59 results about "Data flow diagram" patented technology

The invention discloses a data flow direction management method and system. The method comprises the steps of obtaining a first data flow diagram created by a target object and performing compliance verification; analyzing the first data flow diagram and the verification result through a dynamic topological optimization engine to obtain a first data flow arrangement scheme and executing the first data flow arrangement scheme; in the execution process, monitoring the index state of a preset key node in the first data flow arrangement scheme in real time, periodically checking the data asset change of the data source, and generating an asset version map; analyzing and positioning the exception of the key node and generating an exception handling strategy; and when the key data assets are changed, analyzing the asset atlas and the first data flow direction arrangement scheme by using a dynamic topological optimization engine, and obtaining and executing a reconstructed second data flow direction arrangement scheme. The technical problems that a dynamic asset recognition blind area exists in a traditional data flow direction management scheme, compliance verification is disjointed with the process, and the overall automation degree is low are solved.

The invention provides an MCM-GPU-oriented resource storage optimization method, device and equipment, and the method comprises the steps: carrying out the static analysis of an operator-level data flow diagram of a calculation task in a compiling stage, and extracting the data dependence relation and life cycle characteristics of each operator; generating a storage optimization scheme based on the data dependency relationship and life cycle characteristics of each operator; in the operation stage, task and data collaborative allocation is carried out according to a data prefetching strategy and a data replacement strategy, task and data collaborative allocation and the calculation task are executed in parallel, and a data flow diagram and an operator dependency relationship of the task are analyzed by utilizing a compiling period; in combination with the data locality characteristics of the MCM-GPU multi-level storage architecture and the concurrency requirements of different modules for data access, an appropriate GPU module is selected to carry out data optimization management, so that frequent data exchange between a GPU and a CPU is reduced, and the performance potential of the MCM-GPU architecture in a super-large-scale task is brought into full play.

The invention discloses a data stream display method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: determining a data interaction record of a target system; verifying the data interaction record to obtain a verification record and interaction risk information; a data blood relationship in the target system is determined, a data flow path vector diagram is established according to the data blood relationship, the verification record and the interaction risk information, the data flow path vector diagram comprises nodes and directed edges, the nodes correspond to all modules in the target system, and the directed edges are used for indicating the data flow direction and flow path in the system; the annotation information of the directed edge comprises interaction risk information and a verification record; according to the data flow path vector diagram, a visual data flow diagram is generated, and the data flow diagram comprises annotation information. The technical problem that data security is affected due to the fact that data interaction risks existing in a system cannot be found in time in related technologies is solved.

The invention discloses a coarse-grained reconfigurable architecture cyclic mapping method and device based on a graph neural network, and relates to the technical field of computer reconfigurable computing. The method comprises the following steps: based on a priority prediction model, performing list scheduling according to a data flow diagram and hardware information to obtain a list scheduling table; performing modular scheduling according to the data flow diagram and the hardware information; pre-scheduling the data flow diagram on the basis of a list scheduling table according to the modular data flow diagram and the time extension coarse-grained array to obtain a time step attribute data flow diagram; obtaining a mapping result by using a mapping algorithm based on pattern diagram matching according to the time step attribute data flow diagram on the basis of the time extension coarse-grained array; based on the hardware information, processing unit isomorphism verification is carried out according to the mapping result; and compiling the verified mapping result to obtain an executable configuration information file. The invention provides an efficient and accurate coarse-grained reconfigurable architecture cyclic mapping method based on a graph neural network.

The invention discloses a CGRA multi-task dynamic resource allocation method and a hardware circuit, and belongs to the technical field of dynamic resource allocation. The method specifically comprises the following steps: recording the attribute of each task by using a task attribute table; updating a task attribute table according to a central processing unit message, and generating a task queue and a Boolean value for triggering dynamic resource allocation; the number of processing units is calculated and allocated according to task priorities and the number of data flow diagram nodes; determining the shape of the distributed processing unit according to the number of the distributed processing units; pre-loading the configuration information into a configuration memory of the processing unit so as to match the shape of the allocated processing unit; and dynamic resource allocation is realized by using a finite-state machine. According to the hardware circuit, on the basis of an original CGRA circuit architecture, a dynamic resource distributor, a configuration transmission bus between processing units and configuration receiving circuits in the processing units are added. According to the method, dynamic resource changes caused by task creation and destruction can be flexibly handled.

