39results about How to "Expand the scope of the data" patented technology

The invention discloses a Bayesian reliability comprehensive estimation method based on multisource degraded data, which comprises the following steps of: 1. collecting multisource degraded data; 2. establishing a degraded statistic model and confirming a reliability function; 3. preprocessing the degraded data; 4. confirming and fusing prior distribution and posterior distribution; and 5. estimating the reliability of a product. The invention provides a method for establishing the degraded statistic model, which converts a form of the degraded data by carrying out transformation processing on the performance degrading model of the product and leads the degraded data which is not submitted to probability distribution to submit to the probability distribution, thereby leading the Bayesian method for commonly processing life data to be capable of processing the degraded data and realizing the Bayesian statistic estimation based on the degraded data; accordingly, the Bayesian method is introduced into the estimation method of an degradation accelerating test, and the estimation method of the degradation accelerating test is expanded.

A voice search and analysis system comprises a voice transcription module, an index establishing module, a voice search module and a test analysis module. Keywords contained in voice, positions where the keywords appear and other characteristic information are searched for. Analysis can be effectively performed on massive voice recording files and audio files through voice analysis, knowledge exploration in the voice and rapid search on the voice files are achieved, and the problems that voice data are difficult to search for and analyze are solved.

The invention relates to a big-data analysis system. According to the system, various data collection manners can be utilized to collect data; an encrypted data signal is formed by the collected datathrough encryption processing; the encrypted data signal is transmitted to a data storage module through a data transmission module; the encrypted data signal is transmitted to a data analysis serverby the data storage module; and in the data analysis server, firstly, the encrypted data signal is decrypted through a data decryption module, detection, marking, classification and analysis are sequentially carried out on a decrypted data signal through a data detection module, a data marking module, a data classification module and a data analysis module, then a data analysis result is obtained,the data analysis result obtained by the data analysis module is evaluated through an evaluation module, and finally, deviation correction is carried out on an unqualified data analysis result through a correction module. Accuracy of the big-data analysis system is improved.

The invention discloses a liquid viscosity transmission tester with a hydraulic load device. The liquid viscosity transmission tester with the hydraulic load device comprises an oil supplying system and a simulation load loading system; an oil supplying system loop is connected with an oil supplying oil path coarse filter, a gear oil pump, an overflow valve, a speed regulating valve, a cooler, a liquid viscosity host, a flowmeter and an oil tank in sequence by a hydraulic pipeline. According to the simulation load loading system, a vane pump is adopted to replace the load device to load; the liquid viscosity host drives the load vane pump to work by the connection of a coupler; a simulation load loading system loop is connected with a load oil path coarse filter, the vane pump, a pilot operated compound relief valve and the oil tank in sequence by a hydraulic pipeline. The liquid viscosity transmission tester with the hydraulic load device is suitable for the test research of a liquid viscosity transmission technology, the system is greatly simplified while the basic demands of the test are met, so the system structure is deeply optimized and the design cost and the manufacturing cost are saved; the load loading system is closer to an actual working condition, so the system is more practical and reliable and has broad use value.

The invention discloses a multi-RGB-D full face material recovery method based on deep learning. The method comprises two steps of face material information estimation based on an image and gradient optimization based on differential rendering. The method comprises the following steps: step 1, firstly preprocessing geometric and texture data to generate a mask containing a full-face skin part; then constructing a texture estimation module and an illumination estimation module, and generating a simulation training data set; and finally, obtaining initial values of texture information and illumination coefficients by using a material texture and illumination estimation module and the simulation training data set. step 2, firstly processing and scanning geometric data, and then expanding to realize a full-face rendering equation; improving the loss function to obtain an optimization result; and finally, performing detail optimization on the special region. According to the invention, the data range of the face material recovery technology can be expanded, and the optimization effect of the material recovery technology is improved.

The disclosure provides an interface prototype data generation method and computer equipment. The method comprises following steps: loading business model data of an enterprise, wherein the business model data comprises a data model, a product model, a process model and an interface experience model; establishing a first constraint relationship between the data model and the process model by checking the data entities establishing a second constraint relationship between the product model and the process model by checking the customer-product-channel CPC adaptation model; generating interface prototype data according to the data model, the product model, the process model, the first constraint relationship, the second constraint relationship and the interface experience model. According to the method and equipment of the disclosure, flow model data is introduced during the process of interface prototype data generation, and constraint relationships are built up between the flow model and the product model and the data model, which substantially improve the accuracy of data expression of interface prototype for relative business model data.

