66 results about "Chain code" patented technology

The invention relates to the technical field of machine vision, in particular to a precision part size automatic detection method and system based on machine vision, precision part images are collected through a high-precision industrial camera, part positioning is carried out, sub-pixel-level topological feature mapping is carried out on interested area images, and precision part size automatic detection is carried out. Comprising the steps of gray histogram equalization, gray morphological processing, edge detection and edge chain code tracking, construction of an edge point topological feature space, execution of sub-pixel subdivision, obtaining of an edge line through contour analysis of a feature distance and a feature angle, and double-constraint geometric reconstruction based on the edge line. The characteristic distance and the characteristic angle are used for rotation matrix conversion and geometric dimension calculation, a relation model of the geometric dimension and the actual dimension of the part is established, precise part dimension measurement is achieved through dynamic error analysis and compensation, the measurement precision is remarkably improved, the risk caused by unreliability of a single characteristic is effectively reduced, and the measurement accuracy is improved. And the measurement stability is improved.

The embodiment of the invention discloses an automatic function chain generation method and device based on a graph database and a medium, and relates to the technical field of graph databases, and the method comprises the steps: receiving natural language query information triggered by a user, carrying out intention analysis on the natural language query information through a preset language model, determining a structured query condition, and sending the structured query condition to the user; the structured query condition comprises a query intention category, a query entity parameter and logic step disassembly information; according to the structured query condition, mixed retrieval is carried out in a pre-constructed graph database, a candidate API calling path set is determined, the graph database comprises an API knowledge graph and node semantic vector information, and the candidate API calling path set comprises at least one candidate API calling path; and performing multi-dimensional scoring on candidate API call paths in the candidate API call path set, and dynamically generating an executable function chain to determine an API call chain code of the target programming language corresponding to the executable function chain.

A system and a method are disclosed relating to a transport block processing chain for a transmitter. A code block determination circuit may be configured to determine a size of a code block that maps across multiple slots of a wireless physical shared channel according to a Transport Block over Multiple Slots (TBoMS) configuration, and a rate matching circuit may be configured to rate match bits of the code block to a number of bits available in a transport block that spans the predetermined number of slots of the wireless physical shared channel. Additionally, an interleaver may be configured to interleave a continuous output of the rate matching circuit on a slot basis so that a code block that crosses a slot boundary between a first slot and a second slot is interleaved within the first slot and the second slot.

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 concurrent scene-oriented extensible block chain client optimization method, which comprises the following steps of: decoupling a client into an interface service layer, a message service layer and a data service layer based on an asynchronous message bus, and realizing node dynamic registration and routing table maintenance through a heartbeat protocol; the interface service layer calculates a dynamic weight according to the state information of the data service nodes to construct a dynamic weight table so as to distribute an external request to the surviving data service nodes; a distributed cache layer is introduced, a cache layer cluster is preferentially queried in a read operation path, chain code query is triggered when the cache layer is not hit, and a result is written into a cache; and a write operation path adopts two-stage cache failure guarantee to eliminate dirty reading. Industrial environment parameters of all the data service nodes are collected in real time and scored, and part or all of the flow is intelligently migrated according to the score. According to the method, the client throughput, the response efficiency and the industrial environment adaptability are remarkably improved, and large-scale deployment of intelligent manufacturing high-concurrency scenes is supported.

The invention provides a distributed archive storage method based on an alliance chain, which can be applied to the technical field of alliance chains. The method comprises the steps that in response to a request of uploading an archive file by a first user, the type of the archive file is determined, and the first user is configured to have the authority to upload, query and authorize the archive file; determining a chain code corresponding to the archive file based on the type of the archive file; the archive file is uploaded to the distributed file storage system through the chain code corresponding to the archive file, the chain code is created by an archive file administrator, and the archive file administrator is configured to manage the authority of the chain code. The invention further provides a distributed file storage device and equipment based on the alliance chain, a storage medium and a program product.

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.

