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Real-life Power Quality Sags


The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances.

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Dataset Details

Citation Author(s):
Submitted by:
Juan Jose Gonza...
Last updated:
Wed, 03/28/2018 - 10:54
DOI:
10.21227/H2K88D
Data Format:
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[1] , "Real-life Power Quality Sags ", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2K88D. Accessed: Jun. 22, 2018.
@data{h2k88d-17,
doi = {10.21227/H2K88D},
url = {http://dx.doi.org/10.21227/H2K88D},
author = { },
publisher = {IEEE Dataport},
title = {Real-life Power Quality Sags },
year = {2017} }
TY - DATA
T1 - Real-life Power Quality Sags
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2K88D
ER -
. (2017). Real-life Power Quality Sags . IEEE Dataport. http://dx.doi.org/10.21227/H2K88D
, 2017. Real-life Power Quality Sags . Available at: http://dx.doi.org/10.21227/H2K88D.
. (2017). "Real-life Power Quality Sags ." Web.
1. . Real-life Power Quality Sags [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2K88D
. "Real-life Power Quality Sags ." doi: 10.21227/H2K88D

Peak power generated through the combustion reaction of propane


The file contains two arrays:

 

InCondSim: the initial conditions of the combustion system organized as C3H8, C2H5, CH3, O2, C3H7, HO2, H7C3, CH4, HH, H2, OO, OH, H2O, HO2, H2O2, C2H4, C3H6, C3H5, CH2O, HCO, MM, CH3O, C2H6, C2H3, C2H2, C2H, CO, CH2, CO2.

 

peakPWR: the peak power generated by the combustion.

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Dataset Details

Citation Author(s):
Submitted by:
Corrado Possieri
Last updated:
Wed, 06/20/2018 - 08:55
DOI:
10.21227/H2XH4D
Data Format:
 
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[1] , "Peak power generated through the combustion reaction of propane", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2XH4D. Accessed: Jun. 22, 2018.
@data{h2xh4d-18,
doi = {10.21227/H2XH4D},
url = {http://dx.doi.org/10.21227/H2XH4D},
author = { },
publisher = {IEEE Dataport},
title = {Peak power generated through the combustion reaction of propane},
year = {2018} }
TY - DATA
T1 - Peak power generated through the combustion reaction of propane
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2XH4D
ER -
. (2018). Peak power generated through the combustion reaction of propane. IEEE Dataport. http://dx.doi.org/10.21227/H2XH4D
, 2018. Peak power generated through the combustion reaction of propane. Available at: http://dx.doi.org/10.21227/H2XH4D.
. (2018). "Peak power generated through the combustion reaction of propane." Web.
1. . Peak power generated through the combustion reaction of propane [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2XH4D
. "Peak power generated through the combustion reaction of propane." doi: 10.21227/H2XH4D

Channels Switch Sequences of 300 IPTV viewers in a month


This dataset includes  the Channels Switch Sequences of 300 IPTV viewers in Guangzhou, P.R. China, in Augest, 2014. There are 4 columns in the file, which represent viewer ID, the current channel number, the next channel number, the date of the month, respectively. The first column, the ID code of a viewer, ranks in descent with the times the viewer watched tv channels. The more times a viewer watches tv channels, the bigger the ID is. In a day, the rows are time series and generated step by step as the real watching tv behavior. 

 

 

 

 

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Dataset Details

Citation Author(s):
Submitted by:
Can Yang
Last updated:
Tue, 06/05/2018 - 06:52
DOI:
10.21227/H2396N
Data Format:
 
