253 results about "Reference database" patented technology

A system and method for mitigating cyber-attacks against a target network comprising interconnected note that is implemented by Open Systems Interconnection (OSI) layers monitors the target network for detecting vulnerabilities across one or more OIS layers. a virtual network comprising a virtualized representation of the target network where the virtual network includes one or more virtual nodes that are annotated with identified vulnerabilities of one or more corresponding nods of the target network. A reference database can be configured to store records of known cyber-attacks and their corresponding mitigations where cyber-attacks on the virtual network are simulated based on records of known cyber-attacks and successful cyber-attacks. An AI engine can be configured to generate one or more mitigation actions based on simulation of the cyber-attacks before implementing the one or more mitigation actions to the target network.

The invention discloses an integrated collaborative management method for construction site risk operation data, and belongs to the technical field of data management. The method comprises the following steps: constructing and calibrating a space-time risk reference database; deducing a potential risk conduction link set, and generating an associated intervention knowledge base; during operation, through multi-sensor cooperative verification, an abnormal signal is confirmed as a risk event; matching the risk event with a conduction link to calculate a risk upgrade level and dynamically adjust an early warning threshold; and when the early warning is triggered, generating and issuing a dynamic collaborative response instruction, and feeding back a processing result to correct the reference database to form a management closed loop. According to the method, the technical means of constructing the space-time risk reference, deducing the conduction link, cooperatively verifying the risk and dynamically regulating and controlling the threshold are adopted, so that the predictability of project risk management and control, the efficiency of resource cooperative scheduling and the scientificity of overall management decision are improved.

The invention discloses a reservoir dam safety monitoring method and system based on edge calculation, and relates to the technical field of hydraulic engineering safety monitoring, and the method comprises the steps: obtaining monitoring data by each edge calculation node, carrying out the preprocessing, and generating a standardized data matrix; establishing a reference database, executing anomaly detection, and generating a labeling time sequence data matrix; performing multi-scale decomposition on the labeled time sequence data matrix, and constructing a node response feature matrix; the central processing unit receives data of each edge computing node, analyzes a multi-parameter spatial propagation mode by constructing a parameter-spatial correlation matrix, and obtains a spatial correlation feature matrix; establishing a Bayesian risk assessment model, predicting a dam risk level and outputting a risk evolution trend; and issuing a differentiated early warning instruction according to the risk assessment result. Through a distributed architecture combining edge calculation and central processing, real-time monitoring, intelligent analysis and accurate early warning of the dam safety state are realized, and the monitoring efficiency and the risk identification accuracy are improved.

An automated clinical trial matching system is disclosed, which may be used by a care provider to generate a shortlist of clinical trials that a patient may participate in, or by a trial coordinator to generate a list of patients eligible for a given clinical trial. The clinical trial matching system may rely on large language models (LLMs), clinical ontologies, reference databases, clinical guidelines, etc., to generate patient data models and clinical trial data models including structured data that may be directly compared using a matching model. Clinical trials that match a patient and / or patients that match a clinical trial may then be ranked, with top ranking results being shortlisted for display to the care provider or trial coordinator. The clinical trial matching system may display the top ranking results in a graphical user interface that indicates elements of a clinical trial and patient data that match.

The invention discloses a skull data comparison method based on artificial intelligence. The skull data comparison method comprises the following steps: S1, acquiring three-dimensional scanning data of a skull to be detected and a reference skull database; s2, preprocessing the skull data to be detected; s3, multi-dimensional features of the skull to be detected are extracted through the deep learning model; s4, performing similarity comparison on the skull features to be detected and skull features in the reference database to generate a matching degree score; s5, outputting identity information or a morphological analysis result of the target reference skull according to the matching degree score; the invention further provides a skull data comparison system based on artificial intelligence. The skull data comparison system comprises a data acquisition module, a preprocessing module, a feature extraction module, an intelligent comparison module and a visual output module. Compared with the prior art, the method has the advantages that the comparison accuracy is high; the processing speed is high; the application range is wide.

