60results about How to "Improve data processing efficiency" patented technology

The invention provides a target identification method and system based on multi-source information fusion, and relates to the technical field of low-altitude target detection. The method comprises the following steps: acquiring target radar track data, interception equipment track data and position area information data; based on target radar track data, extracting a first feature in an RCS form dimension, and extracting a second feature in a motion dimension; based on the target radar track data and the track data of the monitoring equipment, determining a frequency spectrum monitoring correlation factor and regional position information features; performing feature fusion on the first feature, the second feature, the spectrum interception correlation factor and the regional position information feature to obtain a target feature, and identifying a target type; and identifying a target threat level based on the target type and the target radar track data. The method and the device are used in a target identification process based on multi-source information fusion, and the technical problem that the target threat degree cannot be accurately identified in a complex environment in the prior art is solved.

This invention relates to a service fault location system and method based on a BMC (Browser Control Center). The system includes: establishing a communication link between the BMC and the server under test (DUT) using a customized IPMI protocol; configuring test parameters and controlling the DUT to power on and start a restart test program; the BMC collecting current hardware-level data; the BMC performing temporary storage and determining whether an anomaly occurred during the current test round; when an anomaly occurs during the current test round, the BMC receives the current customized IPMI message, obtains the anomaly level information, and controls the CPLD (Content Management Logic Controller) to perform a hard restart or not perform a hard restart based on the anomaly level information, and persistently stores the on-site data. No additional test equipment or server hardware / software modifications are required, resulting in lower testing costs and broad applicability; in the event of an abnormal downtime, the BMC can directly operate the CPLD to perform a hard restart, greatly improving testing efficiency and continuity.

The present application belongs to the field of computer vision, image processing technology and neuroscience, and relates to a two-photon calcium ion image neuron cell body segmentation method, comprising the following steps: S1. Adopting a neuron cell body enhancement network, removing noise and neural fiber network background signals in a two-photon calcium ion video, enhancing the spatiotemporal signal of the cell body, and obtaining a cell body enhanced video; S2. Using an anchor-based target detector to detect the position of the cell body on the maximum projection image of the cell body enhanced video; S3. Through a correlation clustering module, a mask of the cell body located at the center is segmented from each anchor output by the target detector. The method of the present application takes into account the advantages of method-driven and data-driven, compared with traditional algorithms, greatly improves the efficiency of processing data, and greatly improves the precision of overlapping cell segmentation for Bessel imaging data with high cell overlap characteristics.

The invention provides a DPU capability multiplexing method and device, electronic equipment, a storage medium and a program product, relates to the technical field of communication, and is used for improving the resource utilization rate of a DPU. The method comprises the following steps: receiving a DPU call request message, wherein the DPU call request message comprises a DPU capability demand of a target application; based on the calling request, determining N reusable DPUs meeting the DPU capability requirement; n is an integer greater than or equal to 1; a calling response message is sent to a source DPU where the target application is located, the calling response message comprises the address information of the N reusable DPUs and is used for indicating the source DPU to segment the to-be-processed data of the target application according to the address information of the N reusable DPUs to obtain N data slices, and the N data slices are sent to the N reusable DPUs respectively.

The application discloses a prior feature auxiliary directional coordinate attention remote sensing road extraction method, and relates to the technical field of remote sensing image processing.The method comprises the following steps: extracting multi-source prior features representing road physical characteristics and optimizing and fusing weight to obtain a fused prior feature map; processing the RGB remote sensing image and the fused prior feature cooperatively to form a fused feature containing multi-scale semantic information and physical prior; predicting a pixel main direction angle in the feature through a directional coordinate attention mechanism, pooling the feature along the main direction and the orthogonal direction to generate an attention map and re-calibrate the original feature; performing step-by-step up-sampling on the decoder and introducing a deep supervision mechanism; and training the model by using a composite loss function containing a Dice loss, a Focal loss and a boundary perception loss.The application fully utilizes road physical characteristic prior knowledge, combines the directional coordinate attention mechanism to capture road geometric characteristics, and effectively improves the accuracy and integrity of remote sensing road extraction in a complex scene.

