9165 results about "State diagram" patented technology

The invention discloses a mine rescue training and danger dynamic simulation method based on virtual reality, and the method comprises the following steps: S1, modeling a rescue process into a directed graph structure, and outputting a task state diagram bound with a virtual reality scene; s2, collecting an operation behavior, a task state, an environmental parameter and a physiological response, and constructing a training state vector; s3, inputting the state vector into the deep Q network to calculate a jump node evaluation value, and outputting a jump node; s4, modeling the control rule as a rule node, constructing a directed acyclic graph, binding a weight, and outputting a rule graph; s5, performing self-evolution on the rule atlas according to training feedback, and outputting an evolution structure; s6, reasoning in the evolution rule map, fusing the rule recommendation node and the jump node, and outputting a final task node; and S7, executing jump control according to the final node, loading a virtual scene, and pushing environment parameters, task contents and risk information. According to the invention, intelligent path decision and training process adaptive optimization of the mine rescue task are realized.

Implementations are directed to receiving unstructured free-form natural language input, generating a chatbot based on the unstructured free-form natural language input and in response to receiving the unstructured free-form natural language input, and causing the chatbot to perform task(s) associated with an entity and on behalf of the user. In various implementations, the unstructured free-form natural language input conveys details of the task(s) to be performed, but does not define any corresponding dialog state map (e.g., does not define any dialog states or any dialog state transitions). Nonetheless, the unstructured free-form natural language input may be utilized to fine-tune and / or prime a machine learning model that is already capable of being utilized in conducting generalized conversations. As a result, the chatbot can be generated and deployed in a quick and efficient manner for performance of the task(s) on behalf of the user.

The invention relates to the technical field of data processing, and discloses a data processing method and system based on liquid leakage detection. The method comprises the following steps: acquiring a sensor signal and processing to obtain leakage basic data; analyzing signal changes to determine leakage types and influence ranges; matching the risk threshold to determine a risk level; associating historical records to analyze leakage laws; calculating a failure probability to generate a maintenance strategy; and constructing a running state diagram to form a hierarchical management report. According to the invention, leakage management is converted from a traditional passive response mode to a data-driven active prevention mode, optimal configuration of maintenance resources is realized, and the leakage prevention and control efficiency is improved while the maintenance cost is reduced.

The invention discloses a task scheduling method based on predictable resource state atlas modeling, a platform is oriented to a heterogeneous computing environment, a unified resource state atlas is constructed by collecting multi-dimensional resource state parameters of computing nodes, and performance characteristics and communication topological relations among the nodes are comprehensively described. On the basis, a bidirectional time sequence model and an attention mechanism are fused, and the load trend of each node in a future short time is predicted. The platform constructs a multi-factor scheduling scoring function based on a task feature vector and resource state prediction map, integrates parameters such as resource matching degree, prediction load, communication delay and energy consumption cost, dynamically evaluates the adaptability of tasks and resources, and realizes adaptive scheduling and optimal resource allocation of the tasks. Compared with the prior art, the method has the advantages of being high in resource state predictability, high in task allocation intelligence degree, outstanding in platform evolution capability and the like, and is suitable for intelligent task scheduling application in a large-scale heterogeneous resource environment.

The invention provides a water heating pipeline pressure self-adaptive regulation and control method and system based on the Internet of Things, and belongs to the technical field of intelligent control of pipelines of the Internet of Things. According to the technical scheme, the method comprises the steps of building a pipeline acoustic sensing network, collecting pipeline external voiceprint signals to generate lightweight feature data, building a voiceprint-pressure mapping model based on the feature data, outputting a real-time pressure value, generating a pipe network state diagram based on the real-time pressure value, generating a pressure regulation and control instruction based on the pipe network state diagram, and achieving pressure self-adaptive regulation. Feedback data is collected according to the regulation and control result, and mapping model parameters are updated. The method has the advantages that the pipeline acoustic sensing network is constructed, edge calculation, depth feature extraction and the parallel neural network are combined, the pressure self-adaptive regulation and control capacity which does not need invasive sensing arrangement and has timeliness and robustness is achieved, meanwhile, a feedback closed loop is formed through a voiceprint-pressure mapping model, and the method is suitable for large-scale popularization and application. And the processing capacity of the system on complex dynamic working conditions is improved.

