Patents Assigned to Zhejiang Lab
  • Patent number: 11456078
    Abstract: Provided is a multi-center synergetic cancer prognosis prediction system based on multi-source migration learning. The system includes a model parameter setting module, a data screening module, and a multi-source migration learning module, wherein the model parameter setting module is responsible for setting cancer prognosis prediction model parameters; the data screening module is arranged at a clinical center, and a management center transmits the set model parameter to each clinical center, such that each clinical center inquires a sample feature and prognosis index data from a local database according to the model parameter, so as to preprocess the data; and the multi-source migration learning module includes a source model training unit, a migration weight calculation unit, and a target model calculation unit.
    Type: Grant
    Filed: December 7, 2021
    Date of Patent: September 27, 2022
    Assignee: ZHEJIANG LAB
    Inventors: Jingsong Li, Yu Tian, Weiguo Chen, Jing Ma
  • Patent number: 11436494
    Abstract: An optimal power flow computation method based on multi-task deep learning is provided, which is related to the field of smart power grids.
    Type: Grant
    Filed: April 10, 2022
    Date of Patent: September 6, 2022
    Assignee: Zhejiang Lab
    Inventors: Gang Huang, Longfei Liao, Wei Hua
  • Patent number: 11437846
    Abstract: Disclosed is a reliable resilient router for a wide-area phasor measurement system of a power grid. The reliable resilient router includes a Data-type data packet processing module, a RetransReq data packet processing module, a RetransReport data packet processing module, a basic data packet processing module, a multi-path forwarding state table module, a content storage queue module and a physical port. The reliable resilient router of the present invention realizes active detection of a lost data packet and a single or batch retransmission mechanism, so that the lost data packet can be directly recovered in the grid from an upstream router through which the lost data packet passes, which improves the recovery time success rate and the high efficiency of the lost data packet, and guarantees the safe and stable operation of the wide-area phasor measurement system of the power grid.
    Type: Grant
    Filed: December 31, 2021
    Date of Patent: September 6, 2022
    Assignee: ZHEJIANG LAB
    Inventor: Boyang Zhou
  • Patent number: 11431632
    Abstract: The present invention relates to the technical field of computer networking, in particular to an ID/location hybrid forwarding method based on source routing, including a message format based on an extension header of a MobilityFirst protocol, a source routing forwarding mechanism based on ID identifiers and a source routing forwarding mechanism based on location identifiers.
    Type: Grant
    Filed: May 9, 2022
    Date of Patent: August 30, 2022
    Assignee: Zhejiang Lab
    Inventors: Qi Xu, Hanguang Luo, Tao Zou, Ruyun Zhang, Geyang Xiao, Wanxin Gao, Huifeng Zhang, Congqi Shen
  • Publication number: 20220265218
    Abstract: The present invention discloses a real-time evaluation method and evaluation system for group emotion homogeneity. The method comprises the steps as follows: enabling testees to be in the same emotion induction environment, and collecting the original electroencephalograph (EEG) signals of multiple persons at the same time through online multichannel EEG equipment; and based on the average instantaneous phase per second of the beta frequency band and the energy value per second of the alpha frequency band obtained after wavelet transformation, calculating the time synchronization degree and the valence consistency degree in real time, and finally obtaining a group emotion homogeneity index for the objective evaluation of group emotion homogeneity.
    Type: Application
    Filed: January 9, 2022
    Publication date: August 25, 2022
    Applicant: Zhejiang Lab
    Inventors: Taihao LI, Guanxiong PEI, Yulong LIU
  • Patent number: 11354499
    Abstract: Disclosed is a meta-knowledge fine tuning method and platform for a multi-task language model. The method is to obtain highly transferable shared knowledge, that is, meta-knowledge, on different data sets of tasks of the same category, perform interrelation and mutual reinforcement on the learning processes of the tasks of the same category that correspond to different data sets and are in different domains, so as to improve the fine tuning effect of downstream tasks of the same category on data sets of different domains in the application of the language model, and improve the parameter initialization ability and the generalization ability of a general language model for the tasks of the same category.
    Type: Grant
    Filed: November 22, 2021
    Date of Patent: June 7, 2022
    Assignee: ZHEJIANG LAB
    Inventors: Hongsheng Wang, Haijun Shan, Shengjian Hu
  • Patent number: 11341326
    Abstract: Provided is a method and a platform for compressing a pre-training language model based on knowledge distillation. According to the method, a universal knowledge distillation strategy of feature migration is firstly designed, and in the process of knowledge distillation from the teacher model to the student model, the feature mapping of each layer of the student model is approaching the teacher's features, focusing on the ability of small samples to express features in the intermediate layer of the teacher model, and guiding the student model by using these features; then, a knowledge distillation method based on self-attention cross is constructed; finally, a linear transfer strategy based on Bernoulli probability distribution is designed to gradually complete the knowledge transfer of feature mapping and self-attention distribution from teachers to students.
    Type: Grant
    Filed: September 24, 2021
    Date of Patent: May 24, 2022
    Assignee: ZHEJIANG LAB
    Inventors: Hongsheng Wang, Haijun Shan, Fei Yang
  • Patent number: 11255767
    Abstract: A method and a device for measuring light field distribution are provided; including steps of utilizing the optical trap to stably levitating particles, moving the optical trap to bring the particles close to the light field to be measured, and utilizing the photodetector to collect the scattered light signals of the particles at different positions in the three-dimensional space of the light field to be measured, and calculating the light field distribution of the light field to be measured according to the scattered light intensity which is proportional to the light intensity at that position. The device for measuring the optical field distribution includes a laser, an optical trapping path, particles, a photodetector, a control system and an upper computer; the laser emits a laser, passes through the optical trapping path, and emits highly focused captured light B to form an V optical trap to capture particles.
    Type: Grant
    Filed: July 10, 2021
    Date of Patent: February 22, 2022
    Assignees: Zhejiang Lab, Zhejiang University
    Inventors: Zhenhai Fu, Cheng Liu, Zhiming Chen, Xingfan Chen, Nan Li, Huizhu Hu