74results about How to "Eliminate redundant data" patented technology

A method for removing redundant data from a backup storage system is presented. In one example, the method may include receiving the application layer data object, selecting a de-duplication domain from a plurality of de-duplication domains based at least in part on a data object characteristic associated with the de-duplication domain, determining that the application layer data object has the characteristic and directing the application layer data object to the de-duplication domain.

A method for removing redundant data from a backup storage system is presented. In one example, the method may include identifying a first back-up data object, identifying a second back-up data object, detecting a first portion of the first back-up data object that is a copy of a second portion of the second back-up data object, and replacing the second portion with a pointer to the first portion.

A vehicle navigation system for use with a traffic information broadcast system which transmits traffic data relating to primary road segments and a communication system which transmits traffic data relating to road segments in a local geographic area. A broadcast receiver receives the broadcast traffic data from the broadcast system and stores the received data. A communication transmitter, when activated, transmits a data request to the communication system. A communication receiver receives the local traffic data from the communication system in response to the data request while a processor displays traffic information on a display screen corresponding to the received broadcast traffic data and the received local traffic data. The local traffic data includes both traffic information relating to local road segments as well as non-traffic temporal events, such as weather, and time-related events which affect traffic flow.

An electronic and transducer device can be attached, adhered, or otherwise embedded into or upon a removable oral appliance or other oral device to form a two-way communication assembly. The device contains a motion sensor to detect external forces imposed on the user such as an explosion, for example. The information is stored for medical treatment, among others. In another embodiment, the device provides an electronic and transducer device that can be attached, adhered, or otherwise embedded into or upon a removable oral appliance or other oral device to form a medical tag containing patient identifiable information. Such an oral appliance may be a custom-made device fabricated from a thermal forming process utilizing a replicate model of a dental structure obtained by conventional dental impression methods. The electronic and transducer assembly may receive incoming sounds either directly or through a receiver to process and amplify the signals and transmit the processed sounds via a vibrating transducer element coupled to a tooth or other bone structure, such as the maxillary, mandibular, or palatine bone structure.

An interface for indicating the presence of inherited values in a document. The interface enables a user to rapidly determine if an audience specific document conforms to the expectations or requirements of an intended audience. The interface distinguishes between current, primary and secondary audience layer values through the use of color or any other mechanism that allows a user to quickly identify data that is missing and needs to be populated, changed or remain unchanged if the inherited data is suitable for the given audience. Using the interface, users can determine at a glance what information is inherited and what level of inheritance that information is from. Before generating an audience specific document targeted at a particular media type, an audience hierarchy may be created and utilized for entry and edit of data for a desired audience.

Audience specific document targeted at a particular media type are generated by accessing data from an audience hierarchy. When obtaining a data value for a particular audience, if that value does not exist for that audience then the audience hierarchy may be utilized to find the data value for an inherited audience. By adding regional, cultural or regulatory subdivisions within the audience hierarchy and inheriting large portions of existing audience specific data entries, a large number of audience specific documents may be generated with a minimal amount of data entry required. Audiences may be specified in a given order for traversal within the hierarchy and displayed in a data entry and editing application utilizing visual characteristics to inform a user if the value for a particular piece of data is inherited from another layer or utilized from the particular layer in use. Audience specific documents may be masked and accessed by payment.

The invention discloses a rough-set-based data fusion method for a wireless multimedia sensor network. The wireless multimedia sensor network can be flexibly deployed in an area of interest of a user to sense richer multimedia information such as audios and videos. However, power is supplied to nodes of the wireless multimedia sensor network by batteries, and the hardware power consumption of the nodes for acquiring and transmitting the multimedia information is far higher than that of the conventional nodes, so that how to save the energy of the nodes to maximally prolong the life cycle of the network becomes one of main difficulties and challenges for the design and the implementation of the wireless multimedia sensor network. For such a problem, the invention provides a rough-set-based data fusion scheme for the wireless multimedia sensor network. According to the scheme, an optimal network topology structure is constructed, cluster head nodes are selected according to certain rules, and a data fusion tree is constructed among the cluster head nodes, so that acquired information can be forwarded along an optimal fusion path to reduce the energy consumption of the nodes in data transmission; and redundancy is eliminated by using an indiscernibility relation of a rough set theory to obtain reduced information, the reduced information is more accurate, and the data volume of the reduced information is greatly reduced compared with a raw data volume, so that the energy of the nodes is further saved, and the life cycle of the whole network is prolonged.

