68 results about "Finite state" patented technology

According to the automatic software development method and device and the computer program, intelligent demand analysis is achieved through a natural language processing technology, dynamic task arrangement is conducted through a finite state automaton, collaborative development is completed by means of a multi-specialized role agent, intelligent verification is implemented based on a template matching mechanism, and the development efficiency is improved. And a complete automatic closed loop from demand to delivery is constructed. According to the scheme, full-process automation is realized, manual intervention is greatly reduced, and the development efficiency is remarkably improved; through division and cooperation of multiple agents, the professionality and decision-making quality of each link are ensured, and the capability limitation of a single agent is overcome; flexible and reliable process control is provided based on state machine management, and development state changes are dynamically adapted; and the standard consistency of the delivery result is ensured by combining template verification. According to the method, the problems of long development period, large quality fluctuation and the like caused by chain splitting, low intelligent level and excessive dependence on manpower of an existing development tool are effectively solved, and a feasible path is provided for comprehensive intelligence of software development.

The invention relates to the technical field of intelligent training and data analysis, in particular to an intelligent model construction method and system for student training data analysis. Comprising the following steps: constructing an SOP time sequence knowledge graph, obtaining a standard operation specification document and expert-level operation demonstration data, and constructing the SOP time sequence knowledge graph; real-time feature extraction: capturing a multi-modal data stream, and generating a real-time behavior feature vector; state recognition and path deduction: inputting the real-time behavior characteristics into an event classifier to recognize a key event, performing path deduction based on deterministic finite state automaton logic in an SOP time sequence knowledge graph, and determining and outputting a current state pointer; deviation analysis and judgment: extracting a compliance mask based on a current state, and injecting the compliance mask into a decoding process of the attention network; and performing feedback and adjustment to generate a corresponding deviation event signal. Through deep analysis, feedback is more targeted, and the accuracy and fineness of training evaluation are remarkably improved.

The invention discloses a finite state inquiry method and system based on a large model and a knowledge graph, and relates to the field of business handling, when there is a business handling intention, a finite state machine sets an initial business state, and a large language model analyzes, inputs and extracts keywords and demands to determine a current state; the user naturally converses with the big language model, and the big model is guided to complete the process according to the knowledge graph and the current state; when the user interrupts questions, the large model answers the questions according to the knowledge graph, and then the finite-state machine records the state to help the user to seamlessly return and continue to handle the questions; according to the method, the problem of large model illusion is effectively solved, and the accuracy and stability of user intention judgment are improved; intelligent autonomous business handling without manual intervention is realized; the seamless recovery process after the user interrupts questions at any time is supported, and the flexibility and coherence of business handling are enhanced; comprehensive knowledge coverage is ensured by means of a knowledge graph, and user questions are accurately answered; and meanwhile, the dependence on manual business personnel is reduced, and the labor cost is reduced.

The invention provides a code-free SaaS application rapid development method and system based on data source driving, and the method comprises the steps: constructing a forward business process directed acyclic graph, defining compensation association and reality binding for a forward operation node of the forward business process directed acyclic graph, and generating a visual transaction model; analyzing the transaction model to generate a transaction step sequence, constructing a finite state set and a state transfer function based on the sequence, and packaging the finite state set and the state transfer function into an SAGA process state machine definition object; generating a global transaction ID when a transaction life cycle is started, constructing a transaction context object in combination with the state machine definition object, and serializing to generate an initial transaction context instance; and loading and deserializing the instance, starting a state-driven execution loop, terminating by iterating single-step state transition when the current state belongs to a termination state set, judging a final result of the transaction, and archiving an audit log. According to the method, transaction process modeling and formalized state driving execution are fused, and the method is suitable for SaaS application development of cross-heterogeneous data sources.