The invention relates to the technical field of music score matching, in particular to an audio and music score matching method and system, and the method comprises the steps: providing a reference database of a music score, which comprises multiple segments of expected playing characteristics of a plurality of music units; acquiring first note data generated by playing of the user at first time; judging whether second note data generated at adjacent second time before the first time is successfully matched with the first target music unit or not; if yes, determining a first dynamic prediction sequence at the first time according to the first target music unit; judging whether the corresponding music unit obtained in the first dynamic prediction sequence is a second target music unit of the first note data or not; and if yes, marking the second target music unit as the current playing node. According to the music score matching technology, the matching time axis can be dynamically adjusted in combination with the playing state, and then positioning matching of the audio and the music score can be rapidly achieved through the limited matching calculation amount.

The present invention discloses a method, device, and medium for identifying software component analysis, which relates to the technical field of software technology. Specifically, it includes: obtaining all files in the software to be identified to obtain a first data set; extracting meta-file data to obtain a second data set, and obtaining a first open-source file set through first feature matching; performing deletion processing on the first data set to obtain a third data set, calculating the minimum hash signature through the program abstract syntax tree and the corresponding sub-syntax tree to generate a second feature set, and obtaining a second open-source file set through third feature matching; performing deletion processing on the third data set to obtain a fourth data set, obtaining an updated syntax tree based on the abstract syntax tree and the fourth data set and constructing a control flow diagram, and obtaining a third open-source file set through fourth feature matching between the third feature set and a preset reference database; merging the first open-source file set, the second open-source file set, and the second open-source file set to obtain the total open-source component set in the software to be identified.

The invention discloses a processing method and device for sensing the position of an elevator, and relates to the technical field of elevator position sensing, which comprises the following steps: running in a full stroke under no-load and rated load conditions respectively, recording pulse signal data of a magnetic induction sensor when the elevator stops on each floor and the maximum value of a pulse signal when the elevator passes through each floor, establishing a dual-mode reference database; elevator regular no-load running full-stroke detection is carried out, and elevator real-time stopping deviation is analyzed; when the elevator is powered off or breaks down, counting of the pulse counters corresponding to the current top sensor and the current bottom sensor is obtained, elevator power-off or fault stopping floors are determined, elevator power-off or fault stopping deviation is analyzed, elevator power-off or fault actual stopping deviation is obtained after elevator real-time stopping deviation is subtracted, and the position of the elevator is determined. And the elevator trapped floor and the position of the elevator trapped floor in the hoistway can be quickly positioned, the response time is shortened, blind operation is avoided, and the secondary accident risk is reduced.

The invention discloses a key marker gene-based intelligent cell type annotation method, which comprises the following steps of: constructing a static knowledge base by using known marker genes in a reference database, and endowing the marker genes with cell specific weights by using a TF-IDF method, so that the annotation accuracy and interpretability are improved. Meanwhile, under the condition that static matching is insufficient, the literature is understood through a large language model, mark information is extracted, dynamic completion of the knowledge base is achieved, the defect that updating of a traditional knowledge base is lagged is overcome, and good adaptability and expansibility are achieved. Besides, static and dynamic matching scores are fused in the annotation process, so that more robust cell type identification is realized, annotation requirements of multi-tissue, multi-species and novel cell states are adapted, high-precision and extensible cell type annotation can be realized in a scene with insufficient reference knowledge or a fuzzy sample, and the annotation efficiency is improved. And the method has good universality and practicability.

The invention relates to the technical field of unmanned aerial vehicle navigation control, and discloses an unmanned aerial vehicle visual navigation and positioning method, system and related equipment, and the method comprises the following steps: obtaining an image in real time; performing joint correction on the current image, and determining a corrected image; high-dimensional semantic features in the corrected image are obtained, and a candidate area is rapidly and roughly matched from the reference database; performing cross-modal comparison on the depth local feature of the corrected image and the depth local feature of each candidate region to determine a target region; and determining current positioning information of the unmanned aerial vehicle based on the target area and the attitude data of the unmanned aerial vehicle, and performing visual navigation based on the current positioning information. According to the method, the matching range is narrowed through joint correction and rapid rough matching, secondary matching is performed on the narrowed range through cross-modal matching, so that the positioning precision is improved, and finally, the matched target area is combined with the flight data (attitude data) of the unmanned aerial vehicle, so that the positioning precision is further improved.

