26results about How to "Guaranteed execution efficiency" patented technology

The invention discloses a robot intelligent scheduling and management and control system and method for hospital delivery services, and relates to the technical field of realizing material delivery services by using robots. The scheduling platform determines the execution category according to the attribute of the transport work order, and when the execution category is robot execution, the scheduling platform assigns the transport work order to the robot according to an order insertion, sequential and / or proximity strategy; a shortest-time-consumption planning strategy is adopted, and the path of the robot assigned to convey the work order is planned; and when executing the work order, the robot interacts with the scheduling platform in real time and reports the task completion condition. The scheduling strategy of the transport work order is further optimized, the transport efficiency and the load rate of the transport robot are improved, and the scheduling platform can master the information of each node in the transport path in real time, so that reference is provided for subsequent planning of the transport path, and the transport efficiency of the transport robot is further improved.

The invention discloses a thread management method and device, equipment and a storage medium. A target task is determined from a task queue, a target thread is determined from idle threads, and the target thread is scheduled to execute the target task. The execution state of the target task is monitored, and when it is monitored that the execution state is cancelled, execution of the target task is stopped, and a new target task is determined again from the task queue. Thus, by directly packaging the target function into the target task and scheduling the thread to execute the corresponding target task, the process of matching the operation language with the thread pool can be omitted, the thread pool is accurately scheduled, the situation that more memory needs to be occupied when the execution state of the target task is cancelled by adopting a lock mechanism is avoided, and the user experience is improved. And the service execution efficiency is ensured.

The invention provides a business process intelligent configuration and security execution method, system and device, and the method comprises the steps: converting a natural language demand into a BPMN 2.0 process model based on a large language model and an enterprise knowledge base; the service rule description is converted into a Grouping script through multi-level security compiling; the process and the script are executed in the Flowable process engine integrated with the security sandbox, and execution data are collected; and calculating a process health score based on the data, generating and implementing an optimization suggestion, and feeding back a result to the knowledge base. The problems that a traditional process system depends on manual coding, the script safety is poor, and continuous optimization is lacked can be solved. The full-link automation and intelligentization of the business process from design, execution to optimization can be realized, the development efficiency and the system security are greatly improved, and the process has the self-evolution capability through closed-loop feedback.

The invention provides a training fault tolerance method and device applied to a distributed training system and a chip product, and relates to the technical field of distributed training. The method comprises the steps that under the condition that execution of a distributed training task is interrupted, a fault node is determined from a plurality of computing nodes, and the fault node refers to a computing node which cannot continue to participate in execution of the distributed training task; determining a first network domain based on the network domains to which the plurality of computing nodes belong, the first network domain being the network domain to which the fault node belongs; and under the condition that the standby node exists in the first network domain, selecting the standby node from the first network domain to replace the fault node. According to the embodiment of the invention, the standby node belonging to the same network domain as the fault node is adopted to replace the fault node, so that the execution stability and the execution efficiency of the distributed training task can be maintained.

The invention discloses a millimeter-wave radar operation management and control system based on anti-interference processing, relates to the technical field of radar operation management and control, solves the technical problem that the operation trend of a millimeter-wave radar cannot be predicted in the prior art, and particularly relates to a method for analyzing the interference influence of the millimeter-wave radar in a detection area by an interference influence analysis unit. Interference information and influence information are collected, and low-efficiency detection signals or high-efficiency detection signals are generated according to information analysis; the operation fault detection unit performs operation fault detection on the millimeter wave radar, collects fault detection information, obtains an operation fault detection coefficient, and generates a detection maintenance signal or a detection qualified signal through coefficient threshold comparison; the operation trend analysis unit analyzes the operation trend of the millimeter wave radar, collects frequency adding information and constant frequency information, and generates an efficiency reduction signal or an efficiency normal signal according to information analysis; and the operation management and control platform performs operation management and control according to the corresponding type signal.

