Abstract: The disclosure provides a method for processing data, and an electronic device. The method includes: obtaining first attribute information of input data and second attribute information of a computing device corresponding to the input data; selecting a target operator implementation mode from a plurality of candidate operator implementation modes based on the first attribute information and the second attribute information; determining a plurality of sub-operators included in an operator required for the input data from an operator library based on the target operator implementation mode, to generate the operator; and obtaining an operation result by performing an operation on the input data by the computing device based on the operator.

Abstract: An information management method, a device, a system and a medium. The information management method applied to a first terminal, including: sending an information acquisition request to a server, so that the server responds to the information acquisition request and sends visitor information to the first terminal; receiving the visitor information sent by the server; generating card information according to the visitor information; and sending the card information to an electronic card, so that the electronic card displays the card information.

Abstract: The disclosure provides an apparatus for high throughput analysis of samples and a method of making an assay card and performing an assay using the apparatus. The apparatus can include a transporter to position and advance a first plate of the QMAX card, a first dispenser to deposit a sample on the first plate, a second dispenser to dispense a reagent to contact the sample, a press to compress the sample between the first and second plates of the QMAX card into a uniformly thick layer, and an imager to image the uniformly thick layer.

Abstract: The invention provides a D-psicose crystal and a preparation method thereof. The method comprises: adding a seed crystal to a D-psicose solution and stirring uniformly, subjecting the solution to crystallization by gradient cooling and constant-temperature crystallization alternately at 50-30° C., stopping the crystallization until the temperature of the solution is 30° C., separating the crystal by centrifugation, washing and drying, to obtain a D-psicose crystal. Rather than evaporative crystallization, organic solvent-assisted crystallization and ultrasonication, controllable crystallization by gradient cooling, constant-temperature crystallization, and other technical means are employed. Thus, the invention has low requirements for equipment, simple process, low energy consumption, and low preparation cost, and thus particularly suitable for large-scale industrial production and processing. The purity of the D-psicose crystal obtained is ?98.

Abstract: Disclosed are a low-cost high-efficiency drip irrigation system for a cotton field and a use method thereof. The drip irrigation system for a cotton field includes a filtering device and a water supply device; wherein the filtering device adopts different types of single filtering devices or combined filtering devices according to different water source types; the water supply device includes multiple stages of main pipes, submain pipes and laterals; the laterals (a drip irrigation tape with labyrinth on one side or a drip irrigation tape inlaid with emitters inside) are laid on the surface of the ground and located below a mulch film. The drip irrigation system adopts the design of large flow (1.5-3.4 L/h), slightly larger pipe diameter (>75 mm), low water pressure (operating pressure of drip irrigation tape being 0.03-0.07 MPa) and suitable drip irrigation uniformity (80%-90%).

Abstract: A method for predicting a size range of a lost circulation channel based on deep learning (DL) is provided. The method includes the following steps: S1: acquiring data of the lost circulation channel, and establishing a prediction dataset of the size range of the lost circulation channel; S2: preprocessing the prediction dataset of the size range of the lost circulation channel, and determining the size range of the lost circulation channel; S3: establishing a prediction model for the size range of the lost circulation channel; and S4: optimizing the prediction model for the size range of the lost circulation channel, and predicting the size range of the lost circulation channel. The method overcomes the shortcomings of conventional methods, for example, the prediction value of the size of the downhole lost circulation channel is single, inaccurate and not real-time.

Abstract: A electronic device includes: a body, a light-emitting component, a photosensitive component, and a processor, wherein the light-emitting component, the photosensitive component, and the processor are all disposed in the body, and the photosensitive component is connected to the processor; the light-emitting component is configured to emit probe light; the photosensitive component is configured to acquire optical information about reflected light of the probe light in response to receiving the reflected light; and the processor is configured to determine a movement trajectory of the light-emitting component based on the optical information.

