29results about How to "Accurate association" patented technology

The utility model relates to cell culture tool technical field especially, more particularly to an array formula multi -hole separation cell culture dish. The utility model provides an array formula multi -hole separation cell culture dish, solves the technical problem that cell culture dish in prior art can only culture same kind of cell under same environment. An array formula multi -hole separation cell culture dish, including frame, culture cavity, culture cavity set up in frame, and mark, mark set up in frame, and, every mark corresponds an independent culture cavity, array formula multi -hole separation cell culture dish sets up a plurality of independent culture cavities, and every culture cavity can be regarded as an independent'small culture dish'. This makes under same frame, to same kind of microorganism in different nutrient solution, medicine or other environmental conditions can carry out culture experiment simultaneously.

The invention discloses a conductance cell system and method for double-range correction, and belongs to the technical field of analytical instruments, the system comprises a first conductance cell and a second conductance cell which are connected in series through a pipeline, and a processing unit connected with the first conductance cell and the second conductance cell. The first conductance cell is suitable for high-concentration detection, and the second conductance cell is suitable for low-concentration detection. The method comprises the following steps: firstly, establishing two calibration curves of different measurement ranges for two conductance cells, and determining critical points of the two curves; during detection, a sample sequentially flows through the two conductance cells, the processing unit selects one of the high-concentration calibration curve and the low-concentration calibration curve for data processing according to a comparison result of a real-time detection signal and a critical point, and finally a concentration value is output. According to the invention, through a series connection structure and intelligent curve selection, the detection range of a single conductance cell is effectively widened, the measurement precision in a full scale is remarkably improved, and automatic and high-precision detection in a wide concentration range is realized.

The invention discloses a method and system for verifying an RISC-V processor and a computer readable storage medium. The method comprises the following steps: analyzing an RISC-V official manual and a micro-architecture user manual, and generating a static instruction-resource mapping table; and generating a first test instruction sequence for each instruction in the static instruction-resource mapping table, executing the first test instruction sequence by using an RISC-V processor simulation model constructed by a software simulator, and dynamically calibrating the static instruction-resource mapping table in the execution process. And traversing the instruction and resource mapping relationship in the calibrated static instruction-resource mapping table, analyzing RISC-V processor verification logic, and if a conflict is found, outputting a conflict report so as to complete defect repair before RTL code writing. According to the application, hardware behaviors can be accurately associated, the problem of disjunction of semantics and micro-architecture is solved, and conflict prediction in an architecture design stage and end-to-end automatic verification from instruction semantics to micro-architecture behaviors are realized.

The application provides an information association method and device, electronic equipment and storage medium, relates to the technical field of communication, and solves the technical problem that in the related art, other users cannot guarantee the security of service data based on the terminal corresponding to a user accessing related services. The method comprises the following steps: receiving an information association request sent by a terminal; in the case that the secret card identifier of the first secret card is the same as the secret card identifier included in the opening information of the first account, and the first field included in the opening information of the first account is empty, sending a first verification code to the terminal, the first field being used to represent the terminal identifier corresponding to the account identifier of the first account; in the case that the first verification code sent by the terminal is received, determining the terminal identifier of the terminal as the terminal identifier corresponding to the account identifier of the first account, and determining the secret card identifier of the first secret card as the secret card identifier corresponding to the account identifier of the first account.

The invention discloses a semantic alignment enhanced lane line detection method based on a Mama framework. The method comprises the following steps: acquiring a lane line data set and inputting the lane line data set into a backbone network for multi-stage feature acquisition; flattening the feature map into a one-dimensional sequence by using a dynamic multi-scale adaptive screening module, stacking different levels of features, and highlighting lane line information through weights; then, through a Mama X branch, through global pooling and convolution, short-distance dependence is captured; then semantic completion is carried out on the output of the dynamic multi-scale adaptive screening module and the output of the Mama X branch through a semantic alignment fusion module, and alignment enhancement features are output; effective features are scanned through a gating module in the Mamba Z branch, and then the state is updated position by position through a scanning module to establish long-distance dependence; and inputting a feature sequence output by the Mama Z branch to a detection head, and outputting a lane line prediction map by continuously updating the position of a prior frame. According to the method, dynamic multi-scale adaptive screening, Mama architecture and semantic alignment fusion are combined, a long-distance dependency relationship can be established for the lane line, and the detection precision of the lane line is improved.

