44results about How to "Reduce storage pressure" patented technology

The invention provides a memristor neural network cloud edge collaboration method and a memristor neural network cloud edge collaboration system based on multi-mode sensing. The method belongs to the field of artificial intelligence multi-modal data processing. The method mainly comprises the following steps: distributing multi-modal data subjected to synchronous acquisition and time-space alignment to an FPGA (Field Programmable Gate Array) and a memristor array for parallel processing; splicing the processed multi-modal data in a channel dimension to generate a multi-channel fusion feature tensor; a memristor array is used for carrying out storage and calculation integrated calculation on the multi-channel fusion feature tensor, and an advanced feature map is output; receiving a differential update packet issued by the cloud, and selectively updating the weight in the memristor array according to the update packet; and carrying out in-situ fine tuning on partial weights in the memristor array based on locally acquired data. According to the method and the constructed system, the memristor array can be effectively compensated, the calculation precision is improved, and rapid self-adaption of a local scene and continuous and efficient iteration of global knowledge are achieved.

The application discloses a kind of relative radiation calibration methods and systems of remote sensing image based on quantile, it is related to remote sensing image processing technical field, the method includes: collecting satellite historical image data and separating according to spectral band;The value of each column of single-band image detector is sequentially arranged in ascending order, and quantile value is uniformly extracted to generate the quantile feature sequence of each column;The arithmetic mean value of all columns under the same quantile level is calculated, and the global reference quantile distribution is constructed;Based on least square method, the linear mapping relationship between each column quantile sequence and reference distribution is constructed, and the radiation correction gain and bias coefficient of each detector column are obtained;The original image is corrected column by column using the coefficient;The present application effectively eliminates the vertical strip noise caused by the non-uniformity of sensor response, overcomes the limitations of traditional calibration under the meteorological conditions and platform maneuvering, significantly improves the timeliness and image radiation quality of high-frequency and high-precision calibration.

The present application relates to solid waste recycling technical field, provide a kind of based on coal-based solid waste's anti-dispersion grouting material and its preparation method and application, the material is made of coal gangue, fly ash, silica ash, cellulose, water reducing agent and alkali activator, wherein, alkali activator is made of deionized water, sodium hydroxide and water glass.The based on coal-based solid waste's anti-dispersion grouting material is prepared according to following steps: after mixing coal gangue, fly ash, silica ash, cellulose and water reducing agent, stirring treatment is carried out, and powder precursor is prepared;Alkali activator is added to the prepared powder precursor, and alkali activator is made of deionized water, sodium hydroxide and water glass, continue to stir to prepare the based on coal-based solid waste's anti-dispersion grouting material.The present application can prepare the anti-dispersion grouting material of excellent fluidity, stability and mechanical property, provides innovative path for the resource of coal-based solid waste, significantly reduces material cost, improves environmental benefits and engineering application value.

The application relates to the technical field of automatic control of unmanned aerial vehicles, in particular to a control system of an unmanned aerial vehicle, which comprises a bus, a self-pilot, a plurality of rudder controllers and a plurality of rudder surface driving mechanisms, the self-pilot and each rudder controller are connected to the bus, each rudder controller is electrically connected with the corresponding rudder surface driving mechanism; each rudder controller is provided with a control distribution table mapped with a flight configuration; during the flight of the unmanned aerial vehicle, each rudder controller determines the corresponding control distribution table according to the flight configuration broadcast by the self-pilot; according to the control distribution table, the weight of each control signal participating in control is determined, and the total control signal is obtained by weighted summation of each control signal participating in control; each rudder controller outputs the total control signal to the corresponding rudder surface driving mechanism to realize the control of the rudder surface driving mechanism. That is, the application scheme can relieve the operation and storage pressure of the self-pilot, simplify the configuration of the self-pilot and improve the universality of the self-pilot.

This invention discloses a device type identification method, terminal device, and storage medium based on traffic sampling. It eliminates the need to collect complete device traffic data; device identification is achieved simply by sampling traffic at the gateway. To address the issue of missing traffic features, traditional tensor imputation algorithms learn the embeddings corresponding to tensor rows, columns, and depths, but cannot generalize to unknown rows, columns, or depths. This results in repeated retraining, time-consuming and costly feature imputation. This invention proposes an inductive tensor imputation method that utilizes historical information to learn and generate embedding functions, enabling fast and effective device traffic feature imputation.

