33 results about "Pattern sequence" patented technology

The invention provides a synchronous sampling type single-pixel imaging system and image reconstruction method based on DLP projection, and the method comprises the steps: constructing an orthogonal coding pattern sequence based on a pattern library, dividing the coding pattern sequence into different pattern segments, each pattern segment comprising at least one frame of pattern, and distributing a pattern number for each pattern; loading the coding pattern sequence to a DLP control module, and projecting the coding pattern sequence to a target object; starting a data acquisition card through a trigger signal to perform integral sampling on a light intensity signal acquired by a photoelectric detector to obtain an effective light intensity value corresponding to the pattern number; according to the collected pattern number and the corresponding light intensity value, estimating sampling energy distribution of each region of the pattern; identifying a low coverage area with energy lower than a threshold value, and generating a pattern rescheduling set; and carrying out fusion averaging on the repeatedly sampled pattern light intensity values, giving a higher weight to the sampling value of the corresponding pattern, and reconstructing a target pattern through a weighted back projection algorithm.

The invention relates to the technical field of intelligent lighting and voice interaction, in particular to a lamplight rhythm control system and method based on voice interaction, and the method comprises the steps: carrying out the analysis and feature extraction of a collected voice signal, and constructing a dynamic model which depicts the vortex core strength and position evolution of a sound field; an acoustic vortex sequence extracted based on the model is converted into an acoustic pattern sequence with space ductility through a pre-trained generative adversarial network. And carrying out space-time folding transformation on the pattern sequence to generate a high-dimensional acoustic instruction code so as to drive a lamplight array to present complex space rhythms associated with the dynamic depth of the voice. According to the method, the limitation of direct mapping of traditional audio visualization is broken through, intelligent generation and nonlinear mapping from a voice dynamic structure to light space art are realized, and the expressive force and immersion of acousto-optic interaction are improved.

The invention relates to the technical field of industrial vision, in particular to a building structure crack recognition method and system based on image analysis, and the method comprises the following steps: projecting a preset coding pattern sequence to the surface of a building structure, and collecting and obtaining a distortion pattern image set, and coding information in the distortion pattern image set is decoded pixel by pixel and triangulation positioning calculation is carried out. According to the method, the coding pattern is projected on the surface of the building structure, the distorted image is synchronously acquired, triangulation positioning calculation is performed after pixel-by-pixel decoding, three-dimensional surface point cloud data with complete details can be generated, a two-dimensional crack grayscale image with uniform illumination is acquired, crack feature missing caused by single-dimensional information is avoided, and the accuracy of crack feature detection is improved. A normal vector and a maximum principal curvature value are calculated based on the three-dimensional surface point cloud data, a threshold value is set to screen a high-change area, and crack points and background points are effectively distinguished, so that the three-dimensional geometrical morphology of the crack can be accurately separated and reserved.

A mode sequencer circuitry for a time-of-flight system, the time-of-flight system including at least an imaging unit and an illumination unit, the imaging unit having a data bus interface for transmitting data to an application processor over a data bus.

The invention relates to the technical field of assisted reproduction health management, and discloses an assisted reproduction management method and system. The method comprises the steps that physiological data of multi-source monitoring equipment is received and subjected to standardization processing, and a multi-dimensional feature matrix is formed through time sequence alignment and feature fusion; identifying a dynamic evolution track of the key physiological mode by utilizing a mode clustering and sliding window technology; performing state deduction on the mode sequence based on the personalized model, and predicting a future physiological state; generating a regulation and control strategy sequence according to the difference between the prediction and the target, and executing the instruction; physiological response data is collected in real time and compared with an expected model, a follow-up strategy is dynamically adjusted, and closed-loop optimization is formed; and finally evaluating path validity and updating model parameters according to complete cycle data. According to the method, continuous accurate prediction and individualized self-adaptive regulation and control of the reproductive physiological state are realized, and the management accuracy and efficiency are improved.

