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Subject:

Workshop Computational algorithms for Sustainability Assessment CLASS 2014

From:

Antonino Marvuglia <[log in to unmask]>

Reply-To:

Antonino Marvuglia <[log in to unmask]>

Date:

Wed, 18 Dec 2013 16:52:00 +0100

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Workshop Computational algorithms for Sustainability Assessment
CLASS 2014

http://oldwww.unibas.it/utenti/murgante/Class/descr.html
in conjunction with
The 2014 International Conference on Computational
Science and its Applications (ICCSA 2014)

June 30th - July 3th, 2014

University of Minho, Guimaraes, Portugal
http://www.iccsa.org/
Description
Environmental applications are often characterized by the utilization
of many different, non-homogeneous information sources, such as text
data, measurement data from monitoring networks, structural data on
chemical substances, satellite data, etc. In particular, environmental
data is often geographically coded, i.e. information is attached to a
particular point or region in space. Properly processing this
heterogeneous and often massive corps of data and assessing the
extremely wide set of possible environmental impacts arising from
human activities is not an easy task and entails a highly
multidisciplinary research.
Life cycle assessment (LCA) is a holistic methodology used to quantify
burdens to the environment over the whole life cycle of a product,
material, service, or facility in relation to a functional unit.
However, LCA results are strongly dependent on the boundaries of the
study, i.e. its spatial and temporal relevance. Even when the embraced
horizon is usually well defined, most of LCAs neglect to take into
account temporal aspects at various stages of the study, mainly
because of the lack of well defined methodologies to perform dynamic
calculations.
After an exponential increase of LCA applications over the last
decades, the science underlying LCA needs to advance to tackle the
challenges of ecosystem protection and assessment of impacts in a more
specific level of detail. Many research efforts aim at an extension of
LCA in order to increase its spatial or temporal detail or to enlarge
its scope. While traditional LCA used lumped parameter, static,
site-independent models to estimate environmental impact, the modern
advances in computing and developments in systems ecology provide now
an opportunity to address the issues of space, time and site
specificity.
Besides LCA, several lifecycle oriented methods for environmental
assessment do exist (from physically based resources accounting
methods, to ecological economics and impact oriented methods), each
with its specificities, but altogether contributing to take the
challenge of managing and quantifying the complex relationships
between human activities and the natural capital.
This workshop aims at presenting methods and applications rooted in
different scientific domains, which are envisioned to provide a valid
contribution to the modern developments in the assessment of the
environmental impacts linked to human activities.
A distinguishing feature of the workshop is its interdisciplinary
nature. It will show how Computer science, Natural sciences, Economy,
Chemistry, Computational Geography (only to mention a few) can all
provide important contributions toward the development of
computational models to support decision making in challenging
real-world problems denoted by the often misused or vaguely defined
concept of “sustainability”.

The programme committee especially requests high quality submissions
on the following (but not limited to) Conference Themes:
Machine learning for environmental data analysis, modelling and visualization;
Geostatistics, remote sensing and Geographical Information Systems
(GIS) applications to for land use change detection and modelling;
Biophysically based models to study the effects produced on ecosystem
services (such as carbon sequestration and erosion regulation) by
human activities entailing land occupation and transformation;
Application of Agent Based Modelling (ABM), economic modelling and
other approaches for consequential life cycle assessment;
Computational approaches for Life Cycle Costing;
Modelling and prediction of dynamic and spatiotemporal phenomena and
systems to derive dynamic life cycle inventories;
Design and optimization of data acquisition systems for environmental
data harvesting;
Network analysis applications to natural and technological systems analysis;
Linear Programming and Constraint Programming applied to solve
constraint satisfaction problems involving environmental constraints;
Emergy accounting of complex systems;
Use of Information Communication Technology (ICT) tools for resource
optimization;
Social data mining to detect consumers orientations and rebound effects;
Uncertainty modelling (fuzzy techniques, Bayesian approaches, etc.)

Each paper will be independently reviewed by 3 programme committee
members. Their individual scores will be evaluated by a small
sub-committee and result in one of the following final decisions:
accepted, or accepted on the condition that suggestions for
improvement will be incorporated, or rejected. Notification of this
decision will take place on March 2014.

Papers accepted to "Computational algorithms for Sustainability
Assessment" will be published in the ICCSA Conference proceedings, in
Springer-Verlag Lecture Notes in Computer Science (LNCS) series, with
DOI, indexed by WOS, Scopus and DBLP.
A selected number of papers will be accepted for a special issue on
"Journal of Environmental Accounting and Management".

Authors Guideline
Please comply strictly with the formatting provided in the template to
prepare your paper and refrain from modifying it.

The submitted paper must be camera-ready and formatted according to
the rules of LNCS. For formatting information, see the publisher's web
site (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0).

Submission implies the willingness of at least one of the authors to
register and present the paper.

Submission
papers should be submitted at:
http://ess.iccsa.org/
please don't forget to select " Computational algorithms for
Sustainability Assessment CLASS 14" workshop from the drop-down list
of all workshops.

Proceedings
Papers accepted to " Computational algorithms for Sustainability
Assessment - CLASS 14" will be published in the ICCSA Conference
proceedings, in Springer-Verlag Lecture Notes in Computer Science
(LNCS) series, with DOI, indexed by WOS, Scopus and DBLP. Participants
to " Computational algorithms for Sustainability Assessment - CLASS
14" will be invited to submit an extended version of their paper for
special issues on International Journals and book.
Important dates

10 February 2014: Deadline for full paper submission
10 April 2014: Notification of acceptance
6 May 2014: Deadline for Camera Ready Papers
June 30, July 3, 2014: ICCSA 2014 Conference

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