Abstract: A semantic segmentation method and system for a high-resolution remote sensing image based on random blocks. In the semantic segmentation method, the high-resolution remote sensing image is divided into random blocks, and semantic segmentation is performed for each individual random block separately, thus avoiding overflow of GPU memory during semantic segmentation of the high-resolution remote sensing image. In addition, feature data in random blocks neighboring each random block incorporated into the process of semantic segmentation, overcoming the technical shortcoming that the existing segmentation method for the remote sensing image weakens the correlation within the image. Moreover, in the semantic segmentation method, semantic segmentation is separately performed on mono-spectral feature data in each band of the high-resolution remote sensing image, thus enhancing the accuracy of sematic segmentation of the high-resolution remote sensing image.

Abstract: Disclosed is system and method of connection information regularization, graph feature extraction and graph classification based on adjacency matrix. By concentrating the connection information elements in the adjacency matrix into a specific diagonal region of the adjacency matrix in order to reduce the non-connection information elements in advance. The subgraph structure of the graph is further extracted along the diagonal direction using the filter matrix. Then a stacked convolutional neural network is used to extract a larger subgraph structure. On the one hand, it greatly reduces the amount of computation and complexity, solving the limitations of the computational complexity and the limitations of window size. And on the other hand, it can capture large subgraph structure through a small window, as well as deep features from the implicit correlation structures at both vertex and edge level, which improves the accuracy and speed of the graph classification.

Abstract: A method and system of graph feature extraction and graph classification based on adjacency matrix is provided. The invention first concentrates the connection information elements in the adjacency matrix into a specific diagonal region of the adjacency matrix which reduces the non-connection information elements in advance. Then the subgraph structure of the graph is further extracted along the diagonal direction using the filter matrix. Further, it uses a stacked convolutional neural network to extract a larger subgraph structure. On one hand, it greatly reduces the amount of computation and complexity, getting rid of the limitations caused by computational complexity and window size. On the other hand, it can capture large subgraph structure through a small window, as well as deep features from the implicit correlation structures at both vertex and edge level, which improves speed and accuracy of graph classification.

Abstract: Provided is a computer-based latent ability model construction method, a parameter calculation method for characteristic parameters of work ability, and a labor force assessment apparatus based on the latent ability model. The method constructs a latent ability model, and introduces characteristic parameters of work ability into the latent ability model to reveal the internal relations among the employee, the activity, and the service time. The characteristic parameters of work ability is calculated to obtain a final value, and labor force assessment can be carried out according to the final value. The labor force assessment comprises performance prediction, work ability comparison, and employee-activity matching evaluation.

Abstract: A method for semantic service registration and query based on WordNet is disclosed. The method includes the following steps: (1) semantic service registration: a service provider registers a service and uploads the Web Service Description Language (WSDL) document corresponding to the service, and a system parses the WSDL document to form a service description tree, then constructs a WordNet ontology tree according to the input of the service, performs a semantic annotation on the input/output of the service to form a Web Service Semantic Description Document (WSDL-S), and finally stores it in a register library; (2) semantic service discovery: a service requester inputs the information of service type, semantic information of the service input/output and other user-defined information to the register library to retrieve the services meeting the requirements; and (3) similarity sorting: the services meeting a certain threshold are sorted in descending order.

Abstract: The present invention provides a workflow management system and a method for implementing a workflow definition tool. The workflow management system comprises a computer, and a workflow definition tool and a workflow engine in the computer, wherein: the workflow definition tool directly represents a process as process definition codes which are computer executable, and the workflow engine directly calls the process definition codes. When the workflow changes, the system of the present invention will only need to correspondingly modify the workflow definition tool instead of modifying the codes of the workflow engine, thus the development, maintenance and use of the workflow management system are facilitated.

Abstract: A method for semantic service registration and query based on WordNet is disclosed. The method includes the following steps: (1) semantic service registration: a service provider registers a service and uploads the Web Service Description Language (WSDL) document corresponding to the service, and a system parses the WSDL document to form a service description tree, then constructs a WordNet ontology tree according to the input of the service, performs a semantic annotation on the input/output of the service to form a Web Service Semantic Description Document (WSDL-S), and finally stores it in a register library; (2) semantic service discovery: a service requester inputs the information of service type, semantic information of the service input/output and other user-defined information to the register library to retrieve the services meeting the requirements; and (3) similarity sorting: the services meeting a certain threshold are sorted in descending order.