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JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Feb 2021
Next issue: May 2021
Avg review time: 55 days


PUBLISHER

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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Improved Wind Speed Prediction Using Empirical Mode Decomposition, ZHANG, Y., ZHANG, C., SUN, J., GUO, J.
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2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
Starting on the 15th of June 2020 we wiil introduce a new policy for reviewers. Reviewers who provide timely and substantial comments will receive a discount voucher entitling them to an APC reduction. Vouchers (worth of 25 EUR or 50 EUR, depending on the review quality) will be assigned to reviewers after the final decision of the reviewed paper is given. Vouchers issued to specific individuals are not transferable.

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2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

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  3/2015 - 18

 HIGHLY CITED PAPER 

HiGIS: An Open Framework for High Performance Geographic Information System

XIONG, W. See more information about XIONG, W. on SCOPUS See more information about XIONG, W. on IEEExplore See more information about XIONG, W. on Web of Science, CHEN, L. See more information about CHEN, L. on SCOPUS See more information about CHEN, L. on SCOPUS See more information about CHEN, L. on Web of Science
 
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Download PDF pdficon (1,702 KB) | Citation | Downloads: 444 | Views: 2,612

Author keywords
high performance computing, geographic information system, geocomputation, communicating sequential process

References keywords
parallel(10), computing(8), cloud(7), system(6), data(6), processing(5), geospatial(5), remote(4), performance(4), high(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): 123 - 132
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.03018
Web of Science Accession Number: 000360171500018
SCOPUS ID: 84940739658

Abstract
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/Big data/ era expose many challenges to geospatial data management, geocomputation and cartography. There is no exception in geographic information systems (GIS) community. Technologies and facilities of high performance computing (HPC) become more and more feasible to researchers, while mobile computing, ubiquitous computing, and cloud computing are emerging. But traditional GIS need to be improved to take advantages of all these evolutions. We proposed and implemented a GIS married with high performance computing, which is called HiGIS. The goal of HiGIS is to promote the performance of geocomputation by leveraging the power of HPC, and to build an open framework for geospatial data storing, processing, displaying and sharing. In this paper the architecture, data model and modules of the HiGIS system are introduced. A geocomputation scheduling engine based on communicating sequential process was designed to exploit spatial analysis and processing. Parallel I/O strategy using file view was proposed to improve the performance of geospatial raster data access. In order to support web-based online mapping, an interactive cartographic script was provided to represent a map. A demostration of locating house was used to manifest the characteristics of HiGIS. Parallel and concurrency performance experiments show the feasibility of this system.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 5
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Cited-By CrossRef

[1] Speeding Up VM Image Distribution for Cloud Data Centers, LEE, C., LEE, H., KIM, E., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 16, 2016.
Digital Object Identifier: 10.4316/AECE.2016.04002
[CrossRef] [Full text]

[2] An Efficient Tile-Pyramids Building Method for Fast Visualization of Massive Geospatial Raster Datasets, GUO, N., XIONG, W., WU, Q., JING, N., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 16, 2016.
Digital Object Identifier: 10.4316/AECE.2016.04001
[CrossRef] [Full text]

[3] Geo-Gap Tree: A Progressive Query and Visualization Method for Massive Spatial Data, Xiong, Wei, Li, Ruiqing, Peng, Jin, Wu, Ye, Guo, Ning, Jing, Ning, IEEE Access, ISSN 2169-3536, Issue , 2019.
Digital Object Identifier: 10.1109/ACCESS.2019.2929531
[CrossRef]

[4] A real-time system for air quality monitoring based on main-memory database, Zhuo Tang, , Xiong, Wei, Chen, Luo, Ning Jing,, 2016 24th International Conference on Geoinformatics, ISBN 978-1-5090-6214-0, 2016.
Digital Object Identifier: 10.1109/GEOINFORMATICS.2016.7578961
[CrossRef]

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


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