3224 results about "Modular design" patented technology

The invention relates to a cross-modal knowledge reasoning method based on a multi-modal large model. In a cross-modal knowledge reasoning process, an existing model is usually limited by single-modal information extraction and shallow feature fusion, so that deep semantic association among data such as texts, images and videos is difficult to fully capture. In order to solve the problem, the invention provides a model for fusing multi-modal information such as texts, images, videos, documents and the like, and processing of multi-modal data is converted into unified feature extraction, interaction and deep reasoning tasks by fully utilizing a supervision fine tuning strategy, a self-adaptive attention mechanism and a cross-language processing technology. The model adopts a modular design, integrates multi-source data complementary analysis, spatial-temporal feature modeling and emotional semantic analysis, and realizes multi-modal collaborative interaction, dynamic scene understanding, long video key event analysis and man-machine co-emotional response. Through sufficient training, the multi-modal large model shows excellent logical reasoning ability and emotion understanding ability in a complex cognitive task, and a brand new solution is provided for efficient extraction, deep semantic analysis and intelligent response of cross-modal information.

This invention introduces an adaptive system for multi-modal media processing and delivery, addressing challenges in modern digital content distribution. The technology dynamically analyzes and processes media content in real-time, optimizing delivery across diverse devices, networks, and content types. Key features include adaptive processing that adjusts compression, encoding, and delivery protocols based on content characteristics and delivery constraints. The system incorporates artificial intelligence for continuous improvement, learning from historical data and user feedback. It addresses network variability and device diversity, adapting to changing conditions and optimizing content for different platforms. Security and personalization features enable protected content distribution and tailored user experiences. The invention's cross-media optimization approach allows efficient handling of various media formats within a unified framework. Its scalable, modular design suits applications from consumer streaming to enterprise-level distribution. This comprehensive solution aims to enhance content distribution efficiency and user experience in the complex, evolving digital media landscape.

The invention discloses an improved convolution neural network model for leukocyte calculation, and relates to the field of artificial intelligence and medical image processing. Aiming at the problems of inaccurate feature extraction, strong background noise interference and insufficient multi-scale feature fusion in a traditional leukocyte calculation method, the model realizes fine processing and feature enhancement of a medical image through a multi-level modular design; the image preprocessing module is used for completing white blood cell positioning and image adaptive division and enhancement; multi-scale edge, texture and gray features are fused by means of an image feature extraction module, and a composite feature vector is constructed; through multi-scale convolution, a double-layer attention mechanism and convolution layer calculation of the improved convolution neural network model module, precise focusing of white blood cell contours and cell nucleus features, background noise suppression and calculation efficiency optimization are realized; and finally, a calculation result is output through a visual terminal, so that the accuracy and robustness of leukocyte counting are remarkably improved, and efficient technical support is provided for medical microscopic image analysis.

The invention belongs to the technical field of target classification, and particularly relates to a three-dimensional point cloud data analysis method and system based on artificial intelligence. Comprising the steps of data acquisition, data preprocessing, model construction, model training, model prediction and the like. The integrity and precision of point cloud data are effectively improved by collecting original point cloud and performing intelligent denoising and complementation operation; constructing a depth model by adopting an input layer, a region proposal layer and a classification and regression layer, and carrying out accurate classification and three-dimensional bounding box prediction on a target; wherein the region proposal layer is combined with a seed point feature extraction and voting mechanism to generate a candidate region, a classification branch outputs a category probability, and a regression branch predicts bounding box parameters. The system adopts a modular design, has the advantages of strong noise suppression, high complementation precision, high target detection accuracy, multi-scene applicability and the like, and is particularly suitable for efficient automatic identification of a complex three-dimensional structure.

