1448 results about "Data modeling" patented technology

A system, program product and method continuously optimize an ultrafiltration rate during an extracorporeal renal replacement process by modeling physiological and actual rate data. The system maps the sensed, physiological data to a mathematical model to assess the data in terms of the ultrafiltration rate. The model provides parameters used to predict where the treatment is headed based on current conditions. The system processes the parameters in terms of preset criteria to generate the optimized ultrafiltration rate. Where the system is networked, communication of the data may be accomplished using remote and online communication techniques.

The present invention is related to method and apparatus for versioning. Versioning information is stored as metadata associated with data entities. A hierarchical relationship between the entities allows the definition of an editorial sequence and separate revisions within that sequence as well as relationships between sequences in a self-contained format.

One or more systems and methods for knowledge pattern search from networked agents are disclosed in various embodiments of the invention. A system and a related method can utilizes a knowledge pattern discovery process, which involves analyzing historical data, contextualizing, conceptualizing, clustering, and modeling of data to pattern and discover information of interest. This process may involve constructing a pattern-identifying model using a computer system by applying a context-concept-cluster (CCC) data analysis method, and visualizing that information using a computer system interface. In one embodiment of the invention, once the pattern-identifying model is constructed, the real-time data can be gathered using multiple learning agent devices, and then analyzed by the pattern-identifying model to identify various patterns for gains analysis and derivation of an anomalousness score. This system can be useful for knowledge discovery applications in various industries, including business, competitive intelligence, and academic research.

Embodiments include generating data models that may give semantic meaning for unstructured or structured data that may include data generated and / or received by search engines, including a time series engine. A method includes generating a data model for data stored in a repository. Generating the data model includes generating an initial query string, executing the initial query string on the data, generating an initial result set based on the initial query string being executed on the data, determining one or more candidate fields from one or results of the initial result set, generating a candidate data model based on the one or more candidate fields, iteratively modifying the candidate data model until the candidate data model models the data, and using the candidate data model as the data model.

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.

Embodiments relate to systems and methods for extracting a model object from a multi-dimensional source database. A modeling client can host modeling logic and an application programming interface (API) to create, access, manipulate, and import / export modeling objects used in modeling applications, such as engineering, medical, financial, and other modeling platforms. In aspects, the source data accepted into the modeling client can include consumer or business-level applications, whose database or other content can be extracted and encapsulated in object-oriented format, such as extensible markup language (XML) format. The resulting model object can be pivoted along selected dimensions, or otherwise manipulated. The modeling client can exchange one or more modeling object directly with external platforms, such as mainframe modeling platforms, via the application programming interface (API) on a programmatic basis. Costs and maintenance savings over mainframe-based modeling tools can thereby be achieved, while providing greater power than consumer or business-level tools.

A method for coding and decoding seismic data acquired, based on the concept of multishooting, is disclosed. In this concept, waves generated simultaneously from several locations at the surface of the earth, near the sea surface, at the sea floor, or inside a borehole propagate in the subsurface before being recorded at sensor locations as mixtures of various signals. The coding and decoding method for seismic data described here works with both instantaneous mixtures and convolutive mixtures. Furthermore, the mixtures can be underdetemined [i.e., the number of mixtures (K) is smaller than the number of seismic sources (I) associated with a multishot] or determined [i.e., the number of mixtures is equal to or greater than the number of sources). When mixtures are determined, we can reorganize our seismic data as zero-mean random variables and use the independent component analysis (ICA) or, alternatively, the principal component analysis (PCA) to decode. We can also alternatively take advantage of the sparsity of seismic data in our decoding process. When mixtures are underdetermined and the number of mixtures is at least two, we utilize higher-order statistics to overcome the underdeterminacy. Alternatively, we can use the constraint that seismic data are sparse to overcome the underdeterminacy. When mixtures are underdetermined and limited to single mixtures, we use a priori knowledge about seismic acquisition to computationally generate additional mixtures from the actual recorded mixtures. Then we organize our data as zero-mean random variables and use ICA or PCA to decode the data. The a priori knowledge includes source encoding, seismic acquisition geometries, and reference data collected for the purpose of aiding the decoding processing.The coding and decoding processes described can be used to acquire and process real seismic data in the field or in laboratories, and to model and process synthetic data.

