57 results about "Source determination" patented technology

The present application discloses a data processing method, device and system, and a storage medium. The method of the present application comprises: constructing a quality problem dictionary on the basis of an experience database, the quality problem dictionary comprising data quality problems and corresponding problem identifiers; acquiring data to be processed, and identifying a target data problem present in the data to be processed; querying the quality problem dictionary for the target data problem to obtain a corresponding target problem identifier; adding the target question identifier into target data by means of a predefined field; reading a plurality of target fields in the target data, determining the plurality of target fields according to a preset fusion rule, and on the basis of a determination result, determining whether there is conflict data; if there is conflict data, identifying a service application scenario of the current data, and selecting an authority source determination strategy on the basis of an identification result; and processing the credible source authority level of each field in the conflict data according to the authority source determination strategy, and updating the database.

The invention relates to the technical field of coal mine safety, in particular to a water inrush and rock burst composite disaster risk multi-source judgment method which comprises the steps that four fields of original data of a target underground area are collected in real time, and the four fields comprise a stress field, a vibration field, an energy field and a seepage field; extracting multivariate feature indexes from the four-field original data to obtain four-field multivariate indexes; constructing a core composite index based on the four-field multi-element indexes, quantifying the coupling strength of water inrush and rock burst, and judging a disaster dominant type; and calculating a comprehensive risk index based on the four-field multi-element indexes and the disaster dominant type, and judging the risk level of the water inrush and rock burst composite disaster according to the comprehensive risk index. According to the invention, accurate identification and graded prevention and control of composite disasters are realized, and the accuracy and timeliness of early warning of mine disasters are significantly improved.

The invention discloses a vehicle communication fault source determination method and related equipment, and relates to the technical field of vehicle communication, the method comprises the following steps: obtaining communication operation information of a plurality of processing levels in a vehicle communication system, the plurality of processing levels comprising a hardware layer, a middle layer, a security layer and a network layer; based on a preset log format, recording the communication operation information, and generating an encrypted log; and performing fault root cause analysis on the encrypted log through a preset fault tree model to obtain a target fault source. Through multi-level log acquisition and fault tree analysis, in combination with a structured format and encrypted storage, vehicle communication fault diagnosis with accurate and efficient fault positioning, data traceability, safety and credibility can be realized.

The invention relates to the technical field of sewage treatment, in particular to a method and a system for quickly tracing sewage. According to the technical scheme, the system comprises a data acquisition and processing module, a data analysis module and a result display and decision support sub-module. According to the method, the sewage pollution source can be quickly positioned, the discharge intensity can be quickly estimated, and the time interval from pollution discovery to pollution source determination is shortened; according to the method, the position of the pollution source and the emission intensity are accurately determined through comprehensive learning and analysis of multiple factors on the basis of an algorithm combining a convolutional neural network and a long-short-term memory network in deep learning, and the traceability accuracy is remarkably improved; through model training and optimization, the system has the characteristic of data driving, model overfitting is effectively prevented by adopting a regularization technology, the generalization ability of the model is enhanced, meanwhile, the model is continuously evaluated and adjusted according to evaluation indexes, and high traceability accuracy and reliability are kept.

The invention relates to the technical field of atmospheric monitoring, and discloses an intelligent data auditing management method for environmental air quality monitoring, which comprises the following steps: establishing a three-dimensional coordinate system at one point of the ground where a monitoring station is located; according to the position and the height of the building, executing an optimal sampling strategy, and calculating the number and the position of the sampling devices arranged at the monitoring stations so as to maximize air circulation; when the data of the gas sample is monitored to be abnormal, executing an abnormal source determination strategy and judging the reason of the data abnormality, specifically, executing a pre-classification strategy, calculating the probability of the data abnormality caused by the equipment fault and the probability of the data abnormality caused by the environment abnormality, and respectively recording the probability as a first probability and a second probability; if the first probability is greater than the second probability, executing an equipment exception judgment strategy to obtain an exception source determination result; and if the first probability is smaller than or equal to the second probability, executing the environment abnormity judgment strategy to obtain an abnormal source determination result, thereby improving the accuracy of atmospheric monitoring abnormal source determination.