The application discloses a kind of alliance chain slice construction and consensus method based on dynamic clustering, comprising, the real-time computing power of alliance chain node, transaction frequency and transmission rate are collected;By verifiable random function, node is divided into Full_node of storing complete data and Slice_node of only storing slice data;DQN algorithm is used to determine the number of slices K, and the final consensus group is formed by selecting consensus representative nodes from Full_node based on dynamic performance threshold;The correlation matrix between the remaining nodes is constructed, and the nodes are evenly distributed to K slices by means of improved clustering algorithm;In each slice and consensus group, the Leader node is elected;When a new transaction arrives, execute the corresponding consensus process according to whether the transaction parties belong to the same slice, and write into the blockchain after verification, collect consensus performance data by Leader, and determine whether to trigger slice reconstruction according to performance data: if triggered, re-slice, otherwise continue to process transactions until completion;The application can improve the throughput of the overall system, relieve the data storage pressure, and improve the system response efficiency.

The application relates to the field of robot control, in particular to a multi-modal perception pipeline inspection robot control method and an inspection robot. The method comprises the following steps: based on the inspection robot, pipeline detection perception is carried out, and a real-time three-dimensional structure map is generated; the real-time three-dimensional structure map is compressed and uploaded to a cloud monitoring platform; when the cloud monitoring platform receives the real-time three-dimensional structure map, spatial topology analysis is carried out, an inspection instruction is generated, and the inspection instruction is sent to the pipeline internal inspection robot; the internal inspection robot receives the inspection instruction, carries out adaptive path planning, and generates a path execution sequence; the inspection robot carries out dynamic inspection operation based on the path execution sequence, synchronously collects data and returns the data to the cloud monitoring platform, and completes the inspection control operation. The application realizes high-precision and automatic buried oil pipeline inspection operation, and improves the detection efficiency and safety of the buried oil pipeline.

The invention relates to the technical field of data processing, in particular to a multi-dimensional automobile accessory big data processing method and system based on a vertical class model, and the method comprises the steps: obtaining multi-dimensional data information of automobile accessories at regular time; according to key text information in the multi-dimensional data information, constructing a text feature vector of the automobile accessory; determining a first similarity between each attribute of each automobile accessory and the automobile accessory with the same name; obtaining the attribute importance degree of each attribute of each automobile accessory; based on a vertical class model, evaluating the similarity degree of the text feature vectors between any two automobile accessories obtained in a single time, and classifying the automobile accessories; and determining a first similarity between each attribute of any automobile accessory in the same kind of automobile accessories and the remaining automobile accessories, and calculating the automobile accessory similarity between the any automobile accessory and the remaining automobile accessories by combining the attribute importance of each attribute of the any automobile accessory so as to perform duplicate removal processing on the same kind of automobile accessories. Therefore, the duplicate removal effect of the automobile accessory data is improved.

The application relates to the technical field of satellite working medium cryogenic storage, in particular to a satellite propellant working medium solid-state storage and partitioned phase change supply device and a manufacturing method thereof.The device comprises a storage box shell, a storage box cover plate, a heat exchange assembly, a storage box liquid port, a storage box gas port, a refrigerator interface, an electric connector and a flowmeter, wherein the storage box shell is in sealed connection with the storage box cover plate to form a closed working medium storage space; the heat exchange assembly is arranged in the interior of the storage box shell; the storage box liquid port and the storage box gas port are arranged on the storage box cover plate; the refrigerator interface is arranged on the storage box shell; the electric connector is arranged on the storage box shell; and the flowmeter is connected with the storage box gas port.The application adopts solid working medium storage, the storage pressure is low, is suitable for the storage box structure design of special-shaped space layout, enhances the flexibility of the structure and layout design of a satellite propulsion system, improves the space occupation ratio of the working medium storage box, and provides additional space for satellite load configuration.

