1305 results about "Computer processing" patented technology

In an approach to coordinating a conversational agent with a large language model for conversation repair, one or more computer processors receive a failure indicator from a first conversational agent. One or more computer processors retrieve a descriptive prompt associated with the first conversational agent. One or more computer processors transmit the descriptive prompt to a large language model. One or more computer processors transfer control of the failed conversation from the first conversational agent to the large language model. One or more computer processors determine the intent of the user associated with the failed conversation using the large language model. One or more computer processors determine whether the intent of the user associated with the failed conversation matches a capability of the first conversational agent. One or more computer processors transfer by one or more computer processors, the user back to the first conversational agent.

The invention discloses a multi-element historic building maintenance and restoration method based on three-dimensional laser scanning, and relates to the technical field of computer processing, and the method comprises the following steps: S01, obtaining the three-dimensional point cloud data of a historic building foundation through a ground laser scanner, the basic three-dimensional point cloud data comprises geometric information of a building facade, a ground structure and a near-ground decoration component; s02, an unmanned aerial vehicle carries a multi-line laser scanning device to scan the top and the high-altitude structure of the building, supplementary point cloud data is generated, and the millimeter-level precision three-dimensional coordinates of the pitched roof, the tower eave and the cornice bracket are covered with the supplementary point cloud data; and S03, synchronously acquiring surface texture data of the historic building by adopting multispectral imaging equipment. According to the method, the millimeter-level precision of three-dimensional reconstruction of the historic building is realized through multi-source data fusion and a hierarchical optimization algorithm, and the maintenance decision efficiency is improved by combining automatic disease recognition and a multi-modal analysis technology.

An intelligent fault-in-rail analysis method based on multimodal fusion learning. Ultrasonic analysis data of the rail and high-definition rail surface images taken by line scan cameras are exploited in combination to detect and display internal and surface faults of the rail through different renditions using multimodal data. Rail DEtection TRansformer (R-DETR) technology or a You Only Look Once (YOLO) inspection machine-learning algorithm are employed in a deep convolutional neural network to analyze B-scan and rail surface image data to recognize rail line faults. After obtaining expressive data through data enhancement by computer processing, faults are recognized and pinpointed using the deep convolutional neural network learning algorithm. Analysis results are corrected with expert systems. The disclosed automatic ultrasonic fault-in-rail inspection solves the problem of slow detection and difficulties in tracking faults in everyday routine maintenance while also protecting the safety of rail operation and maintenance personnel.

Systems, methods, and computer-readable media are disclosed for systems and methods multimodal indexing of video using machine learning. An example method may include deceiving, by a video encoder of an audio-video transformer neural network comprising one or more computer processors coupled to memory, a first frame and a second frame associated with a first segment of a video. The example method may also include receiving, by an audio encoder of the audio-video transformer neural network, an audio spectrogram comprising first audio data associated with the first segment of the video. generating, by the video encoder, a first video embedding. The example method may also include generating, by the audio encoder, a first audio embedding. The example method may also include determining a fusion of the first video embedding and the first audio embedding using a multimodal bottleneck token. The example method may also include determining an output including the first video embedding and the first audio embedding. The example method may also include determining a classification of the first portion of the video based on the output.

Apparatus and methods are described including a ventricular assist device that includes an impeller configured to be placed inside a left ventricle of a subject. A driving magnet is coupled to a motor and is rotated by the motor. A driven magnet is magnetically coupled to the driving magnet and is rotated by the driving magnet. A drive cable extends from the driven magnet and imparts rotational motion from the driven magnet to the impeller. A set of sensors is configured to detect a magnetic phase difference between the driven magnet and the driving magnet. A computer processor receives the detected magnetic phase difference and determines a physiological parameter of the subject, at least partially in response thereto. Other applications are also described.

The invention discloses a battery cell simulation type state sensing and feedback method and system, and the method comprises the steps: providing a simulation battery cell detection device which flows on a production line along with an actual battery cell; the device is provided with a shell matched with an actual battery cell in boundary dimension, a film pressure sensor covering the surface of the shell, and a built-in collector, in the circulation process, the sensor collects pressure data applied by the production line equipment in real time; the built-in collector stores data and sends the data to the upper computer processing system in a wireless mode; and the upper computer processing system receives and analyzes the pressure data, judges abnormity according to a preset pressure threshold value and generates a report. By simulating the real stress condition of the battery cell, comprehensive, real-time and automatic monitoring of the pressure state in the production process is realized, the abnormal reason can be accurately positioned, the problems of lack of monitoring means and difficulty in problem tracing in the prior art are solved, the product quality and the production efficiency are effectively improved, and the potential quality hazard is reduced.