The invention relates to the field of vehicle-mounted equipment optimization, in particular to a vehicle-mounted equipment optimization method and system based on firmware updating. The method comprises the following steps: carrying out running state full monitoring on a vehicle-mounted firmware module, carrying out multi-behavior state sensing modeling, and constructing a firmware behavior state map; performing dynamic change trend analysis on the firmware behavior state graph, performing performance attenuation situation modeling, and constructing a performance attenuation situation curve; based on the performance attenuation situation curve, code-level program root cause analysis is carried out, firmware optimization target quantification is carried out, and firmware optimization demand data is generated; based on the firmware optimization demand data, multiple optimization direction decisions are made, multi-index optimization solution is carried out, and a firmware optimization task list is constructed; and performing firmware configuration update parameter simulation based on the firmware optimization task list to obtain a configuration update parameter scheme. According to the method, the optimal progressive equipment updating is realized, and the reliability and deployment safety of the vehicle-mounted equipment are improved.

The invention relates to the technical field of automatic driving, in particular to a driving control method and system for an unmanned electric tractor, and the method comprises the following steps: obtaining humidity data to generate a state diagram, judging slip to trigger traction adjustment based on the state diagram, analyzing a slope recognition risk to generate a slope parameter, and reading a braking force to judge, coordinate and generate a distribution instruction. According to the method, the humidity difference is obtained through multi-point soil humidity monitoring, distribution characteristics are extracted, accurate sensing of the state of an operation area is achieved, the wheel rotating speed and traction force signals are combined, slipping is recognized in advance, the traction force is dynamically adjusted, and the driving force is kept stable; based on joint analysis of gradient change and vehicle state, slope risk is recognized in advance, optimization control is performed, braking force of front and rear wheels is dynamically distributed, slippage caused by unbalance is avoided, safety of complex terrains is improved, and vehicle stability, path control precision and energy utilization efficiency are improved through cooperation of multi-dimensional data perception and dynamic prediction.

The invention discloses a vulnerability closed-loop disposal method and system based on intelligent collaboration, and belongs to the technical field of information security management. Vulnerability data and disposal information in a plurality of independent security systems are collected, and a multi-dimensional vulnerability semantic model is constructed; constructing a state perception graph based on a semantic model, extracting candidate state paths, and constructing a time sequence closed-loop prediction model in combination with a shortest closed-loop path and a historical track; according to a vulnerability influence range, a service dependency chain and a prediction path key node, adaptively dividing responsibility affiliation, generating a dynamic disposal responsibility graph and realizing automatic assignment; combining the node response capability and the task saturation, dynamically calculating the priority and scheduling the processing task; monitoring an actual disposal behavior, correcting an edge weight of the state diagram in real time and updating the model; according to the method, the whole-process intelligence, collaboration and dynamic evolution of vulnerability management are realized, and the processing efficiency and the prediction precision are improved.

The invention relates to a side cloud collaborative adaptive workflow scheduling method and system, and belongs to the technical field of distributed computing and artificial intelligence. The method comprises the following steps of: firstly, in a macroscopic candidate screening stage, reducing problem granularity through task clustering, and obtaining balance between utilization and exploration based on a weighted distance probabilistic preferential strategy; then, in a collaborative scheduling decision-making stage, a global network state diagram is constructed through a graph neural network, deep spatial features of nodes and neighborhoods of the nodes are extracted, context-aware state representation is formed, and a reinforcement learning agent makes an optimal collaborative decision in multiple options such as local execution, edge migration or cloud unloading according to the state representation; and finally, in a local adaptive optimization stage, performing fine-grained optimization after the task is issued, dynamically adjusting a scheduling frequency and a multi-target weight through an online learning mechanism, realizing balance between a task deadline and a resource utilization rate, and ensuring efficient and robust execution of a node level.

1. Name of the product of this design: Toothbrush (TR‑558). 2. Purpose of this design product: for brushing teeth. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: combination state diagram. 5. Other situations that require explanation Kit description: This design product is a complete set of products.