A software system is provided to allow a computer to install and process web applications according to the invention. Such web applications are written as web pages that have access to the full range of operating system resources, including those not accessible through a web browser. Preferably, a web application is built using three types of languages used for constructing web pages, namely: (a) a visual presentation language; (2) a data modeling language; and (3) a scripting language for embedding logic. The software system preferably comprises a web application manager, an operating system interface module, a scripting language interpreter, and optionally a web browser and / or a data modeling language processor. Various other features such as data caching and security filtering are provided in accordance with such a system.

The invention relates to a java server page (JSP) template-based intelligent table system capable of being defined freely, which controls a table through system configuration under the driving of a table engine to complete various service functions on the basis of data modeling. The (JSP) template-based intelligent table system provides implementing mechanisms of data modeling, service configuration, table drawing, table editing and the like and can realize user-oriented free customization of the table, and a user can realize most service logics by configuring various parameters through pages, thereby greatly improving the flexibility and extensibility of the intelligent table system. In the system, the JSP file is used as a template of the table, and various configuration information controlling the table and the table template are connected through the table engine, thus that the effect that the table service comes into effect as long as configured can be realized. In the part of table editing, the system can realize automatic calculation of table attribute, addition and delete of sub-table rows, secondary authority control of the table, service implementation and control of the table and the like.

The subject invention relates to systems and methods to extend the capabilities of declarative data modeling languages. In one aspect, a declarative data modeling language system is provided. The system includes a data modeling language component that generates one or more data mining models to extract predictive information from local or remote databases. A language extension component facilitates modeling capability in the data modeling language by providing a data sequence model or a time series model within the data modeling language to support various data mining applications.

A computer-implemented schema-independent method of modeling data from a plurality of diverse sources. A server transmits to a client a blueprint for visualizing and interacting with data, wherein the blueprint defines an application, for visualizing and interacting with data that runs on the client. The application may operate on the client within a web browser and may include program code or scripts that operate within the web browser and transmit data and commands to and from the server. In response to receiving a data fetch message from the application running on a client computer, the server receives data from a selected one of a plurality of domains. The server then transforms the received data into a semantic data format. The transformed data is then stored by the server as a first data set. The first data set can then be transmitted to the client computer for further processing and visualization by the application on the client using the blueprint.

The invention provides a power transmission line disaster monitoring and risk assessment platform based on satellite and weather information in order to effectively warn disasters. The platform comprises a power transmission line geographic information sub-platform, a satellite remote sensing data receiving sub-platform, a data modeling and risk assessment sub-platform, a disaster warning and treatment sub-platform, and a support and operation sub-platform. The data modeling and risk assessment sub-platform comprises a fire development trend prediction submodule; the submodule predicts time sequence of fire data by a time prediction method, auto-regressive integrated moving average, captures cross-fire hidden spatial correlation by a spatial prediction method through dynamic regression neural network, simulates stochastic disturbance by a Markov chain model, and acquires space-time integrated and disturbance-removing prediction results by means of statistical regression.

The subject invention relates to systems and methods that extend the network data access capabilities of mark-up language protocols. In one aspect, a network data modeling system is provided. The system includes a protocol component that employs a computerized mark-up language to facilitate data interactions between network components. An extension component operates with the protocol component to support the data transactions, where the extension component supplies various commands above standard network and database protocols. An object model is provided as a wrapper to the extensions in order to support various online and offline database development applications.