The application provides a mixture spectral component identification method and system under an edge computing architecture, and relates to the technical field of intelligent identification. The method comprises the following steps: in a cloud server, based on a standard spectral library and historical sample data, a candidate component spectral set is obtained by using a sparse regression method; the candidate component spectral set is downloaded to an edge computing node and stored locally to construct an edge spectral sub-library; after the edge computing node receives spectral data of a to-be-detected mixed sample, the edge spectral sub-library is linearly combined and solved based on a non-negative least square algorithm to obtain non-negative weight coefficients of each component; and the component composition in the to-be-detected mixed sample and the proportion of each component are determined according to the non-negative weight coefficients. Through edge-cloud cooperation, the application reduces the computing load of the edge end under the premise of ensuring the identification accuracy, meets the on-site real-time detection demand, avoids the negative weight problem, and improves the physical rationality of the result.

This application discloses a meter reading method based on smart meters, comprising the following steps: Step 1: The server presets a unit electricity consumption and presets an identification code for each smart meter under the server's jurisdiction, then sends the identification code and unit electricity consumption corresponding to each smart meter; Step 2: The smart meter receives the unit electricity consumption and identification code sent by the server to determine the recorded value. The smart meter monitors the electricity consumption in real time, and sends its own identification code to the server each time the accumulated electricity consumption of the smart meter reaches the recorded value. This application provides a smart meter-based meter reading method that can reduce the long time occupied between the meter and the server during meter reading, and also reduces the problem of the meter sending duplicate information to the server.

The invention belongs to the technical field of nuclear power, and particularly relates to a thrust bearing early abnormal state recognition method and device. Through a strategy of storing characteristics in a normal state and additionally storing original data in an abnormal state, on the premise of ensuring that key information is not lost, the storage pressure brought by massive acoustic emission data is greatly relieved, and the system deployment and operation and maintenance cost is reduced. According to the method, a complete closed loop including initial verification, benchmark establishment, real-time monitoring, intelligent diagnosis, data retention and the like is constructed. Through comprehensive analysis of four key features of high-frequency, intermediate-frequency and low-frequency energy and a bottom noise effective value, fault types such as poor lubrication and overload can be preliminarily distinguished, and a more accurate basis is provided for maintenance decision.

This invention relates to the field of medical information security technology, and discloses a blockchain-based method and system for auditing and detecting unauthorized access to medical data. The method includes: structurally modeling medical data access behavior to construct access behavior feature vectors; performing multi-source fusion risk assessment based on an access control policy model and a behavior learning model to obtain a comprehensive risk value; executing a graded processing strategy according to the risk level and generating corresponding audit logs; structurally organizing the audit logs and constructing a Merkle tree to generate data fingerprints; writing the data fingerprints and summary information into the main chain, storing the complete audit logs in a side chain or off-chain storage, and achieving consistency verification through Merkle proofs; using smart contracts to verify the audit data and automatically execute access control responses, while simultaneously feeding back the audit results for model updates. This invention enables real-time detection, graded processing, and trusted auditing of medical data access behavior.

This invention provides a slope protection material composed of recycled heavy metal tailings and its preparation method. The material includes: recycled heavy metal tailings treated with a heavy metal chelating agent as a heavy metal ion capture agent, the chelating agent being added at 0.05%–0.2% of the heavy metal tailings weight; recycled heavy metal tailings as aggregate, which is mixed with natural soil to form a base material at a ratio of 1:1.5–2.5; fine aggregate and fine sand, added at 5%–10% of the base material weight; and high-viscosity industrial-grade sodium alginate added as a water-retaining and reinforcing agent, added at 0.5%–2.0% of the base material weight. Additionally, 28% organic matter is added to the base material. The application of this invention effectively solves the problems of ineffective utilization of recycled heavy metal tailings and excessive use of scarce natural soil in existing technologies, and also addresses the issues of weak strength, poor effectiveness in steep slope treatment, and poor stability in existing slope protection materials.

