40 results about "Transition diagram" patented technology

The invention discloses a conversion method and system based on SysML and Modelica model semantic mapping. The method comprises the following steps that S1, a Modelica standard model library is imported into a SysML modeling tool; s2, completing the definition of behavior elements, and forming an SysML model instance; s3, exporting a Modelica model which can be executed by the Modelica simulator; s4, establishing a mapping relation table between SysML model elements and Modelica model elements; s5, when a change event occurs in the SysML model, updating the content of the corresponding Modelica model; s6, the Modelica model is imported into the SysML model, and a corresponding SysML model instance is generated; s7, simulation result mapping and behavior modeling generation are executed, a state transition diagram structure is formed, and structure updating of internal block diagrams in the system model is completed. According to the method, bidirectional conversion and joint simulation optimization between models are realized, and the method is suitable for cross-platform modeling, collaborative design and functional verification scenes of a complex system.

The invention discloses a collaborative optimization method and system for classified disposal and green disassembly of power grid waste and old materials, and relates to the technical field of classified disassembly of materials, and the method comprises the following steps: obtaining multi-source feature data of to-be-disposed power grid waste and old materials; constructing a residual value prediction model based on the multi-source feature data, and outputting a component residual value mapping graph; analyzing the structure information of the target material, and generating a disassembly path decoupling graph in combination with the residual value mapping graph; establishing a dual-objective optimization scheduling model, and solving the scheduling model to generate a green disassembly operation sequence meeting a first constraint condition; and when the disassembling operation sequence is executed, collecting real-time feedback data, dynamically correcting residual value prediction model parameters and scheduling model constraint weights. According to the method, the disassembly path decoupling graph and the disassembly state transition graph are constructed, collaborative representation of the component value and the disassembly topology in the equipment is realized, and the problems of decoupling of residual value evaluation and path planning and lack of green evaluation in a traditional method are effectively solved.

The invention relates to a source code vulnerability detection method and system based on multi-modal feature fusion. The method comprises the steps of obtaining semantic features, grammar features, loop invariant features and state transition diagram features based on a source code to be detected; obtaining logic features and structural features based on the grammatical features, the state transition diagram features, the semantic features and the loop invariant features, and generating a vulnerability probability matrix of the source code to be detected based on the structural features and the logic features; obtaining difference characteristics of the code segments before and after modification of the modified code segments, and generating a vulnerability detection result based on the difference characteristics; generating a source code vulnerability detection result based on the vulnerability detection result and the vulnerability probability matrix; the system provided by the invention is used for implementing the method. Compared with the prior art, more accurate source code vulnerability detection and identification are realized.

The invention relates to the technical field of intelligent operation and maintenance, and discloses an intelligent diagnosis method and system for power equipment maintenance, and the method comprises the steps: constructing a multi-dimensional maintenance model which comprises a basic state transition diagram, a required skill vector and a user skill state vector; based on the historical maintenance event log, generating a causal anomaly weight which is associated with the specific operation and represents the objective risk; when a maintenance task request of a certain user is received, combining the causal anomaly weight with the skill state vector of the user in real time, and calculating a personalized risk weight for the user; and on the basis of the personalized risk weight, solving an optimal maintenance path with the lowest comprehensive cost for the user, and presenting the optimal maintenance path. According to the method, the risk and subjective user ability are mined by fusing objective data, the individuation and precision of maintenance guidance are realized, and the self-adaptive evolution of the system is ensured by utilizing a double-closed-loop mechanism, so that the safety and efficiency of equipment maintenance are effectively improved.

The present invention relates to the field of equipment testing technology, and specifically to an intelligent thermostat durability testing system, comprising: a state modeling unit, the state modeling unit being used to define a state set and an extended variable set of a target thermostat, defining a state transition condition of the target thermostat based on the extended variable set and the state set, and constructing a state transition diagram based on the extended variable set, the state set, and the state transition condition. By defining the state set, the extended variable set, and the state transition condition of the target thermostat, the present invention can accurately simulate and describe the behavior and state changes of the thermostat under different operating conditions. By constructing a state transition diagram, the present invention can ensure that test cases cover all operating states of the thermostat and comprehensively test the system, thereby better evaluating the reliability of the device.

