230 results about "Machine instruction" patented technology

The invention discloses an on-satellite full-autonomous task planning system for an agile remote sensing satellite. Comprising an imaging target database module, a high-precision orbit prediction and orbit calculation module, a target visible arc section calculation module, an imaging task preprocessing module, a subsystem constraint model module, an imaging task planning module, a data transmission task planning module, a solid memory autonomous erasing module, an instruction data block generation module and a satellite state real-time monitoring module. By carrying out constraint modeling on subsystems or single machines such as load, data transmission, control and the like, an on-satellite full-autonomous operation process from receiving of subsystem or single machine instruction blocks from user requirements is established, satellite control is effectively simplified, and remote control uploading efficiency and on-satellite autonomous operation capacity are improved. And through a satellite state real-time monitoring module, the execution condition of tasks on the satellite, satellite state changes and the like are monitored in real time, task execution stopping, whole satellite sun-facing or re-planning are further triggered, task requirements and environment changes are quickly responded, task plans are formulated and adjusted in real time, and the task execution efficiency is improved.

The invention relates to the technical field of workpiece assembly, in particular to a digital twinning and augmented reality guided man-machine cooperation assembly method and system, and the method comprises the steps: collecting a multi-view image, mechanical arm sensing data and a first person image of AR glasses; fusing the data, generating scene assembly information, and constructing a digital twin model; configuring an operation standard, a standard assembly unit space state and a standard hand action template of each assembly process stage, judging a current assembly process stage, identifying an operation intention, predicting a next process in combination with the current assembly stage and the operation standard, and generating a man-machine instruction and simulation data; three-dimensional action guidance is displayed through AR glasses, a mechanical arm is driven to execute planning actions, and a digital twin interface feeds back the assembly state, precision data and prediction animation in real time. According to the method, man-machine standardized cooperation and high-precision assembly are achieved, pre-stored parameters are adaptive to multi-variety production, and the process consistency is improved through real-time feedback.

The embodiment of the invention provides a byte code generation method and device and a machine code generation method and device, and the byte code generation method comprises the steps that a target source code is obtained, first processing is applied to the target source code, and the first processing comprises the steps that a target statement used for integer operation in the target source code is replaced with a preset target function; according to the first processed target source code, a target byte code is generated, the target byte code comprises a byte code instruction generated according to a preset function, and the byte code instruction indicates that integer operation corresponding to the target statement is executed through a preset machine instruction sequence and overflow check for the integer operation is executed.

A task processing method and apparatus, and a device, a storage medium and a program product, which are applied to task processing scenarios such as artificial intelligence, big data and cloud computing. The task processing method comprises: on the basis of task prompt information corresponding to a target task in a service scenario, generating a system interaction parameter corresponding to the target task, wherein the task prompt information is used for describing the target task in the form of natural language, and the system interaction parameter is used for describing the target task in the form of a machine instruction; calling a task system of the target task, and processing the system interaction parameter; and on the basis of output information of the task system of the target task regarding the system interaction parameter, determining a processing result corresponding to the target task.

The invention provides a digital-analog hybrid simulation method and simulator based on a QEMU, a SystemC and a SystemC-AMS. The digital-analog hybrid simulation method comprises the following steps: adding an external memory access interface and a time sequence synchronization interface in the QEMU; the method comprises the following steps: constructing a virtual CPU (Central Processing Unit) device in a SystemC; a register interface function and a logic signal function are realized by adopting a systemc model in the equipment, and a port analog signal function is realized by adopting a systemc-am model; the starting parameters are analyzed in the main program, and the simulation component is loaded; executing a virtual target machine instruction in the instruction core environment; switching to a systemc running environment, changing the value of an on-chip device register, and updating the logic function state and the port state of the device; and exiting from the systemc operation environment, and entering the operation environment of the instruction core again. The technical advantages of the QEMU, the SystemC and the SystemC-AMS are combined, a QEMU instruction set is reused, meanwhile, the hardware description language characteristics of the SystemC and the analog signal processing capacity of a simulation scheduler and the SystemC-AMS are utilized, digital-analog hybrid simulation is achieved, and the verification efficiency and accuracy of SoC design are improved.

The invention discloses a path planning method and system for corner optimization. The method and system are used for cutter radius compensation and machining instruction smooth transition of a three-dimensional path of a numerical control machine tool. The method comprises the steps that a machining instruction is pre-read, and a path point location is analyzed; calculating a path direction vector and a normal vector, and determining a path plane equation; calculating a plane included angle and an intersection direction vector through a normal vector; generating a compensation curve by translating along the perpendicular direction of the intersecting line by taking the radius of the cutter as a constraint; and generating a smooth control instruction through curve subdivision and inserting the instruction into an instruction queue. The problem that three-dimensional path corner transition is not smooth is solved, the machining precision and efficiency are remarkably improved, and the method is suitable for a numerical control machine tool for complex curved surface machining.

