Abstract: A gas detection purification device is disclosed and includes a main body, a purification unit, a gas guider, a gas detection module and a controlling-driving module. The main body includes an inlet, an outlet, an external socket and a gas-flow channel disposed between the inlet and the outlet. The purification unit is disposed in the gas-flow channel for filtering gas introduced through the gas-flow channel. The gas guider is disposed in the gas channel and located at a side of the purification unit. The gas is inhaled through the inlet, flows through the purification unit and is discharged out through the outlet. The gas detection module is plugged into or detached from the external socket. The controlling driving module is disposed within the main body and electrically connected to the gas guider to control the operation of the gas guider in an enabled state and a disabled state.

Abstract: A blood pressure device includes a first blood pressure measuring device, a second blood pressure measuring device, and a controller. The first blood pressure measuring device is to be worn on a first position of a wrist so as to obtain a first blood pressure information of the first position. The second blood pressure measuring device is to be worn on a second position of the wrist so as to obtain a second blood pressure information of the second position. The controller is electrically coupled to the first blood pressure measuring device and the second blood pressure measuring device so as to adjust tightness between the expanders and the user's skin, respectively. The controller receives, processes, and calculates a pulse transit time between the first blood pressure information and the second blood pressure information, and the controller obtains at least one blood pressure value based on the pulse transit time.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a function call for a function that calculates an attribute associated with a machine learning model. For each argument of the function call, the system identifies a parameter type of the argument, wherein the parameter type represents a type of data used with the machine learning model. The system also obtains a value accessor for retrieving features specific to the parameter type and obtains a value represented by the argument using the value accessor. The system then calculates the attribute by applying the function to the value and uses the attribute to execute the machine learning model.

Abstract: The disclosed embodiments provide a system for performing online hyperparameter tuning in distributed machine learning. During operation, the system uses input data for a first set of versions of a statistical model for a set of entities to calculate a batch of performance metrics for the first set of versions. Next, the system applies an optimization technique to the batch to produce updates to a set of hyperparameters for the statistical model. The system then uses the updates to modulate the execution of a second set of versions of the statistical model for the set of entities. When a new entity is added to the set of entities, the system updates the set of hyperparameters with a new dimension for the new entity.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a hierarchical representation containing a set of namespaces of a set of features shared by a set of statistical models. Next, the system uses the hierarchical representation to obtain, from one or more execution environments, a subset of the features for use in calculating the derived feature. The system then applies a formula from the hierarchical representation to the subset of the features to produce the derived feature. Finally, the system provides the derived feature for use by one or more of the statistical models.

Abstract: A basket includes a metal board which is deformed to form four sidewalls. A metal netted plate is connected to respective bottom ends of the four sidewalls to form a substantial cylindrical basket. A space is defined between the four sidewalls and the metal netted plate, and the size of the space is gradually enlarged from the bottom of the basket toward the top of the basket. The basket has four rounded corners and each rounded corner has a non-continuous portion. Each sidewall has an outward folded portion formed on the top end thereof. Multiple clips are connected to the underside of the metal netted plate.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a function call for a function that calculates an attribute associated with a machine learning model. For each argument of the function call, the system identifies a parameter type of the argument, wherein the parameter type represents a type of data used with the machine learning model. The system also obtains a value accessor for retrieving features specific to the parameter type and obtains a value represented by the argument using the value accessor. The system then calculates the attribute by applying the function to the value and uses the attribute to execute the machine learning model.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a feature dependency graph of features for a machine learning model and an operator dependency graph comprising operators to be applied to the features. Next, the system generates feature values of the features according to an evaluation order associated with the operator dependency graph and feature dependencies from the feature dependency graph. During evaluation of an operator in the evaluation order, the system updates a list of calculated features with one or more features that have been calculated for use with the operator. During evaluation of a subsequent operator in the evaluation order, the system uses the list of calculated features to omit recalculation of the feature(s) for use with the subsequent operator.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a model definition and a training configuration for a machine-learning model, wherein the training configuration includes a set of required features, a training technique, and a scoring function. Next, the system uses the model definition and the training configuration to load the machine-learning model and the set of required features into a training pipeline without requiring a user to manually identify the set of required features. The system then uses the training pipeline and the training configuration to update a set of parameters for the machine-learning model. Finally, the system stores mappings containing the updated set of parameters and the set of required features in a representation of the machine-learning model.

