cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4543678
title: ColorShapeLinks 2019/20 Grades Dataset

description: <strong>Overview</strong> This dataset contains grades (0-20 scale) given to students in the context of the ColorShapeLinks AI assignment during the two semesters of the 2019/20 academic year. A number of results presented in the research paper "ColorShapeLinks: A Board Game AI Competition for Educators and Students" are obtained from this dataset. <strong>Reproducibility of results</strong> The results presented in the research paper "ColorShapeLinks: A Board Game AI Competition for Educators and Students", namely in Figure 5 and Table 4, can be reproduced with the Jupyter notebook included with this dataset (file <code>analysis.ipynb</code>). <strong>Licenses</strong> The dataset is made available under a CC-BY 4.0 license (see <code>LICENSE_DATA.txt</code>). The code in the Jupyter Notebook is made available under the MIT license (see <code>LICENSE_CODE.txt</code>).
DOI: 10.6084/m9.figshare.13661246
title: Treadmill data

description: Belt speeds and platform movements
DOI: 10.5519/qd.vt59itzo
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (53 records)
DOI: 10.6084/m9.figshare.13661090
title: Marker data

description: 3D coordinates of 16 lower body markers
DOI: 10.6084/m9.figshare.14098727
title: Appendix S1.xlsx

description: All variables used as predictors for the random forest analysis
DOI: 10.6084/m9.figshare.14098727.v1
title: Appendix S1.xlsx

description: All variables used as predictors for the random forest analysis
DOI: 10.5281/zenodo.4557952
title: OtoMatch: Content-based Eardrum Image Retrieval using Deep Learning

description: There are three classes; Effusion (170), Normal(179), and Tube(96) of eardrum images. Simply use ten fold cross validation for testing and left out set for training and validation. 'Image Names and Labels.xlsx' file contains the labels for each image.
DOI: 10.6084/m9.figshare.14098583.v1
title: Dataset_Compared_Pressure_Vessel_Optimization_Best_Findings.txt

description: This dataset contains an exhaustive list of references related to a well-known engineering design case: the pressure vessel problem. It has been repeatedly used as a reference case for validating a large number of nature inspired optimization algorithms.<br>The dataset contains not only the complete bibliographic references of 55 papers dealing with this engineering design case, but also the best results obtained in the numerical analysis performed on those research works. Detailed tracking of all values corresponding to the cost function and constraints fulfilments or violations are also included.
DOI: 10.6084/m9.figshare.14098583.v2
title: Compared best results for the Pressure Vessel optimization problem reported by a large set of research papers validating Nature inspired search algorithms

description: This dataset contains an exhaustive list of references related to a well-known engineering design case: the pressure vessel problem. It has been repeatedly used as a reference case for validating a large number of nature inspired optimization algorithms.<br>The dataset contains not only the complete bibliographic references of 55 papers dealing with this engineering design case, but also the best results obtained in the numerical analysis performed on those research works. Detailed tracking of all values corresponding to the cost function and constraints fulfilments or violations are also included.The tab separated text file contains the following columns:<br>Columns 1 to 7 (bibliographic reference data)<b>Full reference</b> | <b>Journal </b>| <b>Year </b>| <b>Authors </b>| <b>Search algorithm inspiration</b> |<b>Acronym </b><br><br>Columns 8 to 11 (values of the design variables for the reported best configuration, thickness of shell and cylinder, radius of cylinder and length of cylinder)<b>x<sub>1</sub> </b> (Ts) | <b>x<sub>2</sub> </b> (Th) | <b>x<sub>3</sub> </b> (R) | <b>x<sub>4</sub> </b> (L) <br><br>Column 12 (value of the cost function calculated by the author of this dataset according to the design variables reported by the authors of each paper and presented in columns 8 to 11)<b>f(X)</b><br><br>Columns 13 to 17 (flags indicating which constraints are violated when using the reported values of the design variables) <b>g<sub>1</sub> </b>| <b>g<sub>2</sub> </b>| <b>g<sub>3</sub> </b>| <b>g<sub>4</sub> </b>| <b>T</b> <br>(it is assumed that a constraint is not fulfilled if the expected value is exceeded in more than 0.0001 or the thickness of plates does not follow the problem's definition)<br>Columns 18 and 19 (valid values of the cost function and value of that cost reported by the paper's authors)<b>Valid value </b>| <b>reported f(X)</b><br>Columns 20 to 23 (values of each constraint result calculated using the reported values of the design variables presented in columns 8 to 11)<b>g1 </b>| <b>g2 </b>| <b>g3 </b>| <b>g4</b><br>
DOI: 10.6084/m9.figshare.14098583
title: Compared best results for the Pressure Vessel optimization problem reported by a large set of research papers validating Nature inspired search algorithms

