2129 results about "Template based" patented technology

Techniques are described for a computing system configured to obtain a plurality of candidate logs for a plurality of layers of a computing infrastructure. The computing system may, for each candidate log of the plurality of candidate logs, map the candidate log to a log template of a plurality of log templates, wherein each log template to which a candidate log is mapped is a mapped log template. The computing system may rank mapped log templates based on properties of the mapped log templates. The computing system may select, based on the ranking, one or more candidate logs as critical logs. The computing system may output at least one of (1) an indication of the critical logs to determine a potential root cause associated with a performance issue of a network application or (2) an indication of the potential root cause associated with the performance issue of the network application.

The invention discloses a cross-border e-commerce compliance intelligent auditing platform and a multi-language contract analysis method, and relates to the field of cross-border contract compliance auditing. In the multi-modal data access step, customs codes, laws and regulations and other multi-source data are collected, and 18 kinds of language contract texts are analyzed; in the cross-language semantic alignment step, a knowledge graph is constructed, and multi-language legal concept mapping is achieved; in the compliance risk reasoning step, a rule engine and an agent cooperatively check a contract, and the compliance conclusion confidence is calculated; the dynamic risk assessment step adopts an LSTM network to analyze historical data and predict a risk trend; in the multi-language report generation step, a multi-format bilingual or multilingual report is generated based on a template engine, encrypted and archived. According to the invention, cross-border contracts are audited efficiently and intelligently, dynamic adaptation laws and regulations are analyzed in multiple languages, compliance risks are identified accurately, and a multi-language report is generated quickly; therefore, the checking efficiency is improved, the manual workload is reduced, the compliance risk is reduced, and the enterprise cross-border business competitiveness and the risk response capability are enhanced.

The invention relates to the technical field of continuous integration and continuous delivery, and discloses a Jenkins continuous integration method based on Kubernetes. According to the method, a Jenkins server is deployed in a Kubernetes cluster to serve as a control plane, a construction environment is created through a preset multi-container Pod template, and a Pod containing a plurality of containers is dynamically created based on the Pod template, so that each container executes different construction tasks. Containers in the Pod realize collaboration through sharing a network namespace and a storage volume, and a Jenkins server monitors task execution states of the containers in the Pod and performs dynamic scheduling according to task priorities and cluster load states. And after the task is completed, automatically destroying the Pod and releasing cluster resources. According to the method and the device, dynamic expansion and contraction of a construction environment and efficient parallel execution of tasks are realized, the problem that a traditional Jenkins static resource pool is difficult to deal with load changes is solved, the resource utilization rate is improved, the expandability of the system is enhanced, and an efficient and reliable solution is provided for an enterprise-level continuous integration system.

Implementations utilize a smaller LLM to generate content responsive to a user query and cause a portion of the generated content to be rendered as an immediate response to the user query. Implementations further utilize a larger LLM to generate content that starts with the portion of the generated content and that includes a refined portion succeeding the portion of the generated content. The refined portion can be rendered succeeding the portion of the generated content. In some implementations, instead of using the smaller LLM, alternatively, the portion of the generated content rendered as the immediate response can be generated based on a default text string or a template, where the template can be determined / selected from a plurality of predefined templates based on a natural language understanding of the user query.

The invention belongs to the field of artificial intelligence and finance, and relates to a text classification method, which comprises the following steps: preprocessing an original text data set, labeling classification labels to obtain a labeled text data set, inputting a training set into a large language model for keyword extraction to obtain a candidate keyword set, cleaning the candidate keyword set to obtain a classification keyword set, constructing an instruction template based on the classification keyword set, and inputting the training set and the instruction template into a large language model to obtain a prediction classification result; and based on a prediction classification result and a loss function between the classification labels, performing fine tuning on the large language model to obtain a fine tuning model, evaluating that the fine tuning model is qualified to obtain a text classification model, and inputting the to-be-classified text into the text classification model for classification. The invention further provides a text classification device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the tagged text data set can be stored in a block chain. According to the method, the text classification accuracy and stability can be improved.

Systems and methods are described for video coding using generalized bi-prediction. In an exemplary embodiment, to code a current block of a video in a bitstream, a first reference block is selected from a first reference picture and a second reference block is selected from a second reference picture. Each reference block is associated with a weight, where the weight may be an arbitrary weight ranging, e.g., between 0 and 1. The current block is predicted using a weighted sum of the reference blocks. The weights may be selected from among a plurality of candidate weights. Candidate weights may be signaled in the bitstream or may be derived implicitly based on a template. Candidate weights may be pruned to avoid out-of-range or substantially duplicate candidate weights. Generalized bi-prediction may additionally be used in frame rate up conversion.

