239 results about "Task list" patented technology

The invention provides a computing power center resource centralized self-adaptive control scheduling system and method, and the method comprises the steps: S1, a user submits a computing power training task through an API, and sends the task to a DAG task composer, and forms a task list to be scheduled; s2, the intelligent monitoring analysis module is used for continuously collecting node data and calculating real-time CS and HS scores of each node; s3, analyzing the dependency relationship type data by a task composer, and calling a dynamic programming algorithm in an adaptive scheduler to make a decision; s4, the adaptive scheduler performs dynamic task distribution according to the task list of the DAG task orchestrator and the intelligent monitoring analysis module, and S5, the distributed runtime and environment management module is used for uploading the prepared Docker mirror image to the distributed storage; and S6, through the unified communication adaptation layer, the mirror image is pulled from the distributed storage on the target node and the container is started, the user does not need to concern the difference of the operating system in the whole process, and efficient and intelligent adaptive scheduling is realized.

The invention relates to a cache data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a distributed storage system adopting a three-layer architecture design, and the three-layer architecture comprises a service application layer, a data processing layer and a persistence layer. Comprising the following steps: acquiring access request monitoring information through a service application layer to obtain an access feature data set, and performing pattern classification identification on the access feature data set to obtain a predicted access pattern; generating a prefetching task list and prefetching data according to the predicted access mode, and storing the prefetching data to a data processing layer for caching processing; and executing each prefetching task according to the sequence of the prefetching task list, and reading the prefetching data from the mechanical hard disk and writing the prefetching data into a cache space in a solid state disk resource pool under the condition that the prefetching data does not exist in the solid state disk resource pool of the persistence layer. By adopting the method, the cache performance can be improved.

The invention discloses a business data query reconstruction method and device, equipment and a storage medium. Comprising the steps of obtaining a query task list constructed by a user, and performing permission verification on the query task list; after the verification is passed, reconstructing the query task list to generate a standard query command; executing the standard query command to obtain original query data, desensitizing the original query data to generate safe query data, and displaying the safe query data to a user. The user permission is verified through the permission verification process, the unauthorized query is intercepted from the source, and illegal access to the production database is avoided. By generating the standard query command, the row-level permission condition can be embedded into the query logic, so that the generated query command is ensured to be compliant, permission bypassing is avoided, errors and performance risks of manual writing are avoided, and meanwhile, the development efficiency is improved. By dynamically desensitizing the original query data, on the premise of guaranteeing the service continuity, the data can be available and invisible, the compliance requirement is accurately met, and the data leakage risk is reduced.

The invention discloses an automatic code debugging and optimizing system and method based on an AI agent, and relates to the technical field of artificial intelligence and automatic programming, the system comprises a coordinator module, a plan generation module, a code generation module, a test verification module, a deployment operation module, a project summary module, a language model module and a context management module; the coordinator module supports to select and call an Agent for specific task execution according to the current task process, and the plan generation module is configured to automatically generate a development task plan according to the requirements of a user and transmit a task list to the code generation module. Through the exception retry mechanism and the task backtracking mechanism, the system can automatically detect errors in the code generation process and repair the errors, and the tedious process of traditional manual debugging is avoided. The system optimizes the code generation process by backtracking the historical task and adjusting the generation strategy, and the quality of the final code is ensured.

The invention discloses an automatic design method and system based on BIM software. The method comprises the following steps: initializing an adaptation layer dynamic link library, and establishing a parameter transmission channel with BIM software; preparing BIM design data, registering a basic task in BIM software based on the BIM design data, and establishing a standardized project directory; establishing a parameterized set of tasks which can be automatically modeled; serially arranging the task set into a task list according to design logic, and recording the task list to a project project; and calling the adaptation layer interface through the parameter transmission channel to drive the BIM software or a professional application module in the BIM software to complete automatic modeling. According to the method, the engineering design rule is solidified into the accurate task sequence by calling the BIM software or the interface of the professional application module in the BIM software, automatic execution of the whole process is achieved, the technical problems that manual operation efficiency is low and an existing RPA technology cannot process complex BIM design logic are solved, and design efficiency and quality are remarkably improved.