The invention relates to the technical field of hydraulic support intelligent supporting scheme design, in particular to a hydraulic support intelligent supporting method and system and electronic equipment. The method comprises the following steps: collecting roof pressure, bracket attitude and geological structure parameters in real time through a multi-modal sensor array; performing spatio-temporal feature fusion by utilizing the edge computing nodes to generate a three-dimensional support state map; constructing a dynamic weight adjustment strategy based on a reinforcement learning algorithm, and generating multi-objective optimization support parameters; a control instruction is issued through a dual-mode communication network to realize self-adaptive adjustment of the supporting strength; and a closed-loop feedback verification mechanism is established in combination with the laser radar scanning roof sinkage. And a digital twin model and an energy consumption optimization function are integrated. The problems that a traditional method is single in data dimension, rigid in decision and insufficient in reliability are solved, dynamic optimization of support parameters, active prevention and control of risks and collaborative improvement of energy efficiency are achieved, and the support safety and the intelligent level under complex working conditions are remarkably improved.

The invention relates to the field of resource management, and discloses a park resource scheduling method and device and a medium, and the method comprises the steps: constructing a park resource agent cluster based on park resource information; constructing a resource space-time state diagram based on a preset rule of the park resource agent cluster and the park resource information; based on a pre-constructed strategy cooperation rule and the resource space-time state diagram, determining an initial scheduling strategy of the resource scheduling event when the plurality of resource scheduling events are triggered; and optimizing the initial scheduling strategy through a multi-target optimization model to obtain a target scheduling strategy of the resource scheduling event. By constructing the agent cluster, when the resource scheduling event is triggered, the initial scheduling strategy can be quickly generated through the resource space-time state diagram of the park resource agents, the initial scheduling strategy is optimized when the resource scheduling conflict occurs, and the resource scheduling efficiency is improved while the current resource scheduling event is met. And optimizing resource scheduling strategies of the current resource scheduling event and other resource scheduling events.

The invention provides a network virus propagation prediction method based on a space-time diagram attention model, and mainly solves the problems of strong dependence on propagation parameters and low prediction precision in the prior art. The scheme comprises the following steps: 1) constructing a space-time infection state diagram based on a network topology structure and virus historical transmission data; 2) processing the historical virus transmission data by using a sliding window mechanism, and constructing a data set; 3) constructing a prediction model based on the space-time diagram attention network in combination with the diagram attention network and the long-short-term memory network; 4) training the prediction model by using the constructed data set, and evaluating the prediction performance of the model; and 5) predicting the propagation trend of the future network virus by adopting the trained model. According to the method, the spatial topological characteristics and the time evolution law of virus propagation are effectively combined, and meanwhile, a graph attention mechanism is introduced, so that the prediction accuracy and the calculation speed of virus propagation in a large-scale network environment can be remarkably improved.

The invention relates to the technical field of air tightness detection, in particular to a diaphragm type energy accumulator air tightness detection method which is used for solving the problems that in the prior art, equipment operation characteristics cannot be accurately described, typical defect modes cannot be recognized in combination with spectral clustering, and a quantitative basis cannot be provided for equipment fault trend analysis and intelligent maintenance. The method comprises the following steps: constructing a low-dimensional state map to describe equipment operation characteristics, identifying typical defect modes in combination with spectral clustering, establishing a nonlinear correlation model to reveal a defect evolution relationship, optimizing classification model parameters by adopting an evolutionary algorithm, improving the identification accuracy, mining a most probable defect evolution path based on a transition probability matrix, and improving the identification efficiency. And a quantitative basis is provided for equipment fault trend analysis and intelligent maintenance.

The invention discloses a self-adaptive AI control method based on multi-modal sensing fusion heterogeneous data, and particularly relates to the technical field of multi-modal sensing, and the method comprises the following steps: collecting multi-modal data, constructing a unified time sequence state atlas, and extracting modal activity indexes and variation indexes to represent each modal response and change trend; constructing a multi-path control intention candidate atlas based on the two types of indexes, and dynamically selecting an optimal path to execute a control instruction; the control instruction comprises an action parameter and a modal feedback calibration parameter, and the modal feedback calibration parameter is used for adjusting a subsequent modal acquisition priority; according to the method, time alignment and state fusion of heterogeneous data are realized by constructing a multi-modal state transition map, the recognition capability of the system on environmental changes is improved by using modal activity indexes and variation indexes, a control path and feedback parameters are generated based on dynamic indexes, a closed-loop control mechanism of sensing, decision making and execution linkage is established, and the reliability of the system is improved. And the adaptability and the stability of the system are obviously enhanced.

