Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: The present disclosure provides a method, an apparatus, and a system for health management. The method includes: receiving, from a graphical interface of a first user terminal, login information of a first user account, the first user terminal having a memory, a processor, and a measurement sensor; obtaining, by the first user terminal, physiological data of a user based on a measurement value detected by the measurement sensor; storing the physiological data into a medical record corresponding to the first user account; and sending, by the first user terminal via a server, the physiological data to a second user terminal associated with the first user account remotely.

Abstract: An intelligent terminal remote controller-based internet-of-things control system and control method are disclosed. The control system includes at least two household electrical appliance hosts (1) and an intelligent terminal (2), remote controller software is included in the intelligent terminal (2) and in communication with a model database (9) of the intelligent terminal (2), the model database (9) is configured to store model number information and information of all functions of various household electrical appliance hosts to be controlled, the household electrical appliance host (1) includes an MCU control chip (7) storing model number information of a current household electrical appliance host, and a control system unit (5). The present invention allows invoking a back-end database through software and making recognition and judgment among control subjects, so as to solve the problem that the remote-control functions are different for different electrical appliances of different models.

Abstract: An intelligent terminal remote controller-based internet-of-things control system and control method are disclosed. The control system includes at least two household electrical appliance hosts (1) and an intelligent terminal (2), remote controller software is included in the intelligent terminal (2) and communicated with a model database (9) of the intelligent terminal (2), the model database (9) is configured to store model number information and information of all functions of various household electrical appliance hosts to be controlled, the household electrical appliance host (1) includes an MCU control chip (7) storing model number information of a current household electrical appliance host, and a control system unit (5). The present invention allows invoking a back-end database through software and making recognition and judgment among control subjects, so as to solve the problem that the remote-control functions are different for different electrical appliances of different models.

Abstract: The present disclosure provides a method, an apparatus, and a system for health management. The method includes: receiving, from a graphical interface of a first user terminal, login information of a first user account, the first user terminal having a memory, a processor, and a measurement sensor; obtaining, by the first user terminal, physiological data of a user based on a measurement value detected by the measurement sensor; storing the physiological data into a medical record corresponding to the first user account; and sending, by the first user terminal via a server, the physiological data to a second user terminal associated with the first user account remotely.

Abstract: The present invention discloses a multi-sensor merging based super-close distance autonomous navigation apparatus and method. The apparatus includes a sensor subsystem, an information merging subsystem, a sensor scanning structure, and an orientation guiding structure, wherein a visible light imaging sensor and an infrared imaging sensor are combined together, and data are acquired by combining a passive measurement mode composed of an optical imaging sensor and an active measurement mode composed of a laser distance measuring sensor.

Abstract: The present invention discloses a multi-sensor merging based super-close distance autonomous navigation apparatus and method. The apparatus includes a sensor subsystem, an information merging subsystem, a sensor scanning structure, and an orientation guiding structure, wherein a visible light imaging sensor and an infrared imaging sensor are combined together, and data are acquired by combining a passive measurement mode composed of an optical imaging sensor and an active measurement mode composed of a laser distance measuring sensor.

Abstract: A method for extracting motion parameters from angiography images using a multi-parameter model.

Abstract: A method for separating and estimating multiple motion parameters in an X-ray angiogram image. The method includes: determining a cardiac motion signal cycle and a variation frame sequence of translational motion according to an angiogram image sequence, tracing structure feature points of vessels in the angiogram image sequence whereby obtaining a motion sequence, processing the motion sequence via multivariable optimization and Fourier frequency-domain filtering, separating an optimum translational motion curve, a cardiac motion curve, a respiratory motion curve and a high-frequency motion curve according to the variation frame sequence of translational motion, a cycle of the cardiac motion signal, a range of a respiratory motion signal cycle, and a range of a high-frequency motion signal cycle.

Abstract: A method for separating and estimating multiple motion parameters in an X-ray angiogram image. The method includes: determining a cardiac motion signal cycle and a variation frame sequence of translational motion according to an angiogram image sequence, tracing structure feature points of vessels in the angiogram image sequence whereby obtaining a motion sequence, processing the motion sequence via multivariable optimization and Fourier frequency-domain filtering, separating an optimum translational motion curve, a cardiac motion curve, a respiratory motion curve and a high-frequency motion curve according to the variation frame sequence of translational motion, a cycle of the cardiac motion signal, a range of a respiratory motion signal cycle, and a range of a high-frequency motion signal cycle.