The invention discloses an execution method and device of a cloud management task, a storage medium, equipment and a program, and relates to the field of cloud computing, and the execution method comprises the following steps: matching a text corresponding to a received user instruction with a first dictionary to determine a processing object allowed to process the user instruction, the first dictionary is associated with the business field of the cloud management task; under the condition that it is determined that the processing object comprises the large language model and the risk decision of the first intention of the user instruction is a first value, according to the text and a preset vector database, a cue word of the large language model is constructed, so that an ordered task list corresponding to the user instruction output by the large language model is obtained; and executing the cloud management tasks in the ordered task list. Through application of the method and the device, the problems that a cloud management mode in related technologies mainly depends on a graphical user interface and a command line interface to realize management, the operation is complicated and the efficiency is low are solved, and the cloud management efficiency is improved.

The invention relates to the technical field of remote measurement, in particular to a very simple protocol efficient and high-density meter reading method which comprises the following steps: acquiring data frame content, eliminating identity fields, generating a simplified format identifier, constructing a peak shifting scheduling list, detecting sequence consistency, generating a frame supplementing instruction, and dividing synchronous triggering groups to sort meter reading records. According to the method, identity field compression is replaced, frame body space proportion conversion is introduced, data structure content is simplified, a rhythm dislocation sequence is constructed in combination with time migration to achieve high-density node scheduling, frame loss behaviors are screened based on serial number jumping, a frame compensation response task list is automatically constructed, and a synchronous trigger sequence is constructed in combination with time difference judgment. The volume of transmission data is effectively compressed, the utilization rate of channel resources is improved, peak-shifting uploading between nodes is realized to reduce the probability of data collision, overhigh communication load caused by frequent handshake response and multi-level response is avoided, and the continuity, fault tolerance and rhythm collaboration of meter reading scheduling are enhanced.

The invention discloses a load-algorithm bidirectional elastic scheduling method and device for a hybrid energy storage system, and belongs to the technical field of water, wind and light stations, and the method comprises the steps: obtaining the operation data of a water, wind and light hybrid energy storage system through a collection CPU; performing wind and light ultra-short-term prediction and load evaluation through the prediction CPU, and evaluating the battery state and the water and electricity available capacity to obtain a prediction result; computing resources, priorities, resource allocation proportions and levels of energy storage algorithms of control tasks of multiple time scales are determined by scheduling a CPU according to the operation data and the prediction result, calculation-communication pre-preemption is triggered after an early warning event is generated, and a task list and a resource allocation matrix at the current moment are generated; executing a control operation by controlling the CPU according to the task list and the resource allocation matrix; adjusting a next scheduling cycle strategy or executing a thermal migration mechanism according to a result after execution control, and performing backfilling execution on selectable sub-graphs of the directed acyclic task graph in an empty window period; and bidirectional elastic adaptation of the load and the algorithm is ensured.

The invention relates to the technical field of building construction, in particular to an intelligent scheduling building construction progress optimization method, which comprises the following steps of: acquiring construction environment data in real time by utilizing a sensor network, and dynamically evaluating a resource state in combination with a historical record and a task list; generating an initial construction plan by using a multi-objective optimization algorithm, and performing real-time correction through a fuzzy logic dynamic adjustment mechanism; the resource use condition is monitored by means of Internet of Things equipment, and a data optimization strategy is fed back; and finally determining the arrangement by comparing the optimization plan with the actual progress. The method can significantly improve the accuracy and timeliness of the construction plan, cope with a complex environment, reduce human intervention, ensure that key tasks are completed preferentially, and improve the construction efficiency and the resource utilization rate.

The invention provides a task execution method and device, electronic equipment and a storage medium, and relates to the technical field of large models, in particular to the technical field of artificial intelligence such as natural language processing, image vision and deep learning. Obtaining a target sub-task list after the target task is disassembled, the target sub-task list comprising a task execution sequence of each target sub-task; an execution agent of each target subtask in the target subtask list is determined from a preset agent cluster, and a support mode of each agent in the agent cluster is at least one of multi-mode data; and based on the task execution sequence, sending a corresponding task execution instruction to each execution agent to obtain a target task execution result of the target task.

