> [Apologies if you got multiple copies of this email.] > > DEADLINE IS EXTENDED TO 31 JANUARY 2015 > > ================================================================== > > CALL FOR PAPERS > > JOURNAL OF BIG DATA RESEARCH, ELSEVIER SCIENCE, SPECIAL ISSUE ON > > "Big Data, Analytics, and High Performance Computing" > > SUBMISSION DEADLINE: 31 JANUARY 2015 > > 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/ 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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