The invention discloses a global nerve drawing method and system for a multivariate mixed representation scene, and belongs to the technical field of computer graphics, and the method comprises a scene expression module which is used for loading multivariate mixed scene data; the geometric module is used for generating a multi-channel geometric buffer based on the multivariate mixed scene data; the illumination module comprises at least one neural network sub-module and is used for carrying out illumination calculation based on multi-channel geometric buffering; the scheduling and synchronizing module is used for coordinating cross-module data streams through a rendering graph structure and executing resource merging and task scheduling between the geometric module and the illumination module based on a unified request structure; and the merging output module is used for fusing neural network illumination output and traditional rendering output to generate a final frame image so as to complete global neural rendering. According to the invention, multi-element scene data is integrated through modular design, efficient collaboration of traditional and neural rendering is realized by using a unified interface and a scheduling structure, and the image quality and the system flexibility are improved.

According to the intelligent grotto excavation stability analysis system based on the BIM, through deep fusion of the BIM model and multi-source monitoring data, whole-process dynamic control over the grotto excavation stability is achieved. The system adopts a lightweight model processing technology to remarkably improve the calculation efficiency, and an intelligent inverse algorithm effectively solves the subjectivity problem of traditional parameter determination. A three-dimensional numerical simulation and real-time monitoring data interactive verification mechanism greatly improves the reliability of an analysis result, and a dynamic risk assessment system realizes the accuracy of risk early warning through multi-index fusion analysis. A final support scheme optimization module combines engineering experience with an intelligent algorithm, safety is ensured, economical efficiency is taken into account, and an intelligent solution capable of being self-adaptive to engineering condition changes is formed. According to the whole system, seamless connection of all links is achieved through modular design, and full-chain technical support from data to decision making is provided for safety construction of underground engineering.

The invention discloses a network communication dynamic optimization method based on multi-module collaboration, and relates to the technical field of network communication, a dual-mode communication module is deployed at each network node, and the network communication dynamic optimization method comprises the following steps: each network node broadcasts own existence information and power line channel characteristics through an HPLC (High Performance Liquid Chromatography) channel of the dual-mode communication module; each network node scans surrounding wireless networks through an HRF channel of the dual-mode communication module and reports own wireless channel quality information to the gateway; the global state sensing module collects all information and constructs a global network view containing physical topology and a channel quality map. A dual-mode cooperation mechanism, a machine learning prediction model and a dynamic decision strategy can adapt to complex dynamic environments such as power line noise fluctuation and wireless interference change, and communication parameters can be autonomously optimized without manual intervention; and meanwhile, the modular design is convenient to expand to a multi-mode communication scene, and has a wide application prospect.

The invention provides an enterprise financial comprehensive management system based on an intelligent technology, and relates to the technical field of financial management. The accounting intelligent subsystem is used for acquiring financial data, performing semantic analysis and conversion on the financial data through a preset rule and a multi-stage data mapping mechanism, generating a standardized accounting service instruction and issuing the standardized accounting service instruction to an automatic process engine, thereby automatically generating a financial document meeting an accounting criterion; the financial management subsystem is used for integrally realizing execution of backlog management, compliance guidance manual query and financial data structured storage according to a preset standardized process; and the business service subsystem is used for providing tax-related business service, asset management service, fund management service and operation management service processing and guidance for enterprises through modular design. The invention aims to improve the operation efficiency, reduce the error rate, break information islands, realize effective integration and utilization of resources, and provide powerful support for decision making of enterprises.

The invention discloses a network management racing item question answering system based on a knowledge graph, and belongs to the technical field of knowledge graph teaching. In the system, the association relationship among massive network equipment, protocol configuration and fault cases is stored in a knowledge graph structuralization mode, and natural language processing and graph database retrieval technologies are combined; core knowledge points of complex problems can be quickly positioned, and strong scene adaptability and expansion potential are shown through modular design and a dynamic cooperation mechanism. The knowledge graph management module supports incremental updating and cleaning fusion of multi-source heterogeneous data, can integrate newest competition cases and technical specifications in time, and guarantees the frontier and authority of a knowledge base; and the interaction optimization module automatically identifies a knowledge blind area according to the score of the user on the answer and triggers graph completion. The self-feedback and self-iteration mechanism not only reduces the manual maintenance cost, but also provides a technical basis for cross-domain knowledge migration.

