283results about How to "Improve execution efficiency" patented technology

The invention discloses an intelligent Web testing method and system based on Playwright and AI, and belongs to the technical field of Web testing. According to the method, a test script is executed through a Playwright framework, page elements and operations are packaged, and multi-dimensional information such as a DOM tree, network interaction and screenshot is collected; analyzing the test intention by means of the optimized language model, and generating a structured description; analyzing failure reasons through a multi-modal model in combination with failure moment data and intention description; and searching candidate elements based on an analysis result, generating a repair script, deploying a test node cluster dynamic allocation task and generating a report. According to the scheme, AI and automatic testing technologies are fused, intelligent promotion of the whole testing process is achieved, manual intervention is reduced, the maintenance cost is reduced, the testing accuracy and execution efficiency are improved, the testing coverage range is expanded, and reliable support is provided for quality assurance under Web application rapid iteration.

The invention provides a user interface testing method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the following steps: acquiring a target test script, and performing semantic conversion on an operation instruction in the target test script by utilizing a first model to obtain a target test step set containing business semantic description; the target test step set is executed, in the process of executing the target test step set, the first model is used for determining the positioning mode of the target interface element according to the business semantic description, corresponding interaction operation is executed, and actual interface output is obtained; in response to execution failure of the target test step set, generating a diagnosis result by using a first model at least based on the actual interface output and the business semantic description; and inputting the diagnosis result into a second model, generating a modification code snippet by the second model, and applying the modification code snippet to the target test script.

The invention discloses a compiling method for compiling a C language source code into an RISC-V assembly code. The method comprises the following steps: acquiring a C language source code; performing lexical analysis on the C language source code to generate a mark flow; performing syntactic analysis on the mark flow, and constructing an abstract syntax tree; performing semantic analysis on the abstract syntax tree to generate a target abstract syntax tree; constructing a runtime environment of the RISC-V assembly code; generating an intermediate code and a control flow diagram corresponding to the intermediate code according to a rule in the runtime environment and the target abstract syntax tree; generating a target code by using the intermediate code and the control flow diagram corresponding to the intermediate code; according to the technical scheme, the intermediate representation more adaptive to RISC-V custom instruction mapping can be generated, so that the execution efficiency of assembly codes is improved; and meanwhile, by designing a lightweight runtime environment, the performance overhead is further reduced.

The invention discloses a cuboid and cylinder space collision detection method, which comprises the following steps: based on a preset projection axis set, respectively calculating projection intervals of a cylinder and a cuboid on each projection axis in the preset projection axis set by adopting a projection axis method; if at least one projection axis which enables the projection interval of the cylinder to be not overlapped with the projection interval of the cuboid exists in the preset projection axis set, judging that the cylinder and the cuboid do not collide with each other; and if the projection axis which enables the projection interval of the cylinder to be not overlapped with the projection interval of the cuboid does not exist in the preset projection axis set, judging whether the cylinder collides with the cuboid or not by adopting projection surface convex hull detection. The efficiency and the accuracy of collision detection are effectively considered by comprehensively applying a staged strategy combining rapid projection axis elimination and precise projection surface convex hull judgment.

The invention provides a unified computing power management and control platform and method.The computing power management and control platform is integrated with a plurality of intelligent computing centers in different position areas through a unified northbound interface, a resource management module abstracts physical resources of the intelligent computing centers into virtual resource data, and a unified resource pool is constructed; the data acquisition module receives operation monitoring data of each intelligent calculation center and preprocesses the operation monitoring data; the resource sensing module is used for constructing a dynamic resource portrait for the uniform resource pool based on the preprocessed operation monitoring data; the task sensing module performs resource constraint and service quality demand analysis on a calculation task submitted by a user, and constructs a task portrait; the resource scheduling module forms a resource scheduling decision result according to the dynamic resource portrait and the task portrait; and the resource arrangement module performs resource scheduling and calculation task allocation according to the resource scheduling decision result. The overall utilization rate of the heterogeneous computing power cluster is remarkably improved, and the island effect of a traditional resource pool is broken through.

This application relates to a harvesting robot, which includes a base, a harvesting mechanism, a vibration mechanism, and a loading frame. The harvesting mechanism is disposed on the base. The vibration mechanism includes a carrier, a drive, an eccentric wheel, a connector, and a limiting mechanism. The carrier is stacked on the base, and the drive is disposed on the base. The output shaft of the drive is connected to the eccentric wheel. One end of the connector is rotatably connected to the eccentric wheel, and the other end of the connector is rotatably connected to the carrier. The drive drives the carrier to reciprocate relative to the base. The limiting mechanism is disposed on the side of the carrier away from the base, and the loading frame is restricted by the limiting mechanism. When the carrier reciprocates, it drives the loading frame on the carrier to move, thereby flattening the items such as fruits and vegetables in the loading frame. Thus, the harvesting mechanism can be fixed in a fixed position to fill the loading frame. There is no need to take pictures of the loading frame or control the change of the reciprocating position, resulting in high execution efficiency and high overall working efficiency of the harvesting robot.

