969 results about "System software" patented technology

The present disclosure generally relates to systems, software, and computer-implemented methods for using generative artificial intelligence to improve user interactions. One example method includes identifying, in a contact center application of an agent, a start of an assisted leg of an interaction of a user with a system. A user interaction summary is retrieved that summarizes events that have previously occurred in the interaction. A generative large language model (LLM) artificial intelligence (AI) context prompt is extracted based on the user interaction summary. The context prompt is provided to a generative LLM AI engine to set a context for the generative LLM AI engine. Event information is received that includes a query for the generative LLM AI engine. The query is provided to and a query response is received from the generative LLM AI engine. The contact center application is updated in response to the query response.

The present disclosure generally relates to systems, software, and computer-implemented methods for using generative artificial intelligence to improve user interactions. One example method includes receiving a notification from a contact center application that user interaction events have been generated during an interaction session. Event descriptions for events generated in the session are located in a contact center application use case definition. Event descriptions are enhanced with event information for to generate contextualized event information. The contextualized event information to is added to a generative large language model artificial intelligence context that is provided to a generative large language model artificial intelligence engine. A query is provided to the generative large language model artificial intelligence engine. A query response is received from the generative large language model artificial intelligence engine and the query response is used in the interaction session.

The present disclosure generally relates to systems, software, and computer-implemented methods for using generative artificial intelligence to improve user interactions. One example method includes receiving a notification from a contact center application that user interaction events have been generated during an interaction session. Event descriptions for events generated in the session are located in a contact center application use case definition. Event descriptions are enhanced with event information for to generate contextualized event information. The contextualized event information to is added to a generative large language model artificial intelligence context that is provided to a generative large language model artificial intelligence engine. A query is provided to the generative large language model artificial intelligence engine. A query response is received from the generative large language model artificial intelligence engine and the query response is used in the interaction session.

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 data privacy. One example method includes performing a processing action for a data subject for a purpose using a set of data categories that are associated with the purpose. The purpose has a retention period and is a parent purpose in a purpose hierarchy with at least one dependent purpose as a child purpose of the purpose. Dependent purpose retention periods and dependent purpose data categories are determined for each dependent purposes as respective subsets of the set of data categories. In response to an end of purpose for the purpose, data of the set of data categories is blocked. Data in the set of data categories that are not dependent purpose data categories is retained according to the retention period and data of each dependent purpose data category is retained according to a corresponding dependent retention period.

The invention discloses a part process generation method and system based on a process knowledge base, and the method comprises the steps: S1, connecting a process knowledge base through system software of a terminal, and carrying out the identification and screening of related process data in the process knowledge base; s2, according to the related process data screened and identified in the process knowledge base in the step S1, performing multi-domain similarity calculation and matching to obtain a processing feature process chain of the features of the to-be-processed part, and generating a step sequence set; and S3, according to the work step sequence set obtained in the step S2, optimizing the work step sequence set through an optimization algorithm, and generating a process route of the to-be-processed part. According to the invention, automatic generation of parts from characteristics to processes is realized, and intelligent and datamation automatic process generation is realized, so that the production efficiency of products is improved to a great extent.

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 invention provides a software testing method and a software testing system. The software testing method comprises the following steps. And the processor obtains the test case. When the test case has an incremental code, the processor generates a supplementary test case according to the plurality of feature vectors in the vector database and the test case based on a coverage rate of the incremental code. The step of generating the supplementary test case further comprises the following steps. The processor extracts key information of a test case to obtain a plurality of first data vector units. The processor performs a similarity search according to the plurality of first data vector units and the plurality of feature vectors to obtain a plurality of second data vector units. The processor combines the plurality of second data vector units to generate a supplementary test case, thereby improving the performance of the test operation based on the incremental code.

The present disclosure involves systems, software, and computer implemented methods for data privacy protocols. One example method includes receiving information defining a purpose for processing personal data of a data category stored in an object. A first mapping is received of a processing action to the purpose. Input data to be obtained for the processing action is identified. A determination is made as to whether the input data is of the data category that has been mapped to the purpose. The processing action is executed using the input data as purpose-based processing of the input data, in response to determining that the input data can be used during execution of the processing action for the purpose. Processing of the input data by the processing action is prevented, in response to determining that the input data cannot be used during execution of the processing action for the purpose.

