24results about How to "Improve data availability" patented technology

The invention provides an erasure code compatible read-write method and system based on a bidirectional data access agency, and relates to the technical field of distributed storage, and the method comprises the steps: employing multi-agent reinforcement learning to construct a heterogeneous resource portrait and optimize task allocation, combining a space-time graph convolutional network and a federated learning framework to construct a data format conversion model, and constructing an erasure code compatible read-write model; data features are analyzed through an encoder based on an attention mechanism, a fragmentation strategy is generated, self-adaptive encoding is achieved through a capsule neural network, data integrity verification and repairing are conducted through a double-layer space attention network and a graph attention network, the data access efficiency of a heterogeneous storage system is improved, data format compatibility is enhanced, and the data access efficiency is improved. And the data integrity is ensured.

The invention discloses a method for automatically generating a dynamic language test case based on a large language model, which comprises the following steps of: firstly, in a preprocessing stage, arranging related information of a to-be-tested program into prompts, analyzing a parameter type of the to-be-tested program by the large language model according to the prompts, and generating code information required by a test through an abstract syntax tree; in the test case generation stage, a dynamic multi-objective optimization algorithm is adopted, test cases are continuously crossed and mutated through branch coverage feedback, in the partial evolution process, test data which cannot be generated by conventional variation are generated by utilizing a large language model, and finally, the screened excellent test cases are organized into a complete test suite. In a program repair phase, the test suite is run to detect potential errors, the errors are analyzed and iteratively repaired using a large language model, and an executable and error-free test suite is generated. According to the method, the test coverage rate of the dynamic language is remarkably improved, and the achievement of a coverage target is accelerated.

The invention discloses a differential privacy federal learning method and system based on double knowledge transfer, and relates to the field of machine learning, and the method comprises the steps: training a teacher model through a data subset; determining a teacher voting result of each sample by using a weight-based voting mechanism; based on a teacher voting result, determining a label of an unmarked teacher data set, and training a student model by using a marked teacher data set; determining a student voting result of each sample in the medical server by using a weight-based voting mechanism; labels of unmarked student data sets are determined based on student voting results, and a global model is trained by using marked student data sets; and performing fine tuning and further self-training on the global model by using an importance sampling mechanism to obtain a final global model. According to the invention, a voting mechanism based on weight is introduced in knowledge transfer, and the model weight is adjusted according to the individual difference of the teacher model, so that the model effectiveness of federated learning is improved, and the communication overhead is effectively reduced at the same time.

The invention relates to a multi-modal human body action recognition method, and belongs to the field of human body action recognition. Video space features are extracted through a ResNet152 network, time-dependent features are extracted through a Bi LSTM network, and feature coding is carried out; afterwards, feature fusion is carried out by using an improved series cross attention network, a cross attention module is initialized by adopting a random pulse filtering convolution matrix, and the inductive deviation of the CNN is introduced into the cross attention module, so that the validity of model data is improved, and the model data is easier to fit on a small-scale data set; and finally, performing action category prediction on the fused features through a full connection layer and a Softmax function. According to the method, the performance of multi-modal human body action recognition on a small-scale data set is effectively improved, the universality and universality of the method are enhanced, and the method is suitable for various scenes such as human-computer interaction, monitoring videos and gesture recognition.

This invention belongs to the field of photocrosslinking probe technology, specifically relating to a GUSB photocrosslinking probe, its preparation method, and its application. The GUSB photocrosslinking probe has the general chemical formula C0. 13 H 18 N2O6-R, wherein R is any one of the oxalic group elements or peptide bonds. The R group covalently connects the glucuronic acid recognition core and the photosensitive unit in the GUSB photocrosslinking probe, and the R group contains no more than 4 atoms, resulting in a small size and low steric hindrance. The GUSB photocrosslinking probe provided by this invention uses glucuronic acid as the recognition core, combined with a small-volume diazacyclopropane photosensitive unit and a terminal alkyne group, to achieve µM-level in-situ covalent capture of active GUSB in complex systems such as cells or tissues. The probe of this invention significantly improves positioning accuracy, sensitivity, data availability, quantification, and enrichment, while also possessing advantages such as modular synthesis, mild conditions, and strong system compatibility, effectively addressing the technical shortcomings of existing technologies that struggle to accurately obtain GUSB activity in situ under low-dose conditions.

