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DEADLINE IS EXTENDED TO 22 DECEMBER 2014
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CALL FOR PAPERS
JOURNAL OF BIG DATA RESEARCH, ELSEVIER SCIENCE, SPECIAL ISSUE ON
"Big Data, Analytics, and High Performance Computing"
SUBMISSION DEADLINE: November 24th, 2014 (Extended to 22nd December)
Guest Editors:
Prof. Paul D. Yoo. Khalifa University, UAE
Prof. Albert Y. Zomaya, University of Sydney, Australia
Aims and Scope
We live in an era of data deluge. Given the unprecedented amount of data that
has been produced, collected, and stored in the coming years, one of the
technology industry’s great challenges is how to benefit from it. While Big
Data can be definitely perceived as a big blessing, big challenges also arise
with large-scale datasets. The sheer volume of data makes it often impossible
to run analytics using a central processor and storage, and distributed
processing with parallelized multi-processors is preferred while the data
themselves are stored in the cloud. In addition, as the size of data grows
exponentially, current algorithms are not efficient or scalable enough to deal
with such large volumes of data. Designing more accurate intelligent models so
as to satisfy the market needs will hence bring huge opportunities as well as
challenges to these communities. We believe this special issue will offer a
timely collection of novel research results to benefit the researchers and
practitioners working in these communities. This special issue focuses on all
aspects of big data and targets a mixed audience of researchers from several
communities including analytics, machine learning and data mining, distributed
and high performance computing, etc.
Topics of interest include (but are not limited to):
Theoretical foundations and algorithms for big data analytics
Compressive sampling, matrix completion, low-rank models, and dimensionality
reduction
Efficient learning and clustering
Robustness to outliers; convergence and complexity issues; performance analysis
Scalable, online, active, decentralized, deep learning and optimization
Architectures and applications for large-scale data analysis
Scalable, distributed computing, MapReduce on
Multi-Core, GPU, hybrid distributed environments
Opportunistic / heterogeneous computing
Programming model
Systems biology, genomics, bioinformatics, health, medical, semantics,
sentiment and natural language processing
Green energy and smart power grid analytics; climate; astronomical; geoscience
Cyber security inc. intrusion/botnet detection systems, security and privacy in
cloud
Industrial and systems engineering
Sensors, mobile and wireless communications
Submission Process
Articles submitted to this special issue must contain significant relevance to
Big Data. All submissions will be peer reviewed according to the Elsevier
guidelines. Submitted articles should not have been published or under review
elsewhere. Submissions to this special issue of the Elsevier Journal of Big
Data Research should have significant tutorial value. Manuscripts should be
submitted online at http://www.journals.elsevier.com/big-data-research/
<http://www.journals.elsevier.com/big-data-research/> using the Elsevier
Editorial System. The authors must select "SI: BDA-HPC" as Article Type when
they reach the Article Type step in the submission process. Submissions are
expected to not exceed 20 pages (including figures, tables, and references) in
the journal’s single-column format using 11 point font. Prospective authors
should consult the site "Guide for Authors" at the above link for guidelines
and information on paper submission.
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