182 results about "Instruction list" patented technology

The invention provides a heterogeneous multi-core-based embedded numerical control system, which comprises a development system, an operation system and a bus servo driving unit, and is characterized in that the data output end of the development system is connected with the data input end of the operation system, and the data transmission end of the operation system is connected with the data transmission end of the bus servo driving unit; the development system is used for programming and monitoring tasks, and the operation system is used for executing control logic, controlling external equipment, receiving compiled control programs from the development system and controlling on-site input and output equipment according to instructions in the programs, so that industrial automatic control is realized. The embedded soft PLC is divided into the development subsystem and the operation subsystem to be deployed on different cores of the multi-core embedded processor, the embedded soft PLC independent of PC operation is achieved, a method for directly explaining and executing the ladder diagram is provided, the ladder diagram does not need to be converted into an instruction list program, and the operation efficiency is improved. The algorithm complexity of ladder diagram compiling and interpretive execution is reduced, and the execution efficiency of the numerical control PLC is improved.

The embodiment of the invention provides a prototype verification method and device.The method comprises the steps that a debugging instruction list is generated according to configuration information and at least one test case, the debugging instruction list is executed through a first simulation module based on a spike simulator to conduct prototype verification, a first debugging log is obtained, and a second debugging log is obtained; and executing the debugging instruction list through a second simulation module based on the FPGA to perform prototype verification to obtain a second debugging log, burning a to-be-tested register transfer level RTL file in the second simulation module, and comparing the first debugging log with the second debugging log to obtain a joint simulation report. Through the embodiment of the invention, the problem of low efficiency of a prototype verification method in related technologies can be solved, the program bug existing in RTL design can be quickly detected, the maintenance cost is reduced, and the debug efficiency is improved.

The invention relates to a programming review method and system based on multi-modal data. The method comprises the following steps that source code fragments are collected, character format matching is carried out, consistent items are output, and initial node mapping is generated; extracting a pointer reference and calling sequence, carrying out node association recombination, screening node levels, carrying out semantic mark matching, summarizing a connection path, checking a code security scanning index, and generating a dynamic semantic structure; carrying out stack-up matching to compare pixel distribution and label similarity, scanning edge coordinates, checking label corresponding positions and visible area distribution, judging feature co-occurrence, and generating multi-modal associated features; and performing program logic checking, analyzing a variable initialization sequence, generating a checking element set, comparing code security scanning indexes, generating security scanning information, judging a risk identification level and generating a review instruction list. Compared with the prior art, the information utilization rate and the correlation analysis depth in the code review process can be improved, and the accuracy of program defect and risk discovery is enhanced.

The invention relates to the field of programmable logic controller programming software, in particular to a method for converting a ladder diagram of a PLC into an instruction list, which comprises the following steps of: obtaining a mapped AOV diagram by adopting a mode of adding and deleting virtual nodes; generating a logic tree by adopting a series-parallel scanning method of dynamic priority; and after the logic tree structure is obtained, performing subsequent traversal on the logic tree according to the logic relationship described by the logic tree to generate an instruction table structure. Compared with the prior art, a complex ladder diagram is greatly simplified through a preprocessing mechanism, the scanning steps of continuous series connection or continuous parallel connection original parts can be reduced, unnecessary node scanning can be fully reduced through dynamic priority series-parallel connection scanning, and the scanning efficiency is greatly improved; in addition, the method can be widely applied to a complex ladder diagram program in the PLC, and the series-parallel scanning efficiency can be greatly improved.

The invention provides a voice interaction method and system, electronic equipment and a storage medium, and relates to the technical field of man-machine interaction, and the method comprises the steps: receiving a voice instruction of a user, and carrying out the text processing of the voice instruction, and obtaining a first instruction text; inputting the first instruction text into an identification large model to obtain an instruction vector; matching the instruction vector with a pre-constructed instruction matrix to obtain a target instruction index; based on the target instruction index, calling a target instruction text from a pre-constructed instruction list; and performing text processing on the target instruction text and the first instruction text to obtain a query text, and inputting the query text into the identification large model to generate a target instruction for controlling the vehicle. According to the method, the generation speed of the target instruction is increased, and the adaptability to diversified and complicated scenes is improved.

