Abstract: Embodiments of the present disclosure provide a generating method of data, a processing method of data, an executing method of data and device thereof. A user can create required structured data by means of a terminal device, even if the user does not understand the working principle of an Internet-of-Things device and an instruction code. The terminal device can convert execution sequence data into structured data that can be executed by the Internet-of-Things device and provide the structured data for the Internet-of-Things device, so that the Internet-of-Things device can directly execute a corresponding operation according to a state control instruction in the structured data, thereby improving the structured data custom extension capability of the Internet-of-Things device while meeting user requirements.

Abstract: A test method based on a test system for five-dimensional space effects of ground surface settlement caused by dual-mode shield construction is provided. First, manufacturing a formation similarity material model; then, laying ground surface monitoring points in longitudinal and transverse direction; installing a shield machine model, and performing shield construction, the shield machine model adopts a double-shield body mode; performing five-dimensional monitoring during shield construction; designing an observation method for ground surface settlement data in step length and time dimension, and acquiring five-dimensional data in combination with three-dimensional scanning; and finally, performing deformation information processing according to the monitored data, so as to realize an acquisition of the five-dimensional data.

Abstract: A precision calibration method of attitude measuring systems is provided. The precision calibration method of attitude measuring systems includes the following steps: calibrating a zero-deviation, a scale coefficient, and a non-orthogonal angle between axes of an accelerometer to the attitude measuring system via an ellipsoid fitting model (S1); compensating original data of the accelerometer using a calculated ellipsoid parameter (S2); calibrating an electronic compass via the ellipsoid fitting model according to compensated accelerometer data (S3); compensating original electronic compass data by the calculated ellipsoid parameter (S4); calculating an attitude according to the compensated data of the accelerometer and compensated data of the electronic compass (S5). The above steps of the method have a reliable calibration result and a high precision with a less time consumption of calibration.

Abstract: A method for automatically synchronizing multi-source heterogeneous data resources utilizes a metadata service node, a service node and a production node, wherein the metadata service node stores a data dictionary of a distributed heterogeneous database system, the service node parses user requests of the distributed heterogeneous database system, for regularly synchronizing data with the production node; and the production node provides requests such as querying and updating of a relevant production application system; wherein the service node includes a configuration analyzer, a log parser and a synchronous update device; the configuration analyzer analyzes source database configurations on the production node, and selects an applicable synchronization method; the log parser parses logs of different database systems, which is a preparatory component of incremental synchronization; the synchronous update device recognizes the synchronization method according to the configuration analyzer for data synchroniza

Abstract: A precision calibration method of attitude measuring systems is provided. The precision calibration method of attitude measuring systems includes the following steps: calibrating a zero-deviation, a scale coefficient, and a non-orthogonal angle between axes of an accelerometer to the attitude measuring system via an ellipsoid fitting model (S1); compensating original data of the accelerometer using a calculated ellipsoid parameter (S2); calibrating an electronic compass via the ellipsoid fitting model according to compensated accelerometer data (S3); compensating original electronic compass data by the calculated ellipsoid parameter (S4); calculating an attitude according to the compensated data of the accelerometer and compensated data of the electronic compass (S5). The above steps of the method have a reliable calibration result and a high precision with a less time consumption of calibration.

Abstract: The present invention relates to a technical field of information retrieval, and more particularly to a clustering method for multilingual documents, comprising steps of: step 1: establishing a similar words bank comprising multilingual words; step 2: extracting eight eigenvalues; step 3: calculating a similarity of any two documents i and j; step 4: selecting accumulation points from a set of the documents to establish a cluster; step 5: adding residual documents which are not selected in the set to the cluster; and step 6: disposing the cluster in a circular ring structure. The method of the present invention without limiting categories of languages in the documents, the accumulation points are selected according to judgments of similarity to establish clusters and classify multilingual documents in the clusters. The method of the present invention is suitable for clustering multilingual documents.

Abstract: A virtualization method for large-scale distributed heterogeneous data includes using a three-layer structure and a two-level mapping. According to different abstraction degrees, a data model is defined as three layers from low to high: a physical layer, a virtual table layer, and a virtual view layer. Each layer has a proprietary data model. The two-level mapping comprises a PV mapping and a VV mapping, which is a transformation mechanism of the data models of different layers. As a result, the virtualization method virtualizes decentralized heterogeneous data, and is applicable to data interoperability treatments.

Abstract: Saving database storage space includes receiving, using a processor, one or more properties associated with a newly released commodity input at a front-end server; determining whether the one or more properties of the newly released commodity match a standard property unit (SPU), wherein the SPU includes a plurality of properties common to at least two commodities of which data is stored at a back-end server; and in the event that the one or more properties of the newly released commodity match the SPU, storing data associated with binding the newly released commodity with the matching SPU at the back-end server.

Abstract: A virtualization method for large-scale distributed heterogeneous data includes using a three-layer structure and a two-level mapping. According to different abstraction degrees, a data model is defined as three layers from low to high: a physical layer, a virtual table layer, and a virtual view layer. Each layer has a proprietary data model. The two-level mapping comprises a PV mapping and a VV mapping, which is a transformation mechanism of the data models of different layers. As a result, the virtualization method virtualizes decentralized heterogeneous data, and is applicable to data interoperability treatments.

