47 results about "Database selection" patented technology

To enable interactions during a lecture in a virtual space.SOLUTION: An information processing apparatus which provides a lecture in a virtual space includes an interaction processing unit which enables two-way communications between a person who provides a lecture and an auditor. The interaction processing unit executes at least one of auditor question / answer processing and system question issuing processing. The auditor question / answer processing is a process of receiving an auditor question, referring to a QA database that specifies combinations of assumed questions and assumed answers related to the contents of a lecture, selecting an assumed answer having a high degree of association with the auditor question, the assumed answer being associated with an assumed question having a high degree of association with the auditor question, and outputting the selected assumed answer so as to be perceived by the auditor. The system question issuing processing is a process of creating a system question whose correct answer is a matter related to the contents of the lecture, and outputs the system question so as to be perceived by the auditor.SELECTED DRAWING: Figure 1

This specification provides a database system, and primary database election methods and apparatuses. The system includes at least one auxiliary node and a plurality of clusters. If any cluster is a primary database of the first table and the other clusters are standby databases: the primary database applies to all auxiliary nodes and all clusters for extension of a term of the primary database during the current term, and if the primary database obtains more than half of approval votes before the current term ends, the primary database determines that the term of the primary database is successfully extended, otherwise, the primary database downgrades itself to a standby database; and the auxiliary node and / or the clusters that don't record the primary database of the first table in term initiate a distributed election, and elect a cluster that obtains more than half of approval votes as a new primary database.

The invention discloses an intelligent ship stowage method based on a bypass bidirectional dynamic optimization distribution strategy, and belongs to the technical field of intelligent ship freight, and the method comprises the following steps: S1, preliminarily building a layout region database according to given ship information; s2, establishing a cargo database according to information of heavy cargos needing to be transported and other cargos; s3, selecting a certain cabin, and carrying out cargo stowage by using a bidirectional distribution preferential mechanism and a bypass plate dynamic adjustment algorithm; s4, whether remaining cabins are not loaded or not is judged, if yes, the step S3 is executed again, and if not, the step S5 is executed; s5, distributing the remaining bypass plates; and S6, outputting all cabin arrangement schemes and bypass plate distribution schemes. According to the intelligent ship stowage method based on the bypass two-way dynamic optimization allocation strategy, intelligent allocation is conducted on the bypass plates in the cabin while heavy goods are loaded, and therefore the cabin loading rate of heavy goods transportation is increased.

The invention relates to the technical field of terminal computing power visualization, in particular to a configuration method and system for a dynamic loading strategy of a large-scale 3D model in a digital twin visualization platform, and the method comprises the following steps: collecting front-end burying point data, uploading user data, preprocessing the user data, constructing a user behavior database, and selecting a machine learning model. Model construction and training, machine learning prediction, dynamic loading strategy configuration and loading strategy optimization are carried out; the method has the beneficial effects that the user behavior data is collected through the front-end burying point, and the user concern area is predicted by applying machine learning, so that the dynamic optimization of the loading strategy is realized. According to the method, the loading efficiency of the large-scale 3D model is effectively improved, the waiting time of the user is shortened, meanwhile, according to different attention degrees of the user, the mode of combining preloading and loading as needed is adopted, the smooth experience of the attention area of the user is guaranteed, and system resources are saved.

A computer system accurately selects learning data for improving a prediction accuracy of a predictor, and is connected to a database that stores a plurality of pieces of learning data and information for managing a plurality of predictors generated under different learning conditions. A target predictor is selected, an influence degree representing strength of an influence of the learning data on a prediction accuracy of the target predictor for test data is calculated for each of a plurality of pieces of test data, an influence score of the learning data is calculated for the plurality of predictors based on a plurality of influence degrees of the learning data associated with the predictors, and the learning data to be used is selected from the plurality of pieces of learning data on the basis of a plurality of the influence scores of each of the plurality of pieces of learning data.