The invention discloses an intelligent contract fraud detection method and system based on multi-view comparative learning, belongs to the technical field of block chains, in particular to the technical field of intelligent contract security detection, and solves the problem that an existing intelligent contract fraud detection method is highly dependent on labeled data. The method comprises the following steps: performing strong, medium and weak data enhancement on a given intelligent contract code to generate a plurality of enhanced views; performing feature vector extraction on the code of each enhanced view and the data flow diagram thereof, and obtaining feature representation of each view by using an encoder; constructing a comparison matrix based on the feature representations of the plurality of views, and training a feature extractor through a comparison loss function; training a semi-supervised classifier through the annotation data, the pseudo tag data and the output of the feature extractor, optimizing the classifier through a joint loss function, and finally obtaining a trained classifier; and performing fraud detection on new smart contract code extraction features by adopting the trained classifier. The method is used for intelligent contract fraud detection.

The invention discloses a scheduling-driven high-level comprehensive array division method, which comprises the following steps of: creating an associated access instruction set for arrays in algorithm design, and analyzing an address calculation expression of each access instruction; on the basis of the control data flow diagram designed by the algorithm, instruction scheduling is executed according to an instruction topological sequence and circuit performance requirements, for an array access instruction, a schedulable interval of the array access instruction is calculated, control steps in the interval are traversed, and incremental address conflicts introduced by each scheduling mode are determined; aiming at each scheduling mode of the array access instruction, a minimum overhead array division scheme capable of solving all address conflicts is searched, and the overhead of the division scheme comprehensively considers the number of storage modules after division, address control logic complexity and time delay; the address conflicts comprise the incremental address conflicts and the stock address conflicts. The method has the advantages that compared with an existing array division scheme, calculation scheduling and array division are organically combined, the cost of array division is reduced, and the scheduling performance is improved.

The embodiment of the invention provides a software vulnerability mining method and device based on static analysis and big and small model collaboration.The method comprises the following steps that attack faces are recognized and classified, and a code line annotation node set is generated; performing first-stage filtering on the code line annotation node set based on rules, and performing second-stage filtering on the annotation node set after primary filtering based on a twin neural network; taking a high-confidence node in the high-confidence attack surface set as a tracking starting point, generating a basic data flow diagram, obtaining a front-edge node set through static analysis, expanding the front-edge node set through a large language model and a path expansion algorithm, and generating a complemented data flow diagram; and detecting vulnerabilities based on the complemented data flow diagram to obtain a software vulnerability mining result. According to the scheme, through cooperation of the large language model and the twinning neural network, the false alarm rate is reduced, and the coverage rate and accuracy of vulnerability mining are improved.