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[1] , "Channels Switch Sequences of 300 IPTV viewers in a month", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2396N. Accessed: Jun. 22, 2018.
@data{h2396n-18,
doi = {10.21227/H2396N},
url = {http://dx.doi.org/10.21227/H2396N},
author = { },
publisher = {IEEE Dataport},
title = {Channels Switch Sequences of 300 IPTV viewers in a month},
year = {2018} }
TY - DATA
T1 - Channels Switch Sequences of 300 IPTV viewers in a month
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2396N
ER -
. (2018). Channels Switch Sequences of 300 IPTV viewers in a month. IEEE Dataport. http://dx.doi.org/10.21227/H2396N
, 2018. Channels Switch Sequences of 300 IPTV viewers in a month. Available at: http://dx.doi.org/10.21227/H2396N.
. (2018). "Channels Switch Sequences of 300 IPTV viewers in a month." Web.
1. . Channels Switch Sequences of 300 IPTV viewers in a month [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2396N
. "Channels Switch Sequences of 300 IPTV viewers in a month." doi: 10.21227/H2396N

Channels Switch Sequences of 300 IPTV viewers in a month


This dataset includes  the Channels Switch Sequences of 300 IPTV viewers in Guangzhou, P.R. China, in Augest, 2014.

There are 4 columns in the file, which represent viewer ID, the current channel number, th next channel number, the date of the month, respectively.

The first column, the ID code of a viewter, ranks with the times the viewer watched tv channels. The more times a viewer watches tv channels, the bigger

the ID is. In a day, the rows are time series and generated step by step as the real watching tv behavior. 

 

 

 

 

Dataset Files

No Data files have been uploaded.

Dataset Details

Citation Author(s):
Submitted by:
Can Yang
Last updated:
Tue, 06/05/2018 - 06:40
DOI:
10.21227/H27376
Data Format:
 
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[1] , "Channels Switch Sequences of 300 IPTV viewers in a month", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H27376. Accessed: Jun. 22, 2018.
@data{h27376-18,
doi = {10.21227/H27376},
url = {http://dx.doi.org/10.21227/H27376},
author = { },
publisher = {IEEE Dataport},
title = {Channels Switch Sequences of 300 IPTV viewers in a month},
year = {2018} }
TY - DATA
T1 - Channels Switch Sequences of 300 IPTV viewers in a month
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H27376
ER -
. (2018). Channels Switch Sequences of 300 IPTV viewers in a month. IEEE Dataport. http://dx.doi.org/10.21227/H27376
, 2018. Channels Switch Sequences of 300 IPTV viewers in a month. Available at: http://dx.doi.org/10.21227/H27376.
. (2018). "Channels Switch Sequences of 300 IPTV viewers in a month." Web.
1. . Channels Switch Sequences of 300 IPTV viewers in a month [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H27376
. "Channels Switch Sequences of 300 IPTV viewers in a month." doi: 10.21227/H27376

Timeline data for "The Rise and Evolution of Agile Software Development"


This table summarizes the results of our search of topics/categories on ACM DL and IEEE Xplore and lists the earliest relevant publication found in each topic/category along with the title, authors, direct links, and venue and/or remarks as appropriate.

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Dataset Details

Citation Author(s):
Submitted by:
Rashina Hoda
Last updated:
Sun, 06/03/2018 - 20:18
DOI:
10.21227/H2T08T
Data Format:
 
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[1] , "Timeline data for "The Rise and Evolution of Agile Software Development"", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2T08T. Accessed: Jun. 22, 2018.
@data{h2t08t-18,
doi = {10.21227/H2T08T},
url = {http://dx.doi.org/10.21227/H2T08T},
author = { },
publisher = {IEEE Dataport},
title = {Timeline data for "The Rise and Evolution of Agile Software Development"},
year = {2018} }
TY - DATA
T1 - Timeline data for "The Rise and Evolution of Agile Software Development"
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2T08T
ER -
. (2018). Timeline data for "The Rise and Evolution of Agile Software Development". IEEE Dataport. http://dx.doi.org/10.21227/H2T08T
, 2018. Timeline data for "The Rise and Evolution of Agile Software Development". Available at: http://dx.doi.org/10.21227/H2T08T.
. (2018). "Timeline data for "The Rise and Evolution of Agile Software Development"." Web.
1. . Timeline data for "The Rise and Evolution of Agile Software Development" [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2T08T
. "Timeline data for "The Rise and Evolution of Agile Software Development"." doi: 10.21227/H2T08T

Revolution in software engineering


The software industry is a very flexible phenomenon. Adding network concepts to this industry means we have countless actors with different roles on a single ground. Its players include software developers, customers, users, and software components. The purpose of this article is to create a better way to communicate between these actors.We can imagine software engineering different and more effective than the current situation.