A method of encoding or decoding video data comprises: for each respective intra prediction mode of a plurality of intra prediction modes in a most-probable mode (MPM) list: generating, based on reference samples for a template region and using the respective intra prediction mode, prediction samples for the template region; and determining a cost for the respective intra prediction mode; determining a first intra prediction mode and a second intra prediction mode in the MPM list having lowest costs; determining a preliminary prediction block for the first intra prediction mode and a preliminary prediction block for the second intra prediction mode; generating a prediction block based on a fusion of the preliminary prediction blocks weighted according to a weight for the first intra prediction mode and a weight for the second intra prediction mode.

The embodiment of the invention provides an access control strategy construction method and device, electronic equipment and a storage medium. The access control strategy construction method comprises the following steps: determining access control elements and attributes thereof of an application based on an acquired resource access scene; based on the access control elements and the attributes thereof, an access control strategy template is created according to different access control scenes, and the access control strategy template comprises preset access control elements and attributes; selecting the access strategy template based on a service demand and assigning a value to the attribute to create a corresponding access control strategy; and performing matching calculation on the access control strategy and the intercepted resource access request based on a strategy calculation engine, and if matching succeeds, executing a corresponding strategy action. Through the steps, access control configuration is more convenient and easier to understand, and access control is more flexible.

Provided is a process including: obtaining, with a computer system, access to a code base; decomposing, with the computer system, the code base into parts; classifying, with the computer system, the parts according to content type; selecting, with the computer system, processing templates based on the content types, with at least some different content types having different selected processing templates; and generating natural language documentation for the parts, with one or more generative language models, using the processing templates selected for the parts.

The invention provides a target tracking method and system based on a grouped attention feature extraction network, and the method comprises the steps: obtaining a template and search features based on a template and a search image through employing the grouped attention feature extraction network; learning local areas of the template target image features and the search image features, and aggregating to obtain target information; splicing the template with the search features to obtain the input of the self-attention encoder in the asynchronous interaction stage; the fused features are combined with a prediction head for calculation, a classification regression result is obtained, and a target is predicted according to the classification regression result; training the target tracking model in combination with the large-scale data set to obtain a trained target tracking model, and performing accurate target tracking on the target by using the trained target tracking model; according to the multi-scale feature extraction network based on Transform, sequential local and global information interaction in the windows and between the windows is promoted, and the optimal balance between performance and speed is achieved.

The invention relates to the technical field of chip verification, and discloses a chip verification method, test equipment and a chip verification system.The method comprises the steps that a template file is built, a verification environment and a test case are generated based on the template file, a configuration file is obtained, and parameters in the verification environment and the test case are updated through parameters in the configuration file; according to the method, the verification environment and the test case are updated, the updated verification environment and the updated test case are obtained, regression testing is carried out on the chip on the basis of the updated verification environment and the updated test case, the test result is obtained, the verification environment can be rapidly generated on the basis of the template file, parameters can be rapidly replaced, and the chip testing efficiency is improved.

Embodiments of the present disclosure provide a decoding method, an encoding method, and a storage medium. In the decoding method provided in embodiments of the present disclosure, first transform is performed on first transform coefficients of a current block based on a transform set corresponding to a first intra prediction mode, and the first intra prediction mode is designed to be any one of: an intra prediction mode derived from a decoder side intra mode derivation (DIMD) mode for a prediction block of the current block, an intra prediction mode derived from the DIMD mode for an output vector of an optimal matrix based intra prediction (MIP) mode for predicting the current block, an intra prediction mode derived from the DIMD mode for reconstructed samples in a first template region adjacent to the current block, and an intra prediction mode derived from a template based intra mode derivation (TIMD) mode.

The invention discloses a dialogue type enterprise knowledge question answering method and device, a storage medium and electronic equipment, and relates to the technical field of data analysis, and the method comprises the steps: obtaining user request information; obtaining a corresponding channel; reconstructing the question content to obtain the reconstructed question content; performing vectorization processing on the reconstructed question content to obtain vectorization information of the reconstructed question content; obtaining a plurality of first FAQ knowledge and second FAQ knowledge; obtaining a plurality of pieces of first document block knowledge and second document block knowledge, and obtaining documents corresponding to a plurality of document blocks; obtaining a corresponding prompt word template based on the dialogue intention and the channel; and constructing a large language model, and sorting to obtain corresponding answer information. Based on the question content of the user, the dialogue intention is obtained through analysis, the knowledge base is matched, the answer information is obtained through arrangement, the user question is automatically answered, and the method has the advantages of being simple, efficient and high in real-time performance.