The invention discloses a one-stop checking and submitting system, which comprises a data checking module used for providing checking service for submitted data; the data packaging module is used for packaging and packaging the submitted data passing the verification and distributing an identifier for each data packet; the data submission module is used for submitting the data packet to a supervision mechanism; and the feedback analysis module is used for monitoring and analyzing feedback information submitted by supervision in real time, and automatically analyzing the feedback information. According to the invention, a unified inspection service is provided, the abnormal condition of data can be found in time, risk prevention measures are taken in advance, the source is traced, and the overall submission process efficiency is greatly improved.

The present invention discloses a method for positioning a three-dimensional model component with an adaptive optimal viewing angle. The method comprises the following steps: step 1: obtaining the specified model component and basic information of the scene camera, and generating camera viewing angle parameters for browsing the model; step 2: uniformly generating discrete points on the spherical surface as viewing angle candidate positions; performing operations such as neighbor relationship calculation and orientation information acquisition on the discrete candidate points; step 3: performing operations such as generating the viewing angle candidate position viewPoint n Evaluation is performed, and the best viewing angle is selected as the final camera viewing angle setting position; Step 4: After obtaining the best viewing angle with better visibility and higher orientation priority through comprehensive evaluation, the three-dimensional scene camera is dynamically set and gradually updated to the viewing angle. The present invention has the advantages of being able to adaptively position the camera to the best viewing angle for observing model components, accurately, efficiently and stably.

The invention discloses a fire station regional rescue system, which relates to the technical field of fire emergency rescue, and comprises a data acquisition module for acquiring a fire station resource state and jurisdiction alarm information; the model updating module analyzes the alarm information and generates a structured event vector so as to dynamically update the digital twin data model; the scheme generation module is used for generating a recommendation scheme containing a predicted dynamic combination, a route and time through calculation of an optimization engine on the basis of real-time resources and the updated model; the instruction confirmation module generates an action instruction set containing elastic parameters according to the confirmation scheme and issues the action instruction set to the terminal, and the terminal autonomously plans a microscopic path based on the parameters and local environment data; the data actual measurement module collects action actual measurement data; and the feedback adjustment module calculates the deviation between the actually measured data and the predicted data and adjusts the parameters of the digital twin model according to the deviation. According to the method, dynamic optimization decision, terminal elastic execution and model closed-loop self-learning are realized, and the accuracy, adaptability and overall efficiency of rescue response are improved.

The invention belongs to the technical field of water conservancy projects, and provides a dam mass data distributed processing method based on a cloud computing architecture, which comprises the following steps: S1, performing unified access and standardized description on multi-source heterogeneous dam monitoring data, and generating a structured data object with a spatio-temporal index; s2, performing adaptive data fragmentation and distributed storage optimization based on space-time attributes and access features of the data objects; s3, according to the characteristics and resource requirements of the computing tasks, constructing a dynamic extensible parallel computing workflow; s4, in the process of executing the parallel computing workflow, implementing resource flexible scheduling and task migration based on load feedback; and S5, performing multi-dimensional aggregation on the processing result, and feeding back to the data storage layer.

The invention relates to the technical field of computers, in particular to a production scheduling optimization method and system based on a dynamic algorithm engine, and the system comprises a data processing module which comprises a preprocessing unit used for preprocessing collected order basic data to output order features; the scheduling solving module comprises a function construction unit used for constructing a scheduling optimization objective function; the disturbance recalculation module comprises an evaluation unit used for determining an influence domain of scheduling execution abnormity according to real-time industrial production resource constraints; the schedule judgment module is used for determining whether the stability of the production schedule meets the requirement or not according to the fluctuation characterization value; the delay adjusting module is used for determining a transmission delay coefficient between scheduling processes according to the updating frequency of the recalculation scheduling scheme; and the penalty factor adjusting module is used for determining the dynamic load penalty factor of the high-load equipment in the scheduling optimization objective function solution according to the conflict rate of the production resources in the production scheduling plan. According to the invention, the stability of production scheduling is improved.

