of cellulose and hemicellulose mixtures"
<p>This bundle of files contains all the data and plotting scripts for "Computational study of the effects of density, fuel content, and moisture content on smoldering propagation of cellulose and hemicellulose mixtures", as well as the figures themselves.</p> <p>These results are part of the paper:</p> <p>Tejas Chandrashekhar Mulky and Kyle E. Niemeyer. "Computational study of the effects of density, fuel content, and moisture content on smoldering propagation of cellulose and hemicellulose mixtures," 2018. Accepted for publication in <em>Proceedings of the Combustion Institute</em>, available via <a href="https://arxiv.org/abs/1806.08396">https://arxiv.org/abs/1806.08396</a></p>
Sample single frequency plots of various channels against Altitude and Azimuth for LOFAR single station
<p>Sample of outputs indicating the variation in stokes and linear polarisation channels for LOFAR single station</p>
Data, plotting scripts, and figures for "A Projective Method for Solving the Single-Group Space-Time Neutron Kinetics Equations with Precursor Advection"
<p>Contains all the files necessary for figure reproduction.</p>
Experiment Result Plots of Data Stewardship (FAIR - Assignment 1)
<p>These plots show the results of the experiment by creating a scatterplot of the variables and a line plot.</p>
Plot Piper Hidrostratigrafi CAT Bandung-Soreang berdasarkan Parameter Hidrolik, Hidrokimia dan Isotop Stabil
<p>This repository holds Piper plots. The main connected thesis is available here https://zenodo.org/record/2648267#.XMAI6abgpyU</p>
Text-fig. 7.—A, Ratio (H/L) of height of maxilla (at anterior margin of antorbital recess) to length of maxilla (to anterior margin of antorbital recess), plotted against length (L) of maxilla (to anterior margin of antorbital recess). Length scale in cm. B, Ratio (D/L) of depth of dentary ramus to length of maxilla (to anterior margin of antorbital recess), plotted against length of maxilla (to anterior margin of antorbital recess). Length scale in cm. in A new Theropod Dinosaur from the Upper Cretaceous of Central Montana
Text-fig. 7.—A, Ratio (H/L) of height of maxilla (at anterior margin of antorbital recess) to length of maxilla (to anterior margin of antorbital recess), plotted against length (L) of maxilla (to anterior margin of antorbital recess). Length scale in cm. B, Ratio (D/L) of depth of dentary ramus to length of maxilla (to anterior margin of antorbital recess), plotted against length of maxilla (to anterior margin of antorbital recess). Length scale in cm.
Figures, plotting scripts, and data for "A fast, low-cost, and stable memory algorithm for implementing multicomponent transport in direct numerical simulations"
<p>This dataset contains the figures, as well as the necessary plotting scripts and data to reproduce them, for the article "A fast, low-cost, and stable memory algorithm for implementing multicomponent transport in direct numerical simulations" by Aaron J. Fillo, Jason Schlup, Guillaume Beardsell, Guillaume Blanquart, and Kyle E. Niemeyer (2019). In addition, the code used to generate the eigenvalues in Table 1 is included.</p> <p>The scripts were run in Matlab 2019a, though none of the versions used should be version-dependent. Furthermore, non-standard functions are included with dependencies hard-coded. We used export_fig (https://github.com/altmany/export_fig) to generate high-quality figures, and redistribute the version used here for reproducibility (export_fig was developed by Oliver J. Woodford and Yair M. Altman, and made available openly under the BSD 3-Clause License).</p> <p>The code included in this dataset is released under the BSD 3-Clause License (see LICENSE.txt for details), other than the source of export_fig, as described. The figures are shared under the Creative Commons Attribution 4.0 International License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/).</p>
Fig. 2 in The Distribution of Soil Testate Amoebae under Winter Snow Cover at the Plot-scale Level in Arctic Tundra (Qeqertarsuaq/Disko Island, West Greenland)
Fig. 2. Maps of the spatial distribution of the explanatory environmental variables (A – microtopography; B – snow depth; C – loge(substrate density)) plotted against their spatial coordinates at 57 sampling locations within an 8 × 15 m plot in arctic tundra in Qeqertarsuaq/Disko Island (West Greenland). All data are centred on 0, so square sizes are proportional to the deviations from the mean values at the plot. Open symbols are used for negative values and the filled symbols are used for positive values. Spatial patterns are visualised as aggregations of similar size and colour.