The embodiment of the invention relates to a method for data synchronization, electronic equipment and a computer program product. The method includes determining an environmental state of a synchronization environment by monitoring environmental metrics for the synchronization environment. The method further includes selecting a synchronization operation for target data to be synchronized from a synchronization decision database based on the determined environmental state. The method further includes initiating a synchronization operation between the first storage device and the second storage device of the synchronization environment. The method also includes updating the synchronization decision database in response to the synchronization operation being performed. In this way, appropriate synchronization operation can be dynamically selected for the synchronization environment under the influence of multiple factors according to state monitoring for the synchronization environment. Besides, after the synchronization operation is initiated between the home terminal and the opposite terminal, synchronization decision knowledge is enriched by utilizing synchronization feedback, and subsequent selection is promoted to adapt to the change of a synchronization environment, so that the synchronization reliability is improved, and the efficiency is improved.

The application discloses a kind of collaborative design method and device of gear transmission system for marine environment, it is related to mechanical design field, comprising: the depth that gear transmission system works in marine environment is obtained, based on depth and first relationship, the environmental parameter of marine is calculated;According to environmental parameter and second relationship, the state parameter of lubricating oil used in gear transmission system is calculated;According to the state parameter of lubricating oil and the environmental parameter of marine, select initial gear material in material performance parameter database;According to the design requirement of gear transmission system, select initial configuration in configuration database;Initial gear material and initial configuration are used as initial condition, gear material and configuration are input to coupling performance prediction model to obtain performance index, under constraint condition, target function is solved iteratively using multi-objective optimization algorithm, to obtain the best gear material and configuration.The application overcomes the limitation of traditional separation type design, and can capture complex coupling relationship.

A method and system that include receiving sensor data that is indicative of an operational status of a well construction equipment that is being utilized to construct a planned well that include receiving a well construction plan that includes information that is indicative of the planned well and the well construction equipment. The method and system additionally include accessing a database of operational sequences that are executable to be performed by the well construction equipment to construct a plurality of wells and selecting from the database an operational sequence to construct the planned well. The method and system further include electronically controlling the well construction equipment to autonomously perform the plurality of physical or mechanical operations of the selected operational sequence to drill at least one of: a selected portion of the planned well and a path along the selected portion of the planned well through a subterranean formation.

A method for constructing a lighting environment sharing platform includes constructing a multi-spectrum light-emitting device database stored in a cloud environment module, wherein one or more lighting parameters of specific color temperatures are used to control a multi-spectrum light-emitting device; constructing a light scene database formed by multi-spectrum combinations based on user emotional needs; selecting and controlling light scenes; recording effective scenes to form a spectrum recipe database; and enabling users to store and share spectrum recipes via the cloud.

The invention discloses a protection equipment management system and method based on multi-source data, and relates to the technical field of protection equipment management. Monitoring unit division is carried out on a monitoring area, bird characteristics of the monitoring area are obtained, a bird characteristic database of the monitoring units is established, and the monitoring units with similarity meeting a threshold value are selected as template units; the method comprises the following steps: establishing a template unit database, calling historical use data of protection equipment to obtain a protection equipment template, analyzing the protection equipment template according to a bird feature group, establishing a template database comprising an undetermined protection equipment template, and analyzing the use priority of the undetermined protection equipment template. When a task for protecting a new monitoring unit is received, the undetermined protection equipment template with the highest priority degree is screened, and after a preset updating period is finished, data updating is conducted on the database, the historical protection effect is quantitatively evaluated, the protection equipment template is screened out to serve as an undetermined option, and the reliability of the selected template is enhanced.

An Oracle database big table data deletion method with small disk space occupation comprises the following steps: firstly, selecting a data table to be deleted in an Oracle database, and then carrying out paging query to obtain data of each page; the method comprises the following steps: firstly, screening data of each page to obtain data meeting conditions, then carrying out deletion operation, monitoring execution time of the deletion operation, if the deletion operation is completed within a preset time threshold, continuing to process data of a next page, and if the deletion operation is overtime, checking whether deadlock occurs or not; if the deadlock exists, terminating the deletion operation of the current page, waiting for a preset time length, and then performing the deletion operation of the current page; if the deadlock does not exist, skipping the current page, and continuing to delete the data of the next page; and repeating the above steps on other target data tables in the Oracle database in sequence to perform data deletion until all the data meeting the conditions are deleted, and ending the method. When a large amount of data is deleted, the efficiency is high.