The invention discloses an analog quantity sampling source end data error correction and prevention system and method. The system comprises an ADC chip, an ADC digital interface module and an error data detection and recovery module. The ADC chip is used for converting an acquired analog signal into a digital signal and inputting the digital signal into the ADC digital interface module; the ADC digital interface module is used for repeatedly sending two groups of complete digital sampling signals which are read from a digital interface of an ADC chip and have the same content but different sequences to the error data detection and recovery module through two independent interface data output channels, wherein each digital sampling signal with different sequences is read from the digital interface of the ADC chip; and the error data detection and recovery module performs error detection and / or recovery processing on the digital sampling signals uploaded by the two interface data output channels respectively, and transmits the recovered correct digital sampling signals to the corresponding application function modules. According to the invention, real-time error detection and error correction of ADC sampling data can be realized, and a fault-tolerant effect on accidental data damage when an ADC chip operates in a complex electromagnetic environment is achieved.

The invention relates to the technical field of environment monitoring, and discloses a plateau lake basin cultivated land soil pollution multi-index synchronous monitoring method. The method is suitable for plateau lake basin cultivated land, and under the condition that plateau lake basin cultivated land soil measured data is high in acquisition cost and difficult to acquire in quantity, a spatial distribution diagram of cultivated land soil non-point source pollution source load indexes is acquired in a large-scale, low-cost and high-efficiency manner by assisting limited field monitoring data through a satellite remote sensing means. Through long-term soil pollution index content and variable quantity monitoring and risk level evaluation, visualization, quantifiability, traceability and prevention and control of non-point source pollution are realized, the limitation of replacing surface by point in traditional point location measurement is overcome, and the method is the most efficient method for evaluating the potential risk of agricultural non-point source pollution.

The invention discloses a smart park articulated naturality web node data distributed storage system, and relates to the technical field of smart park data storage. Comprising a data acquisition layer, a distributed storage node cluster, a metadata management module, an intelligent scheduling module, a data security guarantee module, a data verification module, a data adjustment module and an application interface layer, and all the modules cooperate to realize efficient storage, quality control and management of articulated naturality web node data. Aiming at a smart park articulated naturality web data storage pain point, efficient storage and management and control are realized through multi-module cooperation, a distributed architecture, mixed storage and intelligent scheduling are adopted, the storage efficiency and the resource utilization rate are improved, multi-copy backup, cross-physical deployment and automatic fault repair are realized, data reliability is guaranteed, and the system is suitable for large-scale popularization and application. The method comprises the steps of full-process encryption, authority control and multi-dimensional verification, building of a data security defense line, data dynamic optimization and standardization of an interface, enhancement of data availability and system compatibility, and adaptation to the dynamic increase demand of park data.

The invention discloses a concrete mixing quality prediction method based on mixing condition self-adaption and an AI model, and belongs to the technical field of concrete mixing quality prediction, and the method comprises the following steps: collecting batch working condition information related to a concrete mixing technology and a multi-source process signal in a mixing process, judging the working condition type of the current batch, and determining the working condition type of the current batch; determining feature normalization parameters of the current batch, performing feature extraction on the collected multi-source process signals according to process stages to obtain normalized feature expression, constructing the normalized feature expression and batch working condition information as feature input of the current batch, and inputting the feature input into an artificial intelligence model to obtain an artificial intelligence model; and obtaining a prediction result including the concrete quality index set. According to the method, the problems that the cross-working-condition generalization ability is insufficient, the dependence on calibration data is relatively strong, and the output stability and the engineering suitability need to be improved in an engineering scene with complex working condition fluctuation, process event disturbance, equipment difference and long-term drift are solved.