The invention discloses a directional broadcast multi-band interference suppression method based on dynamic beam forming, and relates to the technical field of computer processing, and the method comprises the steps: S01, synchronously capturing electromagnetic signals of at least two working bands through a heterogeneous band receiving array synchronized by a hardware-level clock; s02, analyzing space parameters of a target signal and an interference source in the electromagnetic signal in real time; s03, constructing a layered adaptive codebook based on the interference dynamic parameters; s04, fusing the target signal parameter and the interference dynamic parameter by adopting a block matrix acceleration algorithm and an orthogonal decomposition technology, and calculating a beam forming weight; s05, executing operation through the multi-band coprocessor; and S06, establishing an interference source azimuth drift prediction model, and setting a trigger threshold as the coverage tolerance angle theta. According to the method, the anti-interference real-time performance is improved by utilizing layered adaptive wave beams, frequency band isolation, super-resolution multi-path identification and block decomposition.

The invention discloses an RISC-V vector register pressure-oriented dynamic management method and system, and relates to the technical field of computer processor architecture and compiler optimizing.The method comprises the steps that in the program compiling or executing process, the use state of an RISC-V vector register is monitored in real time, and when it is monitored that the vector register pressure exceeds the limit, the RISC-V vector register pressure is monitored; if yes, selecting a target register and triggering a management strategy; identifying a source instruction of a vector value in the target register, executing heavy materialization validity verification, and dividing the vector value into a heavy materialization type and a non-heavy materialization type according to a verification result; according to a division result, dynamically estimating the heavy materialization cost and the register overflow cost; comparing the two types of costs, and if the heavy material cost is higher, deciding to adopt a register overflow strategy and executing the strategy; and if the overflow cost of the register is higher, a decision is made to adopt a heavy matter strategy and is executed. The computing performance of the processor can be improved, and the problem of performance loss caused by high register pressure is solved.

The invention discloses a Shapefile automatic processing model based on a large language model and multi-agent collaboration, and relates to the technical field of computer processing, and the Shapefile automatic processing model comprises: an input layer, a user uploads a to-be-processed Shapefile and a task instruction; the processing layer is used for extracting to obtain the Shapefile and a task instruction and obtaining a processing task; the thinking decision-making layer is used for generating sub-tasks needing to be executed based on the acquired processing tasks and according to processing of a preset strategy; the execution layer is used for executing the received subtasks needing to be executed and collecting execution results to obtain feedback data; and the judgment layer is used for judging whether the current subtask needing to be executed is completed or not on the basis of the obtained feedback data. According to the method, the problems of high technical threshold, low automation level and complex interaction mode when a user processes the Shapefile are solved, the user does not need to master professional GIS knowledge or programming skills, complex Shapefile processing tasks can be completed only through natural language description, and the Shapefile operation process is remarkably simplified.

An AI-based audio compression method for use with audio formats, alone or in combination with other audio compression and enhancement approaches. A combination of audio pre-processing, sound to visual transcoding of audio, and a sequence of AI-enabled methods enabling maximal entropy order extraction applied within the sound and dimensionally extended visual domain projection of the audio significantly increases the degree of compression of audio files, thereby reducing storage, transmission and processing overhead associated with audio. A unique AI-driven domain conversion is leveraged together with domain-specific AI processing stages to reduce file size, while supporting optional use of standard and proprietary audio encoding, decoding, compression, and other methods. Support for native mode photonic computer processing of the higher-dimensional order representation of media enables further optimization via photonic computing methods that would not be possible if the audio was not extended into higher order visual domain space.