This invention discloses an integrated small embedding cassette and its tissue bottle for a pathological tissue embedding cassette sorting system, comprising a tissue bottle and an integrated small embedding cassette; the tissue bottle includes a top cover and a bottom cover, the inner wall of the top cover having a threaded structure, and the top and bottom covers being detachably connected via the threaded structure; the integrated small embedding cassette is horizontally positioned inside the tissue bottle, and the bottom cover has a sealed cavity for containing liquid; the integrated small embedding cassette includes a body and a lid, the body and lid being integrally formed. This invention, through integrated structural design, integrates the traditionally separate tissue bottle and the integrated small embedding cassette into a coaxial assembly structure, eliminating the sample transfer step, significantly reducing operational complexity, and minimizing reliance on manual labor. By setting a sealed threaded connection between the top and bottom covers, formaldehyde gas leakage from formalin solution is effectively reduced, improving biosafety.

The invention provides an automatic identification and tracking method and system for a lottery ticket bundle, and relates to the technical field of lottery ticket bundle identification and tracking. Multi-angle data of the lottery ticket bundle are acquired, three-dimensional contour data of a plastic package belt are synchronously acquired, and the two data are fused to generate a data set containing visual and spatial morphological characteristics; extracting the shape contour features of the edge area of the plastic packaging belt to reconstruct a three-dimensional edge path, and extracting the surface texture of the contact area of the plastic packaging belt and the lottery ticket bundle; judging the structural integrity of the plastic packaging tape according to the continuity and smoothness of the three-dimensional edge path, and evaluating the fitting tightness degree by combining the surface texture distribution uniformity of the contact area; the integrity and fitting degree result is compared with a reference model representing the standard state of the plastic packaging tape, the state of the lottery ticket bundle plastic packaging tape is marked, and finally lottery ticket bundle information with state marks and tracking codes are bound and written into a quality tracking database, so that precise recognition and information traceable management of the state of the lottery ticket bundle plastic packaging tape can be realized.

This invention proposes an intelligent remote emergency rescue management system capable of rapidly matching resources, relating to the field of remote emergency medical technology. The alarm receiving module triggers the case analysis module to generate priorities, the resource scheduling module allocates instructions to the drone control module, and after the drone completes deployment, the information matching module generates navigation information. Data from the person scanning the code is fed back to the system via the data association unit, forming a complete closed loop of resource scheduling-deployment-feedback. Through real-time data interaction between modules, the traditional emergency resource matching time is shortened from 10-20 minutes to within 2 minutes, while simultaneously improving the accuracy and utilization rate of drone AED deployment, achieving a qualitative leap in emergency response efficiency.

The application discloses a double-link observable-based API interface data loss root cause positioning method, relates to the technical field of data operation and maintenance, and comprises the following steps: acquiring API requests from an API request query link and query request information of the API requests, wherein the query request information comprises first data identifiers and first time identifiers of to-be-queried data; acquiring data generation state information from a data generation link of a data production supply end, wherein the data generation state information comprises second data identifiers and second time identifiers corresponding to data generation tasks; establishing an association relationship between the API requests and the data generation tasks based on the first data identifiers, the first time identifiers, the second data identifiers and the second time identifiers; and if a response result of a target API request is data loss, determining a data loss root cause based on the association relationship, the target API request and a target data generation task. The application improves the positioning efficiency and accuracy of data loss faults.

The invention relates to the technical field of pavement disease detection, and discloses a pavement disease intelligent positioning and quantifying method, which comprises the following steps: acquiring road surface image data and navigation data corresponding to the road surface image data; based on the morphological information of the disease, quantifying the disease length, the disease area, the disease average width and the disease maximum width to obtain quantified disease characteristics; establishing a corresponding relation between the image and the acquisition sequence according to the quantized disease characteristics, and searching navigation data corresponding to the skeleton pixel points; calculating latitude and longitude coordinates of scanning line boundary points according to latitude and longitude coordinates of a scanning center point in the navigation data, and converting any skeleton pixel point in the image into geographic coordinates of a disease so as to realize positioning of a disease target in a real geographic space; and making a disease GIS map based on the geographic coordinates of the diseases and the quantitative disease characteristics. According to the invention, each pixel point in the image is regarded as an independent positioning unit, so that the morphology of the disease can be presented more accurately.

