Patents by Inventor Daniel LAFOND

Daniel LAFOND has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230343236
    Abstract: A computer-implemented method and system for providing adaptive training cursus to a trainee is disclosed. In the context of flight training for a given flight, the method allows providing training cursus recommendations by identifying every relevant phase (maneuvers and/or procedures) in a flight mission performed by a trainee; assessing the ease in flight of the trainee during each of these specific phases using an ease in flight algorithm model using psychophysiological parameters; and based on the conjunction of the ease in flight and predefined skills required to perform each phase, providing training cursus recommendations to target specifically the skills which are not yet mastered by the trainee.
    Type: Application
    Filed: December 17, 2020
    Publication date: October 26, 2023
    Inventors: Jean-François GAGNON, Yannick JAMES, Daniel LAFOND
  • Publication number: 20220027764
    Abstract: There is provided a method and system for providing a recommendation for a given problem by using a set of supervised machine learning (ML) models online by performing dynamic model evaluation and selection. An optional knowledge capture phase may be used to train the set of ML models offline using passive and/or active learning. Upon detection of a suitable initialization condition, the set of ML models is provided for inference and a feature vector is obtained. A set of predictions associated with accuracy metrics is generated by the set of models based on the feature vector. The accuracy metric may be global or class-specific. A recommendation is provided based on at least one of the set of predictions. The recommendation may be provided by selecting a best model, or by performing a vote weighted by the accuracy metrics. The set of ML models is retrained after obtaining an actual prediction.
    Type: Application
    Filed: July 26, 2021
    Publication date: January 27, 2022
    Inventors: Daniel LAFOND, Frédéric MORIN, Bénédicte CHATELAIS
  • Publication number: 20170004435
    Abstract: A method and system are disclosed for providing team-level metrics data, the method comprising for each member of a team, collecting sensor data originating from a plurality of sensors, and locally processing the collected sensor data to provide data representative of an individual functional assessment; wirelessly obtaining each of the data representative of an individual functional assessment and processing each of the obtained data representative of an individual functional assessment to generate data representative of a functional state of the team.
    Type: Application
    Filed: June 30, 2016
    Publication date: January 5, 2017
    Inventors: Jean-François GAGNON, Daniel LAFOND, Martin RIVEST, François COUDERC, Stéphane DION