description: This dataset contains an exhaustive list of references related to a well-known engineering design case: the pressure vessel problem. It has been repeatedly used as a reference case for validating a large number of nature inspired optimization algorithms.<br>The dataset contains not only the complete bibliographic references of 55 papers dealing with this engineering design case, but also the best results obtained in the numerical analysis performed on those research works. Detailed tracking of all values corresponding to the cost function and constraints fulfilments or violations are also included.The tab separated text file contains the following columns:<br>Columns 1 to 7 (bibliographic reference data)<b>Full reference</b> | <b>Journal </b>| <b>Year </b>| <b>Authors </b>| <b>Search algorithm inspiration</b> |<b>Acronym </b><br><br>Columns 8 to 11 (values of the design variables for the reported best configuration, thickness of shell and cylinder, radius of cylinder and length of cylinder)<b>x<sub>1</sub> </b> (Ts) | <b>x<sub>2</sub> </b> (Th) | <b>x<sub>3</sub> </b> (R) | <b>x<sub>4</sub> </b> (L) <br><br>Column 12 (value of the cost function calculated by the author of this dataset according to the design variables reported by the authors of each paper and presented in columns 8 to 11)<b>f(X)</b><br><br>Columns 13 to 17 (flags indicating which constraints are violated when using the reported values of the design variables) <b>g<sub>1</sub> </b>| <b>g<sub>2</sub> </b>| <b>g<sub>3</sub> </b>| <b>g<sub>4</sub> </b>| <b>T</b> <br>(it is assumed that a constraint is not fulfilled if the expected value is exceeded in more than 0.0001 or the thickness of plates does not follow the problem's definition)<br>Columns 18 and 19 (valid values of the cost function and value of that cost reported by the paper's authors)<b>Valid value </b>| <b>reported f(X)</b><br>Columns 20 to 23 (values of each constraint result calculated using the reported values of the design variables presented in columns 8 to 11)<b>g1 </b>| <b>g2 </b>| <b>g3 </b>| <b>g4</b><br>
DOI: 10.6084/m9.figshare.14098583.v3
title: Compared best results for the Pressure Vessel optimization problem reported by a large set of research papers validating Nature inspired search algorithms

