Abstract: Systems and methods are directed to building annotated models based on eyes-off data. Specifically, a synthetic data generation model is trained and used to further train a target model. The synthetic data generation model is trained within an eyes-off environment using an anonymity technique on confidential data. The synthetic data generation model is then used to create synthetic data that closely represents the confidential data but without any specific details that can be linked back to the confidential data. The synthetic data is then annotated and used to train the target model within an eyes-on environment. Subsequently, the target model is deployed back within the eyes-off environment to classify the confidential data.

Abstract: A system architecture, a battery management system controller, and a vehicle are provided. The system architecture includes a first function trigger, a logical processor and a second function trigger, which are connected in sequence. The first function trigger is used for reading a function value of an external function and outputting the function value to the logical processor. The logical processor is used for executing preset computation logic according to the function value and outputting a first computation result to the second function trigger. The second function trigger is used for writing the first computation result into the external function. When the system architecture is in an offline debugging state, the logical processor is in a separated state in which the logical processor is respectively independent of the first function trigger and the second function trigger.

Abstract: A system controller for a battery management includes a control chip including a processor and an architecture embedded in the control chip. The architecture includes a target unit, a project determination unit, a project unit, and a model-level output signal summary unit. The processor is configured to run on the architecture to perform the battery management. The project determination unit is configured to output a project enable signal corresponding to the target unit. The project unit includes the target unit, and the project enable signal is configured to trigger startup of the target unit to execute a corresponding logic control strategy. The target unit is configured to receive the project enable signal, and output a unit-level output summary signal based on the project enable signal, and the model-level output signal summary unit is configured to receive the unit-level output summary signal, and to output a model-level output summary signal.

Abstract: Systems and methods are directed to building annotated models based on eyes-off data. Specifically, a synthetic data generation model is trained and used to further train a target model. The synthetic data generation model is trained within an eyes-off environment using an anonymity technique on confidential data. The synthetic data generation model is then used to create synthetic data that closely represents the confidential data but without any specific details that can be linked back to the confidential data. The synthetic data is then annotated and used to train the target model within an eyes-on environment. Subsequently, the target model is deployed back within the eyes-off environment to classify the confidential data.

Abstract: Systems and methods are directed to building annotated models based on eyes-off data. Specifically, a synthetic data generation model is trained and used to further train a target model. The synthetic data generation model is trained within an eyes-off environment using an anonymity technique on confidential data. The synthetic data generation model is then used to create synthetic data that closely represents the confidential data but without any specific details that can be linked back to the confidential data. The synthetic data is then annotated and used to train the target model within an eyes-on environment. Subsequently, the target model is deployed back within the eyes-off environment to classify the confidential data.

Abstract: The present application provides an apparatus and a method for measuring apparent permeability of a tight rock core, the apparatus comprises: a rock core holder, a first high-pressure injection pump, a second high-pressure injection pump, a micro-differential pressure meter, a micro-flow meter, a first pressure control unit, a second pressure control unit, a first valve, a second valve, a third valve, and a fourth valve; the first pressure control unit comprises: a first pressure-resistant piston container and a second pressure-resistant piston container, both of which are divided into an upper cavity and a lower cavity by a piston, the upper cavities of the first pressure-resistant piston container and the second pressure-resistant piston container are filled with gases and communicate with each other, and the lower cavity of the first pressure-resistant piston container is filled with pump pressure-transmission liquids, and the lower cavity of the second pressure-resistant piston container is filled with ex

Abstract: A high-temperature, high-pressure, and low-velocity gas microtube viscosity measuring apparatus that comprises a thermotank, a fluid filtering and measuring device, a micro-pressure difference metering device, and a data acquisition and processing system. The fluid filtering and measuring device includes a filter, a microtube connector, a flow rate measuring liquid storage tank, an automatic micro-flow rate metering device, and an intermediate container connected in series via pipelines. The micro-pressure difference metering device is connected at two ends to pipelines at the two ends of the microtube connector via detection pipelines. The data acquisition and processing system is electrically connected to the micro-pressure difference metering device and the automatic micro-flow rate metering device to receive pressure difference data and flow rate data.

Abstract: A high-temperature, high-pressure, and low-velocity gas microtube viscosity measuring apparatus that comprises a thermotank, a fluid filtering and measuring device, a micro-pressure difference metering device, and a data acquisition and processing system. The fluid filtering and measuring device includes a filter, a microtube connector, a flow rate measuring liquid storage tank, an automatic micro-flow rate metering device, and an intermediate container connected in series via pipelines. The micro-pressure difference metering device is connected at two ends to pipelines at the two ends of the microtube connector via detection pipelines. The data acquisition and processing system is electrically connected to the micro-pressure difference metering device and the automatic micro-flow rate metering device to receive pressure difference data and flow rate data.

Abstract: The present application provides an apparatus and a method for measuring apparent permeability of a tight rock core, the apparatus comprises: a rock core holder, a first high-pressure injection pump, a second high-pressure injection pump, a micro-differential pressure meter, a micro-flow meter, a first pressure control unit, a second pressure control unit, a first valve, a second valve, a third valve, and a fourth valve; the first pressure control unit comprises: a first pressure-resistant piston container and a second pressure-resistant piston container, both of which are divided into an upper cavity and a lower cavity by a piston, the upper cavities of the first pressure-resistant piston container and the second pressure-resistant piston container are filled with gases and communicate with each other, and the lower cavity of the first pressure-resistant piston container is filled with pump pressure-transmission liquids, and the lower cavity of the second pressure-resistant piston container is filled with ex

Abstract: A high pressure dynamic micro differential pressure gauge, and methods for using and checking the same. The high pressure dynamic micro differential pressure gauge comprises a set of vertical manometer tubes in communication with each other, where one or more manometer tubes are connected to a resistance meter through signal lines, and the resistance meter is connected to a data collection and processing control system. Each manometer tube is full of low conductivity buffer liquid and high conductivity manometric liquid. The resistance meter is configured to measure resistances in the one or more manometer tubes, and the data collection and processing control system is configured to convert the resistances measured by the resistance meter into a differential pressure.

Abstract: A high pressure dynamic micro differential pressure gauge, and methods for using and checking the same. The high pressure dynamic micro differential pressure gauge comprises a set of vertical manometer tubes in communication with each other, where one or more manometer tubes are connected to a resistance meter through signal lines, and the resistance meter is connected to a data collection and processing control system. Each manometer tube is full of low conductivity buffer liquid and high conductivity manometric liquid. The resistance meter is configured to measure resistances in the one or more manometer tubes, and the data collection and processing control system is configured to convert the resistances measured by the resistance meter into a differential pressure.