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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  3/2015 - 15

An Ontology Based Methodology for Satellite Data Semantic Interoperability

ABBURU, S. See more information about ABBURU, S. on SCOPUS See more information about ABBURU, S. on IEEExplore See more information about ABBURU, S. on Web of Science, DUBE, N. See more information about  DUBE, N. on SCOPUS See more information about  DUBE, N. on SCOPUS See more information about DUBE, N. on Web of Science, MIYAR, R. N. See more information about  MIYAR, R. N. on SCOPUS See more information about  MIYAR, R. N. on SCOPUS See more information about MIYAR, R. N. on Web of Science, GOLLA, S. B. See more information about GOLLA, S. B. on SCOPUS See more information about GOLLA, S. B. on SCOPUS See more information about GOLLA, S. B. on Web of Science
 
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Download PDF pdficon (1,179 KB) | Citation | Downloads: 219 | Views: 862

Author keywords
data, INSAT-3D, ontology, satellite, semantics

References keywords
link(16), data(10), ontology(9), semantic(7), science(5), insat(5), information(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-08-31
Volume 15, Issue 3, Year 2015, On page(s): 105 - 110
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.03015
Web of Science Accession Number: 000360171500015
SCOPUS ID: 84940730624

Abstract
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Full text preview
Satellites and ocean based observing system consists of various sensors and configurations. These observing systems transmit data in heterogeneous file formats and heterogeneous vocabulary from various data centers. These data centers maintain a centralized data management system that disseminates the observations to various research communities. Currently, different data naming conventions are being used by existing observing systems, thus leading to semantic heterogeneity. In this work, sensor data interoperability and semantics of the data are being addressed through ontologies. The present work provides an effective technical solution to address semantic heterogeneity through semantic technologies. These technologies provide interoperability, capability to build knowledge base, and framework for semantic information retrieval by developing an effective concept vocabulary through domain ontologies. The paper aims at a new methodology to interlink the multidisciplinary and heterogeneous sensor data products. A four phase methodology has been implemented to address satellite data semantic interoperability. The paper concludes with the evaluation of the methodology by linking and interfacing multiple ontologies to arrive at ontology vocabulary for sensor observations. Data from Indian Meteorological satellite INSAT-3D satellite have been used as a typical example to illustrate the concepts. This work on similar lines can also be extended to other sensor observations.


References | Cited By  «-- Click to see who has cited this paper

[1] S. Haines, V. Subramanian, E. Mayorga, D. Snowden, R. Ragsdale, C. Rueda, M. Howard, "IOOS Vocabulary and Ontology Strategy for Observed Properties," Oceans, vol. 1, no. 9, pp. 14-19, 2012,
[CrossRef] [SCOPUS Times Cited 4]


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[3] O. Daniel, "How Ontologies Benefit Enterprise Applications", Semantic Web - Interoperability, Usability, Applicability (SWJ), IOS Press, Vol. 5, No. 6, pp. 1-5, 2014. [Online] Available: Temporary on-line reference link removed - see the PDF document

[4] F. Cristiano, B. Anna, M. Stefano, O. Alessandro, P. Fabio, P. Monica, S. Alessandro, C. Paola, "RITMARE: Semantics-aware Harmonisation of Data in Italian Marine Research," Procedia Computer Science, vol. 33, pp. 261-265, 2014,
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 4]


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[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 9]


[6] R. A. Samina, S. R. A. Syed, K. Mei, D. Ali, "An Ontology Framework for Modeling Ocean Data and E-Science Semantic Web Services," International Journal of Advanced Computer Science, vol. 2, no. 8, pp. 280-286, 2012. [Online] Available: Temporary on-line reference link removed - see the PDF document

[7] H. Dong-mei, O. Yan-ling, Z. Ming-hua, Z. Chi, "Application of Ontology-based Automatic ETL in Marine Data Integration," In Proc. IEEE Symposium on Electrical & Electronics Engineering (EEESYM), pp. 11-13, 2012,
[CrossRef] [SCOPUS Times Cited 2]


