53results about How to "Avoid missing data" patented technology

An evaluation system and an evaluation method for comfort level of internal operating force of a vehicle are disclosed, characterized in that the system composition includes a vehicle-mounted data acquisition device composed of input / output devices including an analog-digital conversion data acquisition card, an acquisition channel, a vehicle-mounted computer motherboard, a keyboard and a display; for the operating devices, a displacement amount sensor for real-time measurement of an action force and an action force that is applied by a driver to internal operating devices of the vehicle is arranged, a parallel interface data transmission path of the computer is set based on the signal acquired by an external sensor as a data acquisition source of the data acquisition system, a plurality of data acquisition interfaces are utilized to data acquisition for different sensors simultaneously. The evaluation method is the evaluation for comfort level of degree of correlation of curves by comparing a standard curve of comfort level of the corresponding vehicle type with a real-time curve measured by the system and reflecting displacement amount variation characteristics of the action force and the action force that is applied by a driver to internal operating devices of the vehicle. The invention can evaluate comfort level of vehicle in accordance with practical requirement of carmaker.

The invention discloses a paging query method. The method comprises steps as follows: a client sends the number N of data on a current query page to a server, and N is a positive integer which is larger than or equal to 1; if the current query page is the first page, the server extracts N data from a database from the first datum according to the sequence of paging query data in the database and returns the extracted N data to the client for display; if the current query page isn't the first page, the server looks up the last datum on the page before the current query page from the database, performs sequencing on the paging query data in the database, extracts N data from the database from the next datum of the last datum and returns the extracted N data to the client for display. The invention further discloses a paging query system.

The invention relates to the field of logistics equipment, and specifically relates to a self-service express cabinet. The self-service express cabinet includes a cabinet body formed by a plurality of express boxes, and a radar detection system arranged in the cabinet body. The express box includes a box door and an electronic lock arranged on a side of the box door. The radar detection system includes a plurality of probes, a drive circuit, an ultrasonic emission module, an ultrasonic reception module, a signal amplification circuit, a signal decoding circuit, a control module, and an external power supply module. The electronic lock is provided with a probe mounting hole used to mount the probe. Open-close of box doors of the express boxes of the self-service express cabinet is controlled through the radar detection system. When the box door is opened, the radar detection system acquires and records information of existence of express, and size, weight, addressee information and other information in the express box. The self-service express cabinet is safe and convenient, and can realize self-service express sending and receiving, and the ultrasonic probes can detect size of express in the box door without a blind area, and a detection result is accurate.

The invention belongs to the technical field of recommendation systems, and relates to a heterogeneous graph neural network-based recommendation method, which comprises the following steps of: collecting a data set with social relationships among users, user-commodity interaction historical data and commodity category information, filtering invalid data and carrying out negative sampling; randomly selecting a user set and a related commodity set, and carrying out multi-order graph sampling and mapping; node feature extraction: inputting the constructed graph into a heterogeneous graph neural network for processing to obtain a fusion node embedding vector of the nodes, wherein for the commodity nodes which do not need to be subjected to the re-calibration step, the fusion node embedding vector of the commodity nodes is the commodity fusion embedding vector; re-calibration: re-calibrating the user fusion node embedding vector to obtain a user final expression embedding vector; and performing preference prediction by using the user final representation embedding vector and the commodity fusion embedding vector, and obtaining a recommendation sequence. The method solves the problems of data sparsity and data missing, and has the advantages of being accurate in recommendation and the like.

The invention discloses a method for judging operation states of an agricultural machine based on GPS and engine data. The method is characterized by comprising the steps: (S1) a distinguishing modelis trained, specifically, (S11) working data of the machine are obtained, specifically, the GPS data and the engine control unit (ECU) data of the agricultural machine under the different states, namely the operating state, the field transferring state and the idle state are collected, and the GPS data comprise the instantaneous speed and the steering angle of the agricultural machine; (S2) the model is called for prediction; and (S3) the beginning and stopping moments of the operation states are refined. By collecting the ECU and GPS data of the agricultural machine under the different operation states, each type of data is marked, the distinguishing model is trained through the marked data, and then the model is used for distinguishing the operation states of the agricultural machine; dependence on the GPS density of the agricultural machine is avoided, and the distinguishing error caused by change of the GPS density is avoided; and the judging model is trained aiming at the situation of the data loss, and decreasing, caused by the data loss, of the accuracy rate of the judgment result is avoided.

