80 results about "Autocode" patented technology

A publishing system with components, including:a system configured to receive at least one document including text that defines a base alphabet in one or more formats;a system configured to provide additional data for a reader to better understand the document which includes:a method of encoding or marking up non-phonetic words in the document to enable the reader to decode sounds of each non-phonetic word; anda system configured to output an encoded document with the text and the additional data in one or more formats,wherein the method of automatically encoding the non-phonetic words to make the encoded words phonetic:for at least one character (“spelling character”) in the non-phonetic word, using a compound character that includes the spelling character and a sound character, wherein the sound characters:are human-readable characters in the base alphabet and / or in one or more secondary alphabets,are added to the spelling characters to indicate that each spelling character makes the usual sound of the sound character,are added so that spelling characters can be visually discriminated from sound characters,are added such that a reader can recognize the non-phonetic word by sight because the spelling of the word is unchanged, andare added to the spelling characters such that the spelling characters and the sound characters remain human-readable such that the spelling character and the sound character of each compound character are within one visual field; andautomatically outputting the encoded words in a human-readable form / format such that the compound characters in the encoded word visually indicate which of the spelling characters have a sound other than their usual sound and what sound each character makes in the non-phonetic word when it does not make its usual sound.

The invention provides an electronic health record automatic coding method and system, and the method comprises the steps: segmenting an electronic health record text into a plurality of text segments, and obtaining a plurality of unstructured text contents; obtaining structured key medical information based on a preset large language model and the plurality of unstructured text contents; generating a preliminary coding result based on a preset coding rule base and the structured key medical information; and obtaining a final coding result based on a preset verification model, a preset auditing model and the preliminary coding result so as to complete automatic coding of the electronic health record. According to the method, the key health information in the non-structural text is coded, and the coding result is verified, so that the accuracy of the coding result is improved.

The invention discloses a hierarchical coding system-based intelligent recognition and language conversion method for traditional building-riding facade components, which realizes automatic coding and standardized description generation by constructing a six-level hierarchical coding system and training a special component recognition model, and lays a data foundation for evolution analysis of large-scale building-riding buildings. The method comprises the following steps: S1, constructing a six-level standard coding system; s2, collecting, preprocessing and labeling images, and constructing a labeling data set; s3, constructing a building-riding part identification model, and training and identifying the building-riding part identification model by using the existing data set and the annotation data set; s4, allocating coding information of a standard coding system for the recognition result of S3, extracting multi-dimensional features, performing component correlation analysis, and constructing a component feature database; s5, standard component description texts of three levels are automatically generated based on the steps S3 and 4; s6, constructing a structured knowledge graph of the apartment facade components based on the steps S3 to S5; and S7, integrating the processing capabilities in the steps S2 to S6 into a complete system.

The invention belongs to the technical field of financial science and technology, and discloses a multi-agent collaborative document-driven quantitative research and transaction self-evolution system and method. The system adopts a layered architecture, comprises a data and factor service layer, an execution engine layer, an agent layer, an interface service layer and a front-end control layer, and aims to solve the core problems that research and engineering implementation are separated in quantitative strategy research and development, code generation lacks interface constraints and strategies lack self-evolution ability. According to the system, through cooperative work of a research agent, a factor agent and a coding agent, a strategy idea described by a natural language is automatically converted into a standardized document, configuration and executable code; through a closed loop formed by self-monitoring, self-diagnosis and self-improvement intelligent agents, automatic diagnosis and optimization of problems of strategy overfitting, factor attenuation and the like are realized, continuous self-evolution of the strategy is driven, and full-life-cycle automatic management from strategy conception, factor design, automatic coding and real disk back-testing to feedback autonomous optimization is realized.

The invention discloses an automatic coding method for realizing international disease classification, and the method comprises the steps: obtaining electronic medical record data from a medical database, and carrying out the preliminary cleaning of the data; extracting an electronic medical record text, associating the electronic medical record text with an ICD code diagnosed by a doctor, and constructing a training data set; a multivariate knowledge base is constructed, wherein the multivariate knowledge base comprises a UMLS synonym base, an unstructured knowledge base and an auxiliary knowledge base generated through LLM; constructing an ICD coding model which comprises a context coding module, an auxiliary knowledge screening module, a multiple attention interaction module and a fusion prediction module; a binary cross entropy loss function is adopted to optimize an ICD coding model, and automatic coding of international disease classification is achieved. According to the method, multi-level semantic interaction between the text and the code can be effectively captured, and the distinguishing capability and the coding precision of different levels of semantic information of the complex text are improved; the key information can be extracted more accurately, and the coding quality under complex cases and fuzzy diagnosis scenes is improved.

