38 results about "Chain code" patented technology

The invention relates to the field of industrial metering, and discloses a data-driven belt weigher intelligent calibration method and system, and the method comprises the steps: when a calibration command is triggered, collecting real-time data to form a feature vector input model, calculating and predicting a calibration coefficient and zero offset, writing the calibration coefficient and zero offset into a metering instrument to complete calibration, carrying out the importance analysis and screening of feature variables, and obtaining a calibration result. Optimizing model parameters; and performing rationality verification and adaptive adjustment on the prediction parameters, generating a calibration report, and adding data to a historical library. According to the method, a data-driven artificial intelligence model which is fully trained and can deeply reproduce the internal rule of the physical calibration process is used for replacing the traditional physical chain code calibration operation which is time-consuming and labor-consuming and possibly causes danger. Through historical data learning, the mapping relation between the operation states of the belt weigher under various working conditions and environments and the calibration parameters of the belt weigher is established, so that non-contact, high-efficiency and intelligent automatic calibration is realized.

The invention discloses a power transmission line icing thickness detection method and system based on deep learning, and relates to the technical field of image processing and power transmission line online detection, and the method comprises the steps: collecting an icing image of a power transmission line through a standardized dual-light optical device, and carrying out the image preprocessing, and generating an original data set; and performing image segmentation on the original data set, training the deep neural network model by using the lightweight YOLACT network, and performing evaluation. Edge detection is carried out through a multi-direction Sobel operator template, an Otsu method is adopted for binarization processing and nonlinear operator filtering denoising, a boundary chain code array is extracted based on a boundary tracking algorithm of a topological structure, and the MASK of an original power transmission line is determined. And acquiring an image of the power transmission line by using a dual-light camera, performing camera calibration, performing registration and fusion on the calibrated image, and outputting a calculation result of the icing thickness of the power transmission line by using the trained neural network. According to the invention, the detection precision and efficiency are improved, and the thickness estimation deviation caused by image errors is reduced.

The invention discloses a supply chain full-process traceability tracking method based on a block chain, and relates to the technical field of block chain and supply chain traceability, and the method comprises the specific steps: collecting supply chain node identity qualification basic information, and carrying out the structural processing; generating a unique initial dynamic chain code by using an encryption algorithm, and storing the unique initial dynamic chain code in a main chain after binding the unique initial dynamic chain code with qualification information hash; integrating the collected data into traceability data and checking node identities and chain codes; after the verification is passed, the traceability data is bound with a chain code for the second time, and a timestamp is added for chaining; updating the chain code according to the service state, adding an identifier to the old chain code and permanently storing the identifier; according to the invention, a rigorous node identity authentication system is constructed, so that the credibility of a traceability subject is guaranteed, and identity and qualification data can be traced and verified in the whole process; multiple terminals collect data cooperatively, completeness and timeliness are ensured through multiple associations, chain code dynamic update adapts to service changes, and data association continuity is ensured; the whole-process mechanism effectively solves the problem of traditional traceability data splitting.

This invention discloses a multidimensional coupled chain code encoding method based on generalized integrated interleaving codes. It selects d-dimensional chain codes from s-dimensional chain codes for generalized integrated interleaving encoding, resulting in the l-th... i The code length of the wiry chain code is [value], and the information bit length is [value]. The remaining (s-d) wiry chain code is encoded, and the l′ [value] is [value]. i' Wirachain codes use linear block codes with a code length of and an information bit length of as the basic code, and the sequence c... (t) Initialize to an all-zero sequence; set the information sequence u Divide into sL groups. For the l-th dimensional zip code, divide into groups of length k. t,l -m t,l sequence u (t,l) With a length of m t,l sequence w (t,l) The data is fed into a multiplexer to obtain a length of k. t,l sequence a (t,l) The sequence is fed into a basic code encoder for encoding to obtain a codeword sequence. Simultaneously, the sequence is fed into a generalized integrated interleaved code encoder for encoding to obtain another codeword sequence. c (t,0) , c (t,1) ,…, c (t,s‑1) The encoded output sequence c at time t is obtained by feeding it into the multiplexer. (t) This invention has the advantages of simple coding, ease of implementation, and good performance.