This disclosure relates to techniques for supporting wireless communication using an anchor carrier and data carriers. A wireless device may attach to a cellular network via an anchor carrier. The wireless device may receive data transfer scheduling information from the cellular network via the anchor carrier. The data transfer scheduling information may indicate a data carrier on which data transfer is scheduled. The wireless device may receive data for the data transfer via the data carrier.

The invention discloses an elastic scaling method based on load regression prediction in a cloud environment and a readable storage medium, belongs to the field of elastic scaling of computing resources, and aims to solve the technical problem of how to predict the user load in the next time period and reasonably adjust the computing resources of a user according to the load. The method comprisesthe following steps: acquiring historical data of normal operation of a user service in a period of time, and constructing a training data set; based on the training data set, training a regression model, calculating the load of the next moment through the trained regression model, training a linear model between the calculation resource usage amount and the load, and calculating the calculation resource usage amount of the next moment through the trained linear model; and optimizing the user cost by taking the computing resource usage amount at the next moment as a limiting condition to obtain a computing resource configuration target solution set, rearranging the computing resource configuration target solution set and the computing resource configuration current solution set, calculating to obtain a difference, and selecting a proper horizontal telescopic mode or vertical telescopic mode based on the difference.

Embodiments of the invention provide an information search method which is applied to search services. The method comprises the following steps: receiving website information added on a user terminal, creating self-defined search engines corresponding to the website information and classifying the created self-defined search engines; receiving an information search request from the user terminal, extracting a keyword in the information search request, determining whether a self-defined search engine agreeing with the text type of the keyword exists or not, and sending the keyword into the self-defined search engine agreeing with the text type of the keyword to search so as to obtain a search result when the self-defined search engine agreeing with the text type of the keyword exists; returning the search result to the user terminal. According to the information search method, the search process has stronger pertinence and the search result agrees with the user expects better.

A storage controller changes a block size to carry out a shredding process. A data shredder uses a large block size set by a block size setting part to write shredding data in a storage area of a disk drive and erase data stored therein. An error arising during the writing operation of the shredding data is detected by an error detecting part. When the error is detected, the block size setting part sets the block size smaller by one stage than the initial block size to the data shredder. Every time the error arises, the block size used in the shredding process is diminished. Thus, the number of times of writings of the shredding data is reduced as much as possible to improve a processing speed and erase the data of a wide range as much as possible.

The invention discloses a data analysis system. The data analysis system comprises a data acquisition subsystem, a data storage subsystem, a data processing subsystem, a data analysis subsystem and a data presentation subsystem. The data acquisition subsystem is used for acquiring data and transmitting the data to the data storage subsystem; the data storage subsystem is used for storing the data acquired by the data acquisition subsystem; the data processing subsystem is used for cleaning, converting, extracting and calculating the data in the data storage subsystem; the data analysis subsystem is used for carrying out statistical analysis and deep mining on the data processed by the data processing subsystem; the data presentation subsystem is used for presenting the data processed by the data analysis subsystem in the form of tables or images or characters. According to the data analysis system, the data is acquired, stored, processed and analyzed, then the analyzed data is presented to a user in the form of characters or images or tables or the like, the purpose of data integration is achieved, and fastness and visualization are achieved.

The invention discloses a seven-class skin tumor detection method applied to Web, which combines the weight of a model with a Web end based on a model migration technology taking Tensorflow as an intermediary agent, so that the model can normally and quickly run in a browser environment familiar to a user, and meanwhile, a model result is visualized. The model uses an optimized Inception-ResNetV2classification network to propose a skin tumor classification method for skin tumor images. Seven types of skin tumors can be detected through the method so that the ideal effect is achieved, and doctors can be effectively assisted in diagnosis. According to the Web end development method for detecting the seven types of skin tumors, the process of detecting the skin tumors is simplified, the obtained probability result is responded to the client browser, rendering visualization is conducted through the browser, and therefore a doctor and a patient can obtain the detection result in real timeonly by simply operating the Web end.

The invention discloses an improved association rule report data mining method based on mutual exclusion expression, relates to a knowledge discovery and data mining method in the field of data science, and solves the problems of high memory consumption and low efficiency when a traditional association rule algorithm processes massive data. The method comprises the steps of 1, converting data intotransaction data based on a data threshold range, and obtaining a binary sparse matrix with grouping labels based on data logic; 2, obtaining a set in which all frequent items are 1, and removing a non-frequent item set to obtain a new grouping result; and 3, performing self-connection iterative search on the frequent item set to search the frequent item set, and cutting and iterating the candidate item set until a new frequent item set cannot be generated, thereby obtaining an association rule mining result. The basic idea of the method is to convert structured data into transaction data, generate groups based on a mutual exclusion relationship, and perform rule mining, thereby reducing the computing memory and improving the computing efficiency. The application scene is wide, and the social and economic values are very high.