The disclosed system for interacting with objects in an extended reality (XR) environment generated by an XR system may include (1) neuromuscular sensors configured to sense neuromuscular signals from a wrist of a user and (2) at least one computer processor programmed to (a) determine, based at least in part on the sensed neuromuscular signals, information relating to an interaction of the user with an object in the XR environment and (b) instruct the XR system to, based on the determined information relating to the interaction of the user with the object, augment the interaction of the user with the object in the XR environment. Other embodiments of this aspect include corresponding apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

The present disclosure relates to systems and methods for determining comprehensive and asset vulnerability ratings using models such as artificial intelligence (AI) and machine learning (ML) models. These models can identify relevant attributes, optimize attribute values, and determine logical relationships between attributes. The term “model” encompasses various types of AI and ML models, including neural networks, language models, multimodal models, and others. Models can be trained using supervised learning with labeled data to predict or classify new data items. The models can be locally hosted, cloud-managed, or accessed via APIs, and can be implemented in electronic hardware such as computer processors.

Methods and systems for water quality assessment are disclosed. The method includes obtaining a first input data indicative of properties of a first liquid sample, the first input data including turbidity data and total suspended solids data for the first liquid sample, where the first liquid sample is acquired from a liquid source. The method further includes determining, using a computer processor and a machine learning model, a first predicted particle-size distribution of the first liquid sample based on the first input data, where particle-size distribution is controlled, at least in part, by a set of dosage parameters configurable by a water quality system. The method further includes determining, with an optimizer applied to the machine learning model, an optimal set of dosage parameters based on the first predicted particle-size distribution and adjusting the set of dosage parameters of the water quality system to the optimal set of dosage parameters.

The present disclosure generally relates to a monitoring device (100) for remotely monitoring health of a young livestock animal (10), the device (100) comprising: an elongated body (110) within predefined dimensional limits; and a set of electronic components housed within the elongated body (110), the electronic components comprising: a temperature sensor for measuring body temperature of the young livestock animal (10); a computer processor for processing the measured temperature into temperature data; and a wireless communications component for transmitting the temperature data to a remote computer device (210) for processing to monitor the health of the young livestock animal (10), wherein the predefined dimensional limits of the elongated body (110) enable the monitoring device (100) to be orally administrable into the young livestock animal (10) and to remain inside its stomach (12) without being excreted.

The invention provides a multi-system redundant computer processing method and system and electronic equipment, and belongs to the technical field of computers, and the method comprises the following steps: S101, obtaining eight different nodes; s102, establishing a communication channel, encrypting the communication channel, and establishing an on-off channel; s103, acquiring a task feature vector, acquiring a resource feature vector, performing a dynamic clone selection algorithm, acquiring an optimal resource scheduling scheme, and performing resource scheduling; s104, detecting the computer computing node and the computer total node, and if any one node fails, starting a redundancy switching mechanism; s105, the real-time resource use condition of each computer computing node is monitored in real time, and when the load of at least one computer computing node reaches 85%, a redundant resource scheduling mechanism is started; s106, during operation, recording the related information in real time by the backup database; according to the method, resource allocation is more reasonable, and the data processing speed is increased.

Chromatic dispersion compensation is performed in one or more pluggable optical transceiver (POT) devices operating within an intensity-modulated direct-detection (IMDD) optical network. Compensation is performed within each POT using an electrical and / or optical chromatic dispersion module which are controlled by a set of parameters. A network computing device includes a computer processor and a host management interface for communicating with the POT. In the event of a link failure, the computer processor determines a second set of parameters to control the one or more dispersion compensation module(s) of the POT. The second set of parameters are different from a first set of parameters used to control the one or more compensation module(s) in the case of a first optical path. The computer processor causes the POT to use the second set of parameters in place of the first set of parameters.

The invention discloses a low-code automatic generation method based on AI agent collaboration, and relates to the technical field of computer processing, and the method comprises the following steps: S1, receiving a function demand description text input by a user through a natural language; s2, an input analysis agent reads and analyzes the function requirement description text, key information is extracted, and the key information comprises a key intention, an entity object and an operation constraint condition; s3, performing semantic similarity matching in a predefined model library by a model retrieval agent according to the key information, and retrieving and defining a basic generation model with closest semantics; and S4, receiving the basic generation model and the key information by an adaptive modification agent, and performing context semantic understanding enhancement on the basic generation model. According to the method, end-to-end automatic conversion from business demand description to executable codes is realized through natural language understanding and an automatic code generation technology.

