65results about How to "Efficient analysis" patented technology

The invention discloses an automatic auditing system and method for road engineering completion settlement. The system comprises a data acquisition and integration module; a data preprocessing module; a settlement index construction module; an intelligent auditing engine; an abnormity early warning and tracing module; a settlement result management module; and a data analysis and optimization module. The auditing method comprises the following steps: S1, collecting and integrating multi-source settlement data; s2, big data preprocessing; s3, constructing a settlement auditing index system; s4, performing intelligent automatic auditing; s5, performing abnormal early warning and tracing; s6, managing settlement results; and S7, performing big data driving optimization. According to the invention, multi-source data intelligent integration, full-process automatic auditing, abnormal accurate tracing and dynamically optimized big data driven settlement auditing can be realized; the method is applied to whole-process management of road engineering completion settlement, and data-driven intelligent auditing and continuous optimization control are realized in the process.

The application discloses a lining cloth dyeing control method and system based on artificial intelligence, and is used for the control field, and the method comprises the following steps: real-time monitoring of multi-source data in the lining cloth dye vat, capturing the video stream inside the lining cloth dye vat; using a Gaussian mixture variational autoencoder model to extract features from the multi-source data, obtaining multi-source feature data; obtaining the changing moment of the fabric state in the video stream, and extracting the fabric state change feature data according to the observed fabric color change and the heterogeneity of the dye distribution in the video stream; fusion of multi-source feature data and fabric state change feature data; introducing a model predictive control layer, predicting the result to adjust the dyeing parameters in real time; establishing an intelligent feedback mechanism. The Gaussian mixture variational autoencoder model is trained and optimized through the small-batch stochastic gradient descent and back propagation algorithm, important features are learned and captured from the data.

The application discloses a signal processing method based on deep learning and adaptive filtering fusion, comprising the following steps: S1, original signal acquisition and pretreatment; S2, adaptive filtering; S3, constructing a deep neural network model to extract deep features of the filtered signal; S4, signal fusion to eliminate interference; S5, establishing a real-time closed-loop feedback mechanism for dynamic parameter adjustment; S6, end-to-end dynamic optimization process; S7, iterative update and high confidence sample judgment; S8, using the trained adaptive filtering module and deep neural network model to process newly collected signals, and generating reconstructed signals through signal fusion. The application effectively fuses adaptive filtering and deep neural network, realizes accurate suppression of multipath effect, nonlinear noise and transient interference in complex wireless signals, and high-dimensional feature extraction, thereby significantly improving the precision, robustness and real-time performance of signal processing.

The invention discloses a user behavior analysis method and device based on a graph neural network and deep clustering. The method and device are applied to scenes such as social network information transmission analysis and disease transmission prediction. According to the method, social network data are abstracted into a graph structure, node features are extracted through an L-layer auto-encoder, data are reconstructed, the node features and an adjacent matrix are fused through an L-layer graph neural network, network interference is dynamically captured, deep clustering is carried out on graph network output to obtain exposure conditions, and a loss function is defined through a double-feedback network. Global loss function optimization model parameters including a loss function, mean square error loss and a variance item are designed; and finally, the causal effect is estimated by using an inverse probability weighted Hajak estimator. According to the method, dynamic adaptive exposure condition learning is realized, the problems of poor flexibility, low expandability and limited accuracy of a traditional method are solved, and the causal effect estimation precision in a complex network is improved.

The invention provides a physical examination information and data association analysis system based on a medical laboratory. The physical examination information and data association analysis system comprises a data acquisition unit, a data annotation and arrangement unit, an association analysis unit and a visual display unit. The invention further provides a medical laboratory-based physical examination information and data association analysis method, which comprises the following steps of: acquiring physical examination personnel information and a detection result, and storing the physical examination personnel information and the detection result as original physical examination data; labeling and sorting the original physical examination data to obtain to-be-analyzed physical examination data; establishing a correlation analysis model; calculating and analyzing correlation; and the system displays a correlation analysis result. According to the invention, personnel information and detection data are collected and stored in combination with an existing medical examination laboratory management system, and on the basis of monotonicity and discontinuity characteristics of the personnel information and detection data of physical examination people, visual correlation analysis of personnel and regional personnel information and a detection item system can be realized; and the information is converted into effective and valuable health management suggestions which are simple and easy to understand, so that diseases are prevented.