Abstract: Embodiments of the present disclosure disclose a method for processing tasks in parallel, a device and a storage medium, and relate to a field of artificial intelligent technologies. The method includes: determining at least one parallel computing graph of a target task; determining a parallel computing graph and an operator scheduling scheme based on a hardware execution cost of each operator task of each of the at least one parallel computing graph in a cluster, in which the cluster includes a plurality of nodes for executing the plurality of operator tasks, and each parallel computing graph corresponds to at least one operator scheduling scheme; and scheduling and executing the plurality of operator tasks of the determined parallel computing graph in the cluster based on the determined parallel computing graph and the determined operator scheduling scheme.

Abstract: Disclosed are a dual-motor multi-gear hybrid transmission system and a vehicle. The dual-motor multi-gear hybrid transmission system includes an engine, a first motor, a second motor, a first clutch, a second clutch, a first planet row, a second planet row, a first input shaft, a second input shaft, a third input shaft and a brake assembly. The first input shaft is connected to the engine through the first clutch. The second input shaft is connected to the engine through the second clutch, and the second input shaft is sleeved outside the first input shaft. The first motor is connected to the engine. The second motor is connected to the first planet row through the third input shaft. The brake assembly is configured to brake the first planet row and/or the second planet row.

Abstract: Embodiments of the present disclosure relates to an electronic device, a vision-based operation method and system for a robot. The electronic device includes at least one processing unit; and a memory coupled to the at least one processing unit and storing computer program instructions therein, the instructions, when executed by the at least one processing unit, causing the electronic device to perform acts including: obtaining an image containing a tool of a robot and an object to be operated by the tool, the image being captured by a camera with a parameter, obtaining a command for operating the tool, the command generated based on the image; and controlling the robot based on the command and the parameter. Embodiments of the present disclosure can greatly improve the accuracy, efficiency and safety of an operation of a robot.

Abstract: A data transmission method includes an access node sends first traffic to a first core network device in a core network through a first service plane of a bearer network. The access node sends second traffic to a second core network device in the core network through a second service plane of the bearer network. The first service plane and second service plane are independent all-active service planes in the bearer network. Service data sent by the base station is split on the access node, and split data each corresponds to one transmission path. Even if one transmission path is completely interrupted, the service data may still be transmitted by another core network device through the other transmission path.

Abstract: The present application relates to a method for robot control. The method includes: obtaining at least one parameter associated with a robot to be controlled by a controller; determining a first identity of the robot based on the at least one parameter; comparing the first identity with a pre-stored second identity; and in response to the first identity matching the second identity, controlling operations of the robot with the controller. The present application further discloses detection of a mismatch between the controller and the robot in an easy, safe and convenient way.

Abstract: A resistance spot welding electrode cap contains a groove at the center of the welding contact interface. During welding, because of the groove, the area of contact between the electrode cap and a metal workpiece to be soldered is reduced. In the initial stage, the overall heat generation is concentrated on the outer ring of the weld point and heat dissipation becomes slower, helping a weld nugget to form from the outside to the inside. Due to the presence of the groove, the metal workpiece expands toward the groove at the center of the electrode, thereby increasing the size of the weld nugget and reducing splash and deformation. In comparison with conventional electrode caps, the welding current required to form weld points of the same size is lower, saving on electricity costs, and weld points obtained using the same current have higher strength and stability with fewer welding defects.

Abstract: A high-temperature disaster forecast method based on a directed graph neural network is provided, and the method includes the following steps: S1, performing standardization processing on meteorological elements respectively to scale the meteorological elements into a same value range; S2, taking the meteorological elements as nodes in the graph, and describing relationships among the nodes by an adjacency matrix of graph; then learning node information by a stepwise learning strategy and continuously updating a state of the adjacency matrix; S3, training the directed graph neural network model after determining a loss function, obtaining a model satisfying requirements by adjusting a learning rate, an optimizer and regularization parameters as a forecast model, and saving the forecast model; and S4, inputting historical multivariable time series into the forecast model, changing an output stride according to demands, and thereby obtaining high-temperature disaster forecast for a future period of time.