The invention discloses an intelligent Parkinson's disease dysfunction assessment method and system, and belongs to the technical field of medical assistance, and the method specifically comprises the steps: deploying an intelligent interaction terminal in a daily living environment of a user, and continuously collecting unstructured user instruction data through the daily interaction behavior of the user and equipment; carrying out anonymization processing on the collected instruction data, and extracting a multi-dimensional feature set containing instruction logic continuity and intention rationality; a dynamic baseline model is established based on the instruction data of the user in the health state period, the baseline model automatically expands the storage capacity according to the time dimension, and a personalized reference database synchronously evolved with user interaction characteristics is formed; by analyzing the evolution matching degree between real-time instruction features and a baseline model, when it is detected that instruction logic continuity or / and intention rationality continuously declines and exceeds a self-adaptive threshold value, a visual early warning report containing a disease progress risk level is generated; the method can assist in finding early risks of diseases.

The invention discloses a big language model-based sales plan generation method and device, and the method comprises the steps: constructing a marketing knowledge base which comprises a commodity basic information database, a social media database, a competition pattern database and a high-quality sales plan reference database; performing fine tuning training on a large language model according to the high-quality sales plan reference database to obtain a sales plan generation model; and generating a target sales plan according to the marketing knowledge base and the sales plan generation model. According to the method, the marketing plan can be generated by finely adjusting the large language model and utilizing a plurality of databases, so that the efficiency and the applicability are improved, and the cost is reduced. The method can be widely applied to the technical field of artificial intelligence.

The invention relates to the field of pollutant monitoring, in particular to an indoor decoration harmful substance monitoring and early warning method and system based on multi-sensor analysis. The method comprises the following steps that decoration whole-process parameter collection is carried out based on multiple sensor nodes, regional parameter distribution fitting is carried out, and an all-weather monitoring reference database is constructed; performing air pollutant identification marking on the all-weather monitoring reference database, and performing multi-time-point concentration change evolution analysis to obtain a multi-time-point concentration distribution evolution model; carrying out dynamic pollutant diffusion mining on the multi-time-point concentration distribution evolution model, carrying out combined pollution evaluation calculation, and constructing a multi-pollutant combined diffusion risk chain; dynamic interpolation modeling is carried out on the multi-time-point concentration distribution evolution model, micro-scale space-time disturbance reconstruction is carried out, and a pedestrian disturbance space-time diffusion model is constructed. According to the invention, through accurate and efficient risk assessment of indoor decoration harmful substances, dynamic early warning is carried out, and the safety of indoor decoration is improved.

The invention relates to the technical field of drilling machine monitoring and control, and discloses a state monitoring method and system for a drilling machine, and the method comprises the steps: detecting the stratum hardness in real time when the drilling machine is started, comparing the stratum hardness with data in a reference database, and judging the state of the drilling machine; if the state is abnormal, the contact condition of the drill bit and the stratum is checked, and if not, the drilling strategy is adjusted; if the environmental data is normal, checking whether the drilling machine is abnormal, and determining an early warning level according to the abnormal condition; and if the drilling machine is normal, updating the real-time hardness data into the reference database. According to the state monitoring method and system for the drilling machine, the working efficiency of the drilling machine can be improved, poor stratum contact is reduced, the environmental adaptability is enhanced, the safety is improved, reference data management is optimized, and the practical value is remarkable.