The invention relates to the technical field of voice processing, can be applied to business scenes such as financial science and technology, medical health and the like, and discloses a data tracing method, device, equipment and medium based on cooperative training, which comprises the following steps: obtaining a generative model and a discrimination model to output initial intermediate feature representation, generating voice data and inputting the voice data into the discrimination model to generate discrimination loss; updating the generation model based on the discrimination loss to obtain a traceable intermediate feature representation, generating an updated intermediate feature representation by using the updated generation model, generating training voice data, and inputting the training voice data and real data into the discrimination model for training to obtain an updated discrimination model; and when input voice data is received, the updated discrimination model is used for discriminating and outputting a detection result whether the input voice data is generated by the generation model or not. According to the invention, through cooperative training of the generative model and the discrimination model, the generative model outputs voice embedded with traceable features, the rejection capability of the discrimination model to unknown sources is improved, and waveform disturbance reduction and accurate source determination are realized.

The invention discloses a situation awareness-based metal processing error monitoring method and system, and particularly relates to the technical field of intelligent manufacturing, and the method comprises the steps: obtaining workpiece point cloud data, executing geometric reconstruction and coordinate alignment, and forming a workpiece individual geometric expression structure which can be used for recognizing a metal processing error; the structure basis is used for subsequent difference analysis and error source judgment; performing spatial difference vector solution and difference attribute division on the workpiece individual geometric expression structure and the standard design geometric expression structure to form a difference expression structure which is consistent in structure and contains local offset information, and taking the difference expression structure as input of path adaptation; according to the method, a dynamic coupling relation between an individual geometric expression structure of a workpiece and a machining behavior variable is constructed, and a deviation situation among three elements is perceived in real time before a path is generated and in a machining process, so that early recognition and response to a machining error are realized, and the problems that the error cannot be actively recognized and the path is mismatched in a customized machining scene are solved.

A method involving collecting a first geochemical data set for a first plurality of produced water samples; collecting a second plurality of produced water samples; performing geochemical analyses on the second plurality of produced water samples to form a second geochemical data set; and combining the first and second geochemical data sets into a database. The method further includes determining, by a subject matter expert, a water type for each produced water sample in the database and training a machine-learned model with the database to predict the water type of a produced water sample given its geochemical data. The method further includes collecting a third plurality of produced water samples, performing geochemical analysis on the third plurality of produced water samples, and determining, with the trained machine-learned model, the water type for each produced water sample in the third plurality of produced water samples using the third geochemical data set.

The invention provides a glitch power consumption optimization system and method based on logic efficacy, and relates to the technical field of electrical digital data processing.The glitch power consumption optimization system based on the logic efficacy comprises a path efficacy calculation module used for determining the path logic efficacy, the path branch efficacy and the path electrical efficacy of each path, determining the path efficacy of each path; the burr source identification module is used for determining an actual delay difference value between the paths converged to the same path convergence point, and judging the path convergence point as a burr source when the actual delay difference value meets a preset burr source judgment condition; and the burr optimization module is used for generating burr optimization suggestions of the burr source. According to the scheme, potential glitch risks of different circuit topological structures can be rapidly evaluated without depending on a series of processes such as integration, physical implementation, parasitic parameter extraction, post-simulation and glitch power consumption evaluation, traditional experience-driven optimization is converted into data-driven scientific optimization, and the glitch power consumption optimization effect is improved.