The invention discloses a high-performance satellite platform based on a real-time operating system and a wireless bus and a working method of the high-performance satellite platform, and belongs to satellite communication technologies, future deep space exploration and low-orbit satellite constellations. On the basis of an original structure of a satellite platform, a real-time operating system is effectively combined with a wireless bus system, and the real-time operating system comprises a kernel module, a communication module, an equipment driving module, a file system module, an application interface module, a safety module and a fault management module. The wireless bus system comprises a physical layer, a data link layer, a network layer, a transmission layer and an application layer. According to the invention, efficient and reliable communication and task execution capabilities are provided for a satellite platform, the requirements of real-time performance and reliability of a satellite in a complex environment are effectively met through modular design and tight work of the system, and meanwhile, complex lines and interfaces brought by a wired system are avoided.

The invention discloses a drilling-grouting integrated underwater robot and aims to meet the requirement for precise operation in a complex underwater environment. The robot integrates the fin antenna, the hydraulic telescopic crawler belt, the hydrodynamic force wings, the bionic mechanical arm and the integrated drilling and injecting system, and has the multi-terrain adaptation, efficient navigation and autonomous operation capacity; through modular design and a high-strength pressure-resistant structure, the robot can complete tasks such as pipeline repair, resource exploration and infrastructure construction in a deep sea high-pressure environment; the core technology comprises a multi-mode propulsion system, intelligent sensing and navigation, AI optimization operation and dual-mode operation switching. Typical application scenes include submarine pipeline damage repair, deep sea mining area reinforcement sampling, cross-sea bridge pile foundation grouting and the like. The limitation that a traditional underwater robot is single in function and high in energy consumption is broken through, and the safety and efficiency of complex underwater engineering are remarkably improved.

The invention discloses an outdoor workstation air quality monitoring and intelligent ventilation system and method, and belongs to the technical field of environment monitoring and intelligent ventilation control. The system is composed of an environment sensing module, an intelligent control unit and a ventilation execution device. And the environment sensing module realizes pollutant concentration field reconstruction through a multi-dimensional data fusion algorithm. The intelligent control unit constructs a dynamic ventilation model based on an improved fuzzy PID algorithm, and generates an optimal ventilation strategy in combination with meteorological prediction data and workstation structure parameters. And the ventilation execution device adopts a modular design to realize directional air supply and pollutant blocking. The method comprises four steps of real-time environment data acquisition, dynamic risk assessment, ventilation parameter optimization and execution mechanism linkage control, and remote intelligent regulation and control are realized through cooperation of edge computing and a cloud platform. According to the scheme, a passive response mode of a traditional ventilation system is broken through, and the technical advantages of accurate pollutant tracing, dynamic optimization of ventilation efficiency and intelligent adjustment of equipment energy consumption are achieved.

According to the high-speed serial communication system protocol adaptation layer circuit oriented to interconnection between the core particles and the working method, the circuit serves as a bridging layer between an AXI-S bus and a SerDes physical coding sub-layer, and the problems of reliability and flow control in high-speed data transmission between the core particles are solved. The circuit adopts a modular design idea and comprises a transmitter and a receiver. In the aspect of data packet design, a first packet special processing mechanism is adopted, and an event serial number and target address information are only transmitted in a first packet, so that the bit utilization rate is improved. In the flow control design, a credit-based flow control mechanism is adopted, and the data transmission reliability is guaranteed through a special flow control packet. In addition, the system has a point-to-point retransmission function, data packets which fail in transmission are indexed and retransmitted, and successful data transmission is guaranteed within the configured retransmission times. According to the invention, an efficient and reliable protocol adaptation layer circuit solution is provided for high-speed interconnection requirements in core particle design.

The invention discloses an automobile tire defect automatic detection device and system, and belongs to the field of automobile tire processing, through highly integrated modular design, the automobile tire defect automatic detection device comprises a multifunctional image recognition module, a depth measurement and 3D imaging module, an internal structure and air tightness detection module and an analysis and decision module, comprehensive detection of the surface, the geometric structure, the internal structure and the air tightness of the tire is realized, and efficient, accurate and intelligent tire defect detection is realized through cooperative work of each module and equipment.