Dataset Files

No Data files have been uploaded.

Dataset Details

Citation Author(s):
Submitted by:
mohsen pirnajmeddin
Last updated:
Sat, 06/02/2018 - 00:24
DOI:
10.21227/H23H3K
 
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Documentation

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[1] , "Revolution in software engineering", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H23H3K. Accessed: Jun. 22, 2018.
@data{h23h3k-18,
doi = {10.21227/H23H3K},
url = {http://dx.doi.org/10.21227/H23H3K},
author = { },
publisher = {IEEE Dataport},
title = {Revolution in software engineering},
year = {2018} }
TY - DATA
T1 - Revolution in software engineering
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H23H3K
ER -
. (2018). Revolution in software engineering. IEEE Dataport. http://dx.doi.org/10.21227/H23H3K
, 2018. Revolution in software engineering. Available at: http://dx.doi.org/10.21227/H23H3K.
. (2018). "Revolution in software engineering." Web.
1. . Revolution in software engineering [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H23H3K
. "Revolution in software engineering." doi: 10.21227/H23H3K

RSSI-Based Indoor Localization with the Internet of Things


RSSI-Dataset

The RSSI-Dataset provides a comprehensive set of Received Signal Strength Indication (RSSI) readings from within two indoor office buildings. Four wireless technologies were used:

  • Zigbee (IEEE 802.15.4),
  • WiFi (IEEE 802. 11),
  • Bluetooth Low Energy (BLE) and
  • Long Range Area-Wide Network (LoRaWAN).

For experimentation Arduinos Raspberry Pi, XBees, Gimbal beacons Series 10 and Dragino LoRa Shield were also used.  

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Dataset Details

Citation Author(s):
Submitted by:
PETROS SPACHOS
Last updated:
Wed, 05/30/2018 - 20:51
DOI:
10.21227/H25D5X
Data Format:
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[1] , "RSSI-Based Indoor Localization with the Internet of Things", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H25D5X. Accessed: Jun. 22, 2018.
@data{h25d5x-18,
doi = {10.21227/H25D5X},
url = {http://dx.doi.org/10.21227/H25D5X},
author = { },
publisher = {IEEE Dataport},
title = {RSSI-Based Indoor Localization with the Internet of Things},
year = {2018} }
TY - DATA
T1 - RSSI-Based Indoor Localization with the Internet of Things
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H25D5X
ER -
. (2018). RSSI-Based Indoor Localization with the Internet of Things. IEEE Dataport. http://dx.doi.org/10.21227/H25D5X
, 2018. RSSI-Based Indoor Localization with the Internet of Things. Available at: http://dx.doi.org/10.21227/H25D5X.
. (2018). "RSSI-Based Indoor Localization with the Internet of Things." Web.
1. . RSSI-Based Indoor Localization with the Internet of Things [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H25D5X
. "RSSI-Based Indoor Localization with the Internet of Things." doi: 10.21227/H25D5X

On Automatically Assessing Code Understandability


Understanding software is an inherent requirement for many maintenance and evolution tasks. Without a thorough understanding of the code, developers would not be able to fix bugs or add new features timely.  Measuring code understandability might be useful to guide developers in writing better code, and could also help in estimating the effort required to modify code components. Unfortunately, there are no metrics designed to assess the understandability of code snippets. 

