公开(公告)号：US20240282465A1

公开(公告)日：2024-08-22

申请号：US18212727

申请日：2023-06-22

Applicant: ZHEJIANG LAB

Inventor： Zenghui XU ,  YU ZHANG ,  Zhan ZHANG ,  Ting YU ,  Jin ZHAO ,  Linlin HOU

IPC: G16H50/80

CPC classification number: G16H50/80

Abstract: A method of predicting infectious disease infections and a system thereof, a device, and a storage medium are provided. An increment module controls an input module to obtain new incremental data in the current cycle in response to a preset instruction. A graph engine iteratively trains a first graph model based on new incremental data until the first graph model meets a convergence condition, so as to obtain a second graph model and perform dynamic updating of the graph model. Each region acts as a node in the graph model, each node feature is obtained based on the regional disease information, edges are defined by nodes connected to each other according to a geographic location relationship among regions, and each edge is assigned an edge weight according to regional population information. The updated graph model predicts infections based on data to be predicted that is selected by the interaction module.

公开(公告)号：US12067700B2

公开(公告)日：2024-08-20

申请号：US17701692

申请日：2022-03-23

Applicant: ZHEJIANG LAB

Inventor： Wentao Zhu ,  Mengfan Xue ,  Shaojie Li ,  Defu Yang

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/194 ,  G06T7/90

CPC classification number: G06T7/0002 ,  G06T7/11 ,  G06T7/194 ,  G06T7/90 ,  G06T2207/30024

Abstract: Disclosed is a method for automatic classification of pathological images based on a staining intensity matrix. This method directly extracts the staining intensity matrix irrelevant to a stain ratio, a staining platform, a scanning platform and some human factors in the pathological image as the feature information of classification, without restoring normalized stained images, while retaining all impurity-free information related to diagnosis. It avoids the phenomenon that the diagnostic effect of the existing computer-aided diagnosis method of pathological images based on the traditional color normalization method changes with the changes of the selected standard pathological sections. Moreover, it avoids the error introduced by the need to restore the stained image, and has a higher diagnostic accuracy and a more stable diagnostic effect. At the same time, the method can realize the diagnosis of pathological images in a shorter time, which is easy to realize and more practical.

公开(公告)号：US20240267288A1

公开(公告)日：2024-08-08

申请号：US18041538

申请日：2022-11-22

Applicant: ZHEJIANG LAB

Inventor： Xuyang ZHAO

IPC: H04L41/0803 ,  H04J3/02 ,  H04L41/12

CPC classification number: H04L41/0803 ,  H04J3/02 ,  H04L41/12

Abstract: The present disclosure discloses a data transmission method and system in time-sensitive network, which relates to the technical field of time-sensitive network of industrial Internet. The devices include multiple industrial end stations, multiple time-sensitive network switches and a network configuration operating system. In the present disclosure, the method and system can effectively reduce the processing time overhead of time-sensitive data in devices and is compatible with traditional Ethernet data transmission.

公开(公告)号：US12056533B2

公开(公告)日：2024-08-06

申请号：US18354601

申请日：2023-07-18

Applicant: ZHEJIANG LAB

Inventor： Huifeng Zhang ,  Congqi Shen ,  Tao Zou ,  Jun Zhu ,  Ruyun Zhang ,  Qi Xu ,  Hanguang Luo ,  Xingchang Guo

IPC: G06F9/46 ,  G06F9/50 ,  G06N20/00

CPC classification number: G06F9/5038 ,  G06N20/00

Abstract: A method, an apparatus and a medium for optimizing allocation of switching resources in the polymorphic network. The method selects the ASIC switching chip, FPGA and PPK software switching on the polymorphic network element based on machine learning, and specifically comprises the following steps: manually pre-configuring, formulating basic rules for polymorphic software and hardware co-processing; offline learning, designing training configuration in the offline learning stage to capture different switching resource usage variables, running experiments to generate the original data of a training classifier, and using the generated performance indices to train the model offline; and online reasoning, obtaining switching resource allocation advises, and updating modality codes according to the switching resource allocation advises.

公开(公告)号：US12039361B1

公开(公告)日：2024-07-16

申请号：US18494002

申请日：2023-10-25

Applicant: ZHEJIANG LAB

Inventor： Hongsheng Wang ,  Guang Chen ,  Fei Wu ,  Feng Lin

IPC: G06F9/48

CPC classification number: G06F9/48

Abstract: The present disclosure discloses a method for executing a task. The method includes: a master computing device node in a computing cluster system receives a task code of a to-be-executed task; the master computing device node divides the to-be-executed task into subtasks, and for each of the subtasks, the master computing device node determines operators required to execute the subtask based on the task code; the master computing device node respectively distributes the subtasks to computing nodes in the computing cluster system, such that for each of the computing nodes, the computing node generates an executable task subgraph for the computing node based on the operators required to execute the subtask distributed to the computing node and data transmission relationships between the operators required to execute the subtask distributed to the computing node, and runs the executable task subgraph to execute the to-be-executed task.