The invention discloses a high-precision real-time positioning system and method for positioning personnel based on multi-mode fusion. The system comprises a multi-source data acquisition module, an intelligent data processing module, a fusion positioning model construction module and a positioning result application module, provides visual monitoring, trajectory analysis and scene customization functions, and supports flexible expansion through modular design. According to the method, satellite positioning, Bluetooth beacon and inertial navigation technologies are integrated, the weight is dynamically adjusted in combination with an adaptive weighted fusion algorithm, and a fusion positioning model supports outdoor (satellite dominant + EKF calibration, the precision being 2-5 meters) and indoor (beacon dominant + fingerprint matching, the precision being lt); according to the invention, intelligent switching between three modes (inertial navigation + ZUPT correction) and signal loss (1 meter) is realized, data noise is optimized by using Kalman filtering, and high-precision real-time positioning in indoor and outdoor complex scenes is realized. According to the invention, the problems of insufficient precision, poor environmental adaptability and weak expansibility of a single positioning technology are solved, and the comprehensive performance of the positioning system is significantly improved.

The invention relates to the technical field of intelligent communication, and discloses an end-to-end optimization method, a signal constellation geometry and probability joint shaping optimization method in an end-to-end intelligent communication system, and a communication device based on a neural network. According to the method, a transmitter is constructed by using a neural network, and a received signal passes through a two-stage equalization processing system to form an end-to-end optimization framework without assistance of a channel model. The transmitter adopts a modular design, can realize joint optimization of constellation probability shaping (PS) and geometric shaping (GS), and performs joint updating on all trainable parameters of the system based on a total loss function containing an equilibrium error and a decoding error through a back propagation algorithm. According to the invention, computing resources are effectively saved; the two-stage equalization system can accurately compensate channel damage, the realized PS and GS joint optimization can significantly improve the performance of the communication system and reduce the bit error rate, and the method has good performance advantages and practical value in an actual optical fiber communication system.

The invention provides a stacker high-precision motion control method and system based on a fuzzy immune algorithm, belongs to the field of stacker control, and solves the problems that an existing stacker is low in operation precision, poor in control efficiency and the like. The system comprises a multi-axis motion control module, a double-closed-loop feedback module, a parameter self-learning module, a safety protection and diagnosis module, a positioning detection module, a path planning module, an environment and maintenance management module and a stacking machine. The method comprises the following steps: constructing a three-level control architecture; adjusting an integral coefficient and a differential coefficient; establishing a feedback quantity calculation model; constructing machine learning parameters; and optimizing a parameter input system. The system is based on a fuzzy immune algorithm, high precision, strong adaptability and high reliability of motion control of the stacker are realized, and the failure rate is reduced. The stacker adopts a modular design, integrates an intelligent control system, and is efficient and stable. According to the method, fuzzy logic and an immune algorithm are combined, the stacker is endowed with intelligent decision ability, and the method adapts to different warehouses.

The invention provides a multi-modal big language model inference engine which comprises a pre-training big language model adaptation layer, a pollution remediation knowledge graph enhancement module, a multi-modal information understanding and fusion unit, a technology implementation optimization module and an inference chain and decision interpretation generator. The system adopts a hierarchical modular design, all components communicate through a standardized API interface, efficient and stable data circulation is ensured, and the problems of knowledge application limitation, opaque reasoning process, difficulty in professional knowledge fusion, knowledge updating lagging, limited multi-modal data processing capability and the like in the existing contaminated site remediation decision process are solved.

A removable pop out window provides a modular design. The window is configurable for multiple positions, including closed, vented, removable (e.g., pop out) positions, and combination thereof. The window may include latches, actuators, living hinges, or a combination thereof to allow for the multiple positions. The window may be modular, configured to be installed either as fixed of removable in a vehicle.

