14results about How to "Improve execution speed" patented technology

The invention relates to a path planning method of a photovoltaic robot, the photovoltaic robot, equipment and a medium, and the method comprises the steps: setting a distance between adjacent paths according to a machine cleaning performance index, generating an internal cleaning path based on a photovoltaic plate map and the distance between the adjacent paths, and discretizing the internal cleaning path into a plurality of path points with expected poses; an acceptance path point is arranged on each sub-cleaning path of the internal cleaning path, and parameters of the acceptance path points comprise an expected cleaning area; executing an internal cleaning path, monitoring a pose error between an actual pose and an expected pose in real time, and determining a cleaning performance error according to an actual cleaning area and an expected cleaning area; when the pose error is greater than the pose tolerance threshold or the cleaning performance error is less than the cleaning tolerance threshold, a target internal cleaning path is generated and executed based on the pose error and / or the cleaning performance error. The execution speed and the cleaning efficiency of the photovoltaic robot on the cleaning path are improved, and meanwhile it is ensured that the cleaning quality reaches the expected standard.

The invention discloses an automatic test case generation and execution method, which comprises the following steps: obtaining input content uploaded by a user, and analyzing the input content uploaded by the user to obtain structured key data; generating a preliminary test case according to the structured key data and a general rule of a knowledge base, optimizing the preliminary test case according to historical data and a code coverage rate, and generating a test case; compiling a test script according to the test case, and executing the test script; analyzing and processing the test execution result, and generating an execution structure and a test case analysis report; and performing optimization processing on the test execution result and the historical data, and dynamically adjusting a test strategy according to an optimization processing result. The invention further discloses a system for realizing the automatic test case generation and execution method. The test efficiency is improved, the test coverage rate is increased, the execution performance is improved, and automatic continuous testing is supported.

The invention discloses an interface testing method and device based on a cloud platform and a nonvolatile storage medium. The method comprises the steps of obtaining target interface test case data used for target interface test from interface test equipment of a cloud platform; sending a first request message to a server based on a target interface corresponding to the target interface test case data, the first request message being used for indicating an operation type executed by the server; receiving a first response message corresponding to the first request message, and extracting verification information used for verifying an interface test result in the first response message; and verifying the verification information, and determining that the interface corresponding to the interface test case data passes the test under the condition that the verification is passed. The technical problems that a traditional interface testing method generally depends on manual operation, and is low in testing efficiency, difficult to use and unstable are solved.

The present subject matter discloses a system and a method for integration application environment migration utilizing hub and spoke architecture. In one implementation, the method for application environment migration comprising assessing at least one source application code of corresponding integration application environment by a processor (122) of an integration application server. The processor forecasts an assessment statistic (302) that provides at least one functional readiness (304) and a timeline (306) to complete the migration of the each source application code. The processor (122) further scans the each source application code of corresponding source application for generating the integration applications compatible with a target application environment and creates a relationship map to match components of the integrating applications with components of the target application environment. The processor (122) generates a re-factored code for the each source application code by breaking the each source application code into macro-services (426a, ..., 426n) and repackaging the macro-services (426a, ..., 426n) in accordance with the target application code. Thereby, updating components of the integration application environment as per the forecasted assessment statistic (302) and the re-factored code and thus migrating the integration application environment to the target application environment while re-platforming the updated components and the re-factored code of the integration application environment to the target application environment.

The invention relates to the technical field of computer software demand analysis and automation, and discloses an automatic writing method and system oriented to demand analysis, and the method comprises the steps: constructing a domain knowledge graph containing a component mutual exclusion and dependency relationship, and deducing and generating a component compatibility matrix; converting the unstructured demand text into structured features by using a natural language processing algorithm; generating a virtual configuration list in combination with the atlas, and performing conflict detection based on a compatibility matrix and a supervision protocol; when violation is detected, the topological connectivity is quantified by calculating the sum of in-degree and out-degree of the component in the map, and the component is retrieved and replaced according to the topological connectivity for automatic correction; monitoring a change event, calculating an influence domain by using a weight conduction algorithm, and triggering local re-verification; and finally, generating a descriptive text, and executing consistency check by reversely extracting numerical values. According to the method, the configuration verification efficiency and the correction stability are improved through matrix operation and topology analysis, and the accuracy of the demand analysis document is ensured.

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.

This invention discloses a method and system for processing personnel information for business administration based on big data, relating to the field of personnel information data processing technology. The method includes the following steps: acquiring personnel information; preprocessing the personnel information to obtain preprocessed text information; processing the preprocessed text information through an embedding layer based on a CNN-BERT model to obtain a word vector matrix; processing the word vector matrix sequentially through a CNN convolutional layer, pooling layer, and fully connected layer to obtain structured data; using an improved ant colony optimization algorithm to perform path optimization for multi-condition combined queries on the structured data to obtain the globally optimal retrieval path; retrieving personnel information that satisfies the multi-condition combined query from the structured data based on the globally optimal retrieval path; and adaptively updating the global pheromone of the improved ant colony optimization algorithm after each round of multi-ant colony collaborative search to accurately locate the target personnel information.