The invention discloses a data transmission method based on logstash + kafka, which comprises operation of service data producing end and operation of service data consuming end. 1) automatically collecting the service data in the service system database through the service data production terminal logstash, and transmitting the service data to the middleware kafka; 2) the middleware kafka collects the data transmitted by each service data producing end and uniformly sends the data to the service data consuming end logstash; 3) the service data consuming terminal logstash receives the messageof the middleware kafka, converts the message into a data file, and stores the message in the target database. Compared with the prior art, the invention has the advantages of simple configuration andoperation, high processing speed, and can effectively realize the operation of collecting, processing, storing and the like of the dispersed service data, and can quickly and conveniently build the transmission channel between the service data production end and the service data consumption end, and has good expansibility, and reduces the difficulty of development and operation and maintenance. The invention has the advantages of simple configuration and operation, high processing speed, and effectively realizes the operations of collecting, processing, storing, etc.

The invention relates to a method for serial data transmission in a bus system having at least two bus nodes, which exchange messages by means of the bus, wherein the sent messages have a logical structure as per CAN standard ISO 11898-1, wherein the control field of the messages comprises more than six bits, in deviation from CAN standard ISO 11898-1, if a first marker (EDL) is present and the data field of the messages can comprise more than eight bytes, in deviation from CAN standard ISO 11898-1, if the first marker (EDL) is present, wherein the values of the four bits of the data length code are interpreted at least partially in deviation from CAN standard ISO 11898-1 in order to determine the size of the data field, and wherein if a second marker (BRS) is present, the bit length for at least one specified or specifiable range within the message assumes a value that is shortened compared to the bit length used before the presence of the second marker, wherein the range begins with the second marker at the earliest and ends with the CRC delimiter at the latest and the second marker (BRS) appears only if the first marker (EDL) is present and occurs in the control field of the messages that comprises more than six bits in deviation from CAN standard ISO 11898-1.

The invention discloses a method and a device for replaying a disk service, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: loadingbackup service data of a to-be-replayed service in each time period to a local database; determining the service data of a corresponding time period after loading is completed, and reading the servicedata of the corresponding time period from the local database through a section program; and according to the read service data of the corresponding time period, executing the operation of the reframing service according to the service logic of the to-be-replayed service. The difference between the duplication system logic and the original system logic during duplication can be reduced, the duplication system logic is consistent with the original system logic without clone service, the accuracy of system logic restoration and the reliability of a duplication result are improved, the difficulty of system duplication is greatly reduced, the data preparation work before duplication is omitted, a lot of time is saved, the data access speed is increased, and the system duplication efficiency and the overall performance of duplication are improved.

The invention relates to a vector data processing method in a WebGIS management system. According to the vector data processing method of the WebGIS management system, a coordinate system in the WebGIS management system is determined through a reference surface and map projective parameters; a data ellipsoid is a WGS84 (world geodetic system 1984) ellipsoid, namely, a geocentric coordinate system, which is a plane coordinate system in units of meters; projection transformation is performed in the last step; a scale larger than or equal to 1: 500,000 or a BJZ54 (Beijing 54) coordinate system is utilized. The vector data processing method in the WebGIS management system has the advantages that the projection mode has no angle change, no obvious length change and no obvious area change, avoids negative value of the abscissas and has a relatively large data range.

The invention belongs to the field of biomedical cell tissue culture and experiments, and discloses a stimulation culture device and a stimulation culture method for applying two stresses including atraction force and a pressure to cells, controllable time sequences are realized for a culture chamber to respectively realize pressurization and pressure extraction, and the same-frequency stretchingand retraction of an elastic culture cavity are matched to realize the joint stimulation of any pressure and tensile strain on the cells in a controllable range, and a simple and effective device anda technical scheme for forming strain and pressure on the cells by the tensile force and carrying out linkage adjustable stimulation culture on the cells at the same time are provided.

A data processing apparatus comprises a holding unit configured to hold filter coefficients of a transferred filter, a generating unit configured to generate an extended filter by extending a size of the transferred filter while sequentially reading out the filter coefficients held in the holding unit, and an arithmetic unit configured to perform convolution by using filter coefficients of the extended filter.