The embodiment of the invention provides a wafer testing device and testing method, and belongs to the technical field of wafer testing. The wafer testing device comprises an MEMS probe chip installed and connected on a testing machine, and a testing position used for fixing a tested chip. A test contact of a probe of the MEMS probe chip is in contact with a PAD of a tested chip during testing, and the MEMS probe chip is used for collecting a detection signal of the tested chip; wherein a probe of the MEMS probe chip is integrated in the MEMS probe chip based on a cantilever beam type; and the test machine is used for generating a test result corresponding to the tested chip based on the detection signal of the tested chip. The MEMS probe chip in the scheme of the invention adopts a modular design, is convenient to quickly replace, reduces the maintenance cost and time, and provides a better solution for the test requirements of high-frequency and high-density packaged chips.

The invention relates to an air tightness detection tool and detection system integrated design method in the field of air tightness detection equipment, and the method comprises the steps: obtaining product form data, extracting shape, size and material information from a product three-dimensional model database, calculating the key points of the outer contour of a product through a geometric feature analysis algorithm, and calculating the shape, size and material information of the product; determining product form diversity parameters; a clamp, an inflation system and a sorting module are decomposed into independent functional units through a modular design structure algorithm, a standardized interface protocol is generated, and physical connection and data interaction modes among the modules are determined; and according to the final tool design parameters, a solid fixture is generated by adopting a three-dimensional printing technology, a robot is controlled through an automatic assembly algorithm to complete integration of the fixture, an inflation module and a sorting module, and an air tightness detection system which can be put into production is obtained.

The invention provides a modular and multifunctional karst collapse physical simulation experiment platform. Comprising a rigid frame, a bearing device, a moving device, a loading device, a lifting device, a pile foundation construction dynamic load simulation device, a ground traveling dynamic load simulation device, a rainfall simulation device, a computer vision monitoring device, an underground water pumping and draining simulation device and an underground space excavation disturbance simulation device. The moving device is arranged on the bearing device, the lifting device, the loading device and the pile foundation construction dynamic load simulation device are arranged on the moving device, the travelling crane dynamic load simulation device is connected with a traction device of the moving trolley, and the camera shooting monitoring device and the rainfall simulation device are arranged on the rigid frame through a support. According to the method, key disaster-causing conditions in the urban environment are fully considered, the working condition scene coverage is wide, and the applicability is high; modularized design is adopted as a whole, all the modules can be flexibly loaded according to requirements, the real environment can be simulated more truly, and the catastrophe evolution process of surface collapse can be reproduced.

The invention relates to the technical field of robot control, in particular to a robot object grabbing adaptive learning system based on visual and tactile feedback. The robot object grabbing adaptive learning system based on visual and tactile feedback comprises a data acquisition module used for acquiring adaptive control data of a robot; the joint adjusting module is used for obtaining the joint compensation amount of the robot according to the adaptive control data of the robot and adjusting the grabbing motion of the robot to obtain the final joint adjustment degree; the visual feedback module is used for obtaining a rough grabbing force estimation value of the visual information by using a visual feedback formula according to the visual data of the robot; and the tactile feedback module is used for obtaining correction force of tactile feedback by using a tactile feedback formula according to the tactile data of the robot. Through multi-modal information fusion and modular design, high-precision and self-adaptive grabbing of the thermochromic object by the robot is realized.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

The invention discloses a large model-knowledge graph driven data blood relationship traceability reasoning method and system. According to the method, through a closed-loop framework of KG-driven dynamic decomposition, small-model lightweight reasoning and visual credibility verification, the defects are systematically solved, and an interpretable, low-cost and easy-to-expand data consanguinity depth traceability scheme is provided for scenes with high credibility requirements such as data governance, compliance auditing and root cause analysis. According to the system, aiming at complex problem requirements, after a complex problem is input, the problems of no interpretation, low reliability and the like in data blood relationship traceability are solved through two modules, namely problem reasoning and verification presentation. The modular design not only conforms to the technical decoupling principle, but also facilitates independent optimization, and is suitable for medical treatment, scientific research and other scenes with high requirements for interpretability.