This design application relates to a GUI (Graphical User Interface) for transition icons. The transition icons in this GUI are displayed as a result of an aerosol generating device or electronic vape device, such as a heated tobacco product, performing functions such as startup, heating, or preheating. The appearance of the transition icons transitions sequentially between the images shown in Figure 6, which shows the changed state from the initial image.

The invention discloses a human body continuous action recognition method based on state diagram logic conversion. The method comprises the following steps: acquiring continuous actions of a human body by using a radar to obtain a radar three-dimensional data matrix, and generating a state logic conversion diagram; preprocessing the radar three-dimensional data matrix, and performing continuous action segmentation on the preprocessed time Doppler information; acquiring five-dimensional point cloud information of distance, Doppler, height, energy and time; according to a PointNet deep learning network and action state logic conversion, a forward classification method and a backward classification method are combined, and a main classifier is used for classifying independent actions; and the label range of the action is narrowed through the forward or backward sub-classifier, and continuous action classification is further carried out. According to the method, firstly, precise segmentation of continuous actions is realized based on the difference of the continuous actions of the human body in feature, and then, based on the continuity of the continuous actions in state conversion logic, the logic of state conversion between front / back adjacent actions is utilized to assist in judging a current action label, so that the accuracy of the continuous actions is improved. Therefore, efficient and accurate human body continuous action recognition is achieved, the calculation method is effective and feasible, the performance is reliable, and the precision is higher.

This application discloses a code generation method, apparatus, device, medium, and product, relating to the field of application development. The method includes converting front-end application design data into a structured dataset containing page element information, initial interaction topology, and visual design specifications, addressing the problem of insufficient interaction logic description capabilities. It then converts this data into an attributed state transition diagram, describing the complete interaction attributes of the front-end application's page-to-page interaction from pre-interaction preparation to the completion of the interaction's effect, replacing vague natural language descriptions and achieving machine-analyzable interaction logic, bridging the information gap between design and implementation. Finally, it combines a pre-trained language model to directly generate front-end development code, achieving automated and standardized output from design to code, addressing the lack of machine-analyzable formal representation of front-end interaction logic, thereby improving front-end development efficiency and code quality, and reducing communication and maintenance costs.

The invention provides an intelligent perception driven state transition diagram recognition and digital twinning construction and verification method and system. The method comprises the following steps: firstly, obtaining and optimizing a state transition diagram, and decomposing the state transition diagram into a state node layer, a transition path layer and a text labeling layer; then, on the basis of each decomposed layer, calling a deep learning model trained by combining a training data set related to the field, and identifying various state nodes in the state transition diagram; identifying a transfer path between the state nodes; the text information is recognized, and the semantics of the text information in the specific field is understood. A digital twinning model can be further constructed based on the identified result, and formalized verification and / or behavioral simulation are / is performed on the digital twinning model to assess the correctness and reliability of the digital twinning model. The method solves the problems that a traditional manual analysis method is low in efficiency and prone to errors, is particularly suitable for analysis and verification of complex state machines in the fields of semiconductors, memories, communication protocols and the like, and can remarkably improve design efficiency and reduce design defects.

An object of a system according to an embodiment is to support efficient software development by automatically detecting unnecessary processing and inefficiency of a source code.SOLUTION: A system according to an embodiment includes a static analysis unit, a documentation generation unit, a test case generation unit, a vulnerability detection unit, and a UI test execution unit. The static analysis unit analyzes the source code and detects useless processing and inefficiency. The documentation generation unit generates a relation diagram and a transition diagram from the source code analyzed by the static analysis unit. The test case generation unit generates a test case based on the relation diagram and the transition diagram generated by the documentation generation unit. The vulnerability detection unit detects vulnerability based on the test case generated by the test case generation unit. The UI test execution unit executes a UI test based on the vulnerability detected by the vulnerability detection unit.SELECTED DRAWING: Figure 1