This invention relates to a method for the resource recovery of rare earth, thorium, and iron from iron-thorium slag. The method includes the following steps: (1) finely grinding the iron-thorium slag; (2) uniformly mixing the finely ground iron-thorium slag with reducing carbon powder, and then roasting them together in a muffle furnace to obtain roasted slag; (3) mixing the roasted slag with alkaline solution and then placing it in a sealed container for high-temperature alkaline conversion reaction to obtain alkaline conversion slag; (4) washing the alkaline conversion slag with water to remove fluoride and aluminum, and then filtering and drying it to obtain water-washed slag; (5) subjecting the water-washed slag to acid dissolution reaction, and after separation, obtaining a thorium-containing rare earth solution and an acid-leached slag respectively; (6) after deep impurity removal, transferring the thorium-containing rare earth solution to an extraction system to separate and purify rare earth and thorium elements. This invention solidifies most of the iron in the iron-thorium slag in the form of goethite through high-temperature roasting, avoiding the loss of rare earth caused by the subsequent leaching process, and has the advantages of high rare earth recovery rate, low slag rate, and low auxiliary material consumption.

The invention provides a visualization method and system for self-adaptive matching of a display object resolution and a fusion processing mode. The method provided by the invention comprises the following steps: before to-be-displayed content reaches a video physical port of a visualization system, determining a display template according to a plurality of to-be-controlled visualization system display sizes; selecting a target visualization system according to the content density of the to-be-displayed content; determining a display object type in the to-be-displayed content, determining a fusion processing mode of the display object according to the display object type, determining a fused display position of each display object according to the display scene, supplementing a display template corresponding to the target visualization system, and obtaining a target display template; different types of display objects are obtained by utilizing a video physical port, each display object is processed by utilizing a video processor according to a fusion processing mode of each display object, and a plurality of processed to-be-fused display objects are displayed in the same canvas according to a fused display position in a target display template to obtain a fused canvas; and displaying in the target visualization system.

The application discloses a data migration method, comprising: monitoring bandwidth of an enterprise disk and nearline storage media, obtaining a first bandwidth of the enterprise disk and a second bandwidth of the nearline storage media; determining non-hot data in the enterprise disk when the first bandwidth exceeds a first preset threshold and the second bandwidth is lower than a second preset threshold; and migrating the non-hot data to the nearline storage media. The application has the technical effect that part of the non-hot data in the enterprise disk is migrated to the nearline storage media with lower performance based on the bandwidth parameter, so as to reduce the storage pressure of the enterprise disk, fully exert the storage performance of the nearline storage media, effectively improve the storage performance of the storage system, and realize stable storage of data information. The application also discloses a data migration device, an electronic device and a computer readable storage medium, which have the above technical effect.

The application provides a power equipment state monitoring and fault diagnosis system based on multi-modal data, relates to the field of data processing, and comprises a data acquisition module, an acoustic array, an image acquisition device and an infrared thermal induction device, wherein the acoustic array comprises sound acquisition devices arranged at multiple positions on the power equipment; a state monitoring module is used for determining abnormal sound coordinates according to sound data collected by the acoustic array; the data acquisition module is further used for controlling the image acquisition device to collect images and controlling the infrared thermal induction device to collect infrared thermal induction data based on the abnormal sound coordinates; and a fault diagnosis module is used for performing fault diagnosis based on sound data collected by the acoustic array, images collected by the image acquisition device and infrared thermal induction data collected by the infrared thermal induction device, so that the efficiency and accuracy of power equipment state monitoring and fault diagnosis are improved.

The application relates to the technical field of computer application, in particular to a list quota hanging and batch checking and modifying method based on a graphic element in a calculation software, which comprises the following steps: constructing an engineering model in the calculation software and selecting a graphic element; executing a graphic element automatic matching command based on the selected graphic element, completing matching and hanging of the graphic element and the list quota; quickly positioning and batch checking the graphic element whose matching and hanging of the list quota are completed; executing batch modification operation on the graphic element found in the checking result; and summarizing the list quota hung by the graphic element and exporting data to a pricing software. The application can improve the accuracy of list quota hanging and the checking efficiency.

