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Publications: Datasets

  1. Visualized layer-wise visual features in deep residual neural network

    2017-06-29 12:25:42 | Contributor(s): Haiguang Wen, Junxing Shi, Wei Chen, Zhongming Liu | doi:10.4231/R7PR7T1G

    Deep residual neural network is a brain-inspired computational model. 50 layers of neuron-like computational units are stacked into a bottom-up hierarchy. Features encoded at units are visualized for intuitively understanding the internal...
  2. ACI 445B Shear Wall Database

    2017-06-28 14:13:04 | Contributor(s): Merve Usta, Santiago Pujol, ACI Subcommittee 445B, Aishwarya Puranam, Cheng Song, Ying Wang | doi:10.4231/R7HH6H39

    This structural wall performance database is being compiled and vetted several times per year by ACI (American Concrete Institute) Subcommittee 445B and contained 521 wall tests as of April 24, 2017.
  3. Drosophila Optical Stimulator

    2017-06-27 14:06:59 | Contributor(s): Xinping Chen, Walter Leon-Salas, Taylor Zigon, Donald Ready, Vikki Weake | doi:10.4231/R73N21JG

    This publication contains the electronic files required to build an optical stimulator for fruit flies. The stimulator uses red and blue light-emitting diodes (LEDs) and an embedded computer to generate light at different power density levels.
  4. 32-digit values of the first 200 recurrence coefficients for the weight function w(x)=[log(1/x)]^2 on [0,1]

    2017-08-14 16:36:18 | Contributor(s): Walter Gautschi | doi:10.4231/R7W95769

    32-digit values of the first 200 recurrence coefficients for the weight function w(x)=x^a*[log(1/x)]^b on [0,1], a=0, b=2
  5. Drosophila Optical Stimulator - software files

    2017-06-23 16:01:00 | Contributor(s): Xinping Chen, Walter Leon-Salas, Taylor Zigon, Donald Ready, Vikki Weake | doi:10.4231/R7222RS4

    This publication contains the software required to build an optical stimulator for fruit flies. The stimulator uses red and blue light-emitting diodes (LEDs) and an embedded computer to generate light at different power density levels.
  6. Drosophila Optical Stimulator - hardware files

    2017-06-23 16:01:28 | Contributor(s): Xinping Chen, Walter Leon-Salas, Taylor Zigon, Donald Ready, Vikki Weake | doi:10.4231/R75T3HHJ

    This publication contains the electronic files required to build an optical stimulator for fruit flies. The stimulator uses red and blue light-emitting diodes (LEDs) and an embedded computer to generate light at different power density levels.
  7. Purdue University Buildings Demolition, Construction Images, April 2017, MATH Building Camera

    2017-06-12 19:59:52 | Contributor(s): Darcy M. Bullock, Alexander M. Hainen, Andrew T. Sydelko, David Burford, Michael Witt | doi:10.4231/R7348HDK

    Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
  8. Purdue University Buildings Demolition, Construction Images, May 2017, MATH Building Camera

    2017-06-12 20:00:44 | Contributor(s): Darcy M. Bullock, Alexander M. Hainen, Andrew T. Sydelko, David Burford, Michael Witt | doi:10.4231/R7ZG6Q8Q

    Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
  9. Purdue University Buildings Demolition, Construction Images, March 2017, MATH Building Camera

    2017-06-12 20:00:16 | Contributor(s): Darcy M. Bullock, Alexander M. Hainen, Andrew T. Sydelko, David Burford, Michael Witt | doi:10.4231/R7BP00SZ

    Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
  10. Purdue University Buildings Demolition, Construction Images, March 2017, POTR Building Camera 2

    2017-06-12 19:59:07 | Contributor(s): Darcy M. Bullock, Alexander M. Hainen, Andrew T. Sydelko, David Burford, Michael Witt | doi:10.4231/R76W983J

    Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
  11. Code and Dataset for TARP Detection Benchmarks

    2017-05-16 20:07:55 | Contributor(s): Kelsie Larson, Mireille Boutin | doi:10.4231/R7ST7MVC

    The TARP method uses random projections, followed by threshold classifications, to construct receiver-operating characteristic curves and uncover underlying structure in the given data.
  12. Rockville Road Bridge Emergency Reconstruction

    2017-05-12 20:42:32 | Contributor(s): Wayne A. Bunnell, Steven J. Harney, Edward D. Cox, Elsadig Ibrahim, Darcy M. Bullock | doi:10.4231/R7XK8CJN

    This video documents the emergency reconstruction of a damaged section of Rockville Road in Indianapolis, Indiana.
  13. Purdue University Buildings Demolition, Construction Images, December 2016, MATH Building Camera

    2017-05-09 14:05:14 | Contributor(s): Darcy M. Bullock, Alexander M. Hainen, Andrew T. Sydelko, David Burford, Michael Witt | doi:10.4231/R7W9574D

    Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
  14. 32-digit values of the first 100 recurrence coefficients for a Binet-like weight function

    2017-05-31 12:22:27 | Contributor(s): Walter Gautschi | doi:10.4231/R73B5X5B

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=log(1+exp(-abs(x))) on [-Inf,Inf]
  15. 32-digit values of the first 100 recurrence coefficients for a half-range Binet-like weight function

    2017-05-24 19:24:52 | Contributor(s): Walter Gautschi | doi:10.4231/R7736NX3

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=log(1+exp(-x)) on [0,Inf]
  16. 32-digit values of the first 64 recurrence coefficients for the Krylov-Pal'tsev weight function on [0,Inf] with exponent 1

    2017-05-10 19:23:36 | Contributor(s): Walter Gautschi | doi:10.4231/R72J68W1

    32-digit values of the first 64 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*log(1+1/x) on [0,Inf], a=1
  17. 32-digit values of the first 63 recurrence coefficients for the Krylov-Pal'tsev weight function on [0,Inf] with exponent 3

    2017-05-10 19:22:50 | Contributor(s): Walter Gautschi | doi:10.4231/R79Z92XF

    32-digit values of the first 63 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*log(1+1/x) on [0,Inf], a=3
  18. 32-digit values of the first 62 recurrence coefficients for the Krylov-Pal'tsev weight function on [0,Inf] with exponent 5

    2017-05-10 19:22:12 | Contributor(s): Walter Gautschi | doi:10.4231/R7FQ9TMB

    32-digit values of the first 62 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*log(1+1/x) on [0,Inf], a=5
  19. 32-digit values of the first 65 recurrence coefficients for the Krylov-Pal'tsev weight function on [0,Inf] with exponent 1/2

    2017-05-10 19:21:21 | Contributor(s): Walter Gautschi | doi:10.4231/R7KH0KBM

    32-digit values of the first 65 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*log(1+1/x) on [0,Inf], a=1/2
  20. 32-digit values of the first 65 recurrence coefficients for the Krylov-Pal'tsev weight function on [0,Inf] with exponent -1/2

    2017-05-10 18:44:21 | Contributor(s): Walter Gautschi | doi:10.4231/R7Q81B3S

    32-digit values of the first 65 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*log(1+1/x) on [0,Inf], a=-1/2