17results about How to "Reduce storage footprint" patented technology

This invention relates to the field of smart agriculture information technology, and discloses an agricultural pest and disease prediction system and method based on multimodal data fusion and edge AI, comprising: a data acquisition module, an edge AI analysis module, and a communication interaction module; the data acquisition module is used to collect agricultural monitoring data containing agricultural environmental information and crop status information; the edge AI analysis module is used to call a pest and disease prediction model that integrates multimodal agricultural feature extraction to perform multimodal joint feature extraction on the agricultural monitoring data containing agricultural environmental information and crop status information, and infer pest and disease prediction results based on the multimodal joint features, and generate pest and disease early warning information based on the pest and disease prediction results; the communication interaction module is used to upload the agricultural monitoring data collected by the data acquisition module and the pest and disease prediction results and pest and disease early warning information output by the edge AI analysis module to a cloud platform. This invention enables agricultural pest and disease prediction on resource-constrained edge devices.

This application discloses a data-processing-based intelligent management method and system for thermal power fuel, comprising the following steps: collecting multi-dimensional data of the entire life cycle of thermal power fuel; cleaning, standardizing, and fusing the collected multi-dimensional data to obtain pre-processed fuel data; constructing a multi-dimensional analysis model to analyze the pre-processed fuel data, comparing the analysis results with preset condition information, generating procurement adjustment instructions, inventory scheduling instructions, coal blending execution instructions, and equipment operation and maintenance early warning instructions, and pushing the instructions to the corresponding execution terminals, collecting feedback data in real time during the instruction execution process; obtaining instruction execution status data based on the feedback data, visualizing the instruction execution status data, fuel data, and analysis results, and generating multi-dimensional statistical reports; this invention establishes a unified data collection and integration mechanism, breaks down data barriers at each stage, and forms a complete data link for the entire fuel life cycle.

The invention discloses a lightning arrester instrument data image recognition method, system and device and a medium, and the method comprises the steps: obtaining an original image of a lightning arrester instrument, adaptively adjusting collection parameters according to environment illumination, carrying out the geometric correction and quality evaluation, carrying out the dynamic contrast enhancement and multi-scale noise suppression through an illumination decoupling model, and generating a standardized image; inputting a lightweight mobile terminal target detection model, and positioning and cutting an instrument display area; enhancing the sub-images, extracting edge features, and judging the type of the instrument: if the sub-images are digital, segmenting character areas and identifying the character areas by using a private network to obtain initial readings; verifying validity in combination with a preset physical quantity reasonable range, and generating a final reading; and automatically associating a current inspection task, adding time, a position and an image index, storing into a local database through transaction operation, and supporting generation of a structured inspection report. According to the invention, the accuracy and efficiency of inspection work are improved, and the reliability and traceability of data are ensured.

The application relates to a vehicle cabin resource adaptation method and a vehicle. The method comprises the following steps: acquiring a navigation path of the vehicle, and determining at least one intersection point where the navigation path intersects with the region boundary in a geographic fence; for any intersection point, acquiring the current position of the vehicle, determining a preloading trigger parameter according to the current position of the vehicle; when the preloading trigger parameter meets a preset preloading trigger threshold, preloading a compliance adaptation resource package of a target region corresponding to the intersection point; and adapting the vehicle cabin resource according to the compliance adaptation resource package. In this way, only the required region resource of the vehicle is loaded instead of preloading all resources, the storage occupation of the vehicle machine is reduced, the system operation efficiency is improved, the cabin resource adaptation can be automatically completed without manual operation of the user, the use experience is optimized, cross-region compliance adaptation is realized, and the compliance risk of cross-border driving of the vehicle is effectively avoided.

The application discloses an image processing method, which comprises the following steps: determining a quality level corresponding to a first image based on at least a network state parameter and a task demand parameter, wherein the task demand parameter at least comprises a task type; encoding the first image based on the first image and the quality level corresponding to the first image; decoding a received first code stream to generate a second image, wherein the first image is encoded and decoded by a shared variable code rate reversible image codec, and the first code stream at least comprises a task type identifier corresponding to the task type; and inputting the second image into a visual feature reconstruction network to output a perception optimization reconstruction image and / or a task adaptation reconstruction image. The image processing method of the application greatly reduces the storage occupation and model maintenance cost in the image processing process, improves the flexibility and scalability of the image processing method, and can output a reconstruction image meeting the actual scene demand and having high quality.

The present application belongs to the technical field of knowledge compilation and network reliability analysis, and particularly relates to a network reliability intelligent computing method and system for a logical decision graph, comprising: modeling a network system as a triple data structure composed of a network topology graph, a terminal node set and an edge availability probability set; determining a topology order of network nodes and network edges based on the triple data structure; constructing a full binary tree vtree with leaf nodes corresponding to network edges one by one according to the topology order; and compiling the network topology graph into a zero-suppression statement logical decision graph using the vtree, wherein the zero-suppression statement logical decision graph is used to represent a set of valid subgraphs that satisfy terminal node connectivity; and recursively calculating a reliability value of the network system based on the zero-suppression statement logical decision graph.

