145 results about "Data assessment" patented technology

The invention provides a flow system and method for reliable multiparameter data acquisition and particle sorting. In accordance with the invention, a flow system assesses changes in the pattern of data collected in successive time intervals and actuates one or more corrective actions whenever the changes exceed predetermined limits. The present invention overcomes problems associated with collecting data and sorting and enumerating particles in flow cytometry systems that operate for prolonged periods or that must accommodate samples that vary widely in quality.

On the basis of analyzing the features of the electric transmission and transformation device multi-source state assessment data, an electric transmission and transformation device multi-source state assessment data processing method is provided. The method comprises: multi-source data obtaining, data cross-platform access, data preprocessing and preliminary cleaning, data quality assessment model, data standardization conversion and data output, and is applied on the big data platform. The electric transmission and transformation device multi-source state assessment data processing method and the application thereof are configured to provide service such as storage, retrieval and excavation for the main net electric transmission and transformation device multi-source data and provide data support for the high-grade service such as risk assessment and the like. The electric transmission and transformation device multi-source state assessment data processing method and the application thereof belong to the electric power informatization technology field.

The invention provides a method for performing ground check and performance evaluation on a satellite-borne measurement-type GNSS (Global Navigation Satellite System) receiver. The method comprises the following steps of: firstly performing observation data verification on observation data generated by the satellite-borne measurement-type GNSS receiver; and after verification is finished, further performing orbit determination performance test on the satellite-borne measurement-type GNSS receiver by utilizing a geometrical orbit determination method. The process of performing data verification on the observation data mainly comprises four links, namely observation data standard format treatment, observation data type integrity checking, observation data quality evaluation based on calculation on observed value dual difference of different navigational satellites at a same frequency and observed value single difference of a same navigational satellite at different frequencies, and evaluation on pseudo range and carrier noise based on simulation data observation in a zero / short base line under the condition of no satellite; and during orbit determination performance test, by virtue of solving a linearized observation equation and comparing the linearized observation equation with a theoretical value, the orbit determination accuracy of the satellite-borne measurement-type GNSS receiver is obtained. The method provided by the invention can be used for directly and comprehensively evaluating the performance of the satellite-borne measurement-type GNSS receiver.

A method of providing personalized compliance feedback includes detecting user movement data using at least one data sensor, parsing the detected user movement data into segments indicative of potential activity, wherein each segment comprises event motion data occurring during a corresponding time interval, identifying at least one recognized activity from the parsed user movement data, generating feedback based on the at least one recognized activity, and outputting the generated feedback.

The invention provides an electric power operation monitoring data quality assessment system and method. The system includes a data set extraction module, an abnormity discrimination module, and a data quality assessment module that independently execute scripts codes. The method includes that a needed data set is extracted from an electric power operation monitoring data center; for the target data set, the abnormal electric power data is discriminated by means of data quality assessment indexes and constraint rules, the detected data quality problem is processed, an evaluation method is determined, and the calculation result is stored; and the result information of the data quality assessment indexes is acquired and the visualized operation is selected. The system and method prevent the problem in the data quality assessment process in the prior art, greatly improve the whole data quality assessment efficiency, and can visually perform quantification assessment and result feedback, and thus providing a systematic and comprehensive data quality assessment standard, guaranteeing the accuracy, timeliness, effectiveness, and reliability of data, enhancing the improvement of electric power operation monitoring data quality and further improving the running stability of an electric power system.

The invention relates to a quality evaluation method of electricity statistical index data. The method comprises the following steps: obtaining to-be-evaluated electricity statistical index data according to the requirement of an actual evaluation purpose; choosing corresponding data quality evaluation indexes; making data quality evaluation rules corresponding to the data quality evaluation indexes; calculating the weight Wi of a quality evaluation index Ii, and setting an expected value Ei; performing detection and analysis on quality evaluation indexes of the statistical index data, and calculating the percentage Si of data that meets the quality evaluation index Ii; according to the weight Wi, the percentage Si and the set expected value Ei, respectively calculating the comprehensive evaluation value SA, the overall expected value SE and the relative difference SR of the statistical index data, and performing evaluation on the overall quality of the statistical index data according to defined evaluation grades; and processing evaluated unqualified statistical index data. The method provided by the invention can be applied to quality evaluation of electricity statistical index data in the power industry.

