374 results about "First class" patented technology

Techniques are described for a hierarchical caching mechanism enabling efficient cross-region replications. In some embodiments, replication-related information (e.g., key-value pairs) is stored in a particular layout in a binary tree (B-tree) of a file system for replication processing. A hierarchy of caches storing a first type of information (e.g., crypto keys associated with iNodes) may be arranged to match the particular layout in the B-tree to enable efficient parallel processing of a second type of information (e.g., files, file data, or symbolic links), where the replication-related information in the B-tree is partitioned into multiple key ranges for parallel processing. In some embodiments, the caches in different hierarchies may be shared by different parallel-processing key ranges and replication jobs in a file system.

A computer acquires training data including first text, first class information indicating a class mapped to a single word contained in the first text, first position information indicating a position of the single word in the first text, and first range information indicating a range of a first named entity that includes the single word in the first text. The computer executes, based on the training data, machine learning of a machine learning model which is used to estimate, from text, class information, and position information, range information of a named entity included in the text.

System, method, and various embodiments for a request processing system are described herein. An embodiment operates by determining a first sampling rate for each of multiple different types of requests being processed by a first computing landscape, and detecting a change in a performance of a first type of request. The first sampling rate for the first type of request is increased, and a second sampling rate for the first type of request for a second computing landscape responsive is also increased. Results of the tracing corresponding to the increased sampling rates are aggregated, and one or more differences between the first computing landscape and the second computing landscape are identified. An alert to reduce processing of the first type of request is generated based on the aggregated results and the identified one or more differences.

The embodiment of the invention provides a processor core, a processor and a method for the processor. The processor core includes a processing pipeline configured to rename and execute a first instruction including at least one of a first architectural register and a second architectural register, and includes: a first type of physical register configured to be mapped by the first architectural register and configured to store a first type of data; the first type of physical register is configured to be mapped by the first architecture register and configured to store data of a first type, the second type of physical register is configured to be mapped by the second architecture register and configured to store data of a second type, the first architecture register comprises a vector architecture register, the data of the first type stored by the first type of physical register comprises vector data, and the second architecture register comprises a mask architecture register; the second type of data stored in the second type of physical register comprises mask data. The processor core may mitigate processing pipeline stagnation and increase less area.

The invention provides a fault injection method, device and equipment, and the method comprises the steps: obtaining a fault injection command which comprises a command word and fault injection data; if the command word is the command word corresponding to the first type of network card fault, writing the command word and the fault injection data into a target parameter structural body in a specified storage medium; if an IO request sent by the RDMA application to the RDMA network card is received, determining a target command word corresponding to the IO request; and if the target parameter structural body comprises target fault injection data corresponding to the target command word, sending the target fault injection data to the RDMA application so as to analyze the response condition of the target fault injection data based on the RDMA application. Through the technical scheme of the invention, the capability of the RDMA application to cope with the fault of the RDMA network card can be obtained, and the system stability and the data security are improved.

The invention provides a keyword generation model training method, a keyword generation method and a related device, and relates to the technical field of artificial intelligence, in particular to the technical field of large models, keyword generation and the like. The specific implementation scheme is as follows: constructing a first fine tuning instruction based on a first type of samples; the first type of samples comprise a first search sample and a first type of word set comprising at least one first keyword; wherein under the condition that the resources are searched based on the first search sample, the resources expressed by the first keyword at least meet partial search requirements of the first search sample; constructing a second fine tuning instruction based on the second type of samples; the second-class sample comprises a second search sample and a second-class word set comprising at least one second keyword, and the second search sample and the second keyword are constructed based on a preset association relationship; and performing cross training on the initial large model based on the first fine tuning instruction and the second fine tuning instruction to obtain a keyword generation model.

The invention discloses a data processing method and a related device, and relates to the technical field of message queues, a target client requests to carry out target operation on business data of a target theme, a server verifies whether a permission mapping relation matched with a permission authentication request exists in first-class permission data, and if yes, the first-class permission data is sent to the server; the server searches target message queue cluster information matched with the target theme in second-class authority data and sends the target message queue cluster information to the target client, the second-class authority data comprises a plurality of routing relationships, and the routing relationships comprise corresponding relationships between the theme and each message queue cluster in the message queue system; and the target client side executes the target operation in the target message queue cluster according to the target message queue cluster information, so that the flexibility of accessing multiple clusters by each client side is improved through centralized maintenance of authority data by the server side.

The invention provides an intelligent file merging method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence and cloud computing, in particular to the technical direction of big data. According to the specific implementation scheme, first-class files and second-class files are recognized from a to-be-processed file set, the file size of the first-class files is smaller than a target size, and the file size of the second-class files is larger than that of the first-class files; splitting the second class file into a plurality of sub-files; determining a to-be-merged file set based on the plurality of sub-files and the first type of files; and carrying out merging operation on the to-be-merged file set.