The invention belongs to the field of three-dimensional (3D) video coding technologies and provides a novel multi-view video fractal coding, compressing and decompressing method. According to the method, mass data of a multi-view 3D video is efficiently compressed so as to be stored and transmitted; in a coding process, the time and space combined prediction is realized, and a video compressing method in which quick disparity estimation and center-biased pentagonal motion estimation / prediction are combined with fractal coding is provided, so that the data redundancy is effectively reduced; a five-view video is taken as an example, K, L, C, R and S sequentially represent a video view point respectively, a prediction structure of C to L to K and C to R to S is provided, namely that both the view point R and the view point L are predicted by using the view point C and the view point S and the view point K are respectively predicted by using the view point R and the view point L, and start frames of the five view points are all frames I; and view point decoding sequences are same, and the blocking effect is removed by adopting a loop filter. The method has the advantages that under the conditions that better video decoding quality is obtained, the coding rate and compression ratio are greatly increased, the operational complexity is reduced, and a foundation for real-time application of multi-view video coding is laid.

The invention provides a multi-viewpoint video fractal coding compressing and uncompressing method based on objects and belongs to the technical field of three-dimensional video coding. A large amount of data of a multi-viewpoint three-dimensional video is compressed efficiently to be stored and transmitted. In a coding process, an interested object in a video is obtained through an automatic partition method and compressed and coded through fast disparity estimation and a method of combining pentagon motion estimation forecast and fractal codes, and data redundancy is effectively reduced. A forecast structure K-L-C-R-S specific to a video of five viewpoints of K, L, C, R and S is provided, namely viewpoints R and L are forecasted through a viewpoint C, the viewpoints S and K are forecasted through the viewpoints R and L respectively, and initial frames of the five viewpoints all use I frame. Decoding viewpoint sequences are the same, and loop filtering is used for removing a blocking effect. Under the condition that a good video decoding quality is obtained, coding speed and compression ratio are greatly increased, high flexibility is obtained, and a foundation is laid for real-time application for multi-viewpoint video coding.

The invention relates to a map data storage method, a map data road retrieval method and a vehicle system. The map data storage method comprises the following steps: establishing and storing a cross road set, wherein the cross road set comprises main roads and crossroads formed by the main roads; and establishing and storing a crossroad set, wherein the cross crossing set comprises the crossroads and roads formed by the crossroads. The above technical scheme is convenient for query, and the queried crossroad set includes all the roads formed by the crossroads, so demands of a user are satisfied.

The invention belongs to the technical field of radars, and discloses a radar high-resolution range profile target recognition method based on an iMMFA (infinite max-margin factor analysis) model so as to improve classification performance of the radar and reduce solving complexity of the model. The method comprises steps: radar high-resolution range profiles of M categories of targets; feature extraction is carried out on each radar high-resolution range profile; an iMMFA model is built; an initial value of each parameter of the iMMFA model is set, according to a Gibbs sampling rule, after a preheating process of I0 times of iteration, sampling values of each parameter at T0 times are stored respectively; a final FA model, a final TSB-DPM model and a final LVSVM classifier are determined, and a final iMMFA model is formed; a radar high-resolution range profile of a test target is acquired, and feature extraction is carried out on the radar high-resolution range profile of the test target; and according to a clustering label of a test hidden variable as described in the description, a target category to which the test target belongs is determined.

The invention provides an identified association graph self-optimization mechanism based on deep learning, and the mechanism combines a knowledge graph technology and a deep learning technology, carries out the identification processing of continuously collected data through a deep learning model, and then adds the data to an association graph. Data processing is carried out through a plurality ofdistributed data storage nodes and distributed computing nodes in the association graph, and a series of global iterations are carried out through three parts of local computing, communication unitsand fence synchronization on the basis of a block synchronization parallel computing model. Self-adaptive dynamic optimal allocation of computing resources is realized according to the resource utilization rate, the processing performance and the locality of the data of the system. And carrying out continuous disambiguation analysis and clustering calculation on the data added into the associationgraph to carry out continuous simplification and correction so as to realize continuous self-optimization of the association graph.

Technologies are described herein for providing efficient backup of multiple versions of a data file using data de-duplication. A CDP module copies blocks of data of a specific block size from a current version of the data file to a master file maintained in a backup location for the data file. Only blocks of data not matching a unique data block already in the master file are copied. The CDP module then creates an anterior file in the backup location for the current version of the data file containing an ordered list of references to the unique data blocks in the master file. The order of the list of references is based on the order of occurrence of each unique data block in the modified version of the data file. Finally, the CDP module creates a posterior file in the backup location for the current version of the data file containing any remaining block of data in the data file that is less than the specific block size.