Embodiments of the present application are suitable for the field of blockchain technology, and provide a data processing method and device, computer equipment and medium. The method is applied to a blockchain node, and includes: receiving a transaction request from a user, the transaction request including a computing event; if the computing event is a privacy computing event, sending the privacy computing event to an off-chain computing node to obtain a privacy computing result of the privacy computing event; in response to the privacy computing result, verifying the privacy computing result by using a proxy chaincode to obtain a verification result, the proxy chaincode being a contract deployed in the blockchain; based on the verification result and the privacy computing result, returning a privacy computing response to the off-chain computing node, so that the off-chain computing node returns event end information of the transaction request to the user according to the received privacy computing response. Through the above method, the privacy of privacy computing in the blockchain can be guaranteed, and the execution efficiency of privacy computing can be improved.

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.

A system described herein may identify a chaincode record recorded to a blockchain, and may output chaincode discovery information to a chaincode discovery system. A client device may receive the chaincode discovery information from the chaincode discovery system, and may output a request to invoke the chaincode. The system may obtain verification, from the chaincode discovery system, that the client device is authorized to invoke the chaincode, and may instruct a node that maintains the blockchain to execute the chaincode. The system may receive output values resulting from executing the chaincode and may output, to the client device, the output values resulting from executing the chaincode.

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.

An external chaincode (CC) executor controller includes a block tracking circuit to register for events and a first data model type data access layer (DAL) to receive a data point and convert the data point to a native first data model type to be stored in a first data model type database. Furthermore, a second data model type DAL receives the data point and converts the data point to a native second data model type to be stored in a second data model type database. Moreover, a block committer circuit receives a new block notification and determines that the new block notification includes a smart contract data model, and in response thereto dispatch the smart contract to the first data model type DAL or to the second data model type DAL to support delegated execution of the smart contract data model efficiently and reliably.

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.

A method and system for smart contract vulnerability detection on Hyperledger Fabric are disclosed. The method includes uploading the chaincode to be tested, auxiliary chaincode, and test parameters; analyzing and processing the chaincode to be tested to generate an Abstract Syntax Tree (AST); generating a data flow graph and a key data flow graph based on the AST; using the chaincode to be tested and the generated key data flow graph as input for vulnerability detection, obtaining graph learning vulnerability detection results; installing the chaincode to be tested and the auxiliary chaincode on two channels of the blockchain network respectively; acquiring the blockchain network's operating status; generating test cases based on the test parameters; executing the test cases to verify the existence of vulnerabilities, obtaining fuzzing vulnerability detection results; and integrating and displaying the graph learning vulnerability detection results and fuzzing vulnerability detection results. This invention can achieve dynamic and static combined vulnerability detection of chaincode, enhancing the accuracy and efficiency of vulnerability detection.

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.

The present invention discloses an off-chain data acquisition system based on an oracle cluster, which relates to the technical field of off-chain data acquisition, including a user contract, an oracle contract, a database and an oracle cluster; the user initiates a request through the user contract, and the oracle contract encapsulates the request parameters as a chain code event and sends it to the oracle cluster; the oracle cluster includes at least one centralized oracle node, which is responsible for monitoring the chain code event and obtaining the processing right of the event by seizing the event lock. The node that obtains the processing right obtains the data source parameter by parsing the chain code event, initiates a data request to the data source and parses the response result, and finally calls back the user contract through the oracle contract to write the data back to the chain; all nodes in the cluster share a database, and the database implements event locks based on data tables, and the nodes in the cluster collaborate through event locks; the present invention can improve the efficiency of data acquisition, reduce the complexity of design, and ensure the high availability of services.

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 application discloses an industrial robot vision identification and positioning method and system, and belongs to the technical field of intelligent robots, and the technical solution points are as follows: a first image of a workpiece to be processed and a preset texture chain code are acquired; bad points in the first image are determined according to the first chain code corresponding to the first image and the preset texture chain code, and instructions are sent to the industrial robot according to the bad points, so that the industrial robot eliminates the bad points; a second image of the workpiece to be processed and a second chain code corresponding to the second image are acquired, the second image is an image of the workpiece to be processed after the bad points are eliminated; and control parameters are updated according to the second chain code and the preset texture chain code. The application describes the texture features of the workpiece to be processed through the chain code, identifies errors in the processing process based on chain code comparison, and then adjusts the control parameters of the industrial robot according to the errors, and is suitable for scenes in which the controller has limited computing power and cannot perform complex image processing algorithms in the industrial scene.