Figure 6. PCA scatter plot for the 2 canonical variates generated from the 7 morphometric characters from 5 in Morphological and biometrical comparisons of the baculum in the genus Nannospalax Palmer, 1903 (Rodentia: Spalacidae) from Turkey with consideration of its taxonomic importance
Figure 6. PCA scatter plot for the 2 canonical variates generated from the 7 morphometric characters from 5 species.
Text-fig. 2. Plot of height versus height to width ratio of leaf scars of the studied species of Protopteris and Oncopteris. in Revision Of Protopteris And Oncopteris Tree Fern Stem Casts From The Late Cretaceous Of Central Europe
Text-fig. 2. Plot of height versus height to width ratio of leaf scars of the studied species of Protopteris and Oncopteris.
Text-fig. 2. Map showing the distribution of localities included in the treatment of Brown (1962), based on the coordinates presented in Appendix Table 1. Localities are distributed across New Mexico (NM), Colorado (CO), Wyoming (WY), Montana (MT), South Dakota (SD) and North Dakota (ND). Also plotted are cited Canadian localities: Joffre Bridge, in Alberta (AB), and Ravenscrag, in Saskatchewan (SK). Map generated with Map-It (2014) website. in Revisions To Roland Brown'S North American Paleocene Flora
Text-fig. 2. Map showing the distribution of localities included in the treatment of Brown (1962), based on the coordinates presented in Appendix Table 1. Localities are distributed across New Mexico (NM), Colorado (CO), Wyoming (WY), Montana (MT), South Dakota (SD) and North Dakota (ND). Also plotted are cited Canadian localities: Joffre Bridge, in Alberta (AB), and Ravenscrag, in Saskatchewan (SK). Map generated with Map-It (2014) website.
Figure. Constrained ordination plot as produced from canonical correspondence analysis (CCA). The variability of environmental variables is summarized on Axis 1 and Axis 2 of the constrained biplot, explaining the variability of the trophic groups included in the red fox's diet. Trophic groups are shown with black line (unfilled) pyramids, whereas environmental variables are shown with black filled pyramids. Proximity and distance of response centroids to predictor centroids indicate positive and negative correlations between them, respectively. in Factors affecting the diet of the red fox (Vulpes vulpes) in a heterogeneous Mediterranean landscape
Figure. Constrained ordination plot as produced from canonical correspondence analysis (CCA). The variability of environmental variables is summarized on Axis 1 and Axis 2 of the constrained biplot, explaining the variability of the trophic groups included in the red fox's diet. Trophic groups are shown with black line (unfilled) pyramids, whereas environmental variables are shown with black filled pyramids. Proximity and distance of response centroids to predictor centroids indicate positive and negative correlations between them, respectively.
Fig. 1. Circular histogram rose plot showing Rhagoletis brncici and R in Differences in larval emergence chronotypes for sympatric Rhagoletis brncici Frías and Rhagoletis conversa (Bréthes) (Diptera, Tephritidae)
Fig. 1. Circular histogram rose plot showing Rhagoletis brncici and R. conversa larval emergence from fruit in a 24-h clock. For both graphs, the arrow shows the mean time of emergence. Main numbers in sections correspond to time in hours. Numbers accompanying circumferences refer to number of individual larvae replicates.
Figure. Measurement data plotted for all nestlings as a function of age for the black stork: a) wing length (WL), b) head length (HL), c) bill length (BL), and d) tarsus length. in Age estimation of black stork (Ciconia nigra) nestlings from wing, bill, head, and tarsus lengths at the time of ringing
Figure. Measurement data plotted for all nestlings as a function of age for the black stork: a) wing length (WL), b) head length (HL), c) bill length (BL), and d) tarsus length.
Fig. 5. Ordination plot for principal components 1 and 2 in Evaluating sexual dimorphism in the ambrosia beetle Xyleborus affinis (Coleoptera: Curculionidae) using geometric morphometrics
Fig. 5. Ordination plot for principal components 1 and 2 representing elytra shape variation between sexes of Xyleborus Affinis: deformation grids describing variation between sexes on the 2 first principal components are presented.
Fig. 6. Ordination plot for principal components 1 and 2 in Evaluating sexual dimorphism in the ambrosia beetle Xyleborus affinis (Coleoptera: Curculionidae) using geometric morphometrics
Fig. 6. Ordination plot for principal components 1 and 2 representing pronotum shape variation between sexes of Xyleborus Affinis: deformation grids describing variation between sexes on the 2 first principal components are presented.
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.