This invention discloses a method, equipment, and medium for testing the durability of camshafts, relating to the field of durability testing technology. It solves the problem of being unable to test the durability of camshafts under different practical application conditions. The method includes collecting initial parameters of the camshaft used in plug-in hybrid electric vehicles, placing the camshaft in a camshaft test bench and conducting a cyclic wear test, collecting characteristic data of the camshaft after the cyclic wear test, conducting a pressure test on the shaft body and cam tip at the cam mounting point under specific temperature conditions, and comprehensively analyzing the durability of the camshaft based on the results of the cyclic wear test and the pressure test. This invention enables durability testing of camshafts under different practical application conditions.

The invention discloses a multi-modal large model ground penetrating radar disease data intelligent interpretation method and device, and belongs to the computing intelligence and information processing technology. The method is based on a computing device of machine learning, artificial intelligence and a specific mathematical model, and an inference model of specific ground penetrating radar knowledge is fused for information processing. Comprising the following steps: acquiring underground disease data by using multi-frequency ground penetrating radar equipment, and converting the underground disease data into a serialization format adaptive to a multi-modal large model; and then sequentially executing detection, segmentation and image description tasks. Wherein a segmented label mask is generated by adopting a Bayesian optimization method based on a target detection result, and an image description data set is constructed by utilizing a segmentation result; and finally, performing intelligent interpretation on the data by using the multi-modal large model to generate an interpretation report. According to the method, through multi-task collaborative learning, full-process automatic interpretation from disease detection to semantic description is realized, the interpretation efficiency and reliability are improved, and an intelligent basis is provided for road maintenance decision making.

The utility model provides a sterilization glass slide convenient for gram staining and identification, which comprises a glass slide main body, a sample information marking area, a standard bacterium area and a sample bacterium area are sequentially arranged on the front surface of the glass slide main body, and the sterilization glass slide is characterized in that the sample information marking area, the standard bacterium area and the sample bacterium area are sequentially arranged along the length direction of the glass slide main body; the front surface of the glass slide main body is partitioned through partition straight lines coated with the front surface of the glass slide main body, the partition straight lines are arranged in the width direction of the glass slide main body, and the multiple partition straight lines are sequentially distributed at intervals in the length direction of the glass slide main body; separation round lines are respectively arranged in the standard bacterium area and the sample bacterium area; and the thicknesses d of the separation straight lines and the separation round lines are 0.5-2 mm, and the widths D of the separation straight lines and the separation round lines are 0.5-2 mm. According to the utility model, the cross contamination problem in the staining process can be effectively improved, false positive and false negative phenomena are avoided, the accuracy of a staining result is improved, and the operation convenience, the result accuracy and the test efficiency of gram staining and identification of sample bacteria are improved.

The application discloses a park energy management and control method and system based on building energy consumption monitoring, relates to the process control technical field of energy management, and executes edge-end monitoring deployment, constructs a park simulation body through park twinning, determines a target energy structure according to energy management emphasis, executes energy consumption overrun analysis and energy scheduling balanced decision-making, determines an energy management and control strategy and reversely transmits the energy management and control strategy to intelligent monitoring equipment for local management, and is used for solving the technical problems that the prior art cannot make light and flexible analysis and decision-making for diversified park energy scenes, leading to redundant processing modes and insufficient scene adaptability of energy management. The application realizes light and efficient analysis based on energy scenes and precise management of park energy management.

