2177 results about "Data association" patented technology

This invention provides a system and method for identifying, locating, authorizing by proximity and communicating with equipment and personnel in a facility that generally employs a series of limited range transceivers for location determination and a distributed wireless data network for data transfer. The system employs unique RF transceiver tags on personnel and equipment that are each uniquely identified and registered with a facility control application that oversees activities in the facility. The tags are tracked by RF communication based upon their proximity to one or more fixed-base networked access points and relays (which transfer location data by RF back to access points) within four range zones. Location data on all tags is uploaded periodically to a location server that interfaces with the facility control server. Tag data is monitored by the facility control server to track, authorize and deauthorize certain data transfers, movements and activities in accordance with rules established for each tag (or type of tag) within the facility control server's application. Wireless networking (WiFi, for example), in combination with the RF-derived location information, allows the facility control server to correlate and transmit data to staff in conjunction with location and proximity. WiFi can transmit authorizations, deauthorizations and general data based upon triggers established by proximity and location. Likewise, data can be transmitted over WiFi from readers etc. from personnel and equipment located and identified by the system.

The invention provides a method, apparatus and system for classification and clustering electronic data streams such as email, images and sound files for identification, sorting and efficient storage. The inventive systems disclose labeling a document as belonging to a predefined class though computer methods that comprise the steps of identifying an electronic data stream using one or more learning machines and comparing the outputs from the machines to determine the label to associate with the data. The method further utilizes learning machines in combination with hashing schemes to cluster and classify documents. In one embodiment hash apparatuses and methods taxonomize clusters. In yet another embodiment, clusters of documents utilize geometric hash to contain the documents in a data corpus without the overhead of search and storage.

A system & method for dynamically publishing, sharing, communication & subscribing and dynamically presenting and allow to auto subscribe publisher specific active links and associate objects & data of other services, applications, networks, groups, widgets & objects of publishers to users of network is described. A method includes dynamically present selected publishing type or service specific input system, presentations and application features to publisher and subscriber for managing publishing specific contents, shared data, communications & messages, subscribers, privacy settings, user actions, workflow and managing subscribed contents, communications, messages, subscriptions, privacy settings, user actions, workflow. A method further includes publisher can dynamically publish active links and associate objects & data for other services, applications, web site features, widgets, objects, multimedia contents of publisher and allow users of network to search, select, subscribe or auto install & attach said active links with user profile based on privacy settings.

The invention relates to a Federated Kalman filtering-based method for fusing multilateration data and radar data, comprising seven processes: pretreatment, time and space registration, error correction, single-sensor line tracking or airborne trace interconnection and filtration, data association, data fusion as well as error estimation. On the basis of multiclass monitoring information, the technical scheme of the invention establishes data association mapping relations among all classes of targets, constructs a process method fusing the multilateration system data and the radar data, realizes deep fusion of all classes of information and comprehensive utilization on effective information, ensures high updating rate of a multilateration system and the whole precision of system monitoringwhen period is less than or equal to 1sec, reduces impact of radar measuring error on system monitoring precision, and significantly improves the tracking precision of the system.

An industrial control network security protection monitoring system performs real-time prevention and protection on industrial equipment of the industrial control network, and realizes network security protection monitoring through an acquisition layer, an analysis layer, a function layer and a display layer based on an integrated application platform, wherein the display layer mainly displays security trend, system topology and industrial control panorama; the acquisition layer comprises the acquisition of network data traffic and the recording of industrial control network operations; the analysis layer mainly comprises data processing, data association, data aggregation, data modeling, and integrated interfaces of other function modules; and the function layer mainly comprises monitoring audit, intrusion prevention, vulnerability mining, and data isolation. The system provided by the invention protects and protects industrial equipment in real time through the intelligent protectiontechnology of the industrial network control system, monitors and audits the data information of the entire industrial control network through the monitoring and auditing technology to prevent the industrial control network from being attacked externally, and can also have the vulnerability mining function of the industrial control network to escort the entire industrial control network security.