A computer-implemented system that reduces and resists computationally generated fraudulent reviews by enforcing aspect-level decomposition with evidence requirements, multi-tier cryptographic verification, and deterministic trust scoring. Reviewer tiers (public, independent reviewer, independent professional reviewer) use verifiable credentials, zero-knowledge purchase proofs, and device or platform attestation. Evidence gates apply fixed, monotonic transformations; mandatory-evidence aspects yield zero contribution absent a required artifact. A finite-state dialog protocol with immutable timer fields enforces typed, aspect-bound objections. A Consumer Trust Board employing threshold signatures issues binding decisions affecting Consumer Trust Score computation with bounded retro-adjustment. A certification registry maintains credentials and sanctions that calibrate weighting. Non-instrumented submissions are badge-ineligible and weight-capped. Uniqueness keys prevent double counting. Dialog records are version-chained and batch-anchored via collision-resistant commitments. All computations use parameters from a versioned configuration to ensure deterministic reproducibility.

The invention discloses a quantum key distribution system and method. According to the system, a phase coherence monitoring mechanism is innovatively introduced, and early attack detection is realized through a dynamic consensus sampling protocol; a zero-trust relay network is constructed by adopting a wavefront fragmentation principle, and trust dependence on relay nodes is eliminated; self-adaptive safety monitoring is realized based on a finite state automaton, and a system safety strategy is dynamically adjusted. According to the method, the problems of resource consumption type attack, relay trust dependence, static protocol limitation and the like faced by an existing QKD system are solved through a strict mathematical framework, and long-distance quantum key distribution with efficient resources, endogenous security and elasticity and physical layer security guarantee is realized. Experiments show that compared with a traditional scheme, the detection delay of the system is reduced by about 38%, the resource waste is reduced by about 40%, and the availability of the system reaches 99.995% or above.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a computer network intrusion detection method and system based on artificial intelligence, and the method comprises the steps: constructing a finite state automaton to carry out the state jump compliance verification of a connection flow, intercepting the illegal flow, only sending the compliance flow into a feature engineering module, and extracting the multi-dimensional behavior features; inputting a deep neural network classification model to determine whether the behavior is an intrusion behavior; according to the technical scheme provided by the invention, the data input to the artificial intelligence model can be ensured to have complete compliance on the protocol level, so that the model is prevented from learning false feature association caused by protocol violation, and the antagonistic attack based on protocol state jump can be effectively resisted on the premise of not depending on adversarial training.

The invention belongs to the technical field of aviation safety information processing and intelligent retrieval, particularly relates to an aviation safety knowledge mixed retrieval system based on a creative distributed database, and solves the problem that the prior art cannot meet the requirements of aviation safety information processing accuracy, efficiency and reliability. The method comprises the following steps: firstly, depending on a Peng and Feiteng trust and creative server and an OceanBase distributed database, matching an integrated storage engine and a physical collaborative distribution module, and constructing a multi-type data fusion storage base; then realizing precise semantic retrieval, weak network off-line data management and increment synchronization through double-engine cooperation of an intelligent engine layer, fusion of a domain-specific embedded model and an RRF optimization algorithm and combination of a finite-state machine and a positive and negative counter algorithm; and the application service layer standardizes an API and a multi-tenant isolation strategy, and adapts to multi-terminal and third-party system integration. The accuracy, efficiency and reliability of aviation safety information processing are remarkably improved.

The invention discloses a hardware acceleration method and system for a ZSTD data compression algorithm based on an FPGA. Unified hardware implementation and collaborative optimization are carried out on three key links of LZ77 character matching, Huffman coding and finite state entropy coding in the ZSTD data compression algorithm. According to the system, a multi-channel parallel LZ77 character matching hardware architecture is adopted, and character matching is executed on continuous positions in a plurality of parallel windows at the same time. A modular design and a deep pipeline structure are adopted, and a buffer and pipeline mechanism is introduced among modules such as an LZ77 matching module, a Huffman coding module and a finite state entropy coding module. The 375MB / s compression throughput can be achieved under the 100MHz clock frequency, the compression speed is remarkably increased while the compression ratio is guaranteed, and the method is suitable for scenes with high requirements for compression performance of data centers, edge computing and embedded systems and has high practicability and popularization value.