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 invention is suitable for the technical field of plant phenotypic parameter measurement, and provides a leaf phenotypic parameter measurement method and system based on an image processing technology, and the method comprises the following steps: S1, collecting a lemon leaf image, and carrying out the preprocessing of the image, and obtaining a binary contour image of a leaf; s2, extracting the length and the width of the blade by adopting a minimum enclosing rectangle method or an end point method; s3, adopting a Freeman chain code to track the blade contour, and calculating the perimeter of the blade; s4, calculating the leaf area by adopting a pixel number method; s5, measuring a blade tip included angle and a blade base included angle of the blade; the method can rapidly and accurately measure the phenotypic parameters of the lemon leaves, provides powerful technical support for lemon germplasm resource research, variety improvement and breeding work, and has a wide application prospect.

The invention relates to the technical field of image processing, and provides an intelligent image recognition method for a high-precision map, which comprises the following steps of: acquiring various map elements required by the high-precision map and contour information of the map elements, and recording related data of a plurality of attributes of each map element; obtaining a plurality of categories of each attribute of each map element; obtaining a comprehensive basic value of each map element, and constructing a map element basic sequence from large to small; constructing a plurality of scales of the map element quantity from small to large; constructing a map distribution diagram of each scale, and obtaining a chain code vector of each edge in the map distribution diagram; screening to obtain a plurality of reserved scales; marking a plurality of nodes; obtaining a path of each node of each reserved scale; and screening a plurality of reserved paths of each node, and generating a high-precision map in combination with the map distribution diagram of each reserved scale. The invention aims to solve the problem that the matching of a road network and a lane network at an intersection is not accurate enough in a high-precision map making process.

The embodiment of the invention provides an interaction control method and system by monitoring an operation gesture, and the method can recognize gesture features in an operation movement track after the operation movement track is obtained, and matches a target operation instruction according to the gesture features, thereby executing the target operation instruction. Wherein the gesture features are chain codes generated based on position information such as coordinate values, inter-point distances, inter-point angles, point interval time and track directions of the operation track points. According to the method, the global operation event and the control window can be monitored and captured through the asynchronous processing event, and the gesture features are calculated by processing the operation track points, so that the specific control instruction is simulated, and the problem that the operation efficiency is low due to the fact that the operation mode depends on the control layout of the user interface is solved.

The application provides a method and system for deploying chaincode in a consortium chain, the method comprising: a Peer container receiving a command for installing traditional chaincode and chaincode source code sent by a client; the Peer container constructing a chaincode image based on the chaincode source code by using a third-party building module; and the third-party building module starting a traditional chaincode container and loading and starting the chaincode image in the traditional chaincode container. Through the above process, the developer still writes in the traditional chaincode manner without making changes when developing the chaincode source code, so that no additional development cost is added to the chaincode developer. Meanwhile, the chaincode image is constructed by the third-party building module, so that the dependence on Docker is eliminated.

The invention relates to the technical field of image processing, in particular to a tooth consistency intelligent identification method for bulldozer tooth blocks, which comprises the following steps of: obtaining a reference connected domain according to the gray distribution of pixel points in a preset local window of all pixel points in each defect connected domain and the difference between data in an edge chain code sequence of each defect connected domain; obtaining a target connected domain according to the gradient change vector of each reference connected domain and the difference between the decline vectors of all edge pixel points in each reference connected domain; obtaining a projection vector of each reference connected domain according to the decline vector; and obtaining a tooth consistency identification result of the bulldozer tooth block according to the difference between the projection vector and the gradient change vector of any two target connected domains and the distance between any two target connected domains. According to the invention, the accuracy of tooth crack detection of the bulldozer tooth block is improved, and the accuracy of the tooth consistency identification result of the bulldozer tooth block is also 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.