The invention relates to the technical field of building information model optimization, in particular to a large-volume BIM model optimization system based on intelligent loading, which comprises a model analysis unit, a function identification unit, a simplified execution unit and a model recombination unit, and is characterized in that the model analysis unit reads an IFC file and separates component data; the function identification unit outputs a decoration component (first class) set, a non-bearing structure (second class) set and a bearing component (third class) set through geometric and semantic dual-channel analysis, the simplified execution unit performs edge folding on the first class, performs vertex clustering on the second class and skips simplification on the third class, and the model recombination unit binds metadata and constructs a dynamic octree index. The problems that a traditional simplification strategy is single and core information is lost are solved, the model loading efficiency and application precision are improved, and the method is suitable for complex building scenes.

A control section is a control section that controls combined printing of a plurality of documents and includes: a first setting processing section configured to set, in regard to a first setting item, which is a setting item included in a first category, from among a plurality of setting items defining content of processing to be performed on the documents, a setting value of the first setting item of any one document from among the plurality of documents for the first setting item of each of the plurality of documents; and a second setting processing section configured to set, in regard to a second setting item, which is a setting item included in a second category that is different from the first category, from among the plurality of setting items, a default value of the second setting item for the second setting item of each of the plurality of documents.

A method for training a large language model, a method for generating a large language model, an electronic device and a storage medium are provided, relating to the fields of large language model, model training, text processing and other technologies. The method for training a large language model includes: training an initial model according to first training data to obtain a first model; wherein the first training data comprises a first type of text; training the initial model according to second training data to obtain a second model; wherein the second training data comprises the first type of text and a second type of text; and performing parameter fusion according to the first model and the second model to obtain the trained large language model.

The invention provides an exception handling method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps of performing first fault injection on a first module of a database system based on a plurality of first scripts, wherein the first scripts are in one-to-one correspondence with first types of database system faults; performing a first test on the first module subjected to the first fault injection to obtain a first test result of the database system corresponding to each first type; determining an alarm triggering condition of each first type based on the first test result of each corresponding database system; and if the performance index of the database system meets the alarm triggering condition of the first type, determining a fault processing strategy of the database system corresponding to the first type according to the first type. According to the invention, the equipment fault can be automatically identified and repaired.

A data platform for managing an application as a first-class database object. The data platform includes at least one processor and a memory storing instructions that cause the at least one processor to perform operations including detecting a data request from a browser for a data object located on the data platform, executing a stored procedure, the stored procedure containing instructions that cause the at least one processor to perform additional operations including instantiating a User Defined Function (UDF) server, an application engine, and the application within a security context of the data platform based on a security policy determined by an owner of the data object. The data platform then communicates with the browser using the application engine as a proxy server.

The invention provides a demand structuring method and device for a sea area low, small and slow sensing system. The method provided by the invention comprises the following steps: constructing a structured template of a sea area low, small and slow sensing system; carrying out instantiation on the structured template; obtaining a first type of missing instances and a second type of missing instances based on the plurality of structured instances; constructing a first class of training samples by taking the first class of missing instances as samples and taking the corresponding structured instances as labels, and constructing a second class of training samples by taking the second class of missing instances as samples and taking the corresponding structured instances as labels; training the initial model by using the first type of training samples and the second type of training samples to obtain a basic model; freezing partial parameters of the basic model, and finely adjusting the parameters by using the first type of training samples and the second type of training samples to obtain a first special model and a second special model; and selecting the target model according to the currently input text, so that the target model outputs a complete structured instance based on the currently input text to improve the modeling precision.

The invention provides a digital simulation interface system of a face satellite attitude and orbit control subsystem, and relates to the technical field of computer simulation. Interfaces are divided into two classes according to attributes, the first class is simulation class interfaces, and the second class is simulation class interfaces; the interface is used for initialization parameter setting, simulation process control, simulation target data acquisition and data interaction of a simulation state, a running log, a model event, energy simulation data, thermal simulation data and environment simulation data of an attitude and orbit control subsystem model; and the second type is a business type interface, and the interface is used for data interaction with other subsystems or the outside in the function operation of the attitude and orbit control subsystem. Definitions of the two types of interfaces can cover all simulation activities of a satellite attitude and orbit control subsystem, meanwhile, the related internal simulation activities and external simulation activities can be distinguished, and interface testing of a satellite digital subsystem model can be systematically carried out with the fewest units.