Abstract: The disclosed embodiments provide a system for performing online hyperparameter tuning in distributed machine learning. During operation, the system uses input data for a first set of versions of a statistical model for a set of entities to calculate a batch of performance metrics for the first set of versions. Next, the system applies an optimization technique to the batch to produce updates to a set of hyperparameters for the statistical model. The system then uses the updates to modulate the execution of a second set of versions of the statistical model for the set of entities. When a new entity is added to the set of entities, the system updates the set of hyperparameters with a new dimension for the new entity.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a hierarchical representation containing a set of namespaces of a set of features shared by a set of statistical models. Next, the system uses the hierarchical representation to obtain, from one or more execution environments, a subset of the features for use in calculating the derived feature. The system then applies a formula from the hierarchical representation to the subset of the features to produce the derived feature. Finally, the system provides the derived feature for use by one or more of the statistical models.

Abstract: An electronic component is disclosed, the electronic component comprising: a conductive structure, comprising a plurality of conductive layers separated by a plurality of insulating layers, wherein the plurality of conductive layers and the plurality of insulating layers are stacked in a vertical direction, wherein the plurality of conductive layers forms at least one coil, wherein each of the coil is formed along the vertical direction across said plurality of conductive layers, wherein the plurality of insulating layers are not supported by a substrate.

Abstract: An actuator capable of providing movement forces in a first direction, a second direction, and a third direction is provided. The actuator includes two sets of repelling permanent magnets and yokes, a focusing coil, a tracking coil, and a tilting coil. The repelling and attractive fields generated by the permanent magnets enable the coils to generate independent movements in three axial directions. The two sets of permanent magnets are placed in a repelling position, with a small space between the two magnets to generate a field whose magnetic forces repel and attract within the surrounding range. The focusing, tilting and tracking coils are engaged with the lens holder whose movements in the first, second and third directions are determined by the amplitude and direction of the electric current in the focusing, tilting and tracking coils respectively.

Abstract: A method of communication between a protocol-processing unit and an input/output (I/O) device through a device interface controller includes configuring the protocol-processing unit to write command/message data in a predefined write file, and configuring the device interface controller to translate the command/message data written in the predefined write file into a corresponding command/message and to transmit the corresponding command/message thus translated to the I/O device. A system that includes the protocol-processing unit and the device interface controller is also disclosed.

Abstract: A modular storage assembly includes a plurality of connectors and a plurality of panels joined together by the plurality of connectors as to define a compartment. Each of the plurality of connectors includes a body having a plurality of first slots and a plurality of second slots. Two blocks are releasably mounted in one of the plurality of the second slots of the two connectors respectively. A door is pivotally connected with two blocks as to close the opening of the compartment and whereby the door is releasably mounted to the modular storage assembly.

Abstract: An actuator capable of providing movement forces in a first direction, a second direction, and a third direction is provided. The actuator includes two sets of repelling permanent magnets and yokes, a focusing coil, a tracking coil, and a tilting coil. The repelling and attractive fields generated by the permanent magnets provide the coils to generate independent movements in three axial directions. The two sets of permanent magnets are placed in a repelling position, with a small space between the two magnets to generate a field whose magnetic forces repel and attract within the surrounding range. The focusing coil is engaged to a lens holder. The amplitude and the direction of the electric current in the focusing coil determine the movement of the lens holder in the first direction. The tilting coil is engaged to the lens holder. The amplitude and the direction of the electric current in the focusing coil determine the movement of the lens holder in the second direction.