75 results about "Complex data type" patented technology

This invention is directed to relational extenders for a computer-based relational database. Each relational extender includes at least one column, in a first, business table containing a user defined application database, dedicated to object handles for defining the complex data type of an object; a second, attribute, table containing at least one column defining a unique characteristic associated with the one object and one column dedicated to containing the object handle; and a third, metadata, table containing at least one column defining a common characteristic associated with all objects defined within the business table and one column dedicated to containing the object handles and at least one column dedicated to containing a reference to object data associated with the object. The relational extender further includes a fourth table containing a reference to each object handle column defined in the first table, and a fifth table containing the names of the second and third tables for each object defined in the first table.

A data processing system having a main processor and a coprocessor. The main processor responsds to coprocessor instructions within its instruction stream by issuing the coprocessor instructions upon a coprocessor bus and detecting if the coprocessor accepts them by returning an accept signal. The coprocessor instructions include a coprocessor number and the coprocessor checks this number to see if it matches its own number(s) to determine whether or not it should accept the coprocessor instruction. A data type field within the coprocessor number in the coprocessor instruction also serves to specify one of multiple data types to be used in the coprocessor operation; particular coprocessors can interpret this part of the coprocessor number to determine data type. If the coprocessor supports multiple data types, then it has multiple coprocessor numbers for which it will issue accept signals and then uses the data type field to control the data type used. If a coprocessor does not support a particular data type then it will not issue an accept signal for coprocessor instructions that specify that data type. The main processor can then use emulation code to provide support for that coprocessor instruction.

Methods, systems, and computer program products for programmatically serializing complex objects (such as JavaBeans(TM)). In contrast to prior art techniques, a manually-specified data type mapping specification is not required as input to the serialization process. Instead, the present invention programmatically generates this type mapping, responsive to encountering run-time exceptions during the serialization process. The serialization process is therefore "self-healing". This approach is especially advantageous when serializing complex objects that may include complex data types and / or embedded objects. The programmatically-generated type mapping information is preferably used to generate a serialized version of the complex object, and can also be used during deserialization. In addition to improving serialization techniques, this type mapping information facilitates dynamic integration and transformation of data between heterogeneous formats.

A framework for extending the capabilities of an event processing system using one or more plug-in components referred to herein as data cartridges. In one set of embodiments, the data cartridge framework described herein can enable an event processing system to support one or more extension languages that are distinct from the native event processing language supported by the system. For example, certain “extension language” data cartridges can be provided that enable an event processing system to support complex data types and associated methods / operations that are common in object-oriented languages, but are not common in event processing languages. In these embodiments, an event processing system can access an extension language data cartridge to compile and execute queries that are written using a combination of the system's native event processing language and the extension language.

Conceptual Process Redactor (CPR) is a method and system, for describing and translating conceptual descriptions of objects and their methods to OOPS object layouts and methods. CPR utilizes conceptual structures (C-structures or CPR classes), to describe information. C-structures are hierarchical information structures, and each hierarchical path is considered as a CPR data type. Thus, instead describing data in terms of OOPS data types, which are bound to storage layouts of the underlying machines, CPR describes data in terms of CPR data types, which may be regarded as concepts. The CPR translator, translates the CPR data types to their Oops equivalents by making use of Type Translation library, supplied with the CPR class description. CPR data types are unique within the class they are defined, and hence serve to identify the field as well describe a data type. Thus, a typical usage like Part quantity field of sales order header is now a data type in its own right, as well as a field. The uniqueness of the CPR data types is made use of in identifying the parameters of a method, if the context in which the method is invoked in known a priori. The CPR system provides a mechanism, called collaboration, to conceptualize process descriptions. As per collaboration, a group of objects may collaborate to accomplish a particular task (method). The collaboration serves as a context, and hence method invocations in CPR may omit the parameters, and these are identified from the collaboration. Each object acts as a client and the rest of the objects and temporary variables, act as servers. The client / server relationship is made use of by process descriptions called CPR Interface groups, which are specified for each of the collaboration objects, participating in the collaboration. In addition, to the intra object client / server relationship, objects are broadly classified as data sources or data containers, where the first form is considered as a sequential representation of data, and the latter form is considered as a random representation of data. Each data source may be grouped with zero or more data containers, and each such group is called a collaboration group. One or more collaboration groups may be specified in a table called the collaboration table, and collaboration groups with sequential group numbers are considered as a logical unit of execution. Thus, collaboration groups and the associated client / server relationship between the objects in the collaboration groups, may be used to conceptualize fairly complex method descriptions. The CPR translator will translate the process descriptions specified as CPR Interface groups for the collaboration objects into oops methods. The CPR runtime system provides necessary support to access / update the collaboration objects, and to invoke the oops methods generated during translation.