公开(公告)号：US20240214324A1

公开(公告)日：2024-06-27

申请号：US18389820

申请日：2023-12-20

Applicant: ZHEJIANG LAB

Inventor： Xiaoyu YI ,  Yuan LIANG ,  Geyang XIAO ,  Xingchang GUO ,  Tao ZOU ,  Ruyun ZHANG ,  Linlin YAN

IPC: H04L47/6275 ,  H04L47/12

CPC classification number: H04L47/6275 ,  H04L47/12

Abstract: A traffic alarm method and apparatus based on a programmable switch, a device and a medium. The method monitors traffic with different priorities, when the traffic is greater than or equal to a threshold, the programmable switch may give a real-time alarm on a data plane and return low priority traffic information in a current network back to a sending end, and the sending end may adjust a task priority through alarm information. The present disclosure uses a programmable switch device, the lower priority traffic information may be alarmed to the sending end in real time on the data plane without passing through a controller, an alarm delay is significantly reduced, the sending end may adjust a sending rate timely, real-time scheduling of network traffic is achieved, high priority traffic transmission is ensured, and meanwhile link utilization is improved.

公开(公告)号：US12020490B2

公开(公告)日：2024-06-25

申请号：US18493795

申请日：2023-10-24

Applicant: ZHEJIANG LAB

Inventor： Qian Huang ,  Yongdong Zhu ,  Zhifeng Zhao

IPC: G06T7/70 ,  G06V20/58

CPC classification number: G06V20/58

Abstract: The present application discloses a method and a device for estimating the position of a networked vehicle based on independent non-uniform increment sampling. By mapping a laser radar point cloud to a spatiotemporal aligned image, independent non-uniform increment sampling is carried out on the mapping points falling in an advanced semantic constraint region of the image according to a point density of the depth interval where the mapping points are located, and the virtual mapping points generated by sampling are reversely mapped to the original point cloud space and merged with the original point cloud, and the combined point cloud is used to estimate the position of the networked vehicle based on a deep learning method, so as to solve the inaccurate position estimation problem of sheltered or remote networked vehicles due to the sparseness or missing of its own point cloud clusters.

公开(公告)号：US20240198511A1

公开(公告)日：2024-06-20

申请号：US18410566

申请日：2024-01-11

Applicant: Zhejiang Lab

Inventor： Zhijun MA ,  Hengyi LI ,  Yiming LIANG ,  Ruixiang QU ,  Yuan QI ,  Xiangling TIAN

IPC: B25J9/00 ,  D06M11/74 ,  D06M11/83 ,  D06M15/256 ,  D06M101/20 ,  D06M101/24 ,  D06M101/26 ,  D06M101/30

CPC classification number: B25J9/0015 ,  D06M11/74 ,  D06M11/83 ,  D06M15/256 ,  D06M2101/20 ,  D06M2101/24 ,  D06M2101/26 ,  D06M2101/30

Abstract: An electrically-actuated artificial muscle fiber with bidirectional linear strain and a preparation method thereof are provided. The artificial muscle fiber includes a fiber matrix, electrode layers and insulating layers. The artificial muscle fiber takes the fiber matrix as a skeleton, upper and lower layers of the fiber matrix are covered with one electrode layer respectively, and one insulating layer is covered on a surface of each of electrode layers. A helical fiber body is formed by winding. Finally, the artificial muscle fiber is formed through packaging, where metal wires are taken as leads and respectively connected to upper and lower layers of electrodes.

公开(公告)号：US20240176768A1

公开(公告)日：2024-05-30

申请号：US18489879

申请日：2023-10-19

Applicant: ZHEJIANG LAB

Inventor： Yihan WANG ,  Yiteng ZHAI ,  Yao YANG ,  Jiaxi YANG ,  Yang CHEN

IPC: G06F16/215 ,  G06F16/22

CPC classification number: G06F16/215 ,  G06F16/2246

Abstract: The present application disclose a method and a device for detecting and correcting abnormal scoring of peer reviews, which includes: converting collected scoring data into a two-dimensional matrix and preprocessing the data; determining the anomaly of the processed structured data with a one-way anomaly detection method, a consistency check method and a two-way anomaly detection method, and classifying the detected abnormal data into an abnormal data set; repairing the abnormal data for the abnormal data set with an information entropy correction method; generating an ability evaluation report according to the abnormal data set, performing weighed averaging on the corrected scoring data according to the scoring weights of reviewers in the ability evaluation report to obtain a final scoring result, and generating an abnormal scoring correction report. The present application can effectively detect the abnormal phenomenon of peer reviews in the performance appraisal of enterprise personnel.

公开(公告)号：US20240103052A1

公开(公告)日：2024-03-28

申请号：US18097234

申请日：2023-01-14

Applicant: ZHEJIANG LAB

Inventor： GANG HUANG ,  WEI HUA ,  ZHOU ZHOU

IPC: G01R21/00 ,  G06N3/042 ,  G06N3/08

CPC classification number: G01R21/001 ,  G06N3/042 ,  G06N3/08

Abstract: The present invention relates to the cross field of smart grid and artificial intelligence, provides a non-intrusive load monitoring method and device based on physics-informed neural network, comprising the following steps: Step 1, obtaining a total load data and an equipment load data of a building in a certain period of time, and using a sliding window method to cut to construct a training data. Step 2, designing a deep learning neural network model to learn the equipment load characteristics contained in the total load data, and outputting the equipment load forecasting. Step 3, based on a physics-constrained learning framework, training the deep learning neural network model by iteratively optimizing the training loss to obtain a trained physics-informed neural network model. Step 4, monitoring the equipment's power consumption in the building according to the output results of the physics-informed neural network model. The present invention can fully extract the operation characteristics of electric equipment, and improve the accuracy of load identification without increasing additional cost.