This invention discloses an efficient QR matrix decomposition method based on FPGA for implementing systolic matrices, belonging to the field of software-defined radio signal transmission technology for airborne networks. It is based on the design of a multi-channel digital front-end implemented on an FPGA chip. The method includes: designing a general handshake coordination mechanism, designing a timing flow for systolic matrix multiplication, performing fast QR matrix decomposition single-loop operations by calculating the Householder mirror transformation matrix, designing a top-level loop pipeline for QR matrix decomposition, and finally verifying the hardware scheme of the fast QR decomposition algorithm. This invention converts resource consumption into timing consumption by designing the overall pipeline logic and loop operations, enabling fast processing and accurate decomposition of digital information in a multi-channel digital front-end on an FPGA, effectively saving on-chip resources. In addition, this invention has excellent scalability, supporting 64 to 128-bit high-precision fixed-point number formats, and the data matrix order can reach up to 128.

The invention relates to the technical field of big data management, in particular to a whole-process performance data management method based on big data. The specific implementation process comprises the steps of obtaining heterogeneous behavior traces, deconstructing and packaging the heterogeneous behavior traces into space-time cross-domain data streams, and inputting the space-time cross-domain data streams into a distributed cooperative monitoring model; an asynchronous pause frequency and a cross-domain retrieval track are extracted, a cooperative friction coefficient is calculated, and a cooperative retardation degree is generated; inputting the collaborative friction coefficient and the collaborative retardation degree into a performance evolution engine, generating a targeted dynamic weight, and outputting a targeted collaborative performance report; and outputting a resource intervention instruction when the cooperative retardation degree change slope exceeds a preset warning threshold. According to the method, real-time unified access of multi-source heterogeneous process data, continuous association modeling of cross-system behavior tracks, detection of flow blocking nodes and online dynamic updating of evaluation weights are realized by utilizing a distributed collaborative monitoring model and a performance evolution engine, so that the association processing delay of the cross-system data is reduced; and the timeliness and accuracy of flow anomaly detection are improved.

The embodiment of the specification provides a method and device for data processing in multi-party secure calculation. In a service processing process based on multi-party secure calculation, arithmetic inverse square root calculation is performed on a power of 2 in a Boolean sharing form constituted by two data parties. Under the corresponding technical concept, the characteristics of the power of 2 in the binary form and the Boolean sharing, and the positional relationship between the power of 2 and the inverse of the power of 2 before and after the decimal point are utilized. The inverse of the power of 2 in the Boolean sharing form is determined through the bit value reverse arrangement in the Boolean slice. Then, the two parties construct the square root value of the power of 2 by squaring through the splitting of the slice in the Boolean sharing form of the inverse of the power of 2. In this way, the data communication amount of the arithmetic inverse square root calculation of the power of 2 can be greatly reduced, and the service processing efficiency of the secure calculation is improved.

This invention relates to the field of data transmission technology, specifically to a performance optimization system and method for single-QP scenarios based on RDMA. The system includes an electrically connected HCA network interface card (NIC) and a host. The HCA NIC internally includes an electrically connected DB_PROC module, a WQE_PROC module, and a PKT_ENG module. The WQE_PROC module contains a WQE_CACHE cache space. The DB_PROC module obtains the scheduling request for the target QP. The WQE_PROC module queries the WQE_CACHE cache space to check if the target work queue element WQE corresponding to the target QP exists. If it exists, it reads it from the WQE_CACHE cache space; otherwise, it reads it from the host. This invention reduces the latency of reading WQE from the host, thereby improving bandwidth performance in single-QP scenarios and enhancing data processing efficiency.

The invention discloses a big language model security test data processing method and system, and relates to the technical field of memory management, the method comprises the following steps: obtaining test data in a big language model security test platform, the test data comprising multi-modal data, structured attack load data, long-term session state data and short-term temporary data; according to the test data, performing region division on a main memory space to obtain a plurality of initial functional regions; constructing a corresponding regional memory management unit in each initial functional region, the regional memory management unit being used for performing memory allocation according to a memory allocation strategy; and after memory allocation, allocating the test data to the corresponding initial function region, and processing the test data. According to the method, the memory can be allocated in combination with the functional region and the memory allocation strategy, so that the test data has enough memory space, the test data processing is realized, and the memory management reliability and the data processing efficiency are improved.