An intelligent computer aided teaching system based on information fusion and machine learning comprises a teaching process information fusion subsystem and a teaching simulation execution subsystem. The teaching process information fusion subsystem is used for conducting multi-dimensional object information extraction for objects, materials and tool elements involved in the teaching process, processing unstructured incomplete data, eliminating coupling noises and relevant redundant data among various index data, and providing metadata support for the teaching simulation execution subsystem. The teaching simulation execution subsystem is used for mining and integrating the metadata uploaded by the teaching process information fusion subsystem, and simulating the execution process involved in the teaching process; and for achieving optimization and dynamic scheduling of the automatic teaching process according to the evaluation of student learning effects and current teaching resource allocation conditions. The invention provides the intelligent computer aided teaching system based on the information fusion and machine learning, which has higher intelligence and good applicability.

One or more embodiments of the invention enable a user to create multiple non-redundant views using metadata targeted at a specific audience that comprises language, regional, regulatory and / or cultural specific values. The word “audience” for the purposes of this specification means a group of document consumers such as people or computers that are associated with a language, country, region, regulation or culture. Audience specific data therefore is data targeted at a specific audience and audience specific metadata is related to the descriptive information related to the data, such as a table name or a field name for example. At least one embodiment of the invention makes use of rule-based inheritance in providing metadata values via layers that comprise audience specific data.

The invention discloses an image classification method based on the direction gradient histogram in combination with a pseudo-reverse learning training stack self-encoder. The method comprises steps that (1), the direction gradient histogram (HOG) is utilized to extract image gradient characteristics, the image directional diagram is calculated, and an HOG operator is utilized to count directionalcharacteristics of some overlapped local regions to acquire HOG characteristics of images. Parameters of different HOG operators are set to acquire several HOG characteristics, and these characteristics are fused into high-dimensional characteristic vectors; (2), the pseudo-inverse learning algorithm is utilized to train a stack self-encoder (PILAE), and the fused high-dimensional characteristicsof the previous step are put into the PILAE to continue learning characteristics; and (3) the characteristics learned in the PILAE are put into a classifier for classification. The two-dimensional information of the images can be extracted by the HOG. The pseudo-reverse learning algorithm is a non-iterative method for training multi-layer feedforward neural networks. The method is advantaged in that the proposed model has the better training time than other models, most hyperparameters are determined by the input data and the network structure, and manual setting is not necessary.

The present invention relates to the information processing technology, and in particular, to a hypernym aggregation method and apparatus, in order to improve the accuracy of hypernym aggregation. Themethod comprises that: a terminal device calculates the word vector similarity between the hypernyms according to the word vectors contained in each hypernym, calculates the entity type similarity between the hypernyms according to the entity types associated with the entities corresponding to each hypernym, and aggregates each hypernym with the word vector similarity reaching the first preset threshold and the entity type similarity reaching the second preset threshold. Thus, according to the technical scheme of the present invention, the short text such as the hypernym can be effectively processed, so that not only text key information contained in the hypernym can be effectively excavated, but also the type characteristics of the hypernym can be accurately described; and at the same time, the complicated workload of the artificial design of the characteristics can be avoided, and the generalization ability of the model can be enhanced, so that the invalid hypernym can be effectively identified, redundant data in the hypernym can be removed, and the accuracy of the hypernym aggregation can be significantly improved.

The invention relates to a hierarchical quantitative measurement service process-to-process distance system, belonging to the field of computer application technology. The system comprises a process conversion module, a relevant node matching module, a modified path tree computation module and a distance computation module, wherein the process conversion module and the relevant node matching module are connected to transmit the structured process tree information of two converted processes to be compared, the relevant node matching module and the computation modified path tree computation module are connected to transmit the structured process tree information of the two processes with matching information, and the computation modified path tree computation module and the distance computation module are connected to transmit the structured modified path tree information. The modified path tree between processes is computed by matching relevant nodes in the structured process tree of the processes, the measurement of distance between the processes in different hierarchies is realized, and the invention has the advantages of quantification and multiple views.

The invention provides a data resource configuration management method applied to a measuring instrument. The method comprises the steps of establishing correlation between local menu resources and data resources and between remote SCPI command resources and the data resources, data resource access authority control and data resource access interfaces; establishing direct correlation between the local menu resources and the remote SCPI command resources and the data resources, wherein a menu resource item is correlated with a data resource item at the maximum, and an SCPI command is correlated with multiple data resource items; declaring all the data resources to be privately-owned, wherein any client program cannot directly get access to the data resources; providing an access interface and a modification interface for each data resource item in the data resources, wherein the client programs can only get access to or modify the data resources through the access interfaces and the modification interfaces; reserving calling of virtual interfaces in the modification interfaces of the data resource items, wherein the client programs achieve automatic setting of correlation parameters by rewriting the virtual interfaces.