The invention discloses a vision-inertia integrated SLAM (Simultaneous Localization and Mapping) method based on a genetic algorithm. The method comprises the following steps: integrating a vision navigation coordinate system with an inertia navigation coordinate system, and calibrating parameters of a binocular camera so as to solve a three-dimensional space coordinate according to an image pixel coordinate; independently calculating by inertia navigation; calculating by vision navigation; integrating vision navigation information with inertia navigation information by using an extended Kalman filter, and building a system filter model; and observing global feature point road signs by using the binocular camera by taking localization locality into account, carrying out data association on map features based on the genetic algorithm, and feeding extended state vectors back to a filter. The method is capable of carrying out long-time and high-accuracy localization; the genetic algorithm is added for improving the data association of the map, so that the simultaneous mapping accuracy is greatly improved.

Despite advances in recent years in the area of mandatory access control in database systems, today's information repositories remain vulnerable to inference and data association attacks that can result in serious information leakage. Without support for coping against these attacks, sensitive information can be put at risk because of release of other (less sensitive) related information. The ability to protect information disclosure against such improper leakage would be of great benefit to governmental, public, and private institutions, which are, today more than ever, required to make portions of their data available for external release. In accordance with the invention, a solution to the problem of classifying information by enforcing explicit data classification as well as inference and association constraints is provided. We formulate the problem of determining a classification that ensures satisfaction of the constraints, while at the same time guaranteeing that information will not be unnecessarily overclassified.

The invention discloses a spatiotemporal database management method, as well as a management system and a program product thereof. The spatiotemporal database management system comprises a data collection part, a spatiotemporal data association part and a spatiotemporal data management part, wherein, the data collection part is used to collect or receive the spatial information and the timing information about a geographical entity from external systems, and the produced and existed object timing information of the data are arranged; the spatiotemporal data association part is used to associate various data obtained from the data collection part with the object timing information, and store the association into a corresponding spatiotemporal data file, so as to express the evolution history of the geographical entity and predict the change of the geographical entity; the spatiotemporal data management part is used to respectively store the spatiotemporal data file produced by the spatiotemporal data association part according to the temporal information recorded by the timing information of the geographical entity and the evolution trend recorded by the spatial information of the geographical entity, so as to compose a spatiotemporal database.

The invention relates to a system and method for realizing real-time data association in the big data environment. The system comprises an association scheduling framework, a distributed storage framework, a relational database and Redis servers, wherein the association scheduling framework is used for conducting intra-class association, inter association and concurrent scheduling on business objects; the distributed storage framework is used for establishing a connection pool for a master server of each Redis server, storing data related to current data association, sending cold data surpassing updating time limit and excessive data surpassing memory capacity limit to the relational database, and inquiring key values of intra-class association and inter association transferred to the relational database; the relational database is used for storing key values of intra-class association, key values of inter association, intra-class contexts and monitoring contexts. Through the adoption of the system and method, real-time association supporting mass streaming data can be realized, the demand of complex association in various conditions can be met, the model generality is high, and the application range is relatively wide.

The present invention provides software and a method and system of efficient source document data entry and data association. More particularly, the present invention relates to a software module which receives source documents and recognizes or extracts information from the documents or associated files for use in populating fields of related or derivative documents or screens to facilitate accurate transfer of data. The invention also allows for ease in confirming the accuracy of the extracted or imported data by comparison with the source document either directly by a person or through automated or semi-automated procedures.

A low cost, all weather, high definition RF radar system for an autonomous vehicle is described. The high definition RF radar system generates true target object data suitable for imaging, scene understanding, and all weather navigation of the autonomous vehicle. The high definition RF radar system includes a pair of independent orthogonal linear arrays. Data from both linear arrays is fed to a processor that performs data association to form true target detections and target positions. A Boolean association method for determining true target detections and target positions reduces many of the ghosts or incorrect detections that can produce image artifacts. The high definition RF radar system provides near optimal imaging in any dense scene for autonomous vehicle navigation, including during visually obscured weather conditions such as fog.