The animated graphical user interface of this design is used to edit the navigation bar and shortcuts on the discovery page. The appearance of the transition images continuously transitions between the images shown in Figures 1.1-1.2, 1.2-1.3, 1.3-1.4, 1.4-1.5, 1.5-1.6, 1.6-1.7, 1.6-1.8, 1.6-1.9, 1.9-1.10, and 1.6-1.11, respectively. For Figures 1.5-1.6, clicking on the red circled icon in Figure 1.12 transitions the image in Figure 1.5 to the shortcuts page in Figure 1.6. For Figures 1.6-1.7, clicking on one of the heart-shaped icons in the red frame in Figure 1.13 transitions the image in Figure 1.6 to the image in Figure 1.7. With respect to Figures 1.6 to 1.8, clicking on the red circled icon in Figure 1.15 transitions the image in Figure 1.6 to the image in Figure 1.8. The process or period of transition from one image to another does not form part of the design sought to be registered. Dashed lines indicating a display screen or portion thereof do not form part of the design sought to be registered. Text containing English letters and an element consisting of an X or a sequence of Xs does not form part of the design sought to be registered. 1.1) Front view; 1.2) Front view; 1.3) Front view; 1.4) Front view; 1.5) Front view; 1.6) Front view; 1.7) Front view; 1.8) Front view; 1.9) Front view; 1.10) Front view; 1.11) Front view; 1.12) Reference view of 1.5 showing the transition between images from Figure 1.5 to Figure 1.6; 1.13) Reference view of 1.6 showing the transition between images from Figure 1.6 to Figure 1.7; 1.14) Reference view of 1.6 showing the transition between images from Figure 1.6 to Figure 1.8

The embodiment of the invention provides a task scheduling method and device for a graph processing request. The method comprises the steps of obtaining a plurality of task units corresponding to a target image processing request; the plurality of task units correspond to a plurality of calculation modes; obtaining a state machine migration graph which is uniformly constructed for multiple calculation modes; the state machine migration graph comprises a plurality of nodes, each node indicates an execution state of a subtask split from each calculation mode, and a migration edge between the nodes corresponds to the subtask; according to the state machine migration graph, the task units are scheduled and executed, and the scheduling execution of any target task unit comprises the steps that in a first state indicated by the first node, in response to a first triggering condition for starting to migrate to a second state, a target job in the target task unit is scheduled and executed, therefore, the current state is transferred to the second state; the target job belongs to a target subtask corresponding to a migration edge between the first node and a second node corresponding to the second state.

This design application relates to a GUI (Graphical User Interface) for transition icons. The transition icons in this GUI are displayed as a result of an aerosol generating device or electronic vape device, such as a heated tobacco product, performing functions such as startup, heating, or preheating. The appearance of the transition icons transitions sequentially between the images shown in Figure 6, which shows the changed state from the initial image.

The invention discloses an industrial component defect area positioning method based on microscopic image transfer learning. By constructing the modal state transition diagram and the spatial position matrix, the abnormal state and the interference area can be accurately identified, and the processing strategy is dynamically adjusted, so that the response speed and the processing flexibility of the system to the abnormal modal data are effectively improved. Particularly, under the condition that interference data is frequently transmitted or bandwidth resources are limited, data transmission and calculation burdens are greatly reduced through a modal compression and delay decoding mechanism, and continuity and stability of a main processing stream are guaranteed. Meanwhile, the method provided by the invention has relatively strong adaptive capability, cache management and path priority can be dynamically adjusted according to real-time state change, and data congestion and delay diffusion are effectively prevented.