The application relates to the technical field of data processing, and discloses a multi-source heterogeneous data edge processing method and device for field monitoring and a medium, which comprises the following steps: based on a data access link, parallelly receiving original data generated by different monitoring devices in a field monitoring site; extracting multi-dimensional features to determine the data source types corresponding to the original data; calling corresponding analysis engines according to the data source types to generate analysis results through differential analysis; determining the time field priority according to the data source types, selecting target time fields from the analysis results, performing unified event time axis mapping, and generating standardized data; writing the standardized data into a classified cache queue, determining the time effectiveness level according to the time difference between the standard event time and the current time, and performing hierarchical sending scheduling based on the time effectiveness level and the network state. The edge access capability of multi-source heterogeneous data in the field ecological monitoring scene, the cross-source time correlation capability and the key data sending capability under the weak network condition are improved.

The invention discloses a cloud certificate storage method and system based on a threshold algorithm, and relates to the field of information security. The method comprises the following steps: generating a signature public key and a signature private key through a central node, and generating a certificate signature request based on the signature public key; the certificate signature request is sent to a key management center, and a key protection structure is generated and returned through the key management center and comprises an encryption private key and a symmetric key; using the signature private key to perform asymmetric decryption on the symmetric key in the key protection structure, and using the decrypted symmetric key to decrypt the encryption private key in the key protection structure; respectively splitting the signature private key and the decrypted encryption private key by using a threshold algorithm to generate a plurality of key fragments, and encrypting each key fragment; and storing the encrypted key fragments in a plurality of service nodes in a distributed manner. According to the scheme, the private key is split into a plurality of key fragments for distributed storage, so that the security of cloud certificate storage is improved, and the hardware cost and the operation and maintenance complexity are reduced.

The invention relates to the technical field of signal processing, in particular to an intelligent bridge inspection vehicle laser radar interference point filtering method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring point cloud data of a target bridge, wherein the point cloud data comprises environmental information in a target equipment detection area; identifying and removing interference point data in the point cloud data to obtain application point cloud data; and performing advancing control and bridge detection of the target equipment based on the application point cloud data. By adopting the method, the interference in the data detected by the radar can be reduced, the data accuracy can be improved, the defects caused by the existence of interference points can be overcome, the accuracy of the detection result of the sensing system can be improved, the unnecessary alarm or braking action can be reduced, and the availability of the system can be improved.

The invention is applied to the field of logistics management, and discloses an intra-city delivery service provider scheduling method and system, and the method comprises the steps: obtaining real-time heterogeneous service data of each delivery service provider and real-time context data corresponding to an intra-city delivery request in response to the intra-city delivery request; performing protocol conversion on each piece of real-time heterogeneous service data to obtain standardized distribution service data; splicing the standardized distribution service data with the real-time context data to generate distribution feature vectors corresponding to distribution service providers; inputting each delivery feature vector into a pre-trained scheduling decision model, screening a target delivery service provider based on a model output result, and generating a standard scheduling instruction of the target delivery service provider; performing reverse protocol conversion on the standard scheduling instruction to obtain a target execution instruction adaptive to the target distribution service provider; and executing the target execution instruction to complete the city-wide distribution request. According to the method provided by the invention, the service scheduling efficiency is improved.

The invention discloses a molecular structure-activity relationship modeling method based on symbol regression KAN, and belongs to the field of chemoinformatics. The method comprises the following steps: constructing and cleaning molecular property data to form a molecular-chemical descriptor-target property data set; calculating and screening descriptors, and reducing redundancy and colinearity by adopting variance screening and correlation analysis; and training the KAN to obtain a target property prediction function and exporting an explicit expression. By taking the organic amine CO2 absorption cycle period as an example, the upper / lower limit auxiliary screening of the cycle period can be predicted. According to the modeling method, an interpretable basis is provided under a small sample condition, and the dependence on a large amount of experimental data is reduced.