The invention discloses an intelligent precise part machining quotation method and system based on a large language model, and belongs to the technical field of intelligent manufacturing and artificial intelligence. Semantic analysis is performed on unstructured manufacturing demand information through the large language model, and key manufacturing process parameters are extracted; if the demand is not complete, a structured process instruction list is output through multiple rounds of clarification inquiry; after the three-dimensional part model is analyzed, machining features are recognized, and when to-be-confirmed features exist, a machining feature list is generated through a man-machine collaborative confirmation mechanism; calculating technical cost according to the structured process instruction list and the processing feature list; non-technical factor information is obtained through a large language model, verification and adjustment are carried out until compliance is achieved, and non-technical cost is calculated; integrating the two types of costs to obtain a total quotation, visually displaying the total quotation and the cost composition, and outputting a quotation sheet after confirmation; the problems that an existing quotation system is difficult in natural language demand analysis, unreliable in feature recognition and lack of an interaction confirmation mechanism are solved.

The invention discloses a floating point instruction conversion calculation precision optimization method based on an extended control word, and the method comprises the steps: calculating a control word through an extended ARM floating point number, and building a rounding mode mapping table, an exception type mapping table and a virtual exception instruction table in advance; the conversion of an x86 floating-point number control word loading instruction is realized based on a rounding mode mapping table and an exception type mapping table, and for an x86 floating-point number calculation instruction, an ARM instruction sequence which the x86 floating-point number calculation instruction should be converted into is preliminarily determined according to whether the x86 floating-point number calculation instruction is a high-precision calculation related instruction or not; the method comprises the following steps of: acquiring an x86 floating-point number calculation instruction, and determining whether to add an instruction group for simulating exception triggering for the x86 floating-point number calculation instruction according to whether the x86 floating-point number calculation instruction exists in a virtual exception instruction list so as to finish conversion of the x86 floating-point number calculation instruction, so that conversion execution from the x86 floating-point number calculation related instruction to an ARM system is realized, the precision loss of program cross-architecture execution is reduced, and the program cross-architecture execution reliability is improved.

An assistance device according to one aspect of the present disclosure is for assisting a business in which a first person interacts with a second person. The assistance device comprises: a creation unit that creates an instruction document including at least a text representing an utterance of at least one of the first person and the second person, and a command for generating the text and information for assisting the business from the text, on the basis of a pre-created template; and a generation unit that generates the information by a trained machine learning model, on the basis of instruction document.

The invention discloses an address coding method, device and system, and relates to the technical field of coded address communication, and the method comprises the steps: obtaining the number of to-be-coded slave devices; sending a start coding instruction to the slave equipment, wherein the start coding instruction indicates that the slave equipment enters an address coding mode; receiving a request coding instruction and a first storage coding address sent by the slave equipment; counting a first number of the received request coding instructions; and under the condition that the first number is equal to the number of the to-be-coded slave devices and the received first storage coded address of at least one slave device is inconsistent with the preset coded address of the corresponding slave device, sending the preset coded address to the slave device, so that the slave device performs address coding, and obtaining a coding result. According to the embodiment of the invention, the master device and the slave device can be automatically coded, address coding is quickly completed, and the coding efficiency is improved.