The invention discloses a heart tension index dynamic calculation and risk assessment method based on HRV, and the method comprises the steps: carrying out the filtering and denoising of an electrocardiosignal through a Butterworth filter, and obtaining a filtered electrocardiosignal; calculating interval data of adjacent wave crests; processing the interval data according to fast Fourier transform to obtain frequency domain features, and combining the interval data to obtain time domain features; performing normalization processing on the time domain and frequency domain features based on a maximum and minimum normalization method; calculating a cardiac tension index according to the normalized features and a pre-trained multiple linear regression model; matching a pre-constructed reference database according to the individual age, gender and body mass index to obtain a reference cardiac tension index; calculating a cardiovascular risk score in combination with the normalized frequency domain features and a reference cardiac tension index; and repeating the above steps regularly, smoothing through a moving average method based on continuous multiple cardiovascular risk scores, and analyzing the trend to send out cardiovascular risk early warning information.

Methods and systems for automatic detection and filling of information gaps in a reference database are described. Responsive to a user query in an ongoing chat session, a query embedding associated with the user query is obtained. A synthetic question embedding is identified from a vector database, based on a similarity to the query embedding. Responsive to determining that the similarity between the synthetic question embedding and the query embedding does not meet a similarity threshold, the ongoing chat session is monitored to detect an answer to the user query. A prompt is provided to a large language model (LLM) to generate and display a textual content corresponding to the user query, based on the detected answer, for automatically updating the reference database. The disclosed methods and systems effectively incorporate new or undocumented information that is not currently captured within the reference database, as gaps are identified.

The invention relates to the technical field of health evaluation, in particular to a group image health evaluation method and system based on intestinal flora, and the method comprises the steps: collecting intestinal flora samples of a target group through a standardized process, and obtaining microbial sequence information through a high-throughput sequencing technology; microflora diversity characteristics and core flora characteristics are extracted through strain identification and relative abundance analysis, individual flora characteristics are compared with a healthy population reference database, health state scores are calculated, health grades are divided, population health grade distribution is counted, and the population health grade distribution is calculated. And generating a group health evaluation report containing a visual chart and text analysis. According to the method, a complete technical system from sample collection to health strategy making is established, systematic evaluation of the group health state from the perspective of intestinal flora is achieved, and the limitation of a traditional method in group health early evaluation is overcome. The method is suitable for health monitoring of different scales of groups, and provides effective technical support for public health management and health service.

The invention relates to a computer-implemented method and system for determining at least one machine for processing plastics on the basis of criteria determined for producing a component (2.14). In a reference database (RD), reference machine data (2.4) are provided, comprising reference partial datasets (RTDS) required for determining machine parameters. User data (2.3) are provided as determined criteria in a data store (2.2), which user data (2.3) comprise data required for producing at least one component (2.14). A simulation for producing the component (2.14) takes place on the basis of the user data (2.3) on a machine by generating simulation datasets. The simulation datasets are segmented in order to extract partial datasets, wherein the partial datasets relate to machine-related machine parameters with which a machine should be operated in order to produce the component (2.14). The partial datasets are compared with reference partial datasets to identify partial matches, in order to output a minimum requirement of a machine when producing the component (2.14). The minimum requirement is compared, using federated learning, with available machines in order to determine at least one machine suitable for producing the at least one component (2.14), and this machine is then operated accordingly. As a result, at least one machine can be provided to a user for use thereof, which machine is the best-suited for this purpose, according to the circumstances.

A methods, systems, and devices for secure linking and matching of data elements across independent data systems of a first and a second enterprise are disclosed. The system includes a first private data system having a first private database that may include all attributes known to the first enterprise A reference data system having a reference database and is also part of the first enterprise. The reference database may contain a plurality of identity data records that only contain identity attributes that are used for resolving and verifying identities of unknown data records that are external to the reference data system. A first set of query attributes may be used determine whether a subject represented by the first set of query attributes associates uniquely with a subject of any private data record stored in the first private database. A similar comparison may be made in the reference database.

The invention provides a high-throughput detection and bioinformation analysis and identification method for a human ring virus group, the method comprises the whole process from reference database construction, sample processing, high-throughput sequencing to bioinformation analysis, and the technical scheme specifically comprises the following steps: step 1, constructing a human ring virus high-quality reference database; 2, performing high-throughput sequencing on the metagenome of the human sample; and step 3, a ring virus group biological information analysis process.

