Abstract: Provided is a household oxygen generator. The household oxygen generator includes a housing. A compression mechanism, a first air path module and an oxygen generation mechanism which are communicated in sequence are disposed in the housing. The first air path module includes a flow guide pipeline, a movable pipeline and a locking assembly. The movable pipeline is movably connected to the flow guide pipeline. The locking assembly is in transmission connection with the movable pipeline. The flow guide pipeline is connected to the oxygen generation mechanism. The locking assembly has a locking position and an unlocking position. When the locking assembly is in the locking position, the movable pipeline is clamped to or inserted into an air inlet of the oxygen generation mechanism. When the locking assembly is in the unlocking position, the movable pipeline is separated from the air inlet of the oxygen generation mechanism.

Abstract: Provided is a household oxygen generator. The household oxygen generator includes a housing. A compression mechanism, a first air path module and an oxygen generation mechanism which are communicated in sequence are disposed in the housing. The first air path module includes a flow guide pipeline, a movable pipeline and a locking assembly. The movable pipeline is movably connected to the flow guide pipeline. The locking assembly is in transmission connection with the movable pipeline. The flow guide pipeline is connected to the oxygen generation mechanism. The locking assembly has a locking position and an unlocking position. When the locking assembly is in the locking position, the movable pipeline is clamped to or inserted into an air inlet of the oxygen generation mechanism. When the locking assembly is in the unlocking position, the movable pipeline is separated from the air inlet of the oxygen generation mechanism.

Abstract: The present disclosure relates to an auxiliary device and auxiliary method for epidural anesthesia needle placement, the auxiliary device comprising: a needle placement unit (1), a motion guide unit (2) for driving the needle placement unit into movement, and a control unit (3) for supporting and controlling the motion guide unit (2), the needle placement unit (1) being electrically connected to the control unit (3); the needle placement unit (1) comprises: a first support (11) connected to the motion guide unit (2), a second support (12) slidably connected with the first support (11), a needle placement assembly (13) slidably connected with the second support (12), and a first drive (14) arranged on the first support (11) for driving the second support (12) into motion. The scheme of the present disclosure may perform a real-time multidimensional monitoring to the puncture process, achieving autonomous, precise, safe needle placement and puncture operations.

Abstract: The present disclosure relates to a method for determining a target spot path, which is applied to a determining system including a shooting device and a locating device that are separate from each other, and a calibration device connected to the shooting device, the method comprising: S1. obtaining a three-dimensional partial image for an affected part and a virtual path located in the three-dimensional partial image; S2. matching a simulated two-dimensional image obtained based on projection of the three-dimensional partial image with a two-dimensional projection image obtained based on the affected part; S3. determining a surgical guide path on the two-dimensional projection image that corresponds to the virtual path according to position information of the virtual path on the simulated two-dimensional image, when the simulated two-dimensional image and the two-dimensional projection image are matched; and/or S4.

Abstract: Mechanisms are provided for training a computer implemented model. The mechanisms perform multiple instances of training of the computer implemented model, where each instance of training of the computer implemented model comprises training the computer implemented model using a different training data set to generate a different instance of a trained computer implemented model. The mechanisms generate computer implemented model results after each instance of training by executing the corresponding instance of the trained computer implemented model. The mechanisms record differences in the instances of training of the computer implemented model in association with corresponding identifiers of the instances of trained computer implemented model and corresponding computer implemented model results.

Abstract: Mechanisms are provided for training a computer implemented model. The mechanisms perform multiple instances of training of the computer implemented model, where each instance of training of the computer implemented model comprises training the computer implemented model using a different training data set to generate a different instance of a trained computer implemented model. The mechanisms generate computer implemented model results after each instance of training by executing the corresponding instance of the trained computer implemented model. The mechanisms record differences in the instances of training of the computer implemented model in association with corresponding identifiers of the instances of trained computer implemented model and corresponding computer implemented model results.

Abstract: The present disclosure relates to an auxiliary device and auxiliary method for epidural anesthesia needle placement, the auxiliary device comprising: a needle placement unit (1), a motion guide unit (2) for driving the needle placement unit into movement, and a control unit (3) for supporting and controlling the motion guide unit (2), the needle placement unit (1) being electrically connected to the control unit (3); the needle placement unit (1) comprises: a first support (11) connected to the motion guide unit (2), a second support (12) slidably connected with the first support (11), a needle placement assembly (13) slidably connected with the second support (12), and a first drive (14) arranged on the first support (11) for driving the second support (12) into motion. The scheme of the present disclosure may perform a real-time multidimensional monitoring to the puncture process, achieving autonomous, precise, safe needle placement and puncture operations.

Abstract: The present disclosure relates to a method for determining a target spot path, which is applied to a determining system including a shooting device and a locating device that are separate from each other, and a calibration device connected to the shooting device, the method comprising: S1. obtaining a three-dimensional partial image for an affected part and a virtual path located in the three-dimensional partial image; S2. matching a simulated two-dimensional image obtained based on projection of the three-dimensional partial image with a two-dimensional projection image obtained based on the affected part; S3. determining a surgical guide path on the two-dimensional projection image that corresponds to the virtual path according to position information of the virtual path on the simulated two-dimensional image, when the simulated two-dimensional image and the two-dimensional projection image are matched; and/or S4.

Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to configure the processor to implement a cognitive service for cognitive model tuning with rich deep learning knowledge. The mechanism performs a first model training operation and records training data set and hyperparameter information for the model in a. database. The mechanism performs a model testing operation using a testing data set and records metric values that result from the model testing in the database. For a next model training operation for a given model, the mechanism performs an anomalies check for the given model. The mechanism performs a difference comparison on the training data set, hyperparameter information, and the metric values. The mechanism generates a recommendation of a training data set and hyperparameters for the next model training operation. The mechanism performs the next model training operation.

Abstract: Mechanisms are provided for training a computer implemented model. The mechanisms perform multiple instances of training of the computer implemented model, where each instance of training of the computer implemented model comprises training the computer implemented model using a different training data set to generate a different instance of a trained computer implemented model. The mechanisms generate computer implemented model results after each instance of training by executing the corresponding instance of the trained computer implemented model. The mechanisms record differences in the instances of training of the computer implemented model in association with corresponding identifiers of the instances of trained computer implemented model and corresponding computer implemented model results.

Abstract: This application provides an oil refining system and method, including a water circulation system with a chilled water circulation unit including chilled water equipment and a chilled water pipeline, a hot water circulation unit including hot water equipment and a hot water pipeline, and an ambient temperature water circulation unit including an ambient temperature water pipeline. The oil refining system further includes a deacidification system, deodorization system, and a decoloration system to implement a systematization and automation of oil refining.

Abstract: This application provides an oil refining system and method, including a water circulation system with a chilled water circulation unit including chilled water equipment and a chilled water pipeline, a hot water circulation unit including hot water equipment and a hot water pipeline, and an ambient temperature water circulation unit including an ambient temperature water pipeline. The oil refining system further includes a deacidification system, deodorization system, and a decoloration system to implement a systematization and automation of oil refining.