<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div style="margin: 0cm 0cm 0.0001pt; font-size: medium; font-family: Calibri; line-height: 18.200000762939453px;" class=""><span style="line-height: normal; text-align: -webkit-auto; font-size: 15px;" class=""><font face="Arial" class="">*** Apologies for cross posting ***</font></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: medium; font-family: Calibri; line-height: 18.200000762939453px;" class=""><span style="line-height: normal; text-align: -webkit-auto; font-size: 15px;" class=""><font face="Arial" class=""><br class=""></font></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" size="5" class=""><b class="">INNS Conference on Big Data 2015 - Special Session – “Advances and perspectives of Big Data Analytics in Transportation” - CALL FOR PAPERS
</b></font></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">INNS Conference on Big Data 2015, 8-10 August 2015, San Francisco, CA, USA – <a href="http://innsbigdata.org/" class="">http://innsbigdata.org</a></span></font></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><span style="font-family: Calibri; font-size: 15px;" class=""> </span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">Submissions are invited for the INNS Conference on Big Data 2015 Special Session "Advances and perspectives of Big Data Analytics in Transportation".</span></font><span style="font-family: Cambria; font-size: 15px;" class=""><font face="Calibri" class=""> <o:p class=""></o:p></font></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><font face="Calibri" class=""><i class="">Organizers</i>: <o:p class=""></o:p></font></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">Alessandro Ghio, Davide Anguita - University of Genoa, Genoa (Italy)<br class="">Diego Galar - Luleå University of Technology, Luleå (Sweden)</span></font></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">Big Data Analytics in Transportation (BDAT) Special Session webpage: <a href="http://bdat.smartlab.ws/" class="">http://bdat.smartlab.ws</a> </span></font></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><font face="Calibri" class=""><b class="">ABSTRACT</b><o:p class=""></o:p></font></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">Transport asset management is a strategic process and/or service all over the world. The effective monitoring of the assets is a key task in order to guarantee efficient and safe exploitation. Current assets, with plenty of sensors' already installed and pervasive computing on them generate a huge of data along their day. In this scenario, asset managers host a large number of diverse systems where data, regarding different aspects of their activity, are stored. In most cases, these data are captured, stored and processed by different – often incompatible – systems, and further managed by independent departments and not shared at all.<br class="">In the transportation domain, avionics paved the way towards the introduction of advanced analytics solutions in everyday operations: for example, the use of analytics approaches in capacity and pricing optimisation allows minimising vacant rooms, idle fleet, and unoccupied seats, which represent lost revenue. These results go remarkably beyond “pure” statistics, as they conceive real-time correlation of thousands of measures, extraction of non-trivial information from data, and decision supporting/planning. In this framework, Data Analytics and, in particular, Computational Intelligence and Neural Networks based approaches play a central role, both in a descriptive (e.g. clustering, segmentation, analysis of status of an asset) and predictive (e.g. asset status forecast, condition based maintenance, demand forecast) context and application. In this sense, the exploitation of such approaches in other heterogeneous transport domains are on the way, as new insights to dealing with many transport challenges will emerge from combining and exploiting these vast datasets: for example, targets include – but are not limited to – offering better service to final users (e.g. customers, travellers, etc.) and improving transport systems sustainability, from the human, social, economic and environmental point of view.<br class="">They are all included under a new term: Big Data. It refers to systems, algorithms, and procedures suitable to process data sets, which largely overcome the capacity of current single computers. Big Data is one-term drawing attention of many companies and institutions all over the world. Most organizations are speeding up their data processing strategies towards Big Data. This means a clear recognition by industry, agencies and public institutions.</span></font></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><b class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></b></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><font face="Calibri" class=""><b class="">TOPICS</b><o:p class=""></o:p></font></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">This Special Session proposes as an international showcase for researchers working in the field of Big Data Analytics in the framework of transport systems to share information on their latest investigations. The context of the special session comprehends (but is not limited to) Neural Networks, and more broadly Computational Intelligence, Machine Learning and Data Analytics approaches to transport-related problems, targeting the realization of smarter decision support systems for extracting knowledge from amounts of disparate heterogeneous data. Advances, perspectives, and applications both in academic research areas and industrial sectors are of interest within special session. All types of (freight, private, and public) transport means are concerned, including:</span><br class=""><ul class=""><li style="font-size: 15px;" class="">Automotive (including local public transport systems)</li><li style="font-size: 15px;" class="">Avionics</li><li style="font-size: 15px;" class="">Maritime</li><li style="font-size: 15px;" class="">Railways (including light and urban/suburban rails).