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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: Apr. 23, 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

Machine Learning: A Science Mapping Analysis


Machine learning is becoming increasingly important for companies and the scientific community. It allows us to generate solutions for several problems faced by society. In this study, we perform a science mapping analysis on the machine learning research, in order to provide an overview of the scientific work during the last decade in this area and to show trends that could be the basis for future developments in the field of computer science. This study was carried out using the CiteSpace and SciMAT tools based on results from Scopus and Clarivate Web of Science.

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Dataset Details

Citation Author(s):
Submitted by:
Juan Rincon-Patino
Last updated:
Sat, 04/21/2018 - 22:28
DOI:
10.21227/H2337Z
Data Format:
 
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[1] , "Machine Learning: A Science Mapping Analysis", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2337Z. Accessed: Apr. 23, 2018.
@data{h2337z-18,
doi = {10.21227/H2337Z},
url = {http://dx.doi.org/10.21227/H2337Z},
author = { },
publisher = {IEEE Dataport},
title = {Machine Learning: A Science Mapping Analysis},
year = {2018} }
TY - DATA
T1 - Machine Learning: A Science Mapping Analysis
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2337Z
ER -
. (2018). Machine Learning: A Science Mapping Analysis. IEEE Dataport. http://dx.doi.org/10.21227/H2337Z
, 2018. Machine Learning: A Science Mapping Analysis. Available at: http://dx.doi.org/10.21227/H2337Z.
. (2018). "Machine Learning: A Science Mapping Analysis." Web.
1. . Machine Learning: A Science Mapping Analysis [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2337Z
. "Machine Learning: A Science Mapping Analysis." doi: 10.21227/H2337Z

Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications


This paper presents an overview of Unidirectional

Loop Metamaterial (ULM) structures and applications. Mimicking

electron spin precession in ferrites using loops with unidirectional

loads (typically transistors), the ULM exhibits all the

fundamental properties of ferrite materials, and represents the

only existing magnetless ferrimagnetic medium. We present here

an extended explanation of ULM physics and unified description

 

of its component and system applications.

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Dataset Details

Citation Author(s):
Submitted by:
Toshiro Kodera
Last updated:
Sat, 03/31/2018 - 12:20
DOI:
10.21227/H22D4M
Data Format:
 
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[1] , "Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H22D4M. Accessed: Apr. 23, 2018.
@data{h22d4m-18,
doi = {10.21227/H22D4M},
url = {http://dx.doi.org/10.21227/H22D4M},
author = { },
publisher = {IEEE Dataport},
title = {Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications},
year = {2018} }
TY - DATA
T1 - Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H22D4M
ER -
. (2018). Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications. IEEE Dataport. http://dx.doi.org/10.21227/H22D4M
, 2018. Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications. Available at: http://dx.doi.org/10.21227/H22D4M.
. (2018). "Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications." Web.
1. . Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H22D4M
. "Unidirectional Loop Metamaterials (ULM) as Magnetless Artificial Ferrimagnetic Materials: Principles and Applications." doi: 10.21227/H22D4M

Isotropic Surface Remeshing without Large and Small Angles


We introduce a novel algorithm for isotropic surface remeshing which progressively eliminates obtuse triangles and improves small angles. The main novelty of the proposed approach is a simple vertex insertion scheme that facilitates the removal of large angles, and a vertex removal operation that improves the distribution of small angles. Combined with other standard local mesh operators, e.g., connectivity optimization and local tangential smoothing, our algorithm is able to remesh a

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Dataset Details

Citation Author(s):
Submitted by:
Dongming Yan
Last updated:
Sat, 03/31/2018 - 04:24
DOI:
10.21227/H2766V
 
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[1] , "Isotropic Surface Remeshing without Large and Small Angles", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2766V. Accessed: Apr. 23, 2018.
@data{h2766v-18,
doi = {10.21227/H2766V},
url = {http://dx.doi.org/10.21227/H2766V},
author = { },
publisher = {IEEE Dataport},
title = {Isotropic Surface Remeshing without Large and Small Angles},
year = {2018} }
TY - DATA
T1 - Isotropic Surface Remeshing without Large and Small Angles
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2766V
ER -
. (2018). Isotropic Surface Remeshing without Large and Small Angles. IEEE Dataport. http://dx.doi.org/10.21227/H2766V
, 2018. Isotropic Surface Remeshing without Large and Small Angles. Available at: http://dx.doi.org/10.21227/H2766V.
. (2018). "Isotropic Surface Remeshing without Large and Small Angles." Web.
1. . Isotropic Surface Remeshing without Large and Small Angles [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2766V
. "Isotropic Surface Remeshing without Large and Small Angles." doi: 10.21227/H2766V

IAarticles Collection


The IAarticles.csv file has the IAarticles documents collection composed of 66,602 terms (dimensions), 40 documents (objects), and 4 classes (clu, mtx, ont, rif). In the first column it has the name of a document and in the last column it has its class.