description: This dataset contains an exhaustive list of references related to a well-known engineering design case: the pressure vessel problem. It has been repeatedly used as a reference case for validating a large number of nature inspired optimization algorithms.<br>The dataset contains not only the complete bibliographic references of 55 papers dealing with this engineering design case, but also the best results obtained in the numerical analysis performed on those research works. Detailed tracking of all values corresponding to the cost function and constraints fulfilments or violations are also included.The tab separated text file contains the following columns:<br>Columns 1 to 7 (bibliographic reference data)<b>Full reference</b> | <b>Journal </b>| <b>Year </b>| <b>Authors </b>| <b>Search algorithm inspiration</b> |<b>Acronym </b><br><br>Columns 8 to 11 (values of the design variables for the reported best configuration, thickness of shell and cylinder, radius of cylinder and length of cylinder)<b>x<sub>1</sub> </b> (Ts) | <b>x<sub>2</sub> </b> (Th) | <b>x<sub>3</sub> </b> (R) | <b>x<sub>4</sub> </b> (L) <br><br>Column 12 (value of the cost function calculated by the author of this dataset according to the design variables reported by the authors of each paper and presented in columns 8 to 11)<b>f(X)</b><br><br>Columns 13 to 17 (flags indicating which constraints are violated when using the reported values of the design variables) <b>g<sub>1</sub> </b>| <b>g<sub>2</sub> </b>| <b>g<sub>3</sub> </b>| <b>g<sub>4</sub> </b>| <b>T</b> <br>(it is assumed that a constraint is not fulfilled if the expected value is exceeded in more than 0.0001 or the thickness of plates does not follow the problem's definition)<br>Columns 18 and 19 (valid values of the cost function and value of that cost reported by the paper's authors)<b>Valid value </b>| <b>reported f(X)</b><br>Columns 20 to 23 (values of each constraint result calculated using the reported values of the design variables presented in columns 8 to 11)<b>g1 </b>| <b>g2 </b>| <b>g3 </b>| <b>g4</b><br>
DOI: 10.7277/y926-2j73
title: Structural Health Monitoring of Tall & Special Buildings (NEES-2014-0979)

description: &lt;p&gt;Title: Structural Health Monitoring of Tall &amp; Special Buildings (NEES-2010-0979)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Year Of Curation: &lt;/strong&gt;2014&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Description: &lt;/strong&gt;The three-year project is funded by the Center for Embedded Networked Sensing, a NSF&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Award: &lt;/strong&gt;N/A&lt;/p&gt; &lt;p&gt;&lt;strong&gt;PIs &amp; CoPIs: &lt;/strong&gt;John Wallace&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dates: &lt;/strong&gt;January 10, 2007 - September 30, 2010&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Organizations: &lt;/strong&gt;University of California, Los Angeles, CA, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Facilities: &lt;/strong&gt;University of California, Los Angeles, CA, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Sponsor: &lt;/strong&gt;N/A&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;finite element model, steel moment resisting frame, Damage Detection,Instrumentation, structural health monitoring&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Publications: &lt;/strong&gt;N/A&lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.17608/k6.auckland.13211276.v1
title: Spatial uniformity of Dell U2415b

description: For explanation, see dataset titled "Spatial uniformity of EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13211276
title: Spatial uniformity of Dell U2415b

description: For explanation, see dataset titled "Spatial uniformity of EIZO CG247X".<br>
DOI: 10.6084/m9.figshare.14075372.v7
title: RNAseq_Goodwin et al_Feb2021

description: RNAseq data supporting the Goodwin et al manuscript
DOI: 10.5281/zenodo.4557921
title: Video stabilisation results obtained using different tools for UAS-based image velocimetry

description: This dataset contains unstabilised and stabilised images from unmanned aerial systems during image velocimetry campaigns. Stabilised images were obtained using seven digital image stabilisation tools: FFT-CUAS (https://bitbucket.org/SIENA_Research/fishstream) FFT-DCH (https://github.com/salpeha/FFTVidStabilization) SSIMS (https://github.com/ljubicicrobert/SSIMS) KLT-IV (https://sourceforge.net/projects/klt-iv) VISION/FAST (https://doi.org/10.17605/OSF.IO/HBRF2) FlowVeloTool/AKAZE (https://github.com/AnetteEltner/FlowVeloTool) Blender (https://www.blender.org) The tools have been tested with three case studies with different types and magnitudes of motion commonly found in UAS/UAV video footages: Kolubara river, Alpine river, and Basento river. The structure of the repository is: /Case_study/Stabilisation_tool_results. To reduce the repository size, only images are included. In order to create videos from the provided images, one can use the provided Python script (for Python v3+).
DOI: 10.5281/zenodo.4557920
title: Video stabilisation results obtained using different tools for UAS-based image velocimetry