The embodiment of the invention provides a noise source determination method and device, and belongs to the field of mechanical equipment optimization. The method comprises the following steps: carrying out noise contribution analysis on a plurality of components of the mechanical equipment, and determining main noise source components; constructing a finite element structure model of the mechanical equipment; noise excitation is conducted on the finite element structure model to obtain noise response information, corresponding to the main noise source component, of the finite element structure model, and the noise response information comprises noise peak values under different excitation frequencies; performing equivalent radiation sound power analysis on a finite element structure model corresponding to the main noise source component according to the noise response information to obtain a first analysis result; and determining a noise main contribution position of the main noise source component according to the first analysis result and the noise peak values under different excitation frequencies. Through the method, the noise source can accurately determine the specific position on the single component, and the noise optimization of the mechanical equipment is more targeted.

Systems and methods are disclosed for enhanced internet-of-things sensor analysis and real-time trust provenance determination. An example method includes determining a subset of a plurality of IoT sensors from which data is to be aggregated, the subset of the plurality of IoT sensors being responsive to one or more constraints, wherein individual IoT sensors are configured to generate data provenance information which, at least, cryptographically identifies data as originating from the individual IoT sensors; instructing the subset of the IoT sensors to generate data, wherein a first IoT sensor of the subset is instructed to execute a custom workload, and wherein the data provenance information generated via the first IoT sensor is to be cryptographically signed; and aggregating output data associated with the subset of the IoT sensors, wherein data provenance information associated with the IoT sensors is validated to form a trusted network chain.

This application provides a dialing test source determining method and apparatus, and a computing device cluster. In embodiments, the method is applied to a cloud management platform, and includes: providing a configuration interface, where the configuration interface is configured to obtain a dialing test instruction that is set by a user, and the dialing test instruction includes a target service on which a dialing test is to be performed; obtaining, from a database, a set of services that have called the target service, where the database includes a call relationship between multiple services including the target service; and determining a dialing test source based on at least one server corresponding to the set of services that have called the target service, where a server on which a service in the service set is deployed belongs to at least one network segment, and the at least one server also belongs to the at least one network segment. In conclusion, only the service on which the dialing test is to be performed needs to be manually configured, and the cloud management platform automatically determines the dialing test source based on the service call relationship, and does not need to configure the dialing test source. This reduces complexity of dialing test source configuration.

Systems and methods are described for identifying a list of sources available for a content item. An input associated with selecting a content item is received at a computing device. The availability of the content item from more than one source is identified. The available bandwidth of the computing device is determined. The respective resolutions of the selected content item from each respective source is determined based on metadata. A recommendation factor for each of the respective resolutions from each of the plurality of source is determined. The recommendation factor is based on whether the respective resolution is supported by the available bandwidth. A list including the sources and a respective resolution of the content item is generated for output. The list is ordered based on the recommendation factor for each respective source. Each available resolution is formatted base on the associated recommendation factor being above or below threshold level.

A method involving collecting a first geochemical data set for a first plurality of produced water samples; collecting a second plurality of produced water samples; performing geochemical analyses on the second plurality of produced water samples to form a second geochemical data set; and combining the first and second geochemical data sets into a database. The method further includes determining, by a subject matter expert, a water type for each produced water sample in the database and training a machine-learned model with the database to predict the water type of a produced water sample given its geochemical data. The method further includes collecting a third plurality of produced water samples, performing geochemical analysis on the third plurality of produced water samples, and determining, with the trained machine-learned model, the water type for each produced water sample in the third plurality of produced water samples using the third geochemical data set.

A computer-implemented method for monitoring. The method comprises obtaining, by a waste monitoring unit, one or more images of waste, providing data representing the one or more images as input to a first model configured to output, for at least one of the one or more objects depicted in the one or more images, data indicating the at least one object, and outputting an object source score for each of the at least one object, comprising providing the data indicating the at least one object as input to a source determination model configured to output a source determination model output indicating one or more corresponding object source scores, each object source score indicative of a likelihood that a source of one of the at least one objects depicted in the one or more images can be determined.