Embodiments of the invention disclose a video data quality assessment method and an apparatus thereof. The video data quality assessment method comprises the following steps: acquiring a compression distortion parameter of video data; acquiring a frame damage distortion parameter; calculating a video quality parameter according to the compression distortion parameter and the frame damage distortion parameter, wherein the video quality parameter is a difference value of the compression distortion parameter and the frame damage distortion parameter.

The invention provides a traffic data quality monitoring system. An itemized monitoring module dynamically monitors equipment operating statuses and data quality of electronic polices, intelligent toll gates and vehicle detectors; a risk early warning module realizes early warning and integrated processing of abnormal data; a decision support module analyzes system abnormal data detection conditions and effective data situations according to processing results of the risk early warning module and a data checking module; a parameter configuration module provides parameter detection and early warning conditions for the itemized monitoring module and the risk early warning module. The traffic data quality monitoring system has advantages that abnormal data can be recognized, detected data quality assessment, checking and treatment can be realized, and accordingly false detection and judgment caused by abnormal conditions such as equipment faults and environment interferences are avoided, workload is relieved for workers, and law enforcement data validity and reliability are guaranteed.

Disclosed is a step stress accelerated degradation data assessment method based on gray prediction models, which includes five steps: step one: performing primary process and conversion to test data to obtain data series of performance degradation volume of each test sample under each stress level; step two: building prediction models through gray prediction, calculating model parameters, and testing prediction accuracy of each model; step three: calculating the time when each sample reaches a degradation threshold Df under a stress level Sa to obtain life distribution types of samples and general parameters under each stress level; step four: finding relationship equations between general parameters and stress levels, namely, acceleration equations; and step five: estimating product general distribution parameters under normal stress levels through extrapolation methods according to the acceleration equations, and obtaining product reliability functions under normal use conditions according to the estimated values of general parameters. According to the assessment method, gray system fitting product degradation path is utilized so that defects of other models are overcome and the prediction accuracy is improved.

The business method known as QAISys (Quality Assessment and Improvement System) is a process that rates comprehensively and continually the quality of medical images as determined by the interpreting radiologist. The output of this system conveys feedback from the radiologist to the performing technologist and his / her supervisor. This feedback enables medical radiologists, technologists, and managers to bridge any communication gaps between themselves in respect to the quality and effectiveness of medical images. It permits management to assess and track image quality for an entire medical imaging department by modality, location, and / or shift, and for each individual technologist. The QAISys method reveals the nature of recurrent quality failures and highlights which exam types need to be improved. QAISys then indicates practical, cost-effective means of assessing and improving the overall medical images for future patients.

The invention discloses a data quality management method and a data quality management system. The data quality management method comprises the following steps: managing a quality knowledge library; analyzing the data quality characteristics, and presetting a quality problem domain, a quality dimension domain, a quality rule domain and a quality standard domain; collecting quality information: selecting the quality dimension and the quality rules required by a user from the quality knowledge library, and extracting a data set meeting the user requirements from the original data sets; evaluating the data quality: evaluating the data quality according to the collected quality information, and generating and submitting a data quality report to the user or a quality manager according to the quality problem domain and the quality standard domain in the quality knowledge library; and improving the data quality: correcting the data quality problem detected in the evaluation of the data quality for improvement. The data quality management method and the data quality management system are applied to monitoring, evaluating and continuously improving the data quality in the whole hydrology industry based on the whole data processing procedure of the hydrology industry.