The invention provides an automatic coding method and device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence, and the method comprises the steps: obtaining an initial code generated by a preset programming large model based on a programming prompt word; inputting the initial code into a preset compiling agent, so that the compiling agent performs compiling verification on the initial code and generates error information of the initial code; and the error information is input into the programming large model, so that the programming large model corrects the initial code based on the error information. According to the method, the codes generated by the large programming model can be automatically input into the compiling agent for compiling verification, errors existing in the codes are automatically found out through the compiling agent, error information is automatically input into the large programming model, the codes are automatically corrected through the large programming model, and the efficiency is improved. Developers do not need to manually find errors existing in the codes and manually input error information, and the code writing efficiency is improved.

Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.

The invention discloses a medical clinical data coding method based on a large language model and artificial code multiplexing. The medical clinical data coding method comprises the following steps: acquiring medical clinical original data to be coded and identifying a coding type; automatically generating a data cleaning dynamic template, and inputting a data cleaning instruction into the large language model to obtain cleaned data; calling a preset automatic coding rule base to execute automatic coding, wherein the automatic coding rule base comprises matching rules sorted according to priorities; if the automatic coding is not hit, entering a manual coding process and entering a synonym library for semantic association matching of subsequent automatic coding; after the medical coding dictionary is updated, a preset upgrading rule base is called to automatically process coded data, data to be upgraded are recognized, a coding upgrading suggestion is generated in combination with a retrieval enhancement generation technology, and data upgrading is achieved; and exporting a coding result. According to the invention, the efficiency and accuracy of medical clinical data coding can be improved, and manpower and time costs are reduced.

Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.

An approach of the present disclosure includes an algorithm to encode an instruction set of a domain-specific processor automatically in an optimal way, and which yields area-effective hardware. Instruction operands and opcodes can be encoded separately or at the same time. Instructions are not encoded one by one but can be encoded in groups, and instructions are grouped automatically. The decoding logic of control signals for each group of instructions, such as register read enable and write enable, is fed to a logic minimizer to obtain an encoding constraint matrix, and the encoding of each instruction in each instruction group is done using an optimal state assignment method.

The application discloses a kind of for clinical diagnosis text automatic ICD-10 coding text matching model's construction method, device and application, comprising: first, by the coding history text is processed into priority matching set, with the coding result of coding history of previous years Analogy reasoning the coding result of unencoded clinical diagnosis text;Then, realize a kind of based on interactive text matching mode, in matching process, each character in two texts is interactively matched, uses the matching strategy of element-by-element subtraction and element-by-element multiplication through a neural network, retains more original information, obtains better matching effect, in aggregation process, using convolutional neural network, using the convolution kernel with same weight is merged feature to retain more original information, further improve the matching effect;Finally, data that cannot be matched with the coding history of previous years still can be secondarily matched with ICD-10 disease standard name, ensure the comprehensiveness of matching.

The present application relates to devices and components including apparatus, systems, and methods to utilize auto-encoding for channel state information feedback.

In a method for real-time opportunity discovery for productivity enhancement in a production process, a processor extracts a set of features from time series data using autoencoding of a neural network based on uncontrolled variables in the time series data. The processor identifies one or more operating patterns based on the extracted features, wherein the features include a dimensionality reduction of a representation learned from the time series data. The processor identifies a neighborhood of a current operating state based on the extracted features. The processor compares the current operating state with historical operating states based on the time series data in the same operating pattern. The processor uses the neighborhood to discover operating opportunities based on the comparison of the current operating state with the historical operating states. The processor identifies controlled variables in the same pattern that are correlated with the current operating state.

The application relates to the field of artificial intelligence and discloses a text connotation quality evaluation method for improving the accuracy of text connotation quality evaluation and improving model training efficiency. The text connotation quality evaluation method comprises the following steps: obtaining an initial text from a preset medical record text; processing the initial text through a natural language processing algorithm to obtain a target text; performing text coding on the target text through a preset bag-of-words model and a preset automatic coding model to obtain first text features; performing feature extraction on the target text to obtain second text features, wherein the second text features comprise text complexity features, text grammar style features and medical semantic features; performing evaluation processing on the first text features and the second text features through a trained logistic regression model to obtain an evaluation result, wherein the evaluation result is used for identifying the connotation quality grade of the preset medical record text. The application also relates to the blockchain technology, and the target text is stored in the blockchain.

