562 results about "System software" patented technology

The invention discloses a software automatic testing system based on generative artificial intelligence, which is characterized in that a software analysis module identifies attribute information of a UI component based on a multi-modal large model for a test object, and constructs a UI component knowledge graph according to a structured information document; the knowledge retrieval module receives the test requirements and retrieves related historical test cases, test scripts and related test data; the organization interaction module sends a test intention and demand information to the knowledge retrieval module for retrieval according to the input user test intention, and test demand knowledge is returned; sending the UI component knowledge graph to the software analysis module for searching the knowledge graph of the test object, and returning the UI component knowledge graph; a test generation module receives test demand knowledge and the UI component knowledge graph, and generates a test case and a test script; and the script execution module receives the test case and the test script, starts a test process and records a test result.

The invention is applicable to the technical field of vulnerability detection, and provides a power system software security vulnerability dynamic and static combined detection method, which comprises the following steps: acquiring static source code data of power system software and dynamic behavior log data during operation; generating a hierarchical abstract syntax tree and structured time series data; performing multi-dimensional feature extraction on the static source code data and the dynamic behavior log data based on a vulnerability knowledge graph of the power system; generating a domain constraint confrontation sample based on the power protocol features and the abnormal features during operation, and inputting the domain constraint confrontation sample into the constructed hybrid detection model for confrontation training to obtain a trained hybrid detection model; and performing automatic detection on the power system software by utilizing the trained hybrid detection model, and outputting a detection result containing a static code defect position and a dynamic attack path. The full-life-cycle accurate detection of the software vulnerability of the power system is realized, and the network security protection capability of the power system is improved.

The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes receiving text submitted with a request. Token values are automatically extracted for selected token types from the text using a machine learning model. Tokens are identified in the text, and for each token, features and a token type of the token are determined, along with a score that indicates a likelihood that the token has the token type. A token value is extracted for the token from the text. Extracted token values are compared to request data values. A request value for the selected token type is identified in the data values for each selected token type. The extracted token value for each selected token type is compared to the request value. An audit alert is generated in response to determining that an extracted token value does not match a corresponding request value.

The invention provides a full-autonomous cell operation system based on body intelligence, and relates to the field of cell operation, the system comprises a system hardware architecture and a system software architecture; the system hardware architecture comprises a micromanipulation execution system, a precision positioning system, a multi-mode sensing system and an intelligent calculation and control center. The micromanipulation execution system is used for cell environment interaction, the precision positioning system is used for sample bearing and environment control, the multi-modal sensing system is used for providing key information, and the intelligent calculation and control center is used for operation decision making; the system software architecture comprises a sensing layer, a planning layer, an execution layer and an interaction layer. According to the application, cell recognition, tool selection, path planning, operation execution and result feedback can be automatically completed without manual intervention; through tool autonomous switching and strategy dynamic adjustment, various operations such as cell clamping, injection, controllable deformation and micro-assembly can be completed, and the problems that traditional cell operation depends on manual work, efficiency is low, and consistency is poor are solved.

The present disclosure involves systems, software, and computer implemented methods for managing database query plans with dynamic conditions. One example method includes receiving a request to process a query based on at least one dynamic condition. A serialized abstract query plan is identified, deserialized, and converted into a query optimizer tree. A condition provider procedure is invoked to generate a first filter string for each view in the query optimizer tree. Comparisons are made to determine matches between first filter strings and corresponding second filter string stored in the query optimizer tree. In response to determining that a first filter string does not match the corresponding second filter string, query plan compilation is triggered. In response to determining that each filter string matches each corresponding second filter string, a query plan is generated based on the converted query optimizer tree and the query is executed using the query plan.

Modifications to existing computer hardware, compiler changes or source-to-source transforms performed during the software build process, and a collection of libraries and modifications to existing standard system software and libraries. The invention allows a program author to enforce various kinds of locality of causality in software to provide enforcement of boundaries for the following aspects of a computer program: control, space, time, modularity, reference, initialization, and mutability. Where these properties do not suffice to guarantee a property at static time, dynamic checks may be added and the constraints on control flow prevent such dynamic checks from being avoided by the program.