The present invention is directed to a software-based technology system for managing and executing high volumes of work on complex projects across multiple organizations involving multiple users that results in superior outcomes at significantly reduced time and cost. Litigation is the initial application of this invention; each case is handled as a project. As applied to litigation, the system of the invention empowers a novel method of end-to-end case assessment, planning, execution and management by integrating tools, processes and procedures allowing for more informed decision-making and deliberate execution of all case-related actions as well as enhanced coordination and communication among all constituents, resulting in efficient achievement of targeted outcomes. The system provides intuitive, menu-driven functionality for inputting, processing and utilizing vast amounts of information, including company and case-specific information, attorney discretionary evaluation and input, document templates and monitoring and reporting requirements. A threat algorithm cross-correlates via multivariate analysis critical data points with customized company-specific information and business logic to generate a numeric threat score as an output. The system also predicts the expected settlement range with a high degree of precision for a specific case as the output of one or a combination of multiple artificial intelligence (AI) / machine learning algorithms. The system then generates a unique case strategy (which includes an expected outcome, including projected outcome, Case Plan and estimated attorneys' fees and costs). System logic learns from thousands of examples of similar cases and directs highly effective and efficient execution of a specific Case Plan providing each attorney and staff member assigned a role in a case with a prioritized task list that is updated in real time as other users complete tasks and litigation priorities change. For each user, the system integrates assigned tasks across multiple cases and multiple client portfolios into a single, prioritized task list. The execution features become increasingly valuable given the volume and complexity of projects across multiple organizations and users, allowing users to focus on their area of expertise and avoid the wasted time and distraction of trying to determine what they should be working on or recording notes to communicate what they have been doing since the system automatically performs these functions and directs the various users' next steps while monitoring their progress against the plan. Integration of administrative functions, including automated time tracking, billing and reporting without the need to rely on users to update this information, further increases quality and efficiency of legal services. Key objectives of the system of the present invention include eliminating gaps between business objectives and litigation strategy and optimizing communication and coordination of case-related tasks and priorities in a fully automated fashion, which are all achieved by leveraging data and technology to enable a fundamentally different approach that becomes smarter and more precise via machine learning and predictive modeling.

The invention discloses a cross-system collaborative to-do task query and processing method and system based on an AI Agent architecture, and particularly relates to the technical field of artificial intelligence and information system integration. According to the method, to-be-handled task data in each heterogeneous service system is automatically collected through a distributed deployment AI Agent module, and standardized processing is carried out through a unified task modeling module; identifying and combining repeated tasks by using a semantic understanding and deduplication module based on natural language processing, and generating a global unified task view; distributing tasks according to a dynamic strategy through an intelligent task routing and distribution module; realizing cross-system operation and real-time state synchronization by means of a task execution and state synchronization module; and finally, providing an aggregated task list and an operation interface for a user through a unified interaction interface. According to the system, unified integration, intelligent processing and collaborative management of multi-source heterogeneous tasks are effectively realized.

The invention discloses an agent task decomposition method and system in the financial field and a medium, and belongs to the technical field of artificial intelligence. The method comprises the steps that financial task semantic features are extracted through a large language model, intention recognition is completed in combination with user historical preferences, and then a dynamic tree-shaped task graph is generated based on a three-level matching mechanism to enhance the complex task processing capacity; and finally, realizing dynamic reconstruction of the task tree through a confidence-driven adjustment mechanism. The content of extracting the semantic features and intention recognition comprises the steps of task input, wherein a financial task request of a user is received through a front-end dialogue type webpage; feature extraction and preference retrieval: task semantic features are extracted, and user historical preferences are retrieved in combination with user dialogue records stored in context; and structured output: arranging a task list containing task types, key parameters, constraint conditions and user preferences. According to the method, the complex task processing capability can be enhanced, the dynamic adaptability is improved, and personalized task planning is realized.