The invention discloses an electrical work ticket intelligent generation method and device, a medium and equipment in the technical field of power systems, and aims to solve the problems of serious module decoupling, dependence on manual connection and insufficient intelligent generation capability in the prior art. The method comprises the following steps: generating a required digital knowledge base and an electrical work task description generation work ticket based on a pre-constructed work ticket by utilizing a multi-model collaborative generation architecture; the multi-model collaborative generation architecture comprises a rule driving module used for calling a corresponding template based on task element matching; the task execution unit is used for executing a specific subtask according to a pre-deployed lightweight model or rule engine; and the large language model is used for performing semantic understanding and reasoning according to the electrical work task description, calling the rule driving module and the task execution unit according to a semantic understanding and reasoning result, and generating a work ticket in combination with a digital knowledge base required by work ticket generation. The method has both the accuracy of structured knowledge recognition and the flexibility of natural language generation.

The invention provides an environment detection method and system based on a sample target detection model. The method comprises the following steps: synchronously acquiring an environment image, a video stream and physical parameters by using a multi-mode sensor; decomposing the data into image features and environmental parameter components through a dual-time sequence control signal, and realizing space-time alignment by adopting a linear phase filter; constructing a foreground region template based on the depth information, and generating target recognition feature representation containing an abnormal blurred target; adversarial training is carried out on the lightweight target detection network in combination with a transfer learning strategy, the network integrates convolutional features and a Transform attention mechanism, and the weight is dynamically adjusted through environmental parameters; fusing a target result and sensor data in real-time detection, and inputting a decision tree model for risk grading; and after the early warning is triggered, reconstructing a false detection sample through an online learning mechanism and iteratively optimizing the model. The system correspondingly comprises a multi-modal data acquisition module, a data enhancement and annotation module, a model training module, a real-time detection and fusion module and an early warning and optimization module. According to the invention, through multi-source data fusion, dynamic data enhancement and an adaptive compensation mechanism, the small target detection precision, the environmental adaptability and the real-time early warning capability are significantly improved.

The invention provides a Text2SQL generation method and system driven by a large language model, and the method comprises the steps: recognizing key entities and relationships in a natural language question through the large language model, and carrying out the construction to obtain a query graph; constructing a hierarchical graph representation model based on the database mode of the target database; searching candidate sub-image sets which have the same structure as the query graph and are in semantic association with the query graph from the constructed graph representation model; and constructing a structured Prompt template based on the candidate sub-image set and the user question, generating an initial SQL statement, and outputting a final query result after grammar and semantic detection correction. According to the method, a traditional database is converted into the graph knowledge base, so that the SQL generation accuracy and performance are improved; guiding the large model to generate an SQL (Structured Query Language) meeting business requirements through knowledge graph storage and retrieval table and column information; and the accuracy of the SQL is continuously optimized by utilizing a self-adaptive feedback mechanism, so that the method is particularly suitable for a large-scale complex query scene, and self-improvement and customization of the model are realized.

The invention discloses a human resource data natural language query and SQL generation method and system, and relates to the technical field of SQL generation, and the method comprises the steps: preprocessing a natural language query text input by a user, and constructing a query semantic tree; traversing the query semantic tree to generate a candidate entity set, determining an unambiguous entity through a three-layer ambiguity resolution mechanism of semantic scoring, service verification and cross validation, identifying a composite intention, disassembling the composite intention into a sub-intention sequence, and generating an SQL operation instruction set in combination with a preset SQL operation mapping rule; based on the SQL operation instruction set and the human resource data association model, determining a data table set and an association path, generating a dynamic calculation logic and structured condition expression, and constructing a structured query skeleton; according to the method, the personalized SQL template is dynamically generated according to the query skeleton, after filling, grammar verification, strategy optimization and logic consistency verification are performed, and the optimized SQL statement is output, so that the query accuracy and performance are remarkably improved.

An intelligent legal document generation and review system and associated methods are disclosed. The system comprises one or more processors coupled to memory storing instructions to provide a user interface for receiving user input, execute a natural language processing subsystem to extract relevant information, access a legal rules database, store document templates, and execute an AI algorithm. The AI algorithm retrieves a relevant template based on user input and extracted information, populates the template to generate a customized legal document, and stores the document. An attorney feedback loop allows attorneys to provide feedback that the AI algorithm learns from to improve document generation. The AI algorithm collaborates with attorneys to revise and finalize documents based on the feedback. The system streamlines document preparation, automates complex tasks, and provides expert guidance to help users adhere to legal requirements across jurisdictions.

