35 results about "Database selection" patented technology

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.

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 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).

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.

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 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.

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.

A service accesses a RAG system having access to source databases. The source databases are accessible by an LLM tasked with answering user queries. The LLM relies on the source databases to answer the queries. The service accesses a current user query. The service accesses a PQ database of previous user queries that were successfully answered by the LLM. The service retrieves, from the PQ database, a select number of previous user queries that are similar to the current user query. The service identifies source databases used by the LLM to answer those similar user queries. These identified source databases are weighted and ranked. The service generates a subset of source databases by filtering the databases based on the ranked weighted scores. The service tags the subset of source databases as ones the LLM is to potentially use when generating a response to the current user query.

The invention discloses an oil field water quality on-line detection system database design method, which comprises the following steps: 1) database selection and configuration: configuring a corresponding database according to system stability and data security, and carrying out regular data backup on water quality data; 2) data verification, wherein cyclic redundancy verification and MD5 verification are adopted to verify the correctness of data transmission; 3) data packaging and caching: for the received water quality data information in the sensor module, packaging different types of sensor data information into corresponding fixed frame formats; 4) designing a data model, establishing water quality classification meeting standards for the received water quality data transmitted by the remote monitoring equipment, and classifying the water quality data; 5) data encryption and decryption; and (6) data transmission: performing data transmission and access by adopting high-concurrency optimization processing. According to the invention, database management is carried out on the water quality indexes of the water injection detection points, so that data sharing and data independence are realized, and the redundancy of water quality data is reduced.

The present invention provides a method for optimizing the design of a variable-section rim thruster based on changes in section cylindrical coordinates, comprising the following steps: obtaining the geometric characteristic parameters of a parent thruster; selecting the chord length and thickness of the blade and duct airfoil sections, as well as the position and number of the modified sections, as design parameters and determining the parameter variation range and minimum sample variance; obtaining a sample database using a low-variance sampling sequence based on the design parameters; selecting a sample and generating a blade by modifying the blade and duct section profile points according to the sample, and then combining them to generate a rim thruster model; and accurately obtaining the hydrodynamic performance of the rim thruster model corresponding to the sample using a finite element theory hydrodynamic performance calculation program. This design method can flexibly modify the structure of an existing rim thruster without being constrained by traditional design methods, thereby finding more suitable structural parameters and laying the foundation for the future development of suitable rim thruster design concepts and methods.

The invention discloses an RAG knowledge base construction method oriented to intelligent generation of a Modelica model. The RAG knowledge base construction method is used for constructing an electric vehicle system model. The method comprises the steps that a knowledge document of the electric vehicle field is acquired based on data of an electric vehicle physical system, the knowledge document is segmented, each segmented paragraph comprises a complete information unit, and the information units are stored as structured field knowledge; the method comprises the following steps: organizing documents according to component categories of an electric vehicle physical system, partitioning each document, obtaining text embedding vectors after partitioning, and storing the text embedding vectors into a vector database; the method comprises the following steps: selecting an RAG framework and a large language model, building a model generation agent, importing a Modelica language specification knowledge base and an electric vehicle field knowledge base, retrieving knowledge fragments from the knowledge bases by using the RAG framework for user questions in a question and answer form, and generating a model. Based on the method, efficient and accurate generation of the Modelica model of the electric vehicle assembly, the whole vehicle and the control system can be realized.

A communication system that comprises a central cloud server which further includes a processor. The processor obtains sensing information from a plurality of vehicles as the plurality of vehicles move along a travel path, generates a connectivity enhanced database over a first period of time based on the obtained sensing information, and causes one or more RSU devices over a second period of time to direct one or more specific beams of radio frequency (RF) signals to service a donor side of a first edge device of a new vehicle in a case where the new vehicle arrives and moves along one or more first geographical areas of a plurality of geographical areas along the travel path, where the one or more specific beams are selected based on the connectivity enhanced database.

The invention is suitable for the technical field of capacitive stylus control, and particularly relates to a capacitive stylus dynamic interaction method and system supporting gesture recognition, and the method comprises the steps: obtaining product use parameters, and constructing a user-defined gesture database; selecting a user-defined gesture, collecting the user-defined gesture, and recording sensor data corresponding to the user-defined gesture; classifying sensor data, constructing corresponding parameter change curves of the sensors in different test batches, and constructing an anchor point curve interval; and when a user executes the user-defined gesture, acquiring parameters of the sensor in real time to obtain data to be recognized, extracting real-time parameter values, and judging the currently executed user-defined gesture based on the distribution of the real-time parameter values in the anchor point curve interval. According to the method and the device, the recognition success rate of the custom gesture is ensured, the degree of freedom of the custom gesture is greatly expanded, the effect of rapidly executing the corresponding custom instruction through the custom gesture by matching with the custom instruction is achieved, and the operation convenience of the capacitance pen is improved.

The invention provides a model routing system and method, electronic equipment and a storage medium. The model routing system comprises: an index database, which stores different AI models, various index information of each AI model, and calling interfaces corresponding to each AI model; the entrance gateway module is used for receiving a model decision request and determining a target demand for the AI model included in the model decision request; the multi-target routing decision module is used for acquiring the target demand, selecting a target AI model meeting the target demand from the index database according to each piece of index information of each AI model, and feeding back a calling interface of the target AI model to the entrance gateway module; and the entrance gateway module is also used for outputting a calling interface of the target AI model. The model routing system can assist a user in selecting an AI model suitable for own requirements.

The invention provides a method for matrix control of external connection equipment, which comprises the following steps: client software on battery detection equipment is opened, protocol parameter editing is carried out, and a protocol configuration file is generated; issuing the data to a middle computer on the battery detection equipment and storing the data in a database; selecting a to-be-tested channel, starting a work step editor, and performing work step flow parameter editing and matrix configuration editing; after the work step process is edited, clicking to start, and packaging external parameters output by a matrix in the work step process by the client software; the client software sends the packed data, the working step flow and the starting test parameters to the server, the server forwards the packed data, the working step flow and the starting test parameters to the middle computer, the channel is started, the test is started, and the channel executes charging or discharging or standing according to the working step flow; and ending the test until the step flow of the test channel is executed. Simulation data are configured through the matrix, and richer simulation data testing requirements of users are met.