The present application belongs to the technical field of chemical safety monitoring, and particularly relates to a chemical gas leakage detection method based on multi-information fusion, which is used for a mobile inspection platform, the mobile inspection platform is equipped with an image acquisition device, multi-type gas concentration sensors and a GPS / IMU combined positioning module, and the method comprises the following steps: S1: multi-source data synchronous acquisition and preprocessing, real-time video stream data of a chemical scene is acquired through the image acquisition device of the mobile inspection platform, gas concentration data of corresponding spatial positions are acquired through the multi-type gas concentration sensors, and timestamp alignment and standardization preprocessing are performed on the two types of data. The present application can realize early prediction, accurate positioning and hierarchical emergency disposal of chemical gas leakage through the following steps: spatio-temporal synchronous multi-source data acquisition, three-dimensional semantic mapping, rule-based high-level semantic reasoning, multi-modal fusion and double verification.

This invention proposes a multimodal driven and dynamically optimized method and system for power plant inspection image segmentation, belonging to the field of computer vision technology. The method includes: acquiring inspection sample images; generating initial pseudo-labels using a pre-trained visual language model and a multimodal large language model; inputting the inspection sample images into the visual model to obtain dense features, aligning them cross-modally with text semantic embeddings to obtain enhanced visual features; constructing a transition matrix based on image features and enhanced visual features, and inputting these features into a decoder to obtain a dual-path prediction mask, which is then fused to generate a segmentation probability map; optimizing the initial pseudo-labels based on the segmentation probability map and the transition matrix, and using the optimized pseudo-labels to construct a supervision signal to guide the generation of the transition matrix; iteratively optimizing until convergence to obtain a trained image segmentation network, which is then used as input to the inspection image to be segmented to obtain the segmentation result. This improves the segmentation accuracy and generalization ability of inspection images.

This utility model discloses an automatic scanning and data recording device for an infrared emissivity tester, relating to the field of infrared detection equipment technology. It includes a worktable, a support rod, an infrared emissivity testing lens, an infrared emissivity testing main control unit, a computer main control unit, and a moving platform. One end of the support rod is vertically mounted on the worktable, and the infrared emissivity testing lens is mounted on the other end of the support rod. The infrared emissivity testing lens is electrically connected to the infrared emissivity testing main control unit, which is electrically connected to the computer main control unit. The moving platform is mounted on the worktable and is used to move the sample horizontally. This invention overcomes the shortcomings of existing infrared emissivity testers, which require manual sample movement, resulting in low efficiency and large errors.

This invention discloses a furnace temperature control method, relating to the field of intelligent control of electronic packaging welding processes. The method includes: collecting real-time temperature data and welding process parameters of the substrate to be welded, and acquiring post-weld deformation data; aligning and fusing the real-time temperature data, process parameters, and deformation data to extract key features of the furnace temperature curve, and constructing a data record set by associating them with the deformation of corresponding measuring points; based on the data record set, establishing a quantitative prediction model using regression analysis or machine learning algorithms; under preset process constraints, optimizing the furnace temperature curve setpoint with the predicted warpage as the optimization objective, calculating the corresponding predicted warpage using the quantitative prediction model, generating the optimal furnace temperature curve setpoint, and sending it to the welding equipment for execution. By constructing a quantitative prediction model using temperature data from sensitive points and post-weld deformation, the optimal furnace temperature curve is generated through reverse optimization to suppress welding warpage.

