公开(公告)号：US20240422057A1

公开(公告)日：2024-12-19

申请号：US18555805

申请日：2023-07-13

Applicant: ZHEJIANG LAB

Inventor： Peilei WANG ,  Ruyun ZHANG ,  Jun ZHU ,  Tao ZOU ,  Shunbin LI ,  Qi XU

IPC: H04L41/082 ,  H04L41/0894 ,  H04L67/1097

Abstract: A data storage system includes: a server, a client and a control end; the control end is configured to generate a configuration file, and send the configuration file to the client and the server; the client is configured to generate an encapsulation rule based on the configuration file, generate a storage request, perform encapsulation on the storage request to obtain a message packet, and send the message packet to the server; the server is configured to generate an extraction unit and an action unit based on the configuration file, analyze the message packet to obtain the target information, write the target information into each extraction unit, read action information and determine an action unit matching the action information as a target action unit, and execute the storage actions corresponding to the target action unit to store byte stream data of the target information.

公开(公告)号：US20240404642A1

公开(公告)日：2024-12-05

申请号：US18460671

申请日：2023-09-04

Applicant: ZHEJIANG LAB

Inventor： Long ZHENG ,  Yu HUANG ,  Wei ZHOU

IPC: G16B50/30

Abstract: A method, a device and a medium for genome graph analysis based on in-memory computing. The method comprises the following steps: firstly, combining a linear reference genome with genetic variation to construct a genome graph; then, generating indexes for a plurality of vertices of the genome graph, and constructing an index table according to the generated indexes; then dividing the read length into a plurality of substrings with the length of k-mer, and querying the index table to obtain a seed position, generating a reference subgraph according to the seed position, and identifying a candidate mapping position according to the reference subgraph to filter a candidate mapping area; finally, using a PUM mode to run approximate string matching between the read length and all unfiltered candidate mapping positions, so as to complete the optimal alignment of a reference gene sequence and a query gene sequence.

公开(公告)号：US20240398305A1

公开(公告)日：2024-12-05

申请号：US18798861

申请日：2024-08-09

Applicant: ZHEJIANG LAB

Inventor： Yu ZHANG ,  Haotian QIAN ,  Chaoliang SUN ,  Zhichao WANG ,  Huan ZHANG ,  Tianzi JIANG

IPC: A61B5/245 ,  A61B5/00

Abstract: A system for classifying working memory task magnetoencephalography based on machine learning, including: the magnetoencephalography data acquisition module configured to acquire magnetoencephalography data of a subject in different working memory task states; the magnetoencephalography data preprocessing module configured to control the quality of magnetoencephalography data in different working memory tasks and separate noises and artifacts; the magnetoencephalography source reconstruction module configured for sensor signal analysis and source reconstruction analysis for the data processed by the magnetoencephalography data preprocessing module; and the machine learning classification module is configured to classify the working memory tasks to which the subjects belong by taking power time series as features. The present disclosure integrates the complete analysis pipeline from preprocessing to source reconstruction of the working memory magnetoencephalography data, classifies the working memory task magnetoencephalography data, and is of great significance to the study of working memory decoding and brain memory related mechanisms.

公开(公告)号：US20240395408A1

公开(公告)日：2024-11-28

申请号：US18788009

申请日：2024-07-29

Applicant: ZHEJIANG LAB

Inventor： Jingsong LI ,  Peijun HU ,  Yu TIAN ,  Tianshu ZHOU

IPC: G16H50/20 ,  A61B6/00 ,  A61B6/03 ,  A61B6/50 ,  G06T5/20 ,  G06T7/00 ,  G06T7/11 ,  G06T7/13

Abstract: A pancreatic postoperative diabetes prediction system based on supervised deep subspace learning. A deep convolutional neural network and the MITK software are used to obtain postoperative residual pancreas area, so as to taken as the region-of-interest. Traditional image radiomics features and deep semantic features are extracted from the residual pancreas area, and a high-dimensional image feature set is constructed. Clinical factors related to diabetes, including pancreatic excision rate, fat and muscle tissue components, demographic information and living habits are extracted, and a clinical feature set is constructed. Based on a supervised deep subspace learning network, image and clinical features are represented and fused in subspace in dimensionality reduction, while a prediction model is trained to mine sensitive features highly relevant to the prediction risk of a patient suffering postoperative diabetes mellitus with a high degree of automation and discriminative accuracy.

公开(公告)号：US20240388521A1

公开(公告)日：2024-11-21

申请号：US18664368

申请日：2024-05-15

Applicant: ZHEJIANG UNIVERSITY ,  ZHEJIANG LAB

Inventor： Haifeng ZHOU ,  Di WANG ,  Xiang CHEN ,  Chunming WU ,  Wenhai WANG

IPC: H04L43/55 ,  H04L9/40 ,  H04L69/326

Abstract: A method and a system for large-scale traffic generation based on programmable network technology, which are used for the research on network operation and maintenance and defense of attacks such as DDOS. According to the method, the required large-scale traffic is generated as required through the coordination of servers and programmable switches. The method specifically comprises the steps of designing a series of primitives which are based on intentions and are irrelevant to underlying architecture details, and reducing the description difficulty of generating large-scale traffic intentions; completing required configurations on the switch and the server by the designed cooperation mechanism of the server and programmable switch according to intentions expressed by different types of primitives, and achieving large-scale traffic generation by coordinating and utilizing server and switch resources.

