14 results about "String generation" patented technology

The invention discloses a label identification method and device based on filtering character string generation, and belongs to the technical field of wireless radio frequency identification. The method comprises the steps that a label list is set, a set of filtering character strings are generated through a filtering character string generation algorithm, and each filtering character string corresponds to a label in the label list; sending a Select command to the labels to select all the labels containing the filtering character strings in the EPC, and calculating the characteristic character strings of the labels; according to a selection label of the feature character string, performing label checking by sending a Query command, and determining that the label state is a stay label or a leave label; and selecting all tags which are matched with the filtered character string but do not contain the feature character string, sending a Query command to carry out standard checking operation, and collecting a new tag EPC. According to the invention, possible conflicts in the tag identification process can be reduced, and the identification efficiency and accuracy are effectively improved.

A computer-implemented method comprising: generating, based on a plurality of candidate output tokens generated by a large language model, LLM, a plurality of candidate token embeddings, respectively and generating, based on at least one string describing prohibited content, at least one content embedding; comparing the candidate token embeddings with the at least one content embedding to determine for each candidate output token a similarity score indicating similarity between the candidate output token and the prohibited / unwanted content; for each candidate output token, generating, based on the similarity score and based on a selection probability assigned by the LLM to the candidate output token, an output score; and selecting, based on the output scores, a candidate output token for output by the LLM.

This computer system receives, as an input, a character string in which at least one position is masked, holds information on a generation model that outputs a probability distribution for each character at the masked position, receives the input of a target character string, generates a plurality of verification character strings in which one position of the target character string is masked, inputs the plurality of verification character strings into the generation model, acquires the probability distribution for each of the plurality of verification character strings, determines a mutation position of the target character string on the basis of the probability distribution, and determines a character at the mutation position on the basis of the probability distribution acquired by inputting a masked character string in which the mutation position of the target character string is masked into the generation model, thereby generating a mutated character string.

A healthcare computer system, the computer system comprising a communications module, a string generation module, a one-way function module and an anonymised data generation module. The communications module is configured to receive one or more healthcare data packets, each healthcare data packet including: data pertaining to one or more medical analytical tests performed on a sample; a sample identifier, identifying the sample; and a timestamp, indicating when the analytical test(s) was performed. The string generation module is configured to generate a string based on the sample identifier and the timestamp. The one-way function module is configured to apply a one-way function to the generated string to generate an anonymised sample identifier. The anonymised data generation module is configured to generate an anonymised healthcare data packet including the data pertaining to the one or more medical analytical tests and the anonymised sample identifier.

This invention relates to inference guidance. [Solution] The computer implementation method includes the steps of: generating a plurality of candidate token embeddings based on a plurality of candidate output tokens generated by a Large-Scale Language Model (LLM); generating at least one content embedding based on at least one string describing prohibited content; comparing the candidate token embeddings with the at least one content embedding to determine a similarity score for each candidate output token indicating the similarity between the candidate output token and the prohibited / undesirable content; generating an output score for each candidate output token based on the similarity score and the selection probability assigned to the candidate output token by the LLM; and selecting a candidate output token to be output by the LLM based on the output score.

This invention provides a task planning and execution method for laboratory automation, applicable to the field of laboratory automation technology. The method includes: decomposing received user input text using a preset large language model to generate standardized service commands; parsing the standardized service commands to extract command strings conforming to a preset service command format; obtaining intent recognition results matching the command strings and user input text using preset keyword matching rules; and modifying the command strings according to the intent recognition results to generate a list of commands to be executed, for task planning and execution. This invention also provides a task planning and execution device, equipment, storage medium, and program product for laboratory automation.

A code obfuscation tool has been created to safely rename strings within metadata sections of an executable file or binary to obscure program functionality and structure that may be revealed by class metadata in the binary. The code obfuscation tool parses metadata sections of the binary that have references to metadata that can be potentially renamed safely and locates the corresponding strings. The code obfuscation tool identifies from predetermined metadata sections metadata that is unsafe to rename. The code obfuscation tool evaluates each string that is a candidate for renaming against heuristics-based renaming rules and the determined unsafe strings to identify strings that are safe to rename. The code obfuscation tool generates a new name for each string determined as safe to rename based on renaming constraints. The code obfuscation tool creates a mapping structure that tracks renaming of strings and uses the mapping structure for consistent renaming of string.

Provided are a character input device, a character input method, and a recording medium that enable appropriate judgment and evaluation of a user's knowledge, abilities, etc., in a written test administered using CBT. A first character string acquisition unit acquires a first character string based on an input character string. A similar character extraction unit extracts similar characters with similar character shapes from characters belonging to the first character string. A second character string generation unit generates a second character string by replacing some or all of the characters belonging to the first character string with the similar characters extracted by the similar character extraction unit. A conversion candidate output unit then outputs the first character string and the second character string as conversion candidates for the input character string.