This invention relates to the field of activated carbon raw material screening, providing a method and system for activated carbon raw material screening based on multimodal image feature fusion. The method includes: acquiring original images of edge contours and surface textures, constructing a set of binary edge contour images and a set of grayscale surface texture images; extracting edge chain codes to generate edge curvature sequences, extracting effective cutting feature vectors based on coating damage critical thresholds, and mapping them to generate a physical wear risk index; mapping the texture region of interest to a three-dimensional grayscale topological surface, calculating fractal dimension feature values ​​and the proportion of hygroscopic texture, and coupling them to generate an environmental hygroscopic preemption index; calculating the compatibility score of color-changing beads using an environment-medium dual-constraint weighted algorithm, and performing multi-path diversion decisions based on optimization thresholds, elimination thresholds, and physicochemical test data to generate particle grading control instructions. This invention achieves intelligent screening and resource scheduling of activated carbon particle microstructure through synchronous time-division optical field imaging and multimodal feature coupling.

The application is suitable for the technical field of image processing, and provides a battery glue line skeleton extraction method based on an improved ZS thinning algorithm, which comprises the following steps: preprocessing a collected battery glue line image to obtain a binary image; performing improved ZS thinning on the binary image, dividing the image into odd and even subdomains for batch processing, and introducing a constraint condition to iteratively delete redundant pixels to obtain a preliminary skeleton; using a T-shaped 4-neighborhood deletion template to remove T-shaped redundant pixels and realize complete single-pixelization; through 8-chain code tracking, identifying and removing burr branches caused by glue overflow and uneven glue coating, while protecting nodes to obtain a final glue line skeleton. The application solves the problems of skeleton redundancy, over-thinning and burr in existing thinning algorithms, realizes high-precision, single-pixel and burr-free glue line skeleton extraction, and can meet the online detection requirements of battery assembly lines, and has good industrial applicability.

The invention discloses an image region extraction and morphological processing method and system based on color features, and the method comprises the steps: determining the pixel coordinates of a target foreign body through the preset percentage coordinates of the target foreign body, and extracting representative color features in a positioning region of the target foreign body; taking the representative color features as a reference, searching for all pixel regions with similar colors in a total image range for extraction, performing judgment and selection on the extracted colors, and extracting a target foreign matter total image; morphological processing is carried out on the target foreign matter total image to obtain a binary image, and the processing process sequentially comprises Laplace edge detection, brightness normalization, binarization, opening operation and closing operation; and carrying out boundary tracking on the binary image after morphological processing so as to extract contour chain code data of the target foreign body, and reconstructing and outputting a smooth target contour.

The application relates to the technical field of data compression, and discloses a multimedia data compression method and device for narrowband transmission. The method comprises the following steps: performing double-threshold contour extraction on an input image to obtain main contour data and secondary contour data; performing mixed-precision chain code coding on the main contour data and the secondary contour data to obtain compressed contour chain codes; performing parameterization decomposition and superframe coding on an input speech signal to obtain compressed speech parameters; allocating a transmission bandwidth according to the compressed speech parameters, and packing the compressed contour chain codes and the compressed speech parameters based on the transmission bandwidth to obtain a target transmission packet sequence. The application ensures the time synchronization and transmission reliability of image and speech data, solves the problems of multi-modal data asynchronous transmission and high bit error rate in a narrowband environment, and guarantees correct reconstruction and playing at a receiving end.

