Abstract: A monitoring system based on a digital converter station includes a first monitoring terminal deployed at a first-level monitoring side, a second monitoring terminal deployed at a second-level monitoring side, and a third monitoring terminal deployed at a third-level monitoring side; the monitoring terminal at each level includes a communication module, a human-machine interaction module, a device status monitoring module, a device alarm management module, a video fusion processing module, and a data transmission adjustment and control module.

Abstract: This application relates to the field of battery technologies, and provides a battery module, a battery pack, and an automobile. The battery module includes two or more battery cells; a module frame, including an end plate and a side plate. The end plate and the side plate form the module frame for fixing the two or more battery cells and a cell management unit is disposed on the end plate and connected to a sampling line of the two or more battery cells. The cell management unit is disposed on the end plate inside the module frame, which facilitates wiring of the sampling line of the battery cells, thus ensuring an effective energy density of the battery module and balancing the wiring of the sampling line of the battery cells and the energy density of the battery module.

Abstract: A method of wireless communication includes receiving, at a first communication node, information that includes one or more parameters indicating a time-domain characteristic of one or more interfered symbols due to a remote interference between the first communication node and a second communication node. The method also includes performing, by the first communication node, subsequent communications based on the information.

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.