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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Nov 2017
Next issue: Feb 2018
Avg review time: 106 days


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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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ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
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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
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

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.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

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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  2/2017 - 8

A New Optimized Model to Handle Temporal Data using Open Source Database

KUMAR, S. See more information about KUMAR, S. on SCOPUS See more information about KUMAR, S. on IEEExplore See more information about KUMAR, S. on Web of Science, RISHI, R. See more information about RISHI, R. on SCOPUS See more information about RISHI, R. on SCOPUS See more information about RISHI, R. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,184 KB) | Citation | Downloads: 228 | Views: 254

Author keywords
indexing, object oriented databases, open source software, query processing, runtime

References keywords
temporal(17), data(15), relational(7), databases(7), systems(6), information(6), database(6), object(5), time(4), science(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 55 - 60
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02008
Web of Science Accession Number: 000405378100008
SCOPUS ID: 85020110475

Abstract
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The majority of the database applications now a days deal with temporal data. Temporal records are known to change during the course of time and facilities to manage the multiple snapshots of these records are generally missing in conventional databases. Consequently, different temporal data models have been proposed and implemented as an extension of the temporal less database systems. In the single relation model, the present and past instances are stored in a single relation that makes its handling cumbersome and inefficient. This paper emphasize upon storing the past instances of the records in the multiple historical relations. The current relations will manage the recent snapshot of data. The tuple time stamping approach is used to timestamp the temporal records. This paper proposes a temporal model for the management of time varying data built on the top of conventional open source database. Indexing is used to enhance the performance of the model. The proposed model is also compared with the single relation model.


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

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[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 3]


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[CrossRef] [SCOPUS Times Cited 5]


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[CrossRef] [Web of Science Record]


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[CrossRef] [SCOPUS Times Cited 148]


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[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 9]


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[CrossRef] [SCOPUS Times Cited 1]


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[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 8]


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[CrossRef] [SCOPUS Times Cited 7]


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[CrossRef] [Web of Science Times Cited 46] [SCOPUS Times Cited 59]


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[CrossRef]


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[CrossRef] [Full Text] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


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[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 3]




References Weight

Web of Science® Citations for all references: 118 TCR
SCOPUS® Citations for all references: 302 TCR

Web of Science® Average Citations per reference: 6 ACR
SCOPUS® Average Citations per reference: 14 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 2017-12-12 12:19 in 120 seconds.




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


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