30 results about "Source determination" patented technology

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 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 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.

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.

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 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 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.

The application discloses a lubricating oil purification process monitoring and early warning system and method based on big data analysis, and belongs to the technical field of fault prediction and health management, and comprises the following steps: acquiring inlet oil sample MPC data, outlet oil sample MPC data, bypass operation data and equipment surface response data; generating corresponding precipitable precursor difference according to the inlet oil sample MPC data and the outlet oil sample MPC data and generating inlet and outlet difference; forming flow verification records; generating an interpretable drop and an actual drop, comparing and obtaining a drop interpretation result; and generating an MPC drop source determination result and a corresponding early warning result. The application compares the precipitable precursor difference with the purification capacity and links the equipment surface response, so that the effect of accurately determining the drop source of the paint film precursor is achieved, and the problem that the risk cannot be determined only by the MPC value is solved.

The invention belongs to the field of geological disaster recognition, and relates to a mountain geological disaster hazard source recognition method and system based on artificial intelligence, and the method comprises the steps: 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 a plurality of sub-identification areas, and determining heterogeneous meta-paths of the sub-identification areas to obtain a meta-path set and a path instance set of the identification area; processing heterogeneous element paths in the element path set through a self-adaptive path propagation operator to obtain region fusion features of terrain grid nodes of each sub-recognition region; adaptive weight optimization and hazard source determination are carried out based on the regional fusion features and historical disaster point labels, and geological disaster hazard source distribution conditions are obtained; the bottleneck of multi-modal heterogeneous data fusion is broken through, an intelligent identification method adaptive to the regional disaster formation law is constructed, and the accuracy and efficiency of mountain geological disaster hazard source identification are improved.

This application relates to a method and apparatus for multi-dimensional source tracing of water pollution sources. The method includes: performing cluster analysis on the collected fluorescent fingerprints of the water body to be traced and fingerprints in a typical fluorescent fingerprint library in a pre-set multi-dimensional fluorescent fingerprint database to obtain cluster analysis results. If no suspected pollution sources are found in the cluster analysis results, the optimal pollution source determination strategy is matched based on the number of fluorescence peaks and the emission wavelength of the fluorescence peaks in the fluorescent fingerprints of the water body to be traced, thereby determining the suspected pollution sources of the water body to be traced. This solves the problems of inability to simultaneously trace multiple pollution sources, lack of standardized procedures for sample and fluorescent fingerprint collection, low efficiency, and poor timeliness in related technologies. By standardizing samples and fluorescent fingerprints and adopting online multi-pollution source tracing technology, the accuracy of fluorescent fingerprints, the timeliness of the source tracing method, and the reliability and stability of the source tracing results are improved.

The present disclosure provides an image source determination method, an image source determination apparatus, and a storage medium. The image source determination method includes selecting at least a portion of a target image as a target region; when the target region is a valid region, extracting edge pixels in the target region; and determining a generation source of the target image according to a quantity of chromas of the edge pixels in the target region.

The invention discloses an information source determination method and device, a storage medium and electronic equipment, and relates to the technical field of education, and the method comprises the steps: obtaining multi-modal initial data from a plurality of independent information systems, and generating a plurality of information units; determining structured information entities and information source fragments respectively corresponding to the plurality of information units, and constructing a multi-modal knowledge graph corresponding to the multi-modal initial data according to a multi-dimensional association relationship corresponding to the structured information entities and the information source fragments; traceability links corresponding to the multiple information units are generated according to the multi-dimensional incidence relation, and the traceability links are stored in the multi-modal knowledge graph; and calling a target tracing link corresponding to the target information unit, determining a target information source of the target information unit, and displaying the target information source to a user in at least one multimedia form. According to the invention, through constructing the multi-modal knowledge graph, accurate positioning and visual presentation of an information source are realized, and the credibility of a traceability result is improved.

The present disclosure provides a model data source determination method and device, equipment and storage medium, and relates to the technical field of big data. In some embodiments of the present disclosure, first key characteristic index data and second key characteristic index data of a target area in which a target user is located in a set historical period are obtained; an actual general data standard of the target area is determined, and an actual upgrade data standard of the target area is determined; a first difference value of the first key characteristic index data and the actual general data standard is determined, and a second difference value of the second key characteristic index data and the actual upgrade data standard is determined; and a data set that is suitable for the target user is selected from a general data set and an upgrade data set according to the first difference value and the second difference value, thereby providing a method for recommending a matched data source for the target area, and further improving the accuracy of a subsequent network quality difference identification model.

The present application provides a multi-agent area exploration method and system based on tree crown shyness and a pollution source determination method, belonging to the technical field of multi-agent area coverage. The present application can establish an agent area exploration model according to a pollutant density distribution function, determine the direction of the next exploration of the agent using the agent area exploration model, determine the moving path of the agent, obtain the next exploration node of the agent, and achieve the purpose of adaptively determining the shyness space of the agent according to the concentration of the pollutant, thereby covering all areas of pollutant concentration detection. At the same time, based on the tree crown shyness mechanism, the agent can automatically adjust the shyness space according to the adjacent agent or the obstacle occupying space, avoid collision between the agent and the obstacle, realize automatic obstacle avoidance, and avoid path conflict and repetitive exploration.