A method, apparatus, main controller, and storage medium for automatic jacquard encoding are disclosed, belonging to the field of textile technology. The method includes the main controller acquiring the Nth communication address of the Nth jacquard and sending a communication address query message for the (N+1)th jacquard to the Nth jacquard via an optical signal communicator; the Nth jacquard receiving the communication address query message for the (N+1)th jacquard and sending a communication address setting signal to the (N+1)th jacquard; the (N+1)th jacquard receiving the communication address setting signal sent by the Nth jacquard, setting the currently queried address value as the (N+1)th communication address of the (N+1)th jacquard, and responding to the main controller's communication address query message with the (N+1)th communication address as the communication address status of the (N+1)th jacquard, thus completing the automatic jacquard encoding. This solves the problem that using a mechanical dialer for jacquards requires manual dialing and is prone to setting errors.

The application relates to a network congestion link diagnosis method based on an adversarial automatic encoder and belongs to the technical field of network communication, which comprises the following steps: generating a data set containing link states and path states according to the congestion prior probability of a link; feeding the data set into an automatic encoder, superimposing a generative adversarial network on the encoder or the decoder of the automatic encoder, inputting the path states or the link states into the encoder, and reconstructing the link states or the path states; training the generative adversarial network, enabling the generative adversarial network to learn the congestion prior probability information of the link, and outputting a link state solution with the maximum congestion posterior probability; and reversely propagating the reconstruction loss and the generative adversarial loss, and iteratively updating network parameters. The application applies the adversarial automatic encoder, learns the unique mapping relationship from the link to the path through the link states and the path states, does not need to measure the network topology, and meanwhile, the adversarial automatic encoder is data-driven, has strong adaptability and has certain attack resistance.

The invention relates to the technical field of data processing, in particular to an automatic coding agent control system and method for a multi-task scene, and the system comprises a data collection module, a coding processing module, a quality evaluation module, a strategy optimization module, an execution control module, a defect tracing module, a parameter correction module and an iterative optimization module. The quality evaluation module is used for calculating the quality deviation index of the core quality index of each process based on the unified feature vector; and the strategy optimization module is used for fusing the multi-source information to optimize the process parameter regulation and control strategy of each process. According to the method, the limitation of traditional single-process coding is broken, cross-process data representation distortion is effectively avoided, and the coding accuracy and data link integrity of multi-process linkage control are remarkably improved; data coding, quality correlation and parameter iteration are integrated, the problems that a traditional system is insufficient in universality and lacks a closed loop are effectively solved, multi-process quality accurate control is achieved in an auxiliary manufacturing scene, and the production stability and the product consistency are improved.

The invention relates to a hydropower station KKS automatic coding method based on an artificial intelligence large model, and is suitable for the field of water conservancy and hydropower engineering. The method comprises the following steps: acquiring multi-source data of each hydropower station component from a hydropower station BIM model, wherein the multi-source data comprises geometric parameters, attribute data and unstructured function description of the component; carrying out standardization processing on geometric parameters and attribute data of the hydropower station components, extracting keywords from unstructured function description based on a domain dictionary, and forming multi-source features of the hydropower station components; the multi-source features of the hydropower station components are input into the fine-tuned large language model, and the large language model is combined with the KKS coding knowledge graph to output KKS codes of the hydropower station components; according to the invention, based on the multi-source data of the hydropower station component, KKS automatic coding is realized through combination of the large language model and the KKS coding knowledge graph, and the coding efficiency and accuracy are improved.

Examples described herein generally relate to alerting metric baseline behavior change. The examples include performing at least one of a radial basis function (RBF) kernel procedure and an autoencoding procedure for a time-series data; determining whether one or more change points occur in a seasonal pattern of the time-series data based on at least one of the RBF kernel procedure and the autoencoding procedure; and transmitting, to a user, an alert indicating the one or more change points based on a determination that the one or more change points occur in the seasonal pattern of the time-series data.

The utility model discloses an automatic coding system, which comprises a BCMU module and N BMU modules, each BCMU module comprises a first output circuit and a first input circuit, the input end of the first output circuit is connected with the output end of an upper computer, the output end of the first output circuit is electrically connected with the input end of the first BMU module through a hard wire, and the output end of the first output circuit is electrically connected with the input end of the second BMU module through a hard wire. The output end of the Nth BMU module is electrically connected with the input end of the first input circuit through a hard wire, the input end of any one of the rest BMU modules is connected with the output end of the previous BMU module through a hard wire, and the output end of the first input circuit is connected with the input end of the upper computer. Therefore, a communication loop does not need to participate in coding, coding can be carried out only through a hard wire, the problem of high cost is effectively solved, an automatic coding system carries out address coding through transmission of PWM signals, and the anti-interference capability is effectively improved.