A text segmentation and sensitive word detection method based on matrix multiplication, comprising the following steps: obtaining an original text string and a sensitive word library; constructing a deterministic finite state automaton tree diagram of sensitive words according to the sensitive word library; converting the original text string into a text character two-dimensional matrix and recording the length of the text character two-dimensional matrix; constructing a matching two-dimensional matrix according to a horizontal matching rule, a vertical matching rule, an oblique matching rule and an inverse oblique matching rule, the length of the matching two-dimensional matrix being the same as that of the text character two-dimensional matrix; performing dot multiplication processing on the text character two-dimensional matrix and the matching two-dimensional matrix to obtain a corresponding result matrix; generating a corresponding matching text string according to the result matrix, and matching with the deterministic finite state automaton tree diagram to determine whether there is a sensitive word. The application supports interval text character information detection, improves the sensitive word detection accuracy and detection efficiency.

The invention relates to a technique for implementing, controlling and automating a task or process on a blockchain such as, but not limited to, the Bitcoin blockchain. The invention is particularly suited for, but not limited to, automated execution of contracts such as smart contracts for financial agreements. However, other types of tasks and non-financial contracts can be implemented. The invention can be viewed as the implementation or incarnation of a state machine or DFA on a blockchain by using the unspent outputs of blockchain Transactions to represents the states of the machine, and spending of those outputs as the transition of the machine from one state to another. The invention provides a technical realisation and implementation of a mathematical model of computation conceived as an abstract machine that can be in one of a finite set of states, and can change from one state to another (transition) when a triggering event of a finite set (called input) occurs. The invention comprises compilation and codification techniques for the DFA implementation.

A method includes detecting an outage in a wireless communications network, acquiring specifications documents describing communication protocols between a plurality of network elements and a plurality of user equipment of the network, translating, using a generative artificial intelligence technique, the specifications documents into a first FSM that models expected events and corresponding actions from perspectives of the plurality of network elements and the plurality of user equipment, translating, using the generative artificial intelligence technique, a plurality of event logs of the network into a second FSM that models observed behaviors of the plurality of network elements and the plurality of user equipment, detecting, based on a comparison of the second FSM to the first FSM, a behavior of the observed behaviors that deviates from the communication protocols, and identifying a network element of the plurality of network elements that is associated with the behavior as a contributor to the outage.

The invention discloses a trusted space-based data annotation management and control method, system and device, and a medium. The method comprises the following steps: responding to a data labeling task request, determining a task type and labeling a task life cycle, dividing the task into a plurality of finite states, and binding a dynamic strategy set for each state; determining the computing power demand of each state according to the task type, and obtaining and configuring a corresponding resource template; when a user initiates a trusted spatial data loading request, obtaining user information and a loading demand, activating a resource template in an authentication state, and performing authentication according to a dynamic strategy set; after the authentication is passed, triggering a state transition event to enter a data loading state, and loading target data; after labeling is completed, a labeling result is obtained and subjected to quality inspection auditing; and if the audit is passed, outputting a result, and uploading the migration event and the annotation result for evidence storage. According to the method, the labeling work can be efficiently and safely completed according to the task, meanwhile, the integrity, traceability and safety of the data are effectively guaranteed, and the quality and efficiency of the labeling work are improved.

The present invention relates to a computer implemented decoding method that includes decoding a number of run-length encoded mask strings to obtain decoded mask bits for each of a number of scan channels. The method also includes applying the decoded mask bits to automatic test pattern generator (ATPG) scan response data of each scan channel to obtain a multiple input signature register (MISR) signature. Additionally the present invention also relates to an apparatus configured to carry out the method. The apparatus being implemented either with at least one memory and at least one processor or with a plurality of finite state machines and a plurality of logical AND gates.