The application discloses a kind of based on plug-in AI digital person ability extension method, the method includes according to the data that user submits and interacts, extract user information feature matrix, construct user preliminary portrait;Based on user preliminary portrait, select relevant plug-in, pre-load plug-in and automatically select ability extension strategy;Initialize plug-in function, according to ability extension strategy and user dialogue system gradually enable plug-in, expand the ability of AI digital person, record enabled function information;According to enabled function information, construct AI digital person ability management system, output AI digital person ability matrix;Using the document uploaded by user, parse the task list of user, match ability matrix, customize user personalized task list.The application solves the flexibility and personalization problem of AI digital person function expansion under different user needs and scenarios, realizes the intelligent adaptation and ability improvement of AI digital person in diversified application scenarios, provides more accurate and efficient personalized service for user.

The application discloses a PCBA first-piece detection method and system, electronic equipment and a storage medium, comprising: obtaining an integral board virtual assembly drawing, a PCBA physical image, and a first CAD element list; extracting an element list L4; obtaining a second CAD element list on a server, generating a task list, generating an inspection list, and assigning a current task number to at least n1 users without a task; on a user side, obtaining the current task number based on the task list, obtaining the state of the current task number, and when the state of the current task number is incomplete or complete, obtaining the inspection list updated according to the state and the inspection result in the inspection list; on the server, after the results in the inspection list are all updated, obtaining the task list after the state is closed and the current task number is cleared, generating and outputting a report of the current task number. The application can dynamically allocate detection tasks, perform first-piece detection in parallel by multiple people, set multiple re-inspections or cross-inspections, save time, and reduce the error rate of inspection.

The application provides a virtual machine processing method, device and equipment for software testing tasks, and relates to the field of virtual machines.The method comprises the following steps: obtaining a software testing task list and a template testing virtual machine; configuring a resource package of at least one software testing task on the template testing virtual machine according to a plurality of software testing tasks in the software testing task list, to obtain a plurality of virtual machines; performing dependency processing on the plurality of software testing tasks currently being tested by the plurality of virtual machines respectively; determining the running state of the current virtual machine in the dependency processing of the software testing task by the resource package of at least one software testing task after the current virtual machine is started according to a start task; and destroying the current virtual machine and starting the next virtual machine according to the running state until the plurality of software testing tasks are tested.The scheme of the application realizes the automatic management of the whole running cycle of the virtual machine, and improves the efficiency of virtual machine management and the utilization rate of network resources.

In the proxy AI, the service background and the service condition of the user are understood, and abstract instructions are autonomously decomposed into specific tasks and executed. A proxy system is provided. The present invention is provided with a dialogue unit, a resolution unit, an execution unit, and a monitoring unit, each of which can individually use a generative AI, and the dialogue unit grasps a service command from a dialogue with a user through the generative AI, stores the content of the dialogue in a short-term memory as a dialogue log, and monitors the content of the dialogue in the short-term memory. The solving part decomposes a business instruction into tasks through the generative AI and creates a task list, an execution instruction of each task is transmitted to the execution part, an execution result is prompted to a user through the dialogue part, and the execution part executes a job for a corresponding data source through the generative AI corresponding to the task related to the execution instruction and transmits the execution result to the solving part; the monitoring unit refers to the dialogue log at any time, masters the context of the dialogue through the generative AI, predicts the content corresponding to the next step, and stores the content as an abstract in a short-term memory for reference at any time.

The dialogue unit 11 grasps a business instruction by a dialogue with a user 2 by the generative AI, and stores a content of the dialogue as a dialogue log in a short-term storage 16, the solution unit 12 creates a task list by decomposing the business instruction into tasks by the generative AI and passes an execution instruction of each task to the execution unit 13, the execution unit 13 executes a work on a corresponding data source 3 by the generative AI corresponding to the task related to the execution instruction, and passes an execution result to the solution unit 12, and the monitoring unit 14 refers to the dialogue log at any time, grasps a context of the dialogue by the generative AI, predicts a content to be dealt with next, stores the content as a summary in the short-term storage 16.

The application provides a data processing method, an electronic device and a program product. The method comprises the following steps: in response to an export request sent by a client, determining at least one data type and an export parameter corresponding to the export request, and a current running parameter of a server; determining export data information according to the at least one data type and the export parameter; generating a task list according to the export data information and the current running parameter, the task list comprising a plurality of export tasks and a task index corresponding to each export task; and sending the task list to the client, so that the client downloads data corresponding to the plurality of export tasks according to the plurality of task indexes, thereby improving operation and maintenance efficiency.