</li></ul><span style="font-size: 15px;" class="">In particular, in this special session, we encourage submissions related (though not limited) to novel approaches and applications of Machine Learning, Computational Intelligence, Neural Networks Big Data oriented approaches to:</span><br class=""><ul class=""><li class=""><span style="font-size: 15px;" class="">Intelligent Transportation Systems in different domains, including multi-modal integration</span></li><li class=""><span style="font-size: 15px;" class="">Data management, including approaches to enhance security and safety of data</span></li><li class=""><span style="font-size: 15px;" class="">Data fusion, data integration, and data quality (including metrics) in different transport domains</span></li><li class=""><span style="font-size: 15px;" class="">Real-time and on-time monitoring and prediction of current and future status of transport assets</span></li><li class=""><span style="font-size: 15px;" class="">Condition-Based Maintenance of transportation assets</span></li><li class=""><span style="font-size: 15px;" class="">Assessing sustainability impact of transport systems, with respect to human, social, economic, and</span><span style="font-size: 15px;" class=""> </span><span style="font-size: 15px;" class="">environmental sustainability</span></li><li class=""><span style="font-size: 15px;" class="">Increasing robustness and resilience of transport systems.</span></li></ul><span style="font-size: 15px;" class="">Advances and application both in academic research areas and industrial sectors are of interest.</span><br class=""><br class=""></font></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><font face="Calibri" class=""><b class="">SUBMISSION & IMPORTANT DATES</b><o:p class=""></o:p></font></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">We kindly invite you to submit a paper to this special session. Each paper will undergo to a peer reviewing process for its acceptance. Manuscripts should be submitted to special sessions through the paper submission website of INNS BigData 2015 as regular submissions, selecting the special session the paper has to belong to, and following the instructions provided in:<br class=""><br class=""><a href="http://innsbigdata.org/paper-submission/" class="">http://innsbigdata.org/paper-submission/</a> <br class=""><br class="">Papers will be peer-reviewed with the same criteria used for the regular sessions. <br class=""></span></font><span style="font-family: Calibri; font-size: 15px;" class=""><br class=""></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><span style="font-family: Calibri; font-size: 15px;" class="">Paper submission deadline : 22 March 2015</span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><span style="font-size: 15px; font-family: Calibri;" class="">Notification of acceptance : 22 May 2015</span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><span style="font-size: 15px; font-family: Calibri;" class="">INNS Conference on Big Data 2015: 8-10 August 2015</span><span style="font-family: Calibri; font-size: 15px;" class=""> </span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><o:p class=""><font face="Calibri" class=""> </font></o:p></span></div><div style="margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: Cambria;" class=""><span style="font-size: 15px;" class=""><font face="Calibri" class=""><b class="">NOTES</b><o:p class=""></o:p></font></span></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">You can find details about the special session at <a href="http://bdat.smartlab.ws/" class="">http://bdat.smartlab.ws</a>. If you have any questions concerning the special session, please do not hesitate to contact us via email through the dedicated address: <a href="mailto:bdat@smartlab.ws" class="">bdat@smartlab.ws</a> <br class=""><br class="">More information about the Conference Program, accommodation facilities and registration fees is available on the INNS Conference on Big Data 2015 website <a href="http://innsbigdata.org/" class="">http://innsbigdata.org</a> </span></font></div><p class="MsoNormal" style="margin: 0cm 0cm 0.0001pt; font-size: 14px; font-family: Calibri, sans-serif;"><span style="font-size: 14pt; font-family: Calibri;" class=""> </span></p><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class="">---<br class="">Dr. Alessandro Ghio, Ph.D.<br class=""><br class="">Research Assistant<br class="">Smartlab - Polytechnic School – University of Genoa<br class="">Via Opera Pia 11a<br class="">I-16145 Genoa (Italy)<br class=""><br class="">T. +39-(0)10-3532192<br class="">F. +39-(0)10-3532897<br class="">M. +39-3404659908<br class="">@ <a href="mailto:Alessandro.Ghio@unige.it" class="">Alessandro.Ghio@unige.it</a> <br class=""><br class="">W <a href="http://ghio.it/" class="">http://ghio.it</a> <br class="">Twitter @alexghio<br class="">— </span></font></div><div style="margin: 0cm 0cm 0.0001pt;" class=""><font face="Calibri" class=""><span style="font-size: 15px;" class=""><br class=""></span></font></div><p class="MsoNormal" style="margin: 0cm 0cm 0.0001pt; font-size: 14px; font-family: Calibri, sans-serif;"><span style="font-family: Calibri;" class=""> </span></p></body></html>