This application relates to the field of wired remote control technology, and discloses a testing method, a wired remote control, and a wired remote control testing system. The wired remote control includes: a button control chip configured to acquire simulated button signals during testing, the simulated button signals being used to simulate the signals generated when a physical button is pressed; and a main control chip connected to the button control chip, configured to receive the simulated button signals and use these signals to test the firmware under test in the main control chip. Through this method, the dependence on physical mechanical structures can be eliminated, and the testing of the firmware under test in the main control chip can be achieved through interaction between the button control chip and the main control chip within the wired remote control, thus verifying the robustness, fault tolerance, and stability of the firmware under test in the main control chip.

The embodiment of the present specification provides a logistics service object scheduling method, which obtains service data of a target object; then performs data statistics on the service data through a service evaluation index to obtain a service evaluation parameter; and performs data statistics on the service data through a parameter influence index to obtain an influence factor; then adjusts the service evaluation parameter based on the influence factor to obtain a regional familiarity of the target object to a target region; and further schedules a service process corresponding to the target object according to the regional familiarity. Thus, the logistics service capacity resource dynamic scheduling process is realized. Since the multi-dimensional comprehensive service evaluation index is used to quantify the logistics service execution effect, and the multi-dimensional influence factor is used for quantitative correction, the evaluation accuracy of the service effect of the target object in a specific region is improved, and the service process is scheduled based on the obtained regional familiarity, so that the execution efficiency of the logistics service is improved.

The present disclosure provides an intelligent scheduling method, a model training method and a device and system thereof. The method comprises: in the case that a target management node can utilize its own processing resources to schedule a kth rendering task, obtaining kth target state information corresponding to each slave node in N slave nodes contained in the next level of the target management node; the target management node is a jth management node in an ith level in the cluster; obtaining k-1th scheduling feedback information; inputting the kth target state information corresponding to each slave node contained in the next level of the target management node, the k-1th scheduling feedback information, and the task characteristics of the kth rendering task into a target neural network model to obtain a target scheduling strategy of the kth rendering task; and determining a target slave node from the N slave nodes according to the target scheduling strategy of the kth rendering task to allocate the kth rendering task to the target slave node.

The application discloses a visual language navigation method based on adaptive prompt information during testing, comprising the following steps: obtaining natural language-based navigation instructions and 360-degree panoramic visual observation information of an intelligent agent; extracting low-frequency visual features of sub-images and selecting valuable information from an image memory bank for prompting; extracting a text feature vector corresponding to the navigation instructions and an initial state vector of the current environment; selecting historical information from the visual feature memory bank using the state vector for prompting; inputting the state vector and the instruction features into a visual-language interaction module to generate navigation action selection; updating the normalization layer in the full connection layer according to the prediction score of the navigation action selection; and repeating the above steps until the intelligent agent stops selecting or reaches the maximum number of movement steps. The application can effectively enhance the navigation performance of the pre-trained intelligent agent model in unknown test environments.

The invention discloses an account parameter configuration method and device, electronic equipment and a program product, and relates to the technical field of artificial intelligence, and the configuration method comprises the steps: collecting a plurality of dimension data of a target user in a first preset time period under the condition of obtaining the authorization of the target user, fusing all the dimension data, and obtaining a fusion result; obtaining target feature data; a target decision model is adopted to process the target feature data, a configuration strategy set for the target user account parameters is obtained, and the model structure of the target decision model at least comprises a time sequence model and a preset rule decision model; and filtering all configuration strategies in the configuration strategy set to obtain a target configuration strategy set, and configuring the target user account parameters based on the target configuration strategy set. According to the invention, the technical problem that the parameters of the user account cannot be efficiently configured in the prior art is solved.

In order to solve the problem of low actual execution efficiency caused by frequent data update when debugging the chip interface of the ATE device in the prior art, the application provides a system, a method and an application for simulating the debugging interface of a chip, comprising: an input module, a debugging interface device and a chip to be tested; wherein the input module is used for inputting debugging instructions; the debugging interface device interacts with the input module to batch store the debugging instructions; the chip to be tested interacts with the debugging interface device to generate corresponding protocols according to any debugging instruction and the debugging interface device to test the chip to be tested; the system has the advantages of simple structure, and does not need to frequently update data to the DIO unit of the hardware, can batch update data, uniformly trigger transmission, and improves the execution efficiency of the ATE device simulating the debugging interface of the chip.

