57 results about "Schema analysis" patented technology

A research service includes a number of functions for reporting and analyzing data from a multi-region research survey. The service provides an analysis interface to a research client to receive client input using a regional communication mode corresponding to the research client. Based on the client input, the service analyzes data from an on-line survey of a panelist. The on-line survey uses a second, distinct regional communication mode corresponding to the panelist. Analysis results are provided to the client in the analysis interface, again using the regional communication mode corresponding to the research client. In various embodiments, the analysis service similarly provides for analysis of survey data from multiple panelists using multiple regional communication modes.

Schema-driven XML parsing techniques allow an XML parser to optimize its parsing process by composing parse and to dynamically generate parsing code components based on XML schema definition for the targeted XML document. These techniques reduce the XML parsing time and reduce the memory requirement during parsing process. Further, a reconfigurable parser is provided which is guided during parsing of the XML document by XML element lexicographical information and state transition information extracted from a schema associated with the XML document. Pre-allocated element object pools may be provided based on the schema analysis to reduce the requirements for dynamic memory allocation and de-allocation operations.

The present disclosure provides methods and systems for automated analysis of spectrometry data corresponding to particles of a sample, such as large data sets obtained during single particle mode analysis of an inductively coupled plasma mass spectrometer (SP-ICP-MS). Techniques are presented herein that provide appropriate smoothing for rapid data processing without an accompanying reduction (or with an acceptably negligible reduction) in accuracy and / or precision.

A method and system parses natural language in a unique way, determining important words pertaining to a text corpus of a particular genre, such as tax preparation. Sentences extracted from instructions or forms pertaining to tax preparation, for example are parsed to determine word groups forming various parts of speech, and then are processed to exclude words on an exclusion list and word groups that don't meet predetermined criteria. From the resulting data, synonyms are replaced with a common functional operator and the resulting sentence text is analyzed against predetermined patterns to determine one or more functions to be used in a document preparation system.

A method and system for processing and managing referral data are disclosed. The system comprises a business rules engine for applying at least one business rule to referral data associated with a business entity. Further, the system has a data store for storing the referral data. Moreover, the system includes a reporting and pattern analyzer for analyzing the referral data and for generating reports about the referral data. Furthermore, the system includes a notification and alert system for generating an alert to the business entity, wherein the alert is based on a plurality of criteria associated with the referral data.

The invention provides an analysis method for infant brain medical computer scanning images and a realization system. The analysis method is to process the brain medical computer scanning images into images with prominent fractal characteristics, and then perform mathematic quantitative analysis on the images by a chaos fractal analysis method. The method is realized under Matlab R2007 through programming, utilizes chaotic neural network and fractal principles, performs serialized division, identification and fractal mode analysis on the infant brain medical computer scanning images to obtain fractal dimension quantified reference values and quantified reference values of multifractal spectrum width of normal infant brain medical computer scanning images in different age brackets, realizes clinical prediction on sick infants with intelligent disability and brain paralysis which have no typical neural image manifest characteristics by taking the reference values as a comparison standard, thoroughly changes the conventional analysis mode for the infant brain medical computer scanning images, and has high accuracy and strong repeatability compared with scoring results of the clinically widely used Gesell scale.

A value field index for data stored in a data source is generated by analyzing a data source schema, analyzing intended queries of the data and analyzing the data. Problematic queries are identified and token fields are designated. The value field indexes are then created using the data source schema; and the value indexes are embedded in other indexes.

A microscope array with staggered rows of magnifying imaging systems is used to scan a biological tissue sample in a single linear pass to produce an image and corresponding optical-density data. A conventional computerized algorithm is used to identify, isolate and produce segmented images of nuclei contained in the image. The OD values corresponding to nuclear chromatin are used to identify numerical patterns known to have statistical significance in relation to the health condition of the biological tissue. These patterns are analyzed to detect pre-neoplastic changes in histologically normal-appearing tissue that suggest a risk for the development of a pre-malignant and a potentially malignant lesion. This information is then converted to a visually perceptible form incorporated into the image of the tissue sample and is displayed for qualitative analysis by a pathologist.