The invention provides a data storing, managing and inquiring method and system for a distributed key-value storage system. The method comprises the following steps: before storing data, respectively converting data into ordered character strings according to different data classifications and then storing the ordered character strings into the distributed key-value storage system, wherein storage sequences of the converted character strings sequenced according a dictionary sequence are consistent with numerical value sequences before conversion; and during data retrieval, the same conversion is carried out on the numerical values in retrieval conditions. The method provided by the invention supports storage and retrieval of complex data classifications and includes complex data inquiring methods, such as multi-field attribute inquiring, multi-data classification inquiring, numerical value statistic analysis and the like.

The invention discloses a complex audio segmentation clustering method based on a bottleneck feature. The method comprises the steps that a deep neural network with a bottleneck layer is constructed; a complex audio stream is read, and endpoint detection is carried out on the complex audio stream; the audio feature of a non-silent segment is extracted and input into the deep neural network; the bottleneck feature is extracted from the bottleneck layer of the deep neural network; the bottleneck feature is used as input, and an audio segmentation method based on the Bayesian information criterion is used, so that each audio segment contains only one kind of audio type and adjacent audio segments have different audio types; a spectral clustering algorithm is used to cluster segmented audio segments to acquire the number of audio types of complex audios; and the audio segments of the same audio type are merged together. According to the invention, the used bottleneck feature is a deep transform feature, can more effectively describe the feature difference of the complex audio type than a traditional audio feature, and acquires an excellent effect in complex audio segmentation clustering.

A memory system is provided for storing multiple data types. The memory system includes a main memory, a local cache, and a translation unit. The local cache has multiple entries, each of which includes a data field to store data and a status field to indicate a storage state for the stored data. The translation unit includes a translation lookaside buffer (TLB) and a status-cache (STC). The TLB stores address translations for data in the main memory, and the STC stores storage states for data indicated by the address translations.

A method, apparatus, article of manufacture, and a memory structure for providing access to abstract data types using an index providing a tuple. The method comprises the steps of accepting a database query; generating an index predicate from the database query; and determining a tuple from an index using the index predicate. The tuple is associated with an abstract or complex data type responsive to the database query. A data stream is initialized with the index predicate; and the tuple is returned in the data stream. The apparatus comprises means for performing the above method steps, and the article of manufacture comprises a medium tangibly embodying computer instructions for performing these method steps.

A computer-implemented method and an apparatus for use in a computing programming environment are disclosed. The method includes: receiving a plurality of user inputs, each user input specifying an action in a workflow; identifying a data type incompatibility between two of the specified actions; and generating a script for executing the actions in the workflow responsive to the user inputs, the script including code for performing a action for converting one of the two identified, incompatible data types to the second. The apparatus, in a first aspect, includes a program storage medium encoded with instructions that, when executed by a computing device, performs the method. In a second aspect, the apparatus includes a computing apparatus programmed to perform the method.

A method and apparatus for efficiently storing multiple data types in a computer's register or data file. A single data file can store data with a variety of sizes and number formats, including integers, fractions, and mixed numbers. The register file is partitioned into fields, such that only the relevant portions of the register file are read or written.

An apparatus, system, and method are disclosed for updating database indexes on complex data types. Instead of deleting all the index keys for an old indexable entity, only the old index keys which are not in the set of new index keys associated with a replacement indexable entity will be deleted. In addition, only new index keys which are not in the set of old index keys are inserted into the index. In this manner, performance is greatly improved by elimination unnecessary deletions and insertions to an index.