According to the user track protection method and device in crowdsourcing service, the equipment and the storage medium provided by the invention, firstly, the track data generated by the user is acquired, the privacy budget corresponding to the track data is calculated, the target position point in the track data is predicted, and the prediction result corresponding to the target position point is obtained; and then an error between the target position point and a prediction result corresponding to the target position point is calculated to obtain an importance evaluation result corresponding to the target position point, and finally the privacy budget is correspondingly allocated to the target position point according to the importance evaluation result. The privacy of the user can be effectively protected, the maximization of the data value can be ensured, and a safe and credible interaction relationship is established between the user and a service provider. By applying the Kalman filtering technology and comparing a predicted position point with an actual position point, the importance of the position point is evaluated, and a better privacy protection effect and higher data availability are achieved.

The invention relates to the technical field of computers, in particular to a webpage resource request method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of obtaining first data of a target application, wherein the first data comprises resource access interface data corresponding to a resource access request of a target account; according to the resource access interface data, generating a dynamic configuration table corresponding to the target account, the dynamic configuration table being used for configuring a resource access interface; in response to a starting operation of the target application, generating a pre-request for resource access of the target application based on the dynamic configuration table; and sending the pre-request, and receiving webpage resource data in response to the pre-request. By adopting the method, the request efficiency of the webpage resources in a complex request scene and the validity of the requested resource access interface data can be improved.

The invention relates to the technical field of artificial intelligence, and provides a multi-sea-condition detection data set generation method, system, device, product and medium, and the method comprises the steps: arranging an unmanned plane and a camera in a target sea area; a camera tracks passing ships in a target sea area, first ship automatic identification system information of the passing ships is acquired, a calibration key point set is selected through an approximate grid selection method, and calibration of the camera is completed through the calibration key point set and the first ship automatic identification system information; a camera monitors a target sea area, and a monitoring module monitors to obtain information of a second ship automatic identification system, so that a multi-modal ship sample is obtained; inputting the multi-modal ship sample and the sea condition description text into a text picture generation model to obtain an initial multi-sea-condition ship data set; and checking the initial multi-sea-condition ship data set to obtain a target multi-sea-condition ship data set. According to the invention, the multi-sea-condition ship data set can be effectively and automatically generated.

The invention discloses a prepaid function remote control method based on a power supply transfer main body and a terminal user, relates to the technical field of prepaid function remote control, and solves the problem that in the prior art, energy consumption data analysis cannot be performed on the terminal user and the corresponding power supply transfer main body when the terminal user performs remote meter reading; the method specifically comprises the following steps: performing energy consumption data analysis on a power supply main body and a terminal user, deducing whether the current power consumption is abnormal or not according to the energy consumption data analysis, and performing remote meter reading when determining that the current power consumption is abnormal; performing real-time energy consumption prediction on the terminal user, and performing prepayment recommendation according to the energy consumption prediction; according to the real-time energy consumption demand prediction analysis of the terminal user, deducing whether the electricity consumption habit and the electricity consumption demand of the current terminal user need to be prepaid or not; and carrying out supply efficiency analysis according to the power supply process of the power supply transfer main body and the terminal user, and formulating an electric loss sharing rule according to an efficiency analysis result.

The invention provides a data privacy protection method and system based on data annotation, and the method comprises the steps: carrying out the data form reconstruction operation of a talent data set, obtaining a semantic data unit set, carrying out the feature cluster division operation of the semantic data unit set, generating a feature cluster set, and carrying out the data privacy protection based on the semantic density value and field association strength value of each feature cluster. Calculating a noise type and a noise parameter corresponding to each feature cluster by combining sensitive attribute tags of the feature clusters to obtain a feature cluster noise parameter comparison table, and mapping the semantic data unit set into the feature cluster noise parameter comparison table according to a feature cluster attribution relation; performing corresponding noise generation and injection on feature cluster data fields of different sensitive attribute tags to generate a disturbance data set, performing correlation degree evaluation on the disturbance data set, and judging whether a preset correlation maintaining threshold value is met or not by calculating a correlation degree change rate between fields in a semantic data unit before and after disturbance; and if yes, outputting a privacy protection data set for labeling the task. According to the method, the privacy protection accuracy and the data availability are improved.