A system for receiving and processing data includes a data processing and verification component that accepts data from a client in an electronic format and identifies therefrom data elements that can be directly verified. A risk assessment component receives data elements that have not been identified as directly verifiable and assesses a risk that the data elements are incomplete or incorrect. The risk assessment component generates risk assessment data. A decision support component receives the risk assessment data from the risk assessment component and selects appropriate actions for subsequent processing of the client data according to the assessment of risk contained in the risk assessment data.

A data assessment system for ADS-B monitor technology is provided, which comprises an ADS-B airplane scale statistics module that keeps statistics of airplane scale with ADS-B airborne equipments and judges the number of ADS-B airplane, a monitor precision assessment module that assesses the precision of ADS-B position message data, compares the variance between ADS-B, radar position data and standard position in same time section and works out the conclusion of monitor precision, a reliability assessment module that assesses the reliability of ADS-B monitor data, calculates separately the missing dot rate of radar and ADS-B monitor data in same time section, compares them and reaches the conclusion about the reliability of ADS-B monitor data, a data integrity assessment module that assesses the integrity of ADS-B monitor data, a fake object possibility assessment module that assesses the fake object possibility of ADS-B position message data and works out the conclusion about the fake object possibility of ADS-B monitor data. Therefore, the invention, which is easy to be implemented in engineering, effectively realizes the data assessment for ADS-B monitor data.

The invention discloses a method suitable for power data quality assessment and rule check. The method comprises the steps of establishing a differential data quality comprehensive evaluation index system and a data quality rule check library for a device object of a specific region in a power system and for data describing a basic feature, a running feature and an event process of a power device; and automatically generating a multilevel data check rule set based on the rule check library according to to-be-checked power data, thereby realizing automated data monitoring and check. According to the method, the power data quality comprehensive evaluation index system and the data quality rule check library are established and the multilevel power data rule set is automatically generated, so that the features of differential power data are comprehensively assessed and comprehensively evaluated; and the method is of important significance for realizing data quality management control and forming a technical scheme and a long-term mechanism of data management.

The present invention relates to a multi-dimensional verification method for schedule plan data. The method comprises the following steps: step 1, designing a data quality analysis index; step 2, designing a data verification rule; step 3, performing multi-dimensional data quality verification; and step 4, performing data quality analysis. According to the multi-dimensional verification method for the schedule plan data provided by the present invention, multi-dimensional quantitative analysis is performed in aspects of a data type, a data volume, and a period of schedule plan data and the like, the verification rule in combination with schedule operating laws is formulated, the multi-dimensional verification method for data reliability, integrity, timeliness, conformity and consistency is designed, a data quality assessment system is put forward, and multi-source schedule plan data quality is improved, so as to meet statistical analysis requirements for fine-particle-size multi-source schedule plan data.

The invention discloses a multifunctional wisdom home care service platform. The multifunctional wisdom home care service platform comprises a health module, a life entertainment module and an abnormity monitoring module; the health module comprises a body data assessment sub module, a sport diet management sub module and a work and rest prompt sub module; the life entertainment module comprises a life service sub module and an entertainment service sub module; and the abnormity monitoring module comprises a video monitoring sub module and an emergency help-seeking response sub module. Through remote monitoring and an intelligent judgment, the problem, resulted from the fact that aging population in current society is in the majority, that manpower is not enough to care old people in real time is solved. Freedom, convenience and quality of the endowment of the old people are improved.

A location point determination apparatus comprises a geographic feature harvesting module (202) arranged to access and collect, when in use, geographic feature information associated with a predetermined named area datum. The apparatus also comprises a data assessment module (208) arranged to receive the geographic feature information collected by the geographic feature harvesting module and to evaluate from the geographic feature information collected in respect of at least one attribute of each geographic feature associated with the geographic feature information. The apparatus further comprises a selection module (210) arranged to select a geographic feature from the geographic features evaluated in accordance with a predetermined criterion associated with the evaluation of the geographic feature information.