The invention discloses a storage system software defect analysis method and system based on a large model. The method comprises the following steps: firstly, collecting public and internal historical defect data and multi-source logs, training a lightweight log extraction model after cleaning, and coarsely screening original logs of newly added defects; and inputting a coarse screening result into a large language model, and further studying and judging to output a real key log. And fusing and vectorizing the key log and the Bug description, and writing the fused and vectorized key log and Bug description into Elasticsearch to construct a historical case knowledge base capable of semantic retrieval. When a new defect enters the system, quickly extracting a key log by utilizing the trained model, and executing dual-channel retrieval in the knowledge base to recall similar cases; and the big language model is combined with similar cases to automatically generate responsible person recommendation, root cause analysis and executable troubleshooting and avoiding suggestions. According to the method, the problem that historical cases are difficult to retrieve can be effectively solved, similar cases can be quickly and effectively found from massive historical data under the double-control of Bug description and key logs, and study and judgment assistance is provided.

The invention discloses an intelligent driving system reliability evaluation method based on an EMC test, and relates to the technical field of EMC tests, and the method comprises the steps: obtaining intelligent driving system software and hardware interaction request data under the condition that a target vehicle is subjected to the closed electromagnetic interference, evaluating software and hardware interaction states of the intelligent driving system of the target vehicle, performing prior distribution screening on the software and hardware interaction states and functional fault feedback data of the known intelligent driving system, and establishing a known fault chain development network of software and hardware components of the intelligent driving system of the target vehicle; according to the intelligent driving system soft and hard component fault chain development network of the target vehicle, analyzing posterior distribution of the target vehicle open road real-time intelligent driving system soft and hard component interaction request list, and establishing an intelligent driving system fault chain development trend evaluation model; and predicting an intelligent driving system soft and hard component function failure risk score of the target vehicle. The method has the advantage that the safety and robustness of the intelligent driving system of the EMC test are remarkably improved.

The present disclosure involves systems, software, and computer implemented methods for using worst-case predicate selectivity for database query plans. One example method includes identifying a query that includes an initial set of parameter values for a set of predicates. An order of predicate evaluation is determined for a query plan by determining a worst-case selectivity for each predicate and ordering the predicates based on the worst-case selectivities. A second instance of the query is received that includes a second set of parameter values. The second instance of the query is executed, to generate a query result, using the query plan and the second set of parameters by evaluating the set of predicates based on the second set of parameters and the order of predicate evaluation determined based on the worst-case selectivities. The query result is provided in response to the second instance of the query.

This disclosure describes systems, software, and computer implemented methods for taking a user's natural language query, using a generative AI model to produce an embedding of that query, and then comparing that query embedding to a database of embeddings generated from metadata and data set descriptions of the datasets in the datastore. This database of embeddings includes both the embedding vectors, and a metadata object describing each data set in the datastore and is uniquely generated to enable efficient search application. Once comparison results are determined, the closest matching datasets to the user query can be provided to the AI model for a summarization of their contents, before being returned to the user as search results.

The invention relates to the technical field of building maintenance scheme optimization, and discloses a building maintenance scheme optimization method based on an intelligent algorithm, and the method specifically comprises the following steps: 1, interface optimization: after starting MATLAB software, loading a source code of building quality diagnosis system software named as a building doctor, and in a design view interface of the software, carrying out interface optimization on the source code of the building quality diagnosis system software; according to the method, the user interface of the software is ensured to be clearly viewed, then a'optimization 'button in the interface is optimized and adjusted, a'help' menu is newly added in the software interface, and visual elements such as the graphic size and color matching of the user interface are finely optimized and adjusted, so that the functionality of the software is enriched, and the user interface is more vivid. In addition, the friendliness and usability of the user interface are remarkably improved, smoother and more comfortable use experience is brought to the user, the visual and clear user interface is elaborately designed, and it is ensured that the user can easily understand and operate the platform and detect the particularity of the building.

The invention discloses a power system software vulnerability detection-oriented code multi-modal fusion representation learning method, which comprises the following steps of: firstly, obtaining four modals of a text, a pixel image, an attribute graph and complexity measurement of a power system software code through program analysis; then, modal interaction feature extraction is carried out by using dual-channel convolution and a graph neural network, and information transmission between modals is enhanced; and finally, designing a multi-modal collaborative fusion framework, performing reconstruction coding on the features based on feature mapping and cross-modal reconstruction loss, and fusing the multi-modal feature representation of the power system software code into a unified representation for constructing a vulnerability detection model for the power system software. According to the method, the completeness of modeling data representation of the power system software vulnerability detection model is enhanced through a code multi-modal interactive fusion representation learning method.