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Citation Author(s):
Submitted by:
Fernanda Eustaquio
Last updated:
Sat, 03/24/2018 - 11:59
DOI:
10.21227/H2HM1K
Data Format:
Links:
 
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[1] , "IAarticles Collection", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2HM1K. Accessed: Apr. 23, 2018.
@data{h2hm1k-18,
doi = {10.21227/H2HM1K},
url = {http://dx.doi.org/10.21227/H2HM1K},
author = { },
publisher = {IEEE Dataport},
title = {IAarticles Collection},
year = {2018} }
TY - DATA
T1 - IAarticles Collection
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2HM1K
ER -
. (2018). IAarticles Collection. IEEE Dataport. http://dx.doi.org/10.21227/H2HM1K
, 2018. IAarticles Collection. Available at: http://dx.doi.org/10.21227/H2HM1K.
. (2018). "IAarticles Collection." Web.
1. . IAarticles Collection [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2HM1K
. "IAarticles Collection." doi: 10.21227/H2HM1K

Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number


This data is a subset of the results of direct numerical simulations of a turbulent upward-directed flow of a liquid metal in a vertical channel.

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Dataset Details

Citation Author(s):
Submitted by:
Baldwin Nsonga
Last updated:
Wed, 03/07/2018 - 12:04
DOI:
10.21227/H23Q0H
Data Format:
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[1] , "Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H23Q0H. Accessed: Apr. 23, 2018.
@data{h23q0h-18,
doi = {10.21227/H23Q0H},
url = {http://dx.doi.org/10.21227/H23Q0H},
author = { },
publisher = {IEEE Dataport},
title = {Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number},
year = {2018} }
TY - DATA
T1 - Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H23Q0H
ER -
. (2018). Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number. IEEE Dataport. http://dx.doi.org/10.21227/H23Q0H
, 2018. Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number. Available at: http://dx.doi.org/10.21227/H23Q0H.
. (2018). "Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number." Web.
1. . Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H23Q0H
. "Simulation Data of Buoyancy-affected backward-facing step flow with heat transfer at low Prandtl number." doi: 10.21227/H23Q0H

Software Defect


Our defect dataset, comes from PROMISErepository. This data refers to open-source Java systems such as ant, camel, ivy, jedit, log4j, lucene, poi, synapse, velocity and xerces. We selected these datasets since they have at least three consecutive releases (where release i was built before release i+1). This will allow us to build defect predictors based on the past data and then predict (test) defects on future version projects, which will be a more practical scenario.

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Dataset Details

Citation Author(s):
Submitted by:
Arjun Rajpal
Last updated:
Tue, 02/20/2018 - 11:37
DOI:
10.21227/H2K078
Data Format:
 
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[1] , "Software Defect", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2K078. Accessed: Apr. 23, 2018.
@data{h2k078-18,
doi = {10.21227/H2K078},
url = {http://dx.doi.org/10.21227/H2K078},
author = { },
publisher = {IEEE Dataport},
title = {Software Defect},
year = {2018} }
TY - DATA
T1 - Software Defect
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2K078
ER -
. (2018). Software Defect. IEEE Dataport. http://dx.doi.org/10.21227/H2K078
, 2018. Software Defect. Available at: http://dx.doi.org/10.21227/H2K078.
. (2018). "Software Defect." Web.
1. . Software Defect [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2K078
. "Software Defect." doi: 10.21227/H2K078

Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation


Data and source code related to the IEEE TWC submission titled "STAR: STochastically-dominant Access point selection algoRithm".  The URL of Bitbucket repository hosting the source code is: https://YuBai@bitbucket.org/YuBai/cpn-realtime-ns3sourcecode.git.  