The embodiment of the invention discloses a macular cigarette pollution source determination method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an acquired target cigarette image of a target cigarette of a to-be-identified pollution source type; wherein the target cigarette image comprises at least one yellow spot area; target color information of target yellow spots in the target cigarette image is extracted, and target attribute parameters of the target yellow spots are determined based on the target color information; and inputting the target attribute parameter into a pre-constructed target discrimination function model corresponding to each pollution source type, and determining a target pollution source type of the target yellow spot based on an output result of each target discrimination function model. According to the technical scheme provided by the embodiment of the invention, the target pollution source type of the target yellow spot can be quickly and accurately determined, manual participation is not needed, and the labor cost is reduced.

The application belongs to the technical field of data filtering, and discloses a bacteriophage metagenomic sequencing data host sequence filtering method; comprising: obtaining bacteriophage metagenomic sequencing data of a sample to be analyzed and performing pretreatment to obtain quality filtered read data; calculating a host abundance background value corresponding to the sample to be analyzed, configuring a corresponding host genome library, and setting an alignment determination threshold; performing source classification, outputting a host mapping read set, a bacteriophage candidate read set, and a boundary candidate read set; performing joint source re-determination to identify remedial fragments belonging to non-host sequences; performing sequence assembly to obtain candidate contigs and performing true source determination, and performing reverse correction based on the determination result; identifying a deviation state and updating and compensating the alignment determination threshold of the sample to be analyzed in a subsequent batch; and improving the accuracy of bacteriophage metagenomic sequencing data host sequence filtering.

The application discloses a method and device for determining an attack source of an APT attack and electronic equipment. The method comprises: acquiring multi-source data corresponding to a plurality of attack events of a target network in a current period, wherein the attack event refers to a unit supporting independent detection in APT attack detection; determining target confidence degrees corresponding to the plurality of attack events based on the multi-source data corresponding to the plurality of attack events, wherein the target confidence degree is used to indicate the credibility of the corresponding attack event being an APT attack; screening a high-confidence attack event set from the plurality of attack events based on the target confidence degrees corresponding to the plurality of attack events; and determining the attack source of the APT attack based on the target confidence degrees corresponding to the plurality of high-confidence attack events included in the high-confidence attack event set. The application solves the technical problem of inaccurate determination of the attack source of the APT attack in the related art.

The invention discloses a determination method and application method for a pre-examination triage process, and the method comprises the steps: defining a patient type which comprises a first feature and a second feature; pre-examination triage user information is determined, and the name, attribute and content of a user information group are defined; the content of the user information group comprises one or more pieces of user information; the attributes of the user information group comprise an acquisition source, an optimal acquisition time length and an actual acquisition time length; constructing a pre-examination triage module, wherein the content of the module corresponds to the user information group and the patient type; generating a plurality of pre-examination triage test processes; and executing test comparison, determining an optimal acquisition source from a plurality of pre-examination triage test processes, and determining a pre-examination triage process. According to the technical scheme, the speed and accuracy of information registration can be improved, and later data can be reused conveniently.

The embodiment of the invention discloses a task flow source determination method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps that a target burying point data set corresponding to a target task is determined, the target task is used for obtaining a target article, and the target burying point data set comprises user behavior data obtained by setting burying points on a display page of the target article; determining effective behavior data of the target task in the target burying point data set according to an effective tracing condition, and determining source tracking data of the target task according to the effective behavior data; and determining a traffic source of the target task in a traffic source table according to the source tracking data. According to the technical scheme, the flow source table is searched based on the flow source parameters obtained by analyzing the source tracking data of the target task, the flow source of the target task is determined, and the flow source of the target task is accurately determined.

The present invention relates to the field of atmospheric monitoring technology and discloses an intelligent data audit management method for ambient air quality monitoring, comprising: establishing a three-dimensional coordinate system at a point on the ground where a monitoring site is located; executing an optimal sampling strategy based on the location and height of a building, and calculating the number and location of sampling devices arranged at the monitoring site to maximize air circulation; when abnormal data of a gas sample is monitored, executing an abnormality source determination strategy to determine the cause of the data abnormality, specifically: executing a pre-classification strategy to calculate the probability that the data abnormality is caused by an equipment failure and the probability that the data abnormality is caused by an environmental abnormality, which are recorded as a first probability and a second probability respectively; if the first probability is greater than the second probability, executing an equipment abnormality determination strategy to obtain an abnormality source determination result; if the first probability is less than or equal to the second probability, executing an environmental abnormality determination strategy to obtain an abnormality source determination result, thereby improving the accuracy of abnormality source determination in atmospheric monitoring.