This application provides a directed acyclic graph (DAG) scheduling method and system for multiple toolchains in intelligent agents, solving the technical problems of existing scheduling methods that rely on manual orchestration, have high topological redundancy, and low execution efficiency. First, it receives multi-tool collaboration task instructions and parses them to obtain a set of tool identifiers to be orchestrated and corresponding tool capability declaration texts. Then, it extracts historical call topology patterns with time-stamped edges; next, it retrieves candidate directed edges that meet capability connection conditions and combines them to generate an initial DAG skeleton; then, it eliminates redundant edges to obtain a simplified DAG structure; finally, it generates a tool call execution sequence containing time-series tool identifiers and a predecessor dependency list. This invention can achieve automated and efficient scheduling of multiple toolchains, adapt to dynamic task requirements, and reduce the overall task execution time.

The invention belongs to the technical field of information technology, and discloses a special signal generating device based on software defined radio and a GPU server, comprising: a graphic processing unit used for generating high-speed orthogonal data streams corresponding to various communication systems and modulation modes, the high-speed orthogonal data streams being transmitted to an intermediate frequency signal unit through an optical fiber; the intermediate frequency signal unit is used for receiving the high-speed orthogonal data stream, completing signal modulation and outputting an intermediate frequency signal; the software-defined radio platform is used for carrying out secondary development to realize signal generation and reception, and the secondary development builds a heterogeneous system integrated by a central processing unit and a graphic processing unit based on general radio software; the central processing unit is used for task scheduling and memory configuration; the invention aims to solve the problem that a signal generating device in the prior art cannot realize high-efficiency collaboration of a central processing unit and a graphic processing unit in high-speed data stream processing.

The application discloses a vehicle control method, a control device, equipment and a storage medium, and belongs to the technical field of vehicle control. The method comprises the following steps: acquiring a verification process of a vehicle according to a first operation instruction, the first operation instruction indicating an intention of making the vehicle execute a power supply loop access operation, and the verification process being used for determining whether the first operation state of the vehicle supports the power supply loop access operation through a plurality of verification actions; executing the plurality of verification actions according to an execution sequence indicated by the verification process; after executing any verification action, updating a global state index according to an execution result of any verification action, and determining a verification result of the verification process according to the global state index. Through the execution result of any verification action, the global state index is updated, the verification process is globally visible, fault positioning is clear, and the system reliability and maintainability are significantly improved.

The application discloses a high-parallelism reconfigurable multi-axle vehicle dynamics simulation method, a reconfigurable parameter model is constructed by reading parameters; a six-degree-of-freedom coupled dynamics model is established; an initial state is solved based on static force balance; tire slip rate and braking force are calculated; terrain ground contact determination is carried out based on a double-layer elevation map; and vehicle pose and dynamics state are updated by multi-substep integration. The key lies in that a single-step evolution process of the dynamics model is converted into a batch state transition mapping and a computation graph is constructed, the computation graph is cyclically fused and compiled and exported, a high-parallelism simulation execution model supporting input tensors with variable batch size in runtime is generated, and batch control instructions are received, and parallel stepping is implemented on effective vehicles in combination with an activation mask matrix. The application improves adaptability under complex terrain through unified parameter model and double-layer terrain determination, and greatly improves the calculation efficiency and precision of multi-vehicle batch simulation through computation graph compilation and mask parallel processing.

Embodiments of the present disclosure provide a data processing method, a distributed system, an electronic device and a storage medium. The method is applied to a distributed system comprising a master node and a plurality of slave nodes, and comprises: the master node determining task information allocated to each slave node according to a hierarchical attribute of a target model and a computing power state of the plurality of slave nodes, wherein the task information is used to specify a model layer processed by the corresponding slave node; each slave node performing weight quantization processing of the corresponding model layer based on the allocated task information to obtain complete quantized weights of the target model. The method realizes full-link collaborative optimization from computing, memory to storage, significantly improves the execution efficiency of weight quantization tasks and the utilization rate of hardware resources, and provides technical support for efficient deployment of large-scale models.

This invention belongs to the field of motherboard power supply technology. It discloses a motherboard intelligent power supply method and system based on fault diagnosis feedback. The method involves determining the motherboard's historical power supply data and storing it in a preset fault database. Within this database, a collection area, an isolation area, and a trust area are defined. A collection channel is established between the isolation area and the collection area, and a verification channel is established between the isolation area and the trust area. The data within the corresponding collection area is monitored and verified within the collection channel, and the data that passes the monitoring and verification is input as an anomaly parameter to the isolation area. Furthermore, this invention solves the problem that when existing motherboards are undergoing fault diagnosis, if the fault is a maliciously created fault, the fault database is easily affected by the malicious fault, leading to inaccurate power supply strategies output.