The invention discloses a reflection technology-based CAD model total element scripting method and system. The method comprises the following steps of: configuring a CAD secondary development reflection interface; obtaining a CAD type definition, and calling a configured CAD secondary development reflection interface; determining a target scripting language according to a scripting language supported by CAD, and converting the acquired type definition into a code according to grammar of the target scripting language; the CAD model data are traversed, the generated conversion codes are called according to the object type, multiple sections of script character strings, head character strings and tail character strings are combined, and the traversed CAD model data are total element data and comprise geometric features, parameters, rules and attributes; and generating a script file according to the multiple sections of script character strings, the head character string and the tail character string. According to the method, the CAD secondary development reflection interface is configured to realize automatic generation of the conversion code based on the reflection technology, so that a large amount of manual coding work is avoided; the generated script file considers non-geometric feature data and can contain total element information of the CAD model.

The invention relates to the field of information security, in particular to a multi-party ECDSA signature generation method and system oriented to a universal trusted execution environment, and the method comprises the steps: introducing an efficient structured reference character string generation algorithm in a pre-calculation stage, and guaranteeing that a plurality of contributors generate a structured reference character string in a cooperative manner while generating the structured reference character string; and the validity of the structured reference character string generated by the previous contribution value can be verified. In the key generation stage, polynomial commitment is introduced to realize a verifiable secret sharing function. In the signature generation stage, a multiplication triple protocol of secure multi-party calculation is introduced to improve the multiplication efficiency in the share sharing process. And finally, an efficient zero-knowledge proof protocol is designed to ensure that each reference enclave participating in signature really has part of signature information generated by the reference enclave, so that the risk of leakage of a private key of a single reference enclave is effectively avoided.

This formal language conversion system comprises: a formal language conversion means that determines an element to be extracted from formal language data that describes an operation that can be executed by an agent that is to be caused to operate according to a work plan, a state of an operation environment of the agent, and a target state of the operation environment, and extracts the element that is determined from the formal language data to generate a character string; an automatic planning means that executes an automatic plan for generating a work plan on the basis of the generated character string, and determines whether an executable work plan has been generated; and an automatic plan evaluation means that, when it is determined that an executable work plan has not been generated, identifies a cause for why an executable work plan has not been generated, and updates the element to be extracted from the formal language data on the basis of the identified cause.

Generate a secret random number that follows a discrete Laplace distribution without approximation. The secret computing device (1 i ) generates a masked value [r] of a random number r that follows a discrete Laplace distribution with parameter α. The bit string generation unit (11) generates a masked value [b0] of a random number bit b0 that follows a Bernoulli distribution with probability (1-α) / (1+α), and masked values [b1], …, b N of random number bits b1, …, b N that follow a Bernoulli distribution with probability (1-α), respectively, to form columns of masked values [b0], [b1], …, [b N . The absolute value determination unit (12) obtains the masked value [L] of the position L that is set to 1 for the first time when observing from the beginning among the random number bits b0, b1, …, b N . The code determination unit (13) obtains the result [L·s] obtained by multiplying the masked value [L] by a random code s as the masked value [r] of the random number r.

The present invention relates to a method, system, device and storage medium for generating an anti-counterfeiting code from a product number, and belongs to the technical field of anti-counterfeiting code generation methods. The method comprises step S1, generating a unique number P for the product number according to a predetermined rule, and taking a value N for the product sequence number within a predetermined length range; step S2, performing an AES encryption operation on the product number P and the product sequence number N, and obtaining an authentication code after a modulo algorithm; step S3, combining the product number, the product sequence number and the authentication code into a plain code; step S4, performing a full code conversion on the plain code to obtain an anti-counterfeiting code array; step S5, converting the anti-counterfeiting code array into an anti-counterfeiting code; the system comprises a character string generation module, an authentication code generation module, a plain code generation module, an anti-counterfeiting code array generation module, and an anti-counterfeiting code generation module; the device comprises a memory and a processor; a computer program is stored on a readable storage medium, and when executed, the steps of the method are implemented; the encryption strength is high and the program is not easy to crack.

The invention relates to the field of software testing, and particularly provides a mind map multi-branch analysis and Excel intelligent filling method and device.The mind map multi-branch analysis and Excel intelligent filling method comprises the following steps that S1, a win32com component is used for being connected with a MindManager process to process a single file; s2, scanning all. Mmap files under a specified directory according to a file batch processing mode; s3, for a large model integration layer, adding an LLM processing module after a feature character string generation stage, and appointing a used LLM type and a corresponding API key through a configuration file; and S4, retaining the original format and data of excel through a bottom-layer operation non-destructive write-in mechanism of an openpyxl library by adopting a dynamic column positioning technology and based on field name matching. Compared with the prior art, the method has the advantages that the test efficiency and accuracy of converting the mind map case into the excel-format case by a tester can be greatly improved, so that the requirements on high efficiency and comprehensiveness of test case generation in modern software development are met.