This specification provides a unified indexing method, apparatus, electronic device, and medium for multiple metric vectors. The method includes: in the index creation phase, constructing a shared graph topology structure decoupled from similarity metrics; in the query execution phase, enabling the query optimizer to generate an execution plan containing a single index scan node and generating a corresponding metric type identifier; performing graph traversal based on the shared graph topology structure, and if no match is found, calling the underlying calculation kernel function corresponding to the target similarity metric type to perform lazy distance calculation and writing it into a shared memory cache pool; dynamically adjusting the pruning threshold and search width parameters of the graph traversal, continuing to traverse the shared graph topology structure until the termination condition is met, and outputting the final candidate node set; and returning the final candidate node set and its corresponding distance values ​​to the query executor layer of the database system through the index scan callback interface in the custom index access method plugin, and outputting the final query result set.

This invention discloses a hierarchical retrieval method, apparatus, device, storage medium, and product for encrypted data. The method includes: when a query statement indicates a retrieval of encrypted data, requesting a distributed cache node to perform a first-level cache retrieval based on the query keywords in the query statement; if the first-level cache retrieval query fails, parsing and constructing an encrypted index query value from the query keywords in the query statement; performing a second-level encrypted retrieval based on the encrypted index query value to obtain a second-level encrypted retrieval result for the encrypted data; and caching the second-level encrypted retrieval result in a distributed cache for retrieval filtering to obtain the final retrieval result. This invention, by introducing a second-level retrieval mechanism, can effectively improve the accuracy of data retrieval. Furthermore, by introducing an encrypted index query value to achieve encrypted retrieval in the second-level encrypted retrieval, it can effectively improve data retrieval efficiency and reduce storage usage during the data retrieval process.

The invention discloses a method and system for reducing KV storage and loading expenditure in a retrieval enhancement generation system, and the method comprises the steps: S1, compressing a key value cache block of a pre-calculated external document to reduce the storage and loading expenditure of the key value cache block; s2, when the requested key value cache block does not hit the cache, searching and replacing the key value cache block with similar semantics in the cache according to the similarity of retrieval results; and S3, performing comprehensive value evaluation on the key value cache blocks in the cache based on the frequency, the recency and the first retrieval score, and executing cache replacement according to an evaluation result to maximize a cache hit rate. Through an innovative two-stage compression technology, storage occupation and data loading overhead of mass external document pre-calculation key value cache are remarkably reduced. Based on a key value cache reuse strategy of semantic similarity, high-delay disk input / output access is converted into rapid memory access, and the performance bottleneck of data loading is effectively relieved.

The application discloses a temperature and humidity monitoring system and relates to the technical field of temperature and humidity control.The system comprises an intelligent device configuration module, a distributed real-time sensing module, a time series data tracing module, an adaptive intelligent export module and a multi-dimensional dynamic early warning module.The intelligent device configuration module generates device configuration data.The distributed real-time sensing module constructs a dynamic monitoring panel on a UI interface.The time series data tracing module models the historical data of a target detector in a time series and generates an interactive trend curve.The adaptive intelligent export module converts the full data of a corresponding detector into an OFFICE compatible format.The multi-dimensional dynamic early warning module receives real-time data from the distributed real-time sensing module and historical trend data from the time series data tracing module, compares the real-time data with the historical trend data through real-time threshold comparison and trend prediction analysis, and comprehensively generates multi-level early warning signals.The application realizes flexible device configuration, edge computing and dynamic sampling through self-defined port mapping and elastic expansion, improves data sensing accuracy, time series modeling and intelligent labeling, and breaks through the limitations of traditional systems, such as fragmented functions, complex operation and slow response.

The application discloses a pinyin decoding method and related equipment, and relates to the technical field of natural language processing. The application first acquires a first text sequence containing a historical input text sequence and a current to-be-decoded pinyin string, and extracts semantic features corresponding to the text sequence by using a neural network model; then, corresponding statistical information is acquired by relying on a statistical language model. The statistical language model can store various types of text static statistical information, including candidate word entries and corresponding probability information, and the statistical information is mapped to a feature space consistent with the semantic features to obtain statistical features. The semantic features and the statistical features are fused to obtain fused semantic features, and a decoding result corresponding to the pinyin string is generated according to the fused semantic features. The application combines the semantic understanding ability of the neural network and the prior statistical advantage of the statistical language model, and takes into account the decoding accuracy and the use stability, is efficient in reasoning, and is suitable for various input method use scenarios.