The invention discloses a legal instrument generation method and device, electronic equipment and a storage medium, and relates to the technical field of legal instrument generation or other related fields, and the method comprises the steps: receiving first language case information and a legal instrument generation demand; analyzing the first language case information through a semantic analyzer corresponding to the first language to obtain case factors of the target case, and translating the first language case information through a translator to obtain second language case information; querying a target legal knowledge base based on the case factors to obtain a query result; and determining a target document template based on the legal document generation demand, and generating a target legal document based on the target document template, the second language case information, the case factors and the query result. According to the method and the device, the technical problem that the generated legal document is inaccurate and even not compliant due to the fact that professional legal terms and contexts cannot be accurately understood and converted in the cross-language generation process of the legal document in related technologies is solved.

Template based derivation of intra sub-partitioning (ISP) mode is used to improve coding efficiency of intra predicted coded video blocks. The template is formed from surrounding reconstructed top and left samples. In one embodiment, ISP is performed independently from template based intra mode derivation (TIMD). The derivation of an intra sub-block partition mode is determined from template pixels using a current prediction mode for either an upper or left template. In another embodiment, ISP and TIMD are combined. In a further embodiment, a flag is signaled to communicate template based intra mode derivation and intra sub-block partition usage.

Systems, methods, and instrumentalities are disclosed for template based cross component linear model / multimode linear model (CCLM / MMLM) adjustment. In an example, a device, such as a video decoding device, or a video encoding device, may obtain a prediction model for predicting a coding block. The device may select an adjustment model, from multiple adjustment models, for adjusting the prediction model. The device may adjust the prediction model based on the selected adjustment model. The device may process (e.g., encode and / or decode) the coding block based on the adjusted prediction model.

The invention relates to the technical field of intelligent manufacturing of aeronautical parts, and discloses an aeronautical part technological procedure reasoning method and system based on a template, and the method comprises the steps: firstly obtaining and storing technological characteristics and geometric structure characteristics of a to-be-machined part; secondly, encoding the feature data of the to-be-processed part, the feature data of the historical processing part, the technological procedure template data and the technological knowledge data which need to be used in a One-hot mode; then, according to the process characteristics and geometric structure characteristics of the to-be-machined part, a matched process procedure template is obtained through a characteristic-based template matching algorithm, and typical process parameters related to part process procedure compilation based on the process procedure template are obtained through a typical process parameter reasoning decision algorithm; and the matched technological procedure template and the typical technological parameters obtained through calculation are fused, and a part technological procedure is formed and output. According to the method, the required part technological procedure can be quickly and intelligently generated, and the design efficiency of the technological design link in the production process is greatly improved.

The invention relates to an industrial vision adaptive illumination compensation system and method based on Bayesian optimization, and the system comprises an environment perception module which is used for collecting the multi-dimensional environment state data of an industrial site in real time, and collecting an original image; the intelligent preprocessing module is used for enhancing the original image according to the parameter combination output by the Bayesian optimization module to generate an enhanced image; the model reasoning module is used for identifying and detecting the enhanced image through a bimodal algorithm to generate a detection result; the Bayesian optimization module is used for performing objective function calculation to generate an optimization objective score, performing iterative optimization according to the optimization objective score and a historical observation data set, generating a candidate parameter combination, and generating a global optimal parameter and a configuration template based on the candidate parameter combination and a current environment feature; and the industrial interface module is used for transmitting the global optimal parameter, the detection result and the multi-dimensional environment state data to an industrial control system. According to the invention, the efficiency and adaptability of illumination compensation are improved, and the data calculation amount is reduced.

The invention discloses a short message template intelligent identification method and system based on semantic similarity calculation, relates to the technical field of information and communication, and realizes automatic matching of a request short message and a template library through semantic vectorization and similarity calculation; semantic extension, structural constraint and a dynamic feedback mechanism are combined, so that the matching accuracy and robustness are improved; an optimization process driven by a multi-level model and category features is introduced, and an identification-feedback-optimization closed-loop system is formed; the system structurally comprises a semantic modeling module, a similarity calculation module, a dynamic feedback module and a template optimization module, automatic and efficient short message template recognition and updating can be achieved, and the requirements for real-time performance and accuracy in a large-scale application scene are met.