The invention relates to an online and offline activity track analysis method, device and system. The method comprises specific steps of installing a data collection device; collecting and scanning data of a smart device emitting a WIFI search signal and sending the scanned data to a background server in real time by the data collection device; receiving the collected data and analyzing and filtering different types of collected data by the background server, so as to obtain effective data; receiving an inquiry instruction, wherein the inquiry instruction comprises a time period and at least one type of known data; acquiring, according to the inquiry instruction, different types of effective data corresponding to the known data in the time period; ranking the different types of effective data acquired through inquiry according to time, so as to obtain an offline track shown trough a time field and an online track shown through time and other data in each field; and comparing and analyzing consistency of the online track and the offline track.

The present invention discloses a data receiving device and method, for identifying a transmitting mode to which a data signal belongs. The method comprises the following steps: according to a source clock, generating a first reference clock; according to the data signal and a data recovery clock, generating a phase detection signal; according to the phase detection signal, adjusting a phase of the first reference clock to generate a data recovery clock; according to the phase detection signal and the first reference clock, generating a second reference clock, wherein the second reference clock has the same frequency as the data recovery clock and has a phase difference; according to the second reference clock and the data signal, detecting the transmitting mode, to generate a mode signal; and according to the mode signal, determining whether to change the frequency of the first reference clock.

The invention discloses a multilayer cloud computing framework coordinated integrated reduction method for gestational-age newborn brain medical records. The multilayer cloud computing framework coordinated integrated reduction method comprises the steps of firstly constructing a multilayer MapReduce coordinated neuro-subpopulational structure, extracting each neuro-subpopulational elite optimal weighted margin WCi, adaptively dividing a large-scale brain medical record tissue attribute to n neuro-subpopulations which co-evolute through the MapReduce, and acquiring optimal dividing curved surfaces of different brain medical record tissues; and designing a neural network model with a five-layer structure, constructing an elite energy matrix NSMP, performing integrated coordinated reduction of a brain medical record curved surface Sub-curvei by each neuro-subpopulation optimal energy elite Elitist-leaderi, obtaining the optimal reduced set Redi<Ensemble> of a respective divided curved surface, and finally extracting a global optimal attribute reduced set Red<Ensemble> of the brain medical record tissue. According to the multilayer cloud computing framework coordinated integrated reduction method, the reduction efficiency and the reduction efficiency for the gestational-age newborn brain medical records in a big data environment are quickly improved through the multilayer MapReduce frame and coordinating with the neuro-subpopulational elite in a cloud computing environment. Furthermore the multilayer cloud computing framework coordinated integrated reduction method for the gestational-age newborn brain medical records has an important meaning for brain medical record selection, role extraction, clinical decision supporting service, etc.

The embodiment of the invention provides a data prediction and completion method and device based on a time sequence, a medium and computing equipment. The data prediction method based on the time sequence comprises the steps of obtaining monitoring data of at least one first monitoring quantity; based on a specific time series data prediction model and the monitoring data of the at least one first monitoring quantity, obtaining prediction of a second monitoring quantity, wherein the monitoring data of the first monitoring quantity corresponds to the monitoring data of the second monitoring quantity in time sequence, and the time sequence data prediction model comprises at least one kernel function for fitting feature information of the data of the first monitoring quantity and the secondmonitoring quantity. According to the method, data prediction can be carried out on the monitoring quantity of the monitoring object, the problem of data missing is avoided, the safety of the monitoring object can be evaluated, and the safety risk of the monitoring object during operation is reduced.

The invention belongs to the technical field of data storage, and discloses a request response method, a device, equipment and a computer readable storage medium. The method comprises the steps that if a current solid state disk replacement instruction is received, metadata in a current solid state disk is cached to a preset area of a mechanical disk; receiving an access request of an object storage service OSD, and determining a metadata identifier according to the access request; searching corresponding metadata in the current solid state disk based on the metadata identifier; if the corresponding metadata is not found, searching the corresponding metadata in a preset area of the mechanical disk based on the metadata identifier; and responding to the access request according to a searchresult in a preset area of the mechanical disk. By means of the mode, when a large amount of data is migrated, data loss is avoided, and the service access performance of the storage system is not affected.