Method for the automated calibration of functions of a driver assistance system (Advanced Driver Assistance System ADAS / Automated Driving System, ADS) for a variety of scenarios and vehicle configurations, comprising: - Training (S10) a learning reinforcement agent (410) of an optimization module (400) with a training data set (240), wherein the optimization module (400) comprises at least the learning reinforcement agent (410), an action module (420), an environment module (430), a state module (440) and a reward module (450), and wherein the training data set (240) contains calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) of an ADAS / ADS system (10); - generating (S20) a strategy of the learning reinforcement agent (410) for varying calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) in the form of actions (A i) for optimising calibration data sets (15) of ADAS / ADS systems (10); - Entering (S30) a calibration data set (15) of the ADAS / ADS system (10) with calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) via a user interface (220) of an input module (200) or from a database (300); - Selecting (S40) a large number of test cases (T i ) from the database (300) and generating simulation environments with simulation scenarios from the test cases (T i ), where a test case (T i ) to select a parameterized scenario (SZp i ), where both scenario parameters (P i ) as well as associated scenario parameter values ​​(PV i ) not all are fixed, concrete scenario parameters (Pc i ) and concrete scenario parameter values ​​(PVc i) and further information for simulating the behavior of the ADAS / ADS system (10) in a specific driving situation and for managing a specific driving task; carrying out (S50) simulations of the behavior of the ADAS / ADS system (10) in the simulation scenarios, namely in concrete scenarios (SZc i ), in which the concrete scenario parameters (Pc i ) and the corresponding concrete scenario parameter values ​​(PVc i ) or value ranges of the concrete scenario parameter values ​​(PVc i ) and generating simulation results, wherein the simulation results reflect the system behavior of the ADAS / ADS system (10) in the simulation scenarios; - Evaluate (S60) the simulation results in the form of key performance indicators (KPI i ) which describe the behavior of the ADAS / ADS system (10) in the numerous test cases (T i ) defined simulated concrete scenarios (SZc i) and performance values; - Determining (S70) states (S i ) from the key performance indicators (KPI i ) and rewards (R i ) from the performance values; - Calculate (S80) modeled calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) to achieve improved system behavior of the ADAS / ADS system (10) in the simulation scenarios by the trained learning reinforcement agent (410) in several iterations until an optimized calibration data set (17) has been generated; - generating and outputting (S90) output results (550) by an output module (500), wherein the output results (550) contain the optimized calibration data set (17).

The invention discloses a device and a method for aided decision making of a special operation scene of an airplane. The device comprises a man-machine interaction module which is used for inputting a target scene through a man-machine interaction mode; the information extraction and storage module is used for collecting key specified data about a target scene; the database is used for storing preset special operation scene conditions; the information processing module is used for comparing the key specified data with the condition which is selected from the database and is associated with the target scene to generate a feasibility decision; and the information display module is used for displaying the feasibility decision. The invention further discloses a method for carrying out auxiliary decision making on the special operation scene of the airplane by using the device, and numerous other aspects.

A computer system is coupled for access to a first database that stores clinical data including, as an item, information acquired on a clinical site and relating to a patient provided with a therapy and a second database that stores non-clinical data including, as an item, information acquired for an investigation purpose and relating to a patient group provided with a therapy. The computer system selects a predetermined number of pieces of the clinical data from the first database, and aggregate the selected predetermined number of pieces of the clinical data, to thereby generate comparative data; and executes, through use of the non-clinical data and the comparative data which are the same in therapy content, statistical analysis for analyzing a difference in the item.

A data communication device for a vehicle, a center device, a data communication method, and a computer program are provided. As one mode of the present disclosure, an OTA client (7) wirelessly communicates with a center device (2) using a line of a communication carrier to acquire update data for writing to a plurality of ECUs (6). A communication information acquisition section (12) acquires information of the communication carrier and information of a region in which the center device (2) exists by wirelessly communicating. In a database (11), a plurality of communication clients corresponding to different distribution servers (23(1))-(23(3)) are stored. An OTA provider switching control section (10) selects an OTA client (7) corresponding to the communication carrier and the region from the database (11) based on the information acquired by the communication information acquisition section (12) and makes the OTA client (7) active, so that data communication with the distribution server (23) is enabled.