The invention discloses a dynamic environment robot adaptive control method and system, and relates to the technical field of robot adaptive control. According to the invention, dynamic compensation is realized based on multi-sensor fusion and real-time anomaly detection in combination with impedance compliance control; through a lightweight error model and a trajectory interpolation technology, the calculation efficiency is improved compared with traditional model prediction control, and high-frequency real-time correction is supported; the system adopts a modular design, and adapts to a heterogeneous robot platform by adjusting equivalent mass-damping-spring parameters; for sudden disturbance, trajectory smoothing and impedance control technologies are fused, the oscillation amplitude of the system is reduced, and execution jitter is effectively inhibited; according to the method, high-precision force tracking and stable control are achieved in scenes such as complex terrain walking and dynamic grabbing, the problems that traditional fixed parameter control response is lagged, model dependence is high and an actuator is overheated are solved, and the adaptive capacity of the robot to the dynamic environment and the task completion rate are remarkably improved.

The invention belongs to the technical field of boundary layer detection, and particularly relates to an unmanned aerial vehicle atmospheric boundary layer environment autonomous detection system and method.The unmanned aerial vehicle atmospheric boundary layer environment autonomous detection system comprises an unmanned aerial vehicle platform, a detection load subsystem, a flight control subsystem, a data processing subsystem and a ground station subsystem, and the unmanned aerial vehicle platform comprises an unmanned aerial vehicle, a flight control module and a communication module; the unmanned aerial vehicle is made of light-weight composite materials and has good structural strength and weather resistance, an equipment cabin, a battery cabin and a load cabin are arranged in a vehicle body, modular design is adopted, maintenance and upgrading are convenient, in addition, the unmanned aerial vehicle is further provided with an energy module and a power module, and energy and power are provided for the unmanned aerial vehicle; the flight control module comprises a flight control computer, an inertial measurement unit I MU and a GPS / Beidou dual-mode receiver. The unmanned aerial vehicle can effectively avoid movable obstacles such as birds in an atmospheric boundary layer and a strong turbulence area when carrying out environment detection, and the flight safety of the unmanned aerial vehicle during detection is guaranteed.

The invention discloses a polyester fabric printing and dyeing water-saving automatic treatment system based on digital monitoring. According to the system, a printing and dyeing execution device, a filtering regeneration device, a data acquisition device and a system control device are integrated through modular design, temperature, pressure, flow velocity and resin saturation data in the printing and dyeing process are obtained in real time through a sensor network, and a dynamic correlation function is constructed based on the system control device to generate an accurate regulation and control instruction. Uniformity control of wastewater circulation, stability optimization of resin adsorption efficiency and remarkable improvement of the water resource utilization rate are achieved, and the problems that in a traditional process, the manual dependence degree is high, and resource waste is serious are solved.

The invention provides an emergency decision-making auxiliary system based on a knowledge graph. Comprising a data acquisition and processing module, a knowledge graph construction and reasoning module, an information retrieval and generation module, a multi-level reasoning and thinking chain prompting module, a multi-agent cooperation and game optimization module, an incremental learning and dynamic knowledge updating module and a block chain trust guarantee module. The emergency decision-making efficiency, accuracy, cooperation capability and safety are broken through, dynamic and complex emergency scenes can be effectively dealt with, and efficient, reliable and intelligent technical support is provided for decision makers.

The invention discloses a reinforcing method for long-term automatic grouting repair of fractured rock mass.The reinforcing method comprises the steps that a pressure sensor is arranged at the tail end of a grouting opening, and data of the pressure sensor are obtained through an intelligent control system; when the intelligent control system monitors that pressure difference is generated due to pressure unbalance caused by surrounding rock fracture development, the intelligent control system sets grouting parameters and starts a grouting program; in the grouting process, pressure balance between equipment and surrounding rock is maintained through a pressure adjusting module, and it is ensured that grout is stably conveyed within the set pressure range all the time in the conveying process after a grouting program is started; grouting pressure and flow are controlled in the grouting process; in the grouting process, the bacterial liquid and the cementing liquid are input in a separated conveying and on-site gathering mode; and accumulated liquid in the pipeline is rapidly removed after grouting is finished. By adopting the method, cracks can be continuously monitored and periodically repaired, and the manual intervention requirement is reduced. The modular design is convenient for maintenance and replacement of equipment, and the maintenance cost is reduced.