This invention relates to the field of photovoltaic power generation prediction technology, and discloses a photovoltaic power generation system output prediction system and method. The method collects historical power generation data of the target photovoltaic power station, as well as environmental monitoring data including irradiance, ambient temperature, module temperature, and cloud cover. This data is time-aligned to form a synchronized data sequence, from which meteorological and power generation characteristics are extracted. A dynamic correlation model between meteorological and power generation characteristics is constructed, and the instantaneous impact weight of meteorological fluctuations on power generation is calculated. Based on this, sensitive and non-sensitive periods for power generation are defined. High-fluctuation meteorological characteristics are extracted during sensitive periods, and steady-state meteorological characteristics are extracted during non-sensitive periods. The high-fluctuation meteorological characteristics are input into a first prediction network to generate short-term power prediction values, and the steady-state meteorological characteristics are input into a second prediction network to generate long-term power prediction values. The two are then fused to generate a complete output power prediction curve.

This disclosure relates to distributed hardware tracing. A computer-implemented method executed by one or more processors includes: monitoring the execution of program code executed by a first processor component; and monitoring the execution of program code executed by a second processor component. The computing system stores data identifying hardware events in a memory buffer. The stored events occur across processor units including at least first and second processor components. Each hardware event includes an event timestamp and metadata characterizing the event. The system generates a data structure identifying the hardware events. The data structure arranges the events in a time-ordered sequence and associates the events with at least the first or second processor component. The system stores the data structure in a repository on a host device and uses the data structure to analyze the performance of program code executed by the first or second processor component.

The invention relates to the field of biotechnology and dead / living cell detection, in particular to a method for rapidly determining the activity of biological membrane cells in immobilized fermentation. According to the method, a methylene blue and trisodium citrate synergistic chromosome system is optimized, a biofilm EPS matrix is synergistically penetrated by virtue of the dispersion effect of trisodium citrate and the reduction characteristic of methylene blue, and a spectrophotometric method is combined to detect the OD value of a staining solution instead of stained cells, so that the efficient quantitative analysis of the ratio of dead cells to living cells of the immobilized biofilm is realized. The method can complete detection within 200 s, is simple and convenient to operate and low in cost, does not need complex equipment, and is remarkably superior to a traditional fluorescent staining method.

This invention provides a method, apparatus, device, and medium for joint monitoring and analysis of sleep posture and respiratory status, relating to the field of artificial intelligence technology. The method includes: acquiring multi-channel signals; the multi-channel signals are mixed vibration signals of the chest and abdomen during sleep; inputting the multi-channel signals into a pre-trained joint monitoring and analysis model to obtain the joint monitoring and analysis results output by the model; wherein, the joint monitoring and analysis results are the correlation analysis results between sleep posture and OSA (Exhaustive Sleep Acuity). Through the above method, synchronous joint monitoring of sleep posture and OSA is achieved, effectively analyzing the correlation between the two.

The application discloses a kind of electric vehicle travel feature construction methods based on double-layer clustering architecture, it is related to electric vehicle travel feature mining technical field, the method includes: constructing city benchmark feature library;The historical operation data of target electric vehicle is preprocessed, and travel segment is divided based on vehicle state change, and the basic information of each travel segment is extracted;Based on city benchmark feature library, construct unified multidimensional feature vector;Application double-layer clustering architecture, first layer clustering uses variation bayes Gaussian mixture model to cluster normalized single travel feature vector, identify micro travel mode, second layer clustering is based on user behavior portrait vector, using the division clustering algorithm of improved initial center point selection to the user group is grouped, identify macroscopic travel habit;When the amount of travel data newly accumulated reaches preset condition, update city benchmark feature library.The feature construction method of the application can realize cross-city, hierarchical fine description.

This application discloses a method and related equipment for confocal endoscope image processing, relating to the field of image processing. The method includes: inputting the image to be processed into an Inception V3 network and an SPP structure to obtain a first feature, a second feature, and a third feature; extracting a first spatial domain attention map, a first channel domain attention map, and a first mixed domain attention map corresponding to the first feature, the second feature, and the third feature, respectively; performing non-maximum suppression operation on the first spatial domain attention map, the first channel domain attention map, and the first mixed domain attention map to obtain a second spatial domain attention map, a second channel domain attention map, and a second mixed domain attention map; performing a fusion operation on the second spatial domain attention map, the second channel domain attention map, and the second mixed domain attention map to obtain fused features; and performing recognition based on the fused features and a target classifier to obtain a valid image.