A data protocol permitting a source computer to initiate execution of an execution process on a destination computer uses XML data in which different complex data types correspond to different execution processes to be triggered. Parameter data to be used by the associated execution processes may be embedded within the corresponding complex data types.

An iron and steel enterprise information integration platform based on a common information model (CIM) model belongs to the field of information system integration and comprises a heterogeneous system discrete data integration layer, a common object model layer, an enterprise application data service layer and an application layer. The heterogeneous system discrete data integration layer designs corresponding collectors according to different data types and communication methods, discretizes complicated data types in various data sources into data labels, achieves uniformed data organization, storage and expression in a labeling mode, and achieves fusion of heterogeneous data. The common object model layer establishes iron and steel process common object information models. The enterprise application data service layer provides a data communication interface based on the models based on the CIM model. The application layer achieves functions of all application modules based on the CIM module through invoking enterprise application data service layer interfaces. The iron and steel enterprise information integration platform based on CIM model has the advantages of achieving integration and modeling organization of iron and steel enterprise discrete information and providing an integral information integration method for enterprises.

The invention provides Web service client automation generation method and device, wherein the Web service client automation generation method comprises the following steps of: receiving a web services description language (WSDL) document of a Web service; analyzing the basic information and the complex data type parameter of the WSDL document to obtain a simple data type object and a complex data type object; generating a simple type data interface and a complex type data interface which are respectively correspond to the simple data type object and the complex data type object according to the simple data type object and the complex data type object; acquiring data through the simple type data interface and the complex type data interface; detecting whether the data accord with a data structure or not, and if so, generating a simple object access protocol (SOAP) request message used for calling the Web service according to the data; receiving a SOAP response message, and analyzing to obtain a Web service calling result so as to completing the generation of a Web service client. The embodiment of the invention realizes the analysis of complex data types of the WSDL document and is beneficial to generating the automation of the Web service client.

Disclosed is a method of identifying data format information. A regular expression described in schema is matched with data sub-formats. From the matching, a ‘type’ of the regular expression is then identified. More specifically, a regular expression tree is constructed (5001) from the regular expression. At least one sub-format of the data format is then identified, the sub-format comprising at least one constituent part. Each constituent part of each sub-format is represented (5002) with a corresponding Finite State Machine, each Finite State Machine comprising an entry point, an exit point and at least one state. The regular expression tree is then matched (5003, 5004) against the Finite State Machines to identify a matching one of the, sub-formats, the one sub-format thereby representing the data format of the regular expression.

The present invention relates to systems and methods for storing, navigating and retrieving information. In particular, the present invention is concerned with systems and methods for storing data in, for retrieving data from, and for navigating large and / or complex datasets. The systems and methods of the present invention in particular are concerned with the materialization / denormalization of complex data sets comprising a plurality of large, interconnected but distinct data record collections. The materialization / denormalization of such data sets can be performed in a precomputation phase, prior to a browsing / searching operation.

A programmable digital signal processor with a clustered SIMD microarchitecture includes a plurality of accelerator units, a processor core, and a complex computing unit. Each of the accelerator units may perform one or more dedicated functions. The processor core includes an integer execution unit that may execute integer instructions. The complex computing unit may include a complex arithmetic logic unit execution pipeline that may include one or more datapaths configured to execute complex vector instructions, and a vector load unit. In addition, each datapath may include a complex short multiplier accumulator unit that may be configured to multiply a complex data value by values in the set of numbers including {0, + / -1}+ {0, + / -i}. The vector load unit may cause the complex data items to be fetched each clock cycle for use by any datapath in the complex arithmetic logic unit execution pipeline.

The present invention discloses a Bayesian OD matrix estimation method with multiple data types. The method comprises the following steps of: the step 1, obtaining four data types which are a road section flow, a flow of part of paths, a turning flow of an intersection and a road section vehicle travelling speed, performing layering and screening of the four data types, and obtaining relatively independent traffic data on a network; the step 2, respectively calculating likelihood functions corresponding to the road section flow, the flow of part of paths, the turning flow of the intersection and the road section vehicle travelling speed according to the relatively independent traffic data on the network obtained in the step S1, and obtaining a posterior distribution form of Bayesian OD matrix estimation; and the step S3, designing a Markov Chain Monte Carlo sampling method, and solving the posterior distribution form of the Bayesian OD matrix estimation in the step S2. The Bayesian ODmatrix estimation method with multiple data types is helpful for improvement of accuracy and a technology application range of the current OD estimation.