The invention discloses a model construction method for repeated incoming call analysis and recognition. The model construction method comprises the steps: translating voice into text contents, recording the text contents in a single work order table, and judging repeated incoming calls through the analysis of the call contents between a seat person and a customer; judging in combination with theacceptance content and the processing condition in the work order content, and judging that the incoming call is a repeated incoming call when a specified character is contained; judging the main workorder and the associated work order with the same telephone number in the associated work order table as a group of repeated incoming calls, marking the work order as a mother work order, and markingother work orders as child work orders; and extracting the work order of which the information recorded in the work order acceptance content is that ' the associated work order number is ' but is notincluded in the associated work order table. The model construction method introduces the idea of processing the structured work order information and the idea of processing the unstructured text content to repeated incoming call recognition, expands the data range for repeated incoming call recognition, and guarantees the improvement of the model coverage rate and accuracy.

The embodiment of the invention discloses a contact person information processing method and device, a computer device and a readable memory medium and is used for improving the accuracy of an estimation result for an object expected to be contacted by a user in a process of preferentially recommending contact person information. The method provided by the embodiment of the invention comprises the steps of recording latest contact person information of a first communication application, wherein the latest contact person information comprises a first identity identifier of a latest contact person of the first communication application in the first communication application; searching a corresponding second identity identifier of the first identity identifier in a second communication application according to an identity identifier corresponding relationship; and preferentially displaying first communication selection information corresponding to the second identity identifier in the second communication application, wherein the first communication selection information is used for selecting the contact person corresponding to the second identity identifier as an object with which a user of a terminal communicates through the second communication application when a selection instruction for the first communication selection information is received.

The invention discloses a positioning method and a positioning device based on drive test frequency spectrum data and a storage medium. The method comprises the following steps: acquiring drive test frequency spectrum data acquired at a plurality of sampling points; acquiring preset positioning demand information; extracting corresponding personalized signal data from the drive test frequency spectrum data based on the preset positioning demand information; determining a to-be-positioned area; obtaining a preset optimization solving rule; and analyzing the personalized signal data in the to-be-positioned area based on the preset optimization solving rule to generate a positioning result. Positioning is carried out by directly adopting the drive test frequency spectrum data, and the accurate positioning result is determined through the optimization solving rule, so that the positioning difficulty is effectively reduced, the positioning accuracy and the positioning efficiency are improved, and the actual positioning requirement is met.

The invention provides a road design environment exploration vehicle and a use method thereof, and relates to the technical field of exploration vehicles. The road design environment exploration vehicle comprises side plates, wherein the two side plates are fixedly connected through a first connecting rod; a first connecting block is fixedly arranged on the upper surfaces of the two side plates; a spring is fixedly connected onto the upper surface of the first connecting block; a first connecting plate is fixedly arranged at the upper end of the spring; a second connecting plate is fixedly arranged on the upper surface of the first connecting plate; a rotating assembly is arranged in the second connecting plate in a rotating matching way; one end of the second connecting plate is fixedly provided with a distance measuring instrument through a second connecting rod; one end, far away from the distance measuring instrument, of the second connecting rod is fixedly provided with a survey camera; and a connecting shaft penetrates through one end, far away from the survey camera, of each of the two side plates. The multi-angle rotating effect is achieved by changing the rotating angle of the survey camera, so that the survey data range is expanded; meanwhile, the labor investment is reduced; and the survey efficiency is improved.

The invention relates to a big-data analysis system. According to the system, various data collection manners can be utilized to collect data; an encrypted data signal is formed by the collected datathrough encryption processing; the encrypted data signal is transmitted to a data storage module through a data transmission module; the encrypted data signal is transmitted to a data analysis serverby the data storage module; and in the data analysis server, firstly, the encrypted data signal is decrypted through a data decryption module, detection, marking, classification and analysis are sequentially carried out on a decrypted data signal through a data detection module, a data marking module, a data classification module and a data analysis module, then a data analysis result is obtained,the data analysis result obtained by the data analysis module is evaluated through an evaluation module, and finally, deviation correction is carried out on an unqualified data analysis result through a correction module. Accuracy of the big-data analysis system is improved.

The invention discloses a track type inspection robot for an electric power system, which comprises an inspection robot, an inspection track and a main control center; the inspection track provides a moving track for the inspection robot; the main control center is in communication connection with the inspection robot and is used for monitoring the running state of the inspection robot in real time and analyzing and storing data information acquired by the robot; the inspection robot is hoisted on the inspection track, the inspection robot comprises a driving module, a clamping module, a direction adjusting module and a detection module, the driving module is used for driving, the clamping module is used for adjusting the clamping force between the track and the robot, the direction adjusting module is used for adjusting the position and direction of the detection module, and the detection module is used for detection. The track type inspection robot has the beneficial effects that the detection module can freely move in the front-back direction, the up-down direction and the left-right direction, the detection range is wide, the running state of the robot is detected in real time, the friction force between the track and the driving wheels is automatically adjusted in the working process, and the slipping phenomenon is avoided.