The invention discloses a vSLAM implementation method and system based on point and line feature fusion. The method includes Step S110, obtaining an image frame sequence of a target scene; Step S120,preprocessing each frame of image; Step S130, according to successfully matched point features and lie features, initializing an environmental map; Step S140, tracking based on the environmental map,and estimating the pose of a current frame of image; Step S150, judging whether the current frame of image meets a key frame condition, if yes, executing Step S160, otherwise repeatedly executing StepS110 to Step S150; Step S160, executing a step of a local map thread; Step S170, executing a step of a closed-loop detection thread; and Step S180, executing a step of a global optimization thread toobtain an optimized environmental map and complete simultaneous localization and mapping. The extraction and matching processes of line features are improved, so as to improve the accuracy of data association in the front end, and thus the defects of vSLAM which exist in a complicated low-texture scene can be effectively overcome.

The invention discloses an auxiliary disease judgment method based on diagnostic element data association, belonging to the field of information analysis and aid decision making. The auxiliary disease judgment method comprises the following steps: establishing a disease library according to clinical experience and expert data; establishing a symptom library by taking symptoms to which each disease model relates in the disease library to serve as the constitution elements of the symptom library; according to the symptom information of a patient, selecting the symptoms in the symptom library to serve as the symptom set of the patient; according to the selected symptoms, finding all diseases with the symptoms from the preset disease library; and listing as a disease list according to the decreasing correlation degree or suspected probability. In the method, limited known information can be furthest utilized based on the practical requirement on diagnosis and treatment on patients by doctors according to the step of diagnosing patients for doctors in the practical work, and the information can be added and revised to furthest simulate the real situation. The obtained information (contents, such as symptoms and the like) is fully simulated by utilizing a self-forming rule, thus the method is suitable for the complex situation of the randomness and dynamics of the information resource of the disease.

The invention provides a multi-source information fusion based high precision motion track detection system, which includes inertial sensor positioning, machine vision positioning and electromagnetic positioning three subsystems and a data processing platform, wherein the inertial sensor positioning subsystem is used for three-dimensional attitude angle measurement; the electromagnetic positioning subsystem is used for measuring three-dimensional position and three-dimensional attitude information; the machine vision positioning subsystem is used for measuring three-dimensional position information; and the data processing platform performs comprehensive analysis and coordination processing on the multi-source information acquired by the subsystems, carries out coordinate transformation on data and data correction, data association and state estimation fusion based on a distributed state fusion structure model, and realizes six-dimensional pose dynamic detection on robots and other moving parts. The system provided by the invention overcomes the problems that the positioning information content obtained by an individual system is single and is easy to be disturbed by environmental factors.

Disclosed is a system comprising a physical memory, a processor and a software component. The software component includes a policy/domain handler for receiving data and a policy associated with the data; a hypervisor; and a file management module. The file management module receives a request from a third-party application to interact with a data file containing the data; sends an authorization and tag request to the policy/domain handler to check if the user and application are permitted to access the data, and if permitted, to generate hardware tags for the data file; and sends a secure data request to the hypervisor to create a secure data compartment for the data file and the hardware tags. Based on the authorization and tag request, and the security policy associated with the data, the policy/domain handler generates the hardware tags for the data file. Based on the secure data request, the hypervisor creates in the physical memory a secure data compartment containing the data file and the hardware tags, the hypervisor associating the hardware tags with the data in the secure data compartment. As the data is operated upon and moved to other memory areas, the hardware tags are propagated with the data according to tag propagation rules, and checked before performing operations that may lead to security breaches.

The invention discloses a method for mining data in construction regulation field based on associative regulation mining technology; 1. a construction regulation text vector space model is generated, 2. a construction regulation data vector space model is generated, 3. the construction regulation data vector space model is subject transposition to generate a construction regulation data feature vector space model, namely, a frequent feature set is generated, and 4. construction regulation data association degree is calculated and an association rule is output. The method can mine the data in construction regulation field, provides higher recall ratio for a user inquiring data, recommends associative query contents, and solves the technical problem that the existing association analysis technologies can not carry out association analysis on outlier data.

