In the last 10 years, novel measurement technologies are rapidly emerging in many scientific fields including astronomy, physics, quantum mechanics, nanoscopy, medicine, biology, ecology and sociology. They enable the measurements on various objects beyond their past limits on accuracy, resolution and sensitivity of their outcomes, and size, distance, quantity, structure and feature of the objects. They are now largely thrusting the scientific innovation.
On the other hand, these technologies rely on not only their hardware instrument technologies but also the analysis techniques for their measurement data. In many cases, the information on the objects must be estimated by processing measurement outcomes and by applying some prior information. These estimation tasks must be effectively conducted by applying the recent progress of statistics, machine learning and pattern recognition including some novel principles adapted to the measurement problems.
Based on these backgrounds, this special session aims to establish a new DSAA research field named “Mathematical Information Measurement Science (MIMS),” and calls for papers on such innovative work on the statistical, machine learning and pattern recognition techniques developed for the advanced measurements and their applications to the advanced measurement problems.
Statistics, machine learning and pattern recognition techniques for generic advanced measurement problems including measurement optimization, complex measurement, large scale measurement, online and real time measurements and active measurement.
Their adaptation and their application to various scientific, industrial, business and social fields.
Paper Submission: June 8, 2017
Notification of acceptance: July 25, 2017
Camera-Ready: Aug 15, 2017
Advanced Registration: Aug. 31, 2017
Submissions to the main conference, including special sessions are available from Easy Chair
The paper length allowed is a maximum of ten (10) pages, in 2-column U.S. letter style using IEEE Conference template ( see the IEEE Proceedings Author Guidelines :
All submissions will be blind reviewed by the committee members on the basis of technical quality, relevance to session topics of interest, originality, significance, and clarity. Author names and affiliations must not appear in the submissions, and bibliographic references must be adjusted to preserve author anonymity.
To help ensure correct formatting, please use the style files for U.S. letter size found at the link below as templates for your submission. These include LaTeX and Word:
Violations of any of the above paper specifications may result in rejection of your paper. Please note that the Latex template does not allow for keywords. If you are using the Latex template, do not include keywords in your paper.
Genshiro Kitagawa (Research Organization of Information and Systems)
Takashi Washio (Osaka University)