The present application relates to the technical field of automobile emission testing, and specifically discloses a testing method for real-time determination of excessive fueling emission of a vehicle, which comprises collecting vehicle data by using a vehicle-mounted emission detection device; arranging the vehicle data to generate a corresponding fueling emission test condition set; sorting each fueling emission test condition in the fueling emission test condition set according to the order of fueling time; calculating the pollutant emission limit value under the single fueling amount in each fueling emission test condition and the final result value of the pollutant emission test during the fueling process; and comparing and determining whether the current corresponding fueling emission test condition is excessive according to the calculated pollutant emission limit value and final result value. The present application can solve the problem that the vehicle cannot be determined and warned in time when the vehicle fueling process causes excessive pollutants.

This application relates to the field of data transmission technology and discloses a method and apparatus for testing infrared data transmission based on LED light. The method includes: acquiring transmission test data from a data transmission system and analyzing the transmission environment to obtain a target transmission environment; calculating the encoding performance data of multiple LED light sources and the decoding performance data of an infrared receiver; performing network initialization settings on a spatiotemporal graph convolutional network; constructing an encoding-decoding performance relationship curve and performing feature extraction and feature normalization to obtain multiple normalized performance features; performing data transmission performance anomaly analysis through a data transmission performance analysis model to obtain data transmission performance anomaly evaluation indicators; and generating a target anomaly handling strategy based on the data transmission performance anomaly evaluation indicators. This application improves the accuracy of infrared data transmission testing using LED light.

The application relates to the technical field of natural language processing, in particular to an NLP-based income and expenditure analysis report intelligent interaction method and system, which comprises the following steps: extracting a question keyword set of each user question sentence and an interaction keyword set of a corresponding interaction result sentence of the user question sentence; obtaining a close association evaluation value between the user question sentence and each adjacent question sentence of the user question sentence, and then obtaining a question and answer coherence degree of each user question sentence, calculating a semantic evolution degree of each user question sentence, and obtaining a key historical question sentence of the current user question sentence; using a BERT model to perform intent recognition and named entity recognition on the user question sentence, and then obtaining an income and expenditure analysis report. The application can improve the intelligent interaction efficiency of the income and expenditure analysis report.

The invention discloses a data file import method and device, a program product and electronic equipment, and relates to the field of financial science and technology or other related fields, and the import method comprises the steps of obtaining an application file of a target application, processing the application file to obtain a plurality of texts, creating a data job for each text, and creating a data job for each text; and asynchronously executing the data operation by adopting the distributed nodes, and importing the text into a preset data table in a preset database. According to the method and the device, the technical problem that the speed of importing the data file is relatively low in the prior art is solved.

A rare earth crystal observation method based on a deep learning model combined with a watershed algorithm, comprising the following steps: step 1: preparing a rare earth crystal structure image dataset, dividing the entire dataset into a training set and a test set; step 2: data augmentation is performed on the training set images; step 3: the improved Unet3+ deep learning model is trained using the training set, and the segmentation model is evaluated on the test set according to the image segmentation evaluation index, to obtain the final image segmentation model, which is used to predict the crystal structure image to obtain the original segmentation result image; step 4: for the original segmentation result image, a post-processing is performed thereon by using a watershed algorithm; and step 5: the final segmentation result image obtained after the post-processing in step 4 is observed, and the feature information of all connected regions is counted by using an OpenCV library. The present application can provide faster and more accurate crystal segmentation and statistical analysis.

The application relates to the field of engineering cost, and discloses an engineering cost data management method and system, which comprises the following steps: acquiring real-time collected cost data; if the cost data exceeds the monitoring threshold range of the corresponding project type, marking the cost data as a potential abnormal point and obtaining an abnormal data list; judging whether the abnormal point is related to the project type or the construction scale size based on the abnormal data list, regional market fluctuation data and material supply change characteristics, and obtaining an abnormal reason classification result; constructing a warning rule customization mechanism for regional market fluctuation to generate and verify a warning rule set suitable for the regional characteristics; acquiring new real-time cost data; and if the new real-time cost data triggers the conditions in the warning rule set, generating a corresponding warning signal. The method has the following effects: effectively identifying and analyzing cost data abnormalities.

