Patents by Inventor Kaicheng Li

Kaicheng Li 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: 20240343762
    Abstract: A proton pump modulator, and a use of the proton pump modulator in preparing a reagent. The reagent is used for improving learning ability, treating cognitive impairment, and/or treating neurodegenerative diseases. Also involved are an ATP6V1B2 modulator and a use thereof in preparing a reagent used for improving learning ability, treating cognitive impairment, and/or treating neurodegenerative diseases.
    Type: Application
    Filed: June 28, 2024
    Publication date: October 17, 2024
    Inventors: Kaicheng LI, Zhen Li, Pu YOU
  • Patent number: 12060091
    Abstract: The present disclosure provides a deep learning-based stop control method and system for a high-speed train, and relates to the technical field of rail transit management and control. The method includes: obtaining a training data set; establishing a convolutional neural network (CNN); training and optimizing the CNN by using the training data set, to obtain an optimized CNN; obtaining actual running data of a to-be-controlled train; inputting the actual running data into the optimized CNN to obtain a stop position of the to-be-controlled train; determining whether the stop position of the to-be-controlled train is 0; and if the stop position of the to-be-controlled train is 0, outputting a breaking command; or if the stop position of the to-be-controlled train is not 0, performing the step of “obtaining actual running data of a to-be-controlled train”. The present disclosure can ensure accurate stop of a high-speed train without high costs.
    Type: Grant
    Filed: September 17, 2021
    Date of Patent: August 13, 2024
    Assignee: BEIJING JIAOTONG UNIVERSITY
    Inventors: Jiateng Yin, Chenhe Ning, Shuai Su, Kaicheng Li, Tao Tang
  • Publication number: 20220126894
    Abstract: The present disclosure provides a deep learning-based stop control method and system for a high-speed train, and relates to the technical field of rail transit management and control. The method includes: obtaining a training data set; establishing a convolutional neural network (CNN); training and optimizing the CNN by using the training data set, to obtain an optimized CNN; obtaining actual running data of a to-be-controlled train; inputting the actual running data into the optimized CNN to obtain a stop position of the to-be-controlled train; determining whether the stop position of the to-be-controlled train is 0; and if the stop position of the to-be-controlled train is 0, outputting a breaking command; or if the stop position of the to-be-controlled train is not 0, performing the step of “obtaining actual running data of a to-be-controlled train”. The present disclosure can ensure accurate stop of a high-speed train without high costs.
    Type: Application
    Filed: September 17, 2021
    Publication date: April 28, 2022
    Inventors: Jiateng Yin, Chenhe Ning, Shuai Su, Kaicheng Li, Tao Tang