The invention discloses a method for estimating growth period of bahaba flavolabiata through a daily growth increment in otolith. The method comprises the following steps that sample fishes are collected, and the growth indexes of body length and weight are measured; the sample fishes are dissected, and the otolith is taken out, cleaned and dried for use; the otolith is ground till the otolith center is shown, and otolith sheets are obtained; the otolith sheets are etched till the daily increment can be clearly distinguished; the etched otolith sheets are cleaned and air-dried; the otolith sheets are observed, and the number of otolith growth turn patterns is measured and recorded; the day-age, incubation period and spawning period are calculated. According to the method, the growth periodof bahaba flavolabiata is estimated through the daily growth increment in the otolith, and the time required by the work which is completed through long-term field investigation in the prior art canbe greatly shortened; the sampling time does not need to be limited in the breeding season of bahaba flavolabiata, and the defect is overcome that field sampling cannot be completed in the breeding season of bahaba flavolabiata so that data loss can be caused; the accuracy of estimating the growth period of bahaba flavolabiata is high.

The invention discloses an information data model analysis method, which belongs to the technical field of data processing. The information data model analysis method comprises the following steps: generating a corresponding analysis scene and an analysis result according to case-related basic information, selecting a target analysis result, and generating a target analysis task list; acquiring to-be-analyzed data by using a database querier, preprocessing the acquired data to generate intermediate data, establishing a query model, and storing the intermediate data and the query model in a memory; and reading the corresponding analysis models from the algorithm library one by one according to the analysis task list, calling an analysis execution module to analyze the data in the referencedmemory according to strategy trees of the analysis models to generate data features, and storing and displaying the data features on a graphical interface. According to the invention, the problems oflarge time consumption and large workload of case handling personnel due to multiple rounds of analysis, data deviation and repeated work of information analysis of information data such as bank bills, telephone bills, tracks, tax receipts and the like in the existing case handling process are solved.

The invention discloses a mover position detection device and equipment of a linear motor, and belongs to the field of mover position detection. The detection device comprises a position detection unit, a speed measurement rack and a signal processing system, wherein the position detection unit comprises at least two pairs of Hall effect sensors and a sensor mounting plate, the Hall effect sensorsare respectively fixed on a stator of a to-be-tested linear motor through sensor mounting plates, the speed measurement rack is installed on the mover of the to-be-tested linear motor, and sequentially passes through the Hall effect sensors when performing linear motion along with the mover, and the signal processing system converts a change electric signal of the Hall effect sensor into an optical signal, and determines the movement direction and the final position of the rotor through the optical signal. According to the invention, the Hall effect sensors and the speed measurement rack areintroduced to test the position of the rotor, so that the detection device has high reliability, high environmental adaptability and long service life, and safe and reliable operation of the high-speed linear motor is guaranteed.

The invention discloses a master-slave database switching method, computing equipment and a storage medium. The method comprises the steps of monitoring whether a current first master database crashesor not; when it is monitored that the current first master database crashes, selecting a temporary second master database from a plurality of slave databases according to the data synchronization position information of each slave database; synchronizing the temporary to-be-synchronized data of the second master database to other slave databases by utilizing a master-slave synchronization function; selecting a new third main database; reading to-be-synchronized data of the first main database by utilizing a plug-in in the first main database, and writing the to-be-synchronized data of the first main database into the third main database; and updating the configuration information of the master-slave database after switching. By means of the scheme, when the current master database crashes, the slave database can be switched into the master data in time, and it can be guaranteed that the data is not lost.

The invention discloses a commercial bank employee transaction behavior analysis and alarm method and device. The method comprises the following steps: building an employee transaction attribute modelcorresponding to each employee according to the identity attribute parameters and transaction behavior parameters of commercial bank employees; establishing an employee abnormal transaction behaviormodel according to preset employee abnormal transaction behavior entries of the commercial bank, wherein the employee abnormal transaction behavior model comprises abnormal transaction behavior characteristic variables corresponding to different employee abnormal transaction behavior entries; for each employee, matching the employee transaction attribute model with an abnormal transaction behaviorcharacteristic variable in the employee abnormal transaction behavior model; and when the matching succeeds, sending alarm information that the employee transaction behavior is abnormal. According tothe invention, automatic analysis and alarm of commercial bank employee transaction behaviors can be realized, the accuracy and efficiency of commercial bank employee transaction behavior analysis and alarm are improved, and the risk early warning capability of a commercial bank is also improved.