The invention relates to an instruction identification method and device, equipment, a readable storage medium and a program product. The method comprises the following steps: firstly, generating a to-be-tested instruction list according to an instruction format of a target processor, then, carrying out disassembling processing on the to-be-tested instruction list, determining an undefined instruction list of the target processor according to a disassembling processing result, and finally, obtaining an execution result of the target processor on the undefined instruction list, and determining a hidden instruction according to the execution result. By the adoption of the method, the instruction format of the target processor can be recognized, the to-be-tested instruction list can be generated, then the to-be-tested instruction list is disassembled, the undefined instruction list is screened out, and the execution result of the target processor on the undefined instruction list is obtained to obtain the hidden instruction, so that the whole instruction space does not need to be traversed when the to-be-tested instruction list is generated; and the hidden instruction identification efficiency is improved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a mobile phone RPA automatic system based on natural language analysis. The system comprises a voice input interface module which is used for providing an interactive interface for a user and converting voice input by the user into a text; the natural language processing module is used for performing preprocessing, intention classification, entity extraction and task disassembly on the text converted by the voice input interface module and generating structured task description; the RPA module is used for generating a corresponding RPA instruction list by utilizing a mapping rule according to the structured task description, calling an RPA execution engine to sequentially analyze RPA instructions, and simulating user operation on a mobile phone through a UI automatic tool to complete a task; and the feedback display interface module is used for providing feedback information according to the task completion condition and allowing the user to select to continue the operation or re-initiate the task.

The invention discloses a pedal optimization method for a vehicle-mounted meta universe game, which comprises the following steps of: generating a game operation instruction list of pedals according to an operation instruction of a game host, generating a driving operation instruction list according to an operation mode of the pedals in a vehicle, and comparing and matching the game operation instruction list and the driving operation instruction list; for each operation instruction of the pedal, obtaining a difference value between the actual operation of the player and the game feedback; and determining a correction strategy according to the difference value of each operation instruction, and correcting the sensitivity of the pedal according to the correction strategy. The invention further discloses a corresponding system and a storage medium. By implementing the method and the device, the sensitivity of the pedal can be flexibly and accurately adjusted, and the interaction efficiency and experience of the vehicle-mounted meta universe game can be improved.

A method, system, medium and product for automatic control of vehicle-mounted lamps, relating to the field of machine learning. The method comprises: obtaining a user control instruction table of the current main driving user; when the control instruction of the current main driving user is monitored, determining the instruction content corresponding to the control instruction; in the case that the target vehicle-mounted lamp corresponding to the instruction content fails, determining the target fault level of the target vehicle-mounted lamp; according to the target fault level, determining the brightness range of the target vehicle-mounted lamp; obtaining one or more simulation control schemes and their corresponding lighting effect similarities through a vehicle simulation model; in the case that the lighting effect similarity of the simulation control scheme is higher than a preset similarity threshold, selecting the simulation control scheme with the highest lighting effect similarity as a replacement control scheme; and sending a replacement control instruction to the vehicle-mounted lamp. The implementation of the technical solution provided by the present application reduces the impact of vehicle-mounted lamp failures on lighting effects.

The invention discloses a line adjustment system, method and device and a computer readable storage medium, and relates to the technical field of circuits, and the system comprises a line controller and a bus multiplexer; the first input end of the bus multiplexer is connected with the BMC through a public bus, the second input end of the bus multiplexer is connected with the BMC through a private bus, the output end of the bus multiplexer is connected with the slot, and the enabling end of the bus multiplexer is connected with the line controller; the line controller is used for acquiring a line control instruction of the BMC to the slot and analyzing the line control instruction; controlling the first input end to be switched on and controlling the second input end to be switched off in response to the fact that the line control instruction represents access through the common bus; and controlling the first input end to be closed and controlling the second input end to be conducted in response to the condition that the line control instruction represents access through the private bus. According to the method and the device, the BMC can flexibly and adaptively switch the bus of the equipment on the access slot, and the access stability of the BMC to the external equipment is improved.

The invention provides a city enrollment number prediction method and device, a medium and a program product, and the method comprises the steps: inputting a historical enrollment number into a pre-trained large language model, and obtaining a predicted enrollment number; wherein the training of the large language model comprises the following steps of: cutting a historical enrollment number sequence for training into blocks, modeling by using a time sequence encoder to obtain vector representation, and converting the vector representation into a large language model space by using a time sequence adapter; replacing a time sequence specific token in a pre-constructed pluggable sequence sensing instruction with the vector representation converted into the large language model space in a pluggable manner to obtain a replacement instruction representation; and performing model fine tuning by using the replacement instruction representation and a pre-constructed cross entropy loss function to obtain a trained large language model. According to the technical scheme, the advantages of the large model and the time sequence model are combined, and the precision of urban enrollment number prediction can be improved.