The invention is suitable for data processing and provides a unified classification method for data in multiple types. The method comprises steps that, A, in a metric space, original data sets are converted by utilizing a space model to generate data sets having a unified data type; and B, the data sets are classified according a classification algorithm. Compared with the prior art, in the metric space, only distance information of data in different types is considered, other attributes are not considered, so complex data types are simplified and are easy to operate, moreover, through supporting point space model conversion, data in the different types is converted into data in the unified data type, and thereby a classification algorithm use scope is enlarged to a certain degree.

The present invention relates to a Web-service-based electronic official document circulation automatizing method. The steps are as follows: firstly, an XML structure is defined for defining a document XSD and constructing the complex data type of an electronic official document in XML form; secondly, according to the defined electronic official document complex data type, an electronic official document procedure describing document to be formed is defined with a Web service describing document WSDL; thirdly, a business procedure executing language BPEL is constructed, and the electronic official document procedure describing document is formed; fourthly, the electronic official document complex data type in the first step, the Web service describing document WSDL in the second step and the electronic official document procedure describing document in the third step are all packed and issued to a BPEL procedure executing engine. The present invention realizes the recognizable, resolvable and efficient storage and transmission of the electronic official document, solves the support of the electronic official document automatic circulation to inter-department inter-region heterogeneous system platforms and data bases and is in accordance with the practical official requirement of governmental department.

The scalable high-level fusion of structured and unstructured data includes ingesting and processing unstructured data to produce a statistical model stored as extracted entities then mapped to a collection of resource description framework (RDF) triples, and applying a semantic analysis to a set of structured data to produce a logical model stored as a collection of triples. Reasoners are applied to both models generating an extended knowledge graph of both base and inferred knowledge that is decomposed into a wide table database, with each row storing a corresponding triple, and a reasoner converting the RDF triples into associated triples by adding a new column to the database in response to detecting a new predicate for a subject already present in one of the rows of the database so that the new predicate is stored in the new column in a new row created for the subject already present.

The invention discloses a method for enclosing UOML into API which comprises the following procedures that: the UOML object is mapped into a composite data type of the programming language, the property of the UOML object corresponds to the variables of simple data type or the variables of complex data type in the composite data type, sub-elements of the UOML object correspond to the variables of simple data type or the variables of complex data type in the composite data type; the UOML operation is mapped into an API function prototype of the programming language, the object of the UOML operation corresponds to the parameters of the API function prototype; the operation corresponding to the API function in an API function body of the programming language is converted into the UOML operation according to the defined mappings in the procedures, and the return result of the operation is converted into a return type of the programming language. The API functions of the UOML aiming at different programming languages are realized by the method, thereby, the application developers of different programming languages can directly realize the application on the document library system by calling the corresponding API function, and the developing efficiency is improved.

Systems and methods for extending a directory schema independent of schema modification are described. In one aspect, a directory schema data structure includes a flexible attribute data field. The flexible attribute data field identifies a complex data type. The complex data type is used to express one or more operational or data providing properties of a flexible attribute. The one or more operational or data providing properties are independent of the complex data type and independent of directory schema modification. The directory schema data structure also includes a flexible structural object content class to encapsulate the flexible attribute.

The present invention aims at providing an applied data quality test method, the method is mainly used in testing and comparative analysis for a plurality of business systems, and can be used to check out illegal data appointed in a plurality of business systems of different business rules and correct the illegal data to improve the data quality of each business system. The specific steps are as follows: firstly, the complex data testing and analysis can be abstracted into concrete data testing rules, and a SQL generator which is adapted to different database testings is provided, through the SQL generator, the SQL sentences required by data testing rules can be automatically or manually generated; secondly, during the process of data testing ad comparative analysis, the SQL generator executes a single item, a plurality of items or an automatic testing to the testing rules, the testing is automatically executed to formulate an execution plan for the periodical and timing execution; thirdly, the SQL generator makes various comparative analysis for the tested out result and provides query for the tested out but not corrected data.