47results about How to "Fast data analysis" patented technology

An enterprise vulnerability management application (EVMA), enterprise vulnerability management process (EVMP) and system. In one embodiment, the EVMP may include executing computer software code on at least one computer hardware platform to receive login information from a user, inventory current information technology assets of the enterprise, conduct vulnerability scanning of the inventoried information technology assets, analyze vulnerability correlation and prioritization of the information technology assets, remediate one or more vulnerabilities of the information technology assets, and report to the user about the vulnerabilities and remediation undertaken. As part of the analysis, one or more vulnerability scores such as, for example, Common Vulnerability Scoring System (CVSS) scores, may be generated from base score metrics, temporal score metrics and environment score metrics.

Assessment devices, and teaching methods involving the use of the assessment devices, are disclosed. The assessment devices include iterative homework, quizzes, and/or tests, each of which allows for individual students to answer an initial question, and, based on the answer to that question, the next question will be harder or easier. The assessment devices can be administered to the students in print form, or electronically, such as on a computer or a personal digital assistant. Once the data is collated, students can be screened based on their ability to grasp all or a portion of the questions in a given test, and separated into groups based on their understanding of the subject matter. Teachers can then individually teach the different groups of students, ideally using lesson plans designed to work in tandem with the assessment devices, based on the students' grasp of the material.

A computer system and method for securing files in a file system equipped with storage resources that are accessible to an authenticable user operating with an untrusted client device under the semi-trusted client threat model. The file to be secured is stored in one or more blocks belonging to the storage resources along with symmetric per-block key(s) KB_i assigned to each of the blocks in the file. The blocks are encrypted with the symmetric per-block keys to obtain encrypted blocks. The user is assigned user key(s) and each per-block key that was used for encryption is in turn encrypted with one of the user's keys to derive wrapped key(s) for each encrypted block. Wrapped key(s) are placed in encrypted block headers and introduce a level of indirection to encrypted file(s) that is appropriate for the semi-trusted client threat model.

The present invention relates to a system for quickly receiving and distributing power transmission and transformation equipment state monitoring big data, comprising a master control node, a plurality of data nodes, and a subscription process node, wherein the master control node receives monitoring data from an electric power system, establishes a mapping relation between subscription processes and data priority queues, and comprises a load equalizer, the load equalizer uniformly transmits data required to be distributed to the plurality of data nodes according to the mapping relation; each data node assigns a unique id to each received message, each data priority queue corresponds to one index table in a memory of the data node, each row of the index table corresponds to one message box, the value of the row is the id of the first message in the corresponding message box; and the subscription process node obtains subscribed monitoring data from the data nodes. The system of the present invention designs a distributed message buffer queue which takes data priority into account by means of a burgeoning memory cluster technology, thereby achieving quick collection, caching and effective distribution of monitoring big data.

The invention discloses a flow two dimension velocity field measurement method and a flow two dimension velocity field measurement device based on near field scattering. The flow two dimension velocity field measurement device based on the near field scattering comprises a laser, a space filter, a collimating lens, a lens group, a CCD (charge coupled device) camera and a computer. Compared with the prior art, the flow two dimension velocity field measurement device based on the near field scattering has the advantages of being pretty simple in structure, low in demand for light path centering, and capable of achieving the purpose of effectively removing stray light under the circumstance that a complex device for eliminating central light strength is not needed. The particle diameter of tracer particles needed by a measurement technology used in the flow two dimension velocity field measurement method based on the near field scattering can be less than the wavelength of incident light emitted from the laser, and concentration of the tracer particles is high, and therefore the measurement technology can be used in measurement of a nanometer fluid flow two dimension velocity field. The measurement technology is simple and quick in data analysis, can achieve online measurement, and guarantees that accuracy and linearity of the flow two dimension velocity field measurement method based on the near field scattering are not limited by the particle diameter and the concentration of the tracer particles by using a differential processing method.