This application provides a file storage method, apparatus, electronic device, and storage medium. The method includes: receiving chaincode parameters and a file to be processed through a conversion layer of a blockchain server; identifying the chaincode parameters; after confirming that the chaincode parameters include a file identifier, establishing a connection between the conversion layer and the blockchain server, and transmitting the file to be processed to the blockchain server; performing fragmentation on the file to be processed to obtain file fragments; calculating a digest of the file fragments to obtain a fragment hash value for each file fragment; and distributively storing the fragment hash values ​​on the blockchain server. By receiving the chaincode parameters and the file to be processed through the conversion layer of the blockchain server, identifying the chaincode parameters, and establishing a connection with the blockchain server after confirming that the transmitted file is a file, the method enables file storage on the blockchain server, improving file transmission efficiency, eliminating reliance on third parties, and enhancing data security.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a multi-modal generation model acceleration method and system, and the method comprises the steps: constructing an edge cluster, deploying a block chain network in the edge cluster, the edge cluster comprises a plurality of edge calculation nodes, and each edge calculation node is provided with a multi-modal generation model; deploying a multi-modal generation model chain code to a block chain network, wherein the multi-modal generation model chain code defines service logic for processing and storing multi-modal generation model information of the edge computing node; and receiving and processing multi-modal generation model information sent by the edge computing node by using the multi-modal generation model chain code. The calling efficiency of the multi-modal generation model can be improved.

The invention discloses a weighing data acquisition and analysis system and method based on industrial Internet of Things, and particularly relates to the field of industrial metrology, and the system comprises a historical database module, a machine learning model training module, an automatic calibration module and a calibration application module. The historical database module is used for collecting, integrating and storing multi-dimensional data in a historical physical chain code calibration process, forming and establishing a structured database containing the following three types of information and preprocessing the structured database; the automatic calibration module is an execution unit used for calibration and is responsible for completing real-time prediction of parameters when calibration is needed; the calibration application module is responsible for applying the prediction result to a metering instrument of the belt weigher and executing parameter updating and application; according to the invention, the original physical calibration process requiring several hours of shutdown and multi-person cooperation is shortened to several minutes of data acquisition and model calculation process, so that one-key automatic calibration is realized.

The application discloses a method for verifying a Fabric complex endorsement strategy in cross-chain, wherein the Fabric blockchain first registers an MSP list, a chain code ID and an endorsement strategy description into a cross-chain network, transmits a generated cross-chain transaction to a relay chain, then the relay chain analyzes a transaction execution result and a set of endorsement node signatures, generates an endorsement strategy interpreter, and confirms that the transaction execution result is consistent with the chain code ID registered in the cross-chain network, and if not, the verification fails, and finally the endorsement strategy interpreter verifies the set of signatures. The application can verify a complex endorsement strategy customized by a user, is friendly to a user of the Fabric network, does not need to write a verification strategy by itself, and only needs to submit an endorsement strategy description, and can prevent a user from performing malicious attacks through different chain codes.

The invention provides a chained code generation method and device based on a large model, electronic equipment and a readable storage medium, and relates to the technical field of artificial intelligence such as large models, deep learning and natural language processing. The chained code generation method based on the large model comprises the steps of obtaining a plurality of code generation subtasks and an execution sequence of the code generation subtasks according to a code generation demand; using a large model to sequentially execute the plurality of code generation subtasks according to an execution sequence, and respectively generating code files corresponding to the code generation subtasks; and according to the plurality of code files corresponding to the plurality of code generation subtasks, obtaining a code generation result corresponding to the code generation demand. According to the method, the completeness of the dependency relationship between the code files and the code consistency can be ensured in the mode that the code generation subtasks are obtained through decomposition, and then the large model executes the different code generation subtasks in sequence, so that the accuracy of the code files and the code generation result is improved.

The present application relates to the technical field of visual identification, in particular to a kind of engine cylinder cover defect detection method and system, first to gray cast iron cylinder cover fire surface image pre-processing, obtain denoising gray scale chart;Two rows of gas hole profile are extracted and the hole center coordinates, connecting line unit vector and pixel length are calculated. Along the hole center connecting line equidistant sampling, take the gray scale maximum value of local strip in vertical direction as local background gray scale, combined with the preset crack gray scale upper limit, the local threshold value of sampling point is calculated, and the piecewise linear threshold function is generated by linear interpolation. The projection coordinates of cylinder cover nose bridge area pixels on connecting line are solved, the adaptive threshold is obtained by calling threshold function, and binary image is generated by pixel by pixel segmentation. The binary image is denoised and the skeleton is extracted, the skeleton pixel length is calculated using chain code, and the actual length of crack is obtained combined with camera correction factor. The present scheme can solve the fixed threshold mis-detection and missed detection problem caused by the gray scale gradient of the nose bridge area of the cylinder cover fire surface under the condition of no pre-cleaning.