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Dataset Details

Citation Author(s):
Submitted by:
Yu Bai
Last updated:
Tue, 02/27/2018 - 09:50
DOI:
10.21227/H2S074
Data Format:
Links:
 
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[1] , "Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2S074. Accessed: Apr. 23, 2018.
@data{h2s074-18,
doi = {10.21227/H2S074},
url = {http://dx.doi.org/10.21227/H2S074},
author = { },
publisher = {IEEE Dataport},
title = {Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation},
year = {2018} }
TY - DATA
T1 - Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2S074
ER -
. (2018). Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation. IEEE Dataport. http://dx.doi.org/10.21227/H2S074
, 2018. Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation. Available at: http://dx.doi.org/10.21227/H2S074.
. (2018). "Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation." Web.
1. . Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2S074
. "Sample Data Sets and Source Codes for STAR/MD-STAR Evaluation." doi: 10.21227/H2S074

Investigation of space weather hazards at ocean-continent boundaries using FDTD


The geomagnetic disturbances create large-scale geo-magnetically induced currents (GICs) in long conductors at the Earth's surface. The GIC might cause hazard to many infrastructures, out of which, the electrical transmission lines located at the vicinity of ocean is the prime example. The unique physics behind this phenomena lies at the sharp contrast in the electrical conductivity between ocean and continent.

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No Data files have been uploaded.

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Citation Author(s):
Submitted by:
Santosh Pokhrel
Last updated:
Sat, 01/20/2018 - 18:46
DOI:
10.21227/H2XS92
 
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[1] , "Investigation of space weather hazards at ocean-continent boundaries using FDTD", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2XS92. Accessed: Apr. 23, 2018.
@data{h2xs92-18,
doi = {10.21227/H2XS92},
url = {http://dx.doi.org/10.21227/H2XS92},
author = { },
publisher = {IEEE Dataport},
title = {Investigation of space weather hazards at ocean-continent boundaries using FDTD},
year = {2018} }
TY - DATA
T1 - Investigation of space weather hazards at ocean-continent boundaries using FDTD
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2XS92
ER -
. (2018). Investigation of space weather hazards at ocean-continent boundaries using FDTD. IEEE Dataport. http://dx.doi.org/10.21227/H2XS92
, 2018. Investigation of space weather hazards at ocean-continent boundaries using FDTD. Available at: http://dx.doi.org/10.21227/H2XS92.
. (2018). "Investigation of space weather hazards at ocean-continent boundaries using FDTD." Web.
1. . Investigation of space weather hazards at ocean-continent boundaries using FDTD [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2XS92
. "Investigation of space weather hazards at ocean-continent boundaries using FDTD." doi: 10.21227/H2XS92

Investigation of space weather hazards near ocean-continental boundary using FDTD


The geomagnetic disturbances caused during the solar storms create large-scale geo-magnetically induced currents (GICs) in long conductors at the Earth's surface. The GIC might cause hazard to the electrical transmission lines located at the vicinity of ocean. The unique physics behind this phenomena lies at the sharp contrast in the electrical conductivity between ocean and continent. Though analytical methods were used previously to study electromagnetic fields at ocean-continent boundaries, those were only limited for highly simplified geometries and sinusoidal sources.

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No Data files have been uploaded.

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Citation Author(s):
Submitted by:
Santosh Pokhrel
Last updated:
Sat, 01/20/2018 - 16:56
DOI:
10.21227/H22H2W
Data Format:
 
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[1] , "Investigation of space weather hazards near ocean-continental boundary using FDTD", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H22H2W. Accessed: Apr. 23, 2018.
@data{h22h2w-18,
doi = {10.21227/H22H2W},
url = {http://dx.doi.org/10.21227/H22H2W},
author = { },
publisher = {IEEE Dataport},
title = {Investigation of space weather hazards near ocean-continental boundary using FDTD},
year = {2018} }
TY - DATA
T1 - Investigation of space weather hazards near ocean-continental boundary using FDTD
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H22H2W
ER -
. (2018). Investigation of space weather hazards near ocean-continental boundary using FDTD. IEEE Dataport. http://dx.doi.org/10.21227/H22H2W
, 2018. Investigation of space weather hazards near ocean-continental boundary using FDTD. Available at: http://dx.doi.org/10.21227/H22H2W.
. (2018). "Investigation of space weather hazards near ocean-continental boundary using FDTD." Web.
1. . Investigation of space weather hazards near ocean-continental boundary using FDTD [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H22H2W
. "Investigation of space weather hazards near ocean-continental boundary using FDTD." doi: 10.21227/H22H2W

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