[8] G. John, W. I. Anthony, R. Carlos, "Semantic Mediation of Vocabularies for Ocean Observing Systems," Computers & Geosciences, vol.40, pp. 120-131, 2012,
[CrossRef] [Web of Science Times Cited 12] [SCOPUS Times Cited 17]


[9] M. Nagai, M. Ono, R. Shibasaki, "Earth Observation Data Interoperability Arrangement with Ontology Registry," ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. I-2, 2012 XXII ISPRS Congress, 25 August - 01 September, Melbourne, Australia, 2012. [Online] Available: Temporary on-line reference link removed - see the PDF document

[10] R. Kaladevi, T. Mirnalinee, "Heterogeneous Data Management on Environmental Sensors Using Ontology Mapping," Lecture Notes on Information Theory, vol. 1, no. 4, pp. 154-158, 2013,
[CrossRef]


[11] G. Raul, C. Oscar, H. Chris, "A Core Ontological Model for Semantic Sensor Web Infrastructures," International Journal on Semantic Web and Information Systems, vol. 8, no. 1, pp. 22-42, 2012,
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[12] CF Metadata Conventions, ESDS-RFC-021v0.02, 2010. [Online] Available: Temporary on-line reference link removed - see the PDF document

[13] D. Ben, N. Stefano, "Web Coverage Service (WCS) 1.1 Extension for CF-netCDF 3.0 Encoding," Open Geospatial Consortium, Version: 0.2.2, 2009. [Online] Available: Temporary on-line reference link removed - see the PDF document

[14] W3C Semantic Sensor Network Incubator Group, Semantic Sensor Network Ontology, 2005. [Online] Available: Temporary on-line reference link removed - see the PDF document

[15] E. Brian, G. Jonathan, D. Bob, T. Karl, H. Steve, "NetCDF Climate and Forecast (CF) Metadata Conventions", Version 1.7.2 DRAFT, 2014. [Online] Available: Temporary on-line reference link removed - see the PDF document

[16] F. Daniel, P. Catia, S. Emanuel, P. Matteo, F. C. Isabel, M. C. Francisco "The AgreementMakerLight Ontology Matching System", Lecture Notes in Computer Science (LNCS), vol. 8185, pp. 527-541, 2013,
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[18] INSAT DP Team, INSAT-3D Data Products Format Document, Data Products Software Group, SAC, ISRO, Version 1.1, 2014. [Online] Available: Temporary on-line reference link removed - see the PDF document

[19] INSAT-3D, Data Products Catalog, National Satellite Meteorological Centre, India, 2014. [Online] Available: Temporary on-line reference link removed - see the PDF document

[20] Voc2RDF, A web-based transform simple vocabularies into the Resource Description Framework, 2008. [Online] Available: Temporary on-line reference link removed - see the PDF document

[21] A. Sunitha, "INSAT3D Data Product Vocabulary," 2015. [Online] Available: Temporary on-line reference link removed - see the PDF document

[22] VINE 1.4, VINE 1.4 is a vocabulary Integration Environment Tool, developed by MMI, 2010. [Online] Available: Temporary on-line reference link removed - see the PDF document

[23] A. Sunitha, "INSAT-3D Mappings," 2015. [Online] Available: Temporary on-line reference link removed - see the PDF document

[24] SPARQL, SPARQL Query Language for RDF, 2008. [Online] Available: Temporary on-line reference link removed - see the PDF document

[25] HDF Object Package, The HDF Group, 2014. [Online] Available: Temporary on-line reference link removed - see the PDF document



References Weight

Web of Science® Citations for all references: 207 TCR
SCOPUS® Citations for all references: 488 TCR

Web of Science® Average Citations per reference: 8 ACR
SCOPUS® Average Citations per reference: 19 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-08-12 07:22 in 64 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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