An information processing device uses a first machine learning model and obtains a first classification result. The information processing device uses a second machine learning model and obtains a second classification result and identifies a first frame, based on the first classification result and the second classification result. The information processing device identifies a first class with a highest degree of certainty in the first classification result for any frame regarded as a reference and identifies a second frame that is immediately before or after the identified first frame. The information processing device determines a series of frames to be invalid when a predetermined condition is satisfied by a relationship between a first degree of certainty of the first class in the first classification result for the first frame and a second degree of certainty of the first class in the first classification result for the second frame.

A method includes scanning a network having a first and second host, obtaining, via the scanning, a first and second type information of the first and second host, respectively, the first or second type information including a device category, obtaining, via the scanning, a first and second scaling factor of the first and second host, respectively, calculating, a first criticality score of the first host based on the first type information and the first scaling factor, calculating a second criticality score of the second host based on the second type information and the second scaling factor, calculating a first host risk score (HRS) for the first host based on the first criticality score, calculating a second HRS for the second host based on the second criticality score, and applying a security patch on the first host prior to the second host first HRS is higher than the second HRS.

This application provides a code digest generation method, model, apparatus, medium, and device, relating to the field of artificial intelligence technology. The method includes: determining an application programming interface (API) information graph corresponding to the code to be processed, wherein the node types in the API information graph include: a first type, and at least one of a second type and a third type, wherein the associated information of the first type of nodes is the application programming interface, the associated information of the second type of nodes is variables, and the associated information of the third type of nodes is API description information; encoding the API information graph to obtain API encoding features of the code to be processed; and determining a code digest of the code to be processed based on the API encoding features and target features of the code to be processed, wherein the target features include: source code encoding features corresponding to the code to be processed, or source code encoding features and AST encoding features corresponding to the code to be processed. This application embodiment can improve the semantic integrity of the code digest.

The embodiment of the specification provides a method for generating a contract knowledge graph, comprising: inputting each paragraph contained in a contract text into a large model respectively, and making the large model extract a first type of entity corresponding to a clause element. Inputting any first entity belonging to the clause element and a target paragraph to which the first entity belongs into the large model, and making the large model analyze the first entity based on the target paragraph to obtain a second type of entity corresponding to a clause description. Based on the first type of entity, the second type of entity and a third type of entity corresponding to a single paragraph, a multi-level contract knowledge graph is generated. The root level of the contract knowledge graph corresponds to the first type of entity, and in each level, in addition to the connection between the corresponding entities of adjacent levels, the corresponding entities in the root level are also connected.

The application discloses a software development package compiling method and device, and relates to the technical field of computers. A specific implementation of the method comprises the following steps: performing encapsulation based on a second programming language on a first type of module of any core component in a software development package, extracting a header file of the first type of module and a header file of a second type of module after the encapsulation to generate a common umbrella header file of the core component; and after compiling core component source code and upper layer component source code in the software development package into an executable file, processing the common umbrella header file of any core component in the software development package, so that the common umbrella header file only contains declaration content configured in advance for the core component. The implementation can effectively reduce the risk of core code leakage.

A storage controller (for example, a storage control unit 123) can execute log creation processing of, when a write request is processed and control information or cache data is updated, adding a header to the updated data to create an update log and storing the update log in a log buffer. In the log creation processing when first-type control information (normal control information) is updated, the storage controller adds a log header to each piece of updated first-type control information to create an update log (normal log 132), and in the log creation processing when second-type control information (cache directory) is updated, the storage controller creates one consolidated log (consolidated log 137) as an update log related to a plurality of pieces of second-type control information.

The present invention proposes a drone operation network and lightweight data encryption and authentication method. The drone operation network includes a central control unit and at least one node. The central control unit is configured to broadcast a public generator and the ID of each node in the drone operation network to each node, and transmit its corresponding private information to each node. When a sending node needs to send information to a target node, the sending node is configured to generate a first-class send message based on the plaintext to be sent, the ID of the target node, the public generator, and the ID of the sending node, and transmit the first-class send message to the target node. The target node is configured to determine whether the first-class verification value is qualified based on the ID of the sending node and first verification identification information. If qualified, the target node decrypts the first-class ciphertext to obtain the corresponding plaintext. By performing encryption verification, the security of the communication environment is guaranteed.