The present application relates to the field of image processing, in particular to a kind of unmanned aerial vehicle dynamic fuzzy target identification method and system, comprising: obtaining final area and contrast edge in final area;The chain code of different contrast edge in each final area is compared, and the fuzzy performance of each final area is obtained;According to the gradient amplitude of each pixel point on each contrast edge in each final area and the distribution of gradient amplitude, and the fuzzy performance of each final area, the final blurring degree of each final area is obtained;According to the final blurring degree of each final area, the blur kernel of each final area is obtained, and the deblurring processing of image is completed.The present application aims to solve the problem that when the current image is deblurred, the same degree of deblurring intensity is used for different parts of the image, so that the deblurring effect of the image is relatively poor.

Herein is privacy for a smart contract that contains chaincode that sends chaincode events. In a configurable and backwards compatible way, broadcast of a chaincode event can be restricted. Before committing a transaction to a blockchain and without storing a newly generated private event into the transaction, the following are stored into the private event: an event payload, a hash of the payload and, unlike the state of the art, an identifier of a subscriber or organization that can receive the private event. After committing the transaction is an asynchronous detection that the identifier of the subscriber is associated with the event and, responsively, the payload of the event is sent to the subscriber.

The present application relates to the field of environmental protection and intelligent decision-making technology, in particular to a dust control strategy comprehensive optimization decision-making method and system for dry bulk cargo wharf, a multi-source index database is constructed, the marginal contribution of each control measure under different weather, operation and adjacent measures in operation state is cross-correlated and mined to obtain a context-coupled marginal contribution surface; taking scene input as a condition, measure start-stop state parameters and intensity parameters as decision variables, dust concentration not exceeding the control target value as a hard constraint, and the minimum comprehensive operation cost as an optimization objective, a recommended control scheme is solved by a double-chain coding genetic algorithm combined with a minimum cost constraint repair; an instruction card is pushed to the wharf terminal, execution parameters and measured concentration are collected to form a closed-loop feedback sample triple, the surface execution deviation is adaptively incrementally updated; the surface topological features of multiple wharfs are extracted to perform transfer learning to generate a benchmark report, the compliance rate is significantly improved, and the environmental protection cost per unit throughput is significantly reduced.

The invention provides a privacy protection cooperative training method, system and device based on an alliance chain, and the method comprises the steps: carrying out the identity registration and key distribution through the alliance chain, generating and signing a training task through a coordination node, carrying out the model training of private data through each participant locally, and carrying out the privacy protection cooperative training. Differential privacy and security aggregation (using but not limited to homomorphic encryption) are adopted to protect parameter updating, an updated abstract and a signature are linked, and verification and evidence storage are carried out through a chain code; after the minimum participation number threshold value is met, robust aggregation and new model release are carried out, aggregation result hash and signature uplink are carried out, and the traceability of the training process is achieved. According to the method, cross-mechanism collaborative modeling and training can be realized under the condition that original data is not leaked, and identity credibility, private protection of training data and tamper-proof capability of model parameter updating are remarkably improved.

The invention discloses a block chain-based carbon emission control method, apparatus and device, a network and a medium. The method comprises the steps of receiving transaction request information sent by a merchant terminal in real time; calling a chain code based on the transaction request information, traversing a plurality of blocks bound with a user identifier in a carbon footprint block chain through the chain code, extracting a plurality of historical transaction carbon footprints in a preset time period from a non-encrypted header of each block, and aggregating the historical transaction carbon footprints to obtain a plurality of historical transaction carbon footprints; on the basis of the polymerized carbon footprint and the single-item carbon footprint, calculating to obtain a total transaction carbon footprint; and comparing the total transaction carbon footprint with a preset threshold value, determining a transaction signal based on a comparison result, and managing and controlling the carbon emission of the user based on the transaction signal. According to the method, the real-time performance and accuracy of user carbon emission management and control in a consumption scene can be improved by utilizing the block chain.