The invention discloses a molten iron transportation path planning method and system based on an A * algorithm, and relates to the technical field of train automatic path planning, and the method comprises the steps: obtaining track information, building a road network topological structure, and defining a conflict rule; optimizing the transportation path through an A * algorithm, and selecting a path planning strategy according to a conflict rule; and constructing a state transition diagram, and visually displaying a path planning result. According to the method, by establishing a road network topological structure, efficient abstraction and simplification of a railway network are achieved, a system can rapidly understand and process the train running state, a transportation path is optimized through an A * algorithm, optimization of the train running path is achieved, a path planning strategy is selected according to a conflict rule, and the train running state is optimized. According to the method, high efficiency of train operation can be realized on the premise of ensuring safety, direct presentation of a path planning result is realized by constructing the state transition diagram and performing visual display, and the method has better effects in the aspects of efficiency, safety and reliability.

The application discloses a kind of multi-state flow error compensation methods based on deep learning, comprising the following steps: S1, acquisition and processing multidimensional working condition parameters, generate working condition state label, establish state transition diagram;S2, input physical dual layer, execute positive and negative mapping, adaptively correct parameter, output consistency feature;S3, combine feature with state label, establish causal error atlas model, decompose error and output distribution;S4, error distribution is corrected based on consistency feature, and candidate compensation is generated in combination with state label and transition diagram;S5, input candidate compensation amount, set compensation and risk agent, based on confidence game optimization output compensation;S6, according to the compensation weight correction flow value, output final compensation result, execute drift component online update.The application realizes high-precision, continuity and safe robust compensation of flow measurement error under multiple working conditions by introducing physical dual constraint, causal error atlas and game type compensation gate.

The invention discloses a barrier-free interaction method and related equipment based on large model enhancement, and the method comprises the steps: carrying out the traversing of an initial state node of an initial interface, and constructing a state transition diagram; labeling function information of the transfer nodes to generate a node function table; obtaining a current state node and a task purpose of the target task, querying the memorized task table, and when the current state node and the task purpose do not exist in the memorized task table, obtaining a simplified state node; according to the simplified state node, the node function table and the task purpose, generating a cue word; outputting an interaction element ID, an interaction event type and a task completion identifier of the target task through the large model; and updating the current state node, judging whether the task completion identifier is completed or not, and if the task completion identifier is not completed, returning to the step of acquiring the current state node until the identifier is completed. The method can improve the naturalness of barrier-free interaction and the accuracy of an interaction strategy, and can be widely applied to the technical field of artificial intelligence.

The application discloses a kind of customer data processing method and system, it is related to data processing technical field.The method includes the state transition diagram of the power consumption event sequence of each regional power grid customer is constructed;Two-way state structure is constructed to state transition diagram, based on maximum transition probability path extraction atypical state sequence, and mark as regional task key frame state sequence;Collaborative state mapping matrix is constructed, and distributed state abnormal fragment with associated aggregation characteristics is identified;The time sequence coding of task key frame state sequence corresponding to the state abnormal fragment with associated aggregation characteristics in collaborative state mapping matrix is carried out, and structured feature set is generated;The clustering boundary of state node in state transition diagram and transition edge weight are revised based on structured feature set.

A testing method and apparatus of a driving control system, a medium, and a device. According to the method, a state transition diagram is input, and then the test coverage of each state transition in the state transition diagram is gradually implemented on the basis of the state transition diagram and by loop iterative variation of a scenario sample. When the loop iterative variation is performed, a simulation output of the scenario sample is used as a reference, so that the iteration process can quickly converge to the corresponding state transition to achieve the goal of coverage testing. The testing method and apparatus can intuitively test the processing capability and level of the driving control system for a driving environment, and exhibits high test efficiency.

The invention discloses an intelligent lock anti-brute force cracking method and device based on multi-feature fusion, and relates to the technical field of fingerprint verification, and the method comprises the following steps: obtaining time sequence operation features generated in a user fingerprint verification process, and constructing a verification behavior sequence; performing behavior mode division on the verification behavior sequence to obtain a plurality of verification behavior states, and performing state transition analysis to obtain a verification state transition diagram; performing state return visit analysis on the verification behavior sequence based on the verification state transition diagram, and disturbing the verification state transition diagram according to an analysis result to obtain a state disturbance path; performing state diffusion evaluation on the state disturbance path and screening an optimal target path according to an evaluation result; the verification process of the intelligent lock is controlled according to the execution result of the optimal target path, and the security vulnerability problem that when an attacker conducts fingerprint verification through the intelligent lock, system feedback is unstable due to multiple attempts, and therefore forged fingerprints can be continuously adjusted, and unlocking conditions are approached is solved.