The present disclosure generally relates to systems, software, and computer-implemented methods for using generative artificial intelligence to improve user interactions. One example method includes receiving a notification from a contact center application that user interaction events have been generated during an interaction session. Event descriptions for events generated in the session are located in a contact center application use case definition. Event descriptions are enhanced with event information for to generate contextualized event information. The contextualized event information to is added to a generative large language model artificial intelligence context that is provided to a generative large language model artificial intelligence engine. A query is provided to the generative large language model artificial intelligence engine. A query response is received from the generative large language model artificial intelligence engine and the query response is used in the interaction session.

The invention provides an HIL simulation test system of a commercial vehicle domain controller. The system comprises an HIL system software platform, an HIL system simulation model, an HIL system simulation hardware platform and a vehicle body system special simulation assembly which are electrically connected. The HIL system simulation hardware platform is used for providing hardware support and executing the hardware-in-the-loop simulation test; the HIL system software platform is used for controlling a simulation test process, managing a test task and automatically generating an interface model; the HIL system simulation model is used for constructing a virtual test environment of a controller and performing signal interaction with the HIL system simulation hardware platform; the simulation assembly special for the vehicle body system is used for simulating vehicle body control, air conditioner control, gateway and vehicle control functions so as to improve the test coverage degree, and efficient development and iteration of a commercial vehicle domain controller are facilitated.

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 present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes receiving a request to initiate an aligned purpose disassociation protocol for a purpose for an object instance. A determination is made as to whether a timestamp is stored for the purpose and the object instance that indicates an earliest time that the purpose can be disassociated from the object instance. The request is accepted in response to determining that no timestamp is stored for the purpose and the object instance that is greater than the current time. A status request is sent to applications that requests a status response that indicates whether an application can disassociate the purpose from the object instance. Status responses are received from at least some of the applications. A disassociation decision for the purpose and the object instance is determined based on the received status responses.

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 data privacy. One example method includes providing an end-of-purpose query to applications in a landscape that requests an application to determine whether the application is able to block an object. Votes are received from applications that are either a can-block vote that indicates that the application can block the object or a veto vote that indicates that the application cannot block the object. At least one relevant-application veto model is identified that models which applications can raise a relevant veto vote with respect to another application. Received end-of-purpose votes and the relevant-application veto models are evaluated to determine whether any applications should be block instruction recipients. If any block instructions recipients have been identified, a block instruction for the object is set to each block instruction recipient.

The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes receiving a request to initiate an aligned purpose disassociation protocol for a purpose for an object instance. A determination is made as to whether a timestamp is stored for the purpose and the object instance that indicates an earliest time that the purpose can be disassociated from the object instance. The request is accepted in response to determining that no timestamp is stored for the purpose and the object instance that is greater than the current time. A status request is sent to applications that requests a status response that indicates whether an application can disassociate the purpose from the object instance. Status responses are received from at least some of the applications. A disassociation decision for the purpose and the object instance is determined based on the received status responses.

The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes receiving a request to initiate a data privacy integration protocol for applications in a multiple-application landscape. Voting responder group configurations are identified that group the applications into multiple voting responder groups for performing voting for the protocol. A voting request for the protocol is sent to applications in a first voting responder group. Data privacy integration protocol votes are received from the applications in the first voting responder group and a determination is made as to whether any application in the first voting responder group provided a veto vote for the protocol. If at least one application in the first voting responder group provided a veto vote for an object, the protocol is ended for the object without sending a voting request to applications in a second voting responder group.