The invention discloses a satellite-borne equipment embedded system software on-orbit reconstruction method and a satellite-borne equipment embedded system. The method comprises the following steps: partitioning a FLASH memory of a microcontroller of satellite-borne equipment into a region, a BootLoader boot program region and an application program storage region; an independent BootLoader bootstrap program is solidified in the BootLoader bootstrap program area in advance; receiving a program file subpackage from a satellite service computer during on-orbit operation; a two-stage reliable transmission protocol including sequential receiving and packet supplementing receiving is adopted to receive a program file, wrong and missing packets are received and dynamically recorded in the sequential receiving stage, and only the wrong and missing packets are selectively retransmitted in the packet supplementing receiving stage; according to an instruction of the satellite service computer, the received complete program file is verified, the program file is written into the application program storage area after passing the verification, updating is completed, the BootLoader bootstrap program jumps to the updated application program, and on-orbit reconstruction is completed.

The present disclosure involves systems, software, and computer implemented methods for managing database query plans with dynamic conditions. One example method includes receiving a request to process a query based on a dynamic condition. In response to determining that a plan cache does not include a cached query plan for the query, query plan compilation is triggered to generate a query plan. In response to determining that a cached query plan exists, for each query view, a condition provider procedure is invoked to generate a first filter string. First filter strings are compared to corresponding second filter strings in the cached plan. In response to determining that a first filter string does not match the corresponding second filter string, query plan compilation is triggered. In response to determining that each filter string matches each corresponding second filter string, the database query is executed using the cached query plan.

The invention provides an automatic cutter handle production line based on an intelligent cutter system and a machining process. On the premise of guaranteeing the product machining efficiency and automatic intelligent production, in the whole intelligent cutter system-based cutter handle automatic production line operation and machining process implementation process, intelligent cutter wear state monitoring system software of a PC end upper computer monitors all intelligent cutters in a production line in real time through intelligent cutter embedded sensor data, and the intelligent cutter wear state monitoring system software is used for monitoring the intelligent cutter wear state in the production line. Comprise but are not limited to wear states and operation parameters of the intelligent external turning tool, the intelligent grooving turning tool and the intelligent milling cutter. The intelligent tool wear state monitoring system can give an early warning of tool breakage or end of service life in advance, and automatically calls a standby tool or prompts replacement, so that stable operation of a production line and high-precision consistency of tool holder products are ensured.

The invention provides a database concurrency control and memory access optimization method which can be applied to the technical field of computer system software performance optimization. According to the method, multi-level instruction-level reconstruction is carried out on an execution path of a database kernel through the characteristics of an underlying hardware instruction set of a collaborative application processor platform, and the method comprises the following collaborative implementation optimization dimensions: based on a register file and a cache hierarchical structure of the processor platform, an access mode of a database core data structure is optimized; the number of memory access instructions is reduced; the data locality is improved; on the basis of atomic instruction set extension of a processor platform, instruction-level reconstruction is carried out on key primitives in a database multi-thread synchronization mechanism so as to reduce the overhead and contention of synchronization operation; on the basis of single-instruction multi-data-stream extension of a processor platform and a vector atomic operation instruction of the single-instruction multi-data-stream extension, parallel acceleration is carried out on batch life cycle management operation of objects in a database.

The invention discloses a test control method and system for a direct-current power supply, and relates to the field of simulation testing, and the method comprises the steps: constructing a three-dimensional adaptive model to complete the matching calibration of system software and hardware, and achieving the load calibration through the comparison of dynamic load simulation and actual measurement data; in the testing process, a three-stage starting mechanism is adopted to power on step by step, fault protection is configured, and parameter scanning and real-time recording are executed according to a preset mode and a testing point; a double-closed-loop feedback mechanism is introduced, an inner loop adjusts output parameters, and an outer loop predicts power grid disturbance and performs advanced compensation; a safety threshold value is dynamically generated in combination with real-time environment data, linkage protection of approaching early warning and overrun protection is achieved, and a reliable effective data set is formed through fusion processing and double verification of multi-source test data. The system has the advantages that the precision and intelligence of the whole test process are realized through dynamic load simulation, a multi-level safety protection system is constructed through a three-level starting mechanism, and the precision, safety and data value of the test are comprehensively improved.