This invention provides an AI text-based order placement method and system based on multimodal parsing and context awareness, belonging to the field of artificial intelligence technology. The method includes acquiring multi-source heterogeneous order data; preprocessing the multi-source heterogeneous order data to generate standardized text data; dynamically slicing the standardized text data exceeding a preset length threshold using an intelligent slicing engine to generate a semantically continuous text slice sequence; inputting the text slice sequence into a cascaded routing hub for hierarchical parsing to obtain parsing results; based on the parsing results, performing parallel product retrieval using a hybrid strategy recall engine; processing the product retrieval results to obtain a candidate product set; and performing context-aware completion processing on the candidate product set, completing missing product attributes based on the user's historical order knowledge graph and resolving fuzzy referencing to generate a standard order object. This achieves automatic, highly accurate, and low-cost parsing and input of order text.

The application discloses a multi-source heterogeneous data correlation retrieval method and system based on a unified identifier, a terminal and a medium, and relates to the technical field of information retrieval.The technical solution points are as follows: the application uses a unique identifier to perform strong correlation mapping between all scattered and heterogeneous physical storage and logical indexes at a logical level, and constructs a unified data view centered on an entity, so that data originally stored in object files, metadata tables, structured records, relationship graphs and retrieval indexes can be stably and accurately correlated and traced.Especially, the two-stage retrieval mode of keyword preliminary screening and graph expansion first efficiently locates a target through a retrieval engine, and then uses graph mining to find the correlation network.The application effectively solves the disadvantage that the existing retrieval scheme cannot perform correlation resource expansion, upgrades data query from single finding to network discovery, and improves the data correlation discovery rate and query completeness in a complex business scenario.

The invention discloses a multi-source attack detection method for computing power cluster security protection, and belongs to the technical field of host security attack detection. The method comprises the following steps: inputting an operating system auditing log of a computing node in a computing power cluster to be identified into a pre-trained time sequence anomaly detection model to calculate an anomaly probability score of the operating system auditing log, when the anomaly probability score exceeds a threshold value, judging that the operating system auditing log is attacked, and otherwise, judging that the operating system auditing log is safe; the pre-trained time sequence anomaly detection model is obtained through the following steps: collecting an operating system audit log of each computing node, analyzing an event in the log into a standardized quintuple event, and obtaining a global cause and effect graph based on the event; active entity nodes in the global causal graph are screened, and multi-dimensional feature coding is carried out to generate a feature sequence; and inputting the feature sequence into a pre-constructed time sequence anomaly detection model to obtain a trained time sequence anomaly detection model. According to the invention, the problem that the existing detection technology is difficult to restore a cross-host complete attack link is solved.

The film and television script extraction method and device, the storage medium and the computer device provided by the application, after the audio and video file of the film and television is split into a video file and an audio file, the video file is subjected to feature recognition to obtain a subtitle text, a speaker face information and a video understanding text; and the audio file is subjected to speech understanding to obtain a speech transcription text and a speech understanding text; wherein the speech transcription text can be corrected into a standard transcription text with higher accuracy through the subtitle text. Therefore, based on the speaker face information, the standard transcription text and the dialogue segment of each speaker in the audio and video file are aligned, the speaker information with accurate segmentation and coherent semantics can be obtained, then the script information is constructed by combining the character profile text generated by the profile analysis of the speaker based on the video, the speech understanding text and the speaker information, the script information can cover the related feature description of the character on the basis of the dialogue content, thereby enriching the content and depth of the script.

The invention discloses a method for separating elastic deformation and pore elastic deformation and related equipment, and relates to the field of geodesy, and the method comprises the steps: taking a preset number of InSAR earth surface deformation time sequences as an initial mass center, and employing a spatial clustering algorithm to obtain a plurality of clusters; for each cluster, determining the category of the cluster based on the average value and spatial distribution characteristics of the InSAR earth surface deformation time sequence in the cluster; if the category of the cluster is the pore elastic deformation dominant category, obtaining a pore elastic deformation dominant deformation time sequence according to the InSAR earth surface deformation time sequence in the cluster; if the category of the cluster is a seasonal pore elastic deformation and elastic load deformation aliasing category, performing principal component analysis on the InSAR earth surface deformation time sequence in the cluster to obtain an elastic load deformation sequence and a seasonal pore elastic deformation sequence; according to external data, separation is proved to be successful. According to the method, the elastic deformation and the hole elastic deformation can be effectively separated from the InSAR earth surface deformation.