The invention belongs to the technical field of unmanned aerial vehicle control, and particularly relates to an unmanned aerial vehicle body intelligent operation method based on visual feedback and behavior tree control, a readable storage medium and a program product. The method comprises the following steps: firstly, optimizing a large-scale language model through prompt word engineering and instruction fine tuning, and converting a user password into an unmanned aerial vehicle instruction; then obtaining a potential risk target in the route based on a visual target detection algorithm of ensemble learning; then, behavior tree nodes are designed, and a behavior tree system architecture is designed from top to bottom; and finally, information interaction among the modules is carried out based on a robot operation system, and stable operation of the unmanned aerial vehicle body intelligent algorithm system is realized. According to the method, the unmanned aerial vehicle can effectively understand user instructions, intelligently detect risk points in the cruising process and autonomously execute unmanned aerial vehicle tasks such as fly-around under the condition that no waypoint is preset, dynamic environments and complex tasks are effectively dealt with, and intelligent application of the unmanned aerial vehicle is promoted.

The invention relates to the technical field of data processing, and provides an error compensation method, device and equipment for shaft part machining and a storage medium, and the method comprises the steps: obtaining the measurement data of the actual size of a shaft part, calculating the deviation data, inputting the measurement data and the deviation data into a preset neural network compensation model, compensation parameters and machining stability parameters are obtained, the path of a machining tool is adjusted based on the compensation parameters, a target path machining instruction is obtained and subjected to spectral analysis, a corrected instruction is obtained and checked through the machining stability parameters, and the shaft part is machined after the target machining instruction is obtained. The actual size of the shaft part is measured, deviation is calculated, a machining path is adjusted in combination with a neural network compensation model, a machining instruction is optimized through a spectral analysis technology, and the problems that errors of dynamic changes in the machining process cannot be coped with, tremor is likely to occur in the machining process, and the part compensation difficulty is aggravated are solved. And the problem of insufficient real-time error correction exists.

The invention provides a code compiling method and device based on a P4 assembler, the assembler and a medium. The code compiling method comprises the steps that a to-be-processed assembly code file is obtained; splitting and compiling the assembly code file to obtain a plurality of code segment compiling results; according to the auxiliary information, by taking Parser components, Mat components and Deparser components contained in the Ingress unit and the Egress unit as classification types, classifying the code segment compiling results to obtain code segment groups; linking the P4 table item data and the machine instruction code contained in the code segment group, and endowing a link result with a global instruction identifier and code segment header information to obtain a code segment binary code; and generating a firmware file based on the code segment binary code. The compiling process of the network processor can be simplified, so that the development efficiency is improved.

The invention provides a PLC control task execution time prediction method and device, equipment and a medium, and the method comprises the steps: carrying out the machine instruction processing of a PLC control task, and generating a machine instruction program corresponding to the PLC control task; carrying out basic block division processing on the machine instruction program, and determining a plurality of basic blocks in the machine instruction program; generating a control flow chart corresponding to the machine instruction program based on the pointing relationship among the plurality of basic blocks; and taking the total weight value of each basic block as the weight value of each basic block in the control flow chart, performing depth-first traversal on the control flow chart to predict a target execution path corresponding to the PLC control task, and determining the actual execution time of the PLC control task based on the total weight value of the target execution path and the clock period of the processor. The execution time of the PLC control task can be accurately predicted, and the problem of unreasonable task period setting is solved.

A system includes a processor and a non-transitory computer-readable medium storing machine instructions that cause the processor to perform a first fast Fourier transform (FFT) on received radar data to obtain a range-antenna data array and to perform a second FFT on the range-antenna data array to obtain a range-Doppler-antenna data cube. The processor performs peak detection on the range-Doppler-antenna data cube based on object information to obtain a subset that includes confirmed peaks and candidate peaks. The processor performs angle of arrival calculations for the subset of the range-Doppler-antenna data cube, and filters candidate peaks in the subset to obtain a point cloud representative of an environment. In some implementations, the confirmed peaks are detected based on a default threshold value, the candidate peaks are detected based on at least one adapted threshold value, and the at least one adapted threshold value is determined based on the object information.