The embodiment of the application provides a kind of based on multi-dimensional feature constraint's net body intelligent multi-model calling method and product, it is related to artificial intelligence technical field.The method comprises: obtaining directed graph structure;Wherein, directed graph structure includes multiple graph nodes and the node feature and the edge feature corresponding to each graph node;According to user task request, generate task request feature;According to task request feature and the multiple graph nodes in directed graph structure and the node feature and the edge feature corresponding to each graph node, one or more graph nodes in directed graph structure is determined as target graph node;According to target graph node, determine task processing path;Wherein, task processing path is used to call the model corresponding to target graph node according to the model calling order corresponding to task processing path when processing user task request;Solved the problem that the model called in prior art scheme exists poor matching, improves data processing efficiency and resource utilization.

The invention provides a bridge monitoring method, system and equipment based on deep learning and a medium, and the method comprises the following steps: collecting an original strain sequence and environmental parameters of each monitoring point of a road bridge, calculating a theoretical thermal strain according to the environmental parameters and a material thermal expansion coefficient, and carrying out the alignment subtraction of the theoretical thermal strain and an original data time sequence, so as to obtain a structural strain through correction; constructing a space-time strain matrix in a preset time window according to the monitoring point position and the acquisition time sequence, and uploading the space-time strain matrix to the cloud; inputting the matrix into a deployed convolutional neural network at a cloud end, extracting deep features by adopting multi-layer convolution comprising a time dimension convolution kernel and a space dimension convolution kernel, and then mapping the deep features into settlement state probability vectors through a full connection layer; and comparing the vector with a reference health state vector, and if the deviation exceeds a safety threshold, triggering settlement early warning. By implementing the technical scheme provided by the invention, environmental interference can be effectively eliminated, and the accuracy and real-time performance of bridge settlement monitoring are improved.

This application relates to the field of communication technology, providing a data transmission method, apparatus, electronic device, storage medium, and computer program product, applied to data source nodes of a data source organization in a blockchain network built on a consortium blockchain. The data transmission method includes: encrypting the data to be transmitted based on its data sensitivity type to obtain encrypted data; fragmenting the encrypted data to obtain fragmented data; and transmitting the fragmented data to at least one data processing node of the data processing organization in the blockchain network. This application improves data transmission security by utilizing the immutability of blockchain technology and encrypting the data; furthermore, by fragmenting the encrypted data before transmission, data privacy can be protected through multi-party computation, further enhancing data transmission security. Therefore, it can improve data processing efficiency and resource utilization while ensuring data transmission security.

The application relates to the technical field of numerical simulation, and discloses an ice-induced vibration simulation method based on DEM-FEM coupling, which comprises the following steps: a predicted displacement matrix is calculated by using a historical node displacement matrix, a historical node velocity matrix and a historical node acceleration matrix; a micro time step calculation is performed within a current macro time step to reconstruct a transient displacement boundary matrix; a bonding stress failure judgment is performed to generate a transient contact force matrix, a micro fracture density parameter is calculated, and the transient contact force matrix is integrated into an equivalent node load matrix; the equivalent node load matrix and a virtual compensation force matrix are input into a macroscopic kinetic control equation to obtain a real node displacement matrix; an interface energy deviation scalar is calculated to generate the virtual compensation force matrix; and the next macro time step is calculated by using the micro fracture density parameter and returned to the cycle. The application can reduce the calculation error caused by the inconsistency of the macro and micro time steps, improve the simulation accuracy, and balance the calculation time consumption.

The application discloses a health exercise service system and equipment fusing local medical treatment and community resources, and relates to the technical field of data processing; the method comprises the following steps: preprocessing medical data and community detection data to obtain a first medical feature vector and a first community detection feature vector; calculating the first medical feature vector to obtain a medical evaluation coefficient; calculating the first community detection feature vector to obtain a community detection evaluation coefficient; substituting the medical evaluation coefficient and the community detection evaluation coefficient into an intelligent health service model to obtain an adaptive service score; and dividing corresponding adaptive service schemes according to the adaptive service score; the medical feature data and the community detection feature data are fused, the data processing efficiency is greatly improved, and the health service quality is improved.