The images represented in the image diagrams are interactive graphical user interfaces (GUIs) that visually convey information to a user related to systems for (i) creating and / or modifying and / or analyzing unit operations and data generated therefrom in manufacturing processes, such as cell and gene therapy manufacturing processes, (ii) combining live data from databases with textual information, and (iii) interactive analysis of data (e.g., patient data visualization systems) and analysis of data related to manufacturing processes. (A. Graph-Based Visualization and Interactive Data Views for Pharmaceutical Manufacturing Process Data Reconciliation) For example, in certain embodiments, the images represented in the image diagrams are associated with graph-based visualization tools that enable a user to analyze data related to one or more experiments and / or manufacturing processes used to produce pharmaceutical products and / or variations thereof. In particular, the images for graph-based visualization and data analysis GUI tools represented in the image diagrams can be used in association with GUIs that enable a user to automatically and / or semi-automatically (e.g., in conjunction with user review and / or input) generate visualizations that facilitate the examination of experiments and / or manufacturing processes and reconcile data generated across multiple processes and / or process runs. For example, among other things, the interactive graph-based visualization tools and their images may be provided (e.g., rendered) individually or together via one or more GUIs or windows, sub-windows, panels, etc. (Process Graph) For example, the image diagram illustrates a GUI that provides a visualization of a process graph. In one embodiment, the graph-based visualization tool represented in the image diagram includes generating and / or rendering a process graph that displays an experimental and / or manufacturing process for the production of pharmaceutical products, including biologics such as cell-based therapeutics and biologic drugs. The process graph includes multiple nodes, each representing a data point corresponding to a unit operation in a particular experimental and / or manufacturing process where information is collected and / or an action is performed.The image diagrams further illustrate various approaches for capturing and / or displaying these data points and how users interact with them. (Comparing and Reconciling Multiple Processes) In certain embodiments, the images depicted in the image diagrams are used as GUIs to provide graph-based visualization tools that provide comparison and / or reconciliation of data from multiple experiments and / or manufacturing processes, e.g., in an automated and / or semi-automated manner (e.g., coupled with user interactions such as review and selection actions). Among other things, the images depicted in the image diagrams include designs that overlay multiple graph processes, structurally compare them, and reconcile them based on data points. For example, the images depicted in the image diagrams may provide rendering data created by process comparison and reconciliation tools that (e.g., automatically) identify and address discrepancies, missing data, or anomalies, which can be used to generate a harmonized data set for further analysis, such as mathematical modeling. Thus, among other things, the graph-based visualization tools provided in the images depicted in the image diagrams address the challenges presented by unreconciled data across multiple experiments and / or manufacturing processes and / or within a single process that may be performed under varying conditions. Achieving automated reconciliation of such data is a significant challenge that, if not addressed, hinders effective and accurate analysis, which, in turn, can dramatically impact a user's and / or organization's ability to optimize and / or maintain manufacturing process quality and / or develop new processes. In particular, the images presented in the graph-based visualizations and the graphical representations that present them aid in adjusting sampling points to maximize overlay for effective comparisons and / or, in certain embodiments, identify overlapping points in existing data for effective real-time analysis. For example, the graphical representations show examples of multiple levels of data views and clickable / expandable pop-ups. In particular, in certain embodiments, the graphical representations are associated with GUIs that integrate the ability to collect and link actual data with process diagrams.For example, multiple levels of data can be viewed in an interactive and dynamic manner. For example, images presented in pictorial diagrams provide a high-level view, and while not all data may be directly visible, they provide clickable / expandable, customized, dynamic nodes for each node type, allowing users to simultaneously inspect and analyze collected and / or input data. In this manner, images presented in pictorial diagrams facilitate the identification and analysis of differences between processes. In some embodiments, structural differences between different processes indicate variations in conditions (e.g., temperature, duration, chemical concentrations), as well as the sequence and / or presence of certain steps. While unit operations (basic steps or stages in a process) may be generally similar to other processes, unique conditions and / or sequences can significantly affect the outcome, or the nature of the product or result. Thus, images presented in pictorial diagrams that provide visual display tools can be extremely useful in process optimization, troubleshooting, and ensuring that a process meets desired specifications. For example, changing the device that performs a unit operation and / or certain parameter values ​​within the unit operation (e.g., rotation speed, total volume, duration, etc.) can have a significant impact on the quality, recovery, efficacy, etc. of the output of that unit operation, which in turn can affect characteristics such as the biological / potency of the product, and additionally or alternatively, factors such as the cost of production, the number of doses produced per manufacturing run, and the like. Thus, among other things, images depicted in pictorial diagrams can be associated with and provided with GUIs that present generated data, such as automatically generated data (e.g., using ontologies), which helps to identify commonalities and / or differences between studies and facilitates performing analyses to determine, for example, whether device or parameter changes have significant impacts.In particular, as described herein, a graph-based visualization tool represented in a pictorial diagram provides a user with a visual representation of one or more manufacturing processes via a graph-based approach that easily communicates and highlights differences in conditions and unit operations, as well as their nature. For example, an image represented in a pictorial diagram may include visual features that highlight unreconciled data points. This approach facilitates the identification and correction of data reconciliation issues, thereby streamlining data analysis for research and process development conducted in the creation and production of pharmaceuticals, such as cell-based therapeutics and biologic drugs. (i. Process Graph with Interactive Nodes) The pictorial diagram illustrates an example of a graph-based visualization of a manufacturing process. As shown in the pictorial diagram, a manufacturing process can be represented and displayed via a process graph. Each node in the process graph displays a data point corresponding to a unit operation in the particular manufacturing process that it (e.g., the process graph) represents. The node may include information about the current data state and content (e.g., in real time) of the data point it represents. Within a graph-based visualization, nodes can