CONTENT CACHING METHOD FOR SATELLITE TERRESTRIAL INTEGRATED NETWORK WITH DIFFERENTIATED INTEREST AND ACCESS MODE

    公开(公告)号:US20240305849A1

    公开(公告)日:2024-09-12

    申请号:US18592565

    申请日:2024-03-01

    Applicant: ZHEJIANG LAB

    CPC classification number: H04N21/2665 H04N21/2183

    Abstract: A content caching method for a satellite terrestrial integrated network with differentiated interests and access modes, including: collecting user proportion information, content popularity distribution information, cache capacity information, and link delay information in the satellite terrestrial integrated network; determining a content caching problem of the collaboration of base stations and a satellite for a delay optimization based on differentiated user interests and differentiated access modes; solving the content caching problem to obtain a content caching strategy of the collaboration of the base stations and the satellite; and based on the obtained content caching strategy, caching contents in the base stations and the satellite to provide a content service for base station access users and satellite access users in the satellite terrestrial integrated network.

    METHOD AND APPARATUS FOR MONITORING LINK STATE BETWEEN NODES

    公开(公告)号:US20240297836A1

    公开(公告)日:2024-09-05

    申请号:US18245338

    申请日:2023-01-16

    Applicant: ZHEJIANG LAB

    CPC classification number: H04L43/0811 H04L12/437

    Abstract: The present disclosure discloses a method and apparatus for monitoring a link state between nodes. The method includes: determining, by a first node, whether to transmit a first diagnosis message to a second node based on a monitoring result of whether to receive message data transmitted by the second node for a first time duration; processing, by the second node, the received first diagnosis message and transmitting the processed second diagnosis message to a third node; processing, by the third node, the received second diagnosis message and transmitting the processed third diagnosis message to the second node; determining, by the second node, whether to transmit the third diagnosis message to the first node; and determining, by the first node, a link state between the first node and the second node based on a monitoring result of whether to receive the third diagnosis message for a second time duration.

    METHOD OF PREDICTING INFECTIOUS DISEASE INFECTIONS AND SYSTEM THEREOF, DEVICE, AND STORAGE MEDIUM

    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

    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.

    Method for automatic classification of pathological images based on staining intensity matrix

    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

    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.

    DATA TRANSMISSION METHOD AND SYSTEM IN TIME-SENSITIVE NETWORK

    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

    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.

    Method, apparatus and medium for optimizing allocation of switching resources in polymorphic network

    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

    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.

    Methods and apparatuses for executing tasks, storage mediums, and electronic devices

    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

    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.

    TRAFFIC ALARM METHOD AND APPARATUS BASED ON PROGRAMMABLE SWITCH, DEVICE AND MEDIUM

    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

    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.

    Method and device for estimating position of networked vehicle based on independent non-uniform increment sampling

    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

    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.

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