The invention provides a user personalized scientific research planning scheme generation method and system based on multi-agent interaction. The method comprises the following steps: firstly, receiving a question of a user, outputting a keyword through a keyword disassembling agent, further generating a related expert agent, integrating literature information, forming a theme through interactive discussion between the user and the multiple agents, and storing the theme into a global memory library; after a user selects a theme, entering an interactive inspiration and approval stage, generating an initial scheme by a scientific research scheme planning agent, and constructing a feasible literature reference database through second correlation screening; the keyword generation agent is combined with the database to generate literature keywords, a final combination is obtained through exchange and mutation operation, scheme feasibility is enhanced through the detailed agent, evaluation is conducted through the review agent, if optimization is needed, evaluation is conducted again after updating is conducted through the optimization agent, and if improvement is not needed, a final scheme is output. The framework links are compact, and abundant, efficient and accurate scientific research intelligent reply and planning schemes can be provided for users.

The invention discloses an ocean jacket platform structure damage identification method and system, and belongs to the technical field of ocean platform structure damage identification, and the method comprises the steps: obtaining different types of reference data in a reference database through classification, and determining the statistical values and damage thresholds of damage sensitive features corresponding to the different types of reference data; when the damage sensitive characteristic statistical value corresponding to the test data is greater than the damage threshold value corresponding to the reference data of the current category, judging that the jacket platform structure is damaged, and starting an on-site detection and maintenance process; when no damage is actually detected on site, taking the test data as a new working condition sample, putting the new working condition sample into the reference database, and updating the category label; and otherwise, taking the test data as normal data, classifying the normal data, and incorporating the normal data into the reference data of the corresponding category. According to the method, the influence of the excitation environment change on the structural damage identification result is considered, and the uncertainty of the structural damage identification result of the ocean platform is greatly reduced.

The invention relates to the technical field of building construction, and discloses an attached vibrator vibration parameter matching decision-making system, which comprises a perception execution dual-mode vibrator network, a vibration acoustic fingerprint generation and analysis module, a fingerprint evolution time sequence inference module and a multi-target dynamic decision-making engine, generating a vibration acoustic fingerprint formed by multi-dimensional physical characteristics according to the response signal; the method comprises the following steps: constructing a fingerprint evolution sequential sequence, comparing the fingerprint evolution sequential sequence with a reference database, deducing the performance of a concrete material on line, and further calling a mapping function matched with the performance to evaluate a real-time compactness state; and finally, based on the evaluated compactness, the multi-target dynamic decision engine adopts a model prediction control strategy to generate an optimal dynamic operation instruction for each vibrator node. Closed-loop self-adaptive control of detection, evaluation, decision making and execution is constructed, the optimal vibration parameters can be matched in real time, the vibration quality and uniformity of concrete are remarkably improved, energy consumption is reduced, and dependence on artificial experience is reduced.

The invention provides a credible manuscript review decision-making method, system and equipment and a readable storage medium. The method comprises the following steps: receiving a manuscript to be reviewed, analyzing a document structure of the manuscript to be reviewed, and identifying a paper type; based on the identified paper type, calling a data processing agent, extracting a performance index corresponding to the paper type from at least one of a text, a table and a chart of the to-be-reviewed document, and converting the performance index into standardized structure data; traversing a preset database, comparing the data in the reference database with the structured performance indexes, and determining the similarity and the relative sequence of the performance indexes of the to-be-reviewed manuscript and the data in the database; and based on the similarity and the ranking percentage, outputting a quantitative score of the to-be-reviewed manuscript and the confidence of the quantitative score. Compared with the prior art, the method has the advantages that the professionality, objectivity and credibility of review are remarkably improved; and interference caused by training data prejudice and text subjective description is effectively reduced.