be dynamic, such that, for example, a user interaction with a particular node (e.g., a mouse hover, click, touchscreen tap or long press, etc.) triggers the display of a tooltip indicating the current data state for the displayed data point, including data collected at various stages of the manufacturing process. Process graphs can be rendered and used for experiment design and process execution to outline complex manufacturing experiments over multiple days of manufacturing procedures and to visualize and track different stages of a real-time experiment.Experimental Overview: In some embodiments, a graph is displayed as an experimental overview, providing a high-level overview of an experiment, including the process steps and (e.g., approximate) order in which they were performed, the dates particular process steps were performed, how the process steps relate to one another (e.g., the top half of FIG. 1A ), and an overview of the various states / arms evaluated during the experiment and how those states relate to one another (e.g., the bottom half of FIG. 1A ). Timeline: In some embodiments, a process graph may include a timeline, displaying multiple timepoints, such as the days, during which a particular experiment or manufacturing process represented by the graph was performed. As shown in the image depicted in the pictorial diagram, the timeline may be displayed along the horizontal axis, with labeled circular icons used to visually represent individual timepoints (e.g., days of execution from day 1 through day 21). Other ways of visually displaying the timeline may be used, for example, along the vertical axis and / or using other shaped icons, other units (e.g., hours, weeks, etc.). Process Unit Operations: In some embodiments, a process graph may visually identify individual process unit operations performed during a manufacturing process. Individual process unit operations may be displayed, for example, through a combination of text labels and icons or markings that convey the particular unit operations performed and, optionally, the time at which they are carried out and / or their (e.g., temporal) relationship with respect to other unit operations. For example, the graph-based visualization shown in the image depicted in the pictorial diagram includes a series of text labels along the top row (of nodes) identifying various unit operations such as "Material Preparation," "Start-Up," "Transduction," and "Compounding." In one embodiment, as shown in the image depicted in the pictorial diagram, for example, the text labels also include a numerical component and identify the particular day on which each unit operation is performed, and the text labels are arranged sequentially from left to right along the horizontal axis to mark the order in which the operations are performed over time.The vertical dotted lines extending downward from each text label provide a visual guide for the expected schedule for each unit operation and / or a temporal mapping of the manufacturing process. (Data Points (Nodes)) As shown in the images depicted in the pictorial diagrams, data points in the manufacturing process associated with a particular unit operation and from which pertinent information (measurements and / or recorded observations) is collected are represented via nodes. Nodes may be rendered as icons such as filled circles as shown in the images depicted in the pictorial diagrams. In the images depicted in the pictorial diagrams, each circle is a node and is positioned so as to be visually aligned with a particular unit operation. That is, in the images depicted in the pictorial diagrams, it is located on a vertical dotted line extending downward from a text label identifying a particular unit operation, thereby identifying the data point related to that particular unit operation. (Connectivity) In some embodiments, the process graph may display the dependency or sequence of material and / or data flow from one unit operation to another via rendered connections between the various nodes. For example, as shown in the image depicted in the pictorial diagram, node connectivity may be rendered as lines connecting nodes across a timeline. (Data Connection Points) Specific points along the process where data is collected are marked, such as important checkpoints for quality control or measurements required for process evaluation. (Arms) In some embodiments, a process graph may include and / or display one or more (e.g., separate) arms, each representing a different experimental condition and / or baseline process variation. For example, in the image depicted in the pictorial diagram, the arms are rendered as various smaller graphs positioned below the timeline. Each line in the arms section indicates a different arm / condition as defined by the operator.Labels are provided to help clarify the focus of these steps and / or to distinguish and identify nodes as belonging to one condition, so that corresponding data collected from the laboratory are placed in the correct node and we do not mix data across conditions. In this case, the base process may be the step following a standard or control process, while other processes are steps that make experimental changes to that process or supplement the base process (e.g., making media, preparing materials, etc.). (Baseline Process and Base Process Graph) A baseline process may be a control and / or standard procedure and may be rendered as a base process graph. Text labels, color schemes, icon styles, positioning, and the like may be used to visually identify the baseline process, such as in graph-based visualizations. For example, in images presented in pictorial diagrams, the baseline process is identified and displayed as a node line directly below the timeline. In process graphs of images presented in pictorial diagrams, the baseline process may be the standard process against which other variations are compared. Variations and Outputs / Endpoints In some embodiments, a graph-based visualization can include one or more auxiliary subgraphs, each corresponding to and representing variations to experimental conditions and / or baseline versions of a manufacturing process. For example, the image depicted in the image diagram shows auxiliary subgraphs displaying variations labeled as "Ver1.1," "Ver1.2," "Ver2.1," "Ver2.3," etc., and "Condition 1," "Condition 2," "Condition 3," etc., representing different experimental arms or conditions. In this manner, the graph-based visualization tool can be used to communicate variations in materials used, process conditions, or specific unit operations performed. Additionally or alternatively, endpoints and / or outputs of different processes can also be displayed (e.g., via endpoint graphs).For example, as shown in the image depicted in the pictorial diagram, a series of nodes labeled "Out.1" and "Out.2" represent different endpoints and / or outputs of a process, such as different ways of processing or storing a final product. For example, in the exemplary subgraph shown in the image depicted in the pictorial diagram, lines refer to experimental conditions or interrelated subsets of a process, such as preparing materials (e.g., media) to feed a cell-containing process. Arm / condition sections help orient operators to the specific task being performed, and by identifying various arms in a descriptive manner, data collected in the lab are entered into corresponding nodes, and numbers / quantities, etc., are not mixed between conditions. Process graphs therefore facilitate the visualization and management of complex manufacturing processes. Among other things, they allow researchers to track the progress of experiments, compare different conditions or variations side by side, and ensure that data is systematically collected at designated points throughout the process. The ability to visualize the entire process in this way helps identify bottlenecks, ensure consistency, and facilitate data-driven decision-making.