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Dataset Details

Citation Author(s):
Submitted by:
Simone Scalabrino
Last updated:
Thu, 05/17/2018 - 07:25
DOI:
10.21227/H24M3X
Data Format:
Links:
 
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[1] , "On Automatically Assessing Code Understandability", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H24M3X. Accessed: Jun. 22, 2018.
@data{h24m3x-18,
doi = {10.21227/H24M3X},
url = {http://dx.doi.org/10.21227/H24M3X},
author = { },
publisher = {IEEE Dataport},
title = {On Automatically Assessing Code Understandability},
year = {2018} }
TY - DATA
T1 - On Automatically Assessing Code Understandability
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H24M3X
ER -
. (2018). On Automatically Assessing Code Understandability. IEEE Dataport. http://dx.doi.org/10.21227/H24M3X
, 2018. On Automatically Assessing Code Understandability. Available at: http://dx.doi.org/10.21227/H24M3X.
. (2018). "On Automatically Assessing Code Understandability." Web.
1. . On Automatically Assessing Code Understandability [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H24M3X
. "On Automatically Assessing Code Understandability." doi: 10.21227/H24M3X

Jaw Motion and Jaw Kinematics Model


We recorded and extracted 833 jaw poses of a real person from 3-calibrated cameras. Each jaw pose corresponds to a rigid motion (rotation and translation) and is mapped to the Lie algebra of rigid motion, i.e., se(3). In the file "JawPose.txt", each row stores a jaw pose, corresponding to a 6-dimension vector in se(3), the first three is the rotation component, while the last three is the translation component.

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Dataset Details

Citation Author(s):
Submitted by:
Wenwu Yang
Last updated:
Fri, 05/11/2018 - 19:17
DOI:
10.21227/H2JT1Z
Data Format:
 
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[1] , "Jaw Motion and Jaw Kinematics Model", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2JT1Z. Accessed: Jun. 22, 2018.
@data{h2jt1z-18,
doi = {10.21227/H2JT1Z},
url = {http://dx.doi.org/10.21227/H2JT1Z},
author = { },
publisher = {IEEE Dataport},
title = {Jaw Motion and Jaw Kinematics Model},
year = {2018} }
TY - DATA
T1 - Jaw Motion and Jaw Kinematics Model
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2JT1Z
ER -
. (2018). Jaw Motion and Jaw Kinematics Model. IEEE Dataport. http://dx.doi.org/10.21227/H2JT1Z
, 2018. Jaw Motion and Jaw Kinematics Model. Available at: http://dx.doi.org/10.21227/H2JT1Z.
. (2018). "Jaw Motion and Jaw Kinematics Model." Web.
1. . Jaw Motion and Jaw Kinematics Model [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2JT1Z
. "Jaw Motion and Jaw Kinematics Model." doi: 10.21227/H2JT1Z

Tourists Reviews Dataset


This dataset contains user online reviews of two tourist places namely London' Parks and Art Museums.

London Parks Reviews

In this dataset, the top five most visited parks are selected, such as St. James' Park, Hyde Park, Regent's Park, Kensington Park and Greenwich Park. For each park, 600 reviews from Jan to Sep 2017 are present in CSV format.

London Art Museums

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Dataset Details

Citation Author(s):
Submitted by:
Muhammad Usman
Last updated:
Mon, 05/07/2018 - 12:07
DOI:
10.21227/H29H4T
Data Format:
 
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[1] , "Tourists Reviews Dataset", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H29H4T. Accessed: Jun. 22, 2018.
@data{h29h4t-18,
doi = {10.21227/H29H4T},
url = {http://dx.doi.org/10.21227/H29H4T},
author = { },
publisher = {IEEE Dataport},
title = {Tourists Reviews Dataset},
year = {2018} }
TY - DATA
T1 - Tourists Reviews Dataset
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H29H4T
ER -
. (2018). Tourists Reviews Dataset. IEEE Dataport. http://dx.doi.org/10.21227/H29H4T
, 2018. Tourists Reviews Dataset. Available at: http://dx.doi.org/10.21227/H29H4T.
. (2018). "Tourists Reviews Dataset." Web.
1. . Tourists Reviews Dataset [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H29H4T
. "Tourists Reviews Dataset." doi: 10.21227/H29H4T

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