The invention discloses an indoor positioning technology based on inertial data and visual features and discloses a corresponding implementation device to implement the steps. The indoor positioning technology specifically comprises: (1) multi-sensor data processing: a camera calibration and image feature extraction method; an IMU data modeling and filtering method; (2) multi-sensor coordinate system calibration: a system modeling, relative attitude calibration and relative position and attitude joint calibration method; (3) an indoor positioning and tracking technology fusing the inertial data and the visual features. Compared with an existing traditional single camera tracking technology, the indoor positioning technology disclosed by the invention has the advantages that single camera tracking is a simple assumption based on constant-speed motion; a better prediction can be provided by using the inertial data of an IMU, so that a search area is smaller during feature matching, the matching speed is higher, the tracking results are more accurate, and the camera tracking robustness in the image degradation and un-textured areas is greatly improved.

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate model.

The invention relates to an SCR (Selective Catalytic Reduction) denitration system ammonia spraying quantity optimal control system and method based on intelligent feedforward signals. The SCR denitration system ammonia spraying quantity optimal control system based on intelligent feedforward signals is characterized in that as input parameters of a denitration system can be easily influenced by the combustion state of a boiler and for adapting to the requirement of large range of depth change of conditions for a thermal power generating unit, the SCR denitration system ammonia spraying quantity optimal control system based on intelligent feedforward signals takes the historical data of a power plant as the basis, utilizes the idea of data modeling, takes adjustable parameters at the boiler side as input and NOX concentration at the outlet of a hearth as output, utilizes a Least Squares Support Vector Machine algorithm to construct a prediction model which can be used for constructing an intelligent feedforward controller in a ammonia spraying quantity control strategy, and takes dynamic matrix control (DMC) as a main controller and PID as an auxiliary controller to construct a cascade feedback control structure; during the operating process, the intelligent feedforward controller outputs feedforward control signals in real time according to changes of the parameters at the boiler side, quickly gives a response to change of conditions of the unit, and forms an SCR system ammonia spraying quantity optimal control strategy together with feedback control, and can realize quick accurate control of the ammonia spraying quantity.

A system and method to compress, aggregate and archive Internet of Things data originating from sensors can use a point cloud based geometric data model and a distribution and aggregation method based on compressed point cloud representations. The compression can occur at a gateway or a point of presence near the access point, or alternatively in an IoT server located anywhere else in a network, such as in a core data center. In one embodiment a cloudlet in an access point performs the data modeling and compression at the access point. In some embodiments, a system or method stores and distributes data to relevant entities formatted in a point cloud based model that combines (x,y,z) geometry attributes with values attached in the attributes (a1, a2, a3) and uses point cloud compression. A receiver can then decode the point cloud and recompose the aggregated sensor data, enabling inspection of the data.

Delivering data and formatting information includes delivering object definition files from a server to a client; generating definitions and object instantiations at a client using JavaScript or another simple browser-interpreted language, for objects relating to data modeling and presentation; and presenting data using those objects at the client, using a web browser without a separate runtime environment or application plug-in, but maintaining substantial state at the web browser regarding the data itself and the format for its presentation. Definition files are modified to provide object properties consistent with a full object-oriented language, including for example hierarchical inheritance of object properties. Code ballooning generates definitions and individual instantiations, with the effect that a very large amount of DHTML, or another markup or presentation definition language for use with the application, can be generated from relatively small aggregate size of definition files communicated from the server to the client.

The present invention simplifies the data modeling process and enables its full dynamic versioning by employing a non-hierarchical non-integrated structure to the organization of information. This is achieved by expressing data modeling, storage and transfer in a particular non-hierarchical, non-integrated neutral form. The neutral form of the present invention enables complete parallel processing of both data storage and data transfer operations. It also enables the direct integration of separate but related data models and their data without remodeling or reloading. Finally, the present invention enables direct transfer of neutral form information in a manner that includes all of the properties required to independently understand and interpret each transferred data value.