The present application discloses a system and encoding / decoding method suitable for DNA storage of PB-level data. The data storage system includes multiple DNA clusters. The DNA cluster contains a data chain formed after binary data encoding, an XOR redundant chain generated by the data chain, an address chain of the DNA cluster at the storage system location, a basic information chain of the stored file, and a redundant chain generated by the XOR of the address chain and the file information chain. When a save operation is performed on a file with a preset suffix, a user-mode monitoring program receives an execution instruction and copies the file to a working directory, and encodes or decodes the file according to the file suffix. The result of the encoding or decoding operation is copied back to the original file directory. The present application enables the total capacity of the DNA database to reach above the PB level, allowing DNA storage to realize the application potential of high data density. At the same time, it can realize the automatic encoding of binary data and the automatic decoding of base sequences, streamline and automate the entire encoding and decoding process, and facilitate subsequent data management and archiving.

The application discloses an intelligent network connection terminal multi-attack intrusion detection method based on OTA signature update, first injects multi-type combined attacks into an ICTs platform, then performs signature update based on OTA upgrade, next designs a CNN IDS based on automatic coding design, and finally realizes classification of attack modes after training. The application improves attack detection success rate and reduces calculation cost.

The application provides a knowledge extraction method and system based on prompt learning, embedding obtained unstructured text data to obtain a cache vector value; embedding a homogeneous prompt string to obtain a homogeneous prompt symbol vector value, and embedding a heterogeneous prompt character string to obtain a heterogeneous prompt character vector value; splicing the cache vector value, the homogeneous prompt symbol vector value and the heterogeneous prompt character vector value to obtain a spliced vector, taking the spliced vector as a cache vector value of a pre-training language model; adopting a regular matching method to obtain structured data from text data generated by the pre-training language model; the application uses automatically encoded prompt characters, automatically learns a potential semantic representation of a label, and solves a knowledge extraction problem in a general way through a generative large-scale pre-training language model, thereby improving the precision and efficiency of knowledge extraction.

The invention discloses a method and a device for realizing user-defined data directory coding based on online configuration. The method comprises the following steps: configuring a directory dictionary to define business attribute fields and enumeration code values required by coding, and supporting manual input or interface import; a coding rule is dynamically constructed through a visual interface and is formed by flexibly splicing a plurality of code segments such as business fields, sorting codes, dates, serial numbers and the like; setting a header, a screening condition and operation item display of the directory list on line; the coding rule is bound to the whole process of auditing, publishing, portal displaying, changing and offline of the resource catalog, and automatic coding generation is achieved; when the rule is changed, historical codes are reserved to ensure the continuity of stock data, and a new rule is only applied to a newly added instance. Zero code management is realized through template online configuration, multi-version parallel and multi-scene adaptation are supported, the customization cost is remarkably reduced, and the flexibility, readability and retrieval efficiency of a data directory are improved.

The present application relates to the technical field of data processing, and especially to an automatic coding intelligent agent control system and method for multi-task scenarios, comprising a data acquisition module, a coding processing module, a quality evaluation module, a strategy optimization module, an execution control module, a defect traceability module, a parameter correction module and an iterative optimization module; the quality evaluation module is used for calculating the quality deviation index of each process core quality index based on a unified feature vector; the strategy optimization module is used for optimizing each process parameter regulation strategy by fusing multi-source information. The present application breaks the limitation of traditional single process coding, effectively avoids cross-process data representation distortion, significantly improves the coding accuracy and data link integrity of multi-process linkage control; has the functions of integrating data coding, quality correlation and parameter iteration, effectively solves the problems of insufficient generalization and closed loop loss of traditional systems, and assists in realizing multi-process quality accurate control in the manufacturing scene, improving production stability and product consistency.

A wireless device (10) measures Channel State Information, CSI, data for a wireless channel between the wireless device (10) and a node (100) of the wireless communication network. Further, the wireless device encodes the CSI data by an encoder part of an machine-learning based autoencoder. Further, the wireless device (10) applies a mask to the encoded CSI data. The mask defines unmasked data elements and masked elements of the encoded CSI data. The wireless device (10) then transmits the encoded CSI data excluding the masked data elements to the node (100).

The invention relates to the technical field of automatic coding, in particular to a one-object-one-code system-oriented unique code automatic coding method and device, and the method comprises the steps: determining a matched character space according to a unique code character demand parameter and an actual application parameter required by a user, screening out a matched target sub-character space, and carrying out the automatic coding of a unique code. Carrying out cyclic coding operation on current space parameters, parameters of all characters used for constructing a character space and unique code character demand parameters to obtain a character cyclic coding result, obtaining time, an actual application scene and actual use time in combination with corresponding characters, and analyzing to obtain a unique code required by a user; the uniqueness of the unique code is guaranteed from the source, the coding length is reduced, the density of the formed unique code is reduced, and the definition of the jet-printed unique code is guaranteed, so that the scanning accuracy and efficiency of the unique code are improved, and the safety management and control of full-link traceability (traceability) of articles / products based on the jet-printed unique code are improved.