This invention discloses a method for protecting electricity metering data, comprising the steps of: acquiring electricity metering data; acquiring a predefined localized differential privacy function; binarizing the electricity metering data and performing random perturbation using the localized differential privacy function and a Cuckoo filter; sending the data to a server; the server receiving the data, obtaining statistical information on specific categories of data, calculating an unbiased estimate of the proportion of the specific categories of data, thereby obtaining the filtered statistical results of the electricity metering data. Implementing this invention, by employing a localized differential privacy protection method, can improve user privacy regarding electricity metering data.

The present invention relates to a method and system for generating global land surface temperature data based on MODIS data. The method comprises: performing mean processing on global land surface temperature LST data and global sea surface temperature SST data; resampling SST data according to the resolution of LST data; splicing the resampled SST data with LST data; interpolating the spliced ​​data, including interpolation of mid-latitude missing value areas and interpolation of Arctic missing value areas; wherein for missing values ​​in the Arctic region, the temperature value of the region is reassigned; and generating global land surface temperature GST data according to the interpolation result. The method and system for generating global land surface temperature data based on MODIS data provided by the present invention can not only take into account the information of clear sky images, but also avoid the problem of low data accuracy caused by the warming / cooling effect of cloud cover on the surface temperature.

The present invention relates to the field of artificial intelligence technology, and provides a method, system, device, product and medium for generating a multi-sea condition detection data set, including deploying a drone and a camera in a target sea area; the camera tracks a passing ship in the target sea area, and collects and obtains the first ship automatic identification system information of the passing ship, selects a calibration key point set by an approximate grid selection method, and completes the calibration of the camera by the calibration key point set and the first ship automatic identification system information; the camera monitors the target sea area, and a monitoring module monitors and obtains the second ship automatic identification system information, thereby obtaining a multi-modal ship sample; the multi-modal ship sample and the sea condition description text are input into a text image generation model to obtain an initial multi-sea condition ship data set; the initial multi-sea condition ship data set is tested to obtain a target multi-sea condition ship data set. The present invention can effectively and automatically generate a multi-sea condition ship data set.

The invention relates to the field of power plant measuring point monitoring, in particular to a measuring point monitoring method and a measuring point management system based on correlation analysis, and the method comprises the steps: carrying out the standardized coding processing of mass measuring point data; establishing a communication environment of a plurality of measuring point data sources and a real-time data platform; acquiring measuring point data, and transmitting the measuring point data to a real-time data platform; establishing a measuring point data dynamic analysis and verification model, and processing and analyzing the measuring point data; and intelligent matching query of measuring point data is realized. According to the invention, the monitoring effect of power plant managers on abnormal measuring points can be improved.

The invention discloses wearable detection equipment, a pulse wave detection method and a related device, and relates to the technical field of biology, the wearable detection equipment comprises a controller, a micro inflator pump, a micro air release valve, a micro air bag, a pulse sensor and a wrist strap; the micro inflator pump, the micro air escape valve and the pulse sensor are all electrically connected with the controller; the pulse sensor and the micro air bag are arranged on the inner surface of the wrist strap, the pulse sensor is wrapped in the micro air bag, and the inner surface is the surface, making contact with the skin of a user, of the wrist strap; the micro inflator pump is connected with the micro air bag, and the micro air release valve is arranged on a connecting passage of the micro inflator pump and the micro air bag. Appropriate pressure can be applied to the skin of the user by inflating the micro air bag, so that the controller can obtain the change of the pulse wave from zero to the maximum peak value, the complete waveform of the pulse wave in the change period is obtained, the situation that part of the pulse wave is lost is reduced, and the data availability of the pulse wave is effectively improved.