The invention relates to the technical field of computer software and digital signal processing, and discloses an audio engine real-time processing method and system based on topological sorting, and the method comprises the following steps: packaging an audio processing logic into an independent Block unit; all the Blocks exchange data through the shared audio bus, and each Block reads and writes data on the audio bus according to the input bus identifier and the output bus identifier of the Block, so that decoupling of the functional unit is realized. The core of the invention lies in that the system dynamically generates a unique and correct execution sequence of all Blocks by carrying out topological sorting on the data flow diagram before processing. The calculation ensures that any Block is executed after its data source Block by reversely traversing the data flow diagram from the final output Block. According to the method, the time sequence correctness and the system stability of the data stream in any complex and dynamically variable audio processing link are effectively ensured, and meanwhile, the flexibility and the intuition of audio processing flow construction are greatly improved.

The invention relates to the technical field of resource allocation management, and particularly discloses a resource allocation method and system for an enterprise asset panoramic management platform, and the method comprises the steps: obtaining business process definition information and resource domain topological information representing the distribution characteristics and transmission characteristics of a resource pool; constructing a business process data flow diagram; generating a candidate resource allocation combination set conforming to the data sensitivity constraint; calculating the total end-to-end cost and total time consumption of the whole business process; based on a preset optimization target, selecting a resource allocation combination from the candidate resource allocation combination set according to the total cost and / or the total time consumption, and generating a resource allocation instruction according to the selected resource allocation combination; according to the method, the problem that end-to-end global optimization cannot be carried out due to the fact that tasks are processed in an isolated mode through an existing strategy and data dependence between the tasks and cross-resource pool transmission characteristics are neglected is solved, and the effects of reducing unnecessary overhead and time delay are achieved.

The invention discloses a low-cost anti-SEU (single event upset) high-reliability circuit design automation method. The method comprises the following steps that a circuit design program described by a high-level language is compiled into an intermediate data flow diagram through an algorithm-level comprehensive EDA tool; in nodes of the CDFG, detection and repair design combining space redundancy and time redundancy is adopted for logic nodes and data nodes; eCC (error correction code), DMR (dual modular redundancy) or TMR (triple modular redundancy) detection logic is dynamically allocated according to node types, and RTL-level circuit design codes with self-detection and self-repair functions are generated. The method has the beneficial effects that the algorithm-level reinforcement EDA technology in the technical scheme can reduce the area cost of the TMR reinforcement technology by 2.3 times, and meanwhile, higher anti-SEU reliability is achieved.

The system efficiently distributes data in a cloud pipeline to geographically distributed users. To enable efficient distribution of resources to multiple users, the production pipeline can be represented as two flow graphs: a flow graph of tasks as well as a flow graph of data. The flow graph of tasks can indicate a sequence of tasks, departments, and users in a production pipeline. The flow graph of data can indicate location of data needed for each task in the flow graph of tasks, and location of the users assigned to the particular task. Based on the next task that needs to be executed in the flow graph of tasks, the system can proactively gather the data from the various locations and deliver the data to the users assigned to executing the next task.