The invention discloses a data fusion based portable lightweight human brain state detection method. The method includes: acquiring original electroencephalogram signal data of N channels by electroencephalogram signal acquisition equipment, and preprocessing the original electroencephalogram signals data; subjecting the preprocessed original electroencephalogram signals data to blind source separation to obtain signals of multiple signal sources, and performing feature extraction on the signals of each signal source on the basis of wavelet packet transform; inputting each signal source into aplurality of well trained lightweight convolutional neural network models to analyze, and subjecting outputs of the multiple lightweight convolutional neural network models to weighted voting to obtain a final classification result. The lightweight convolutional neural network models take features obtained through wavelet packet transform of each signal source as inputs and take signal source types as outputs.

The invention discloses a Wifi probe and a data balanced collection system and method. The data balanced collection method includes the steps that the Wifi probe sequentially scans Wifi channels in a detection area of the probe in a rotary mode to obtain broadcast data packages of devices in the Wifi channels; the Wifi probe uploads the obtained broadcast data packages to a server. By means of the rotary scanning mode of the Wifi channels, different scanning time is allocated to different Wifi channels according to a single factor or multiple factors so that the balance degree of data collection can be guaranteed to the largest extent; before the data is uploaded to the server, the data is preprocessed, invalid information in the data is removed, only valid information is kept, the data transmission magnitude can be greatly reduced, the transmission cost is reduced, and subsequent quick and accurate data analysis is benefited.

The invention discloses a blade top air injection stability controller for an axial flow compression system. The controller comprises a processor, an eight-way high-speed analog signal acquisition module, a six-way analog signal acquisition module, a frequency signal acquisition module, a communication module, a pulse output module, an eight-way high-frequency-response proportional electromagnetic valve driving module and a power module. A plurality of sensors are symmetrically arranged on the wall faces of a casing and used for detecting front stall omen signals during operation of the axial flow compression system by adoption of signal analysis means. The controller transmits displacement signals to the high-frequency-response proportional electromagnetic valve driving module to reasonably control openness of a high-frequency-response proportional electromagnetic valve so as to control air injection volume in real time, and the blade top air injection volume is gradually increased along with operating conditions approaching to a stall point, so that energy is saved while improvement of instability margin can be effectively realized. The controller can control air injection volume in real time to enable the axial flow compression system to have wider flow and pressure ratio operating range on the premise of energy conservation.

The invention relates to the technical field of optoelectronic devices and discloses an angular accuracy computing and tracking accuracy assessing system and method. The system comprises a timing system unit, a data processing component, a rotating shaft system, a collimator component and an adjustable reflecting mirror. The collimator component and the adjustable reflecting mirror are arranged on a rotating arm of the rotating shaft system and are adjusted dynamically. The data processing component uses signals of the timing system unit for computing angular accuracy and accessing tracking accuracy according to motion data information of the rotating shaft system and target data information sent by an optoelectronic device to be detected. According to the system and method, testing covering most part of a view field can be completed only in an inner field, data analysis can be completed quickly, compared with an outer field fly-detecting testing mode, implementation cost is very low, implementation difficulty is small, and testing accuracy is high.

The invention discloses an intelligent traffic management system. The system comprises a data collection module (100), a vehicle-mounted control module (200), a data transmission module (300), a central control module (400) and a memorizer module (500), wherein the data collection module (100) is used for collecting data of logo information, vehicle information and human body information, the vehicle-mounted control module (200) is used for analyzing and processing the logo information, the vehicle information and the human body information and generating analytic data and a processing result,the data transmission module (300) is used for transmitting the analytic data and the processing result to the central control module (400), the central control module (400) is used for transmittingthe analytic data, the processing result, a classification result and a grading result to the memorizer module (500), and the memorizer module (500) is used for storing the analytic data, the processing result, the classification result and the grading result. The intelligent traffic management system can be used for providing a driver with relevant prompt through hierarchical early warning and warning, thereby reducing accident happening risks and alleviating traffic pressure in a city.

The invention discloses an intelligent vehicle-mounted manager. The manager comprises a data acquisition device used for collecting identification information, vehicle information and human body information, a data classification device used for classification of collected data, a data processing device used for judging whether the operation of a vehicle meets the requirements of road markings andtraffic signs or not, judging whether the vehicle information and the human body information exceed the set threshold or not and generating prompt information, a grading device used for classifying the prompt information and generating early warning information or alarm information, an early warning device used for generating early warning signals or alarm signals, a data base used for storing road marking requirements, traffic sign requirements, vehicle information thresholds, human information thresholds and grading standards and a display device used for feeding back the warning signals oralarm signals to a driver. The manager can detect hidden dangers in the course of vehicle operation in time, provide relevant hints to the driver by grading early warning and alarm, and reduce the risk of accidents.