This invention discloses a quantitative characterization method for differentiating clay minerals of different origins in continental shale, relating to the field of reservoir mineral characterization technology in unconventional oil and gas resource exploration. It includes: S1, data acquisition step; S2, type classification step; S3, data analysis step; S4, difference source determination and quantitative determination step; S5, inversion step. The quantitative characterization method for differentiating clay minerals of different origins provided by this invention offers a theoretical basis and scientific evidence for the brittleness evaluation of continental shale, and has significant guiding significance for breaking through the theoretical bottleneck of continental shale oil fracturing and improving production efficiency.

The application discloses a heterogeneous well logging data processing method and device, and the method comprises the following steps: collecting well logging data of a target well hole; determining data screening conditions of different well logging data types according to depth index sources corresponding to the different well logging data types; the data screening conditions comprise a reference depth and a curve value mode; determining candidate well logging data according to the data screening conditions of the different well logging data types comprising the reference depth and the curve value mode; and determining target well logging data according to the candidate well logging data. By determining the data screening conditions of the different well logging data types, such as the reference depth and the curve value mode, and then determining the target well logging data from the candidate well logging data determined based on the data screening conditions, the efficiency and accuracy of well logging data screening can be improved.

The present disclosure provides a defect processing method, device, equipment, storage medium and program product, relates to the technical field of computers and data processing, and particularly relates to the technical field of software defect processing. The specific implementation scheme is as follows: for any target party in a plurality of parties, in response to a confirmation instruction for a target defect, a target source is determined according to a candidate source of the target defect, wherein the processing party of the target defect is the target party, the processing party of the target defect is obtained according to a code label of target code including the target defect; the candidate source is determined by the processing party processing the target defect; and in response to a modification operation of the processing party on the target defect, target party defect analysis data is determined.

The invention relates to a metabolic aging biological age assessment method and device based on an AIP index. The method comprises the following steps: carrying out source determination and preprocessing on metabolic syndrome related evaluation data; based on the preprocessed AIP index and other clinical indexes, adopting a machine learning PCA algorithm to construct a metabolic aging biological age (MS-BA) model; and calculating individual MS-BA according to the model, evaluating the health state in combination with the social age, and generating an intervention scheme. According to the method, an exclusive model is constructed for people with metabolic syndromes, and the metabolic aging degree is accurately reflected through quantitative calculation.

The application discloses a kind of basin water body nitrogen pollution multi-fingerprint coupling accurate tracing method, comprising: detecting the anion, cation and isotope data of end member sample, construct local fingerprint database, detect in-situ closed hydrological unit, obtain anion, cation and isotope data, calculate nitrate residual proportion, nitrate nitrogen denitrification fractionation coefficient and nitrate oxygen denitrification fractionation coefficient, collect water sample at sampling section, detect anion, cation and isotope data, remove non-nitrogen pollution source input, calculate nitrogen pollution source input, obtain corrected molar ratio, calculate nitrate residual proportion and corrected pollution source original isotope characteristic value, and match with local fingerprint database to obtain the type of pollution source. Thus, it can solve the distortion of isotope correction caused by general denitrification fractionation coefficient, utilize the whole process accurate correction of chlorine ion tracer fingerprint, and greatly improve the accuracy of pollution source determination result.

The application discloses a special robot cooperative auxiliary rescue control method for building fire fighting. In the real fire source determination process, the application introduces the features of the flame centroid displacement and the flame roughness, so that the problem that the mobile flame cannot be accurately recognized in the indoor environment is solved. In addition, a multi-sensor fusion recognition algorithm is adopted, so that the recognition misjudgment rate is greatly reduced. When the building fire fighting robots are dispatched, the number of the building fire fighting robots K is used to adjust the edge bar items of the fire source convex hull, so that more convenient and reasonable robot spraying station positions are realized. The application provides a complete, safe and fast emergency fire extinguishing scheme from discovering a suspected fire source, judging the authenticity and category of the fire source and dispatching the building fire fighting robots to extinguish the fire.

The application discloses a genome penetration identification method fusing parent-specific SNPs and population allele frequencies, and relates to the technical field of bioinformatics and data processing. The method is based on the whole genome variation data of a parent population with a known source, uses the difference in population allele frequencies to screen parent-specific diagnostic SNP sites, and constructs a diagnostic SNP library. For the whole genome variation data of a sample to be measured, parent sources are determined in a preset sliding window through a physical path and a statistical path. On this basis, the double-path determination results are fused according to the decision rules of physical priority and loss completion, and the final determination results of each sliding window are obtained. Then, through continuous window merging and chromosome physical coordinate mapping, a phase block list and a visual karyotype map are output. The method is beneficial to improving the accuracy and robustness of parent source determination of chromosome segments.