Fast approach for automatic data retrieval using R programming language
The development of big data analytics in recent years has enabled wide use of analysis tools such as R in various industries including robotics and automation. Its most recent reported application for data analysis is limited to only a small dataset and the processing time was not reported. Thus, th...
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Institute of Electrical and Electronics Engineers Inc.
2017
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Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015897769&doi=10.1109%2fROMA.2016.7847824&partnerID=40&md5=1de67c804051735d632e9633bb02f781 http://eprints.utp.edu.my/20137/ |
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my.utp.eprints.201372018-04-22T14:42:24Z Fast approach for automatic data retrieval using R programming language Chung, T.D. Ibrahim, R. Hassan, S.M. Rosli, N.S. The development of big data analytics in recent years has enabled wide use of analysis tools such as R in various industries including robotics and automation. Its most recent reported application for data analysis is limited to only a small dataset and the processing time was not reported. Thus, this work proposes a fast approach for automatic data retrieval using R, a powerful programming language for statistical and big data analysis. The developed algorithm performs data retrieval using a source file and a map file as inputs and produces a desired output file. Based on the experiment results on a real dataset, significantly low processing time can be achieved using the approach. In addition, the developed algorithm is general and thus can be applied in various similar data retrieval applications such as pooling sub-dataset in manufacturing environment involving the use of robotics and automation. © 2016 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015897769&doi=10.1109%2fROMA.2016.7847824&partnerID=40&md5=1de67c804051735d632e9633bb02f781 Chung, T.D. and Ibrahim, R. and Hassan, S.M. and Rosli, N.S. (2017) Fast approach for automatic data retrieval using R programming language. 2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation, ROMA 2016 . http://eprints.utp.edu.my/20137/ |
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The development of big data analytics in recent years has enabled wide use of analysis tools such as R in various industries including robotics and automation. Its most recent reported application for data analysis is limited to only a small dataset and the processing time was not reported. Thus, this work proposes a fast approach for automatic data retrieval using R, a powerful programming language for statistical and big data analysis. The developed algorithm performs data retrieval using a source file and a map file as inputs and produces a desired output file. Based on the experiment results on a real dataset, significantly low processing time can be achieved using the approach. In addition, the developed algorithm is general and thus can be applied in various similar data retrieval applications such as pooling sub-dataset in manufacturing environment involving the use of robotics and automation. © 2016 IEEE. |
format |
Article |
author |
Chung, T.D. Ibrahim, R. Hassan, S.M. Rosli, N.S. |
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Chung, T.D. Ibrahim, R. Hassan, S.M. Rosli, N.S. Fast approach for automatic data retrieval using R programming language |
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Chung, T.D. Ibrahim, R. Hassan, S.M. Rosli, N.S. |
author_sort |
Chung, T.D. |
title |
Fast approach for automatic data retrieval using R programming language |
title_short |
Fast approach for automatic data retrieval using R programming language |
title_full |
Fast approach for automatic data retrieval using R programming language |
title_fullStr |
Fast approach for automatic data retrieval using R programming language |
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Fast approach for automatic data retrieval using R programming language |
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fast approach for automatic data retrieval using r programming language |
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Institute of Electrical and Electronics Engineers Inc. |
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2017 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015897769&doi=10.1109%2fROMA.2016.7847824&partnerID=40&md5=1de67c804051735d632e9633bb02f781 http://eprints.utp.edu.my/20137/ |
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