2018年11月12日（星期一）16:00-18:00通訊所演講訊息如下，歡迎踴躍參加!!
演講題目：Interval Data Fusion with Preference Aggregation
演 講 者：Prof. Sergey V. Muravyov, Tomsk Polytechnic University
時 間：2018/11/12（Monday）16:00-17:00
地 點：清華大學綜三館 315室SP‧ARK (General Building III R315)
ABSTRACT
It is discussed the interval data fusion procedure intended for determination of an interval to be consistent with maximal number of given initial intervals (not necessary consistent among each other) and to be with maximal likelihood including a value x∗ that can serve as representative of all the given intervals. An algorithm of the interval fusion with preference aggregation (IF&PA) is proposed and discussed that can be carried out with help of representation of intervals on the real line by weak order relations (or rankings) over a set of discrete values belonging to these intervals. It is possible to determine a consensus ranking for collection of discrete values rankings, corresponding to initial intervals. The highest ranked value, accepted as a result of the fusion, guarantees improved accuracy and robustness of the interval data fusion procedure outputs. It is considered a space of weak orders induced by the intervals, its properties and dimension. A reasonable number choice problem of discrete values, representing the interval data, is investigated. Related to the problem, computing experiment results and recommendations are given. The interval data fusion procedures can be widely applied in interlaboratory comparisons, prediction of fundamental constant values on the base of different measured values, conformity testing, enhancement of multisensor readings accuracy in sensor networks, etc.
BIOGRAPHY
Sergey V. Muravyov graduated from the Tomsk Polytechnic University (TPU, Tomsk, Russia) in 1977, where he studied computer engineering. He received the PhD degree (Candidate of Technical Sciences) in automatic control theory in 1984, and DSc (Doctor of Technical Sciences) degree in electrical measurements and software engineering in 1998 from the TPU. Since 1977 he has been working in various positions in the Department of Computer-aided Measurement Systems and Metrology of the TPU. In 1999-2014 he was a Full Professor and a Head of the Department. Now he is a Full Professor of the Division of Automation and Robotics at the TPU.
In 1991-2002 many times he acted as a Visiting Researcher a Visiting Professor in measurement information systems theory at the Department of Computer Science and Information Systems, University of Jyväskylä, Finland. In 2007-2009 he participated in joint researches in Sensor and Information Fusion under the EERSS Programme of the National University of Singapore. In 2016 for three months he was a Visiting Professor at Vignan University, India.
He is a member of TC7, Measurement science (in 2006-2012 acted as a Vice-Chairman of the Technical Committee), and of TC1, Education and training in measurement and instrumentation, of the International Measurement Confederation (IMEKO). He is an editor of Sensor Review and reviewer of many international journals. He served as a Session Chair and Program Committee Member of many international conferences. He serves as an expert of the Russian Science Foundation; a member of Higher Certifying Commission's (VAK) expert board on electronics, instrumentation, radio engineering and communication (Moscow); a member of Academic Council of the TPU, etc.
He has published over 150 scientific papers. His current research interests include measurement theory, sensor data fusion with preference aggregation, chemical measurements, electrical and magnetic measurements, modeling of measurement procedures and systems.
演講題目：Interval data fusion with preference aggregation in wireless sensor network:
energy-accuracy trade-off in presence of outliers
演 講 者：Prof. Liudmila I. Khudonogova, Tomsk Polytechnic University
時 間：2018/11/12（Monday）17:00-18:00
地 點：清華大學綜三館 315室SP‧ARK (General Building III R315)
ABSTRACT
For balancing measurement accuracy and energy consumption in a wireless sensor network in presence of outliers it is proposed sensor accuracy enhancement algorithm SensAcc and active node selection algorithm ActiveNode based on the interval data fusion method IF&PA. The results of numerical experimental investigation of the developed algorithms are presented. It is shown that the SensAcc provides the reduction of the uncertainty of measurement result at least tenfold comparing with the uncertainty of multisensor readings under possible existence of failed nodes. Simulation results have shown the ActiveNode allows to reduce the cluster nodes energy consumption approximately threefold.
BIOGRAPHY
Liudmila I. Khudonogova received her MSc degree in 2012 in Metrology, Standardization and Certification and PhD degree in 2017 in Devices and Methods for Control of Environment, Substances and Materials from the TPU. Since 2012 she is with the group of Prof. Muravyov at the TPU. Since 2018 she is an Associate Professor of Division of Automation and Robotics at the TPU. Her research interests include development and research in sensor data fusion with preference aggregation, voting methods, visual programming languages.