The invention discloses a JEDEC state transition diagram question and answer pair generation system and method based on agent joint optimization feedback learning. The system comprises a first agent which analyzes image information of a state transition diagram through a node information extraction model and extracts state node information in the image information; the second intelligent agent is used for recognizing connecting lines and character information in the JEDEC state transition diagram through a state transition logic recognition model, and extracting state transition logic information; and through a question-answer pair generation model, based on the state node information, the state transition logic and a preset question-answer pair generation instruction, constructing a third agent of state transition structured question-answer pairs, and based on a preset evaluation rule, analyzing each structured question-answer pair to obtain a state transition structured question-answer pair. And the fourth agent is used for feeding back a corresponding lifting instruction to the first agent, the second agent and the third agent according to an evaluation result, so that other agents modify parameters of the corresponding callable models, and the structured question and answer pairs are obtained again. According to the method, the multi-modal information in the JEDEC state transition diagram can be reliably extracted through joint optimization feedback learning of the intelligent agent, and the high-quality question and answer pairs about the state transition process are generated.

A risk evaluation device (20) includes: a graph processing unit (23) that creates a state transition diagram of a continuous-time Markov chain that is a data structure including each node and each edge of a BAG and in which an obtained transition rate is applied to each edge instead of an exploit success probability of each edge; and a graph analysis unit (24) that calculates a risk probability of each node that changes with an elapsed time t from when an attacker has started an attack by performing a Markov analysis process on the basis of the state transition diagram created by the graph processing unit (23) and the elapsed time t.

The animated graphical user interface of the design is primarily used to display stock ranking information. The appearance of the transition images transitions continuously between the images shown in Figures 1.1-1.2, 1.2-1.3, and 1.2-1.4, respectively. Regarding Figures 1.1-1.2, clicking the icon indicated by the red arrow in Figure 1.5 transitions the image of Figure 1.1 to the image of Figure 1.2. Regarding Figures 1.2-1.3, clicking the icon indicated by the red box in Figure 1.6 transitions the image of Figure 1.2 to the image of Figure 1.3. Regarding Figures 1.2-1.4, clicking any one of the stocks numbered in red within the red box in Figure 1.7 transitions the image of Figure 1.2 to the image of Figure 1.4. The process and duration of the transition from one image to another do not form part of the design sought to be registered. The dashed lines indicating the display screen or portions thereof do not form part of the design sought to be registered. Text containing Chinese characters, numbers and elements consisting of a single X or a string of multiple Xs does not form part of the design sought to be registered. 1.1) Front view; 1.2) Front view; 1.3) Front view; 1.4) Front view; 1.5) Reference view of 1.1 showing the transition between the images of Figure 1.1 to Figure 1.2; 1.6) Reference view of 1.2 showing the transition between the images of Figure 1.2 to Figure 1.3; 1.7) Reference view of 1.2 showing the transition between the images of Figure 1.2 to Figure 1.4

The system according to this embodiment aims to streamline the software development process and automatically detect and improve unnecessary processing and inefficient parts. [Solution] The system according to the embodiment comprises a static analysis unit, a test generation unit, a documentation generation unit, a vulnerability detection unit, and a UI testing unit. The static analysis unit performs static analysis of the source code. The test generation unit automatically generates test programs based on the unnecessary processing and inefficient parts detected by the static analysis unit. The documentation generation unit automatically generates relationship diagrams and transition diagrams based on the test programs generated by the test generation unit. The vulnerability detection unit detects vulnerabilities based on the documents generated by the documentation generation unit and proposes countermeasures. The UI testing unit automates user interface testing based on vulnerabilities detected by the vulnerability detection unit.