description: This dataset contains unstabilised and stabilised images from unmanned aerial systems during image velocimetry campaigns. Stabilised images were obtained using seven digital image stabilisation tools: FFT-CUAS (https://bitbucket.org/SIENA_Research/fishstream) FFT-DCH (https://github.com/salpeha/FFTVidStabilization) SSIMS (https://github.com/ljubicicrobert/SSIMS) KLT-IV (https://sourceforge.net/projects/klt-iv) VISION/FAST (https://doi.org/10.17605/OSF.IO/HBRF2) FlowVeloTool/AKAZE (https://github.com/AnetteEltner/FlowVeloTool) Blender (https://www.blender.org) The tools have been tested with three case studies with different types and magnitudes of motion commonly found in UAS/UAV video footages: Kolubara river, Alpine river, and Basento river. The structure of the repository is: /Case_study/Stabilisation_tool_results. To reduce the repository size, only images are included. In order to create videos from the provided images, one can use the provided Python script (for Python v3+).
DOI: 10.17608/k6.auckland.13218239
title: Flicker cycle-averaged rms luminance for Dell U2415b

description: For details, see file "Flicker cycle-averaged rms luminance for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13218239.v1
title: Flicker cycle-averaged rms luminance for Dell U2415b

description: For details, see file "Flicker cycle-averaged rms luminance for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13218188
title: Flicker cycle-averaged rms luminance for EIZO CG247X

description: Data for Figure 8 of the manuscript. Data are organized into 10 rows and 30 columns. Each column comprises 10 repeated measures. Columns 1 to 6 are for contrast = 20%, flicker frequency = 0.94 ... 30 Hz. Columns 7 to 12 are for contrast = 40%, flicker frequency = 0.94 ... 30 Hz. And so on. Data are normalized as described in the manuscript.<br><br>
DOI: 10.17608/k6.auckland.13218188.v1
title: Flicker cycle-averaged rms luminance for EIZO CG247X

description: Data for Figure 8 of the manuscript. Data are organized into 10 rows and 30 columns. Each column comprises 10 repeated measures. Columns 1 to 6 are for contrast = 20%, flicker frequency = 0.94 ... 30 Hz. Columns 7 to 12 are for contrast = 40%, flicker frequency = 0.94 ... 30 Hz. And so on. Data are normalized as described in the manuscript.<br><br>
DOI: 10.17608/k6.auckland.13217660
title: Flicker cycle-averaged luminance for Dell U2415b

description: For details, see file "Flicker cycle-averaged luminance for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13217660.v1
title: Flicker cycle-averaged luminance for Dell U2415b

description: For details, see file "Flicker cycle-averaged luminance for EIZO CG247X".<br>
DOI: 10.5281/zenodo.4558098
title: OtoMatch: Content-based Eardrum Image Retrieval using Deep Learning

description: There are three classes; Effusion (170), Normal(179), and Tube(96) of eardrum images. Simply use ten fold cross validation for testing and left out set for training and validation. 'Image Names and Labels.xlsx' file contains the labels for each image.
DOI: 10.15131/shef.data.8100638
title: Normalised Squeeziness and Failed Error Propagation Data

description: The data for all of the experiments that were described in "Normalised Squeeziness and Failed Error Propagation".
DOI: 10.17608/k6.auckland.13217651
title: Flicker cycle-averaged luminance for EIZO CG247X

description: Data for Figure 8 of the manuscript. Data are organized into 10 rows and 30 columns. Each column comprises 10 repeated measures. Columns 1 to 6 are for contrast = 20%, flicker frequency = 0.94 ... 30 Hz. Columns 7 to 12 are for contrast = 40%, flicker frequency = 0.94 ... 30 Hz. And so on. Data are normalized, but not offset, as in the manuscript.<br><br>
DOI: 10.17608/k6.auckland.13217651.v1
title: Flicker cycle-averaged luminance for EIZO CG247X