This invention discloses a method for autonomous operation of humanoid robots based on ROS. It employs a decision-making and control framework that fuses hierarchical finite state machines with YOLOv8 vision to achieve continuous autonomous execution of multiple tasks in complex unstructured environments. The method includes: system initialization and standardized processing of multimodal perception data; target 3D localization fused with YOLOv8 and coordinate transformation; task scheduling and state transitions using hierarchical finite state machines; segmented navigation and motion planning of joint trajectories; and ROS command issuance and full-process closed-loop control. This invention addresses the rigidity of traditional script-based control by fusing hierarchical state machines with visual servoing. Combined with a full-process anomaly handling mechanism and multi-target scene processing rules, it can dynamically adapt to changes in complex unstructured environments, effectively avoiding problems such as state freezes and erroneous grasping.

The invention discloses a sliding input method, a sliding input device, sliding input equipment and a medium, which are used for a mobile terminal, are internally provided with an input keyboard, and comprise the following steps: responding to a sliding input operation on the input keyboard, generating an activated key sequence, and extracting sequence features based on coordinate information contained in the activated key sequence; and searching an initial candidate word list corresponding to the activation key sequence by adopting a finite state conversion machine, and screening and / or sorting according to sequence features to obtain a target candidate word list and displaying the target candidate word list. The sliding input method is not limited to specific languages and keyboard layouts, and can meet the sliding input requirements of the multi-language multi-keyboard layout mobile equipment under the language families such as the Euclidean language family, the sub-non-language family and the Kongsu language family. Meanwhile, the feature extraction method is simplified, the computing resource consumption of feature extraction can be greatly reduced, and the requirement of a user for highly matching candidate words is met while efficient computing is kept.

A system can include a plurality of hardware threads, one or more schedulers, and one or more execution pipelines. At least one hardware thread of the plurality of hardware threads can include one or more finite state machines. At least one finite state machine of the one or more finite state machines can be of a first type. The at least one finite state machine can process hazards on instructions. The at least one finite state machine can determine cycles in which the instructions are safe to issue to at least one of the one or more execution pipelines.

The application belongs to the technical field of software dangerous behavior detection, and is a multi-level specification software dangerous behavior detection method, comprising the following steps: setting a positive and negative example set and a distance measurement function for quantifying the similarity degree of software behavior sequences, and dividing the positive example set into a plurality of positive example subsets; constructing a temporal logic specification weight tree as a triple consisting of a root node weight function, a left child formula depth weight function and a right child formula depth weight function; extracting positive examples from the positive example subsets to form a positive example reduced set; inquiring a large language model to obtain software dangerous behavior logic formulas and converting the software dangerous behavior logic formulas into equivalent finite state automata; sampling a negative example reduced set from the automata; inquiring the large language model based on the positive and negative example reduced sets multiple times to obtain formula fragments, dynamically updating the weight tree, and obtaining candidate formulas; and selecting the optimal candidate formula as a temporal logic specification to detect whether the software behavior sequence conforms to the temporal logic specification. The application alleviates the challenges of scarce dangerous behavior data and a too large dangerous behavior search space.

The invention relates to the technical field of data management, and particularly discloses a warehouse operation data management and control method, which comprises the following steps: constructing a multi-source heterogeneous data unified access layer, and carrying out standardization and metadata annotation; establishing a space-time alignment fusion mechanism based on the high-precision timestamp and the three-dimensional grid index; deploying a dynamic rule engine to realize millisecond-level self-adaptive updating of a service rule; respectively constructing a Markov chain, a finite-state machine and a hidden Markov model for three types of core entities of goods allocation, order and equipment to carry out state evolution prediction; and an abnormal risk index is calculated in combination with the prediction deviation and the rule conflict, and closed-loop verification is realized through end-to-end log comparison. According to the technical scheme, real-time consistency guarantee of storage data, operation traceability enhancement and prospective early warning of abnormal risks can be achieved, and fine operation of millisecond-level response and large-scale intelligent storage in a high-concurrency scene is supported.