Provided are computer-implemented methods for generating embeddings for objects which may include receiving heterogeneous network data associated with a plurality of objects in a heterogeneous network; selecting at least one pattern of objects; determining instances of each pattern of objects based on the heterogeneous network data; generating a pattern matrix for each pattern of objects based on the instances of the pattern of objects; generating pattern sequence data associated with a portion of each pattern matrix; generating network sequence data associated with a portion of the heterogeneous network data; and combining the pattern sequence data and the network sequence data into combined sequence data. In some non-limiting embodiments or aspects, methods may include generating a vector for each object of the plurality of objects based on the combined sequence data. Systems and computer program products are also provided.

The invention discloses a signal sorting method and device based on multi-hypothesis tracking, and a storage medium, and relates to the technical field of radar signal processing. The method comprises the following steps: acquiring a pulse TOA sequence, and calculating a PRI candidate value set; searching an effective initial pulse pair in the TOA sequence, and creating an initial tracking hypothesis for the effective initial pulse pair; aiming at the initial tracking hypothesis, searching the next matched pulse; if the matched pulse is found, judging whether the currently used PRI value is consistent with the PRI value of the initial tracking hypothesis or not: if so, updating the initial tracking hypothesis; if not, creating a new branch hypothesis; fusing and pruning all tracking hypotheses at regular intervals; confirming the tracking hypothesis meeting the output condition as a sorted radar pulse sequence, and outputting the sorted pulse sequence and a corresponding PRI change mode sequence; and repeating the steps in sequence for the residual pulse sequence which is not sorted until the sorting ending condition is met. According to the invention, the reliability of PRI sorting is improved.

The application discloses a kind of both can guarantee calculation real-time, and can realize the high-fidelity restoration of missing link working condition flow power consumption settlement method, device, equipment and medium, wherein method includes: receiving the electric meter data message sent by edge computing node;According to the time zone of electric meter, the timestamp of energy consumption cumulative indication value is uniformly converted into logical local time, and maximum tolerance disorder time is determined based on network delay fluctuation in data message upload process to construct flow water level line, and flow water level line is used to drive the flow settlement of statistical window;Based on instantaneous power feature vector, load fingerprint library of electric meter is generated using clustering algorithm, and the load fingerprint library includes various load fingerprint patterns and their corresponding reference values;After detecting that electric meter is missing and recovered, extract the instantaneous power feature vector before and after missing, deduce the load fingerprint pattern sequence during missing period in combination with load fingerprint library, and restore the power increment generated during missing period to the corresponding each statistical window in missing period.

A fencing training system delivers programmable visual cues to simulate referee commands and tactical bout scenarios. It includes a transparent panel (11) with addressable LED lights (10), mounted on a tripod (12) and controlled by a microcontroller (14). Timed color and pattern sequences prompt fencers to initiate offensive, defensive, or interpretive actions. Users can customize delay intervals, cue types, and repetition frequency. The system improves timing accuracy, footwork consistency, and decision-making within the four-meter engagement zone. Configurable preparation windows and distance markers (20, 22, 24) aid spatial judgment. The system is adaptable for saber and foil fencing and may include auditory cues, motion detection, or mobile app control. Designed for portability and real-time responsiveness, it supports solo and group training. The invention may also be adapted for other sports requiring timed decision-making in confined spaces and incorporate AI-based customization using bout performance data to personalize footwork timing and cue sequences.

The application relates to a structured light 3D camera system and a measurement method based on FPGA heterogeneous computing, wherein the system comprises a projection module for projecting a structured light coding pattern sequence containing multiple frames of patterns; a collection module for collecting a structured light coding pattern sequence modulated by a target object and outputting the structured light coding pattern sequence in a preset format; and a processing chip module for generating a phase diagram of the target object by pipeline processing of the structured light coding pattern sequence through each hardware acceleration processing pipeline in an FPGA programmable logic unit and sending the phase diagram to an external host through Ethernet to perform three-dimensional modeling of the target object. Through the application, pipeline processing of the structured light coding pattern based on the FPGA hardware acceleration processing pipeline is realized, the time consumption of three-dimensional reconstruction is greatly reduced, edge computing on the camera system is realized, and the problem of how to improve the calculation real-time performance of three-dimensional reconstruction is solved.