Abstract: The present disclosure provides a meteorological big data fusion method based on deep learning, including the following steps: constructing multi-source meteorological data samples; according to an original resolution of different climate variables, selecting a corresponding super-resolution multiple to obtain an optimized super-resolution module under the constraint of maximizing information retention efficiency; constructing a spatial-temporal attention module using a focused attention mechanism, and selecting a corresponding time stride according to periodic characteristics of different climate variables; constructing a meteorological data fusion model in combination with the optimized super-resolution model and the spatial-temporal attention module; taking a minimum resolution of climate variables as a loss function, and training the meteorological data fusion model with the multi-source meteorological data samples; and importing the acquired real-time meteorological data from multiple data sources into t

Abstract: A blank material for a ceramic tile consists of the following components in percentage by weight: nepheline powder: 10%-15%; clay with a carbon content of ?3.0 wt %: 10%-15%; clay with a carbon content of ?0.5 wt %: 15%-22%; clay with a carbon content between 0.5 wt % and 3.0 wt %: 10%-15%; recycled waste blank: 5%-10%; sodium potassium powder: 5%-10%; sodium feldspar powder: 12%-20%; desulfurization residue: 0%-7%; waste from edging and polishing: 15%-26%; waste porcelain powder: 5%-10%; liquid gel remover: 0.3%-1.0%; liquid reinforcing agent: 0.2%-0.8%. Its preparation method comprises the following steps: preparing raw materials for a blank body and ball milling, powder spray granulation, aging, pressing and molding of the blank body, drying, polishing the blank body, spraying water, glazing, applying a decorative pattern, firing.

Abstract: A high-temperature disaster forecast method based on a directed graph neural network is provided, and the method includes the following steps: S1, performing standardization processing on meteorological elements respectively to scale the meteorological elements into a same value range; S2, taking the meteorological elements as nodes in the graph, and describing relationships among the nodes by an adjacency matrix of graph; then learning node information by a stepwise learning strategy and continuously updating a state of the adjacency matrix; S3, training the directed graph neural network model after determining a loss function, obtaining a model satisfying requirements by adjusting a learning rate, an optimizer and regularization parameters as a forecast model, and saving the forecast model; and S4, inputting historical multivariable time series into the forecast model, changing an output stride according to demands, and thereby obtaining high-temperature disaster forecast for a future period of time.

Abstract: The present disclosure provides a meteorological big data fusion method based on deep learning, including the following steps: constructing multi-source meteorological data samples; according to an original resolution of different climate variables, selecting a corresponding super-resolution multiple to obtain an optimized super-resolution module under the constraint of maximizing information retention efficiency; constructing a spatial-temporal attention module using a focused attention mechanism, and selecting a corresponding time stride according to periodic characteristics of different climate variables; constructing a meteorological data fusion model in combination with the optimized super-resolution model and the spatial-temporal attention module; taking a minimum resolution of climate variables as a loss function, and training the meteorological data fusion model with the multi-source meteorological data samples; and importing the acquired real-time meteorological data from multiple data sources into t

Abstract: An evaluation method for evaluating a precipitation-induced landslide disaster loss under climate change is provided. The evaluation method belongs to the technical field of geological disaster prevention and treatment. The evaluation method uses a physical process based model, in considering of spatial heterogeneity of land-surface features of grids in the area, to obtain precipitation thresholds corresponding to the respective grids in the area having the spatial heterogeneity. Historical data and climate model data are taken in combination to select suitable climate models, and the model then is used to simulate landslide prone zones and possible influence zones caused by landslides. An influence zones simulated by the evaluation method can better match disaster loss grid data, which can solve the problem that climate change scenarios and influence of landslide are difficult to be evaluated in landslide disaster evaluation.

Abstract: An evaluation method for evaluating a precipitation-induced landslide disaster loss under climate change is provided. The evaluation method belongs to the technical field of geological disaster prevention and treatment. The evaluation method uses a physical process based model, in considering of spatial heterogeneity of land-surface features of grids in the area, to obtain precipitation thresholds corresponding to the respective grids in the area having the spatial heterogeneity. Historical data and climate model data are taken in combination to select suitable climate models, and the model then is used to simulate landslide prone zones and possible influence zones caused by landslides. An influence zones simulated by the evaluation method can better match disaster loss grid data, which can solve the problem that climate change scenarios and influence of landslide are difficult to be evaluated in landslide disaster evaluation.