The application discloses a document image tilt correction method based on a Freeman code, and specifically comprises the following steps: step one, image preprocessing, converting the image into a gray image, and performing binarization and morphological operation; step two, image effective text connected block extraction, removing non-text images in the image; step three, connected block image thinning processing, extracting a text connected block skeleton, and performing deburring processing on the text connected block skeleton; step four, tilt angle calculation, extracting the contour of the text connected block skeleton, performing Freeman code boundary tracking on the text connected block skeleton, calculating the chain code value of each connected block contour and the proportion occupied by the chain code value, and taking the angle corresponding to the highest proportion of the number of chain code values in the vertical and horizontal directions as the rotation angle; and step five, document image tilt correction. The application supports complex document images containing illustrations, tables and the like.

The application belongs to the technical field of medical image processing and computer-aided diagnosis, and discloses a method and system for predicting postoperative complications of TIPS based on vascular tortuosity, which realizes accurate quantification of the vascular tortuosity feature by pre-processing, skeleton extraction, down-sampling processing, slope chain code quantization, histogram statistics and visual interactive of the portal vein image, and establishes the correlation model between the vascular tortuosity feature and the postoperative complications of TIPS. The application quantifies the vascular tortuosity by using the slope chain code technology, and solves the defect that the traditional method cannot capture the local tortuosity feature of the blood vessel by combining with the ball drop down-sampling processing, so as to realize accurate representation of the spatial configuration complexity of the blood vessel. By establishing the correlation model between the tortuosity histogram feature and the clinical outcome, the prediction accuracy of the postoperative complications of TIPS is significantly improved, and a reliable basis is provided for early intervention. The generated interactive HTML file realizes efficient conversion from data to clinical decision, and facilitates doctors to intuitively analyze the high-risk section of the blood vessel.

The application provides a software supply chain code and component collaborative risk assessment method, belonging to the technical field of power network security and software engineering, which can at least partially solve the problems of insufficient detection of deep logic defects of code, lack of global aggregation perspective in component risk assessment, and mutual fragmentation of the two in the prior art. The application comprises: constructing a multi-dimensional knowledge graph of power generation assets and quantifying the version time effectiveness deviation coefficient and the whole network reuse weight of third-party components; injecting a set of power working condition constraints to perform path traversal and logic anomaly mining on the code to be detected and obtain symbolic execution coverage; calculating an exposure surface diffusion index and a business impact depth index based on the knowledge graph to synthesize a supply chain comprehensive risk value; fusing the results of logic anomaly mining and the supply chain comprehensive risk value to construct a dynamic attack graph and calculate an attack chain comprehensive achievement rate; and generating a collaborative disposal strategy according to the attack chain comprehensive achievement rate. The application realizes the collaborative quantification and defense from micro-code to macro-supply chain situation.

An Electronic Shelf Label (ESL) management server and a method for controlling the ESL management server are disclosed. An ESL management server for compressing an image to be displayed on an external display device of the ESL system comprises a communication unit obtaining an image including product information; and a processor applying a first pre-processing process to the image, chain coding the image to which the first pre-processing process has been applied, encoding a chain code and a chain code table obtained as a result of the chain coding into a bitstream, generating a compressed image file using the bitstream, and transmitting the compressed image file to an external display device through the communication unit, where the first pre-processing process converts data with a high local correlation within the image into a small integer but converts data with a small local correlation within the image into a large integer.

The application discloses a simplified development method and device of a smart contract chain code, and is used for reducing the use difficulty, operation and management difficulty and use cost of the smart contract chain code. The method comprises the following steps: obtaining target natural language input by a user according to uplink business data, the target natural language is used for defining target data of a target smart contract contained in a target chain code and defining a target operation mode of the target data, and the target chain code at least contains one target smart contract; mapping the target natural language into target code by calling a preset data-code mapping model; packaging the target code by calling a packaging model to generate a target source code file of the target chain code; packaging the target source code file into a target chain code project package according to a preset project model, the target chain code project package comprising the target source code file and a target configuration file; and deploying the target chain code project package on a blockchain platform.