Abstract: Providing object information on the Internet includes configuring a plurality of front-end categories for a plurality of network objects and a plurality of screening conditions for screening the plurality of network objects, where each of the plurality of screening conditions uniquely corresponding to a respective one of the plurality of the front-end categories. Providing object information further includes receiving object information pertaining to a network object, the object information including a screening condition for the network object; storing the object information in a back-end category, determining a front-end category to which the network object belongs, according to the screening condition and storing correlation information of the object and the front-end category, wherein the back-end category is separate from and different than the front-end category.

Abstract: A data storage and query method supporting an agile development and horizontal scaling, in a field of computer applications, includes steps of: transforming data into a 2-tuple (Key, MiniTable) and identifying any MiniTable (having a data set removed) with a unique Key, wherein the MiniTable includes multiple data columns; a structure of each data column is limited by a pre-defined mode; and the data columns are sorted according to a primary key defined by the mode. The data storage and query method obtains a capability of the horizontal scaling via removing dependency among the data sets, and a capability of the agile development via supporting an analogous SQL grammar by saving dependency among the data within the data sets. The data storage and query method can be applied to a data management system which supports the horizontal scaling of big data and the agile development of short development lifecycles.

Abstract: A computer account management system includes: an account management subsystem; an information asset management subsystem; an authentication (integrated) subsystem; a service (integrated) subsystem; and an account portal subsystem; wherein the account management subsystem manages information of physical accounts and logical account numbers; wherein the information asset management subsystem manages data information resources generated by network activities of physical account information; wherein the authentication subsystem provides an authentication integrated interface to the physical account numbers; wherein the service subsystem is a customizable interface which is open to internet or local network; wherein the account portal provides interfaces and tools of login, service list management of services subscribed or bought by the account, account information management and information asset management.

Abstract: Providing object information on the Internet includes configuring a plurality of front-end categories for a plurality of network objects and a plurality of screening conditions for screening the plurality of network objects, where each of the plurality of screening conditions uniquely corresponding to a respective one of the plurality of the front-end categories. Providing object information further includes receiving object information pertaining to a network object, the object information including a screening condition for the network object; storing the object information in a back-end category, determining a front-end category to which the network object belongs, according to the screening condition and storing correlation information of the object and the front-end category, wherein the back-end category is separate from and different than the front-end category.

Abstract: A virtual table index mechanism and a method for a multi-attribute compound condition query relate to a field of computer application technology. The virtual table index mechanism for a multi-attribute compound condition query includes: an index manager; a condition analyzer; and a pre-execution engine. The present invention forms index key values corresponding to a plurality of attributes in a virtual table. When querying, a query condition for the virtual table is calculated. Referring to a key value index, whether a mapping physical table of the virtual table should be executed is independently pre judged according to the attributes, so as to ensure that query is applied only to a virtual sub-table satisfying a corresponding key value condition. The present invention is effective for multi-attribute compound condition query, and is suitable for indexing virtual tables.

Abstract: Providing object information on the Internet includes configuring a plurality of front-end categories for a plurality of network objects and a plurality of screening conditions for screening the plurality of network objects, where each of the plurality of screening conditions uniquely corresponding to a respective one of the plurality of the front-end categories. Providing object information further includes receiving object information pertaining to a network object, the object information including a screening condition for the network object; storing the object information in a back-end category, determining a front-end category to which the network object belongs, according to the screening condition and storing correlation information of the object and the front-end category, wherein the back-end category is separate from and different than the front-end category.

Abstract: Saving database storage space includes receiving, using a processor, one or more properties associated with a newly released commodity input at a front-end server; determining whether the one or more properties of the newly released commodity match a standard property unit (SPU), wherein the SPU includes a plurality of properties common to at least two commodities of which data is stored at a back-end server; and in the event that the one or more properties of the newly released commodity match the SPU, storing data associated with binding the newly released commodity with the matching SPU at the back-end server.

Abstract: The present invention relates to a field of computer application technology, and more particularly to a computer account management system and a realizing method thereof.

Abstract: A data storage and query method supporting an agile development and horizontal scaling, in a field of computer applications, includes steps of: transforming data into a 2-tuple (Key, MiniTable) and identifying any MiniTable (having a data set removed) with a unique Key, wherein the MiniTable includes multiple data columns; a structure of each data column is limited by a pre-defined mode; and the data columns are sorted according to a primary key defined by the mode. The data storage and query method obtains a capability of the horizontal scaling via removing dependency among the data sets, and a capability of the agile development via supporting an analogous SQL grammar by saving dependency among the data within the data sets. The data storage and query method can be applied to a data management system which supports the horizontal scaling of big data and the agile development of short development lifecycles.

Abstract: Saving database storage space includes receiving, using a processor, one or more properties associated with a newly released commodity input at a front-end server; determining whether the one or more properties of the newly released commodity match a standard property unit (SPU), wherein the SPU includes a plurality of properties common to at least two commodities of which data is stored at a back-end server; and in the event that the one or more properties of the newly released commodity match the SPU, storing data associated with binding the newly released commodity with the matching SPU at the back-end server.

Abstract: Saving database storage space includes receiving, using a processor, one or more properties associated with a newly released commodity input at a front-end server; determining whether the one or more properties of the newly released commodity match a standard property unit (SPU), wherein the SPU includes a plurality of properties common to at least two commodities of which data is stored at a back-end server; and in the event that the one or more properties of the newly released commodity match the SPU, storing data associated with binding the newly released commodity with the matching SPU at the back-end server.