description: Data for Figure 8 of the manuscript. Data are organized into 10 rows and 30 columns. Each column comprises 10 repeated measures. Columns 1 to 6 are for contrast = 20%, flicker frequency = 0.94 ... 30 Hz. Columns 7 to 12 are for contrast = 40%, flicker frequency = 0.94 ... 30 Hz. And so on. Data are normalized, but not offset, as in the manuscript.<br><br>
DOI: 10.18112/openneuro.ds003542.v1.0.0
title: Adult language learners
DOI: 10.17608/k6.auckland.13217435
title: Viewing angle for Dell U2415b

description: For details, see file "Viewing angle for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13217435.v1
title: Viewing angle for Dell U2415b

description: For details, see file "Viewing angle for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13217429
title: Viewing angle for EIZO CG247X

description: Data for Figure 3 of the manuscript. The file is organized in 2 blocks, each comprising 9 rows of 6 repeated measurements. The upper block is for display in the "landscape" orientation. The first column is the angular rotation (degrees) of the turntable. The lower block is as per the upper block, but the display was in the "portrait" orientation. Unit of measure is cd/m^2.<br>
DOI: 10.17608/k6.auckland.13217429.v1
title: Viewing angle for EIZO CG247X

description: Data for Figure 3 of the manuscript. The file is organized in 2 blocks, each comprising 9 rows of 6 repeated measurements. The upper block is for display in the "landscape" orientation. The first column is the angular rotation (degrees) of the turntable. The lower block is as per the upper block, but the display was in the "portrait" orientation. Unit of measure is cd/m^2.<br>
DOI: 10.17608/k6.auckland.13216199.v1
title: Two-pulse time series EIZO CG247X

description: Data for Figure 9 of the manuscript. This file contains 16 columns. Column 1 is time rel. to a trigger, running from approx. -0.05 to 0.5 s. Columns 2,3,4 are the measured, predicted, error time series (see figure) for interpulse interval T = 0. Columns 5,6,7 are the measured, predicted, error time series for interpulse interval T = 16.7ms. And so on. <br><br><br>
DOI: 10.17608/k6.auckland.13216199
title: Two-pulse time series EIZO CG247X

description: Data for Figure 9 of the manuscript. This file contains 16 columns. Column 1 is time rel. to a trigger, running from approx. -0.05 to 0.5 s. Columns 2,3,4 are the measured, predicted, error time series (see figure) for interpulse interval T = 0. Columns 5,6,7 are the measured, predicted, error time series for interpulse interval T = 16.7ms. And so on. <br><br><br>
DOI: 10.17608/k6.auckland.13215698.v1
title: Two-pulse time series Dell U2415b

description: For details, see file "Two-pulse time series EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13215698
title: Two-pulse time series Dell U2415b

description: For details, see file "Two-pulse time series EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13211294
title: Spatial uniformity of EIZO CG247X

description: Data for Figure 2 of the manuscript. Rows 1 to 3 are low, medium, and high-luminance measurements, respectively, at display position 1. Rows 4 to 6 are low, medium, and high-luminance measurements, respectively, at display position 2. And so on. Columns are repeated measures. Unit of measure is cd/m^2.<br>
DOI: 10.17608/k6.auckland.13211294.v1
title: Spatial uniformity of EIZO CG247X

description: Data for Figure 2 of the manuscript. Rows 1 to 3 are low, medium, and high-luminance measurements, respectively, at display position 1. Rows 4 to 6 are low, medium, and high-luminance measurements, respectively, at display position 2. And so on. Columns are repeated measures. Unit of measure is cd/m^2.<br>
DOI: 10.17608/k6.auckland.13211423.v1
title: Time series (for computing Fourier spectra) for EIZO CG247X

description: Time series data for Figure 4 of the manuscript. The file contains 110 time series (columns), each is 1 second duration, sampled at 100kHz. Time series 1 to 10 (ie., columns 1 to 10) are measurements of a test patch at 0% luminance. Time series 11 to 20 are measurements of a test patch at 10% luminance. And so on. Unit of measure is mV.<br>
DOI: 10.17608/k6.auckland.13211423
title: Time series (for computing Fourier spectra) for EIZO CG247X