The invention relates to an error collaborative calibration method, system and device based on a high-precision rotary table, and the method comprises the steps: obtaining the installation positioning data of a tilt angle sensor, carrying out the installation offset calibration of the high-precision rotary table, and obtaining an installation parameter set; according to the installation parameter set, controlling the high-precision turntable to carry out partition inclination angle scanning on the inclination angle sensor to obtain calibration response data; performing multi-source error identification on the calibration response data to obtain a collaborative error parameter set; and obtaining a dynamic simulation instruction template according to the tilt angle sensor, and performing instruction construction on the dynamic simulation instruction template and the collaborative error parameter set to obtain a turntable swing instruction set. Tracking errors caused by static calibration parameters can be avoided, and the execution precision of the rotary table in complex motion control is improved.

The invention relates to the technical field of data processing, in particular to a training system and method for a task processing model and a related device, and the system comprises a comprehensive scheduling agent which is used for generating training configuration information, at least one piece of input configuration information and template configuration information based on task description data; the function scheduling agent is used for obtaining constraint information fed back by the scheduled function agent based on each piece of input configuration information; the template agent is used for generating an initial prompt template based on the template configuration information; the comprehensive scheduling agent is also used for adjusting the initial prompt template to obtain a target prompt template based on the at least one piece of constraint information; and the training agent is used for training to obtain a task processing model based on the target prompt template, the training configuration information and the sample set. In this way, intelligent decision making and judgment can be conducted in all links of the task processing model obtained through training, and the training efficiency and the training effect of the task processing model are improved.

The invention provides an air-ground cooperative unmanned aerial vehicle countering signal adaptive generation method and system, and relates to the technical field of unmanned aerial vehicle countering, and the method comprises the steps: obtaining a target unmanned aerial vehicle communication signal, and extracting a feature analysis protocol; a secondary coding structure is adopted, and parameters are optimized by using a genetic algorithm with a composite fitness function; selecting and adjusting an interference waveform template based on the protocol type; executing air-ground collaborative resource optimization allocation, and dynamically allocating power and computing resources by adopting a reinforcement learning algorithm; and controlling the air-ground countering equipment to generate an interference signal. According to the method, the interference effect can be improved, the energy consumption is reduced, the detection resistance is enhanced, and intelligent dynamic allocation of countering resources is realized.

The invention provides a ship trajectory optimization method and system based on a visual language model and multi-modal collaborative decision, and relates to the field of ship trajectory prediction.The method comprises the steps that a trajectory prediction model is established, and a ship trajectory optimization model is established based on the visual language model; establishing a ship trajectory optimization cue word template based on chain thinking; first multi-modal data is obtained, and the first multi-modal data at least comprises a track classification label; generating a basic trajectory prediction result according to the first multi-modal data through a trajectory prediction model; generating second multi-modal data according to the basic trajectory prediction result and the first multi-modal data; and through the ship trajectory optimization model, according to the ship trajectory optimization cue word template based on chain thinking and the second multi-modal data, an optimized trajectory prediction result is generated, and the ship trajectory prediction method has the advantage of improving the accuracy of ship trajectory prediction.

The invention discloses a digital twinning progress tracking and risk pre-control method for hydraulic engineering construction, and relates to the field of hydraulic engineering construction, and the method comprises the steps: obtaining mechanical positioning, material entering and environment monitoring data through a multi-source sensing terminal, and generating a time-space aligned construction situation data set; a progress weight template is activated based on the construction stage identifier, and a dynamic weight vector is generated in combination with the environment data; comparing the construction situation data with the reference model to calculate a comprehensive progress deviation index; when the index exceeds the limit, constructing a resource topological relation graph to generate an elastic scheduling instruction; outputting a derivative risk probability through the risk conduction model and generating an optimized scheduling instruction set; triggering a calibration instruction to feed back a correction parameter according to the execution data; by establishing a three-level calibration mechanism linked with the construction progress, the risk change and the environmental disturbance, layered accurate adjustment of data acquisition, environmental factors and model parameters is realized.

The invention relates to the technical field of computer data processing, provides a cross-border data compliance processing method, device and equipment, and is used for solving the problems of relatively low cross-border data processing efficiency and data processing strategy errors in related technologies. According to the embodiment of the invention, the multi-method domain and regulation knowledge graph is established in advance, laws and regulations of a plurality of regions are summarized, the multi-method domain and regulation knowledge graph can be updated in real time, and the cross-border scene template library and the data label template base library are established according to the multi-method domain and regulation knowledge graph. The cross-border scene template library and the data label template base library can be dynamically updated along with updating of the knowledge graph, and a cross-border gateway can process data by adopting a compliance strategy according to a data cross-border scene through the cross-border scene template library, so that related data management enterprises and institutions efficiently manage data outbound in a compliance manner; through the data label template library, the cross-border gateway can rapidly and accurately carry out data marking work, and the efficiency of data classification processing is improved.