The invention provides a medicine abnormal toxicity inspection electronic experiment record management system. The system comprises an inspection method management module, an animal management module, an animal data management module and an inspection result management module. Wherein the inspection method management module can carry out design, auditing and version control on a drug abnormal toxicity inspection experiment recording template; the animal management module is used for recording full life cycle data of experimental animals; the animal data management module is used for recording drug abnormal toxicity inspection experiment data; and the inspection result management module is used for generating, auditing and publishing electronic experiment records of drug abnormal toxicity inspection. According to the embodiment of the invention, the system achieves the automatic and full-life-cycle management of the drug abnormal toxicity inspection experiment data, guarantees the primitiveness, authenticity, safety and traceability of the laboratory data, effectively improves the inspection work efficiency, and achieves the comprehensive, scientific, unified, ordered and efficient computerized system management of the inspection data.

The application relates to a long and large suspended tunnel bidirectional fluid-structure coupling calculation method under a wave environment, and belongs to the field of marine engineering suspended tunnel structure design. In view of the problems of low calculation efficiency, neglect of structure disturbance to a flow field and incapability of processing complex topography of the existing method, a modeling strategy based on a two-dimensional potential flow wave tank group is provided: key sections are divided along a tunnel axis to establish independent water tanks, section wave loads are obtained by parallel solving of mathematical models of the water tanks, full pipe body load distribution is calculated by interpolation, and dynamic interaction of fluid motion and pipe body vibration is realized by bidirectional coupling iteration. The application efficiently processes kilometer-level suspended tunnel fluid-structure coupling calculation, significantly improves wave load precision, can simulate multidirectional waves and complex seabed topography, comprehensively outputs section forces and moments, is excellent in numerical stability, and provides a reliable analysis means for suspended tunnel engineering design.

The application discloses a Freebsd system industrial protocol deep inspection method, and relates to the technical field of industrial network security. The method injects a new industrial protocol deep inspection related module into three modules, namely, a Freebsd system kernel protocol stack, a communication intermediate library and a user space rule analysis program, so that the rate of industrial protocol inspection can be improved, network communication delay can be reduced, and normal production operation of the industrial control network can be ensured under the premise of guaranteeing the communication security of the industrial control network. Compared with traditional methods and prior art, the method has the advantages of not needing to completely change the system architecture, simultaneously considering performance and security, and providing more reliable security protection for the industrial control network.

This invention belongs to the field of imprinted sensor fabrication and application technology, and discloses a temperature-responsive yeast cell imprinted modified electrode, its fabrication method, and its application. This invention utilizes chronoamperometry and drop casting to modify gold electrodes, obtaining Au / AuNPs / Ti3C2T. x Au / AuNPs modified electrode. Using fluorescently labeled yeast cells as catalyst and template molecules, N-isopropylacrylamide as the temperature-responsive functional monomer and α-methacrylic acid as the auxiliary functional monomer, the electrode surface was modified using the MVL ATRP method. After removing the yeast cells, Au / AuNPs / Ti3C2T electrode was obtained. x / AuNPs / CIPs modified electrode. This modified electrode can be used as an electrochemical sensor for detecting yeast cells. This sensor has advantages such as fast detection speed and high sensitivity, with a linear response range of 1.0 × 10⁻⁶ for detecting yeast cells. 2 ~1.0×10 9 cells / mL.

The application discloses a kind of offshore circular inflatable beam deflection calculation method, device and electronic equipment, the method comprises: establishing offshore circular inflatable beam model, the offshore circular inflatable beam model includes circular inflatable beam body model and sea surface foundation model;With spring model instead of sea surface foundation model to establish offshore circular inflatable beam stress state model;According to the stress parameter of offshore circular inflatable beam stress state model and the measurement parameter of circular inflatable beam body model, establish deflection theoretical calculation model;Based on the deflection theoretical calculation model, the deflection of offshore circular inflatable beam to be measured is calculated.The present application establishes simple, efficient deflection theoretical calculation model by introducing winkel hypothesis, to realize for the load deformation of offshore circular inflatable beam of floating inflatable membrane structure composition, promote the purpose of inflatable beam development.