The invention discloses a heat map visualization method through reverse rendering. With a single pixel point of a window as an analysis point, the distribution of adjacent data points of the single pixel point is analyzed according to an influence power superposition mode suitable for current analysis, and an influence power image is calculated and mapped to a gray level image; according to the whole distribution law of the gray level image, a graded color grading threshold is divided and obtained, the color gradient of the heat map is acquired in the adaptive mode, and the heat map is obtained through coloring. The actual geographical and spatial distribution condition of the data is thoroughly considered, influences from the map scale are little, the data features can be expressed more stably, and the data visualization effects are good. First calculation and then rendering are carried out according to the screen pixel point, influence power superposition does not depend on a renderer, different influence power superposition models can be set according to different requirements, and the method is more suitable for geographical and spatial POI analysis.

The invention provides a substation equipment defect recognition method and device, and particularly relates to the technical field of data analysis and processing, and the method can comprise the steps: building an infrared and visible light double-vision system, and obtaining a visible light image and an infrared image of detected substation equipment; carrying out the fusion through employing an image fusion algorithm of IHS transformation and Contourlet transformation, and generating a to-be-recognized image after fusion; constructing a neural network, performing feature extraction on the batch of original video data, and establishing an equipment defect database including abnormal data of the power transformation equipment in different states; then constructing a transfer learning network based on infrared image features to obtain a temperature mode analysis result of the equipment area; and finally, carrying out anomaly identification and defect judgment on the to-be-recognized image by utilizing a multi-network fusion algorithm. Based on the scheme provided by the invention, the intelligent degree of substation equipment fault detection is improved, and the efficiency and accuracy of fault detection are improved.

The invention relates to an aviation dynamotor fault diagnosis method based on a FWA-RNN model, and belongs to the dynamotor state monitoring and fault diagnosis field; the method mainly comprises thefollowing steps: 1, analyzing fault modes and selecting test signals; 2, determining an aviation dynamotor to-be-tested signal, using sensors to gather mass data under various work states, and sending the data to a computer for data storage; 3, making FFT transformation for obtained mass data, carrying out normalization processing, and splitting obtained data into training samples and test samples; 4, combining test sample data, using FWA to optimize all initial parameters of a RNN, building a nerve network model, and inputting the training samples so as to make fault analysis; 5, detecting the model accuracy. The method has excellent data adaptive ability and robustness, and can effectively improve the aviation dynamotor fault classification detection efficiency and accuracy.

The present invention relates to a system and a method for diagnosing and controlling an incineration facility and managing the life cycle thereof through a heat exchange and design program and an operation mode analysis of an operator of the incineration facility, and the purpose of the present invention is to improve operation efficiency by comparing and analyzing initial design values (a) of the incineration facility, measured actual values (b) obtained by measuring waste composition and heating values changed after constructing the incineration facility, and operation values (c) indicating output values which are actual operating adjustment values and operating result values operated by the operator and by analyzing operation modes of the operator. The system for diagnosing and controlling an incineration facility and managing the life cycle thereof through a heat exchange and design program and an operation mode analysis for an operator of the incineration facility, according to the present invention, comprises: a database for storing, in a predetermined period of time, the operation values (c) according to an operation of the operator, which are detected by incineration facility operating sensors (10) and provided through an MMI, the incineration facility operating sensors (10) detecting operation values of the incineration facility, which include a primary amount of combustion air, a secondary amount of combustion air, a fire grate moving speed, a temperature, an amount of discharged gas and an amount of steam, outputted by an operation of the operator, the design values (a) according to the design of the incineration facility, which are calculated through the heat exchange program, and the measured actual values (b) according to an operation of the incineration facility constructed under the design; and a server for extracting design values, measured actual values and operation values on the basis of data stored in the database and extracting and providing the design values, the measured actual values and the operation values as data including comparable graphs and tables.

The present disclosure provides methods and systems for automated analysis of spectrometry data corresponding to particles of a sample, such as large data sets obtained during single particle mode analysis of an inductively coupled plasma mass spectrometer (SP-ICP-MS). Techniques are presented herein that provide appropriate smoothing for rapid data processing without an accompanying reduction (or with an acceptably negligible reduction) in accuracy and / or precision.

