artificial intelligence

Activities of Daily Living


Recognition of human activities is one of the most promising research areas in artificial intelligence. This has come along with the technological advancement in sensing technologies as well as the high demand for applications that are mobile, context-aware, and real-time. We have used a smart watch (Apple iWatch) to collect sensory data for 14 ADL activities (Activities of Daily Living). 

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Dataset Details

Citation Author(s):
Submitted by:
Walid Gomaa
Last updated:
Wed, 11/22/2017 - 09:06
DOI:
10.21227/H2PS74
Data Format:
 
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[1] , "Activities of Daily Living", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2PS74. Accessed: Nov. 24, 2017.
@data{h2ps74-17,
doi = {10.21227/H2PS74},
url = {http://dx.doi.org/10.21227/H2PS74},
author = { },
publisher = {IEEE Dataport},
title = {Activities of Daily Living},
year = {2017} }
TY - DATA
T1 - Activities of Daily Living
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2PS74
ER -
. (2017). Activities of Daily Living. IEEE Dataport. http://dx.doi.org/10.21227/H2PS74
, 2017. Activities of Daily Living. Available at: http://dx.doi.org/10.21227/H2PS74.
. (2017). "Activities of Daily Living." Web.
1. . Activities of Daily Living [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2PS74
. "Activities of Daily Living." doi: 10.21227/H2PS74

Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink


This work presents a novel Anti-Islanding (AI) protection of Photovoltaic (PV) Systems based on monitoring the dc-link voltage of the PV inverter. A PV System equipped with AI protection like frequency relays, a rate of change of frequency (ROCOF) relay, and respectively the proposed dc-link voltage relay is simulated under the conditions of islanding and the detection time for all these AI techniques are compared. The study shows under which conditions our proposed dc-link voltage AI relay is the most efficient.

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Citation Author(s):
Submitted by:
Ioan Viorel Banu
Last updated:
Thu, 10/19/2017 - 10:36
DOI:
10.21227/H28W5P
Data Format:
Links:
 
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[1] , "Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H28W5P. Accessed: Nov. 24, 2017.
@data{h28w5p-17,
doi = {10.21227/H28W5P},
url = {http://dx.doi.org/10.21227/H28W5P},
author = { },
publisher = {IEEE Dataport},
title = {Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink},
year = {2017} }
TY - DATA
T1 - Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H28W5P
ER -
. (2017). Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink. IEEE Dataport. http://dx.doi.org/10.21227/H28W5P
, 2017. Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink. Available at: http://dx.doi.org/10.21227/H28W5P.
. (2017). "Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink." Web.
1. . Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H28W5P
. "Islanding Prevention Scheme for Grid-Connected Photovoltaic Systems in Matlab/Simulink." doi: 10.21227/H28W5P

A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems


This work presents a Matlab/Simulink study on anti-islanding detection algorithms for a 100kW Grid-Connected Photovoltaic (PV) Array. The main focus is on the islanding phenomenon that occurs at the Point of Common Coupling (PCC) between Grid-Connected PV System and the rest of the electric power system (EPS) during various grid fault conditions. The Grid-Connected PV System is simulated under the conditions of islanding, and anti-islanding (AI) relay reaction times are measured through the simulation.

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Citation Author(s):
Submitted by:
Ioan Viorel Banu
Last updated:
Thu, 10/19/2017 - 10:32
DOI:
10.21227/H2DP80
Data Format:
Links:
 
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[1] , "A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2DP80. Accessed: Nov. 24, 2017.
@data{h2dp80-17,
doi = {10.21227/H2DP80},
url = {http://dx.doi.org/10.21227/H2DP80},
author = { },
publisher = {IEEE Dataport},
title = {A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems},
year = {2017} }
TY - DATA
T1 - A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2DP80
ER -
. (2017). A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems. IEEE Dataport. http://dx.doi.org/10.21227/H2DP80
, 2017. A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems. Available at: http://dx.doi.org/10.21227/H2DP80.
. (2017). "A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems." Web.
1. . A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2DP80
. "A Study on Anti-Islanding Detection Algorithms for Grid-Tied Photovoltaic Systems." doi: 10.21227/H2DP80

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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Categories & Keywords

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[1] , "BHI 2017: Big Data Analytics Competition", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H2W886. Accessed: Nov. 24, 2017.
@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