The present invention provides a motor diagnostic device for diagnosing motor abnormalities using only motor current information. The device includes a current input unit for inputting motor current value data, an FFT analysis unit for performing FFT analysis on the current value data to obtain power spectrum data, a normalized current calculation unit for calculating a normalized current based on the current value data, a load factor calculation unit for determining a load factor corresponding to the normalized current, a correction value data recording unit for recording, in a database, correction values ​​corresponding to the load factors, to adjust the effect of the difference between a reference value of the power spectrum data and the load factor of the power spectrum data during diagnosis, an FFT analysis result correction value selection unit for selecting a correction value based on the load factor during diagnosis and the database, an FFT analysis result correction unit for correcting the power spectrum data during diagnosis using the correction value, and a motor abnormality diagnosis unit for calculating the difference in current signal strength at the power supply frequency and the rotation frequency for the corrected power spectrum data during diagnosis and the reference value, and comparing the differences to diagnose motor abnormalities.

The invention relates to the technical field of virtual reality, and particularly discloses a practical training method based on a virtual reality technology, which comprises the following steps: acquiring professional direction information of a user and storing the professional direction information to a terminal equipment information database; a professional direction is selected based on the database, a corresponding virtual practical training scene model and teaching content are matched, and a scene loading instruction is sent to the virtual reality interaction device; the equipment presents a virtual practical training scene model according to the instruction; the user obtains operation data in real time during operation, analyzes the data in combination with the preset professional practical training evaluation standard, generates real-time feedback and pushes the feedback to the equipment, high-precision operation scenes and high-risk scenes can be reproduced through the virtual practical training scene model without physical equipment investment, the cost of single professional practical training equipment is reduced, meanwhile, the geographical limitation of the scenes is broken, and the practical training efficiency is improved. Remote colleges and universities can access a standardized practical training scene through virtual reality equipment without transporting scarce pathological samples and high-end instruments.

An automated operation controller 45 of an automated work system 10 includes: a work status management section 452 that selects a work content according to a work DB 456 that records a work plan for a hydraulic excavator 1 and a work order in the work plan, creates an operation plan based on the selected work content and information on the surrounding environment measured by laser scanners 34, and outputs a control signal to a vehicle body controller 41 based on the operation plan; and an abnormal object detection section 454 that detects an abnormal object present on a work site based on the information on the surrounding environment measured by the laser scanners 34. When the execution of the operation plan is determined to be hindered by the presence of the abnormal object, the work status management section 452 selects another work content from the work plan.

Method for the automated calibration of functions of a driver assistance system (Advanced Driver Assistance System ADAS / Automated Driving System, ADS) for a variety of scenarios and vehicle configurations, comprising: - Training (S10) a learning reinforcement agent (410) of an optimization module (400) with a training data set (240), wherein the optimization module (400) comprises at least the learning reinforcement agent (410), an action module (420) with an action space, an environment module (430), a state module (440) and a reward module (450), and wherein the training data set (240) contains calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) of an ADAS / ADS system (10); - generating (S20) a strategy of the learning reinforcement agent (410) for varying calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) in the form of actions (A i) for optimising calibration data sets (15) of ADAS / ADS systems (10); - Entering (S30) a calibration data set (15) of the ADAS / ADS system (10) with calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) via a user interface (220) of an input module (200) or from a database (300); - Selecting (S40) a large number of test cases (T i ) from the database (300) and generating simulation environments with simulation scenarios from the test cases (T i ) in the environment module (430); - performing (S50) simulations of the behavior of the ADAS / ADS system (10) in the simulation scenarios and generating simulation results, wherein the simulation results reflect the system behavior of the ADAS / ADS system (10) in the simulation scenarios; - Evaluate (S60) the simulation results in the form of key performance indicators (KPI i ) and performance values; - Determining (S70) states (S i ) from the key performance indicators (KPI i ) and rewards (R i ) from the performance values; - Calculate (S80) modeled calibration parameters (Pcal i ) and calibration parameter values ​​(PVcal i ) to achieve an improved system behavior of the ADAS / ADS system (10) in the simulation scenarios by the trained learning reinforcement agent (410) in several iterations until an optimized calibration data set (17) has been generated, wherein to determine the decisions of the learning reinforcement agent (410) regarding the actions to be carried out (A i ) the action space of the action module (420) into discrete parameter step sizes with which a certain parameter (P i) during which the optimization is adapted or updated, is divided such that, in addition to a first parameter step size, which is predetermined by the discretization of the action space, a second parameter step size is added, the amount of which is smaller than the amount of the first parameter step size, and wherein the learning reinforcement agent (410) determines the calibration parameter value (PVcal i ) of a calibration parameter to be varied (Pcal i ) by one or more parameter increments, such that the learning reinforcement agent (410) decides whether to use a value of a calibration parameter (Pcal i ) by a certain number of the given first step size of the action area and by a certain number of the smaller second step size by adding, subtracting or leaving the first and second step sizes unchanged; - generating and outputting (S90) output results (550) by an output module (500), wherein the output results (550) contain the optimized calibration data set (17).