The invention discloses an intelligent identification and management system and method for key commodities of a vegetable basket, and relates to the technical field of computer processing, and the system comprises a multi-modal data collection and preprocessing module which is used for collecting commodity images, temperature and humidity curves, vibration frequencies and electronic quality inspection reports through Internet of Things equipment, the block chain technology is adopted to encrypt and store production batches and detection values; and the intelligent labeling and label generation module is used for performing instance segmentation on the commodity image, analyzing semantic information of the quality inspection report and generating a multi-level quality label. According to the invention, through a multi-modal data fusion and dynamic association analysis technology, image recognition, sensor data and text analysis are integrated, an intelligent supervision system covering a production-retail full link is constructed, and on the basis of an adversarial training mechanism and an edge cloud collaborative architecture, the production-retail full link is completely supervised. The real-time identification capability of complicated illegal behaviors such as water-injected meat, pesticide residue exceeding and label tampering is obviously improved, and the whole-process safety guarantee of livelihood commodities is enhanced.

A system for registering position and orientation (P&O) of mobile devices relative to a construction site may include: a light projector; at least one sensor configured to record at least one set of XYZ coordinates of at least one specific surface, and a set of XYZ coordinates of the light projector within the construction site; and a computer processor, wherein the light projector is configured to project the XYZ coordinates of the at least one set of position markers onto the at least one specific surface; and wherein the projection of the XYZ coordinates of the at least one set of position markers is detectable by at least one sensor located at a mobile device, allowing registration of XYZ coordinates of a virtual reality interface of the mobile device relative to the projection of the position markers onto the at least one specific surface.

The invention relates to the technical field of computer processing, in particular to a Kafka cluster configuration parameter adjusting method and device, equipment and a medium, and is used for relieving problems caused by a fixed change means of code modification. The method comprises the following steps: according to related historical data of a Kafka cluster, predicting a first predicted load index in a future time period through a first time sequence model, and predicting a second predicted load index in the future time period through a second time sequence model; weighting the first predicted load indicator; weighting the second predicted load index; determining a predicted load index according to the weighted first predicted load index and the weighted second predicted load index; determining a plurality of first candidate adjustment actions according to the predicted load index; selecting a first candidate adjustment action from the plurality of first candidate adjustment actions as a first adjustment action; and adjusting a partition allocation index and a copy allocation index of the Kafka cluster configuration parameters by using the first adjustment action.

Exemplary artificial intelligence (AI) systems, methods and computer-accessible medium can be provided for detecting a breast cancer using mammography. For example, using at least one computer processor, it is possible to receive a mammography image, apply a neural network employing, e.g., a You Only Look Once X (YOLOX) architecture to predict one or more locations and probabilities of lesions. Further, with such exemplary systems, methods and computer-accessible medium, it is possible to make an overall image-level prediction for the received mammography image so as to provide a particular breast cancer prediction. It is also possible to generate breast-level predictions by averaging all predictions from FFDM, C-View, DBT modalities for each breast. For example, when used in clinical decision support, the exemplary model can reduce radiologist workload by, e.g., about 45% and unnecessary recalls by, e.g., about 32.4%, without missing malignancies.

The invention provides a measurement system for the waviness of a neutron conduit. The measurement system comprises a high-precision granite guide rail, a total station, an auto-collimation eyepiece, a computer and a measurement auxiliary assembly. The high-precision granite guide rail provides a stable sliding reference, the total station slides along the high-precision granite guide rail for measurement, the auto-collimation eyepiece is matched with the normal direction of the measurement conduit, and the computer processes data. The system can adapt to measurement requirements of neutron conduits in different geometrical shapes, and the waviness is calculated through a preset formula, and the assembly precision of multiple sections of conduits and the influence on neutron reflection are evaluated; the measurement auxiliary assembly and the jack ensure stable measurement. The system is high in measurement precision, strong in universality, efficient in data processing, good in stability, simple and convenient to operate and capable of guiding design and manufacturing of neutron conduits, reducing production cost and improving neutron flux and experiment accuracy and reliability.

A system, method, and computer-program product includes obtaining, via an application programming interface (API), a test object that includes application usage data of a deployed AI application for a target time span, executing, in real-time by one or more computer processors, one or more application behavior tests that assess an operational behavior of the deployed AI application, detecting, by the one or more computer processors, that a misbehavior occurred in the deployed AI application during the target time span and one or more deviant features contributing to the misbehavior in response to executing the one or more application behavior tests, and returning, by the one or more computer processors, the one or more deviant features contributing to the misbehavior to a subscribing entity associated with the deployed AI application.

