"Advances on Learning, Analytics and Intelligent Computing Systems"
published by Springer
Volume Title:
"Modelling, Computing and Data Handling Methodologies for Maritime
Transportation"
Purpose
Maritime transportation is the major conduit of international trade. In
terms of cost, maritime transport is very competitive against land and
airborne transport, increasing only by a few percent the total product cost.
On the other hand, maritime transportation takes longer or may cause harbor
congestion which further increase the voyage time. Furthermore, there are
difficulties in integrating this transportation mode efficiently with other
transport or distribution options. On top of that, the safety and the
environmental impact of maritime transportation, in particular, in the case
of sea accidents, are always two challenging issues.
As recent advances on maritime transportation require the synergy of both
computer science and maritime science, the main focus in this edited volume
will be upon the latest developments on IT methodologies for maritime
transportation. Computational intelligence, data mining and knowledge
discovery/representation, risk assessment methodologies as well as
combinatorial optimization are the IT fields that have gain importance in
maritime studies because of their potential in giving solutions for
effective sea transportation.
Book chapters on timely topics, state-of-the-art reviews providing a
comprehensive survey and evaluation of a subject area are welcomed for
submission. The main emphasis should be on the presentation of research
aiming for more effective and safer sea transportation, targeting complex
and large-scale optimization problems with conflicting criteria, requiring
innovative solution techniques and ideas from mathematical optimization,
theoretical computer science, massive data analysis and operations research.
Specifically, topics of interest include, but are not limited to:
* Graph and Network algorithms for Maritime Transportation
* Combinatorial optimization techniques for Maritime Transportation
* Environmentally Safe Shipping
* Safety and Security of Maritime Shipping
* GIS in Maritime Applications
* Spatiotemporal and Maritime Data Handling
* Route Planning and Monitoring
* Piracy Protection
* Risk Analysis, Assessment and Prediction
* Maritime Data Mining and Knowledge Discovery Applications: surveillance,
maritime traffic control, anomaly detection, emergency management, situation
recognition, etc.
* Decision Support Tools for Maritime Transportation
* Integration of Heterogeneous Maritime Data Sources
Submission Information
The volume will be published by Springer in Series "Advances on Learning,
Analytics and Intelligent Computing Systems". First a chapter proposal of
1500 words should be sent to Volume Editors for evaluation. Upon proposal
acceptance, the authors will be called to submit the full manuscript before
a certain deadline. Then, the submissions will be double-blind reviewed for
deciding the chapters that will be included in the volume.
Important dates
Submission of chapter proposals: December 11, 2015
Notification for proposal acceptance: January 11, 2016
Submission of full chapters: April 11, 2016
Notification for chapter acceptance: May 31, 2016
Submission of the camera-ready chapters: July 1, 2016
Volume Editors
Dr. Charalampos Konstantopoulos
Department of Informatics
University of Piraeus
Greece
Prof. Grammati Pantziou
Department of Informatics
Technological Institution of Athens
Greece
k
**********************************************************
*
* Contributions to be spread via DMANET are submitted to
*
* DMANET@zpr.uni-koeln.de
*
* Replies to a message carried on DMANET should NOT be
* addressed to DMANET but to the original sender. The
* original sender, however, is invited to prepare an
* update of the replies received and to communicate it
* via DMANET.
*
* DISCRETE MATHEMATICS AND ALGORITHMS NETWORK (DMANET)
* http://www.zaik.uni-koeln.de/AFS/publications/dmanet/
*
**********************************************************