Quality assessment of probe data collected from GPS systems is performed by a system and method of determining a value of data points provided by different vendors of such data. Incoming raw probe data is initially analyzed for removal of extraneous data points, and is then mapped to roadway links and smoothed out. The resulting output is processed to determine the coverage value of data provided by a given vendor and enable a comparison between different vendors. Such a model of probe data processing also enables an evaluation of a contribution of further vendors of raw probe data to an existing dataset. Additionally, a real-time performance evaluation of continually-ingested probe data includes building historical and data count profiles, and generating output data represented by a number of data points for a specific distance within a geo-box representing a geographical area, to project a value of raw probe data for a next incremental time period.

The invention discloses a processing method and system for power equipment to monitor abnormal data in an online manner. The method comprises the following implementation steps of carrying out abnormal data positioning analysis on an original data set, and selecting a DBSCAN clustering algorithm to carry out missing value filling to complete data cleaning or an abnormal data cleaning method basedon an association rule to complete data cleaning; calculating each data quality index value in a preset data quality evaluation system, and generating a data quality evaluation report; and displayingand outputting an abnormal data positioning analysis result and a data quality evaluation report. According to the invention, the accurate and effective cleaning of abnormal data can be realized; thecleaning effect is good, the visual display of the data quality before and after data cleaning can be realized, the proportion and the reason of abnormal data generation are statistically displayed, power grid workers can take corresponding measures to improve the data acquisition and uploading process, and the generation of abnormal data is reduced from the source, so that the workload of data processing is reduced, and the working efficiency and the accuracy are improved.

The present invention discloses a transformer substation energy efficiency assessment method based on an AHP (analytic hierarchy process). The method comprises: acquiring n index values for m to-be-assessed transformer substations; establishing an original index data matrix based on a gray relational analysis method, and carrying out standardized processing to generate a to-be-assessed index data matrix; establishing an index hierarchical structure, determining a relative weight,relative to a top level index, of each energy efficiency assessment index of a bottom layer of the index hierarchical structure to acquire a relative weight matrix; as for the to-be-assessed index data matrix, separately calculating an index value of each energy efficiency assessment index of each to-be-assessed transformer substation after the standardized processing, and a correlation coefficient between reference values of corresponding energy efficiency indexes in a reference line, thereby acquiring a correlation coefficient matrix; and calculating an integrated assessment result matrix of m to-be-assessed transformer substations. According to the method disclosed by the present invention, a reasonable degree of energy efficiency of the transformer substations can be analyzed, a power saving magnitude before and after reconstruction of the transformer substations can also be analyzed and assessed, so that the method has the advantages of high data assessment accuracy, and high-speed and efficient assessment.

A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

The invention provides a flow system and method for reliable multiparameter data acquisition and particle sorting. In accordance with the invention, a flow system assesses changes in the pattern of data collected in successive time intervals and actuates one or more corrective actions whenever the changes exceed predetermined limits. The present invention overcomes problems associated with collecting data and sorting and enumerating particles in flow cytometry systems that operate for prolonged periods or that must accommodate samples that vary widely in quality.

A system for receiving and processing data includes a data processing and verification component that accepts data from a client in an electronic format and identifies therefrom data elements that can be directly verified. A risk assessment component receives data elements that have not been identified as directly verifiable and assesses a risk that the data elements are incomplete or incorrect. The risk assessment component generates risk assessment data. A decision support component receives the risk assessment data from the risk assessment component and selects appropriate actions for subsequent processing of the client data according to the assessment of risk contained in the risk assessment data.

A system for receiving and processing data includes a data processing and verification component that accepts data from a client in an electronic format and identifies therefrom data elements that can be directly verified. A risk assessment component receives data elements that have not been identified as directly verifiable and assesses a risk that the data elements are incomplete or incorrect. The risk assessment component generates risk assessment data. A decision support component receives the risk assessment data from the risk assessment component and selects appropriate actions for subsequent processing of the client data according to the assessment of risk contained in the risk assessment data.