Disclosed are a recommending device and a recommending method based on user model evolution. The recommending device comprises a user model constructing unit, an evolution mode analyzing unit, and a recommending content generating unit. The user model constructing unit is configured to receive user log information from one or more client devices and construct a user model for each user based on the user log information of the user of each client device. The evolution mode analyzing unit is configured to analyze a time evolution mode of the user model for each user. The recommending content generating unit is configured to predict a user model evolution trend of a target user based on analysis results of the evolution mode analyzing unit, generate a recommending content corresponding to a predicted result, and send the recommending content corresponding to the predicted result to the client device of the target user, wherein the user log information comprises data about user browsing behaviors when the user is using the Internet, and wherein the evolution mode represents the change of interests in different periods of the user.

An autonomic event parser configured for association with a message adapter. An autonomic event parser can include a store of parsing rules, the parsing rules having a strategically specified order. Additionally, a pattern analyzer can be programmed to identify patterns of received messages and to recommend the strategically specified order of the parsing rules. Finally, a parsing rules manager can be communicatively coupled both to the pattern analyzer and the store of parsing rules, the parsing rules manager having a configuration for ordering the parsing rules in the store based upon the recommended order of the pattern analyzer.

The invention relates to a method for identifying a settlement pattern during shield tunnel construction. The method comprises the following steps of: 1, acquiring ground settlement monitoring data of a shield tunnel and storing the data into a database; 2, analyzing and identifying a transverse settlement curve pattern and a longitudinal settlement curve pattern of the tunnel and determining the pattern of the tunnel; and 3, analyzing to obtain construction parameters associated with the pattern of the tunnel, so that guidance and basis are provided for construction optimization. Compared with the prior art, the method has the advantages that the current situation that monitoring data and construction parameters can only be identified manually is changed; and automatic identification of the curve pattern, automatic generation of a curve analysis result and fitting of relevancy of various parameters are realized, so that the guidance and basis are provided for construction optimization.

The invention discloses a spatio-temporal data mining-based online booked car client credit investigation method. By extracting historical order information of clients, performing credit history analysis, fulfilling ability assessment, identity trait description, preference mode analysis and personal connection graph determination on the clients, and performing more accurate credit rating on the clients, finite online booked car resources can be matched to the clients with relatively high credit ratings.

The invention provides a wide-azimuth pre-stack seismic reflection mode analysis method for a tensor depth self-encoding network, and the method comprises the following steps: S1, data preprocessing:extracting the wide-azimuth pre-stack seismic data of a target layer according to a layer target analyzed by a seismic reflection mode, and forming a three-dimensional tensor sample set; S2, traininga TDOEN network by using the sample set; S3, obtaining deep features of the sample set; and S4, clustering depth features obtained in the step S3 by combining an SOM clustering algorithm to generate aseismic facies division result. According to the method, a tensor model represented by high-dimensional data is adopted, through tensor product operation model analysis, a tensor-based weight networkhas fewer weight parameters, and feature expression can be performed more fully. Therefore, the tensor-based learning network is more suitable for processing wide azimuth data than a vector (matrix)-based deep learning model.

The invention discloses a community population feature analysis and power supply classification service system based on big data, and belongs to the field of power supply management. Power consumption mode analysis is carried out based on daily power consumption of the residential users according to flat valley period data, and analysis and recognition are carried out for various key user types; analyzing by adopting a support vector machine method with supervised learning and a k-means clustering method without supervised learning to obtain user characteristics and power utilization modes of various key user types; completing specific evaluation on various key user types; the electricity consumption data is applied to mining analysis of population characteristics, and the community population characteristic evaluation method is provided, so that the electricity industry can better serve communities. The power utilization data is applied to mining and analysis of the population characteristics, and a diversified power supply service system for the population characteristics is constructed, so that a power supply company can expand the terminal energy utilization market; the application value of the power utilization information acquisition system is exerted, and power utilization data value increment is realized. The method can be widely used in power supply management field.