The invention discloses a target strategy model training method and device, an instruction execution method and device and a medium. The training method of the target strategy model comprises the following steps: determining a to-be-executed instruction sequence; determining memory occupancy information used for executing instruction sequence hardware; based on the instruction sequence, the memory usage information and the initial strategy model, determining an execution mode corresponding to the instruction sequence; evaluating the execution mode to obtain evaluation information; performing iterative training on the initial strategy model based on the instruction sequence, the memory usage information, the execution mode and the evaluation information; and in response to the condition that the iteratively trained initial strategy model meets a preset training ending condition, taking the iteratively trained initial strategy model as a target strategy model. According to the embodiment of the invention, the execution efficiency of the instruction sequence can be improved.

The utility model provides a portable external diaphragm pacemaker, and belongs to the field of diaphragm pacemakers. According to the structure, a bottom plate is fixedly connected to the bottom end of a diaphragm pacemaker host, a plurality of fixing holes are formed in the bottom plate, a rotating table is fixedly connected to the bottom plate, one side of a cross arm is connected with the rotating table, a rotating disc is arranged on the other side of the cross arm, a base is connected to the rotating disc, and a lead screw is connected to the lower side of the base in a threaded mode; an electrode slice of the diaphragm pacemaker host is fixedly connected to the bottom end of the lead screw. On the premise that the electrical principle is not changed, the electrode slice is carried on the two-axis movement mechanism, free positioning is carried out on the horizontal plane, and then the action that the electrode slice is attached to the body surface of a patient is achieved by means of vertical feeding movement of the lead screw mechanism. The action mode is high in automation degree, positioning precision and execution efficiency are better guaranteed, standardized operation is expected to be achieved, and remarkable technical progress is achieved.

The invention provides an inter-system integration method and device based on configured zero codes, a graphical arrangement front end is constructed by adopting frameworks such as Vue, a back-end execution engine is constructed based on Spring Boot / Cloud, and a complete nodal process configuration and execution system is formed. According to the system, JSON Schema metadata is generated by automatically collecting and analyzing a Feign interface, and a user is supported to assemble integrated logic in a zero-code mode by dragging prefabricated function nodes and connecting lines; and the background models the structured JSON into a directed acyclic graph for topological sorting and static verification based on types and rules, and finally serializes the structured JSON to configure persistent storage. According to the method, visual and configured construction of integrated logic is realized, and the development threshold and the coding quantity are greatly reduced; and through built-in verification and structured storage, the reliability, maintainability and traceability of the process are remarkably improved, so that business personnel or common developers can rapidly and flexibly arrange and reliably operate the enterprise-level integrated process.

The embodiment of the present application provides a method, device, equipment and storage medium for transmitting Msg3, the method comprising: a terminal device receives Msg3 repetition transmission indication information sent by a network device, determines the configuration parameters for repetition transmission of Msg3; and repetition transmission of Msg3 according to the Msg3 repetition transmission indication information. The method, device, equipment and storage medium for transmitting Msg3 provided in the embodiment of the present application perform repetition transmission of Msg3 according to the channel conditions, improve the reliability of Msg3 transmission and reduce the number of retransmissions, and ensure the efficiency of random access process execution.

The invention provides a remote data calling method and device, equipment and a storage medium. The method comprises the following steps: receiving first request information sent by a client; the first request information is used for requesting to call remote data; the first request information comprises at least one of the following items: a remote interface address, a remote interface parameter, a script instruction and a server link address; determining a request type according to the first request information; forwarding the first request information to a remote interface address in response to the request type being API call, and receiving response data; in response to the fact that the request type is a script instruction, forwarding the first request information to a server link address, executing the script instruction, and determining an execution result; and sending the response data or the execution result to the client. The request is directly forwarded and processed according to the request type, unnecessary processing steps are reduced, the integration efficiency is improved, the integration workload is reduced, and the development complexity is reduced.