The invention provides an AI-based network intrusion prevention data processing method and system, and the method comprises the steps: obtaining original flow data generated in a network communication process, carrying out the discretization segmentation of the original flow data, generating a flow data unit set, carrying out the threatening feature recognition of each flow data unit, and carrying out the threatening feature recognition of each flow data unit. According to the matching degree of the identified threat features and a preset threat mode library, generating threat evaluation vectors, calculating threat feature association degrees between adjacent flow data units based on the threat evaluation vectors of continuous time windows, constructing a threat evolution trajectory map, and inputting the threat evolution trajectory map into a preset generative adversarial network model to obtain a threat evolution trajectory map; performing feature boundary optimization on the threat evolution trajectory map to generate a threat judgment matrix; protocol semantic analysis is carried out on the threat judgment matrix, threat confidence verification is carried out on the threat judgment matrix in combination with the protocol field association relation obtained through analysis, and a network intrusion prevention instruction is generated. According to the invention, pertinence and execution efficiency of network intrusion prevention response can be improved.

The application discloses a kind of dynamic partitioning method and system based on data skew model, it is related to big data technology field, including collecting data and pre-processing data, establish data skew evaluation model to predict pre-processed data, according to data characteristics, the data skew degree in job processing process is predicted, determines partition optimization strategy, designs evaluation experiment to compare dynamic partitioning with static partitioning, and repeatedly optimizes dynamic partitioning.This application proposes dynamic partitioning algorithm based on data skew model, which can select suitable partitioning strategy according to the skew degree of the data being processed, use the algorithm of three optimization methods based on Spark dynamic partitioning to process data performance comparison experiment, design and verify the universality and efficiency of the above dynamic partitioning scheme, can make the load balancing of the whole computing cluster, make full use of the computing resources of cluster, more efficiently complete data processing and calculation.

The invention provides an instruction processing method and device, electronic equipment, a storage medium and a chip, and relates to the technical field of computers. The method comprises the following steps: acquiring execution time information of a plurality of to-be-processed instruction sequences and position information of the plurality of to-be-processed instruction sequences; according to the execution time information and the position information, determining an execution sequence of the plurality of to-be-processed instruction sequences; and executing the plurality of to-be-processed instruction sequences according to the execution sequence. The execution time information reflects the time characteristic, the position reflects the space characteristic, the time characteristic and the space characteristic are considered at the same time, instruction execution better meets the actual requirement, and the instruction execution efficiency is improved.

The application relates to the technical field of network security, in particular to a Java Restful interface security test method based on static analysis, which comprises the following steps: generating a Jimple intermediate representation of source code of a target Java application; performing data flow analysis based on the Jimple intermediate representation to generate a complete data flow graph; identifying a pollution source and tracking a pollution propagation path on the basis of the data flow graph, judging whether a pollution object reaches a convergence point, and determining a vulnerable interface; extracting an interface routing signature in the pollution analysis process to generate routing signature information; grouping interfaces based on parent routing of the interfaces, performing interface security test in combination with the routing signature information, introducing a reinforcement learning method to dynamically optimize a test strategy, performing parameter variation and attack load injection of a test case on the vulnerable interface; and setting a security monitoring strategy in a dynamic plug-in manner, and completing interface security risk judgment according to recorded logs and the test case.

The application provides a method for automatically decomposing and dynamically scheduling quantum tasks under a quantum super-fusion architecture. The method comprises: obtaining a task script corresponding to a quantum task, and performing parsing processing on the task script to obtain circuit information, the circuit information including quantum bit quantity and circuit gate depth information; generating a plurality of sub-task scripts and a sub-task execution chain according to the circuit information and the task script, the plurality of sub-task scripts including a compiled task script, a simulated task script and a post-processing task script; for any one sub-task script, determining a job scheduling script corresponding to the sub-task script according to the circuit information; associating and binding a plurality of job scheduling scripts according to the sub-task execution chain to generate a target execution script, and submitting the target execution script through a preset native interface, thereby improving the quantum task execution efficiency and resource utilization.