The invention discloses a mold project progress lag risk early warning method, which is applied to the technical field of risk early warning, and comprises the following steps: defining a key monitoring node of an automobile mold, and constructing a risk judgment rule base containing a threshold value, a key index and a task dependency relationship; the plan data and the multi-source actual feedback data are integrated, the plan data and the actual execution data are compared in real time through an intelligent linkage engine, a progress deviation value is calculated, and an early warning node is recognized according to a threshold value in a risk judgment rule base; based on the dependency relationship in the risk decision rule base, the identified early warning node is evaluated, the influence path of the early warning node is simulated, and a visual data flow diagram is generated; and triggering a grading early warning notification according to the risk grade in the evaluation result. According to the method, various risk factors are fused into the comprehensive risk index through the dynamic aggregation algorithm, so that the accuracy and reliability of risk early warning are effectively improved.

The invention discloses an intelligent application recommendation and aggregation method and device based on scene perception, and relates to the technical field of mobile computing and human-computer interaction. The method comprises the steps of inputting multi-dimensional data of a current user scene into a pre-trained intention recognition model, and outputting a current task type of a user and an associated application function demand; screening application components meeting all application function requirements; constructing a cross-application API bus, and generating a data flow diagram; generating a dynamic aggregation interface through an adaptive layout engine; in the interaction process, data field change is monitored in real time, and preloading and data updating of downstream application components are triggered through an API bus; if the user leaves the current task scene, unused application components are automatically unloaded. By adopting the technical scheme provided by the invention, the task completion steps can be reduced by more than half; the cross-application data synchronization delay is maintained at a hundred millisecond level; and a multi-mode input triggering aggregation service is supported.

The invention discloses a sea clutter task-level simulation optimization method, a medium and a program product, the sea clutter task-level simulation optimization method comprises the following steps: a pre-constructed data flow diagram of sea clutter calculation tasks is acquired, nodes of the data flow diagram represent the calculation tasks, and data dependence relations among the calculation tasks are directionally represented; hierarchical processing is conducted on the data flow diagram, all the calculation tasks are divided into different hierarchies, and no data dependence relation exists between the calculation tasks of the same hierarchies; and performing task calculation layer by layer based on a CUDA parallel calculation framework according to a hierarchical sequence. According to the method, the calculation tasks are divided into different levels, the calculation tasks of the same level have no data dependency relationship, and parallel execution of task levels is realized by combining a CUDA multi-stream processing technology, so that the sea clutter simulation efficiency is effectively improved, and theoretical and technical support is provided for rapid simulation of the sea clutter.

The invention belongs to the technical field of astronomical star-pointing explanation software, and discloses a master control method of an intelligent astronomical star-pointing explanation instrument, which comprises an intelligent voice interaction module, a celestial body positioning calibration module and a large model knowledge engine and interaction module. The invention also provides a modularized layered architecture which covers three core modules, namely a voice interaction module, a celestial body positioning module and a large-model knowledge engine module. Through a use case diagram and a data flow diagram, interaction logic between a user and a system and a flow mode of data between software and hardware are presented. Meanwhile, the software and hardware list and the deployment diagram further define resource and environment configuration required by system operation. The key technology design focuses on the problems of data interaction protocols, voice recognition optimization, user experience enhancement and the like, for example, the voice recognition error rate is reduced through fuzzy matching, the telescope operation precision is improved through rocker hierarchical control, and the learning requirements of different users are met through hierarchical knowledge display.

The embodiment of the invention provides a vehicle safety risk control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a business data flow diagram and asset category information of a target vehicle, the business data flow diagram being used for representing the data flow relationship among a plurality of information safety assets associated with the target vehicle, and the asset category information being used for representing the asset category information of the target vehicle; the asset category information is used for representing asset types and security attributes of the plurality of information security assets; determining a risk attack path based on the business data flow diagram, and determining target risk scene information based on the business data flow diagram and the asset category information; performing assessment processing on the target risk scene information and the risk attack path to obtain a risk assessment result; and determining a target risk control strategy of the target vehicle according to the risk assessment result. The technical problems that a vehicle safety risk control method provided in the related technology is low in standardization degree and high in implementation threshold are solved.