The present application belongs to the technical field of lens detection, and provides a spectral testing method and system for a lens assembly, the method comprising: acquiring projection images of different lens assemblies, the projection images being images of an elliptical light spot and a plurality of fringes; evaluating the different lens assemblies, and according to the results, labeling the projection images as qualified or unqualified to form a training set, obtaining a first subset and a second subset based on pixel point recognition; inputting the first subset and the second subset into a lightweight convolutional neural network with depth separable convolution and an efficient convolutional neural network with an attention mechanism, collecting the outputs, and training to obtain a testing model; and when performing spectral testing on the lens assembly, acquiring the projection image thereof, inputting the projection image into the testing model, and obtaining a testing result; the present application can solve the problems of low efficiency and low accuracy in the manual testing of the light transmission performance of the lens in the prior art.

The invention is suitable for the technical field of water conservancy project informatization, and provides a water conservancy project patrol management and protection method and system, and the method comprises the steps: collecting shoreline parameter data, water area parameter data and reservoir surrounding environment data; preprocessing the shoreline parameter data, the water area parameter data and the reservoir surrounding environment data to obtain a shoreline feature data set, a water area feature data set and a reservoir surrounding environment feature data set, and performing weighted fusion on the shoreline feature data set, the water area feature data set and the reservoir surrounding environment feature data set to obtain a comprehensive feature data set; constructing a potential safety hazard prediction model, inputting the comprehensive feature data set into the potential safety hazard prediction model, and predicting to obtain a potential safety hazard coefficient of the water conservancy project; comparing the predicted potential safety hazard coefficient of the water conservancy project with a preset potential safety hazard coefficient threshold value of the water conservancy project, and judging whether the potential safety hazard exists in the water conservancy project or not; according to the invention, the inspection efficiency and accuracy are greatly improved, and problems can be found and solved in time.

This invention discloses a device and method for measuring the thickness of oil pipe couplings, as well as a method for analyzing the connection strength of oil pipe couplings, belonging to the field of oil-specific thread testing technology. The oil pipe coupling thickness measuring device includes a mounting bracket, a digital display, a movable probe with a displacement sensor, and a fixed measuring shoe. The fixed measuring shoe includes a movable frame and a measuring shoe head mounted on the movable frame. The movable frame is telescopically connected to the mounting bracket, and the measuring shoe head is used to position the thread of the coupling to be measured. The movable probe with the displacement sensor is used to radially abut against the outer diameter of the coupling during thickness measurement. The displacement sensor on the movable side measures the coupling thickness based on the displacement change of the movable probe. This invention solves the problem in the prior art that there is no device for directly measuring coupling thickness and that coupling connection strength can be analyzed through coupling thickness measurement, achieving efficient and accurate measurement of oil pipe coupling thickness and reasonable analysis of coupling connection strength.

The invention discloses a method for constructing an enterprise large model knowledge base, which specifically comprises the following steps of: S1, data access and extraction: classifying data of a data source according to file types, and processing different types of files in a processing mode respectively; s2, data partitioning processing, including file structure analysis, semantic unit extraction, dynamic partitioning and length control and metadata injection; s3, vectorization and storage are carried out; s4, performing retrieval and generation; and S5, performing safety management and control. According to the scheme, the files of common types are classified, data extraction is carried out in an independent mode, efficient analysis of the files of multiple types is achieved, meanwhile, semantic units exceeding maxtokens are segmented through a sliding window and a semantic boundary alignment algorithm by means of dynamic partitioning and length control, the coherence of document data semantics is guaranteed, and therefore the efficiency of document data processing is improved. And the finally obtained retrieved result is more comprehensive and accurate.