This invention discloses a data fusion method for initial classification of remote sensing digital images, belonging to the field of remote sensing digital image processing technology. The method uses at least one data fusion template to perform multiple rounds of scanning processing on the initial classification results of the remote sensing digital image. The data fusion template includes an internal fusion template and an edge optimization template. The upper left pixel of each template is defined as an anchor point, and the template contains reference points and correction points at pre-set fixed positions. During processing, the anchor points are sequentially aligned with the positions of each pixel in the image. Based on the category value of the pixel corresponding to the reference point, it is determined whether to modify the category of the pixel corresponding to the correction point to the same category. The multi-round scanning processing includes sequentially using multiple different templates, repeatedly using the same template, and alternating between the internal fusion template and the edge optimization template. This invention can eliminate salt-and-pepper noise and small patches, optimize ground feature boundaries, and improve classification accuracy.

This invention provides a method and system for road condition data acquisition and analysis based on a commercial vehicle connected driving recorder. The invention utilizes a connected driving recorder, a mandatory standard feature in commercial vehicles, to acquire road images in real time via an image acquisition module and perform preprocessing such as backlight compensation, distortion correction, noise reduction, and effective area cropping. An image recognition module employs a lightweight deep learning and rule-based algorithm to locally identify congestion and traffic accidents. A positioning module acquires latitude and longitude, vehicle speed, and timestamps via GPS / BeiDou dual-mode, achieving precise spatiotemporal binding through timestamp alignment and interpolation compensation. A 4G communication module uploads data using a strategy prioritizing event triggering and supplementing with periodic heartbeats. A data monitoring platform verifies the data, performs 3D deduplication, and then visualizes it on an electronic map. This invention requires no additional hardware, is low-cost, has wide coverage, and strong real-time performance, enabling automatic and precise monitoring of road conditions across the entire area, and is suitable for traffic management and logistics scheduling.

This invention provides a shared memory management method, apparatus, electronic device, and storage medium, relating to the field of mobile application development technology. The method includes: when shared memory expansion is possible, determining the actual expansion memory based on the relationship between the target memory and the maximum preset memory, and expanding the shared memory according to the actual expansion memory. The target memory is the size of the shared memory after expansion according to preset rules. The actual expansion memory is used as the expanded shared memory, and listeners on the mobile webpage and native application are notified to update memory usage statistics. This invention can reduce or even avoid the overhead of string serialization and deserialization. Expanding shared memory when expansion is possible ensures the stability of data transmission between the native application and the mobile webpage. It reduces CPU utilization and improves CPU operating speed and data processing efficiency.

This application relates to a method, apparatus, medium, and computer equipment for constructing urban water network models. The method includes: establishing a coupled InfoWorks ICM-Delft 3D model based on an InfoWorks ICM model and a Delft 3D model; establishing an objective function based on the coupled InfoWorks ICM-Delft 3D model; and determining at least a flood control plan based on preset rules and the objective function. The apparatus uses the method described above. This application, by establishing a coupled InfoWorks ICM-Delft 3D model, then establishing an objective function, and finally training the objective function according to preset rules to determine the flood control plan, can better establish a drainage and flood control model for simulating and predicting flood control systems and tracing the source of water pollution. It also has high data processing efficiency and improves the accuracy of water depth prediction for non-monitoring units and the accuracy of water quality process change prediction.

The application discloses a charging gun data pushing method, a terminal and a storage medium, wherein a control message middleware acquires current state data of a charging gun in batches according to a preset time window; corresponding cache state data of the charging gun is read in a cache database; the current state data and the cache state data of the charging gun are compared, and the charging gun with different current state data and cache state data is marked as a target charging gun; the current state data of the target charging gun is overlaid on the corresponding cache state data in the cache database, and the current state data of the target charging gun is sent to a target platform. The application expands the data processing object from a single message to a batch of messages, can reduce the consumption blocking risk caused by processing messages one by one, and reduces the redundant cache update and redundant platform pushing caused by state data without changes, so that the overall data processing efficiency and state pushing efficiency are improved in the scene with a large number of charging guns and a high reporting frequency.