The invention discloses a cluster computing resource allocation method. The method supports three resource service forms of a virtual machine, a container cloud and a bare computer. Wherein the virtual machine resources are used for deploying system software with a UI (User Interface) and a C / S (Client / Server) architecture; the container cloud resource is used for deployment of system software of a B / S architecture and operation of a large test sample; the bare computer resources are used for specific function system software, Kafka middleware and / or database deployment; and service computing resource elastic scheduling and control are deployed to realize cluster computing resource allocation. According to the method, multiple resource service forms are flexibly adopted, and virtual cluster management and high-availability design are applied, so that test resource automatic deployment strategy generation and computing resource flexible scheduling and control can be realized, and high-performance, high-reliability, servitization and easy-to-use cluster computing resource allocation and deployment services are provided for users.

The invention provides a software quality evaluation method and device for a power grid dispatching automation system. Belongs to the technical field of power dispatching automation. The method comprises the following steps: acquiring running state data of power grid dispatching automation system software, and extracting a third-level index from the running state data; determining subjective and objective fusion weights of the third-level indexes; aggregating the third-level indexes related to the same quality feature according to the subjective and objective fusion weights of the third-level indexes to obtain corresponding second-level indexes; an index vector composed of the second-level indexes is input into the dynamic fuzzy neural network model, and the first-level indexes of the corresponding subsystems are output to serve as comprehensive quality evaluation scores; and determining the software quality grade of the business subsystem according to the comprehensive quality evaluation score and a preset grade threshold value. The method is suitable for power grid dispatching automation system software quality evaluation oriented to complex operation scenes, and comprehensive evaluation and self-adaptive optimization of dispatching software under multi-dimensional and dynamic conditions can be achieved.

The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes determining to initiate an integrated end of purpose protocol for an object of an object type. Target applications are determined that are allowed to process objects of the object type for at least one purpose, based on identified purpose information. An end-of-purpose query is provided to the target applications and an end-of-purpose status is received from each target application that indicates whether the application is able to block the object. The received statuses are evaluated to determine whether an aligned end of purpose has been reached for the object. In response to determining that the aligned end of purpose has been reached for the object, a block command is provided to each of the multiple applications that instructs a respective application to locally block the object.

Embodiments of the present disclosure relate to a system, software application, and methods for providing an improved electronic written communication that sounds like the user, as well as being tailor-fit to the writing style of the recipient in order to avoid miscommunication caused by personality, clarity, cultural, or generational writing differences. Systems and methods of the present disclosure may enhance written electronic communication through the integration of personalized profiles for both senders and recipients. By leveraging advanced stylometry and behavioral psychology profiling, the system tailors communications to fit individual needs. Additionally, this solution ensures that system-generated content matches the sender's natural writing style, saving time and maintaining authenticity. The system also provides real-time feedback and adjustments to avoid potential communication frictions. Moreover, embodiments of the present disclosure bridge miscommunication gaps caused by cultural and generational differences by interpreting these nuances and incorporating them into the improved electronic written communication.

The present invention provides an automated method and device for testing flight control system software. The device includes: automated adaptation software; an automated adaptation device, which includes: a mode control module, a power supply control module, a reset control module, a network port communication module, and a serial port communication module. The method includes: the automated adaptation device completes the work mode, power supply, and reset of the target machine according to the control of the automated adaptation software, automatically loads the test target file to the target machine, and obtains and analyzes the test result file generated by the target machine in real time. It realizes the non-interventional automated testing function of the flight control system software, avoids problems caused by human misoperation, and greatly improves the testing efficiency at the same time.

The invention discloses a system problem analysis method and device based on a Linux system. The method comprises the following steps: starting a data collection service, and collecting the following system data: system software data, system hardware data, kernel operation data and system security data; storing the collected system data in a database; analyzing the system data of the specified time period in the database through a preset rule, determining abnormal data, and generating an analysis result; and displaying the analysis result in a visual data chart form. According to the scheme, the data information existing in the system can be quickly and visually checked, and the time consumed by data arrangement and collection is shortened; when system operation and maintenance work is carried out, possible problems can be found in advance, so that the time consumed for continuously carrying out problem analysis and positioning in the operation and maintenance process is shortened; a visual analysis report can be output, the granularity of data is improved, and operation and maintenance personnel are helped to carry out problem positioning and system maintenance more quickly.