The application relates to the technical field of data management, and is an industrial production energy consumption optimization management data processing system. The system comprises an energy consumption graph construction module, an energy efficiency matrix generation module, an energy consumption evaluation module, an abnormality identification and strategy retrieval module and an instruction generation and adaptation module. Real-time energy consumption data and operation parameters of a production line are subjected to multi-scale feature analysis to construct a multi-dimensional energy consumption graph and a multi-modal energy efficiency state matrix. The expected energy consumption state of the production line under the current working condition is subjected to weighted quantitative evaluation to obtain a theoretical optimal energy consumption value. The multi-dimensional energy consumption graph and the multi-modal energy efficiency state matrix are subjected to collaborative identification, and the identification result is mapped to a historical optimization case database of the production line to retrieve a candidate regulation and control strategy. Equipment regulation and control parameters and execution time sequences in the adaptive strategy are encoded and packaged to obtain an optimization regulation and control instruction list. The application can improve the efficiency of industrial production energy consumption optimization management.

An online concierge system generates suggested instructions for presentation to a user. The online concierge system access instruction examples corresponding to a target item category and generates candidate instruction representations based on instruction messages within each instruction example. The online concierge system generates preliminary scores for the candidate instruction representations that are directly related to an intra-category frequency of use of the instruction tokens of the candidate instruction representation within the target item category. The online system normalizes these preliminary scores for the candidate instruction representations based on the inter-category frequency of use of the instruction tokens in all item categories to generate final scores for the candidate instruction representations. The online concierge system selects a set of instruction representations based on these final scores and generates suggested instructions based on the set of instruction representations.

The present disclosure provides a quantum circuit processing method, device and electronic device, which relates to the field of quantum computing technology, and specifically to the field of quantum circuit technology. The specific implementation scheme is: obtain a first instruction list of a first quantum circuit including 2N quantum bits, the first quantum circuit is a quantum circuit of a combined structure or a subcircuit of a quantum circuit of a combined structure; based on the first instruction list, perform equivalent compilation on the first quantum circuit to obtain a second instruction list for the second quantum circuit; the equivalent compilation includes: adding a first reset operation instruction after the first measurement operation instruction in the first instruction list; remapping each first target operation instruction in the first instruction list to the quantum bit of quantum bit i; adding a second reset operation instruction after the second measurement operation instruction in the first instruction list; remapping each second target operation instruction in the first instruction list to the quantum bit of quantum bit N+h.

The application provides a device data processing method and device, electronic equipment and readable storage medium, and applies to the technical field of device data processing. The method comprises the following steps: when the communication state between a management device and an instruction sending device is switched from disconnection to reconnection, the management device identifier is sent to the instruction sending device, so that the instruction sending device acquires the data deletion instruction corresponding to the management device identifier from the data deletion instruction list according to the management device identifier, and sends the data deletion instruction to the management device; the device type of the to-be-deleted device carried by the data deletion instruction is acquired; the data deletion strategy corresponding to the device type is acquired, and the local data of the to-be-deleted device is deleted according to the data deletion strategy. The method of the embodiment can delete the local data of the to-be-deleted device at the same time when deleting the device, so that the leakage of device data is prevented.

The invention relates to the technical field of multi-modal interaction, in particular to a multi-modal interaction control method and system for a sweeping robot, and the method comprises the following steps: collecting voice and gesture input, extracting voice trigger information and action features, generating a modal frequency mark and an instruction list, matching a task path, and generating a modal identification table. The method comprises the following steps: extracting and comparing action sequences to recognize a master control mode, analyzing continuity to generate a response mark, and screening consistent input to generate an interaction instruction result. In the method, through extracting time, quantity and confidence characteristics of voice and gesture input, establishing frequency and trigger marks of multi-mode input, realizing accurate recognition of an input state; a task path and semantic content are combined to carry out space and semantic matching, the task relevance judgment capability is improved, based on action code comparison, dominant modes are identified, conflict instructions are eliminated, the master control status of each mode in continuous tasks is dynamically balanced, the control response accuracy is improved, and an interaction mechanism with intelligent judgment capability is constructed.

