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SUMMARY:Qualitative Trend Analysis: An artificial intelligence approach to
  information extraction
DTSTART:20141028T161500
DTEND:20141028T171500
DTSTAMP:20260408T034122Z
UID:acdd78149baaf56143d75fafe54af6246699cd0ee5d604c2340525a8
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Kris Villez\, SPIKE (Sensor management\, Process Intelligen
 ce and Control)\, Process Engineering (Eng)\, EAWAG Duebendorf\nAbstract:\
 nOne of the most critical elements for automation of wastewater treatment 
 processes is measurement of the key variables involved. In practice\, many
  such key variables cannot be measured directly. Fortunately\, indirect me
 asurements can be of great assistance to approximately assess the changing
  condition of wastewater treatment plants.  Evaluated indirect measuremen
 ts include macroscopic variables such as the pH and oxidation-reduction po
 tential and images of sludge settling experiments. To infer the state of a
  wastewater treatment plant from such indirect measurements\, specialized 
 algorithms for information extraction are however necessary.\nCurrently\, 
 qualitative trend analysis (QTA) is one of the strategies selected to do s
 o. QTA permits to extract coarse grained information about the process dyn
 amics by focusing on the signs of signal derivatives rather than their exa
 ct values. Currently\, these algorithms are developed further and fine-tun
 ed for an ever increasing diversity of applications. Early successes were 
 achieved for reaction end-point detection in a sequencing batch reactor fo
 r nitrogen and phosphorus removal from communal wastewater. In the meantim
 e\, newly developed QTA algorithms have also been applied successfully for
  batch process diagnosis and control of the Hard wastewater treatment plan
 t in Winterthur (Switzerland). Currently\, the QTA algorithms are tested f
 or analysis of images of sludge settling experiments. In this talk\, basic
  concepts\, challenges and opportunities regarding QTA will be covered.Sho
 rt biography:\nKris Villez obtained his Ph.D. in Applied Biological Scienc
 es in 2007 at Ghent University (Belgium). After postdoctoral work at Unive
 rsité Laval (Québec\, QC\, Canada) and Purdue University (West Lafayette
 \, IN\, USA) he now works at Eawag (Dübendorf\, Switzerland) since 2012 i
 n a tenure-track group leader position. In his research\, he focuses on mo
 nitoring\, diagnosis\, and automation of wastewater treatment processes.
LOCATION:GR A3 31 http://plan.epfl.ch/?room=GR%20A3%2031
STATUS:CONFIRMED
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