The present disclosure provides a data processing method and device, electronic equipment and computer readable storage medium, the method comprising: obtaining configuration information to be processed, wherein the configuration information is information for indicating target data to be deleted; generating a target deletion execution instruction according to the configuration information; sending the target deletion execution instruction to a database storing the target data based on a preset data operation interface, the database being configured to precompile the target deletion execution instruction, wherein the preset data operation interface supports placeholders and precompilation of the target deletion execution instruction; and deleting the target data in the database according to the target deletion execution instruction. According to the embodiments of the present disclosure, the target data in the database can be conveniently and efficiently deleted.

The disclosure provides a due diligence report generation method, which comprises the following steps: obtaining a due diligence task instruction through a digital human interaction module, and analyzing the due diligence task instruction to obtain key due diligence parameters of the due diligence task; task planning is performed based on the key due diligence parameters by a scheduling agent to obtain a task execution process of the due diligence task; wherein the task execution process comprises a plurality of subtask nodes; the scheduling agent schedules an execution agent matching a subtask type indicated by each subtask node according to the execution order between the plurality of subtask nodes to execute a corresponding subtask execution strategy, so as to obtain a target task execution result of the due diligence task; and a report generation agent generates a due diligence report of the due diligence task according to the target task execution result. The technical problems of low artificial docking efficiency, large instruction understanding deviation, lack of task allocation pertinence and long report generation period in the traditional due diligence processing process can be effectively solved.

This application discloses a data processing method, apparatus, storage medium, and program product, belonging to the field of data quality inspection technology. The data processing method includes: acquiring a first quality inspection algorithm and a second quality inspection algorithm; the first quality inspection algorithm is constructed based on a preset set of anomaly detection rules and is used to detect general anomalies in the data to be processed; the second quality inspection algorithm is constructed based on data processing rules input by the user and is used to detect target anomalies in the data to be processed; the data processing rules are determined based on the business information of the data to be processed; based on the business information of the data to be processed, the execution strategies of the first and / or second quality inspection algorithms are matched, and a target quality inspection algorithm is determined according to the execution strategies; based on the target quality inspection algorithm, quality analysis is performed on the data to be processed to generate a quality score for the data to be processed. The data processing method of this application achieves multi-faceted quality inspection, improving the coverage and accuracy of data quality inspection.

The invention discloses an audit industry-oriented large model agent collaboration system, which is characterized by comprising a main control module, at least two special agent modules and an audit knowledge base, and is characterized in that the audit knowledge base stores a knowledge graph and a rule of an audit field; the main control module is used for receiving an audit task description, disassembling the audit task description into sub-audit tasks, and scheduling the corresponding special agent module to execute the sub-audit tasks according to task types of the sub-audit tasks; the at least two special agent modules comprise a document analysis agent configured with a document language model and used for analyzing a to-be-audited document in combination with the audit knowledge base; the data analysis agent is configured with a data language model and is used for analyzing the to-be-audited structured data in combination with the audit knowledge base; and the main control module is also used for performing conflict arbitration and fusion on the analysis results returned by the at least two special agent modules to generate an audit work result.

The invention provides an automatic operation and maintenance scheduling system and method in a cloud computing environment. The method comprises the following steps: predicting a load demand curve through historical load time sequence data and real-time load indexes of an online service cluster; generating an arbitration decision of resource operation and maintenance scheduling according to the simulated resource occupation contour of the online service cluster constructed by the load demand curve and the resource request queue corresponding to the offline task cluster; issuing a reserved resource permission to the second control ring by the arbitration decision, and injecting a virtual node resource view complementary with the reserved resource permission in time and space into the first control ring; and when the real-time load index triggers the first control ring to perform resource scaling operation, the first control ring executes instance scaling in a resource boundary limited by the virtual node resource view, and the second control ring starts and stops the offline task instance in the corresponding resource block according to the current reserved resource permission. According to the technical scheme provided by the invention, collaborative scheduling of operation and maintenance of the online service cluster and the offline task cluster can be realized under load fluctuation.

This application discloses a real-time adaptive radiotherapy management system, relating to the field of medical technology. The system includes: a real-time data processing unit for acquiring real-time data of the target object during radiotherapy; an adaptive decision-making unit for determining a target radiotherapy plan matching the current state of the target object from multiple alternative radiotherapy plans based on the real-time data, wherein the multiple alternative radiotherapy plans are associated with different physiological motion phases or anatomical states of the target object; a plan execution sequence splitting unit for parsing and splitting each alternative radiotherapy plan into one or more hardware execution sequences; and an execution scheduling unit for sending at least one hardware execution sequence corresponding to the target radiotherapy plan to the control system of the radiotherapy equipment. This application solves the technical problem that existing adaptive radiotherapy systems, due to their rigid architecture and singular decision-making mode, cannot achieve highly real-time dynamic plan switching during treatment.