Disclosed are systems and methods for detecting a vulnerability across programs of an enterprise system and notifying remediation agent. The systems and methods utilize artificial intelligence (“AI”) systems to process data received from a particular network, such as systems, software, and software configuration data. The AI systems processes the software and software configuration data and compares the data to known vulnerabilities stored to a database. The system maps the vulnerabilities to attack signatures. When a vulnerability is identified within the network, the AI systems run classification analysis and categorization analysis to determine the probability a vulnerability is a known vulnerability and the category of software it relates to. The AI systems then runs a remediation agent analysis to determine the proper remediation agent to mitigate the vulnerability. Once a remediation agent is determined, a remediation agent is notified of the vulnerability and mitigates the vulnerability by removing or patching.

The invention provides an automatic test method and system for heterogeneous process verification and system software debugging, and relates to the technical field of software debugging, and the method comprises the steps: collecting and producing holographic monitoring data, and carrying out semantic annotation through a preset ontology model; a multi-head attention mechanism and a graph neural network are adopted to train an ontology model, and associated features of process parameters, equipment states and defect types are extracted; constructing an initial knowledge graph based on the features, and calculating a node weight relationship by using causal reasoning to generate a dynamic weight matrix; and in combination with real-time process data, features are extracted and fused through a deep residual network, and defect risk assessment and early warning are realized. Through dynamic updating and feature fusion of the knowledge graph, the accuracy and automation degree of heterogeneous process verification are improved, and intelligent early warning of process quality is realized.

The present disclosure involves systems, software, and computer implemented methods for data privacy. One example method includes receiving a first request to correct personal data or restrict processing of personal data of a data subject. Response data is identified that is provided by applications in a multiple-application landscape in response to a second request for access to personal data processed by respective applications in a multiple-application landscape. Relevant applications for the first request are identified based on the response data. A data correction or data restriction work package is sent to each relevant application and data correction or data restriction work package responses are received from relevant applications. An overall data correction or data restriction result is determined based on the data correction or data restriction work package responses and is provided in response to the first request.

A computer-implemented operation method is provided for isolating a software application from operating system software, including: installing a configuration file; installing a plurality of detectors; and installing and executing a monitoring software program. The configuration file enables interaction with the application. The detectors analyze input to the application. The input either belongs to an authorization list or else is absent therefrom. Executing the monitoring software program loads the detectors, receives application information from the configuration file, and activates an alert in response to the input being absent from said authorization list.

The invention discloses an edge intelligent computing platform device and a data processing method thereof, and belongs to the field of computers, and the device comprises a customized hardware layer and a system software layer. The hardware layer is integrated with a plurality of high-performance GPUs supporting full-precision calculation, a large-capacity memory and an NVMe flash disk to form a strong computing power and storage basis. A system software layer is integrated, such as a Ray distributed framework, and the key improvement of the system is that an NVMe flash disk is configured as overflow storage of a memory, when the memory is insufficient due to processing of mass data or large model reasoning tasks, intermediate data can be automatically overflowed to a high-speed flash memory, and system crash is avoided. Through deep collaborative optimization of hardware and software, the technical problem that a large model cannot be efficiently operated and big data cannot be processed due to resource limitation on an edge side is effectively solved, and full-stack AI reasoning and high-performance distributed data processing at the edge side are realized.

The invention discloses an automatic system for customizing and distributing and deploying system software of an embedded system. The automatic system comprises a configuration management module, a configuration management module and a configuration management module, wherein the configuration management module is used for storing a declarative configuration file in a Git version control system; the automatic execution module is realized by a CI / CD server, the CI / CD server is closely integrated with a Git warehouse of the configuration management module through a Webhook mechanism, and a CI / CD assembly line can be automatically triggered once the change of a configuration file is detected to be pushed to a specified branch; the product management module is used for archiving, storing and distributing the constructed product after the automatic execution module successfully completes the construction; and the end-side deployment module is used for deploying the system software on development equipment according to requirements for rapid deployment, verification and rollback use.

Provided are systems, software, and methods for phishing analysis and detection. The provided systems, software, and methods may comprise interfaces configured to capture and scan network session activity in real-time to detect a phishing attack using a set of trained machine learning classifiers, detect a phishing attach, classify the attack into one or more phishing classes, block the phishing attack and provide a safe preview of the blocked phishing attack. The machine learning classifiers may be deployed remotely. The systems, software, and methods may further comprise a web application programing interface configured to integrate the one or more analysis interfaces into at least one external software or application.