This utility model discloses a lifting platform suitable for yachts, including a hull, a stern fixedly connected to the deck, a lifting platform on the stern, a limiting groove on the side of the stern, the lifting platform being fixedly connected to the limiting block, a sliding groove on the bottom surface of the lifting platform, a slider inside the sliding groove, a telescopic rod fixedly installed on the deck, the upper surface of the deck being fixedly connected to a side plate, a pedal on the side of the side plate, the pedal being hinged to one end of a connecting plate, and the pedal being movably hinged to a connecting plate, and a second telescopic rod fixedly installed on the side of the side plate. This utility model uses the first telescopic rod to move the slider inside the sliding groove, pushing the lifting platform to rise and fall, achieving convenient lifting and falling of the platform, reducing the difficulty for users to move landing craft onto the yacht. The second telescopic rod pushes the pedal to extend outwards, facilitating user contact with the water surface from the pedal, improving the yacht's recreational experience. Simultaneously, the pedal can be retracted for storage, reducing the space occupied during storage.

The application relates to a preparation method and application of a steel fiber reinforced graphite tailing cement-based composite filling material, and relates to the technical field of coal mine goaf foundation repair. A screening-impurity removal-drying combined process is adopted to obtain graphite tailing particles; in the critical range of 15%-20% of the graphite tailing content, each component is weighed according to the proportion, including steel fiber, cement, graphite tailing and mixing water, and a water reducing agent is selected according to the requirement; the steel fiber, the cement and the graphite tailing are mixed until the materials are uniformly mixed; the mixing water is added twice, the water reducing agent is pre-dissolved at the second time, and wet mixing is performed until a uniform slurry is obtained; after stirring is completed, the slurry fluidity is detected by using an expansion degree method, and the expansion degree is ensured to be 200-250 mm. The critical content range of the graphite tailing is determined, the mechanical properties-water cement ratio-water permeability performance of the composite filling material are synergistically optimal, the grouting fluidity and the late strength development are considered, and the performance requirement of the coal mine goaf foundation repair is met.

The invention provides a video content intelligent analysis method based on an edge computing platform, and the method comprises the steps: collecting a video stream through an image collection interface of the edge computing platform, and carrying out the preprocessing of a video frame at a CPU end, and obtaining standardized image data; the method comprises the following steps: converting a pre-trained neural network model into a special format model adaptive to an NPU (Network Processing Unit), and adopting a hierarchical quantization strategy in the conversion process: quantizing at least one network layer responsible for basic feature extraction in the model by adopting first numerical value precision, quantizing other network layers responsible for classification and regression in the model by adopting second numerical value precision lower than the first numerical value precision; dynamically scheduling the number of processing cores in an activated state in the NPU based on a processing load determined by analyzing the current video frame content represented by the standardized image data, and utilizing the processing cores in the activated state to load a special format model to infer the standardized image data; and post-processing the reasoning output result of the NPU to generate a structured analysis result.

The invention discloses a 3D car model dynamic generation system and method based on configuration word driving and a car, and belongs to the technical field of car cabin man-machine interaction, and the system comprises a configuration word generation module which is used for generating a production configuration word instruction set containing a unique identifier of vehicle basic configuration according to vehicle order configuration information, writing into a vehicle domain controller; the modular model library is used for storing vehicle body basic components with unique IDs; the configuration word analysis module is used for reading a configuration word instruction set in the vehicle domain controller, performing configuration mapping according to the configuration word instruction set, and analyzing the configuration word instruction set into a 3D vehicle model part ID instruction set of the current vehicle in combination with a preset rule; and the rendering display module is used for calling and loading the corresponding 3D car model component according to the 3D car model component ID instruction set of the current car, and displaying the 3D car model on a cabin display screen after real-time rendering. According to the method, automatic mapping from the vehicle type configuration parameters to the visual model can be realized, and the dynamic rendering requirement is met.

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

The invention relates to an energy storage battery health state monitoring management method and system. The method comprises the following steps: constructing a multi-dimensional physical characteristic tensor according to charging and discharging data of a battery; establishing a KAN network fused with a physical model, inputting the multi-dimensional physical feature tensor into the KAN network for joint pre-training, and updating spline coefficients in the KAN network and physical parameters in the physical model; performing first-order Taylor expansion on the spline coefficient based on a total loss function of joint pre-training, and calculating the physical sensitivity of each connection in the KAN; performing structure pruning on the KAN network according to the physical sensitivity, and screening effective input features in the multi-dimensional physical feature tensor according to a structure pruning result; subspace fine tuning is carried out on the KAN network after structure pruning, a sparse neural network model used for battery health state estimation is obtained, and the neural network model training method and the battery management system achieve deployment of the neural network model containing physical constraints in a BMS hardware resource limited scene.