An object-goal navigation framework for an autonomous mobile robot uses a dynamic Scene Graph (DSG) and a Relational Semantic Network (RSN) for semantic-guided object-goal navigation. The DSG is a hierarchical world representation generated from a prior spatial configuration of the environment. The RSN encodes relational semantic knowledge between objects and the regions or rooms in the environment. The object-goal navigation problem is then solved using a probabilistic planning framework with relational semantic knowledge. Using DSG and RSN, the global planning problem is formulated as a Markov decision process (MDP). The computed global planning policy directs the robot to visit a room or perform local searches. A finite state local controller is then used to execute the global planning policy and search for the target object.

The invention discloses an index recovery method, device and equipment and a computer readable storage medium, which are applied to the technical field of computers, and the method comprises the following steps: when a fault occurs, analyzing a data topological structure corresponding to an index data fragment stored by a node; based on the fragment access log of the node, calculating a heat value of the index data fragment by adopting a time decay model; determining a loading thread count according to the node resource state; determining the priorities of the index data fragments based on the business query priorities, the popularity values and the fragment memory efficiency, and determining a loading sequence according to the priorities; and according to the loading thread count and the loading sequence, loading the index data fragments in the nodes from the persistent storage to the cache, and constructing a memory finite state converter structure capable of being directly retrieved based on a data topological structure. According to the method, on the premise that the system architecture is not changed, the distributed retrieval system can be quickly recovered when the fault occurs, the unavailable time of the system is shortened, and the availability, stability and resource utilization rate of the system are improved.

This invention discloses a robot intelligent control system, relating to the field of robotics, including a memory internally storing pressure thresholds, height thresholds, and height difference thresholds; a data acquisition device; a prediction device including a pressure analysis module; a height analysis module that compares the collected n leg heights, sorts them by leg height to form a leg height array, generates a leg height difference between two adjacent data in the array, forms a leg height difference array, filters out the group of data with the largest leg height difference, removes the data closest to the height threshold, and maps it to the other leg; a finite state automaton; a height calculation unit; and a drive device. The robot intelligent control system of this invention, because it adopts a direct monitoring method, can acquire the physical quantities and state of the target in real time, has high real-time performance for the rapid decision-making of the finite state automaton, thus ensuring adjustment accuracy, and has a relatively fast processing time.

A method of quantum probability estimation of an event in a stochastic process is provided. The stochastic process is modelled based on a finite state-machine model. A classical predictive model for the event is modelled based on the stochastic process and includes a set of states and a set of state transition matrices associated with the finite state-machine model. The method includes: generating a circuit description of a quantum state-preparation operator based on a past observation sequence of the stochastic process and the set of state transition matrices of the classical predictive model; generating a circuit description of a quantum search operator based on the circuit description of the quantum state-preparation operator and an event indication function, whereby the event indication function is configured to indicate whether the event is to occur with respect to the future sequence of the stochastic process; generating a plurality of circuit descriptions for a plurality of measurement quantum circuits, respectively, for compiling the plurality of measurement quantum circuits on a quantum computer, whereby each circuit description of the measurement quantum circuit is generated based on the circuit description of the quantum state-preparation operator and the circuit description of the quantum search operator; for each of the plurality of circuit descriptions of the plurality of measurement quantum circuits: compiling the circuit description of the measurement quantum circuit on the quantum computer to form the measurement quantum circuit thereon; and executing the measurement quantum circuit formed on the quantum computer to obtain a measurement result associated with the measurement quantum circuit that indicates a number of times that the measurement quantum circuit produces an indication that the event is to occur; and estimating a probability of the event based on the measurement results obtained. There is also provided a corresponding system for quantum probability estimation of an event.