Tracking systems using multi-object-tracking (MOT) combine data from a plurality of sensors (101) to derive a state estimate of one or more objects (103) are described. The interfaces to the sensors (101) are such that different ones of the sensors (101) can be used. The tracking (102) in the system consists of different blocks for state estimation (104), object's existence estimation (106), and data association (105). To utilize the data of a sensor, the sensor data and the system which is observed is modeled using the Bayesian filtering framework. All interfaces of the system, i.e. the interfaces between the sensors (101) and the MOT system as well as of the blocks in the MOT are of a characteristic that ensures that only compatible models are used with each other already when designing the system

The invention discloses an end-to-end fault diagnosing and positioning platform of IPTV (Internet Protocol Television) business. The platform comprises a presentation layer, an application layer, a logic layer, a data layer, a collection layer and a system management layer, wherein the collection layer is used for collecting various data by using online or offline method and processing and integrating the collected data; the data layer is used for storing and managing various KPI (Key Performance Indicator) data; the logic layer is used for carrying out logic association and analysis processing on the original data; the application layer is used for constructing fault diagnosis and analysis through establishing a data association analysis model; the presentation layer is used for providing a service supporting interface; and the system management layer is used for managing system privilege, security and logs. The invention provides an end-to-end fault diagnosing and positioning platform of the IPTV business; and because the abnormity is actively found and the problem is handled through periodically inspecting quality situations of a terminal, a bearing network and a platform, the end-to-end fault diagnosing and positioning platform of the IPTV business disclosed by the invention has the advantages of rapidness in diagnosis, accuracy in positioning, active operation and the like; end-to-end business monitoring and prewarning are realized; the IPTV business operation capacity is increased; the processing efficiency is increased; and the processing period is reduced.

The invention relates to a data mining-based plate shape control key process parameter optimization system, and belongs to the technical field of automatic control of cold continuous rolling plate shape. The data mining method is adopted for acquiring key process parameter optimization settings which can meet the good cold continuous rolling plate shape. The system is characterized by comprising the following functional modules: an actual data acquisition and storage module, a process data pre-processing module, a process data storage module, a process data correlation analysis module, a process data clustering analysis module, a process data association rule analysis module, an optimization result generating module and an optimization result application module. The system has the advantage that the good plate shape can be obtained by applying the plate shape control system. The method avoids endless theoretical research on plate shape control and fully utilizes actual plate shape control process data containing successful operation experience of field operators, and the plate shape process parameter settings which can obtain the good plate shape are acquired by data mining, so the plate shape qualification rate and the finished product rate of cold continuous rolled strip steel are improved.

The present invention provides a visual tracking system and its method comprising: a sensor unit, for capturing monitored scenes continuously; an image processor unit, for detecting when a target enters into a monitored scene, and extracting its characteristics to establish at least one model, and calculating the matching scores of the models; a hybrid tracking algorithm unit, for combining the matching scores to produce optimal matching results; a visual probability data association filter, for receiving the optimal matching results to eliminate the interference and output a tracking signal; an active moving platform, for driving the platform according to the tracking signal to situate the target at the center of the image. Therefore, the visual tracking system of the present invention can help a security camera system to record the target in details and maximize the visual information of the intruding target.

Embodiments of the present invention relate generally to the classification and management of digital data artifacts, and particularly to systems and methods for annotating and associating a comment with a content item available on a computer, TV or mobile (e.g., handheld) device using forms. The digital data artifacts may include at least user-defined and extensible artifacts, or pre-built artifacts, or comments and tags. Comments may include, but are not limited to, one or more of unstructured text, structured data (e.g., data entered or browsed to via a form), an audio or video file, tags, etc. The artifacts may act as a classification system for a user. A method embodying the invention includes navigating to a content item for comment or annotation, and selecting a tag set and/or a form, which is filled in and used to comment on the item and then saved in a database. A tagging or data association server saves the form and user extensible tag set and related files and data sets with the content item and provides various presentation, analysis and information retrieval functionalities. Community responses to the form may be analyzed by semantic analysis and subsequent aggregation and display of the form data.