1713 results about "Computer processing" patented technology

A computing system may include non-transitory computer-readable media storing instructions that when executed by the one or more computer processors, causes the computing system to perform operations comprising: causing presentation of a graphical user interface, the graphical user interface being associated with patient health data, wherein the graphical user interface is configured to: display one or more user interface elements, receive information identifying a logging action and at least one classification associated with the logging action, generate, by the processor, one or more models based on the received information, based on the generated one or more models, automatically associate the one or more user interface elements with one or more logging actions and update the graphical user interface with at least a portion of the one or more user interface elements.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The present disclosure provides a system for secure compute using artificial intelligence agents. The system includes a hardware execution environment with one or more computerized processors and electronic storage media. The processors are configured to establish a secure agent comprising a secure state management module, an encrypted state transition management module, a threshold cryptography implementation, and a digital signature verification module. The system also includes a plurality of atomic agents, each configured to perform a composite task and comprising a task-specific execution module, a state management interface, and a communication module. An orchestrator agent coordinates secure execution of the atomic agents and includes a task distribution module, a result aggregation module, a workflow management module, and a security policy enforcement module. The orchestrator agent integrates encrypted outputs from the atomic agents to perform composite tasks while maintaining data integrity and security through the secure state management module.

The invention relates to the technical field of computer processing, in particular to a software architecture code generation method and system based on a large language model, and provides the following scheme: obtaining demand information input by a user, analyzing demands by using a natural language processing technology, and extracting functional elements; performing classification processing on the functional elements through a clustering algorithm to generate a functional module group; mapping the function module group to a system architecture layer, and generating an architecture diagram represented by UML (Unified Modeling Language); and generating a corresponding source code according to the UML graph, and optimizing the source code. The optimization strategy comprises static analysis of format problems and potential vulnerabilities in identification codes and performance optimization of complex functions. Through combination of the large language model and the automatic code generation and optimization technology, the software development efficiency is improved, manual intervention is reduced, and the correctness and maintainability of the generated code are ensured.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention relates to an endoscope image reflection restoration method based on detection network and filtering fusion, and belongs to the technical field of medical image computer processing. The method aims at improving detection and removal of specular reflection in an endoscope image, a variant of TransUnet is adopted in the detection stage, and U-Net and Transform architectures are combined; the method comprises Atrous spatial pyramid pooling (ASPP), information bottleneck (IB) and a convolutional block attention module (CBAM). The enhancement functions improve the identifiability of specular highlight and solve the problem of weak generalization in endoscope data concentration. In the removal stage, the invention designs an enhanced median filtering module for removing specular reflection. The module first applies Gaussian blur to the repaired region and then calculates color information from the non-reflective region. According to the method, mirror reflection is effectively eliminated from the endoscope image, clearer and more accurate visual information is provided for clinicians, and improvement of diagnosis precision is facilitated.

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.

Providing an NFTed avatar that may be used across different metaverses and may be dressed up with different items. There is provided a method for processing dress-up of an NFTed avatar by a computer, and the method comprises the steps of: referencing, by the computer, a smart contract for the avatar and data for displaying the avatar, and displaying the avatar to a user; referencing, by the computer, a smart contract for items and data for displaying the items, and displaying the items to a user; providing the user, by the computer, with a try-on interface for trying items on the avatar; providing the user, by the computer, with an interface for allowing the user to decide items to attach to the avatar; and executing, by the computer, based on the user's decision on items to be attached on the avatar, a writing on the blockchain for associating item NFTs with an avatar NFT for the smart contract for the avatar.

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.

The invention relates to a colorectal lesion typing method based on a KAN network and a variable attention mechanism, and belongs to the technical field of medical image computer processing. According to the method, colorectal lesions are classified; a KAN-ResNet backbone network typing model is established and initialized; setting an optimizer and a loss function; model training; storing and outputting the model; and parting the model. According to the method, a ResNet backbone network and a KAN mechanism are combined to capture complex modes and interdependence relations in colorectal images. The KAN-ResNet model aims at improving the classification performance of a fine-grained data set, so that the accuracy of distinguishing subtle changes of colorectal lesions is improved. Layered features are effectively captured by using a deep residual learning framework of a residual network ResNet, a variable attention mechanism and complexity of adapting to lesions are combined, so that the model can focus on related areas, accurate features can still be captured although deformation exists, and adaptability and accuracy in the aspect of colorectal lesion classification can be improved.

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.

A machine learning model, such as a Gradient Boosting Machine model, is trained using historical data associated with different types of operations. The machine learning model extracts features from the historical data and learns which features result in a predefined outcome, such as approval by a predefined entity. After the machine learning model is trained and validated as being accurate, it is used to predict the likelihood of a prospective operation achieving the predefined outcome when submitted right away versus a future date. If the likelihood of achieving the predefined outcome is low if submitted right away, the submission of the prospective operation is temporarily suspended. The machine learning model calculates a future time during which to submit the prospective operation for approval, where the future time has a greater likelihood of achieving the predefined outcome. This reduces waste of electronic resources including computer processing power and network communication bandwidth.