Broad spectrum metrology for various metrology marker types is described. The systems and methods utilize a modulator, such as a spatial light modulator (SLM). The alignment mark is projected onto the SLM through the imaging lens. A pattern sequence on the SLM modulates the incoming image and all reflected energy collected by a collection lens, and a time-varying signal may be generated from a single detector or array of detectors. Color demultiplexers may be added to separate the signals at different wavelengths and direct them to respective detectors to allow for simultaneous multi-color measurements. The alignment mark may be irradiated in a static or scanning mode. The combination of the varying mark positions and SLM patterns allows various signals to be generated for alignment position measurements. Moreover, the SLM may readily accommodate the size of a region of interest and the marker.

The invention relates to the technical field of image communication, and discloses a performance test method and system for a wireless image transmission module, and the method comprises the steps: firstly, obtaining a target image of the wireless transmission module, constructing a test link comprising a transmitting unit, a receiving unit and a channel simulator, configuring a standard pattern sequence of the transmitting unit, acquiring a decoded image sequence output by the receiving unit, and extracting a synchronous mark frame to calculate unit transmission delay; the method comprises the following steps: identifying interference elements of a channel simulator, analyzing an interference intensity index, calculating a decoding effect value of a target image, constructing a transmission performance matrix based on a standard pattern sequence, time delay and the decoding effect value, identifying a critical state point, reconstructing a load test process according to the critical state point, and configuring a coding rate and a modulation order. And carrying out image performance test on the module to finally obtain a performance test result. According to the invention, the actual transmission performance of the wireless image transmission module can be detected.

The application provides a data center machine room operation and maintenance anomaly detection method based on deep learning, comprising: for a low-dimensional feature set, using a long short-term memory network to analyze time series and capture subtle patterns in low-dimensional dynamic characteristics to obtain a behavior pattern sequence; extracting packet structure and time delay changes from an abnormal candidate set, using an isolation forest algorithm for secondary screening to determine a hidden abnormal behavior set; according to the abnormal pattern set, using a sliding window mechanism to analyze real-time data streams to determine whether abnormal patterns continue to appear to obtain an abnormal persistence score; according to the final abnormal detection result, updating the parameters of the behavior benchmark model, using an online learning mechanism to optimize the model to obtain an updated behavior benchmark model; for the updated behavior benchmark model, cyclically executing real-time data stream analysis to continuously capture subtle patterns to obtain continuous abnormal detection output.

This invention relates to the technical field of industrial equipment monitoring, specifically to a method for monitoring the operation of an MVR evaporator used in industrial wastewater treatment. This method is immune to amplitude interference under normal operating conditions and can dynamically fuse waveform patterns from multiple sensors. The method includes: S1, obtaining a normalized pattern sequence for each sensor; S2, calculating the pattern offset score between the normalized pattern sequence and its corresponding healthy pattern template; S3, weighted fusing the pattern offset scores of each sensor based on dynamic sensitivity weights to obtain an adaptive blockage index; and S4, analyzing the continuous offset trend of the adaptive blockage index relative to a preset healthy baseline using a cumulative sum control chart to monitor the operating status of the MVR evaporator. This invention improves the monitoring sensitivity and decision reliability for early-stage collaborative anomalies related to blockage.

The application discloses a radar working mode recognition method and device based on a predicted state representation, comprising the following steps: training a probability model in advance by using a statistical method; sequentially searching for possible working mode transition probabilities of each time step from the probability model according to known states and known modes, and calculating transition path lengths; determining the shortest path of mode transition and the corresponding path value in the entire time sliding window according to the possible mode transition probabilities of each time step and the corresponding mode transition path lengths; recording the above results, moving the sliding window down by one time step, and repeating the above process; and voting to determine the optimal mode recognition result of each time step according to the voting result. The application estimates the mode value of each time step by searching for the maximum a posteriori probability of the mode sequence under the condition of the known state sequence, and adjusts and optimizes the recognition effect by comparing the recognition results in different sliding windows.

A transmission system includes a calculation unit that calculates a jitter pattern sequence of a plurality of packets transmitted by a transmission device via a network using a transmission interval of the plurality of packets and a difference between arrival times at which the packets arrive at a reception device, a generation unit that inputs the jitter pattern sequence to a first learning model to generate a state index indicating a state of the network, and a buffer estimation unit that determines a buffer size of a reception buffer of the reception device based on the state index.