The invention provides a question reply method and device and electronic equipment, and relates to the technical field of artificial intelligence such as human-computer interaction, natural language understanding, large models and light weight. The method comprises the steps of obtaining a to-be-processed question input by a user in a current session; a plurality of alternative models associated with the to-be-processed problem are utilized to process the to-be-processed problem in parallel to obtain a plurality of candidate replies, the alternative models comprise at least one first-class model and at least one second-class model, and the parameter scale and / or single call cost of the first-class model are / is lower than that of the second-class model; determining a target model in the plurality of alternative models according to behavior information of the user for the plurality of candidate replies; and during the duration of the current session, generating corresponding reply contents for the input subsequent questions by using the target model. According to the method, the target model conforming to user preferences can be rapidly and clearly determined by simultaneously presenting the behavior information of the multiple candidate replies to the multiple alternative models by the user, and the interaction turns and the clarification cost are reduced.

In an implementation, a data storage method comprises obtaining a write request by a processing apparatus, where the write request includes first data to be written. Determining based on at least one of an access feature and a service requirement of the first data, a first category of the first data at a current moment; and indicating the storage apparatus to store the first data in a first type of storage unit. The first category indicates a programming rate requirement of the first data, and the first type is determined based on the first category.

The application provides a demand structuring method and device for a sea area low-small-slow perception system. The method provided by the application comprises the following steps: constructing a structured template of the sea area low-small-slow perception system; instantiating the structured template; obtaining first-type missing instances and second-type missing instances based on a plurality of structured instances; constructing first-type training samples by taking the first-type missing instances as samples and corresponding structured instances as labels, and constructing second-type training samples by taking the second-type missing instances as samples and corresponding structured instances as labels; training an initial model by using the first-type training samples and the second-type training samples, to obtain a basic model; freezing part of parameters of the basic model, fine-tuning the parameters by using the first-type training samples and the second-type training samples, to obtain a first special-purpose model and a second special-purpose model; and selecting a target model according to a current input text, so that the target model outputs a complete structured instance based on the current input text, to improve modeling accuracy.

The application relates to the field of computer data processing and discloses a traffic automatic playback method for software testing, which comprises the following steps: obtaining software traffic data and obtaining data packets and time intervals in the software traffic data; according to interval values and time sequence distribution relationships of the time intervals, a first category is obtained through multi-threshold segmentation, a third category is obtained through threshold segmentation of the first category, and all intervals except the third category in a time interval sequence are classified into a fourth category; a first compression rate of each interval in the fourth category is obtained, and a second compression rate of each interval in the third category is obtained; a correction coefficient is obtained according to the number of elements of the first category to which each interval in the fourth category belongs and packet values of adjacent data packets, and a third compression rate is obtained; and the traffic data is compressed and automatically played back according to the obtained compression rates. The application aims to solve the problems that the existing equal compression of time intervals between data packets leads to packet loss and large differences between traffic data before and after compression.

This application discloses an information processing method, apparatus, device, storage medium, and computer program. The method includes: when a collaborative document in a first state contains a first atomic operation and a second atomic operation, obtaining the tree structure corresponding to the collaborative document; updating the collaborative document from the first state to a second state based on the tree structure according to the operation intent expressed by the first atomic operation; wherein the first atomic operation includes a first type of operation among N predefined atomic operations in the tree structure, and the first type of operation is an operation that can be split into two or more atomic operations; performing intent restoration transformation on the operation intent expressed by the second atomic operation according to the operation intent expressed by the first atomic operation to obtain a transformed operation intent; and updating the collaborative document from the second state to a third state based on the tree structure according to the transformed operation intent. Using this application embodiment can improve the accuracy of conflict handling.

The invention provides a method for detecting security risks of firmware and related equipment. The method comprises the following steps: acquiring an in-firmware partition mirror image of first firmware; according to the partition mirror image in the firmware, obtaining files in the partition mirror image, file type information of the files in the partition mirror image and pseudo code files of the files in the partition mirror image; and determining a first type engine matched with the pseudo-code file based on the file type information, and performing security risk detection on the pseudo-code file through the first type engine. According to the method for detecting the security risk of the firmware and the related equipment, source-code-free deep semantic analysis is realized, so that a more accurate security risk detection result can be obtained.

The present disclosure provides an information processing method, device, equipment, storage medium and computer program product, relates to the technical field of computers, and particularly relates to the field of software development. The specific implementation scheme is as follows: acquiring at least one item of information in file information and version information of a specified version in a remote version library; archiving the at least one item of information to obtain an archiving package of the specified version; the type of the archiving package of the specified version is a first type or a second type, the archiving package of the first type carries the file information of the specified version, and the archiving package of the second type carries the file information and the version information of the specified version; sending the archiving package of the specified version to a third-party storage system; and the third-party storage system is used for storing the archiving package. The technical scheme of the present disclosure can archive at least one item of information in the file information and the version information of the specified version in the remote version library and store the information in the third-party storage system, so as to reduce the read-write pressure of the remote version library and improve the overall read-write performance and throughput.