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BEGIN:VEVENT
UID:20260731T031852Z - 66915@eu684a.odoo.com
DTSTART;TZID=Europe/Brussels:20260807T150000
DTEND;TZID=Europe/Brussels:20260807T170000
CREATED:20260731T031852Z
DESCRIPTION:<a href="https://www.openhub.be/event/studentlabs-sharing-the-o
 utcome-21">StudentLabs: Sharing the outcome</a>\nJoin us online on TEAMS!
  After several weeks of working on issues proposed by partner companies\, 
 the students present the results of their work in a series of short pitche
 s. La session s'ouvrira par une introduction au Service Learning présent
 ée par le professeur Benoit Macq\, qui reviendra sur la démarche pédago
 gique et les objectifs de la collaboration entre étudiant·es et entrepri
 ses partenaires proposée à l'occasion de ce programme des StudentLabs. M
 icrosoft Teams Meeting Join: https://teams.microsoft.com/meet/356607052708
 514?p=aDY3Fe1hzjGe9w5rsL Meeting number: 356 607 052 708 514Code secret : 
 JL9Dr6Bq Schedule The goal is to best adhere to the following schedule to 
 allow everyone to enjoy the full menu or choose their projects à la carte
 ! 15h15 - Muse: 15h25 - CPBourg: This project aims to modernize the interf
 ace of C.P. Bourg finishing printing machines to make it clearer\, safer\,
  and more intuitive for operators. After a phase of usage analysis\, the t
 eam designed touchscreen prototypes tailored to production constraints and
  the actual needs of the field. 15h35 - Parasensor: aims to facilitate the
  collection of home data in neuroscience by optimizing the number\, placem
 ent\, and type of sensors needed to record the activity of patients who ha
 ve or have not suffered a stroke. Using data collected during various task
 s (lying down\, sitting\, standing\, walking...)\, the project trains an a
 ctivity classifier and analyzes its accuracy as the number of sensors is r
 educed\, allowing for the elimination of redundant sensors while maintaini
 ng comparable performance. 15h45 - EMEIS: Despite existing precautions\, E
 meis nursing homes continue to face the risk of falls among residents. Thi
 s project has allowed for the training of a statistical machine learning m
 odel on historical data to predict the likelihood of a resident falling in
  the next three months\, with good [...]
DTSTAMP:20260731T031852Z
LOCATION:OpenHub\, Place du Levant 2\, 1348 Ottignies-Louvain-la-Neuve\, Be
 lgium
SUMMARY:StudentLabs: Sharing the outcome
X-ALT-DESC;FMTTYPE=text/html:<a href="https://www.openhub.be/event/studentl
 abs-sharing-the-outcome-21">StudentLabs: Sharing the outcome</a>\nJoin us
  online on TEAMS! After several weeks of working on issues proposed by par
 tner companies\, the students present the results of their work in a serie
 s of short pitches. La session s'ouvrira par une introduction au Service L
 earning présentée par le professeur Benoit Macq\, qui reviendra sur la d
 émarche pédagogique et les objectifs de la collaboration entre étudiant
 ·es et entreprises partenaires proposée à l'occasion de ce programme de
 s StudentLabs. Microsoft Teams Meeting Join: https://teams.microsoft.com/m
 eet/356607052708514?p=aDY3Fe1hzjGe9w5rsL Meeting number: 356 607 052 708 5
 14Code secret : JL9Dr6Bq Schedule The goal is to best adhere to the follow
 ing schedule to allow everyone to enjoy the full menu or choose their proj
 ects à la carte! 15h15 - Muse: 15h25 - CPBourg: This project aims to mode
 rnize the interface of C.P. Bourg finishing printing machines to make it c
 learer\, safer\, and more intuitive for operators. After a phase of usage 
 analysis\, the team designed touchscreen prototypes tailored to production
  constraints and the actual needs of the field. 15h35 - Parasensor: aims t
 o facilitate the collection of home data in neuroscience by optimizing the
  number\, placement\, and type of sensors needed to record the activity of
  patients who have or have not suffered a stroke. Using data collected dur
 ing various tasks (lying down\, sitting\, standing\, walking...)\, the pro
 ject trains an activity classifier and analyzes its accuracy as the number
  of sensors is reduced\, allowing for the elimination of redundant sensors
  while maintaining comparable performance. 15h45 - EMEIS: Despite existing
  precautions\, Emeis nursing homes continue to face the risk of falls amon
 g residents. This project has allowed for the training of a statistical ma
 chine learning model on historical data to predict the likelihood of a res
 ident falling in the next three months\, with good [...]
END:VEVENT
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