The invention relates to an on-duty person violation behavior detection method and system, belongs to the technical field of intelligent video analysis, and solves the problems of low efficiency, highcost and low recognition accuracy of an existing detection method. The method comprises the following steps: constructing a target detection network model, and training by using a data set; acquiringmultiple paths of videos at different angles in the same scene in real time, carrying out multi-target detection and tracking by utilizing a trained target detection network model and a target tracking algorithm, acquiring personnel information in each path of videos, carrying out integration processing, and judging whether behaviors of personnel on duty are abnormal or not. According to the invention, an environment camera video is used as an input video source for intelligent video analysis; the system supports multi-channel video source input and fusion analysis, greatly improves the recognition accuracy of illegal behaviors through deep learning and data modeling means, and achieves the real-time and accurate monitoring of the duty behaviors of personnel on duty in scenes such as a monitoring center, a duty room, a command center and the like.

A method for segmenting an image comprising: determining an initial estimation of a boundary between at least two components in a region of an image to be segmented; providing image data from the region of the image to be segmented, the image data representing gray level values of a plurality of image elements of the components; modelling the image data on a mixture of at least two statistical distributions, each statistical distribution having more than one parameter, and each component being associated with certain weights of the statistical distributions in the mixture; estimating the parameters of the statistical distributions in the mixture; for each component, estimating the weights of the statistical distributions in the mixture based on the estimated parameters and the image data of each image element; and optimizing the initial estimation of the boundary between the components based on the estimated parameters and estimated weights.

A system and method of integrating diverse sources of data and data streams is presented. The method can include selecting a scenario based on a topic, creating a multi-relational directed graph based on the scenario, identifying and converting resources in accordance with the scenario and updating the multi-directed graph based on the resources, identifying data feeds in accordance with the scenario and updating the multi-directed graph based on the data feeds, identifying analytical routines in accordance with the scenario and updating the multi-directed graph using the analytical routines and identifying data outputs in accordance with the scenario and defining queries to produce the data outputs from the multi-directed graph.

The subject invention relates to systems and methods to extend the capabilities of declarative data modeling languages. In one aspect, a declarative data modeling language system is provided. The system includes a data modeling language component that generates one or more data mining models to extract predictive information from local or remote databases. A language extension component facilitates modeling capability in the data modeling language by providing a data sequence model or a time series model within the data modeling language to support various data mining applications.

A computing system initializes a first frontier to be a root of a multi-dimensional hierarchical data structure representing an entity. The system acquires first data corresponding to the first frontier. The system performs modeling on the first data to obtain a first model and a corresponding first statistic. The system expands a dimension of the first frontier. The system gathers second data corresponding to the expanded frontier. The system applies the data modeling on the second data to obtain a second model and a corresponding second statistic. The system compares the first statistic of the first model and the second statistic of the second model. The system sets the second model to be the first model in response to determining that the second model statistic is better than the first model statistic. The system outputs the first model.

A method for modelling a dataset includes a training phase, wherein the dataset is applied to a non-stationary Gaussian process kernel in order to optimize the values of a set of hyperparameters associated with the Gaussian process kernel, and an evaluation phase in which the dataset and Gaussian process kernel with optimized hyperparameters are used to generate model data. The evaluation phase includes a nearest neighbour selection step. The method may include generating a model at a selected resolution.

The invention discloses a method for modeling on basis of power information data and applying metadata management. The method comprises the following steps of: establishing a power information main body coding and application index coding rule base first; constructing a structured power information data storage mode in a database according to a physical dimension, an application index dimension and a time dimension of the main body, and according to coding rules, marking the physical dimension, the application dimension and the time dimension on the structured data to form power information statistical analysis service application-oriented modeling data. The modeling data is managed and defined by using a power information application-oriented metadata management technique which realizes application of a main body metadata management method and application of an application index metadata management method. The method solves the problem of performing atomization and structuring treatment on the power information service data in practical application, and realizes a basic data model for standard storage of the power information.