The invention discloses a quality assessment method of multi-source position trajectory data based on AHP and mainly relates to the technical field of data quality assessment. The method comprises thesteps of (S1) making a dynamic data quality assessment process with a feedback mechanism, (S2) determining an assessment index system of quality data according to the data quality assessment process,(S3) establishing a corresponding data quality assessment model according to the assessment index system, (S4) determining a single-resource location trajectory data quality assessment index weight according to the data quality assessment model, (S5) determining a multiple-resource location trajectory data quality assessment index weight according to the data quality assessment model, and (S6) applying the data quality assessment model to measure the data quality. The method has the advantages that the method can be adapted to quality assessment requirements of multiple-source and heterogeneous data sources by various applications in the era of big data, proposed assessment indexes are quantifiable analysis indexes, and the development of subsequent quality assessment software is facilitated.

The application provides a data assessment system and method. The system comprises a data acquisition unit used for acquiring to-be-assessed data, a quality determination unit used for determining a quality assessment result of the to-be-assessed data according to an index value of the to-be-assessed data in a preset data quality index, and a value assessment unit used for determining an assessment result of the to-be-assessed data according to the index value of the to-be-assessed data in the preset data value index aiming at the condition that the quality assessment result is in accordance with a preset quality assessment requirement. According to the system and method, during data assessment, the quality of business data can be determined objectively and accurately, human participationis avoided in a determination process of the quality of the business data, the possibility of human leakage of the business data is reduced, and the security of the business data in an assessment process is improved.

The present invention provides a face quality evaluation method based on three dimensional point cloud data. The main content of the method comprises inputting the three dimensional face point cloud data; detecting a face specific area in the three dimensional face point cloud data; carrying out the data registration on the detected face specific area; carrying out the depth face data mapping on the registered three dimensional face point cloud data and carrying out the face depth data quality evaluation on the depth face data. According to the present invention, by utilizing the face specific area detection at a point cloud layer and utilizing the template data verification at a depth data layer, the three dimensional face data quality is evaluated, thereby being able to determine whether the acquired three dimensional data satisfies the face identification quality, effectively evaluating the face data quality layer by layer from the point cloud data space to the depth image space, and guaranteeing the quality of the data applied to a face identification algorithm.

The invention discloses an intelligent table tennis training system. The intelligent table tennis training system comprises a table tennis ball fall point position data acquisition module, a table tennis ball motion trajectory data acquisition module, a motion state acquisition module, an action standard assessment module, an action guidance suggestion output module, a comprehensive assessment module and a central processing unit. By acquiring table tennis ball motion trajectories, table tennis bat motion trajectories and motion trajectories of the hands, paces and bodies of athletes, monitoring of table tennis training process is achieved on multiple aspects, the system provides a training data assessment function, provides guidance suggestions for formulation of training schemes, accordingly makes training more targeted and greatly improves the training efficiency. A holographic projection form is adopted in the later explaining process to play historical training data or teaching guidance data, repeated viewing, emulation and understanding of a trainee to all actions are greatly facilitated, the training efficiency is improved, and meanwhile the working amount of training is also decreased.

The invention relates to a method and device for point cloud measurement data quality evaluation optimization. The method comprises the following steps that point cloud measurement data is obtained, wherein the point cloud measurement data comprises external calibration parameters of measurement tools and time deviation parameters; a Gauss hybrid model for probability distribution of source positions of the point cloud measurement data is established, a value function is established according to entropy of the Gauss hybrid model, and the quality of the point cloud measurement data is evaluated with the value function; evaluation scores of the value function are optimized, and optimal time deviation parameters are obtained; the external calibration parameters are optimized according to the optimal time deviation parameters, and optimal external calibration parameters are obtained. The problem that in the prior art, the quality of certain measurement tools, especially point cloud measurement data is not good enough is solved.