description: Time series data for Figure 4 of the manuscript. The file contains 110 time series (columns), each is 1 second duration, sampled at 100kHz. Time series 1 to 10 (ie., columns 1 to 10) are measurements of a test patch at 0% luminance. Time series 11 to 20 are measurements of a test patch at 10% luminance. And so on. Unit of measure is mV.<br>
DOI: 10.17608/k6.auckland.13211429
title: Time series (for computing Fourier spectra) for Dell U2415b

description: For details, see file "Time series (for computing Fourier spectra) for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13211429.v1
title: Time series (for computing Fourier spectra) for Dell U2415b

description: For details, see file "Time series (for computing Fourier spectra) for EIZO CG247X".<br>
DOI: 10.17608/k6.auckland.13211471
title: Rise times for Dell U2415b

description: Data for Figure 5 in the manuscript. Rows 1 through 5 are rise times for transitions from 0% luminance to 0, 25, 50, 75, and 100% luminance, respectively. Rows 6 through 10 are rise times for transitions from 25% luminance to 0, 25, 50, 75, and 100% luminance, respectively. And so on. Negative numbers (-1 or -2) are place-holders and can safely be ignored (eg., there is no rise from 0% to 0% luminance, nor from 25% to 0% luminance.) Columns are repeated measures (10 for each transition).<br><br>Unit of measure is ms.<br>
DOI: 10.17608/k6.auckland.13211471.v1
title: Rise times for Dell U2415b

description: Data for Figure 5 in the manuscript. Rows 1 through 5 are rise times for transitions from 0% luminance to 0, 25, 50, 75, and 100% luminance, respectively. Rows 6 through 10 are rise times for transitions from 25% luminance to 0, 25, 50, 75, and 100% luminance, respectively. And so on. Negative numbers (-1 or -2) are place-holders and can safely be ignored (eg., there is no rise from 0% to 0% luminance, nor from 25% to 0% luminance.) Columns are repeated measures (10 for each transition).<br><br>Unit of measure is ms.<br>
DOI: 10.17608/k6.auckland.13211477.v1
title: Fall times for Dell U2415b

description: Data for Figure 5 in the manuscript. Rows 1 through 5 are fall times for transitions from 0% luminance to 0, 25, 50, 75, and 100% luminance, respectively. Rows 6 through 10 are fall times for transitions from 25% luminance to 0, 25, 50, 75, and 100% luminance, respectively. And so on. Negative numbers (-1 or -2) are place-holders and can safely be ignored (eg., there is no fall from 0% to 0% luminance, nor from 0% to 25% luminance.) Columns are repeated measures (10 for each transition). Unit of measure is ms.<br>
DOI: 10.17608/k6.auckland.13211477
title: Fall times for Dell U2415b

description: Data for Figure 5 in the manuscript. Rows 1 through 5 are fall times for transitions from 0% luminance to 0, 25, 50, 75, and 100% luminance, respectively. Rows 6 through 10 are fall times for transitions from 25% luminance to 0, 25, 50, 75, and 100% luminance, respectively. And so on. Negative numbers (-1 or -2) are place-holders and can safely be ignored (eg., there is no fall from 0% to 0% luminance, nor from 0% to 25% luminance.) Columns are repeated measures (10 for each transition). Unit of measure is ms.<br>
DOI: 10.17608/k6.auckland.13211489.v1
title: Rise times for EIZO CG247X

description: For details, see file "Rise times for Dell U2415b".<br>
DOI: 10.17608/k6.auckland.13211489
title: Rise times for EIZO CG247X

description: For details, see file "Rise times for Dell U2415b".<br>
DOI: 10.17608/k6.auckland.13211495.v1
title: Fall times for EIZO CG247X

description: For details, see file "Fall times for Dell U2415b".<br>
DOI: 10.17608/k6.auckland.13211495
title: Fall times for EIZO CG247X

description: For details, see file "Fall times for Dell U2415b".<br>