The invention provides a distributed computing task office resource allocation method and device, equipment and a medium. The method comprises the following steps: in response to a received distributed computing task of an office scene, obtaining a type identifier of the distributed computing task, and associating the type identifier with a preset task stage template; monitoring a current stage identifier of the task process based on the constructed global state graph, and generating an execution stage migration event containing a target stage identifier when detecting that the logic state identifier is changed; matching a resource demand baseline of the target stage identifier according to the task stage template, and generating a target stage resource demand prediction value in combination with the global state map; and traversing the residual resource quantity of all the nodes in the global state map, screening a candidate node set meeting the resource demand predicted value of the target stage, and generating an optimal scheduling strategy based on the data locality parameter and the hardware suitability parameter of each candidate node in the candidate node set. By adopting the method, the execution efficiency of the distributed computing task can be improved.

The embodiment of the invention provides a fuzzy test method and device for an underwater control system communication protocol, and the method comprises the steps: defining each protocol field and an invariant segment according to a protocol description file, and generating input data meeting the protocol requirements; modeling a protocol interaction process based on the state diagram, and performing multi-path traversal in the state diagram based on input data; monitoring abnormity of network communication and a target process in operation of the fuzzy test program, obtaining feedback information, and adjusting the test case based on the feedback information; and according to the anomaly detection information in the test process, generating a standardized test report and a test case script capable of collapsing and reproducing.

1. Name of the design product: Graphical user interface for operating data of electronic devices. 2. Use of the design product: For electronic devices. 3. Design key points of the design product: Lies in the interface content of the graphical user interface. 4. Picture or photo that best shows the design key points: Front view. 5. Use of the graphical user interface: For displaying operating data. 6. Description of the change states of the graphical user interface: Clicking "This Week" in the front view enters the interface change state diagram 1; Clicking on the time number in the interface change state diagram 1 enters the interface change state diagram 2.

The invention belongs to the field of electric power, and provides a method for performing operation and maintenance on power grid assets based on a large reasoning model, comprising the following steps: collecting multi-source operation data of the power grid assets; constructing a power grid topological structure, and forming a power grid operation state diagram; performing targeted training and optimization on the pre-trained reasoning model to ensure that the running state prediction output by the reasoning model meets the electrical feasible region; enabling the reasoning model to automatically avoid maintenance schemes which do not accord with the load curve, the reserve capacity and the scheduling approval in the reasoning process; optimizing the inference model through a chain type inference loss function, so that the inference model can predict the linkage effect of the equipment fault; and based on an output result of the reasoning model, generating a maintenance action sequence which accords with a feasible region of the power grid maintenance period and can minimize risk conduction. According to the method, the operation and maintenance efficiency of the power grid assets is improved.

1. The name of the product of this design: Graphical operating interface with floor thickness detection for electronic equipment. 2. Purpose of the product of this design: an electronic device. 3. The design highlights of this appearance design product are the graphical user interface on the screen. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6. Purpose of the graphical user interface: This electronic device is a floor thickness detector. The interface displayed in the main view of this appearance product is the interface of the detector APP. The main display interface includes four modules: thickness detection button, measurement and verification button, data management button, and system setting button, as shown in the main view of Design 1. Click the thickness detection button in the main view of Design 1 to enter the floor thickness measurement interface, as shown in the Design 1 change state diagram. Click the Metrology Verification button in the main view of Design 2 to enter the Metrology Verification interface, as shown in the Design 2 change state diagram.

1. Name of the product of this design: Dynamically activated graphical user interface with voice keyboard for electronic devices. 2. Purpose of this design product: an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: Design 3 interface change state diagram 5. 5. Designate Design 3 as the base design. 6. Purpose of the graphical user interface: The purpose of the interface is to select and start the dynamic change process of the voice keyboard according to user operations, collect the user's voice and convert it into text. 7. Human-computer interaction method of graphical user interface: In Design 1, the main view is the main interface displayed by the electronic device. When the user clicks the input box in the main view, the interface jumps to interface change state diagram 1, interface change state diagram 2, interface change state diagram 3 and interface change state diagram 4 in sequence. In Design 2, the main view is the main interface displayed by the electronic device. When the user long presses the circular microphone icon in the main view, the interface jumps to Interface Change State Diagram 1, Interface Change State Diagram 2, and Interface Change State Diagram 3 in sequence. In Design 3 and Design 4, the main view is the main interface displayed by the electronic device. When the user clicks the input box in the main view, the interface jumps to Interface Change State Diagram 1 and Interface Change State Diagram 2 in sequence; when the user long presses the circular microphone icon in Interface Change State Diagram 2, the interface jumps to Interface Change State Diagram 3, Interface Change State Diagram 4 and Interface Change State Diagram 5 in sequence.