The invention provides a syndrome biological information data analyzing system and subsystems thereof. The syndrome biological information data analyzing system comprises a server and a plurality of subsystems, wherein each subsystem comprise a syndrome biological information data analyzing module, a display module, an input module and a management module. The syndrome biological information data analyzing module stores syndrome biological information data and provides data information analysis and visible charts for users; the display module displays the analysis results and charts in an image-text form; the syndrome information data, the analysis mode and the form of the visible charts are chosen in the input module; and the management module distributes the operating authority to researchers. Therefore, the syndrome biological information data analyzing system can share the syndrome information data on line, realize the cooperation of different regions and different research groups, conveniently carry out upgrade, and also provide the automatic field defining function, thereby realizing the diversity and the flexibility of data collection and analysis.

The invention discloses a data transmission method and system between a memory database system and a data warehouse system. The data transmission system comprises the memory database system, the datawarehouse system, a data loading module and an SQL data management system. The data loading module is used for loading a data event into the memory database system; the memory database system sends adata event to the SQL data management system; and the SQL data management system transmits the received data event to the data warehouse system, and the data warehouse system stores the data event andsends a query signal to the memory database system so as to query the data event which is not stored in the data warehouse system. The method and system have the advantages that the limitation of a big data/rapid data system can be overcome, so that better, more comprehensive and faster data analysis can be realized.

A detection method of residue a nitrogen-containing pesticide based on infrared photoacoustic spectroscopy is as follows: (1). collecting infrared photoacoustic spectroscopy data of a sample, to be more specific, using an infrared photoacoustic spectroscopy instrument, selecting appropriate parameters such as moving mirror speed and scanning times, and collecting the infrared photoacoustic spectral data of the sample; (2). performing pre-processing including wavelet analysis for smoothing and noise reduction, data normalization, and the like on the infrared photoacoustic spectral data obtainedin the step (1) to obtain an infrared photoacoustic spectral curve of the sample to be tested; (3). performing analysis including characteristic peak position identification and principal componentanalysis on the spectrogram obtained in the step (2); and (4). analyzing results, to be more specific, by combining the molecular structure of a pesticide, analyzing the spectrogram obtained in the step (3), and determining the position of an infrared absorption peak of a specific functional group in the molecular structure of the pesticide to be tested; and comparing the sample and contrasting that whether an infrared absorption peak occurs at the position, finally determining the type of the pesticide residue. The method can realize rapid, non-destructive and in-situ detection of agricultural products, and can be quickly developed into rapid on-site detection.

The invention provides a correlation judgment method for wafer test parameters, which comprises the following steps of: acquiring data to obtain N test parameter groups; performing data preprocessing on the N test parameter groups to obtain N first parameter groups; carrying out dimensionality reduction on the N first parameter groups to obtain N second parameter groups; determining the number k of the N second parameter groups to be grouped to obtain k initial centroids; and automatically grouping and carrying out correlation judgment. By adopting the method, the correlation of wafer test parameters under different test methods can be automatically identified, a wafer test parameter group with high correlation can be quickly found, data analysis can be quickly performed, and time and cost are saved; and the accuracy of yield analysis can be further improved. The invention further provides a system for judging the correlation of the wafer test parameters. The system has corresponding advantages due to the adoption of the method for judging the correlation of the wafer test.

The invention relates to a white tea manufacturing time determination method based on year white tea characteristic compound, which belongs to the technical field of tealeaves determination. The method comprises the following steps: establishing a linear equation of the content of 8-CN-ethyl-2-pyrrolidone-substituted epigallocatechin gallate in white tea and white tea manufacturing time, and substituting a determined quantitative result of the 8-CN-vinyl-2-pyrrolidone-substituted epigallocatechin gallate in an unknown white tea sample into the linear equation, thus obtaining a predicted valueof the manufacturing time of the white tea sample. The method provides effective technical support to the determination of the manufacturing time of the market available white tea. The method has theadvantages of simplicity in operation, data quantification, objective result and high determination accuracy.