公开(公告)号：US12147909B2

公开(公告)日：2024-11-19

申请号：US18491817

申请日：2023-10-23

Applicant: ZHEJIANG LAB

Inventor： Feng Lin ,  Yunhe Pan

IPC: G06N5/022 ,  G06F40/30 ,  G06V10/77 ,  G06V10/80 ,  G06V40/20

Abstract: A method and an apparatus for cross-media corresponding knowledge generation. The method comprises: generating a second knowledge unit of a second medium according to a first knowledge unit of a predefined first medium; generating a first feature parameter vector corresponding to the first knowledge unit and a second feature parameter vector corresponding to the second knowledge unit; mapping the first feature parameter vector and the second feature parameter vector to a corresponding two-dimensional spherical feature surface to obtain a first feature point of the first feature parameter vector on the corresponding two-dimensional spherical feature surface and a second feature point of the second feature parameter vector on the corresponding two-dimensional spherical feature surface; indexing the first feature point and the second feature point to obtain a first index and a second index; and generating a bidirectional index corresponding relationship between the first knowledge unit and the second knowledge unit.

公开(公告)号：US20240354577A1

公开(公告)日：2024-10-24

申请号：US18374669

申请日：2023-09-29

Applicant: ZHEJIANG LAB

Inventor： Yong LI ,  Laiping ZHAO ,  Zezheng MAO ,  Wen CHENG ,  Guang CHEN ,  Lingfang ZENG

IPC: G06N3/084

CPC classification number: G06N3/084

Abstract: A method, a system, a device, and a storage medium for operation resource placement of deep learning are provided. The method includes: acquiring training operations to be placed and corresponding priorities; based on an order of the priorities, selecting a network structure for operation placement according to required resource amount of the training operations in sequence; the network structure including a server, a top of rack, a container group set denoted as Podset and a trunk layer switch; based on the selected network structure, taking a transmission amount of network data in a training process as an optimization target to perform minimization optimization, and obtaining a corresponding operation placement scheme.

公开(公告)号：US12119108B2

公开(公告)日：2024-10-15

申请号：US18363701

申请日：2023-08-01

Applicant: ZHEJIANG LAB

Inventor： Jingsong Li ,  Wenchao Xiang ,  Guangyuan Deng ,  Tianshu Zhou ,  Yu Tian

IPC: G06F16/25 ,  G06F9/48 ,  G16H10/60 ,  G16H40/20

CPC classification number: G16H40/20 ,  G06F9/4881 ,  G06F16/254 ,  G16H10/60

Abstract: The present disclosure discloses a medical ETL task dispatching method, system and apparatus based on multiple centers. The method includes following steps: step S1: testing and verifying ETL tasks; step S2: deploying the ETL tasks to a hospital center, and dispatching the ETL tasks to a plurality of executors for execution; step S3: screening an executor set meeting resource demands of ETL tasks to be dispatched; step S4: calculating a current task load of each executor in the executor set; step S5: selecting the executor with a minimum current task load to execute the ETL tasks; and step S6: selecting, by the dispatching machine, the ETL tasks from executor active queues according to a priority for execution. The present disclosure selects the most suitable executor by analyzing a serving index as a task to be dispatched on a current dispatching machine.

公开(公告)号：US12118832B1

公开(公告)日：2024-10-15

申请号：US18492767

申请日：2023-10-23

Applicant: ZHEJIANG LAB

Inventor： Hongyang Chen ,  Chenxi Liu ,  Zhu Xiao

IPC: G07C5/02

CPC classification number: G07C5/02

Abstract: The present application discloses a method and a system for analyzing and predicting a vehicle stay behavior based on multi-task learning, and the method includes the following steps: acquiring vehicle GPS and OBD data including a vehicle ID, a travel start time, a start longitude, a start latitude, an end time, an end longitude, and an end latitude after desensitization; preprocessing vehicle GPS and OBD data to obtain vehicle stay behavior data including stay location and stay duration; extract a spatial-temporal characteristic of the preprocessed vehicle stay behavior data by a deep recurrent neural network; inputting the spatial-temporal characteristic into a multi-task learning and predicting network, and obtaining the correlation between a stay location prediction task and the stay duration prediction task based on the historical stay behavior of the vehicle through the multi-task learning and predicting network to predict the stay location and stay duration.

公开(公告)号：US12117829B1

公开(公告)日：2024-10-15

申请号：US18505068

申请日：2023-11-08

Applicant: ZHEJIANG LAB

Inventor： Yuntao Liu ,  Yongdong Zhu ,  Zhifeng Zhao ,  Wei Hua ,  Qian Huang ,  Shuyuan Zhao ,  Daoxun Li ,  Zimian Wu

IPC: G05D1/00 ,  B60W60/00 ,  H04L67/12

CPC classification number: G05D1/0022 ,  B60W60/00 ,  H04L67/12 ,  B60W2556/45

Abstract: The present disclosure discloses an autonomous vehicle remote control apparatus and a method based on heterogeneous networks. The apparatus comprises a vehicle information acquisition module, a first message sending module, a first message receiving module and a first remote control module. According to the present disclosure, the possibility of failure of remote control is avoided or greatly reduced by bypassing the area where the network quality does not support remote control when planning a vehicle path, heterogeneous network resources are reasonably utilized on the vehicle driving path, the real-time performance of obtaining vehicle-related information by a remote control terminal is improved, and the availability and reliability of remote control and the safety of vehicle driving are effectively enhanced.