The application provides an agent-based power grid protection setting value matching and checking method, and relates to the technical field of power system automation. The steps of the application comprise: implementing OCR identification on a setting value single image to obtain a text sequence, and synchronously extracting protection setting values of corresponding equipment; utilizing a finite state automaton to analyze the text to generate a preliminary field-value pair, and combining state description to perform fault-tolerant reasoning by an agent to output a corrected field-value pair; executing fuzzy comparison to generate a difference list and mark an alarm level; storing difference information into a database and triggering an alarm or recording a log according to a result, so as to realize high-precision and strong-robust full-process automatic checking.

The invention discloses a finite-state agent behavior decision-making method, device and equipment, a medium and a product. The method comprises the following steps: acquiring system related information; according to the system related information, a system action graph Action-Graph is constructed, and the Action-Graph comprises nodes and edges; according to the Action-Graph, a logic mapping set is constructed, and the logic mapping set comprises an initial function set, an operation set and a dependency relationship between functions and operations; according to the logic mapping set, the Action-Graph and the task description information, an initial decision is determined, the initial decision comprises at least one of a task identifier, an operation sequence, a data dependence constraint and a cost evaluation index, through the technical scheme of the invention, an end-to-end automatic process suitable for the intelligent agent can be constructed, and the efficiency of the end-to-end automatic process is improved. And full-process automatic processing from task description of a natural language to task execution is realized.

An analysis method for investment decision-making involves, firstly, acquiring news data, invoking a custom-trained topic model to extract entities from the news data, and creating a finite state mach

The invention discloses a supervision and control method for a simulation automatic driving system based on automaton learning, which is used for solving the problems of response delay and safety guarantee in the automatic driving system, and comprises the following steps: 1) operating a simulation system to obtain historical data of an automobile; 2) discretizing historical data into an input and output track set; 3) adopting a MoreMI algorithm to construct a controlled system model; 4) constructing a system demand model; 5) converting the Moore machine into a deterministic finite state automaton; according to the method, the original system design does not need to be changed, the system can be optimized and upgraded only by adding the supervision control module, the implementation cost and the technical threshold are reduced, and safety accidents caused by response delay of the controller can be effectively prevented.

A memory testing device uses a master control unit to concurrently operate multiple, intelligent, slave control units (SCUs). SCUs have one or more processing unit(s) (i.e. Finite State Machines, micro controllers, processors) capable of processing one or more firmware with or without operating system (i.e. bare-metal, embedded OS, RTOS (real time operating system)) to perform a series of task defined by firmware(s) for testing volatile and / or non-volatile memory devices connected into one or more DUT devices plus SCU has capability of having operating system and install and run host applications locally within each SCU units to mimic host applications environments along with performing regular memory testing.

A radio-head apparatus can comprise memory to store dithering information of the apparatus. The radio-head can further include radio-head circuitry to generate a clock signal according to the dithering information and to provide a wakeup signal, subsequent to commencement of clock signal generation, to instruct a secondary RH to use the clock signal of the RH. The same wakeup signal is also used to synchronize the finite state machines of both RHs that govern and report the dithering information. Synchronization of the FSM allows estimation of information to be used in the secondary RH for compensation of the clock dithering applied in the primary RH. Other systems and apparatuses are described.

The invention discloses an FPGA (Field Programmable Gate Array)-based compressed data regular expression matching acceleration method and an FPGA-based compressed data regular expression matching acceleration device, which are characterized in that an acceleration processing mechanism is provided for a pointer unit in compressed data, so that the matching throughput rate is remarkably improved and the time delay is greatly reduced on the premise that complete decompression is not carried out. The device adopts a co-processing architecture, and a scanning module of the co-processing architecture is responsible for identifying and separating literal quantities and pointers in data streams; the deterministic finite state automaton performs conventional state transition on the literal quantity; and the verification module, the pointer data queue and the storage control module carry out equivalent state jump calculation on the pointer in parallel, and finally the matching result is integrated by the output queue. According to the method, original one-by-one matching of long data sequences is converted into single-time efficient calculation of pointers, and the matching efficiency is optimized fundamentally.