The present invention provides a method for vulnerability detection, comprising the following steps: obtaining a target readable instruction list and a target task list, obtaining a designated readable instruction list corresponding to the target readable instruction list, and performing vulnerability detection on the target readable instruction according to the designated readable instruction list, wherein target risk information and a target risk position are determined, and a designated detection position is obtained according to the target risk position, and when a target function does not exist at the designated detection position, it is determined that a vulnerability exists in the target readable instruction, and when a target function exists at the designated detection position, a target risk coefficient corresponding to the target readable instruction is obtained, and vulnerability detection of the target readable instruction is performed based on the target risk coefficient. The present invention screens tasks based on feature data of codes corresponding to the tasks, thereby narrowing the scope of vulnerability analysis and improving the efficiency of vulnerability detection, and detecting vulnerabilities based on risk coefficients corresponding to information associated with risk data, so that the accuracy of vulnerability detection is high.

The invention discloses a method for optimizing calculation precision of floating-point instruction conversion based on extended control words. By extending an ARM floating-point calculation control word, pre-establishing a rounding mode mapping table, an exception type mapping table and a virtual exception instruction table, the conversion of an x86 floating-point control word loading instruction is realized based on the rounding mode mapping table and the exception type mapping table. For an x86 floating-point calculation instruction, the ARM instruction sequence to which the instruction should be converted is preliminarily determined according to whether the instruction is a high-precision calculation-related instruction. Then, according to whether the instruction exists in a virtual exception instruction table, it is determined whether to add an instruction group for simulating exception triggering to the instruction, so as to complete the conversion of the x86 floating-point calculation instruction, realize the conversion and execution of the x86 floating-point calculation-related instruction to the ARM system, reduce the precision loss of program cross-architecture execution, and improve the reliability of program cross-architecture execution.

The invention relates to the technical field of computers, in particular to a metamorphic relation identification method based on program dependency graph features. The method comprises the following steps: obtaining a control flow graph (CFG) of a target program, and obtaining a control dependency graph according to the control flow graph and a forward dominating tree; obtaining a program dependency graph according to the control dependency graph and the data dependency relationship; according to a program analysis requirement slicing criterion C = (N, V) of a target program, graph traversal is conducted on the program dependency graph, program slicing features are obtained, N represents instructions in the target program, and V represents a variable set; and inputting the program slice features into a target prediction model for identification, and obtaining a prediction result corresponding to the metamorphic relationship of the target program. By the adoption of the method and device, the metamorphic relation obtaining accuracy can be improved, the situation that the metamorphic relation cannot be obtained is reduced, program testing convenience can be improved, and software quality is improved.

This invention provides a method, apparatus, electronic device, and storage medium for converting control programs. The method includes: storing instructions from a non-standard control program in a first global instruction list in line-by-line order; storing variables and their data types in a variable mapping table; inserting and deleting ladder identifiers in the first global instruction list according to the positions of the first operator and the serial block operator of the parallel loop to obtain a second global instruction list; inserting omitted instructions in the second global instruction list according to the operators of each instruction in the second global instruction list to obtain a third global instruction list; and determining a standard control program based on the third global instruction list and the variable mapping table. This invention enables the conversion of non-standard control programs into standard control programs.

Provided is a control program editing device that can use an appropriate instruction even when the user does not know an instruction to be utilized and the function thereof. A control program editing device (1), which is used to edit a control program, comprises: a search word input unit (11) that receives a user input of a search word as a user instruction for inputting an instruction; an instruction list acquisition unit (12) that acquires an instruction list of instructions, instruction names, and function descriptions; an extraction unit (13) that extracts instructions related to the search word; and a display control unit (14) that displays the instructions extracted by the extraction unit, instruction names, and function descriptions. A user input for selecting one instruction from among the displayed instructions is received and applied to the control program.