The application relates to the technical field of data governance, in particular to a task management method and device and computer equipment. The method is applied to a task scheduling system and comprises the following steps: determining a current to-be-executed subtask from a task list, determining a target agent corresponding to the to-be-executed subtask according to a type label of the to-be-executed subtask; calling the target agent to execute the to-be-executed subtask, obtaining execution result data, and feeding back the execution result data to a main agent; when it is determined that the execution result data represents execution failure, calling the main agent to process the execution result data and a memory chain of the main agent, obtaining an adjusted task sequence; updating the task list based on the adjusted task sequence, and continuing to execute each subtask that has not been executed in the updated task list. The scheme can improve the execution efficiency of the task scheduling system.

The application discloses a cloud management task execution method and device, a storage medium, equipment and a program, relates to the field of cloud computing, and comprises the following steps: matching a received text corresponding to a user instruction with a first dictionary to determine a processing object that is allowed to process the user instruction, wherein the first dictionary is associated with a business field of the cloud management task; in the case that the processing object comprises a large language model and a risk decision for a first intention of the user instruction is a first value, constructing a prompt word of the large language model according to the text and a preset vector database to obtain an ordered task list output by the large language model corresponding to the user instruction; and executing the cloud management task in the ordered task list. Through the application, the problem that the cloud management mode in the prior art mainly relies on a graphical user interface and a command line interface to realize management, operation is complex and inefficient is solved, and the cloud management efficiency is improved.

1. Name of the product subject to this design: The main body of an intelligent dialogue graphical user interface for electronic devices. 2. Purpose of this design: An electronic device. 3. The key design features of this product are the graphical user interface in the electronic device for which protection is sought. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of Graphical User Interface: Graphical user interfaces are used for intelligent dialogue. The protected portion of the graphical user interface is used to display a list of tasks and the current task status in the dialog area, and to display a list of recent dialogs in the navigation bar. 7. Human-computer interaction method of graphical user interface: In response to the need to confirm information with the user during the task execution process, the graphical user interface changes from the main view of Design 1 to the change state diagram of Design 1 to show the state of the task being paused and waiting for the user to confirm information. Users can pause the execution of the current task by touching or clicking the pause button in the input box of the Design 2 main view. Users can send instructions through the input boxes in the Design 3 main view to confirm information. 8. Other situations requiring explanation: The portions of the graphical user interface shown by the dashed lines in the views of Design 1 to Design 3 do not constitute the parts protected by this design.

The invention relates to a dynamic testing method and system for embedded equipment, belongs to the technical field of software testing, and solves the problems of mismatching of testing requirements and hardware resources and low concurrency efficiency in the prior art. The method comprises the steps of obtaining a CI / CD variable and a to-be-tested source code, and determining a test task type; determining a target test case set according to the test task type and the to-be-tested source code; according to the case type, dividing the target test case set into test case subsets, and determining a subset type; starting a corresponding container for the test case subset; generating a test task list according to all the test case subsets and the hardware resource state table by utilizing a hardware resource allocation service of the container; based on the test task list, the container starts a thread for the corresponding hardware equipment, the hardware equipment is controlled to execute a test, and a test result is output. According to the method and the device, the test cases and hardware resources with adaptive performance are automatically, efficiently and dynamically selected based on the source code change condition.

The application discloses a task list engineering quantity segmentation control method and system based on WBS and a pricing list, relates to the technical field of engineering progress management, and comprises the following steps: an engineering project is decomposed into minimum task control units layer by layer through a WBS structure, and basic cost measurement is carried out on each unit based on a pricing list; scheduling constraints and overflow costs among units are generated, and costs are dynamically adjusted in real time through real-time input of engineering progress data; further, a prediction and an optimal scheme are generated based on actual data of completed engineering, and a project profit state and risks are comprehensively judged; through multidimensional evaluation and a sliding optimization algorithm, an optimal segmentation node is automatically identified, and segmentation control and scheme fine adjustment are realized. The method improves the fine management of engineering costs, risk early warning and dynamic optimization capability, and provides technical support for efficient, controllable and sustainable profit of complex engineering projects.