The application provides a data format conversion method of an Internet of Things sensor, a gateway and a communication device, and the method comprises the following steps: receiving data transmitted by a sensor based on a transmission protocol, analyzing identification information of a protocol layer of the data, wherein the identification information is related to a sensor device manufacturer code and a device type code; identifying whether the identification information is a default value; when it is identified that the identification information is not the default value, obtaining a data format conversion protocol corresponding to the identification information; and performing format conversion on the data according to the data format conversion protocol. Compared with traditional device ID binding and mac address binding, the application does not require a device ID and a mac address, but only requires a sensor device manufacturer information and a device type, thereby greatly reducing the dependence on a sensor device manufacturer and reducing the data storage and processing pressure of a platform.

The application discloses a gas storage system, in particular to a gas storage system for compressed air energy storage power station and a construction method thereof, and belongs to the technical field of design and construction of energy storage power station gas storage building. The application provides a gas storage system for compressed air energy storage power station and a construction method thereof, which can significantly reduce the sealing requirement of equipment and the stress of the structure of the gas sealing layer. The gas storage system comprises a gas storage body and a constant temperature and pressure adjusting and maintaining mechanism, the inner cavity of the constant temperature and pressure adjusting and maintaining mechanism is connected with the inner cavity of the gas storage body, and the gas pressure and temperature stored in the gas storage body are always maintained within the specified pressure and temperature variation range under the regulation and control of the delivery and regulation medium of the constant temperature and pressure adjusting and maintaining mechanism. The construction method comprises the following steps: firstly, excavating the surrounding rock base reservoir, then grouting and reinforcing, constructing the waterproof layer, installing the water supplement pipe, the drainage pipe, the flower pipe and the corrugated steel lining layer, and finally pouring the flexible concrete lining layer and backfilling and grouting.

This invention relates to a training method, system, and readable storage medium for streaming image semantic segmentation models, belonging to the field of image segmentation technology. The training method includes dividing a streaming dataset into multiple data subsets based on a streaming data partitioning strategy; training multiple image semantic segmentation models based on each data subset; wherein each data subset corresponds one-to-one with an image semantic segmentation model, and each image semantic segmentation model has a identifiable category used to identify the data category of the corresponding streaming data; integrating the multiple image semantic segmentation models into a final segmentation model based on the identifiable categories of the image semantic segmentation models and their dynamic voting weights; the final segmentation model identifies the data category of the input streaming data and performs semantic segmentation according to the dynamic voting weights of the image semantic segmentation models. This invention can improve the segmentation performance of streaming image semantic segmentation models using minimal storage and training resources.

The application provides a data hierarchical storage evidence method, a data encoding method, a device, equipment, a medium and a product, comprising: receiving a storage evidence request submitted by a data owner, the request carrying a data digest, data fragments, a timestamp and a data signature generated based on to-be-stored data, obtaining the access heat of each data fragment, dividing the data fragments into hot data fragments and cold data fragments according to the access heat, and respectively storing the hot data fragments and the cold data fragments into high-performance storage nodes and cold data storage nodes; calculating the hash values of the data fragments, constructing a Merkle tree based on the hash values and determining the root node hash value, storing the data digest, the timestamp, the data signature and the root hash value as storage evidence metadata into a main chain; and when a fragment verification request of a data access requester is responded, performing integrity check on the data fragments based on the storage evidence metadata on the main chain. Thus, under the premise of ensuring data tamper resistance and completeness, the storage efficiency, access performance and scalability of the data are significantly improved.

The invention relates to an intelligent terminal decentralized data storage and calling method and system and a storage medium, and the method comprises the steps: enabling a cloud data center to divide total data into a plurality of logic data fragments, distributing a main storage region, and generating and maintaining a general table key rule library; issuing the data items to the regional monitoring equipment; the method comprises the following steps: storing data items in an intelligent terminal through regional monitoring equipment, recording a mapping relationship between data item identifiers and intelligent terminal addresses storing the data items, and forming and maintaining a metadata index table; when the first intelligent terminal obtains target data, a query request is sent to the area monitoring equipment of the area; querying the metadata index table through the region monitoring equipment, determining an address of a second intelligent terminal storing the target data, and returning the address; and establishing point-to-point connection with the second intelligent terminal based on the returned address to obtain target data. The cloud storage pressure is reduced, the data access efficiency is improved, and the system reliability is enhanced.

