ACS 2012 : 1st International Workshop on Analytics for Cyber-Physical Systems
Call For Papers
1st International Workshop on Analytics for Cyber-Physical Systems (ACS-2012) Held in conjunction with SIAM Data Mining (SDM-2012)
Call for Papers
A cyber-physical system (CPS) is a system that exhibits a co-ordination between the system's computational and physical elements. Such systems are becoming increasingly ubiquitous with applications in diverse domains such as transportation, health care, emergency response, physical infrastructure, etc. Typically, such systems are often configured as a system of sub-systems that are functionally independent but operationally dependent on each other. Analyzing data collected from such CPS requires a system of systems approach, which is not often seen in traditional data analytic solutions. The CPS domain possesses unique sets of challenges, in terms of modeling the relationship between different sub-systems to effectively extract knowledge from underlying data, while operating under real time constraints and handling massive and often streaming data.
The 1st workshop on Analytics for Cyber-Physical Systems aims to bring together researchers from academia, government and industrial research labs who are working in the area of Cyber-Physical Systems with an eye towards real world deployments. Large scale physical systems are increasingly being instrumented with various types of sensors (including human sensors). To convert this data into actionable insights, analytics is needed at each step: From signal processing of distributed sensor data, to business intelligence techniques to integrate data from various sources, and to techniques from data mining to machine learning to give us insights over this data.
Topics of Interest
The workshop welcomes contributions in any area of analytics for Cyber-Physical systems. The topics include:
Signal processing of real world sensor data
Scaling standard analytic algorithms to massive data
Time series mining
Data mining/machine learning for massive sensor data
Data mining/machine learning for streaming data
Identifying faults and anomalies in cyber-physical systems
Application case studies that demonstrate real life deployment of cyber-physical systems
Analyzing Logs for Event Detection
Complex Event Processing
Distributed Data Mining
Mining Heterogeneous Data
Transfer learning from one cyber-physical domain to another
The main motivation for this workshop stems from the increasing need for a forum to exchange ideas and recent research results, and to facilitate collaboration and dialog between academia, government, and industrial stakeholders.
We solicit high quality papers in the general areas of data analytics for large cyber-physical systems.
All submitted papers will be peer reviewed. We have identified a set of researchers who are currently active in the related research areas as potential reviewers (Click here for the preliminary list). If accepted, at least one of the authors must attend the workshop to present the work. Selected accepted papers will be recommended for submission to special issues of journals.
All accepted papers should have a maximum length of 9 pages (single-spaced, 2 column, 10 point font, and at least 1 inch margin on each side). Authors should use US Letter (8.5 in x 11 in) paper size. Papers must have an abstract with a maximum of 300 words and a keyword list with no more than 6 keywords. Authors are required to submit their papers electronically in PDF format (postscript files can be converted using standard converters) to https://cmt2.research.microsoft.com/SDM2012/Default.aspx . We would like to encourage you to prepare your paper in LaTeX2e. Papers should be formatted using the SIAM SODA macro, which is available through the SIAM website. You can access it at http://www.siam.org/proceedings/macros.php. The filename is soda2e.all. Make sure you use the macros for SODA and Data Mining Proceedings; papers prepared using other proceedings macros will not be accepted. For Microsoft Word users, please convert your document to the PDF format. All submissions should clearly present the author information including the names of the authors, the affiliations and the emails. The submitted papers should be submitted as an email attachment to email@example.com.
Paper Submission: January 14, 2012
Notification of Acceptance: January 30, 2012
Camera Ready Paper Due: February 15, 2012
1. Umeshwar Dayal, Hewlett Packard Labs, CA, USA.
2. Chetan Gupta, Hewlett Packard Labs, CA, USA.
3. Varun Chandola, Oak Ridge National Laboratory, TN, USA.
4. Ranga Raju Vatsavai, Oak Ridge National Laboratory, TN, USA.
5. Robert Grossman, University of Chicago, IL, USA.
6. Elke Rundensteiner, Worcester Polytechnic Institute, MA, USA.
For more information: http://www.ornl.gov/sci/knowledgediscovery/asc-2012/