The invention discloses a flight support node intelligent recognition system. The system is composed of a streaming media processing platform, a YOLOv3 + AddNN algorithm platform, a message queue, a node intelligent recognition system, a database and a WEB system display platform. Firstly, a to-be-identified video is collected into a storage server; then, the video stream is transmitted to a streaming media platform; video playing, slicing and picture cutting are carried out through real-time transcoding; transmitting the video stream to a YOLOv < 3 + > AddNN algorithm platform; and the algorithm platform uses an improved deep neural network recognition framework to identify the annotation data set and put a result into a message queue, then the node intelligent recognition system completes node pushing and database storage by subscribing the queue, and finally the WEB system display platform accesses the nodes in the database to perform front-end page display. According to the invention, collection and recognition of data of each guarantee node in airport process management and control can be accurately completed, the labor cost is reduced, missing report and delay of data are avoided, and reliable reference is provided for efficient management of airports.

The invention discloses a method for monitoring the combination and match of apparel products in the retail market, which mainly comprises the following steps that: an RFID signal transceiving antenna and an RFID reader are respectively installed in each dressing room and on each dressing mirror, and an RFID chip is installed on the apparel product; the RFID reader in each dressing room and on each dressing mirror is respectively connected with a data analysis system through signals, and data information on the RFID chip of the apparel product entering each dressing room and data information on the RFID chip of the apparel product entering a dressing area before each dressing mirror are displayed on the data analysis system by RFID equipment, so that the combination and match of the apparel products in the retail market can be obtained by the analysis of the data information. The method can accurately count up the data of the combination and match of the apparel products in the retail market, so that enterprise decision-makers can collect correct market information.

The invention discloses a rice population three-dimensional morphological structure digitalization and visualization reconstruction method, and relates to the technical field of plant three-dimensional digitalization and visualization construction. The method comprises steps: S1, adopting a 'positioning-separation-measurement' method, referring to different coordinate systems, positioning positions and directions of rice plants, stems and blades, and measuring geometrical morphologies of stalks, the blades and other organs; S2, according to different levels, structuring data obtained in S1, and constructing digital rice-population two-dimensional morphological structure; and S3, by utilizing a geometric explanation principle, transforming the positions and directions of the rice plants, the stems and the blades in different reference coordinate systems and the geometrical morphologies of the stalks, the blades and the other organs to the same field coordinate system, and reconstructing digitalization and visualization rice population three-dimensional morphological structure. Through utilization of the method of the invention, the complexity of three-dimensional data acquisition can be effectively reduced, and the visual reconstructed rice population morphological structure and an actual image have a high similar degree.

The invention discloses a medical record viewing method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining medical record data of aconsultation object in a remote consultation application and an expert account supporting consultation when the remote consultation application initiated by a system doctor account is detected; basedon the medical record data, determining whether the doctor account remote consultation application has an application permission or not and whether the expert account has a consultation receiving permission or not; if the doctor account has the application authority and the expert account has the consultation receiving permission, endowing the expert account with a medical record sharing permission for checking the medical record data; and obtaining a sharing timeliness corresponding to the medical record sharing permission, and closing the medical record sharing permission based on the sharing timeliness. The medical record data can be prevented from being leaked under the condition that remote consultation is not affected.

The invention discloses a small-sized double-weighing-unit automobile weighbridge which comprises a roadbed, a display screen and a bearing head. A mounting groove is disposed in the middle of the roadbed. A support plate groove is fixed to the right side of a support plate. A speed bump is mounted on the top of the support plate. The surface of the speed bump is provided with an anti-slip groove.Stopping blocks are fixed to both sides of the speed bump and are provided with stopping protrusions. The rightmost side of the display screen is provided with an infrared probe. A vertical column isarranged below the bearing head. A telescopic device is mounted below the vertical column. A weight sensor is connected to the bottom of the telescopic device. The small-sized double-weighing-unit automobile weighbridge is equipped with the speed bump which can be used as a speed bump when the weighbridge is not in use. The speed bump is supported by the support plate under the speed bump so thatthe bearing head are not stressed when not in use. The small-sized double-weighing-unit automobile weighbridge is simple in overall structure is simple, and is relatively small in slotted volume andconvenient to install compared to a general large weighbridge.