The present invention provides a method and apparatus for generating a data flow diagram. The method includes: analyzing the dependency information of data in the code in the scenario where there is a parent loop in the code block; traversing each process block in the code block to generate a block data flow diagram corresponding to each process block; analyzing and adding dependency information to the data flow diagrams corresponding to each process block to generate a code data flow diagram corresponding to the code block; eliminating duplicate variables in the code data flow diagram, simplifying the process blocks and establishing connection relationships between each process block to generate a first data flow diagram file, so as to display the data flow diagram of the loop code through the first data flow diagram file. The above method utilizes the llvm front end, the intermediate representation (IR) and some existing analysis steps thereof. llvm is an open-source compiler framework that facilitates users to add compilation steps (passes) or modify the compilation process according to the architecture of their own processors. The present invention is used for the front end of a reconfigurable compiler, but is not limited to a reconfigurable compiler.

1. The name of the design product: electronic device data flow display graphical user interface. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the interface content of the graphical user interface. 4. The picture or photo that best indicates 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 present design graphical user interface is used to display data flow. Design 1 front view is a data flow display page, the interface displays multiple function modules and the flow direction between each data module, the current page displays data overview, when the user clicks the left first function icon of data source management, design 1 interface change state diagram is presented, which is used to view index overview. Design 2 front view is a data flow display page, the interface displays multiple function modules, data flow direction and index overview, the current page displays data overview, when the user clicks the "index panel" button at the bottom of the interface, design 2 interface change state diagram is presented, which is used to display index details.

This invention discloses a DSP-based synthetic aperture radar (SAR) imaging component design method. The main idea is to build a processing system for this DSP-based SAR imaging component design method. First, a command parsing framework is built in the signal processing board (DSP). Then, a data flow diagram for the DSP-based SAR imaging component design method is constructed. Finally, the RD algorithm is implemented using the DSP, controlled by the main control board, to process the radar echo data, thereby realizing the software-based implementation of SAR imaging technology and decoupling the SAR imaging algorithm from the hardware. This design method can adapt to different hardware resources.

The invention discloses a fully homomorphic encryption operation method, a fully homomorphic encryption operation system and a non-transient computer readable recording medium thereof. The fully homomorphic encryption operation method comprises the following steps: receiving a homomorphic encryption application; converting the homomorphic encryption application into a data flow diagram; and scheduling the data flow diagram according to the connection relationship of the plurality of processing modules and the execution time to generate a scheduling result. Wherein the processing modules have at least two different processor types.

The invention provides a high-reliability multi-data flow diagram execution device, which is characterized in that a proxy distribution module is used for storing a pre-generated data flow diagram pool when a current program is executed, and a plurality of data flow diagrams in the data flow diagram pool are loaded to a reconfigurable array in parallel under the control of a feedback control module; when the data flow diagram is wrongly calculated, other data flow diagrams which belong to the same program with the data flow diagram which is wrongly calculated are scheduled; the reconfigurable computing array is used for executing a plurality of heterogeneous data flow diagrams corresponding to the same to-be-executed program in parallel; the strategy judgment module is used for judging whether calculation is correct or not, outputting a result when the calculation is correct, marking a data flow diagram of a calculation error when the calculation result is wrong, and feeding back the data flow diagram to the reconfigurable calculation array and the feedback control module; and the feedback control module is used for controlling the operation of the whole device and sending the received feedback information to the proxy distribution module so as to control the proxy distribution module to schedule and calculate other data flow diagrams, belonging to the same program, of the wrong data flow diagrams in the diagram pool.

The invention provides a code security function verification system based on data driving, which is feasible in an actual scene and faces the Internet of Things, a two-stage software code formalization verification analysis system is constructed, and in the first stage, a data flow diagram DFD is constructed by taking user authentication information and user behavior information as starting points and taking data full life cycle flow as a main axis. And in the second stage, for the globally unique DFD which depends on a single user at a certain moment, a method for determining code flow control corresponding to each DFG node, a method for constructing local sub-CFA based on single code flow control, and a method for splitting the overall system overall CFA into local, refined and small operable CFA, so that code security function verification based on data driving is realized. The method not only ensures the coverage of the code security function formalized verification analysis system for the operation of the Internet of Things intelligent equipment on codes, but also provides a formalized verification analysis system which can be practically applied.