This invention provides a simulation-based method for predicting the load-bearing capacity of a conical sleeve, comprising: a parameter modeling agent reading the structural, material, and loading parameters of the conical sleeve connection joint, and establishing a load-bearing simulation model including the reinforcement load-bearing domain, grouting force transmission domain, sleeve constraint domain, first interface contact relationship, and second interface contact relationship; a conversion calculation agent extracting the axial displacement sequence, radial constraint pressure sequence, and interface slip sequence based on the load-bearing simulation model, calculating the radial constraint conversion efficiency, and establishing a digital constraint valve model; a constraint identification agent identifying the constraint opening position, peak constraint position, and constraint fallback position, and generating a set of effective constraint state intervals; a load-bearing deduction agent calculating the joint load-bearing capacity and determining the failure mode sequence, critical loading step, and force transmission state; and a prediction correction agent outputting the predicted load-bearing capacity, safe constraint interval, and parameter correction results.

The invention discloses a deep learning-based turbid water body holographic turbulence field three-dimensional reconstruction method and system, and relates to the technical field of underwater optical imaging, and the method comprises the steps: irradiating a turbid water body through a holographic light path, and driving a camera to capture a transient holographic interferogram sequence; denoising by adopting a noise suppression model, and outputting an optimized hologram; positioning particles through a cascade convolutional neural network to generate an initial plane coordinate set; calculating the axial depth of the particles to obtain a transient space coordinate set; space-time diagram association is executed, and a three-dimensional particle field dynamic sequence is generated; and executing flow field inversion to generate a three-dimensional transient turbulence velocity field. The technical problem that a traditional image-based three-dimensional reconstruction method is difficult to overcome the defects of strong holographic image noise and particle signal distortion in a turbid water body scene is solved, interference caused by turbid water body scattering is effectively resisted, key data needed by turbulent flow field three-dimensional reconstruction are comprehensively and accurately obtained, and the reconstruction efficiency is improved. Therefore, the technical effect of three-dimensional reconstruction of the turbulent flow field of the turbid water body is accurately realized.

A method for constructing a large prediction model of coal burst based on multimodal data is provided. The method includes: constructing a multimodal data set by collecting data from different modalities; preprocessing the multimodal data set to construct precursor pattern sequences; and converting, according to features of different mining areas, each precursor pattern sequence into a corresponding grade form to assign a corresponding risk grade label of coal burst; processing graded precursor pattern sequences by using Transformer to predict an occurrence probability of risk grade of coal burst; evaluating, by using a comprehensive index method, risk degrees of mining information data and geological structure data, and evaluating an overall risk grade of coal burst comprehensively by combining the prediction result output by the coal burst prediction module. The method can improve applicability and prediction accuracy of the model under different mining conditions, and achieve accurate prediction of coal burst risks.

This application relates to the field of printing equipment condition monitoring technology, and discloses a method and system for monitoring and fault early warning of the rotational state of printing rollers. By collecting vibration and temperature data of the printing rollers, a time series decomposition algorithm is used to separate short-term fluctuations and long-term trends to obtain a trend sequence; the slope change of the trend sequence is calculated, and deterioration signs are captured by combining signal strength and duration, generating a slope growth pattern sequence; positive growth portions are identified and potential deterioration tendencies exceeding duration thresholds are marked, forming a labeling sequence; the deviation between cluster centers and normal ranges is calculated through cluster analysis to obtain a deviation degree sequence; the deviation values ​​are compared with thresholds to generate a candidate fault signal set; finally, a fault progression feature model is matched to determine and confirm the fault signal set. This application can effectively capture early abnormal trends of the rollers, improve the accuracy of fault judgment, and is suitable for online condition monitoring and intelligent early warning of printing equipment, realizing fault prediction and health management of the equipment.

