472 results about "Storage model" patented technology

A multidimensional storage model includes a set of non-sparse entries for each of a plurality of dimensions. The non-sparse entries each identify an associated data value. A set of interdimensional links is provided for each non-sparse entry. The interdimensional links each identify an intersection between non-sparse entries in disparate dimensions and collectively identify all intersections between non-sparse entries in the dimensions.

A method of indexing data in a multidimensional database includes creating a multidimensional logical access model, creating a multidimensional data storage model in which data is located in cells that are stored and retrieved in blocks, gathering data access information derived from one or more user queries of the database, and reorganizing one or more selected cells in the multidimensional data storage model based on the data access information to reduce the time taken to access the one or more selected cells in response to a user query of the database. A computerized apparatus in communication with a multidimensional database includes a program to perform the method. A computer readable medium contains instructions to cause a computer to perform the method.

The invention provides a data storage method, device and system based on a blockchain. The data storage system based on the blockchain comprises a transaction server which is used for performing a transaction according to an intelligent contract and a consensus mechanism and obtaining blockchain data; a database server routing and configuration unit which is used for dynamically configuring and routing a database server and obtaining a target database server, wherein the target database server is used for storing the blockchain data; a storage model calling unit which is used for calling a corresponding database access protocol from a uniform database drive interface of various database protocols and calling a corresponding storage model from a target database; and the database server which is used for storing the blockchain data to a database in the storage model and/or a data table.

The present invention aims to provide a data processing device that provides a result of categorization that is satisfactory to a user, even when user data includes an object specific to the user. The data processing device stores therein model data pieces each indicating detection counts of feature amounts; judges, for each target data piece, whether the target data piece is a non-categorization data piece including an uncategorizable object, using the model data pieces and the detection count of each of at least two feature amounts detected in the target data piece; when, as a result of the judgment, two or more of the target data pieces are judged to be non-categorization data pieces, specifies at least two feature amounts that are each included, and detected the same number of times, in a predetermined number or more of the non-categorization data pieces, and newly creates a model data piece based on the at least two feature amounts that have been specified, using a class creation method, and stores the model data piece into the storage unit.

Techniques for determining intra-model dependencies for a model and persistently storing the determined dependency information. The dependency information for a model may be stored in file associated with the model.

Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in training of a machine learning model according to the user interaction, the machine learning model configured to determine a prediction, classification or clustering of a result of a first search query by utilizing a result of at least a second search query as input to the machine learning model.

Information is stored in a data structure as an item element and an association element. The item comprises a content attribute. The association comprises a count attribute and a sign attribute, and represents a relationship between two items. The data structure itself is an occurrence of a storage model that conforms to axioms of information that define characteristics common to all forms of information. The elements of the data structure can be added, deleted and/or edited and such modifications of the data structure are validated before being applied. Explicit and implicit constraints are also enforced during modification. An item can represent a factual or an expectational object. Informational processes may be executed to generate real objects from corresponding expectational objects. An association element has a directionality representing the creation sequence of the items it associates. Output from the data structure is generated in response to a query.

The invention provides an image identification method based on depth learning and transfer learning. The image identification method based on depth learning and transfer learning includes the following steps: 1) a preparation step: reading a pre-training model, reading an image directory, and dividing a training set, a verification set and a test set; 2) a training step: constructing a full connection neural network classifier, taking the image set as input of the pre-training model, and using the output of the pre-training model to update the full connection neural network classifier; and 3) a storage step: storing the model result. The image identification method based on depth learning and transfer learning has the advantages of integrating with the application of depth learning and transfer learning so as to provide a relatively accurate bladder cancer diagnosis result for a user, on the basis of the extremely limited training time and training sample quantity.

The invention discloses an information sharing and safe multi-party computing protocol based on a block chain, mainly solves the problem that the existing secure multi-party computation is easy to cause the user to be unable to control the data independently that is easy to get the data by the third party. The technical solutions are as follows: 1) constructing the storage model, and storing the index table information on the chain and the database under the chain in the way. 2) constructing a data sharing model,wherein users can access their data by authorizing a third party or revoke their privileges at any time. 3) using the consensus mechanism of the block chain to ensure the consistency among nodes; 4) Based on the correctness of nodes, using MapReduce programming model, the model isdivided into two phases: Map and Reduce, and the master node assigns the tasks of Map and Reduce to the nodes; 5) Map node uses the improved homomorphic encryption algorithm for encryption calculation; 6) Reduce node integrates the encrypted data to output data files.

An advertising display kiosk device of various configurations in size and application that passively and proactively dispense advertising to target subjects in the immediate local environment of the display device. An apparatus, process and method for acquiring sensory information from the local environment and processing the information in a AI computer program to determine a likely match to a set of stored models. The AI selects ads or responses to the set of stored models. Relevant ads are matched by the AI Program for the purpose of displaying relevant informational ads, notifying emergency services, or connection to two way capable data streams via network connections. These devices can also act to connect to (PSTN) or other communication networks.