The application relates to the technical field of monitoring data processing, and discloses a monitoring terminal of a combined overflow pipeline system and a data processing method, which comprises the following steps: time alignment of liquid level data and gas concentration data based on timestamps, frequency domain filtering of time series data sets based on the set blocking bandwidth of astronomical tidal periods, segmentation and interception of target time series data sets based on a sliding time window in an edge computing terminal, determination of the correlation result of the liquid level and the gas concentration based on a correlation rule algorithm, matching of the change rate, the change gradient and the correlation result with the pipe network structure correlation, determination of the risk identification of the corresponding monitoring terminal based on the pipe section connection relationship and the flow direction information, and division of the event level based on the risk identification in the edge computing terminal. The monitoring data is processed through edge computing, so that the response timeliness, data efficiency and intelligent level of the combined overflow pipeline system monitoring are ensured.

This invention discloses a method and system for quantifying cigarette consumer preferences based on multimodal fusion, belonging to the fields of data processing and artificial intelligence technology. The method includes: collecting voice data from consumers during smoking and behavioral observation data recorded in real-time by interviewers; processing the voice data to extract text features and acoustic emotion features; structurally encoding the behavioral observation data to generate a temporal behavioral feature sequence; and inputting the multimodal features, after time alignment, into a multimodal fusion analysis model based on an attention mechanism for fusion analysis, generating and outputting a structured quantitative index of consumer preferences. The system includes corresponding functional modules for implementing the above steps. This invention solves the problems of high cost, single insight dimension, and difficulty in quantifying conclusions associated with traditional methods. It can efficiently and accurately fuse consumers' subjective speech and objective behavioral responses in natural interview scenarios, outputting quantitative preference indicators that can directly guide cigarette product development, and has significant advantages such as low cost, high feasibility, and operable results.

The application discloses an environment sensing method and device for rail transit, and the method comprises the following steps: acquiring continuous frame image information F n ; performing Gaussian filtering processing on the continuous frame image information F n to obtain initial processing image information; performing fusion operation on the initial processing image information to obtain fused image information; performing reprocessing operation on the fused image information to obtain reprocessing image information; and determining environment sensing information of rail transit based on the reprocessing image information. Through data optimization processing and detail enhancement processing on the continuous frame image collected in the rail transit process, the data analysis and processing amount in the environment sensing process is effectively reduced, the environment sensing efficiency is improved, and the accuracy of environment sensing is effectively improved.

The invention belongs to the technical field of aircraft test flight data processing, and discloses a test flight data analysis method based on a node graph, which comprises the following steps of: analyzing a processing flow of test flight data, creating a node graph of test flight data analysis, defining a name and a function of each node, and creating input and output of each node in the node graph. And compiling a test flight data processing task program of each node, constructing an execution sequence of the test flight data processing task programs based on the node graph, and completing tasks on all the nodes of the test flight data according to the execution sequence. According to the method, by creating the data processing workflow, the data processing process is easy to master, the data processing flow is standardized, in addition, in the creation process, various data processing nodes can be developed, and the nodes can be shared to others for use and can also be reserved as technology accumulation; in addition, a plurality of data processing workflows can be created in software, and the workflows are processed at the same time through a multi-thread technology, so that the data processing efficiency is improved.

The application provides a size detection device for calendering roller processing, and relates to the technical field of calendering roller size detection, so as to solve the problems of complicated distance adjustment, inflexible base installation and low detection precision caused by the lack of matching software of the existing device. The device comprises a laser transmitter and a laser receiver arranged opposite to each other, a bottom plate with a guiding groove on the top surface, a sliding assembly comprising a driving motor, and a control software system, which comprises a pattern interference removal module, a data acquisition module, a distance self-adaptive adjustment module, a multi-dimensional parameter fusion calculation module, an error compensation module and a motor control module. The sliding assembly drives the laser transmitter to automatically adjust the distance, and the bottom surface of the bottom plate can accommodate a fixed plate to adapt to multiple scenes. The control software system removes the pattern interference, calculates the outer diameter, the cylindricity and the local concave-convex degree, and compensates for the environmental and mechanical errors. The device effectively solves the problems of the existing device, has strong software and hardware adaptability, significantly improves the detection efficiency and precision, is suitable for multiple specifications of calendering rollers, is convenient to operate and has high practicability.