The application provides a brain-computer interface data acquisition and analysis method, system and sensing device, and belongs to the technical field of data processing. Specifically, brain-computer interface data of a target terminal when the target terminal is combined with an associated sleep monitoring device to verify a sleep state is acquired as feature data, deviation of the brain-computer interface data of the target terminal and the feature data and acquisition data of the brain-computer interface data are obtained, when forgetting processing of the brain-computer interface data is required, forgetting management methods of the brain-computer interface data of different target terminals are determined according to model recognition deviation of different target terminals in a target period, and the demand for storage space in a cloud platform is reduced.

This disclosure discloses an online monitoring method for high-voltage circuit breakers, comprising the following steps: S100: constructing a data warehouse; S200: using the constructed data warehouse as a training set to train a high-voltage circuit breaker fault diagnosis model to obtain a trained high-voltage circuit breaker fault diagnosis model; S300: continuously collecting real-time operating data of the high-voltage circuit breaker under test and expanding it into the data warehouse, and continuously performing online training on the trained high-voltage circuit breaker fault diagnosis model based on the real-time operating data to iteratively optimize the model.

This invention provides a method and system for redundant data processing and transmission in FPGA-ROS, relating to the field of robot operating system communication. The method executes input and output processing flows in parallel within the FPGA: in the input flow, newly received ROS topics are compared with historical topics; if the content differs, it is stored in main memory; otherwise, it is discarded. In the output flow, topics are read from main memory and sent according to a preset mode. In the non-timing mode, a second comparison is performed before transmission to filter redundancy, and topics oriented towards the executor can be translated into instruction format. This invention implements dual redundancy filtering and instruction conversion in hardware, significantly reducing storage and bandwidth overhead and improving system processing efficiency and compatibility.

This invention discloses an on-chain collaborative assessment method for electricity consumption anomalies, relating to the field of power data processing technology. Specifically, it includes: acquiring multiple sources of electricity consumption anomaly clue data and converting them into unified event records; forming an anomaly assessment set by associating them with the target electricity user and the time period of occurrence; extracting on-chain summaries and generating off-chain indexes; writing the summaries and indexes into the blockchain ledger and storing the clue data in off-chain space; generating collaborative assessment tasks based on smart contracts and distributing the content to be verified according to verification permissions; after receiving verification information, performing consistency checks based on the on-chain summary, the target electricity user, and the clue time sequence; generating a review instruction when conflicts exist; and generating an assessment result when the source, quantity, and time sequence conditions are met; binding the assessment result to the anomaly assessment set, generating a trusted traceability link, and outputting the assessment formation process upon a traceability request. This invention improves the reliability of clue merging, verification review, and traceability.

This utility model belongs to the technical field of seeder accessories, specifically referring to an adjustable frame structure for a seeder. It includes a left support frame and a right support frame, with a front connecting rod and a rear connecting rod detachably connected between the left and right support frames. Each end of the front connecting rod has a connecting plate. The left and right support frames have fixing plates that cooperate with the connecting plates. The connecting plates and fixing plates are detachably connected via a connector. Locking sleeves are located at the bottom of both ends of the rear connecting rod, mounted on the left and right support frames and detachably connected via a connector. The purpose of this utility model is to provide a simple adjustable frame structure for a seeder that reduces warehouse storage pressure.

The invention discloses a real-time prediction method for low-storage environment monitoring time sequence flow data, and belongs to the field of environment monitoring and pollution early warning, and the method comprises the steps: S1, collecting environment monitoring data, carrying out the preprocessing, dividing the data into independent batches, and taking the target pollutant concentration as a response variable; s2, constructing an autoregression error model, integrating regression and autoregression parameters, and configuring optimization parameters; s3, initializing parameters based on a renewable estimation framework, calculating historical summary statistics, alternately updating the parameters, synchronously screening key factors, determining a time sequence dependence order, performing loop optimization and releasing an original data memory; and S4, outputting the optimal parameter verification performance and predicting the concentration. By the adoption of the method, full-amount original data does not need to be reserved, real-time model updating is achieved through the current data and historical key statistical information, the storage pressure is reduced, the prediction precision is improved, and the requirements for environment monitoring and pollution real-time early warning are effectively met.