The invention provides a test case generation method and device based on artificial intelligence, electronic equipment, a readable storage medium and a computer program product, and relates to the field of intelligent generation, in particular to the field of artificial intelligence and testing. According to the implementation scheme, test demand data related to functions of a to-be-tested product are obtained, the functions of the to-be-tested product comprise a plurality of function modules, and each function module comprises at least one function point; based on the test demand data, a large language model is utilized to obtain a first state diagram and a second state diagram, the first state diagram comprises a plurality of first state nodes, the first state nodes correspond to one corresponding function module in the function modules, and the second state diagram comprises a plurality of second state nodes; and based on the first state diagram and the second state diagram, obtaining a first test case set corresponding to the test demand data.

The invention discloses a computer resource scheduling optimization method based on artificial intelligence, and relates to the technical field of computer resource allocation, and the method comprises the steps: constructing a twinborn computer space, marking twinborn collection ends, and collecting resource use data; constructing an original coordinate system according to the resource use data and performing state generation to obtain a resource use state diagram; performing traversal check on the resource use state diagram to obtain a periodic fluctuation segment, and performing resource quantification through a twin computer space to obtain a fluctuation proportion accommodating frame; monitoring and deploying the CPU based on the twinborn computing space to obtain virtual deployment resources, applying the virtual deployment resources to the computer, and generating an optimal scheduling strategy according to the application process; resource allocation is optimized, the CPU utilization rate is improved, computer operation pressure is reduced, and idle or overuse of resources is avoided.

Implementations involve: receiving an unstructured free form natural language input; generating a chat robot based on the unstructured free form natural language input and in response to receiving the unstructured free form natural language input; and causing the chat robot to perform a task associated with the entity on behalf of the user. In various implementations, the unstructured free-form natural language input conveys details of the task to be performed, but does not define any corresponding dialog state graph (e.g., does not define any dialog state or any dialog state transition). Although, the unstructured free-form natural language input may be used to trim and / or launch machine learning models that have already been able to be used to conduct generalized conversations. As a result, the chat robot may be generated and deployed in a fast and efficient manner to perform tasks on behalf of the user.

1. Name of the Design Product: Graphic User Interface of Hotel Picture and Text Show for Electronic Devices. 2. Use of the Design Product: An electronic device. 3. Design Key Points of the Design Product: Lies in the graphic user interface. 4. Picture or Photo Best Showing the Design Key Points: Front view. 5. Use of the Graphic User Interface: Click the "Show All" button in the lower area of the front view to enter Interface Variation State Diagram 1; Slide up Interface Variation State Diagram 1 to enter Interface Variation State Diagram 2; Slide up Interface Variation State Diagram 2 to enter Interface Variation State Diagram 3. The grey color blocks in the front view and Interface Variation State Diagrams 1 to 3 are content screens.

1. The name of the design product: asset allocation graphical user interface for electronic device and its main body. 2. The use of the design product: an electronic device. 3. The design points of the design product: the part in the graphical user interface, the part outside the dotted line is the claimed part. 4. The picture or photo that best shows the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the overall interface is used to adjust asset allocation for financial planning; the use of the claimed part of the interface is the same as that of the overall interface. 7. The human-computer interaction mode of the graphical user interface: in design 1 front view, the user can search for content in the search bar, click the "save for 30 days" or "save for 90 days" option control to switch the deposit period, slide the joystick control on the slide rail left and right to adjust the deposit amount and view the corresponding estimated interest, and click the "transfer to "save and take out"" control to complete asset allocation. In design 2 front view, the user can search for content in the search bar, click the "save and take out" or "save for 30 days" option control to switch the deposit period, slide the joystick control on the slide rail left and right to adjust the deposit amount and view the corresponding estimated interest, and click the "transfer to "90 days"" control to complete asset allocation. The human-computer interaction mode of design 3 is the same as that of design 1. In design 4 front view, when the user clicks the "save for 90 days" option control to switch the deposit period, the cartoon figure's hand on the barbell and expression change (the shorter the deposit period, the lower the interest rate, and the more relaxed the cartoon figure's expression; the longer the period, the higher the interest rate, and the more difficult the cartoon figure's expression), presenting the interface change from design 4 front view to design 4 interface change state diagram. In design 5 front view, when the user long-presses the joystick control on the slide rail and slides it to the right, the deposit amount and the corresponding estimated interest are changed, presenting the interface change from design 5 front view to design 5 interface change state diagram. The human-computer interaction mode of design 6 is the same as that of design 1.