This application discloses a method, apparatus, terminal device, and storage medium for generating instruction expressions, belonging to the field of natural language processing. The method comprises: acquiring unstructured text; extracting semantic features of the unstructured text using a large language model; mapping the unstructured text into a first instruction expression conforming to preset grammatical rules based on the semantic features; running the first instruction expression using a preset instruction execution engine to obtain a first feedback result characterizing the semantic mapping accuracy of the first instruction expression; feeding the first feedback result back to the large language model to drive the large language model to perform semantic alignment correction on the first instruction expression based on the first feedback result, obtaining a second instruction expression; iteratively updating the second instruction expression using a preset algorithm until a preset termination condition is met, obtaining and outputting the target instruction expression. This application can solve the problem of low accuracy in instruction expression generation.

The invention relates to the technical field of tunnel lining protection, and discloses a tunnel lining crack active control method and system based on SHCC. The method comprises the following steps: continuously acquiring lining surface crack dynamic image data through a sensing array deployed in a tunnel; inputting the data into a crack semantic analysis module, calling a crack history archive and a tunnel structure database by the crack semantic analysis module for joint reasoning, and outputting a crack regulation and control target vector; constructing a geometric topology network with lining segments as vertexes and mechanical dependency relationships between the segments as edges, mapping regulation and control target vectors to the network, calculating influence scores of the vertexes through a similarity diffusion algorithm, and screening a key regulation and control vertex set; a candidate regulation and control instruction list is generated according to the set operation multi-index decision model, instructions are executed to complete SHCC material high-precision injection, active control over tunnel lining cracks is achieved, and the regulation and control requirements of crack dynamic changes in the tunnel operation process are met.

The invention relates to the technical field of network security, and particularly discloses a format perception fuzzy testing method and system based on taint analysis, and the method comprises the steps: inputting an input sample and a seed queue into a target program for testing, and carrying out the taint analysis of an instruction level on the target program to obtain a taint instruction list; based on the taint instruction list, dividing an input sample into regions according to bytes, identifying region types and dependency relationships according to a relationship between an instruction control flow and a data flow, and constructing a file format tree and a dependency relationship table; the nodes of the file format tree are varied according to the file format tree, the dependency relationship of the varied nodes is obtained, related fields are adjusted according to the dependency relationship of the varied nodes to generate legal test cases, and the test cases are added into the seed queue.

The invention relates to an instruction extension method and device, a model training method and device and a storage medium. The instruction expansion method comprises the steps that instruction expansion is conducted on an initial instruction, an expanded first instruction is obtained, and the semantic similarity between the first instruction and the initial instruction meets a first similarity requirement; based on the first instruction, a first lexical element is determined, and the first lexical element is a lexical element which is not allowed to appear in the instruction; instruction expansion is conducted on the initial instruction on the basis of the first lexical element, a second instruction is obtained, the second instruction is determined as a target instruction after instruction expansion, and the semantic similarity between the second instruction and the initial instruction meets a second similarity requirement. Through the method provided by the embodiment of the invention, the possibility of single expression of the expanded instruction can be reduced.

The invention discloses a read-write acceleration method and device, a storage control chip and a storage medium. The method comprises the following steps: processing a plurality of operation instructions according to a preset configuration rule to obtain a multi-transmission operation instruction list; storing the multi-transmission operation instruction list into a static random storage area; and reading the multi-transmission operation instruction table, and loading the operation instructions in the multi-transmission operation instruction table one by one to complete Flash read-write operation. According to the method, the MT mode is adopted to read and write the Flash, compared with an ST mode, the generated multi-transmission operation instruction list is stored in the static random storage area, and the NFCMU module for managing the Flash in the master control can directly access the static random storage area to read and load the multi-transmission operation instruction list, so that the Flash can be read and written in the MT mode. According to the invention, it is unnecessary to consume extra time to execute corresponding firmware codes to realize reading and loading in a CPU, so that the read-write operation processing of each main controller on Flash is accelerated.