SURVEILLANCE DEVICE, LEARNING DEVICE, SURVEILLANCE METHOD AND STORAGE MEDIUM

    公开(公告)号:US20210248385A1

    公开(公告)日:2021-08-12

    申请号:US17052957

    申请日:2019-05-07

    Abstract: A surveillance device according to the present invention includes: a memory; and at least one processor coupled to the memory. The processor performs operations. The operations includes: calculating, based on a value of a parameter that is contained in a received data frame and represents a state of an apparatus, a change in the state of the apparatus; and determining whether the change is included in an allowable range determined in accordance with the state of the apparatus before the change.

    EXTRACTION DEVICE, EXTRACTION METHOD, RECORDING MEDIUM, AND DETECTION DEVICE

    公开(公告)号:US20210141895A1

    公开(公告)日:2021-05-13

    申请号:US17042622

    申请日:2018-04-27

    Abstract: An extraction device includes: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: sort each set of frames that have the same identifier associated with a node, into frames maintaining a cycle and frames out of the cycle; and extract, as an event rule, a feature of a bit change in a data field related to an event occurrence, from the frames that have the same identifier and are out of the cycle.

    INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM

    公开(公告)号:US20210026343A1

    公开(公告)日:2021-01-28

    申请号:US16982623

    申请日:2018-03-30

    Abstract: An information processing device includes: an acquisition unit that acquires a communication packet used for monitoring and controlling a system and process data collected from an apparatus installed in the system via a network; and a detection unit that detects an abnormal communication pattern on the network based on a correspondence between a communication pattern related to the communication packet and the process data.

    COMMUNICATION ROUTE SETTING METHOD

    公开(公告)号:US20250096889A1

    公开(公告)日:2025-03-20

    申请号:US18727379

    申请日:2022-01-26

    Abstract: A communication route setting device 100 of the present invention includes an optical signal acquisition unit 121 that acquires an optical signal on a transmission path in a network in which optical communication devices are connected to each other via an optical transmission path, a condition determination unit 122 that determines a physical condition of at least one object of the optical transmission path and the optical communication devices on the basis of the optical signal, and a route setting unit 123 that sets a communication route for transmitting the optical signal on the network on the basis of the determined physical condition.

    LEARNING METHOD
    9.
    发明公开
    LEARNING METHOD 审中-公开

    公开(公告)号:US20240281712A1

    公开(公告)日:2024-08-22

    申请号:US18566795

    申请日:2021-06-07

    CPC classification number: G06N20/00

    Abstract: A learning device 100 according to this invention includes: a classification unit 121 configured to classify measurement value data measuring performance of an object on the basis of situation data each representing a situation of the object when the measurement value data are measured; a selection unit 122 configured to select the measurement value data from each of the classifications according to the number of the measurement value data for each of the classifications; and a learning unit 123 configured to perform machine learning on the basis of the selected measurement value data.

    STATE ESTIMATION DEVICE, STATE ESTIMATION METHOD, AND PROGRAM RECORDING MEDIUM

    公开(公告)号:US20240044764A1

    公开(公告)日:2024-02-08

    申请号:US18267423

    申请日:2021-03-24

    Inventor: Takashi KONASHI

    CPC classification number: G01N15/02

    Abstract: A state estimation device includes an acquisition unit, an extraction unit, an estimation unit, and an output unit. The acquisition unit acquires first time series data pertaining to a generation environment of the targeted chemical substance. The extraction unit extracts a feature amount of the first time series data. The extraction unit extracts a feature amount of the first time series data. The estimation unit estimates, based on the feature amount of the first time series data, the state of the targeted chemical substance by using an estimation model trained, through machine learning, on the relationship between the state of the targeted chemical substance in the generation process and a feature amount of second time series data pertaining to the generation environment. The output unit outputs the estimated state.

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