The application discloses a kind of conversion method and system based on SysML and Modelica model semantic mapping, comprising the following steps: S1, in SysML modeling tool, import Modelica standard model library;S2, the definition of behavior element is completed, and SysML model instance is formed;S3, export the Modelica model that can be executed by Modelica simulator;S4, the mapping relationship table between SysML model element and Modelica model element is established;S5, when SysML model changes event, update corresponding Modelica model content;S6, import from Modelica model to SysML model, generate corresponding SysML model instance;S7, execute simulation result mapping and behavior modeling generation, form state transition diagram structure, and complete the structure update of internal block diagram in system model.The application realizes the bidirectional conversion between models and joint simulation optimization, and is suitable for complex system cross-platform modeling, collaborative design and functional verification scene.

The present invention relates to the field of information security. More specifically, it relates to a construction method and circuit design of a high-dimensional digital domain chaotic system. The key points of its technical solution are as follows: draw a strongly connected state transition diagram with 2m state points; use the first formula and the strongly connected state transition diagram to inversely deduce the logical function formula corresponding to the m-dimensional digital domain chaotic system with precision N = 1, and use the logical function formula to complete the solution of the logical expression. The advantage of the present invention is that it proposes a general construction method of a high-dimensional digital domain chaotic system, which solves the defect that the prior art cannot efficiently construct a high-dimensional digital domain chaotic system under the condition of limited computing resources.

The present invention discloses a scenario testing method, apparatus, medium, and equipment for a driving control system. The method inputs a state transition diagram and then, based on the state transition diagram, gradually achieves test coverage for each state transition in the state transition diagram through cyclic iterative mutation of scenario samples. The simulation output of the scenario samples is used as a reference during the cyclic iterative mutation, allowing the iterative process to quickly converge to the corresponding state transition and complete the coverage test. The present invention can intuitively test the driving control system's ability and level of handling the driving environment, with high testing efficiency.

The invention discloses a train working diagram recovery method, device and equipment under operation disorder and a storage medium, and relates to the technical field of rail transit, and the method comprises the steps: taking a target plan line in an original plan working diagram as a reference plan line, and creating a reference working diagram; the target plan line comprises a plan line which passes through the current time and of which the end time is after the current time, and a plan line of which the start time is after the current time; matching a reference plan line for the online train; if the unmatched online trains exist, creating a warehousing reference plan line for the unmatched online trains; taking the reference plan line or the warehousing reference plan line corresponding to the online train and the unmatched reference plan line as a transition plan line, and creating a transition running chart; and sequencing and translating the transition plan lines, and adjusting the arrival and departure time of the transition plan lines. According to the method, the transition running chart can be automatically created when the train runs disorderly, and the train can run according to the transition running chart and can quickly recover to the original plan to run.

The invention discloses an overlay precision error detection method, a storage medium and a terminal. The method comprises the following steps: acquiring an initial design layout; obtaining an initial measurement layout through the initial design layout; first image processing is conducted on the initial design layout, a first transition layout is obtained, and the first transition layout comprises a plurality of first transition graphs corresponding to the design graphs; a first measurement area is arranged in the first transition layout, a first transition graph in the first measurement area is obtained to serve as a first measurement graph, and the first measurement graph has position information in the first transition layout; second image processing is conducted on the initial measurement layout, a second transition layout is obtained, and the second transition layout comprises a plurality of second transition graphs corresponding to the actual graphs; according to the position information of the measurement graph, extracting an effective graph corresponding to the first measurement graph from the plurality of second transition graphs; acquiring a second measurement area in the initial measurement layout according to the position of the effective graph; according to the overlay precision error detection method, the first measurement pattern on the initial design layout is obtained, the first measurement pattern is combined with the second transition pattern, and then the effective pattern corresponding to the first measurement pattern in the second transition layout and the position of the effective pattern are obtained. The position of the effective pattern corresponds to the position of the measurement frame, so that the second measurement area is obtained, namely, the position of the measurement frame in the initial measurement layout is determined, and the accuracy and efficiency of subsequent overlay precision error detection are improved.