The application relates to a pipeline updating system based on a 'node-edge' relationship, belongs to the technical field of underground pipelines, and solves the problems that pipeline data nodes are not marked and manual updating is time-consuming and laborious when new pipeline data is added in the prior art. The updating system comprises the following units: a data acquisition unit used for acquiring added pipeline data and added folding points; a data updating unit used for dividing original pipeline segment vector data by using the added folding points to obtain new pipeline data; and a data storage unit used for storing the original pipeline data and the new pipeline data. The updating system realizes updating of the original pipeline data, provides an intelligent, efficient, replicable and generalizable pipeline updating system.

The invention discloses a protocol identification method for an electric power Internet of Things terminal, which comprises the following steps: interacting with the electric power Internet of Things terminal, acquiring protocol data in the interaction process, and carrying out data preprocessing on the protocol data to form an effective load data set; performing feature extraction on the effective load data in the effective load data set to obtain input features; inputting the input features into a power Internet of Things terminal equipment protocol classification model constructed based on a density space clustering method, carrying out learning training, and outputting a classification model after training is finished; and inputting the to-be-classified present network protocol message data subjected to data preprocessing and feature extraction into the trained classification model for classification, and outputting a classification result. The method does not depend on manual labeling any more, the influence of manual intervention and errors is reduced, the method can quickly adapt to access of new equipment and change of protocols in the dynamic environment of the power Internet of Things terminal equipment, and the stability and safety of a power system are guaranteed.

This invention provides a method, system, computer equipment, and storage medium for correcting nighttime light remote sensing data, belonging to the field of urban environmental monitoring technology. The method includes: using a multi-source remote sensing sensor to statistically analyze the impermeable and non-impermeable layers in a target area, and calculating a multi-source data consistency index (CI); using the CI to correct the impermeable layer classification results of the target area; and based on the corrected impermeable layer classification results, counting the number N of impermeable layer pixels within the target area. b Number of pixels N in impermeable layer n , using N b and N n Calculate the proportion P of the impermeable layer within a unit pixel. b Using the nighttime light remote sensing brightness value NTL and the proportion of impermeable layer per unit pixel P b A calibration model was constructed to effectively reduce light spillover interference in impermeable areas, significantly improve the accuracy of impermeable layer data, and provide high-precision data support for urban expansion monitoring, light pollution assessment, and socio-economic activity analysis.

The application relates to the technical field of power load monitoring, and particularly discloses a power load monitoring method and system based on data feedback, which comprises the following steps: S1, collecting relevant data of each working state of a charging gun, a charging gun environment and a corresponding charging vehicle in a charging station through a data collection layer; and S2, pre-processing the collected data through each edge computing layer; through comprehensive and targeted data collection and subsequent processing and analysis, the application achieves the effect of effectively monitoring the power load of the charging station; on one hand, comprehensive data collection can provide rich and accurate basic data for subsequent anomaly analysis, so that the anomaly analysis is more comprehensive and accurate; on the other hand, the layered processing mode can improve the data processing and transmission efficiency, abnormal conditions in the charging process can be found in time and a warning can be given, so that the safe and stable operation of the charging station is ensured.

The present application relates to the field of data processing, in particular to a data processing method and device, computer equipment and storage medium. The method comprises: obtaining to-be-processed data and an original data processing model corresponding to the to-be-processed data; performing compression processing on the original data processing model to generate a target data processing model; calculating the total task quantity of the target data processing model processing the to-be-processed data according to the to-be-processed data and the target data processing model; and distributing the total task quantity to multiple hardware platforms to complete the processing of the to-be-processed data. The software compression is connected to the actual hardware acceleration, and the hardware support of the software layer optimization result is realized. The time consumption and resource consumption during the inference of the original data processing model are reduced. Thus, the efficiency of data processing on the to-be-processed data is improved.