A new machine procedure and electronic circuitry are provided that hide one or more signals inside noise. In an embodiment, a random nonce helps unpredictably move the hiding locations of the signals. In an embodiment, the quantum complexity is related to the complexity of Grover's algorithm so that the hiding procedure is resistant to quantum computers. In some embodiments, public keys are hidden in the noise. In some embodiments, quantum randomness generates random noise and a random nonce, using photonic emission with a light emitting diode, and flip-flops.In other embodiments, our machine procedures and circuits use robustness, unpredictably and variability to hinder malware infection. In some embodiments, our machine instruction opcodes are randomized. The computing behavior of our machine is structurally stable (invariant) to small changes made to its machine instructions. Our invention expands the engineering method of stability to a cryptographically stable machine that is resistant to malware sabotage by an adversary.

A task processing method performed by an electronic device includes generating, based on task prompt information corresponding to a target task in a service scenario, a system interaction parameter corresponding to the target task. The task prompt information describes the target task in a form of natural language, and the system interaction parameter describes the target task in a form of machine instructions. The method further includes invoking a task system of the target task to process the system interaction parameter, and determining a processing result corresponding to the target task based on output information of the task system for the system interaction parameter.

A Health Value Analytics (HVA) system includes an electronic medical record (EMR) / HVA access device in the form of comprising machine instructions for facilitating a physician's workflow. A processor at a physician's work terminal executes the machine instructions to connect the terminal with a HVA server and / or an EMR server. The processor sends a medical information request for a patient and information related to characteristics and parameters of the terminal, to one or both the HVA server and the EMR server. The processor receives, in response, an EMR page generated and adapted by the EMR server for display on the terminal. The EMR page displays an electronic medical record of the patient, and one or more HVA data objects generated by the HVA server, after the EMR server adapts the EMR page based on mode information that includes characteristics of the terminal.

The invention discloses an experiment scheme execution method and system based on a large language model, and relates to the technical field of scheme design, and the experiment scheme execution method based on the large language model comprises the steps: obtaining multi-modal information input by a user, recognizing the intention of the user, and triggering a workflow; verifying whether the experiment information corresponding to the user intention is complete or not according to the intelligent agent, and if yes, integrating and outputting an initial experiment scheme through a large language model; according to the knowledge base, performing knowledge retrieval on the initial experiment scheme, and combining the retrieved reference content with the initial experiment scheme to obtain a candidate experiment scheme; performing user real-time interaction based on the candidate experiment scheme to obtain a modification opinion input by a user, obtaining real experiment environment information, and modifying the candidate experiment scheme according to the modification opinion to obtain an executable experiment scheme; and compiling the executable experiment scheme into a machine instruction format to drive equipment to execute the executable experiment scheme. According to the method, the suitability of the biological wet experiment scheme is improved.

Disclosed in the present invention are a numerical control system path measurement method and the use. The method comprises the following steps: analyzing a pre-configured machining instruction to obtain a reference machining path; on the basis of the pre-configured machining instruction and preset machining parameters, performing path planning to obtain a planned machining path; and, on the basis of the reference machining path and the planned machining path, measuring a path of a numerical control system. The method can effectively measure deviation errors of planned machining paths, so as to avoid damage to machined workpieces and machine tool spindles caused by deviations of the machining paths.

The invention discloses a design method for an on-orbit accompanying measurement and control communication machine state machine model, and the method comprises the steps: constructing a data model of a measurement and control communication machine state machine, and enabling the data model to be used for calling data externally; constructing a context model of the state machine of the measurement and control communication machine based on the data model, and constructing a logic architecture of the state machine of the measurement and control communication machine based on scene service data; based on the logic architecture, the context model obtains an executable extended state machine and updates the feature attributes; obtaining a simulation model through periodic continuation based on the state machine capable of executing expansion and the context model, wherein the simulation model is used for processing uplink and downlink remote control and telemetering, voice and distance measurement service data of satellite communication, responding to a communication machine instruction set of the state machine of the measurement and control communication machine and outputting communication machine product telemetering; universal configuration is implemented based on the communicator instruction set and the communicator product telemetry.

The invention discloses an ALU operation fusion processing module and method suitable for a neural network, and the module comprises a control unit which is used for receiving and decoding a machine instruction, managing the execution processes of internal and external circulation and microinstruction circulation, and generating a control signal of each stage of a microinstruction assembly line; the microinstruction buffer area is used for storing a microinstruction sequence pre-generated by the neural network compiler; the register file is used for storing source operands and results of ALU operation; each entry of the register file is composed of a valid bit, a tag bit and a data bit; the ALU computing core adopts an SIMD (Single Instruction Multiple Data) architecture and comprises a plurality of paths of parallel arithmetic logic function units; the Load / Store unit is used for processing data exchange between a register file and a local buffer area; and the data selection interface is used for selecting a data source or a target buffer area according to the storage tag field of the microinstruction. According to the method, the high efficiency and the flexibility of the ALU in the neural network hardware accelerator can be effectively considered.