The invention relates to an optical mark positioning device for PC component mold visual inspection and a detection method. The method comprises the following detection steps: step 1, a preparation stage: selecting a base matched with the height of a to-be-detected mold, assembling the optical mark positioning device, and loading component quality inspection data by a machine vision system background; secondly, a mold and a mark are placed, specifically, an operator places the PC component mold on a mold table, and then an optical mark positioning device is adsorbed to the mold table according to a preset rule; step 3, triggering detection: triggering a machine vision system; step 4, image acquisition and processing: shooting by a camera, and identifying an optical mark and identification information thereof in an image by software; the machine vision system calculates the actual position and posture of the mold according to the marked position, the actual position and posture are compared with standard data, and whether the mold is qualified or not is judged; and step 6, result feedback and mark removal: the HMI displays the result, and the magnetically attracted mark positioning device is taken down from the mold table for storage after the detection is completed.

This application discloses methods, apparatus, equipment, and media for interlaboratory quality assessment or data analysis in medical laboratories, relating to the field of medical laboratory testing technology. The methods include: generating a corresponding reference standard deviation based on randomly generated reference target values ​​and reference coefficients of variation; performing normal distribution random sampling to obtain reference reported values; linearly fitting the reference target values ​​and reference reported values ​​to obtain reference coefficients of determination; determining a new step size for the reference coefficient of variation to initiate a new external loop until the external loop ends; generating relative coefficients of variation based on the reference standard deviation; constructing a target mapping relationship matrix between each relative coefficient of variation and the reference coefficient of determination; determining the target relative coefficient of variation based on the target mapping relationship matrix and using the actual coefficients of determination of each actual sample; and obtaining the target sigma metric value using the target relative coefficient of variation, thereby obtaining the analytical and quantitative results of the actual interlaboratory quality assessment. This improves the accuracy and efficiency of interlaboratory quality assessment analysis.

The application discloses a picture mark information recognition method based on visual intelligence, comprising the following steps: obtaining and preprocessing a picture to be recognized; extracting multi-source visual trace features; recognizing mark superimposed candidate pixel regions in the picture to be recognized; performing mark layer de-coherence separation processing on the picture to be recognized, generating an original image content layer and a mark information candidate layer and recording a layer separation mapping relationship; performing text, line segment and contour recognition on the mark information candidate layer; projecting a mark element set back to the original image content layer and performing mark element back projection adaptive correction; determining a corresponding relationship between the mark element set and a marked object and generating a picture mark information recognition result. The application utilizes multi-source visual trace analysis and layer de-coherence separation methods, realizes accurate association between picture mark information and a marked object, and has the advantages of high recognition accuracy and strong complex scene adaptability.

The invention relates to the technical field of network operation and maintenance, and discloses a network jitter diagnosis method and device, equipment and a medium. The method comprises the following steps: when a data packet is confirmed to be delivered, calculating network jitter data; embedding the network jitter data into the service calling link data to obtain embedded link data; and carrying out jitter root cause analysis on the embedded link data to obtain a network jitter diagnosis result. According to the embodiment of the invention, the network jitter can be accurately associated with the affected user, and the influence of the network jitter on the service is clear.

The application relates to the technical field of automatic driving, and provides a method and system for associating an automatic driving perception target and a true value target, wherein the method comprises the following steps: respectively extracting motion feature parameters and scene feature parameters of the perception target and the true value target in continuous multiple frames; respectively generating motion feature curves of the perception target and the true value target based on the motion feature parameters; determining a scene type based on the scene feature parameters, and assigning weight coefficients to different motion feature parameters based on the scene type; calculating the similarity between the perception target and the true value target based on the motion feature curves of the perception target and the true value target and the weight coefficients; and performing association determination based on the similarity, and outputting an association result of the perception target and the true value target. The application scheme realizes accurate association between the perception target and the true value target in a complex scene, and improves the accuracy and robustness of the association result.