The present disclosure provides a deep space exploration microwave load interference source determination method, device, equipment and medium, the method comprising: calculating the time domain correlation coefficient between the microwave signals received by different polarization antennas at the same time; calculating the frequency domain correlation coefficient between the microwave signals received by different polarization antennas at the same frequency point; calculating the cross-correlation coefficient between the microwave signals received by the same polarization antenna at different times; determining the source and frequency of the interference signal according to the time domain correlation coefficient and / or the frequency domain correlation coefficient and / or the cross-correlation coefficient. This method can realize intuitive and reliable analysis of microwave interference sources, solving the technical problem of determining the interference source due to complex interference conditions.

Systems and methods are disclosed for enhanced internet-of-things sensor analysis and real-time trust provenance determination. An example method includes determining a subset of a plurality of IoT sensors from which data is to be aggregated, the subset of the plurality of IoT sensors being responsive to one or more constraints, wherein individual IoT sensors are configured to generate data provenance information which, at least, cryptographically identifies data as originating from the individual IoT sensors; instructing the subset of the IoT sensors to generate data, wherein a first IoT sensor of the subset is instructed to execute a custom workload, and wherein the data provenance information generated via the first IoT sensor is to be cryptographically signed; and aggregating output data associated with the subset of the IoT sensors, wherein data provenance information associated with the IoT sensors is validated to form a trusted network chain.

The embodiment of the present specification belongs to the field of numerical simulation, and particularly relates to a first collision source determination method and device for shielding calculation, which comprises the following steps: obtaining information of a source term of a particle and information of a preset first collision point of the particle, wherein the preset first collision point represents a position where the particle collides with a material for the first time in a transport process; determining one or more geometric body models for representing a region passed through by the particle when the particle reaches the preset first collision point; calculating a passing distance of the particle in each of the geometric body models, and determining a first collision source corresponding to the preset first collision point according to the passing distance and material information corresponding to each of the geometric body models. The embodiment of the present specification solves the problem of high calculation cost of the first collision source in the existing simulation calculation.

The invention relates to the technical field of pollution supervision, in particular to an accurate pollution source supervision system based on the Internet of Things and big data. According to the system, through the whole-process design of constructing a prediction region concentration thermodynamic diagram, identifying a high-concentration clustering region, extracting key features, establishing space-time correlation mapping, screening candidate pollution source correlation points and determining time sequence causal intensity, the independent advantage and the collaborative advantage of logic progression are formed; a two-dimensional evaluation system of thermodynamic diagram clustering evidence credibility and monitoring point correlation evidence score credibility is introduced, the thermodynamic diagram clustering evidence credibility verifies the reliability of pollution source positioning through the matching degree of the space gravity center of a high-concentration clustering area and the concentration peak value, and the monitoring point correlation verification method strengthens data support through the linear correlation degree of a correlation verification monitoring point. And the two methods form a comprehensive credibility index through weighted fusion, so that the one-sidedness of a single evidence is avoided, and the scientificity and the anti-interference capability of pollution source judgment are remarkably improved through a space-data dual verification mechanism.

The invention provides a method for identifying rhizoma acori graminei and rhizoma acori graminei based on an MALDI-MSI technology, and relates to the technical field of pharmaceutical analysis. The method comprises the following steps: preparing a frozen slice and coating the surface of the frozen slice with a matrix; scanning the frozen section in a positive ion mode to acquire mass spectrum imaging data; and identifying the spatial distribution characteristics of the characteristic ions in the region of interest. According to the method, a DHB matrix is coated with a sublimation method for MALDI-MSI imaging, sample swelling and migration are avoided, and it is ensured that in-situ information is real; based on the distribution difference of characteristic ions from a cambium to a center column, pretreatment and reference substances are not needed, the problem that the grass-leaved sweetflag rhizome and the Tibetan acorus calamus are similar in form and difficult to identify is solved, and objective and visual base source judgment is achieved.