A parameterized instruction selection method is applied to optimizing a compiling process executed by a compiler. According to the parameterized instruction selection method, a corresponding machine instruction set is generated for instructions in a to-be-compiled code in advance during compiling, so that one or more corresponding machine instructions which can be selected by each instruction in the code during compiling are indicated on the basis of the machine instruction set; according to the method, the compiler does not select a default machine instruction for an instruction in a code any more, the compiler is guided to select different machine instruction combinations in the compiling process, so that multiple different target files are obtained, finally, the target file with the optimal execution performance is selected by executing the multiple target files, the flexibility of the instruction selection process is improved, and the user experience is improved. And compiling to obtain the target file with higher execution performance.

A system for synthetic voice generation may include a computer system having at least one processor and at least one memory storing executable machine instructions, wherein the computer system is configured to execute machine instructions to perform operations including: receive one or more recorded voice samples, each voice sample corresponding to a different human speaker voicing a training text with one or more voice characteristics different from voice characteristics of another human speaker; generate a structured training dataset based on the received recorded voice samples; train an artificial intelligence (AI) synthetic voice generation model using the generated structured training dataset; provide input corresponding to a target text to a deployed generative AI process to generate a narration track; and combine the synthetic narration track with a predetermined target video segment to generate a narrated audiovisual segment.

A system, method, and computer-readable medium having machine instructions provides for predicting geometric shape accuracy of 3D printed products. Such a prediction may involve developing a model of an object and determining ways in which an actually-manufactured 3D object corresponding to the model differs in real life. These differences correspond to shape deviations. Shape deviations may be process dependent and / or path dependent, and different layers of the object as well as the manufacturing process to make the different layers may introduce shape deviations in layers of the object. By developing a transfer functions of the manufacturing process and associated interlayer effects of the layers and then appropriately offsetting inputs to the manufacturing process, the shape deviations may be ameliorated.

The invention relates to the field of code vulnerability detection, in particular to a binary vulnerability retrieval and positioning method and system based on high-dimensional vulnerability characterization, and the method comprises the steps: firstly inputting a binary file, analyzing the structural information of the binary file, and analyzing a machine instruction; extracting binary file function information, generating a cross-platform basic block IR instruction sequence, constructing a control flow graph, and constructing a data dependency graph; splicing the program dependency graph feature vector and the basic block IR instruction sequence feature vector, and performing multi-modal feature fusion to generate a comprehensive high-dimensional vulnerability representation vector; and finally, inputting the high-dimensional vulnerability representation vector into an index for searching to obtain a plurality of nearest neighbor indexes and distances, converting the distances into similarity, filtering according to a similarity threshold to obtain a most similar vulnerability vector, and obtaining vulnerability information and vulnerability positions corresponding to the vulnerability vector. The problems that traditional binary vulnerability detection cross-platform and compiler optimization detection fails and the result reliability is low are solved.

The invention provides an instruction stream reconstruction method and device, electronic equipment and a readable storage medium. The instruction stream reconstruction method comprises the steps that a target instruction address sent by processing equipment according to a target sampling interval and execution times recorded in various types of registers respectively are acquired; the target instruction address is the address of a target machine instruction currently executed in the machine instruction set; each type of register has a corresponding instruction execution type; the number of execution times is the total number of execution times of the machine instruction of the corresponding instruction execution type, and determining all branches between two target instruction addresses according to the source code and the target instruction addresses sent by two adjacent sending operations; the source code records the machine instruction needing to be executed, the change condition of the execution times of each type of register in two adjacent sending operations is calculated, the target branch is determined from all branches according to the change condition, and the machine instruction set is reconstructed according to the target branch, so that the instruction stream can be accurately recovered.

The invention discloses a cross-platform binary code block hierarchical semantic similarity detection method and a related device, and belongs to the field of code vulnerability detection.The cross-platform binary code block hierarchical semantic similarity detection method comprises the following steps that structural information of a binary file is analyzed, a machine instruction is analyzed through a hybrid disassembling engine, a basic block is extracted from the structural information of the binary file, and the basic block is extracted from the binary file; constructing a control flow graph, a data dependency graph and a function call graph; extracting instruction level semantics, basic block level semantics and function level semantics from the instruction sequence, the basic block, the control flow graph, the data dependency graph and the function call graph; according to the instruction-level semantics, the basic-block-level semantics and the function-level semantics, constructing instruction-level features, basic-block-level features and function-level features; and carrying out hierarchical similarity detection on the instruction-level features, the basic block-level features and the function-level features. The method and the related device can solve the problems of low detection efficiency and poor accuracy when a traditional vulnerability detection method is used for detecting vulnerabilities.