The embodiment of the invention relates to a fault prediction method and prediction system, the fault prediction method is applied to a server, and the prediction method comprises the steps: obtaining charging data when a charging pile fails; performing feature extraction on the charging data to obtain feature charging information corresponding to each charging pile fault; dividing each charging pile fault into a corresponding preset fault type through fault qualitative analysis so as to generate a training sample set of each preset fault type; and training according to the training sample sets to generate fault models corresponding to the preset fault types, wherein the fault models are used for fault prediction of the charging pile. According to the embodiment of the invention, the effective data in the charging data can be accurately obtained through the feature extraction step, and the corresponding fault models are established for different preset fault types, so that the data analysis speed can be further improved, and the fault prediction efficiency and maintenance efficiency of the charging pile are improved.

The invention relates to a transient thermal state online evaluation method and device based on a reduced-order model, and a medium. The method is used for thermal coupling state evaluation of a complex structure in industrial equipment, and the evaluation method comprises the following steps: firstly, establishing a parameterized numerical model for operation parameters of the industrial equipment structure in an offline stage; then obtaining different types of data sets in the thermodynamic analysis process through parameterized numerical simulation, and carrying out feature analysis and extraction; and finally, establishing a complete reduced-order simulation model based on a finite element discrete model, and performing online correction and state evaluation of working condition parameters in combination with sensor measurement data in an online stage. Compared with the prior art, the invention has the advantages that various physical states of the transient nonlinear thermal coupling problem can be quickly and accurately obtained, and quick data analysis and theoretical support can be provided for state evaluation of an industrial equipment structure.

The invention discloses a TLV format protocol fast parsing method based on C language. The invention belongs to the technical field of TLV format protocol parsing, which makes the network request speed between the 2G network connection client and the server fast, the network communication ability strong, the network data exchange fast and the TLV format data parsing fast. A compiler and a parser are arranged on the client, and a compiler and a parser are arranged on the server, so that both the client and the server have the coding ability and the decoding ability at the same time; Client andserver realize data exchange between client and server through socket long link module. The TCP/TP transport protocol is encapsulated in the transport layer, and then the data stream of data object tlv format is used to transmit the data of 2G network, so as to realize the fast data exchange between the client and the server. The parser is equipped with a TLV data parsing interface which can deserialize a piece of data in TLV format into a struct type data parsing interface.

The invention discloses a block chain data supervision system and method, and relates to the technical field of block chains, a data filtering module is set, a coding main body department of a data stream is optimized and shortened, the optimization of a coding main body is realized, each data node forms an index link sequence, and the index link sequence is divided into a plurality of data nodes; an optimized data stream is formed with the optimized coding main body, the optimized coding prefix and the optimized coding suffix, so that the coding main body information of the data stream can be hidden, and the information in the data stream can be better protected; by arranging a data distribution module, the data streams generated in the system are divided according to the data magnitude, then the data streams of different data magnitudes are sent to the corresponding data processing modules, and the situation that the data magnitude is far beyond the processing capacity of the data processing modules or far less than the processing capacity of the data processing modules, therefore, the data processing capacity in the data processing process is not matched with the data processing capacity is avoided.

The invention discloses a data analysis method, computing equipment and a storage medium, and the data analysis method comprises the steps: selecting a target grouping dimension from a plurality of data grouping dimensions; extracting source data from the source data table, and performing offline calculation on the source data according to the target grouping dimension to obtain an offline calculation result corresponding to the target grouping dimension; wherein the source data in the source data table is real-time data obtained by performing data volume loading on log data generated by the business server according to a plurality of data grouping dimensions; and in response to a data analysis query request containing the target grouping dimension, fusing the offline calculation results corresponding to the target grouping dimension to obtain a data query result. According to the scheme, the offline calculation result corresponding to the target grouping dimension is obtained by utilizing the offline calculation mechanism, and the offline calculation result corresponding to the target grouping dimension is fused, so that the data query efficiency is improved, and the resource consumption of data analysis is reduced.