A method for providing personalized task information is provided. The method according to some embodiments may include identifying, by a computing device, a task list including a first task and at least one module required to perform the first task, based on first information including task system data of a first user; generating, by the computing device, customized detailed information for the at least one module, based on second information including experience of the first user; and automatically generating, by the computing device, a user-customized UI based on the task list, the at least one module, and the customized detailed information.

The invention discloses a self-adaptive parallel data transmission method and system, and relates to the technical field of computer networks and data processing. Dividing to-be-transmitted data to obtain a plurality of sub-data blocks, and summarizing the sub-data blocks into a global task list; screening out an available server set in an idle state from the server cluster; calculating an aggregation transmission rate in the current time window; if the current aggregation transmission rate is greater than or equal to the historical aggregation transmission rate, increasing the current degree of parallelism, and adding a new target server from the available server set; if the current aggregation transmission rate is smaller than the historical aggregation transmission rate, the current parallelism degree is reduced, and the server is released from the current target server; and if all the sub-data blocks in the global task list are successfully transmitted, splicing and checking the target sub-data blocks, and ending the data transmission after the target sub-data blocks are checked to be correct. By implementing the provided technical scheme, the problem that an existing fixed concurrent transmission scheme cannot adapt to environmental changes is solved.

The application relates to the field of data security, in particular to an image data labeling method and device, computer equipment and a storage medium. The method comprises the following steps: receiving a task labeling request sent by a user terminal, wherein the task labeling request carries a task identifier; querying a storage address of an image file corresponding to the task identifier and a first key from a task list stored in a local database; sending the first key to the storage address in the cloud, wherein the cloud is used for verifying the first key, and after the verification succeeds, returning a desensitized image file; sending the desensitized image file to the user terminal, so that the user terminal analyzes the image file to obtain pixel information and desensitized information, and displays the obtained pixel information and desensitized information; receiving structured data obtained by the user terminal after labeling the pixel information, and uploading the structured data to the cloud to be associated with the image file stored in the cloud. The method can improve data security.

1. Name of the product in this design: Graphical User Interface for Real-Time Monitoring of Loaders for Electronic Equipment. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: Used for real-time monitoring of the loader; the left side of the main view displays the equipment's operating status in map form, while the right side displays the equipment list and task list in list form; clicking the buttons in the interface allows for corresponding operations, such as clicking "Pause Operation" in the upper right corner to remotely control the equipment. 6. Other situations requiring explanation: Other explanation: X represents text content.

The present application relates to the technical field of data processing, in particular to a data processing method, device, computer equipment and storage medium, comprising the following steps: obtaining field label order and positioning index, analyzing combination change mapping order relationship, extracting variable field and judging homing condition, matching upper and lower combination tracking arrangement path, comparing order extraction state information, associating field number to generate task list, executing processing operation according to state, and outputting result mapping table.In the present application, the field order fluctuation characteristics and position mapping relationship are extracted, the dynamic sorting model between fields is established, the arrangement condition and attribution position of the field in the structure are determined by combining the label attribution state and adjacent combination difference, the order adjustment, content removal and structure reservation operation are executed according to the state information, the data processing range is limited, the structure mixed use interference is avoided, and the structure adaptation ability, order identification ability, task allocation ability and result mapping ability are enhanced.

According to the human factor analysis and verification platform and method for human-computer interaction interface design provided by the embodiment of the invention, a human factor analysis module carries out function analysis on a task list needing to be realized by a human-computer interaction interface so as to determine a target task needing natural persons to participate in operation; the human factor verification module is used for verifying the to-be-tested human-computer interaction interface based on a preset human factor design criterion library, the task sequence information and multi-modal data corresponding to the target task executed by a user, and performing flow splitting and operation error evaluation on the target task to determine the task sequence information of each step of the target task, and the human factor verification module is used for verifying the to-be-tested human-computer interaction interface based on the multi-modal data corresponding to the target task executed by the user. And determining to-be-corrected elements which are not matched with the task sequence information in the to-be-tested human-computer interaction interface. The human-computer interaction interface to be tested is constructed and verified based on the human factor analysis module and the human factor verification module, finally designers are assisted in accurately constructing and effectively correcting the human-computer interaction interface, and the rationality and task suitability of interface design are improved.