The invention discloses a deep learning task execution method and device based on running time length prediction. The method comprises the following steps: executing a target deep learning task according to a current task allocation strategy through each computing node in an intelligent computing cluster, and obtaining a performance monitoring data sequence of computing resources on each computing node within a specified duration after the target deep learning task is executed for the specified duration, processing the performance monitoring data corresponding to each computing node, and for target monitoring data corresponding to each computing node, extracting a time domain feature of the target monitoring data in a time domain and a frequency domain feature of the target monitoring data in a frequency domain; and inputting the time domain feature and the frequency domain feature into a pre-trained time length prediction model, determining a running time length required for completing the target deep learning task, and according to the running time length, adjusting a current task allocation strategy so as to execute the target deep learning task according to the adjusted task allocation strategy.

The present invention belongs to the field of computer technology, and discloses a multi-table connection query method, device, equipment and storage medium. The present invention extracts table connection relations and data filtering conditions in a target multi-table query statement, and constructs a multi-table connection matrix according to the table connection relations; performs connection probability analysis on the multi-table connection matrix through a preset connection strategy model to obtain a multi-table connection vector; constructs a query execution plan according to the multi-table connection vector and the data filtering condition; and performs database query based on the query execution plan. Since the preset connection strategy model can perform probability analysis on the multi-table connection matrix, a table connection sequence with high execution efficiency is selected according to the connection probability, and a multi-table connection vector is generated, there is no need to enumerate the connection space, and then a query execution plan with high execution efficiency can be generated according to the multi-table connection vector for query, which avoids enumerating all connection spaces while also ensuring the execution efficiency of the query execution plan.

The application discloses a distributed test resource scheduling method, comprising the following steps: receiving test task request information sent by at least one task node; S2: obtaining resource types required by test tasks according to the received test task request information, and acquiring working state queue information of at least one resource node meeting the resource type condition; S3: performing resource scheduling according to the test task request information and the working state queue information, generating a scheduling result in such a manner that each test task to be processed in the task node is sequentially completed and the total time is the shortest, and allocating resource nodes according to the scheduling result; sending the scheduling result to the task node, and sending at least one working request to the resource nodes allocated according to the scheduling result. Through priority scheduling, the application can still stably run various tasks when the task queue is long, and effectively guarantees the execution efficiency of the test system when long tasks and short tasks are alternately executed.

The invention discloses a display method and device, equipment and a storage medium, and the method comprises the steps: determining a target key point of a target part, determining a moving direction of the target key point from a plurality of preset candidate directions, and carrying out the movement of the target key point after an end point of an interaction vector of a user in a user interface is operated according to the interaction of the user. And according to the endpoint of the interaction vector and the moving direction, determining a target position which can be used for representing the moving distance of the target key point along the moving direction after the interaction operation, and finally, according to the target position, determining display data. Thus, the moving distance of the target key point in the moving direction can be determined, under the condition that the moving direction follows the constraint condition, it can be naturally guaranteed that the moved three-dimensional model structure also follows the constraint condition, and the execution efficiency of simulation services is further guaranteed.

The present disclosure discloses a method for optimizing matrix multiplication of an on-chip system and related products. The on-chip system is included in a computing processing apparatus of a combined processing apparatus. The computing processing apparatus includes one or a plurality of integrated circuit apparatuses. The combined processing apparatus further includes an interface apparatus and other processing apparatus. The computing processing apparatus interacts with other processing apparatus to jointly complete a computing operation specified by a user. The combined processing apparatus further includes a storage apparatus. The storage apparatus is connected to the apparatus and other processing apparatus, respectively. The storage apparatus is configured to store data of the apparatus and other processing apparatus. The solution of the present disclosure may reduce the amount of data transmission between an internal device and an external storage apparatus, thus minimizing the I / O bottleneck caused by bandwidth limitations and then improving overall performance of an integrated circuit apparatus.

The invention provides a network optimization task execution method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining node type information and node level information of a first task node, obtaining initial task data according to the node type information and the node level information, and obtaining an initial network optimization model, the initial network optimization model has corresponding historical rule data, training the initial network optimization model according to the initial task data and the historical rule data to obtain a target network optimization model, and executing a second network optimization task in the network optimization system according to the target network optimization model. According to the method and the device, full-process data marking can be carried out on a plurality of task nodes of network optimization, data marking in a thinking analysis process of network optimization is realized, the operation behavior marking rate is effectively improved, effective information after loss is avoided, the forming rate of reusable knowledge is effectively improved, and the data marking efficiency is improved. And the execution effect and the execution efficiency of the network optimization task of the network optimization system are ensured.