The invention discloses an energy data analysis method and system based on big data, and relates to the technical field of data analysis, and the method comprises the steps: obtaining the energy collection point data of a plurality of energy utilization systems in different operation regions in a coal mine enterprise, and building an energy collection node library; performing system division and operation area mapping on the node library data, and generating an energy consumption distribution table divided according to a time sequence and a system category; calculating an energy consumption correlation coefficient between energy consumption systems and an energy consumption ratio between the system and an operation area based on the distribution table, constructing an energy consumption relation topological graph, mapping the energy consumption relation topological graph into an energy operation matrix, and arranging typical energy consumption combinations and mode sequences to form an energy mode library; real-time energy data is acquired, preprocessed and mapped to a pattern library, matching is performed node by node according to a pattern sequence and a typical energy consumption combination, an energy pattern matching table and an analysis report are generated and stored in a database, structured analysis and modeled monitoring of multi-system and multi-region energy consumption are achieved, and abnormity discovery and optimization management are facilitated.

The invention discloses a slope flexible surface layer failure self-adaptive diagnosis system, and relates to the technical field of self-adaptive detection, and the system comprises a data collection unit which builds a three-dimensional constraint graph through setting an acceleration collection point at the anchor head of each anchor rod and setting a strain collection point at the geometric center of each grid unit; the constraint iteration sparse diagnosis unit is used for detecting an impact event in an acceleration sequence and a deformation event in a strain sequence on the established three-dimensional constraint graph for each time slice, judging a pull-out type, a stripping type, a tension fracture type or a slippage type failure mode, calculating a mismatch index and generating a failure mode sequence; and the alarm mapping unit is used for mapping according to the calculated mismatch index and the generated failure mode sequence to obtain an alarm level, and generating a protection action suggestion set including anchoring encryption, grid reinforcement, root dredging and drainage optimization. According to the invention, an efficient, reliable and landing technical support is provided for long-term stable and safe operation of the side slope.

The application belongs to the technical field of land change degree analysis methods, and particularly relates to a land change degree analysis method and system based on space-time data, which comprises the following steps: acquiring multi-temporal remote sensing data of a space monitoring unit and extracting time sequence characteristics; constructing a preliminary time similarity pair set based on the similarity between time sequence characteristic analysis units; constructing a space connection relationship graph by using a graph theory method, and identifying a candidate change group; performing spatial clustering analysis on the candidate group, and screening a group with strong internal connectivity; performing time sequence consistency analysis on the screened group, and fusing interannual change characteristics to generate a space-time comprehensive homogeneity score to determine a homogenous change region; identifying a dominant change mode sequence of each homogenous region and classifying the evolution law thereof; and finally performing grouping optimization based on the evolution law type. The application solves the problem of time-space fragmentation and difficulty in accurately identifying homogenous change regions in traditional methods, and realizes high-precision automatic identification and law interpretation of change regions.

The embodiment of the invention provides a test method, test equipment, a test device and a storage medium, which are applied to the technical field of communication and are used for efficiently evaluating signal quality. The test method comprises the following steps: receiving a test signal sent by a to-be-tested object; the test signal is a periodic signal of any code pattern; obtaining a code pattern sequence of the test signal based on the period information of the test signal; and outputting a test result based on the code pattern sequence, the test result is used for representing the signal transmission quality of the to-be-tested object.

This application relates to the field of image imaging, and more particularly to a single-pixel imaging method, apparatus, device, and storage medium. It involves acquiring pre-codified pattern sequences and performing pre-codified modulation on the object to be imaged to obtain pre-codified bucket detection measurement data. Based on the pre-codified bucket detection measurement data, the spatial information distribution of the object to be imaged is determined, and a sampling weight map and a reconstruction weight map are generated according to the spatial information distribution. Based on the sampling weight map, subsequent coding modulation is performed on the object to be imaged to obtain subsequent bucket detection measurement data. Image reconstruction is performed based on the pre-codified bucket detection measurement data, subsequent bucket detection measurement data, and the reconstruction weight map to obtain the imaging result of the object to be imaged. This application uses two types of bucket detection measurement data for image reconstruction, enabling the allocation of measurement resources and the adjustment of reconstruction constraints to complement each other. Under a limited single-pixel measurement budget, this improves the reconstruction quality of high-information areas and reduces noise and artifacts in low-information areas.