This application belongs to the field of radar reconnaissance technology and provides a single-source radiation determination method based on temporal information entropy. It first calculates the Time Difference of Arrival (TDOA) of all adjacent pulses, then sets a clustering threshold and a first-class cluster center, and uses a clustering algorithm to obtain multiple clusters based on the TDOA. Next, it reduces the number of clusters and removes invalid elements by merging and removing harmonics. The distribution probability of each TDOA is calculated based on the number of indices in the merged clusters after harmonic removal. The temporal information entropy is calculated based on the distribution probability of each TDOA. A set information entropy discrimination threshold is set; if the temporal information entropy does not exceed the threshold, the pre-sorted signal is considered to be composed of a single radiation source; otherwise, it is composed of multiple radiation sources. This method can accurately determine the composition of radiation source signals in the radar pre-sorting clustering results, avoiding further PRI main sorting processing of single-source signals and reducing redundant sorting calculations.

The present application belongs to the field of geological disaster identification, and relates to a mountainous area geological disaster hazard source identification method and system based on artificial intelligence, comprising: collecting multi-modal heterogeneous data related to geological disasters, and constructing a multi-modal heterogeneous attribute graph based on the multi-modal heterogeneous data; dividing the identification area into multiple sub-identification areas, and determining the heterogeneous meta path of the sub-identification area to obtain the meta path set and the path instance set of the identification area; processing the heterogeneous meta path in the meta path set through an adaptive path propagation operator to obtain the regional fusion features of the topographic grid nodes of each sub-identification area; performing adaptive weight optimization and hazard source determination based on the regional fusion features and historical disaster point labels to obtain the distribution of geological disaster hazard sources; breaking through the multi-modal heterogeneous data fusion bottleneck, constructing an intelligent identification method suitable for regional disaster patterns, and improving the accuracy and efficiency of mountainous area geological disaster hazard source identification.

The invention discloses a full-band electromagnetic signal interference device and method based on noise coverage. The full-band electromagnetic signal interference device comprises a receiving link module, an interference source determination module, a noise generation module, a power distribution module and an antenna radiation module, the receiving link module is used for sensing a target electromagnetic signal in a target area in real time, scanning and analyzing the electromagnetic signal in a frequency band range of 1 MHz to 40 GHz, and converting the signal into a digital signal; and the interference source determination module is used for carrying out de-synchronization processing on the digital signal. The invention belongs to the technical field of electromagnetic signal interference, and aims to solve the problems that interference is carried out only for a specific frequency band, an ultra-wide frequency band is difficult to cover, and energy distribution among the frequency bands cannot be solved in the prior art. The method has the technical effects that the problems that only specific frequency bands are interfered, ultra-wide frequency bands are difficult to cover, and energy distribution among the frequency bands cannot be solved are solved.

The invention discloses a data processing method and device, equipment, a storage medium and a program product, and relates to the technical field of databases. The method comprises the steps of obtaining a target table and a blood relationship mapping relation corresponding to the target table; under the condition that the first field with the field value missing exists in the target table, tracing the source of the target table according to the blood relationship mapping relation, and determining a source table corresponding to the target table; positioning a field position corresponding to the first field in a source table to obtain a target field corresponding to the first field in the source table; performing semantic analysis on the target field to obtain a field identifier and field attribute information of the target field; searching value association information corresponding to the target field according to at least one of the field identifier, the field attribute information and a blood relationship mapping relationship; generating a target field value according to the value association information; and filling the target field value into a position corresponding to the target field in the source table. According to the embodiment of the invention, the data generation and filling efficiency can be improved.