The embodiment of the invention provides an equipment energy-saving method and system, equipment and a storage medium, relates to the technical field of communication, and is used for improving the energy-saving effect of network equipment. The method comprises the following steps: acquiring a network state diagram sequence; the network state diagram sequence comprises network state diagrams of the network equipment at multiple moments, the network state diagrams at the multiple moments are used for representing a network topology structure of the network equipment at the multiple moments, and the multiple moments comprise the current moment; based on the network state diagram sequence, determining a first energy-saving risk value of the network device, the first energy-saving risk value being used for representing the risk degree of energy saving of the network device under the network topology structure at the current moment; and sending the first energy-saving risk value to the network equipment.

The invention relates to the technical field of generators, and provides an intelligent speed regulation universal generator system, which is characterized in that a global sensing module performs fusion processing on static characteristic parameters and dynamic characteristic parameters of a prime mover and parameter data of a universal generator, and realizes unified representation of the state of the whole system in combination with sensing state diagram construction; the working condition prediction module realizes short-term, medium-term and long-term layered trend prediction based on a multi-branch structure of a long-short-term memory network and a graph attention network, and ensures that a speed regulation strategy adapts to working condition evolution in advance; the target optimization module constructs operation constraint conditions based on static characteristic parameters of a prime mover, generates an elastic constraint boundary through Bayesian reasoning, and effectively improves the operation efficiency by combining dynamic adjustment of a working condition evolution trend; the execution scheduling module verifies instruction time sequence matching through dynamic time warping, and adjusts execution gain in combination with dynamic characteristic parameters of a prime motor and a load change rate, so that the self-adaptive operation capability of a generator system under complex working conditions is remarkably enhanced.

The embodiment of the invention discloses a digital management method and system for a main and distribution network project. The method comprises the following steps: performing project information structured modeling on a full life cycle of a target main and distribution network project to obtain a project stage node index model; chain type tracking analysis is carried out on the engineering stage nodes, an information interaction rule and a data transmission path are established, and a data flow topological graph is obtained; extracting front-end node state layer information and rear-end engineering monitoring layer information based on a front-end and rear-end separation strategy; and constructing a multi-dimensional influence factor association network by using the information to perform risk evolution path deduction and risk event simulation to obtain a simulation result and generate a cross-node cooperative response strategy. According to the embodiment of the invention, through the digital support of the node chain type tracking and the front and back end separation architecture, the data island of each stage of the main and distribution network project is eliminated, the cooperation efficiency of the project management is improved, and the controllability of the whole life cycle process is enhanced.

1. Name of the product of this design: Graphical user interface for employee absence reporting for electronic equipment. 2. Purpose of this design product: This design product is used for an electronic device. 3. The key design point of this design product lies in the interface content of the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5. The electronic equipment is of conventional design and other figures are omitted. 6.Purpose of the graphical user interface: used for employee outbound reporting application. 7. Human-computer interaction mode of the graphical user interface: click the "Out-of-office application" module in the main view to enter the interface change state diagram 1; fill in the content information of the out-of-office application in the interface change state diagram 1 to enter the interface change state diagram 2; click the "Submit" button in the interface change state diagram 2 to enter the interface change state diagram 3; click any "Out-of-office report submitted by me" in the interface change state diagram 3 to enter the interface change state diagram 4; if the application for out-of-office report is approved, enter the interface change state diagram 5 from the interface change state diagram 4; in the main view, interface change state diagram 2, interface change state diagram 3, interface change state diagram 4, and interface change state diagram 5, "XXX" is used to indicate that characters can be replaced, and the number of "XXX" does not limit the number of characters that can be replaced; the gray block in the main view is the content screen.