A method for safety management and risk assessment in a work environment. The method includes obtaining data from a plurality of sources. The method further includes preprocessing, using a computer processor, the obtained data, where the preprocessing includes cleaning and normalizing the obtained data. The method further includes determining, using the computer processor and a machine learning model, a plurality of predictive variables based on the preprocessed data. The method further includes determining, using the computer processor and the machine learning model, risk exposure prioritization score based on the plurality of predictive variables. The method further includes determining, using the computer processor and the machine learning model, a plurality of safety recommendations based on the risk exposure prioritization score. The method further includes performing, in response to the safety recommendations and the risk exposure prioritization score, a maintenance operation on an equipment in the work environment.

Apparatus and methods are described for use with a bodily emission of a subject that is disposed within a toilet bowl. While the bodily emission is disposed within the toilet bowl, light is received from the toilet bowl using one or more light sensors. Using a computer processor, intensities of at least two spectral bands that are within a range of 530 nm to 785 nm are determined, by analyzing the received light, and a ratio of the intensities of the two spectral bands is determined. In response thereto, the computer processor determines that there is a presence of blood within the bodily emission. The computer processor generates an output on an output device, at least partially in response thereto. Other applications are also described.

The invention discloses a river water level detection method, and relates to the technical field of computer processing, and the method comprises the following steps: S01, presetting a distributed pressure sensor array in each target collection region to obtain underwater pressure data k and real-time water flow data v of a plurality of target collection regions of a river to be detected; s02, establishing a dynamic pressure water level model based on the water flow direction pressure conduction quantity estimation of the plurality of target acquisition areas in combination with real-time water flow velocity and wave period parameters; s03, performing signal attenuation compensation on the underwater pressure data according to the dynamic pressure water level model to obtain initial water level data; s04, multi-source data fusion calibration is carried out on the preliminary water level data, a river water level detection result is generated, and the result comprises a wave height frequency spectrum and a water level change curve after peak elimination correction; and S05, generating a wave energy spectral density map according to the calibrated water level data, performing real-time comparison according to the wave energy spectral density map and a preset threshold value, and performing result return according to a comparison structure. The small-wave-height short-period wave measurement precision and the water level detection reliability are remarkably improved, the intelligent flood prevention early warning and dynamic adjusting capacity is achieved, and it is guaranteed that data collection is accurate and consistent.

Apparatus and methods are described for use with a bodily emission of a subject that is disposed within a toilet bowl. One or more light sensors are configured to receive light from the toilet bowl, while the bodily emission is disposed within the toilet bowl. A computer processor detects a set of three or more spectral components that have a characteristic relationship with each other in a light spectrum of a microorganism, by analyzing the received light, and determines that there is a presence of the microorganism within the bodily emission in response thereto. Other applications are also described.

The invention relates to the technical field of computer processing, in particular to a learning strategy generation method, electronic equipment and a storage medium, and the method comprises the steps: obtaining an evaluation result after a target user completes individual ability evaluation; performing multi-modal interpretation processing on the evaluation result, and determining an interpretation video of the evaluation result; the interpretation content of the interpretation video comprises knowledge point mastering condition information of the target user, capability condition information of each evaluation dimension, subject potential prediction information and occupational prediction information; and matching the ability condition information of the target user under each evaluation dimension with the content label of the learning content in the learning resource library to generate a learning strategy. According to the method, the interpretation video with the multi-dimensional interpretation content is provided, the understandability of the user to the evaluation result can be improved, meanwhile, the personalized learning strategy is given, the evaluation result is converted into the action scheme, and the quality of learning development guidance can be improved.

The invention discloses a digital twinning three-dimensional model dynamic synthesis system based on multi-modal feature fusion, and belongs to the technical field of digital twinning, computer processing and three-dimensional reconstruction crossing. Data flow characteristics are divided into high-frequency real-time data flow in a machine tool running state and low-frequency / event triggering data in a machine tool static state, a specific processing fusion path is intelligently selected based on a self-adaptive double-path processing mechanism, a state parameter set for driving a three-dimensional basic model is generated, and the three-dimensional basic model is obtained. The method not only optimizes the dynamic synchronization and prediction of the operation state, but also achieves the modeling and tracking of the static state (such as cooling recovery, maintenance calibration and environmental evolution) of the machine tool, constructs a digital twin system covering the whole scene of operation-shutdown-maintenance of the numerical control machine tool, and supports the real whole life cycle management.