[AISWorld] FGCS SI on Big Data Analytics for Sustainability (IF: 3.997; 5-year IF: 4.787; deadline: end of Aug 2017)

Wed Aug 9 09:38:38 EDT 2017

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-----Original Message-----
From: mycolleagues-bounces at mailman.ufsc.br [mailto:mycolleagues-bounces at mailman.ufsc.br] On Behalf Of Chang V.I.
Sent: Thursday, August 3, 2017 1:56 PM
To: mycolleagues at mailman.ufsc.br; aisworld at lists.aisnet.org; isworld at listserv.heanet.ie; latincolleagues at mailman.ufsc.br
Subject: [Mycolleagues] FGCS SI on Big Data Analytics for Sustainability (IF: 3.997; 5-year IF: 4.787; deadline: end of Aug 2017)

Dear colleagues,

I have 1 CFP: FGCS SI on Big Data Analytics for Sustainability (IF: 3.997; 5-year IF: 4.787; deadline: end of Aug 2017) due at the end of Aug 2017. We are looking for very high-quality papers on related topics to smart cities. See https://www.journals.elsevier.com/future-generation-computer-systems/call-for-papers/special-issue-on-big-data-analytics-for-sustainability for details. Please submit on https://ees.elsevier.com/fgcs and select "SI: BD Analytics Sust"  . Thanks.

Thanks and regards,

Victor

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Sustainability is a paradigm for thinking about the future in which environmental, societal and economic considerations are equitable in the pursuit of an improved lifestyle. Most of the economies are developing with breakneck velocities and are becoming epicenters of unsustainable global growth. Immense utilization of natural resources, waste generation and ecological irresponsibility are the reasons for such a dire situation. Big data analytics is clearly on a penetrative path across all arenas that rely on technology.

At present scientific area of chemical process engineering and natural hazards management is recognized as a method to integrate an efficient sustainability analysis and strategy. Those two engineering domains provide handful solution to manage systems by enabling the use of modeling, simulation, optimization, planning and control in order to develop a more sustainable product and process. In this context scientific simulation based on big data and collaborative work has to be developed for succeeding Computer-Aided Design/Engineering (CAD/E) of sustainable system. In scientific simulation based High Performance Computing (HPC) area, pre and post-processing technologies are the keys to make the investments valuable.

This special issue calls for high quality, up-to-date technology related to big data analytics for Sustainability and serves as a forum for researchers all over the world to discuss their works and recent advances in this field. A few best papers from IoTBDS 2017 and COMPLEXIS 2017 will be invited. In particular, the special issue is going to showcase the most recent achievements and developments in big data discovery and exploration. Both theoretical studies and state-of-the-art practical applications are welcome for submission. All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue.

The list of possible topics includes, but not limited to:

Geographical Big Data Analysis
Geography Big Data Mining and Exploration Big Data for Smart Cities and Smart Homes Large-scale Sustainable infrastructure and smart buildings Large-scale Human Activities Data Computing Sustainability Analysis of Energy Distributions Internet of Things (IoT) services and applications Internet of Vehicles (IoV) technologies Passenger Sensing, Control and Management Data-Driven Urban Management Environment-Aware Application, analytics and visualization Environment Big Data Processing and Analysis Big Data Information Security for Sustainability Knowledge-based systems, computing and visualization for Sustainability Computational intelligence and algorithms for Sustainability Cloud Computing Platform Based Big Data Mining Energy-Consumption-Aware Ubiquitous Computing Complex information systems for Sustainability Environmental sensor networks, monitoring, environmental and weather studies Energy efficient communication protocol for networks Energy-efficient metrics and modeling for communication networks Network traffic model and characteristics for information-centric networking Future Generation Green ICT Submission Guidelines

Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the Future Generation Computer Systems at https://ees.elsevier.com/fgcs. Authors should select "SI: BD Analytics Sust" when they reach the "Article Type" step in the submission process.

Tentative schedule

Submission deadline: August 31, 2017
Pre-screening notification: Oct 15, 2017 (or as soon as possible) First round notification: November 30, 2017 Revision due: January 30, 2017 Final notification: March 15, 2018 Final Manuscript due: March 31, 2018 Tentative publication date: Summer 2018

Guest editors

Dr. Zhihan Lu (Lead guest editor)
Qingdao University, China; University College London, UK.
Email: lvzhihan at gmail.com
(If you make an enquiry, please state FGCS SI: Big Data Analytics for Sustainability' in your email's subject)

Dr. Rahat Iqbal
Coventry University, UK
Email: r.iqbal at outlook.com

Dr. Victor Chang
Xi'an Jiaotong-Liverpool University, Suzhou, China
Honorary/Visiting: University of Liverpool, UK; University of Southampton, UK
Email: ic.victor.chang at gmail.com