The invention relates to a software development application data processing method based on cloud computing, which belongs to the technical field of software development and comprises the following steps: S1, data receiving and preprocessing: receiving data from different sources based on application data information generated by a software development platform; the integrity and accuracy of data receiving are ensured, and errors in the data are identified and corrected through a check and error processing mechanism; and cleaning the received data, and removing invalid, repeated or abnormal data. According to the software development application data processing method based on cloud computing, by adopting an advanced encryption technology, multi-factor authentication and a strict data access control strategy, the security and privacy protection level of data can be remarkably improved; data leakage and unauthorized access can be effectively prevented, and the integrity and confidentiality of the data in the transmission and storage process can be ensured.

The invention provides a container sinking method and device based on a DPU, a storage medium and a program product, and relates to the technical field of computers.The method comprises the steps that under the condition that a first containerization platform receives a container operation request, calling information is generated based on target container information carried in the container operation request, and a first container network interface plug-in is called; under the condition that the calling information carries a preset sinking identifier, generating a hypertext transfer protocol request based on the target container information through the first container network interface plug-in, and sending the hypertext transfer protocol request to a second container module; receiving the hypertext transfer protocol request through a second container network interface plug-in in a second container module, and extracting target container information; executing an operation corresponding to the container operation request based on the target container information through the second containerization platform; the problem that the execution efficiency and the execution speed of a service application are low due to the fact that all containers run on a CPU of a server node can be solved.

The application discloses a kind of multi-task constraint end-to-end noisy speech emotion recognition methods based on teacher-student model, comprising: propose an end-to-end multi-task constraint network based on teacher-student model, draw lessons from the idea of knowledge distillation, after the multi-task training of teacher model is completed, the mature teacher model that has been trained is extracted to pure, significant emotional features, to guide the training process of student model;A multi-level enhancement loss mechanism is introduced, so that the student model can learn the key emotional information extracted from the clean speech by the teacher model in the middle layer;The idea of speech enhancement auxiliary task is adopted, and the speech enhancement auxiliary task is combined with multi-level enhancement loss;During the test phase, only the core process specific to speech emotion recognition classification in the student model needs to be focused on, effectively improving the execution rate of the test.The application realizes the speech emotion recognition task in noisy environment, improves the accuracy of emotion classification, and is suitable for intelligent customer service and mental health monitoring.

The invention belongs to the field of fault diagnosis, and particularly relates to a steam turbine fault diagnosis method based on multi-channel time-frequency spectrum cloud model fusion, and the method comprises the steps: carrying out the time-frequency transformation through multi-channel sensor data, and obtaining a plurality of time-frequency spectrums; then, dividing the cloud model into a plurality of sub-regions along the frequency direction, overlapping the sub-regions, and calculating feature parameters of the cloud model of each sub-region, namely a mean value, entropy and hyper-entropy, so as to form three matrixes; three convolutional neural networks are established respectively, the matrixes serve as input of the convolutional neural networks respectively, decision layer weighted fusion is carried out on output, a known state data set is used for training a model, and the output after model fusion is the fault type of the steam turbine; three feature matrixes are calculated according to the above steps for the to-be-tested monitoring data, and the three feature matrixes are input into the trained neural network model to diagnose the fault type of the steam turbine. The fault diagnosis precision can be effectively improved, early warning is provided, and safe and stable operation of the steam turbine is ensured.

The invention provides an identification method and system for a jacking mode of ship structural parts, and the method comprises the steps: dividing the ship structural parts into plate parts and profile parts through a modeling mode, judging whether the plate parts belong to batten parts or not, and carrying out the gantry jacking of battens if the plate parts belong to the batten parts; and if not, carrying out numerical control nesting on the plate. Only the section shape of the section part needs to be observed, and if the section shape is non-rectangular, section nesting is carried out; and if the section shape is rectangular, further judging whether the profile part belongs to a batten part or not so as to judge the nesting mode. The identification method can quickly identify the jacking mode of the ship structural part, and is simple and convenient to operate and wide in practicability; and parallel operation can be realized, so that the execution speed and efficiency are improved.

The invention relates to a data processing method and device, electronic equipment and a storage medium. The data processing method provided by the invention comprises the following steps: in response to a starting event for a target application instance, creating a target thread for running the target application instance based on a single-thread application framework; wherein the target application instance is an instance for opening a target application program to run; and in the process of running the target thread, running the target application instance based on the resource data of the target application instance bound in the target thread. According to the data processing method provided by the invention, the target application instance is operated based on the resource data of the target application instance bound in the target thread, so that the situation that the resource management identifier needs to be frequently transmitted when the resource data of the target application instance is used in the target thread is reduced; and the difficulty of managing the application instance resources through the resource management identifier is also reduced.