The present application discloses a storage management method, system and device for medical data, which are applied to the field of medical data management technology, including: after the medical device finishes the current medical treatment, based on the data collected during the current medical treatment, a piece of medical data to be stored is generated; the current free address of the data storage unit and the current free address of the sequence number storage unit are determined; starting from the current free address of the data storage unit, the medical data is stored, and starting from the current free address of the sequence number storage unit, the current free address of the data storage unit is stored; after the storage is completed, the free address of the data storage unit and the free address of the sequence number storage unit are updated. By applying the scheme of the present application, historical medical data can be effectively stored and viewed. Since the data storage unit and the sequence number storage unit are respectively set, the execution efficiency of these operations can be effectively guaranteed when performing subsequent operations such as data reading and data deletion.

The invention relates to the technical field of warehouse supervision, and particularly discloses a warehouse work order task whole-process intelligent supervision method and system, and the method comprises the following steps: obtaining work order tasks and task information in a work period of the warehouse work order tasks, and calculating the execution stability rate of the work order tasks; a period execution stable signal or a period optimization recheck signal is obtained; calculating a path deviation rate and comparing the path deviation rate with a path deviation rate threshold value; obtaining a work order task path normal signal or a work order task path abnormal signal; calculating a task processing time deviation rate and comparing the task processing time deviation rate with a task processing time deviation rate threshold value to obtain a work order task execution abnormal signal or a work order task double-monitoring signal; calculating an execution deviation performance value of the work order task and comparing the execution deviation performance value with an execution deviation performance qualified value; the execution verification qualification signal or the work order task execution abnormal signal is obtained and generated, the accuracy and timeliness of warehousing work are improved, and an executor or execution equipment in the warehousing work order task execution process is effectively supervised.

The present invention relates to a method and system for synchronizing data in different networks based on a dynamic resource pool of an isolation device, the method comprising: constructing an isolation area, storing the required external network data in the isolation area; constructing a mirror operation isolation area in the isolation area, when a user executes a certain intranet program in the intranet: if the intranet program needs to use static data of the external network, read the corresponding static data from the isolation area, cache it in the storage area of ​​the intranet for use by the intranet program; if the intranet program needs to use dynamic data of the external network, read the input data of the corresponding intranet program, transfer the input data to the mirror operation isolation area, execute the intranet program in the mirror operation isolation area, call the required dynamic data in the isolation area, and obtain output data, cache the output data to the storage area of ​​the intranet, and read it into the memory. The present invention can effectively realize a resource scheduling method that converts traditional function and interface interactions into data interactions.

This application relates to a product search method, apparatus, device, and medium in the field of e-commerce technology. The method includes: responding to a product search request and obtaining a recall list coarsely recalled based on user-input search keywords; determining the node servers corresponding to each recalled product in the recall list, where each node server caches multiple search-related scores for some recalled products across different dimensions, the search-related scores representing the relevance between the recalled products and the search keywords in a specified dimension; sending a score calculation request to each node server to obtain the search scores calculated by the node servers for the cached recalled products, the search score for each recalled product being calculated based on multiple search-related scores for that product; and constructing a search results list by filtering products from the recall list whose search scores meet preset conditions based on the search scores. This application can quickly and accurately search for products.

The invention discloses a simulation service execution method, device and equipment and a storage medium, simulation data including a target structure and working condition data of the target structure is determined to execute a simulation service to obtain a simulation result, and then the simulation service is executed according to a matching result of deformation quantities corresponding to all connecting pieces included in the simulation result and a preset deformation threshold value. And generating a load file. Therefore, the research and development personnel can be prompted to adjust the demand in time under the condition that the demand of the research and development personnel is unreasonable, so that the resource waste is avoided, and the execution efficiency of the simulation service is ensured.