The invention discloses a tea garden abnormal data correction method and system based on deep learning, and a storage medium, and the method comprises the steps: collecting the environment data of a target tea garden, carrying out the preprocessing of the environment data, taking the preprocessed environment data of the target tea garden as the input data, and inputting the input data into a CNN-SVM (Convolutional Neural Network-Support Vector Machine), carrying out anomaly detection on the data, and meanwhile, inputting the data into a long-term and short-term memory neural network LSTM to predict the environmental data; and when the detection data of the CNNSVM model is abnormal data, extracting time characteristics of the abnormal data detected by the CNNSVM model, selecting data with the same time characteristics from the data predicted by the LSTM model for correction, and then outputting the data to a tea garden data set. According to the method, abnormal data can be corrected, the specific fault location of the sensor can be judged according to the abnormal data, and high correction accuracy, specificity and generalization ability are achieved.

The invention provides an ethylene gas content monitoring device and method. The device includes a control unit, an information acquisition unit, an A / D conversion unit, a clock unit and a storage unit. The information acquisition unit is used for real-time acquisition of an ethylene gas analog signal. The A / D conversion unit is used to convert an ethylene gas analog signal into a digital signalto obtain the ethylene gas content; the clock unit is used for recording the corresponding acquisition time when the information acquisition unit collects the ethylene gas content; and the control unit is used to control the acquisition process of the information acquisition unit and the recording process of the clock unit, also used to obtain the ethylene gas content and the corresponding acquisition time, and send the ethylene gas content and the corresponding acquisition time to the storage unit. The ethylene gas content in the cold chain logistics of fruits and vegetables can be recorded in real time. The device facilitates the establishment of changes in the ethylene gas content over time in the cold chain transportation of the fruits and vegetables, and provides a theoretical basis for the cold chain transportation and storage technology of the fruits and vegetables.

The invention discloses a three-rainfall-sensor fusion system, in rainfall fusion calculation, all values of variables related to rainfall are replaced by sensor output pulse numbers, and for a 0.1 mm rainfall sensor, the value of the variable in a fusion calculation formula is divided by 10 to obtain a rainfall element value. The method comprises the following steps: S1, preliminary calculation of a minute rainfall fusion value: calculating an initial value of minute rainfall fusion according to the mutual relation of current minute rainfall observation values of three rainfall sensors; S2, calculating differences between minute values and minute fusion initial values of the three rainfall sensors; S3, calculating accumulated rainfall deviations of the three rainfall sensors; S4, calculating a minute rainfall fusion value correction amount; S5, correcting the fusion value and the accumulated rainfall deviation value, wherein the value is B; S6, judging the state of the sensor; and S7, further correcting the corrected value by the environmental factor, wherein the value is A. Meanwhile, the workload of manual data processing and maintenance is reduced, and a good foundation is provided for ground meteorological observation service automation.

The invention provides a data processing method and system based on a blockchain. A blockchain service system comprises a plurality of nodes. A first node broadcasts a message of first data uplink after receiving first data of a preset type, and each node stores an area obtained by packaging the first data by a first main node in a local blockchain. An intelligent contract corresponding to the first data is generated, so that the problem of data loss when the single node fails due to the fact that the data is stored in the single node can be avoided. After the first node receives second data preset and associated with the first data, an uplink message of the second data is broadcasted, an area obtained by packaging the second data is stored by the second main node to the local block chain by each node, and an intelligent contract corresponding to the first data is executed according to the second data to obtain an execution result. By applying the scheme provided by the invention, the problem that the claim process is long due to the fact that a large number of personnel are needed for auditing in the claim process can be avoided.