The invention discloses a fusion safety-oriented potential hazard identification method for a high-level intelligent driving system, and belongs to the technical field of intelligent networked automobiles. Based on the requirements of three types of standards of ISO26262, ISO21448 and ISO / SAE21434, the method is integrated in a unified hazard identification process, and the method comprises the following steps: defining system related items and assets, analyzing and identifying vehicle hazards by HAZOP, establishing a system safety control structure, mapping a network safety data flow diagram, and identifying unsafe control behaviors and causes including component faults, insufficient safety of expected functions and STRIDE network threats. Potential hazards of system-level hazards caused by system faults, function limitation and network attacks are comprehensively recognized in the same framework, the problems of incomplete dimension coverage, repeated recognition, hazard omission and the like of an existing method are solved, hazard recognition integrity and development efficiency are improved, and the method is suitable for safe development of various high-level intelligent driving systems and has wide application prospects. And the method has wide engineering application value.

The invention relates to the field of data processing, in particular to a visual data pipeline generation method and system.The method comprises the forward process of converting an initial data flow diagram into a target language code and the reverse process of converting the target language code into the initial data flow diagram; the method comprises the following steps: after obtaining a target language code depending on a forward or reverse process, storing the target language code into a preset database, and finally, responding to trigger started by a user, converting the target language code stored in the database into a final data flow diagram and executing line production according to the final data flow diagram. Compared with the prior art, the method solves the problem that in the prior art, the consistency of data processing assembly lines is difficult to synchronize.

The invention relates to the technical field of building engineering information, and discloses an engineering project digital archive management method based on BIM. The method comprises the following steps: initializing a BIM platform environment, importing a BIM model and related archive data, and carrying out standardization processing; constructing a project component association graph and an archive data flow graph by using a graph technology; and capturing state change through event monitoring, and synthesizing a project operation state diagram and an archive data dynamic flow diagram in real time. The core innovation lies in that a row calls a semantic analyzer and an authority checker to scan and check a double-dynamic graph, and outputs an abnormal identifier set; positioning an abnormal node and performing dependency chain backtracking along an archive flow graph, and accurately extracting a problem root; a test case is generated by combining static analysis and a novel test strategy, and defect details are monitored and recorded during operation. And integrating the problem root and the defect record to generate a comprehensive management report. According to the invention, the real-time performance of engineering file management and the accuracy of problem tracing are improved.

The embodiment of the invention discloses an encrypted circuit generation method and device, equipment and a medium, and the method comprises the steps: obtaining a data flow diagram of a cryptographic algorithm, and enabling different types of nodes in the data flow diagram to represent electronic devices corresponding to different types of encryption operations in the cryptographic algorithm; according to the type of the node in the data flow diagram, a time sequence score and a power consumption score of the node are determined from a preset security score library, the time sequence score represents the time delay of the node in the encryption process, and the power consumption score represents the power consumption of the node in the encryption process; determining a plurality of security type diagrams according to the connection relationship of the sub-diagrams of the data flow diagram and the time sequence score and the power consumption score of each node; and generating a compatibility graph according to the plurality of security type graphs, determining a target fusion graph according to the compatibility graph, and generating an encrypted circuit according to the target fusion graph. According to the technical scheme provided by the invention, the comprehensive performance and safety of the encrypted circuit can be improved, and the quality of the encrypted circuit is improved.

The invention provides a Sencil calculation compiling optimization method based on a data stream architecture, a Sencil program is written in a mode of adding a guidance statement in a C language, and the statement is used for defining a data dependency relationship between a Sencil calculation type and a time axis; the compiler analyzes the guidance statement, analyzes the data dependency relationship between the time axes, and determines the starting interval of each time axis and the data needing to flow; time axis operation is distributed to adjacent parallel computing nodes according to the relation between the number of times of time axis iteration and the number of parallel data flow computing nodes, and continuous time axis iteration is distributed to the adjacent data flow computing nodes; a data flow instruction is generated for operation in each time axis, and asynchronous communication and parallel execution between nodes are controlled through a data flow diagram. The invention further provides corresponding electronic equipment. Therefore, the parallel execution between the time shafts is realized while the flexibility of Sencil programming is ensured, the memory access overhead and the synchronization overhead of a plurality of computing nodes are reduced, and the program performance is improved.