The invention particularly relates to an image deblurring method and device based on a convolutional sparse coding feature insertion network, and the method comprises the steps: obtaining a to-be-processed blurred image; and inputting the to-be-processed blurred image to a pre-trained image deblurring model, extracting depth features from the to-be-processed blurred image through the pre-trained image deblurring model, and outputting a clear image of the to-be-processed blurred image according to the depth features of the to-be-processed blurred image, the pre-trained image deblurring model is obtained by training a preset recovery network by using the blurred image training set and a reference image training set corresponding to the blurred image training set based on a preset sparse coding algorithm. Therefore, through the convolution sparse coding feature insertion network, the clear reference database and the blurred image training set are combined, depth feature extraction and reference feature connection are utilized, the clear image is output, the problem that in the prior art, deblurring cannot be carried out on the blurred image of spatial transformation is solved, and the deblurring effect is improved.

A vehicular system has a database of position data of discrete points on a route, a first positioning circuit that measures an own vehicle position by using the magnetic markers, a second positioning circuit that measures the own vehicle position by autonomous navigation, and a control circuit that controls the vehicle by taking a deviation of the own vehicle position with respect to the route as a control target. In the database, marker position data with reference to any discrete point is recorded as linked to position data. The first positioning circuit identifies the detected magnetic marker by referring to the database. The control circuit identifies the deviation of the own vehicle position with respect to the route by referring to the database.

The invention relates to the field of data processing, in particular to an intelligent extraction method and system for key information of a patient, the motion condition and the motion intensity of a user are recognized through motion data collected by intelligent wearable equipment, and when the motion intensity reaches a certain value, the current motion duration of the patient is accumulated. Meanwhile, collecting physical sign data of the user in real time, determining reference physical sign data matched with the patient from a physical sign reference database in combination with the current exercise intensity, and calculating the similarity between the actually measured physical sign data and the reference physical sign data. If the similarity is too low, it can be deduced that the patient possibly feels uncomfortable during movement, at the moment, a question answering process is executed through a pre-constructed question template, and a symptom entity possibly appearing during movement of the patient is found. Finally, the accumulated exercise duration, the symptom entity, the actually-measured sign data and the exercise intensity data serve as key data to be extracted and provided for doctors, and the doctors have related data to refer to and judge the recovery condition of the patient.

In one aspect, an example method includes (i) while a media playback device of a vehicle is playing back content received on a first channel, sending, by the media playback device to a server, a preview request, the preview request identifying a second channel that is different from the first channel; (ii) receiving, by the media playback device from the server, a response to the preview request, the response including identifying information corresponding to content being provided on the second channel; and (iii) while the media playback device is playing back the content received on the first channel, providing, by the media playback device for display, at least a portion of the identifying information corresponding to content being provided on the second channel.

The invention discloses a sky-base collaborative tower camera image high-precision positioning method, which comprises the following steps of: carrying out virtual squint projection on a satellite image based on a high-resolution satellite orthoimage of an area around a tower camera, and mapping the satellite image to a tower camera squint coordinate system; performing multi-scale phase fusion terrain enhancement feature extraction and cross-view matching on the satellite reference image and the tower camera image to obtain high-precision homonymy points and meter-scale control points; block adjustment and absolute positioning are carried out on a reference database image collected by a tower camera; and based on the positioned reference database, carrying out high-precision geographic positioning on the natural resource illegal behaviors. According to the method, high-precision positioning of the tower camera can be efficiently and automatically realized, the positioning efficiency of the tower camera image is remarkably improved, and protection of natural resources is facilitated.

The invention relates to the technical field of transformer winding fault detection, in particular to a preventive maintenance method and device for transformer winding faults. The method comprises the following steps: acquiring current signals of a three-phase winding of a transformer and vibration acceleration signals in different directions; obtaining an excitation-response spectrum matrix based on the current signal and the vibration acceleration signal, and constructing a health state vibration mode base; projecting the excitation-response spectrum matrix to a health state vibration mode base to obtain a vibration mode contribution coefficient vector; constructing a frequency-mode association graph structure according to similar conditions of different frequencies in a health state vibration mode base at the initial stage of equipment commissioning; endowing nodes of the graph structure with features to obtain winding structure state feature vectors, and establishing a reference database of each temperature interval; and matching the winding structure state feature vector and the vibration mode contribution coefficient vector in the current time period with a reference database, and determining a fault reason. According to the invention, the timeliness of transformer winding fault early warning is improved.