The application provides a file monitoring method and an electronic device. The method comprises the following steps: during the running of a first operating system, changing a kernel code to replace an initial inotify event processing function in the kernel with a preset inotify event processing function; obtaining a target file operation event and target context information of a target file through the preset inotify event processing function; wherein the target file operation event and the target context information are determined by the preset inotify event processing function based on a preset first configuration file, and the first configuration file is used to record at least one target file; and recording the target file operation event and the target context information in a kernel log. By dynamically replacing the inotify event processing function and adding the context information of the file operation, the application can ensure that the key file operation is captured in time. In this way, during the problem positioning and troubleshooting process of the electronic device, the whole process of the event occurrence can be accurately restored, thereby greatly improving the maintainability of the system.

The application discloses a power industry dynamic knowledge base construction method and system based on a large language model, relates to the field of electric digital data processing, and comprises the following steps: receiving a power field document imported by a user, and converting the power field document into an electronic document; calling a large language model to analyze the electronic document, extracting professional term definitions, chart position information and document logical levels in the electronic document, and generating knowledge units containing multiple contexts; connecting the knowledge units into directed knowledge links, calculating semantic similarity between adjacent knowledge units in the directed knowledge links, segmenting the directed knowledge links, and obtaining multiple knowledge topics; receiving a knowledge retrieval instruction, determining a target knowledge topic corresponding to the knowledge retrieval instruction; extracting a target knowledge unit corresponding to the target knowledge topic, and generating a knowledge retrieval result based on a target context of the target knowledge unit. The application can optimize knowledge base construction and guarantee the integrity of knowledge base data.

The application provides a control information transmission method, a sending end and a collecting end. The method comprises the following steps: periodically broadcasting state data of a coal mine excavation device monitored by the sending end to at least one collecting end; receiving control information sent by the at least one collecting end in a broadcast mode after receiving the state data; generating at least one control setting feedback information after performing local control setting according to the control information; adding identification information of a target sending end sending the control setting feedback information into the at least one control setting feedback information to obtain at least one target control setting feedback information; and sending the at least one target control setting feedback information to the at least one collecting end, so that the at least one collecting end updates a sending end control setting feedback information table according to the target control setting feedback information, and determines a control setting state of the sending end in a preset time period according to the control setting feedback information table. The application can confirm whether each sending end completes the control setting.

This invention discloses a cultivation experimental device suitable for studying the biogenesis mechanism of maize rRNA, belonging to the field of cultivation experimental technology for the biogenesis mechanism of maize rRNA. It includes an experimental platform with a refrigerator at its bottom. A connecting plate is located on one side of the refrigerator, and a cultivation experimental chamber is located on the side of the connecting plate away from the refrigerator. The cultivation experimental chamber has a cultivation tank inside, and a first rotating shaft is rotatably connected to one side of the cultivation tank. This invention, through a series of structural features, creates a dynamic cultivation environment by rotating the platform, precisely matching molecular events and significantly improving the scientific rigor of experimental data. Secondly, it employs a closed-loop precision liquid injection system, allowing for the addition of culture medium without removing the dish, thus improving operational efficiency and avoiding the impact of environmental fluctuations on cell state, ensuring experimental stability and consistency.

The application is suitable for the technical field of aluminum alloy production, and particularly relates to an aluminum alloy ingot impurity element traceability analysis method and equipment. The aluminum alloy ingot impurity element traceability analysis method comprises: obtaining aluminum alloy ingot impurity information and production chain information; wherein the aluminum alloy ingot impurity information is used to reflect the composition and corresponding content interval of impurities in multiple aluminum alloy ingots, and the production chain information is used to reflect the production process of the aluminum alloy ingot; an impurity isomorphism graph is constructed based on the aluminum alloy ingot impurity information; a potential source is determined based on the impurity isomorphism graph; and the final traceability result of the impurity element is determined based on the production chain information and the potential source. The method effectively solves the problems of insufficient detection data integrity, weak impurity correlation analysis and disconnection between production chain information and impurity characteristics in the prior art, realizes multi-dimensional information integration and quantitative correlation analysis of the source of the aluminum alloy ingot impurity element, and significantly improves the accuracy, multi-source differentiation capability and result reliability of impurity traceability.