The application discloses a three-dimensional model compression method based on two-dimensional chain codes, comprising the following steps: S1: inputting a three-dimensional voxel model; S2: cutting the three-dimensional voxel model to obtain a three-dimensional voxel model patch; S3: performing inner and outer contour extraction and chain code traversal on the three-dimensional voxel model patch to obtain an inner and outer contour sequence, an inner and outer contour offset sequence and an anchor point sequence of the three-dimensional voxel model patch; S4: obtaining a plurality of anchor point connection information and a layer anchor point offset sequence between adjacent three-dimensional voxel model patches according to the anchor point sequence of the three-dimensional voxel model patch; and S5: encoding the inner and outer contour sequence, the inner and outer contour offset sequence, the anchor point connection information and the anchor point offset information of the three-dimensional voxel model patch to obtain a three-dimensional voxel model encoding sequence based on two-dimensional chain code compression. The method can reduce the storage space occupation and decoding calling time length of three-dimensional voxel model data without losing the precision of the three-dimensional voxel model.

A system and method for a trusted data-exchange interface using a peer-driven transaction sequence on a permissioned blockchain network is disclosed. A first peer initiates the sequence by invoking a smart contract in an endorsing peer. The endorsing peer retrieves information from an external system. A second peer executes chaincode to generate a determination. An ordering peer commits a result of the determination to an immutable ledger. The peers may be implemented as distinct containers in a shared hardware environment.

Example operations can include one or more of receiving a request to merge a first blockchain network and a second blockchain network, the request including a script specifying a network structure; synthesizing the script with configuration data of the first blockchain network and the second blockchain network to generate a plurality of merge operations; and merging the first blockchain network with the second blockchain network based on the plurality of merge operations to create a merged blockchain network, wherein the merging includes merging chaincodes and channels from the first blockchain network and the second blockchain network into merged chaincodes and merged channels.

This document describes a set of smart contract and off-chain tools that enable data management and organization, allowing data to be stored in a distributed ledger according to relational database principles. A cross-platform distributed ledger specification, along with reusable core components, creates a system that can be deployed on distributed ledger platforms to enable data storage and retrieval to and from the distributed ledger governed by relational principles. One implementation of this system allows the addition of System Chain Code to Hyperledger(r) Fabric and uses schemas and data represented as JSON. In use, the user can create, update, and query data from code, a console, or a smart contract, where each update is a distributed ledger transaction.

Herein is privacy for a smart contract that contains chaincode that sends chaincode events. In a configurable and backwards compatible way, broadcast of a chaincode event can be restricted. Before committing a transaction to a blockchain and without storing a newly generated private event into the transaction, the following are stored into the private event: an event payload, a hash of the payload and, unlike the state of the art, an identifier of a subscriber or organization that can receive the private event. After committing the transaction is an asynchronous detection that the identifier of the subscriber is associated with the event and, responsively, the payload of the event is sent to the subscriber.

The application belongs to the technical field of data transmission, and particularly relates to a data transmission state monitoring method and system based on FPGA, which comprises the following steps: setting the order of MacAdam ellipse during current data transmission according to the state monitoring result of last data transmission, screening out multiple MacAdam ellipses which can completely cover the entire chromaticity diagram and have the least number from all MacAdam ellipses distributed on the chromaticity diagram and taking the multiple MacAdam ellipses as multiple color features, scanning all pixel points in the image data to be transmitted to obtain a pixel point sequence, forming a color feature sequence by taking the color features of all pixel points in the pixel point sequence, setting a multiple-connected chain code for each color feature, converting the color feature sequence into multiple chain codes, compressing and encoding all chain codes, and obtaining a compression and encoding result of the image data to be transmitted and transmitting the result. The application can adapt to current data characteristics and transmission environment.