A three-dimensional model data producing processing apparatus produces three-dimensional model data using design data (CAD data) of an object to be recognized. The three-dimensional model data producing processing includes processing conversion processing, edit processing, and teaching processing. The conversion processing and the edit processing are performed to the design data on a computer. The teaching processing is performed in a practical environment. It is not necessary to image a workpiece model in the three-dimensional model data producing processing.

An information processing device includes: an object module determining unit for determining of a learning model having a time series pattern storage model for storing a time series pattern as a module which is the minimum component, a maximum likelihood module having the maximum likelihood, or a new module to be an object module that is a module having a model parameter of the storage model to be updated; and an updating unit for updating the model parameter of the object module using learned data to be used for learning that is the time series of an observed value; with the object module determining unit using the learned data to determine the maximum likelihood module or the new module to be the object module based on the posterior probability of the learning model in the case that learning of the maximum likelihood module or the new module has been performed.

The invention discloses a multi-copy storage method and a multi-copy storage system for a distributed database system, and belongs to the field of computer software. The multi-copy storage system comprises a main Master node, a standby Master node, a plurality of storage nodes and a connection network. The multi-copy storage method includes steps of 1, storing data in different data pieces; 2, only allowing a user to operate the data in a primary version, and enabling the multi-copy storage system to synchronize change of the data to various copies in real time and guarantee the atomicity; 3, enabling the multi-copy storage system to detect survival conditions of the nodes via synchronous heartbeat detection, and enabling a main Master host to instantly select an available copy to replace the primary version when a certain storage node of the data in the primary version dies; 4, enabling the multi-copy storage system to carry out detection and repair operation for the storage copies regularly, and migrating the data pieces with excessively low quantities of copies to other available storage nodes by means of local storage migration. A main storage model and a standby storage model are adopted for each data piece, and the copies are of completely identical logical structures and are distributed on different physical storage nodes. The multi-copy storage method and the multi-copy storage system have the advantages that the integrity and the availability of the data are protected against the death of optional nodes of the system.

The invention discloses a hierarchic scheduling method for service and resources in a cloud computation environment, which comprises the stages of submitting a user request, partitioning task units, defining a computation model, defining a storage model, defining a service analysis process, a service scheduling process and a resource scheduling process, evaluating the scheduling and the like, specially comprises the steps: defining and applying a mathematic model of a service combination file into the cloud environment; firstly analyzing the service combination file so as to determine the service priority; and classifying tasks by utilizing a resource pool, executing service through operation characteristics by using a proper resource allocation method, wherein the scheduling method considers data locality and related service completion rate. Observing from simulation experiments, according to the hierarchic scheduling method, the resource utilization rate can be improved, and a higher service completion rate can be realized compared with the default FIFO (First-In First-Out) scheduling of Hadoop. According to the method provided by the invention, the requirements of users and service providers can be met through high-efficiency scheduling and the reallocation of priority.

A model edit control system controls editing of a data model. A model repository manager allows multiple users to copy a stored model stored in a repository for executing changes on multiple model copies in parallel. An action log manager crates a model action log for the stored model and tracks actions executed on the stored model. The action log manager also creates a current action log for each model copy to record actions executed on the model copy. A model merger manager merges the model copies into the stored model in the repository, by playing the actions in the current action log against the stored model in the repository.

A system and method of determining a model default swap spread for a firm which includes the following steps: (i) determining a calibration group of the firm, wherein the calibration group comprises other firms having a region, a sector and a coarse quality related to the firm; (ii) setting firm leverage variables through combining observable data with a value of at least one model parameter; (iii) calibrating variables based on the calibration group; (iv) calculating the model default swap spread based on at least one of calibration variables; and (v) storing the model default swap spread.

The invention discloses a multi-source heterogeneous spatial data flow method based on an Oracle database. The method comprises the steps of receiving a data request; determining a database node to be accessed through a spatial data index according to the request; reading multi-source heterogeneous data, and conducting spatial data model transformation according to a spatial data conversion module; conducting simple pretreatment on the conversed data; storing the data or storing the data after processing the data. According to the multi-source heterogeneous spatial data flow method based on the Oracle database, mature relational database spatial data storage and spatial database engine technologies are combined, and by building an integrative vector and raster data storage model, optimizing a spatial data retrieval mechanism and integrating spatial data which is distributed and stored in each spatial database, and the data flow of the heterogeneous spatial data is achieved. An Oracle database data driving engine NMSDE is developed based on the multi-source heterogeneous spatial data flow method, and the tests show that both the storage efficiency and inquiring efficiency of the Oracle database data driving engine NMSDE are superior to ArcSDE.