The invention discloses a query intention recognition method based on bert + bolstm + crf and fused with sentence pattern analysis. The method comprises the steps that a data set is marked and constructed, domain intentions are defined, intention classification and intention word grooves are clarified, a domain term set corresponding to the word grooves is constructed, a question set is collected, and question intention classification and word groove information are marked. According to the marked question and the corresponding intention information, a sentence pattern for matching verification in an intention recognition model reasoning stage is generated; and a query intention recognition model is constructed based on bert+bilstm+crf. According to the method, slot dictionary matching, sentence pattern analysis, slot entity recognition based on bert+bilstm+crf and intention classification based on bert are fused, the problem that the model is wrongly recognized when the model training data and the model prediction data are inconsistent in distribution is well solved, and the accuracy of recognizing the user input port linguistic content intention by the model is improved.

The invention provides a bank human resource system and a working method, and the system comprises: an identity authentication module which is used for receiving an identity recognition number and biological feature information of a user, recognizing the identity of the user, and determining the identity information of the user; a historical question and answer mode analysis module which is used for calling a historical question and answer record of the user according to the identity information of the user and analyzing the historical question and answer record of the user to obtain a question language combination mode of the user; an intention recognition module which is used for extracting questioning terms in questions input by the user according to the questioning term combination mode of the user and determining intention information required to be queried by the user; and a retrieval module which is used for querying in a bank knowledge base according to the intention information and feeding back a query result to the user. According to the system, the situation that a plurality of search pages need to be opened is avoided, the waiting time of a user during search is shortened, the user experience is improved, and the office efficiency of the user is also improved.

The invention discloses a spatial sampling method for social survey data. Firstly, samples are obtained through layered spatial sampling; then, a spatial point pattern analysis method is used to judge equilibrium of sampling result distribution according to a parameter calculation result; and if spatial equilibrium requirements are not met, re-sampling is carried out until a sampling result meeting the spatial equilibrium is obtained. Spatial sampling, spatial equilibrium evaluation and social survey are organically combined, thereby realizing effective cohesion between non-spatial data and spatialization technology. The traditional sampling method is improved, and a good auxiliary support is provided for social survey. Through visualizing the sampling result, a more intuitive visualized result is provided, and more accurate judgment can be obtained through spatial equilibrium evaluation.

The invention discloses a terminal equipment adjusting system and method with a wireless charging function, an intelligent wireless charging clamping seat is arranged in the system, is arranged at theback of each terminal equipment and is used for wirelessly charging the terminal equipment, and different terminal equipment residual electric quantity monitoring modules are used for monitoring thereal-time electric quantity of different terminal equipment. The terminal equipment to-be-transmitted data volume statistical analysis module is used for counting the to-be-transmitted data volume ofkey equipment needing to be charged and analyzing and estimating the power consumption of transmitted data, and the terminal equipment charging mode analysis confirmation module is used for estimatingthe data input quantity of the terminal equipment according to the historical data input quantity. And the estimated power consumption of the data input quantity is analyzed, the different terminal equipment real-time power consumption checking modules being used for checking the power consumption of different terminal equipment in the same time period, screening the terminal equipment with abnormal power consumption for monitoring and analysis, and the different terminal equipment abnormity warning modules being used for warning the terminal equipment with abnormal power consumption.

The invention belongs to the technical field of data privacy protection, and particularly relates to a data privacy protection method in a hybrid cloud environment, which comprises the following steps: step 1, taking a DaaS bearing platform as a hybrid cloud, and analyzing the potential risk of data privacy leakage after the introduction of a cloud platform according to the characteristics of high-dimensional sparse data and a data release mode; step 2, on the basis of an anonymous segmentation strategy, analyzing a constraint scene with maximum data availability through a greedy strategy; step 3, analyzing the influence of noise addition on data availability by utilizing statistical search of interactive differential privacy protection; and step 4, for data error segmentation caused by parallel anonymous segmentation, reducing the data volume reserved on the private cloud by sharing the aggregation cluster. According to the method, information loss can be reduced, and the execution efficiency of the algorithm is improved, so that the feasibility and practicability of privacy protection of data are improved.