The invention discloses a man-machine instruction automatic generation external control system and method based on physical isolation perception. The system comprises an external execution body, a display sensing module, an artificial intelligence decision module and an input execution module. The local independent proxy device operates independently of the controlled system, acquires a screen display signal of the controlled system in one direction through an external display acquisition link, generates a control instruction based on acquired interface information, acts on the controlled system through a standard man-machine input interface, and constructs a closed-loop verification mechanism taking the screen display signal as a judgment basis. The information acquisition constraint, the judgment constraint and the execution authenticity constraint are followed, and verifiable confirmation of a control instruction execution result is realized. The system supports multi-mode triggering and external physical equipment extension control, solves the problems of insufficient safety, limited compatibility and poor verification reliability in the prior art, and is suitable for application scenes with high safety requirements.

The invention relates to the field of code vulnerability detection, in particular to a vulnerability detection method and system based on code block features. The method comprises the steps that firstly, a binary file is analyzed, and a machine instruction is analyzed through a hybrid disassembling engine; secondly, performing static linear scanning on the extracted binary file instruction, constructing a control flow graph, dividing basic blocks, extracting an operation code sequence in the basic blocks, and constructing a cross-basic-block data dependency graph and a system calling sequence called by the basic blocks; secondly, using an LSH algorithm to realize rapid filtering, performing similarity comparison on extracted basic block features and vulnerability feature library features, realizing coarse-grained matching, and screening out a matching candidate set; feature fusion is carried out on the candidate set basic block operation code sequence, the basic block data dependency graph and the system calling sequence called by the basic block, GNN fine-grained matching is carried out on the fused features, and vulnerability detection is carried out. The problems that traditional binary vulnerability detection is poor in adaptability and low in result reliability are solved.

The present invention relates to a deep learning machine instruction generation method and device supporting multiple types of backend computing hardware. The method comprises the following steps: obtaining a deep learning model program, and converting the deep learning model program into a series of computational graphs; comparing each computational graph with target hardware support information, determining whether an operator which is not supported by the target hardware exists in the computational graph, if yes, partitioning the current computational graph to obtain second-level sub-graphs, and if not, directly using the current computational graph as a second-level sub-graph, wherein a corresponding sub-graph type is marked on each second-level sub-graph; generating a corresponding operator code on the basis of the sub-graph type marked on each second-level sub-graph; and connecting the operator codes to generate a complete machine instruction set. Compared with the prior art, the present invention has the advantages of being compatible with various hardware scenarios and the like.

The invention belongs to the technical field of laboratory automation, and particularly relates to a laboratory automation system based on an artificial intelligence technology. The system comprises an intelligent man-machine interaction module which is used for interacting with a user and obtaining input information; the intelligent analysis module is used for processing the obtained input information, converting the information into a standardized machine instruction and providing an optimization suggestion for a user experiment scheme through a knowledge base; the information sensing module is used for sensing the space positioning of the biological experiment instrument in the operation space so that the mechanical arm can conduct grabbing movement and experiment operation; and the experiment execution module is used for automatically completing an experiment process through a mechanical arm. The invention has the characteristics of high flexibility and low operation threshold.

The invention relates to a control method for beam guidance and measurement acquisition for scanning applications. A beam scanning control system includes a motion compiler, a positioning compiler, and a controller. The motion compiler receives a high-level description language of a plurality of scan regions defining a scan area and a plurality of scan parameter subsets corresponding to the plurality of scan regions, calculates a two-dimensional (2D) scan pattern based on the high-level description language, and generates an assembly instruction based on the 2D scan pattern. Each scan parameter subset corresponds to a respective scan area of the plurality of scan areas. The positioning assembler compiles an assembly instruction into a machine instruction based on one or more characteristics of the 2D scanning system. The controller executes the machine instructions and generates a control signal for controlling the 2D scanning system to perform a 2D scan on the scan area according to the 2D scan pattern based on executing the machine instructions.

A list sort instruction is provided to perform a sort and / or merge operation. The instruction is an architected machine instruction of an instruction set architecture and is executed by a general-purpose processor of a computing environment. The execution includes sorting a plurality of input lists to obtain one or more sorted output lists as output.