A multichip package having a main die coupled to one or more daughter dies is provided. The main die may include embedded universal interface blocks (UIB) each of which can be used to interface with a corresponding daughter die to support high bandwidth parallel or serial communications. Each UIB may include an integrated processor subsystem and associated pattern sequencing logic to perform interface initialization and margining operations. Each UIB may perform simultaneous accesses to a daughter die across one or more channels. Each UIB may also include multiple phase-locked loop circuits for providing different clock signals to different portions of the UIB and a 2× clock phase generation logic. Each UIB may include multiple IO modules, each of which may optionally include its own duty cycle correction circuit. Each IO module may include buffer circuits, each of which may have a de-emphasis control logic for adjusting buffer drive strength.

The present application belongs to the technical field of computational biology, and particularly relates to a protein surface multi-level modular representation method and an interaction interface prediction method. First, a protein manifold triangle mesh containing multi-modal physical and chemical characteristics is constructed. Then, based on the geodesic distance and local density field, the continuous surface is discretized into geometrically compact virtual residues using a restricted region growing algorithm. Next, an improved soft subspace clustering is used to mine atom patterns with specific functions, and a graph-guided manifold autoencoder is introduced to map them into high-dimensional embedding vectors. On this basis, a compatibility network is constructed by fusing statistical, semantic and physicochemical characteristics, frequent sub-patterns are mined, and the surface is resolved into a structured sub-pattern sequence. Finally, a graph neural network model is constructed for PPI prediction, and the prediction area is resolved into core modules and variable modules. The present application uses a unique four-level hierarchical structure and manifold geometry calculation to solve the problems of weak geometric perception and lack of interpretability in the prior art.

The invention relates to a structured light 3D camera system based on FPGA heterogeneous calculation and a measurement method, and the system comprises a projection module which is used for projecting a structured light coding pattern sequence comprising a plurality of frames of patterns; the acquisition module is used for acquiring the structured light coding pattern sequence modulated by the target object and outputting the structured light coding pattern sequence in a preset format; and the processing chip module is used for carrying out pipeline processing on the structured light coding pattern sequence through each hardware acceleration processing pipeline in the FPGA programmable logic unit, generating a phase diagram of the target object, and sending the phase diagram to an external host through the Ethernet to execute three-dimensional modeling of the target object. According to the method and the device, the assembly line processing of the structured light coding pattern based on the FPGA hardware acceleration processing pipeline is realized, the time consumption of three-dimensional reconstruction is greatly reduced, the edge calculation on a camera system is realized, and the problem of how to improve the calculation real-time performance of the three-dimensional reconstruction is solved.

The invention discloses an adit water level intelligent inspection and decision analysis system based on edge calculation, and the system comprises a water level sensing module which is used for generating original water level time sequence data; the edge data preprocessing module executes preprocessing to obtain an aligned water level sequence; the water level operation state construction module is used for calculating a water level operation state sequence; the power mode modeling module is used for establishing a switching linear power system and configuring a state transition relation and an observation mapping relation; the power mode recognition module is used for generating a power mode sequence, a mode confidence coefficient sequence and an observation residual error sequence; the event triggering constraint module is used for generating a power mode sequence after constraint updating; the risk level evaluation module is used for calculating a risk level; and the processing strategy and cloud edge collaborative updating module is used for generating an instruction and updating and switching the linear power system through the cloud. Intelligent adit water level inspection and risk decision making are achieved based on the edge side switching linear power system, and the method has the advantages of being accurate in recognition, low in misjudgment rate and timely in response.

The application provides a synchronous sampling type single-pixel imaging system and an image reconstruction method based on DLP projection, and the method comprises the following steps: constructing an orthogonal coding pattern sequence based on a pattern library, dividing the coding pattern sequence into different pattern sections, each pattern section containing at least one frame of pattern, and assigning a pattern number to each pattern; loading the coding pattern sequence to a DLP control module and projecting to a target object; starting the integration sampling of the light intensity signal collected by a photoelectric detector by a trigger signal to obtain an effective light intensity value corresponding to the pattern number; estimating the sampling energy distribution of each region of the pattern according to the collected pattern number and the corresponding light intensity value; identifying a low coverage region with energy lower than a threshold value to generate a pattern rescheduling set; fusing and averaging the light intensity values of the repeatedly sampled patterns, giving a higher weight to the sampling values of the corresponding patterns, and reconstructing the target pattern by a weighted back projection algorithm.