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Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction


The file contains raw data collected from 9 pedestrians. Three of them walked in Track 1, another three walked in Track 2 and the last three walked in Track 3. All the pedestrians ended their walks at the starting point. Track 1 and Track 3 cover a distance of 150.3m. While, the Track covers a distance of 111.4m.

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Dataset Details

Citation Author(s):
Submitted by:
Mohd Nazrin Muhammad
Last updated:
Thu, 03/22/2018 - 03:14
DOI:
10.21227/H2ND4W
Data Format:
 
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[1] , "Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2ND4W. Accessed: Apr. 23, 2018.
@data{h2nd4w-18,
doi = {10.21227/H2ND4W},
url = {http://dx.doi.org/10.21227/H2ND4W},
author = { },
publisher = {IEEE Dataport},
title = {Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction},
year = {2018} }
TY - DATA
T1 - Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2ND4W
ER -
. (2018). Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction. IEEE Dataport. http://dx.doi.org/10.21227/H2ND4W
, 2018. Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction. Available at: http://dx.doi.org/10.21227/H2ND4W.
. (2018). "Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction." Web.
1. . Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2ND4W
. "Raw data for Indoor Pedestrian Tracking Using Consumer-grade Inertial Sensors with PZTD Heading Correction." doi: 10.21227/H2ND4W

TEDP: An enhanced topology discovery service for Software-Defined Networking


   Packet INFlow_ModPacket OutData PlaneTEDP-SMedium10766,562510823,751 Deviation2261,474562261,415880 Variance4794625,54794376,690 TEDP-S*Medium170,625227,43751170,625Deviation2,305789811,7114808402,3057898Variance4,9843752,7460937504,984375TEDP_HMedium146,000,000,00146,13Deviation0,730,000,000,81Variance0,500,000,000,61LLDPTheoretical 14444144144TEDP-STheoretical 144881144TEDP-HTheoretical 14400144

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Dataset Details

Citation Author(s):
Submitted by:
Joaquin Alvarez...
Last updated:
Tue, 03/20/2018 - 03:47
DOI:
10.21227/H2XT00
Data Format:
 
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[1] , "TEDP: An enhanced topology discovery service for Software-Defined Networking", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2XT00. Accessed: Apr. 23, 2018.
@data{h2xt00-18,
doi = {10.21227/H2XT00},
url = {http://dx.doi.org/10.21227/H2XT00},
author = { },
publisher = {IEEE Dataport},
title = {TEDP: An enhanced topology discovery service for Software-Defined Networking},
year = {2018} }
TY - DATA
T1 - TEDP: An enhanced topology discovery service for Software-Defined Networking
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2XT00
ER -
. (2018). TEDP: An enhanced topology discovery service for Software-Defined Networking. IEEE Dataport. http://dx.doi.org/10.21227/H2XT00
, 2018. TEDP: An enhanced topology discovery service for Software-Defined Networking. Available at: http://dx.doi.org/10.21227/H2XT00.
. (2018). "TEDP: An enhanced topology discovery service for Software-Defined Networking." Web.
1. . TEDP: An enhanced topology discovery service for Software-Defined Networking [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2XT00
. "TEDP: An enhanced topology discovery service for Software-Defined Networking." doi: 10.21227/H2XT00

Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems


This dataset contains the numerical results and Excel graphing used to create the results images in the main paper.

 

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Dataset Details

Citation Author(s):
Submitted by:
Andrew Roscoe
Last updated:
Tue, 03/20/2018 - 09:21
DOI:
10.21227/H20926
Data Format:
Links:
 
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[1] , "Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H20926. Accessed: Apr. 23, 2018.
@data{h20926-17,
doi = {10.21227/H20926},
url = {http://dx.doi.org/10.21227/H20926},
author = { },
publisher = {IEEE Dataport},
title = {Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems},
year = {2017} }
TY - DATA
T1 - Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H20926
ER -
. (2017). Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems. IEEE Dataport. http://dx.doi.org/10.21227/H20926
, 2017. Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems. Available at: http://dx.doi.org/10.21227/H20926.
. (2017). "Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems." Web.
1. . Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H20926
. "Dealing with Front-End White Noise on Differentiated Measurements such as Frequency and ROCOF in Power Systems." doi: 10.21227/H20926

travel time data


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Dataset Details

Citation Author(s):
Submitted by:
Sheng Jin
Last updated:
Thu, 10/12/2017 - 13:01
DOI:
10.21227/H2R33B
Data Format:
 
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[1] , "travel time data", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2R33B. Accessed: Apr. 23, 2018.
@data{h2r33b-17,
doi = {10.21227/H2R33B},
url = {http://dx.doi.org/10.21227/H2R33B},
author = { },
publisher = {IEEE Dataport},
title = {travel time data},
year = {2017} }
TY - DATA
T1 - travel time data
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2R33B
ER -
. (2017). travel time data. IEEE Dataport. http://dx.doi.org/10.21227/H2R33B
, 2017. travel time data. Available at: http://dx.doi.org/10.21227/H2R33B.
. (2017). "travel time data." Web.
1. . travel time data [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2R33B
. "travel time data." doi: 10.21227/H2R33B

BHI 2017: Big Data Analytics Competition


Data Science is all about the processes and methods to access and analyze data to gain insights for informed decision making. To promote the awareness and analytic technology of Big Data, IEEE EMBS and the IEEE Big Data Initiative are organizing a Data Analytics Competition. The competition will be held during the International Conference on Biomedical and Health Informatics (IEEE BHI2017), 16-19 February 2017 in Orlando, Florida, and is open to all participants of the conference.


The submission period for this data competition has ended.

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Dataset Details

Citation Author(s):
Submitted by:
Chris Franzino
Last updated:
Tue, 08/08/2017 - 10:52
DOI:
10.21227/H2W886
Data Format:
Links:
 
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[1] , "BHI 2017: Big Data Analytics Competition", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2W886. Accessed: Apr. 23, 2018.
@data{h2w886-16,
doi = {10.21227/H2W886},
url = {http://dx.doi.org/10.21227/H2W886},
author = { },
publisher = {IEEE Dataport},
title = {BHI 2017: Big Data Analytics Competition},
year = {2016} }
TY - DATA
T1 - BHI 2017: Big Data Analytics Competition
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H2W886
ER -
. (2016). BHI 2017: Big Data Analytics Competition. IEEE Dataport. http://dx.doi.org/10.21227/H2W886
, 2016. BHI 2017: Big Data Analytics Competition. Available at: http://dx.doi.org/10.21227/H2W886.
. (2016). "BHI 2017: Big Data Analytics Competition." Web.
1. . BHI 2017: Big Data Analytics Competition [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H2W886
. "BHI 2017: Big Data Analytics Competition." doi: 10.21227/H2W886