The present disclosure involves systems, software, and computer implemented methods for using multiple synonymous identifiers in data privacy integration protocols. One example method includes identifying a request to initiate a protocol in a multiple-application landscape for an object with an identifier. A determination is made that at least one context-using application participant of the protocol relies on a context-providing application participant of the protocol for resolving the identifier to a local identifier local to a context of the context-providing application participant. A resolution request is sent to context-providing application participants that can provide resolution for an identifier for at least one context-using application. A local identifier corresponding to the identifier that is local to the context of the context-providing application participant is received from each context-providing application participant. A protocol work package that includes a resolved local identifier to is sent to each context-using application participant.

The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes determining, by a data privacy integration service, a condition that has occurred from performing a data privacy integration protocol that indicates that a first object is to be redistributed to applications in a multiple-application landscape. Application responder group configurations are identified that group the applications into multiple redistribution responder groups for performing redistribution operations for an object type of the first object in response to redistribution requests. A redistribution command to redistribute the first object is sent to each application in a first redistribution responder group. If all redistribution statuses received from applications in the first redistribution responder group indicate successful redistribution of the first object, the redistribution command is sent to each application in a second redistribution responder group.

The invention discloses a power system software risk assessment method based on improved machine learning, and relates to the field of power system software security. Through the steps of data acquisition, preprocessing, feature engineering, improved machine learning model training and the like, risk assessment and prediction are carried out on components in the software supply chain. According to the method, the precision and applicability of software supply chain risk assessment can be effectively improved, a safer and more reliable software supply chain platform is provided for a power system, and a reference is provided for software security management in other industries.

The invention belongs to the technical field of computer system software, and particularly relates to a fault monitoring system based on an embedded Linux operating system, which is used for visually monitoring the embedded Linux operating system. The fault monitoring system comprises a monitoring data acquisition module, a fault diagnosis and processing module, a log management module and a visualization module. According to the method, the change of the system state can be captured and fed back in time, rapid fault judgment and processing are realized, and a visual graphical interface is provided, so that the usability is improved.

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.

A direct-attached storage device software RAID control communication system includes a chassis housing a software RAID subsystem coupled to an operating system and a controller device. The software RAID subsystem provides a virtual adapter device and a virtual miniport driver for the operating system, provides a physical miniport driver for the controller device, and provides a helper driver between the virtual miniport driver and the physical miniport driver. The helper driver identifies, via the physical miniport driver, a communication entry point for the controller device and logical storage subsystem(s) provided by storage device(s) connected to the controller device, and identifies them to the virtual miniport driver. The virtual miniport driver then presents a logical storage device to the operating system that includes at least some of the logical storage subsystem(s), and uses the communication entry point to transmit communications between the operating system and the physical miniport driver.

Disclosed in the present invention are a gravity compensation algorithm for a tail end tool of a robotic arm, and a system, a device and a storage medium, which are applied to the field of system software. The method comprises: acquiring the gravity of a tail end tool of a robot; acquiring zero-point values of a force sensor according to the gravity; determining whether a sampling time reaches a preset time T; if the sampling time reaches the time T, calculating zero-point values within the time T, and taking the average value of the zero-point values as a zero-point value at the start of the force sensor; and if the sampling time does not reach the time T, re-acquiring zero-point values of the force sensor; subtracting the gravity and the zero-point value at the start of the force sensor from a reading of the force sensor, so as to obtain a real external force value; and a robotic arm moving to execute a corresponding task. In the method, the average value of zero-point values within a time period after the start of a force sensor is used as a zero-point value at the current start, and a zero-point value is calculated once after each start and is used as the zero-point value at the current start. Therefore, compared to the prior art in which only one fixed zero-point value is taken, the method is more accurate.

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 present disclosure involves systems, software, and computer implemented methods for generating new credit accounts for immediate availability for use in current online transaction. One example process includes identifying, at a merchant application, a request to perform a credit application process associated with a particular user via a client application. The credit application process is associated with a financial institution, and the merchant application stores a set of user accounts, each associated with a merchant-specific identifier identifying the particular user profile at the merchant. An interactive application is presented within the merchant application, and information associated with the completed application is transmitted to an API associated with the financial institution with the merchant-specific identifier of the associated user. A payment credential for a newly created credit account is received, and can be associated with the user profile corresponding to the merchant-specific identifier.

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.