The invention discloses a distributed system timing task processing method and device and a storage medium. The method comprises the steps of obtaining global job information, wherein the global job information comprises a plurality of timing tasks in a namespace; generating a timing task list according to the plurality of timing tasks; comparing the plurality of timing tasks with timing tasks ina namespace with the same name in a database to obtain task states of the plurality of timing tasks in the database; if the task state of the timed task in the database is invalid, updating the task state of the timed task to be invalid, and deleting the timed task from the timed task list; and mounting the timed task list of which the invalid timed task is deleted to a registration center, so that the timed task in the timed task list runs according to set time and mode. According to the method, the task job which is set to be invalid cannot be reset to be valid after the job server is restarted, and the problems of data missing and data pollution are avoided.

The embodiment of the invention relates to an electric energy meter firmware program upgrading method and device based on ESAM, a medium and equipment. The method comprises: transmitting upgrading file information through identity authentication of a master station and an electric energy meter, and encrypting and decrypting the upgrading file information transmitted by the master station and the upgrading file information received by the electric energy meter by adopting an ESAM security module; after ensuring that only after the electric energy meter receives legal and correct upgrading file information, the main station transmitting an upgrading data packet to the electric energy meter, firmware program upgrading can be conducted only after the electric energy meter decrypts the upgrading data packet and passes verification, integrity and reliability checking of the upgrading data packet is achieved, data loss of the upgrading data packet is avoided. The firmware program of the electric energy meter cannot be upgraded, and the risks of abnormal attacks such as information interception, illegal code attacks, repeated upgrading attacks, repeated resource application attacks and electric energy meter data tampering in the upgrading process are avoided.

The invention provides a nasal nursing sensitivity quality evaluation index system. The system comprises a nasal nursing sensitivity data evaluation system, a nasal nursing sensitivity data evaluation method and a computer readable storage medium for realizing the method. The system comprises a first data entry subsystem for receiving exercise sensitivity data uploaded by a user terminal; a second data classification subsystem ofr grouping the exercise sensitivity data; a third data labeling subsystem for labeling the exercise sensitive data to obtain a grouping labeling result; and a fourth data evaluation subsystem for sending nursing evaluation feedback to the corresponding user terminal based on the grouping labeling result. The method comprises the steps: the uploaded exercise sensitivity data comprises an exercise video picture and a corresponding exercise sensitivity index value; and storing the exercise sensitivity data of which the exercise video pictures belong to the same type in the same grouping queue, and listing the exercise sensitivity data corresponding to a relatively large exercise sensitivity index value.

The invention discloses a method and system for intelligent identification of telemetering jumping in an EMS dispatching automation system. The method comprises the steps of obtaining basic data sources through an EMS, respectively analyzing the different data sources, recognizing abnormal data sources, and displaying abnormal information through a display terminal in a report mode. The system comprises a basic data source obtaining module, an abnormal data recognizing module and an abnormal information output module. Basic data can be collected comprehensively and analyzed, abnormal information omission is avoided, the abnormal information is displayed hierarchically in the report mode, the abnormal information of different grades is processed according to severity, the whole process is achieved automatically, time is saved, and integral working efficiency is improved.

The invention relates to the technical field of communication, in particular to a Spark application program control method and device. The control method for the Spark application program comprises the following steps: judging whether a historical state parameter of the Spark application program is effective or not, and if yes, adding the historical state parameter into an operation environment ofthe Spark application program; The Spark application program is operated according to the acquired historical state parameters; Judging whether the Spark application program operates abnormally or not, and if yes, keeping the current state parameter of the Spark application program; And storing the current state parameters in an administrator to update the historical state parameters. According to the method, the running accessibility of the Spark application program is ensured, the problems of data loss, data repeated consumption and the like caused by discontinuous states are avoided, and the usability of the program is improved.

The invention discloses a method and device for predicting environment information of the Internet of Things, and relates to the technical field of environment monitoring of the Internet of Things. The method comprises the following steps: acquiring environment information collected by a sensor, wherein the environment information at least comprises one of temperature information, humidity information, harmful gas concentration, smoke concentration, illumination intensity and soil PH value; the environment information is preprocessed; establishing a data prediction model according to the environment information obtained after preprocessing; and predicting the environment information according to the data prediction model. Through the established data prediction model, when the communication module is powered down or has a fault, the environment information which is not transmitted completely can be predicted through the data prediction model, so that missing data is supplemented, and the real-time performance and the accuracy of prediction are realized. The situation that corresponding data is lacked when the communication module fault environment information is not transmitted completely is avoided.