A computer-implemented method selects publicly traded assets suitable for trading consideration. A computer accesses market databases, selects assets, and defines an analysis configuration with parameters and timeframes common across assets. For each parameter-timeframe series, the computer forms a normalizing indicator from at least two smoothed sequences and builds multiple deviation bands using specified band families and settings. Within a time window, boundary-crossing events of the indicator are detected for each band. For every asset, the computer records counts of boundary crossings in a result matrix, computes an integral score, optionally with weights, and forms an ordered set of result matrices obtained under alternative configurations. An asset-level output includes a per-matrix score and a set-wise score, such as a sum of per-matrix scores. Assets may be sorted or grouped by these values, and results may be visualized as comparison charts.

The invention discloses a conversation service storage management method and device, electronic equipment and a storage medium, and relates to the field of financial science and technology or other related fields, and the method comprises the steps: recognizing a service path of a remote conversation service request under the condition that the remote conversation service request is received, and processing the remote conversation service according to the service path; obtaining call service data in the processing process, and copying the call service data to obtain a call service data copy; determining an available database based on a preset database selection strategy, and determining a storage routing path; and storing the call service data copy to an available database according to the storage routing path. Through the method and the device, the technical problem of poor financial call service quality caused by defects of a remote financial system in aspects of data statistics and management in related technologies is solved.

Apparatuses, methods, and systems are disclosed for location-aware beam selection. One method a communication device (i.e., a UE and / or gNB) includes mapping a set of beam signal characteristics to UE location information and storing said mapping to a Beam Fingerprint (“BFP”) database. The method includes identifying a UE location and selecting an optimal beam based using the UE location and the BFP database, said optimal beam being one of: a transmit beam and a receive beam.

The present invention belongs to the technical field of electromechanical equipment management and maintenance, and particularly relates to a method for predicting the life of electromechanical equipment. It mainly includes the following steps: determining the expected life correlation attribute sequence according to the type of electromechanical equipment; determining the data to be analyzed and the initial reference data; screening samples from the samples to establish a sample database, selecting a suitable data period, using a sliding time window to intercept the corresponding period monitoring data for similarity analysis to determine the similarity and extract effective data, calculating the period change rate deviation to optimize the samples and establish an effective reference database; establishing a prediction weight and prediction based on the time series similarity of the sample data. The electromechanical equipment life prediction method of the present application is mainly used to provide a method applicable to new equipment, which can better consider the correlation between historical measurement data and the life cycle, manifest the relationship between the operating states of different life stages of electromechanical equipment and the final expected life, and better analyze and predict the expected remaining life of electromechanical equipment.

The invention provides a switchable holographic metasurface design method and device, equipment and a medium, and belongs to the field of multiplexing holographic metasurface research, and the method comprises the steps: designing a metasurface unit structure with a cylinder and a circular ring cylinder coupled, scanning the radius of the cylinder and the inner radius of the circular ring cylinder in FDTD, obtaining a relation graph of a phase and the two radiuses, and calculating the position of the metasurface unit structure according to the relation graph; and comparing the relation diagrams of the two phase-radius relations before and after the phase change. Data are analyzed by MATLAB, a two-dimensional eight-level phase sampling scheme is provided, a radius-size database before and after phase change is made, the size needed by each unit structure is selected based on the database, and switching of any two holograms can be achieved. Under the condition that only the temperature of the whole metasurface is changed, active multiplexing of the metasurface and switching of the holograms are achieved, the holographic switching step is greatly simplified, phase influences of the two holograms all come from a set of unit structures, and structural waste is avoided.