The invention provides a welded joint ultrasonic phased array automatic detection device and method, and the method comprises the steps: selecting a longitudinal wave mode or a transverse wave mode on an interface of a control computer, inputting sample parameters, calculating acoustic beam excitation delay, and setting the acoustic beam excitation delay in an ultrasonic transmitting / receiving module; a mechanical scanning mechanism is driven according to the set parameters, so that a phased array probe moves on the surface of the welding joint according to a preset path; ultrasonic waves are sent to the welding joint according to the acoustic beam excitation delay, echo signals are received, the echo signals are processed to obtain scanning signals, and the scanning signals are uploaded to the control computer; processing the scanning signal to generate a scanning image, segmenting and identifying the scanning image, and extracting incomplete fusion and incomplete penetration defect areas in the scanning image; and performing three-dimensional visual imaging on the defect area and analyzing a characteristic curve extracted from the primary echo amplitude of the echo signal to obtain three-dimensional data of the defect area and storing the three-dimensional data.

The invention provides a blind person voice navigation auxiliary method with a built-in offline AI intelligent model, and relates to the technical field of computer processing, and the blind person voice navigation auxiliary method comprises the following steps: S01, collecting environment image data in real time through an infrared-visible light binocular camera, synchronously obtaining six-degree-of-freedom motion attitude data of an inertial measurement unit, the binocular infrared-visible light binocular camera comprises a thermal imaging sensing channel; s02, inputting the environment image data into a pre-trained multi-task neural network model, and generating a three-dimensional semantic map containing a blind sidewalk topological structure and a dynamic obstacle detection result; and S03, based on a deep reinforcement learning algorithm, carrying out space-time clustering analysis on the historical paths of the user, and constructing a personalized habit route database fused with human body turning inertia. The sensing precision, the path planning humanization, the positioning accuracy and the extreme weather adaptability of the navigation system in a complex environment are remarkably improved, and safe navigation of the blind is guaranteed.

Technology advancements in computer processors, including in particular graphics processing units (GPUs), have included the introduction of parallel processing capabilities which offer high compute throughput and memory bandwidth. Currently, programmers spend considerable time optimizing their code to best exploit the available parallel processor resources. However, some applications are still unable to consistently attain high compute throughput or memory bandwidth despite the presence of abundant parallelism. The present disclosure provides both hardware and software support for accelerating parallel processing pipelines.

The invention provides a collaborative computing method, system and device based on SIMD and SIMT, and belongs to the technical field of computer processing. The method is applied to a Warp composed of a plurality of SPs, and the Warp comprises an SIMT front end and an SIMD rear end. Each SP corresponds to a vector register combined by a plurality of short registers; generating instruction fetching indication information under the condition that a thread bundle scheduler at the front end of the SIMT determines that a first thread bundle corresponding to the calculation task is in an activated state; obtaining a first cache instruction corresponding to the first thread bundle through an instruction fetching unit, and sending the first cache instruction to a decoding unit at the front end of the SIMT for analysis; obtaining one or more corresponding required operands through an operand collection unit at the rear end of the SIMD; and distributing the required operands to the corresponding calculation management units through the SIMD rear end to execute the corresponding calculation tasks, and writing the calculation results corresponding to the calculation tasks back to the storage unit through the write-back unit.

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.

A computer system for automatically generating cognitive exercises includes a computer memory that can store a memory list comprising subjects that a user has difficulty to remember, wherein the computer memory can store personal data associated with the user, and computer processors in communication with the computer memory can execute a cognitive exercise computation agent and a large language model responsive to the cognitive exercise computation agent. The cognitive exercise computation agent can retrieve the memory list and the personal data associated with the user from the computer memory. The cognitive exercise computation agent can produce generated cognitive exercises using the large language model under constraints of the memory list and the personal data associated with the user.

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.

Disclosed herein are systems and methods for distributed processing of secure multi-party computations. One example method includes dividing an overall SMPC circuit into partitions to be processed by different computers, balancing the computational load across the computers by ensuring the partitions are of similar sizes, identifying and minimizing a number of inputs and outputs crossing partition boundaries to optimize performance and employing a controller computer to orchestrate distributed computational tasks and recover from potential system failures.

The invention discloses a device and a method for testing wear resistance of a coating material in a high-temperature environment, and relates to the technical field of coating material testing, and the device comprises a workbench, a friction force loading mechanism, a test force loading mechanism, a high-temperature heating system, a force detection unit and a computer. The friction force loading mechanism provides stable friction force, the test force loading mechanism accurately applies test force, the high-temperature heating system creates a high-temperature environment, and the force detection unit detects force data in real time and transmits the force data to the computer for processing and analysis. The second driving mechanism is unique in structure and can accurately control test force loading, the circulating cooling unit is further arranged to protect the transmission shaft, the high-temperature furnace meets different temperature requirements, inert gas can be introduced to prevent high-temperature oxidation, and compared with a vacuum testing machine, the manufacturing cost can be greatly reduced. The problem that an existing detection device cannot accurately test the wear resistance of the coating material in a high-temperature environment is solved, and powerful support is provided for research, development and application of the coating material in the fields of aerospace and the like.

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.