Abstract: The disclosure provides a full-color light emitting device and a display module. A light emitting layer, a refractive layer, a spacer layer and a light processing layer are included. The refractive layer is disposed above the light emitting layer, the spacer layer is disposed above the refractive layer, and the light processing layer is disposed above the spacer layer. The light emitting layer includes a first light emitting part, a second light emitting part and a third light emitting part. The light processing layer includes a first light processing part, a second light processing part, and a third light processing part, and a baffle wall is disposed between any two adjacent light processing parts in the first light processing part, the second light processing part and the third light processing part. A light refractive index of the refractive layer is greater than a light refractive index of the spacer layer.

Abstract: Provided is a data processing system for a heterogeneous architecture, including, a job decomposing component, configured to decompose a to-be-completed job into a series of tasks executed by an execution subject in the heterogeneous architecture; a task topology generating component, configured to generate a task relationship topology based on an inherent relationship between the decomposed tasks during the job decomposition, where a task node of the task topology includes all node attributes required to execute a corresponding task; an execution subject creating component, configured to create a corresponding execution subject for each task in a computing resource based on the task relationship topology; and an execution subject network component, configured to include one or more data processing paths including various created execution subjects, and fragment actual job data into task data when receiving the actual job data.

Abstract: The present disclosure relates to a method of evaluating effective green water resources based on dynamic crop coefficients and a device thereof. The method includes constructing a SWAT model of an area to be measured; constructing a mathematical relation expression of vegetation potential transpiration, and introducing dynamic crop coefficients into the SWAT model; evaluating results obtained by operating the SWAT model according to the measured evaporation data and leaf area index monitoring data obtained in advance, and calibrating crop growth parameters and evapotranspiration parameters; judging evaporation effectiveness according to a land cover type and a dynamic coverage calculation method, and carrying out daily simulation to obtain a total amount of effective green water resources in the area to be measured.

Abstract: The present disclosure provides a logical node distributed signature decision system for a distributed data processing system, including: an initial logical node generating assembly, configured to receive task configuration data input by a user, and generate an initial logical node topology for the distributed data processing system, wherein a source logical node has a specified logical distributed signature, each initial logical node is attached with a candidate logical distributed signature set based on the task configuration data; and a logical distributed signature selecting assembly, configured to, according to a distributed descriptor of an output end of each upstream logical node for which a logical distributed signature is already determined, for each candidate logical distributed signature of a current logical node, compute a cost of data transmission required to transform the distributed descriptor of the tensor of the output end of each upstream logical node into the distributed descriptor.

Abstract: The present disclosure provides a parallel decision system and method for distributed data processing. The system includes: an initial logical node generation assembly, a logical node traversal assembly, a predetermined configuration cost computation assembly, and a parallel decision assembly. The initial logical node generation assembly is configured to receive task configuration data input by a user to generate an initial logical node topology for the distributed data processing system. The logical node traversal assembly is configured to traverse the initial logical node topology to obtain a predetermined configuration in the initial logical node topology. The predetermined configuration cost computation assembly is configured to compute a transmission cost of each predetermined configuration and a cost sum.

Abstract: The present disclosure provides a parallel decision system and method for distributed data processing. The system includes: an initial logical node generation assembly, a logical node traversal assembly, a predetermined configuration cost computation assembly, and a parallel decision assembly. The initial logical node generation assembly is configured to receive task configuration data input by a user to generate an initial logical node topology for the distributed data processing system. The logical node traversal assembly is configured to traverse the initial logical node topology to obtain a predetermined configuration in the initial logical node topology. The predetermined configuration cost computation assembly is configured to compute a transmission cost of each predetermined configuration and a cost sum.

Abstract: The present disclosure provides a logical node distributed signature decision system for a distributed data processing system, including: an initial logical node generating assembly, configured to receive task configuration data input by a user, and generate an initial logical node topology for the distributed data processing system, wherein a source logical node has a specified logical distributed signature, each initial logical node is attached with a candidate logical distributed signature set based on the task configuration data; and a logical distributed signature selecting assembly, configured to, according to a distributed descriptor of an output end of each upstream logical node for which a logical distributed signature is already determined, for each candidate logical distributed signature of a current logical node, compute a cost of data transmission required to transform the distributed descriptor of the tensor of the output end of each upstream logical node into the distributed descriptor.

Abstract: Provided is a data actor, which is in data communication with direct upstream actor and/or downstream actor. The data actor includes a message bin, a finite state machine, a processing component and an output data cache. The message bin is configured to receive a message from the upstream actor and/or the downstream actor; the finite state machine is configured to change a current state of the actor based on the received message in the message bin and an operation of the processing component; when a state of the finite state machine reaches a trigger condition, the processing component directly reads output data in a readable state in an output data cache of the upstream actor and executes a predetermined operation, and then stores result data subsequent to execution of the predetermined operation in an output data cache of the data actor.

Abstract: Provided is a data processing system for a heterogeneous architecture, including, a job decomposing component, configured to decompose a to-be-completed job into a series of tasks executed by an execution subject in the heterogeneous architecture; a task topology generating component, configured to generate a task relationship topology based on an inherent relationship between the decomposed tasks during the job decomposition, where a task node of the task topology includes all node attributes required to execute a corresponding task; an execution subject creating component, configured to create a corresponding execution subject for each task in a computing resource based on the task relationship topology; and an execution subject network component, configured to include one or more data processing paths including various created execution subjects, and fragment actual job data into task data when receiving the actual job data.

Abstract: In implementations of the subject matter described herein, each token for containing an element in the training data is sampled according to a factorization strategy in training. Instead of using a single proposal, the property value of the target element located at the token being scanned is iteratively updated one or more times based on a combination of an element proposal and a context proposal. The element proposal tends to accept a value that is popular for the target element independently of the current piece of data, while the context proposal tends to accept whenever the property value that is popular in the context of the target data or popular for the element itself. The proposed modeling training approach can converge in a quite efficient way.

Abstract: In implementations of the subject matter described herein, each token for containing an element in the training data is sampled according to a factorization strategy in training. Instead of using a single proposal, the property value of the target element located at the token being scanned is iteratively updated one or more times based on a combination of an element proposal and a context proposal. The element proposal tends to accept a value that is popular for the target element independently of the current piece of data, while the context proposal tends to accept whenever the property value that is popular in the context of the target data or popular for the element itself. The proposed modeling training approach can converge in a quite efficient way.