The present disclosure discloses a systematic method for generating a planar expandable structure by adding hinged points and hinged rods based on uniform tessellation, including: establishing a database of planar uniform tessellation graphs; selecting, inputting a graph of arbitrarily size range, naming it Graph A; drawing a dual tessellation graph of the Graph A, and extracting a basic unit b from it; determining whether the basic unit b has rotational symmetry, if not, then expanding the basic unit b to adjacent units, and denoting a final combined unit as Graph C; choosing to add hinged points or hinged rods, adjusting a length of each side of the Graph C, making Graph C′; adding original tessellation polygons in the Graph A to corresponding angular points of the Graph C′, rotating at a predetermined angle; hinging adjacent polygons by the hinged points or hinged rods together to obtain an expandable structural unit.

To provide a planting selection system and the like capable of appropriately selecting a plant planted in an area to be planted of a building.SOLUTION: A planting selection system includes: a storage part which stores a database in which a type of plant is associated with characteristics regarding shade tolerance and wind tolerance; a simulation part which performs sunshine simulation and air current simulation regarding an area to be planted of a subject building by using a three-dimensional shape model of the subject building and its surrounding buildings; and a selecting part which selects a plant planted in each of a plurality of sections of the area to be planted on the basis of a result of simulation and database.SELECTED DRAWING: Figure 1

This invention provides an optimization method, storage medium, and device for database selectivity calculation. The method includes: extracting a first constraint clause using AND predicates; merging columns with functional dependencies in the first constraint clause into a first target column set based on these dependencies, and calculating the first selectivity for each merged target column in the first target column set; calculating the second selectivity for target columns outside the first target column set in the first constraint clause; sorting the first and second selectivity, and selecting a preset number of target columns according to preset rules, then substituting their selectivity into a preset formula to calculate the total selectivity. This method enables reasonable selectionivity calculation and incorporates data relevance into the selectivity formula, thereby improving the accuracy of the optimizer's selectivity calculation.

Techniques for retrieving products conforming to specific specifications from a question text in a natural language are improved. An information processing device (20) is provided with a control unit (21) that registers, in a database, one or more attributes and attribute values, which are attribute values, for a plurality of vehicles, and performs control that, when a question text expressed in a natural language is input, specifies search conditions relating to the attributes indicated in the question text using machine learning, and performs search for the search conditions relating to the attributes indicated in the question text. And generating a query for selecting a vehicle satisfying the determined search condition from the database, and outputting a search result of the database based on the query.

Vehicle systems and methods for compensating for scheduled battery charging. A vehicle system includes a database and a control module. The control module is configured to determine a plurality of compensation factors for a plurality of planned charging power values, each compensation factor being determined based on a system weight and an error between an estimated energy provided for the charging time slot and an actual energy provided during the charging time slot for charging a battery in the vehicle, each of a plurality of compensation factors specific to one of the planned charging power values is stored in a database, one of the stored compensation factors is selected from the database based on a subsequent planned charging power value for charging the battery in the vehicle, and determine an adjusted duration for charging a battery in the vehicle based on the selected compensation factor. Other example vehicle systems and control methods are also disclosed.

The present application discloses a database fault handling method, system, device and readable storage medium. According to the preset database and fault judgment strategy adaptation relationship, a target fault judgment strategy that is adapted is selected for the master-slave database to be detected for fault detection; according to the target fault judgment strategy, whether the master-slave database is faulty is determined; if so, the target fault type to which it belongs is determined based on the fault information of the master-slave database, and the target fault handling strategy that is adapted to the target fault type is determined based on the preset fault type and fault handling strategy adaptation relationship, so as to handle the master-slave database fault according to the target fault handling strategy. It can be seen that the present application configures fault judgment strategies that are adapted to different databases, thereby making fault judgment more flexible; and the present application configures fault handling strategies that are adapted to different fault types under the master-slave database architecture, thereby solving different types of faults, and has a wide range of applications.