776results about How to "Facilitate communication" patented technology

The invention provides a natural language control method for a humanoid robot. By constructing the simple skill library and the complex skill library of the robot, the dependence on a large amount of operation data in a specific field is effectively reduced. According to the method, a large language model is used as a base of a task planner, and the capabilities of scene learning, semantic understanding and common sense reasoning of the task planner are brought into full play. By introducing a visual model in the field of computer vision, high-level semantic information and low-level spatial information of the environment can be obtained, and an accurate scene graph is constructed to serve as environment state representation. According to the voice interaction interface constructed by the invention, the naturalness of man-machine interaction is improved, so that a user can more conveniently communicate with the robot and input instructions, the user experience is effectively improved, and popularization of the humanoid robot in an actual application scene is facilitated.

The invention relates to a CBCT image tooth segmentation method. The method comprises the following steps: generating a two-dimensional oral cavity panoramic film from a CBCT image; carrying out tooth two-dimensional segmentation and tooth ID classification on the two-dimensional oral cavity panoramic film by adopting a deep learning algorithm; calculating a key point coordinate of a two-dimensional single tooth and mapping the key point coordinate to a three-dimensional CBCT image coordinate; respectively cutting the CBCT image to obtain an area of each tooth; segmenting each three-dimensional tooth region by adopting a deep learning algorithm; and assigning ID to all the tooth segmentation results, and splicing to obtain a three-dimensional tooth segmentation result. According to the method, accurate segmentation of the tooth area in the CBCT image can be realized, complex conditions such as tight tooth arrangement, similar shapes and artifact interference can be effectively handled, the problems of tooth segmentation result fusion, ID confusion and metal artifact interference can be effectively solved, and resource consumption is remarkably reduced by determining the tooth key points on the panoramic film, so that the tooth segmentation efficiency is improved. The overall segmentation efficiency is improved, and the segmentation time is shortened, so that the accuracy of the segmentation result and the processing speed are improved.

The invention discloses a real-time cultural tourism path optimization and adjustment system based on big data analysis, and relates to the technical field of cultural tourism path optimizing.The system comprises an acquisition and analysis module, the acquisition and analysis module is connected with a combination and matching module, the combination and matching module is connected with a path optimization module, and the path optimization module is connected with a data processing module. The path optimization module is connected with an interaction feedback module, and the collection and analysis module is used for collecting tourism behavior characteristic information of tourists in real time by using a big data analysis technology. According to the real-time cultural tourism path optimization and adjustment system based on big data analysis, a personalized model is established, tourism paths can be customized for tourists, unique tourism requirements and preferences of the tourists are met, the satisfaction degree and participation degree of the tourists in the tourism process are improved, the tourism paths can be adjusted in time according to real-time external data, and the tourism efficiency is improved. The tourists are prevented from being caught in unfavorable conditions such as congestion and severe weather, and smooth and efficient travel itinerary is ensured.

A three-dimensional point cloud task analysis method fusing local features and global context information belongs to the field of three-dimensional point cloud task analysis, and comprises the following steps: step 1, constructing a point cloud data set: step 1.1), defining the data set; step 1.2), preprocessing the point cloud data set; step 2, point cloud data set sampling: down-sampling the point cloud number of the original point cloud data set to a fixed value through a farthest point sampling FPS mode; step 3, grouping point cloud data sets; 4, extracting local features; step 5, neighborhood feature propagation; step 6, constructing a space shape position code; step 7, constructing channel attention; step 8, local feature enhancement; step 9, global context feature extraction; and step 10, performing three-dimensional point cloud classification and segmentation tasks. According to the invention, the precision of the three-dimensional point cloud task is effectively improved.

The invention discloses an AI-driven complete-cycle scoliosis management system, which belongs to the field of scoliosis management systems and comprises a data fusion module, a feature extraction module, a text processing module, a diagnosis inference module and an output presentation module. Wherein the data fusion module is used for performing deep fusion on sensor data of the wearable equipment and X-ray / CT medical image data to generate comprehensive fusion prediction data; the feature extraction module uses a pre-trained fusion encoder to perform feature extraction and encoding on the fusion prediction data to generate potential feature representation; the text processing module adopts a pre-trained text encoder to encode free text diagnosis information provided by a doctor and a patient and extract semantic features; and the diagnosis inference module is used for fusing the fusion features and the text features. According to the invention, the sensing data of the wearable device and the medical image data can be effectively integrated to give full play to the complementary advantages thereof, so that the diagnosis accuracy is improved.

The invention relates to the technical field of breach image processing, in particular to a breach rapid situation awareness method and system based on multi-source data. The method comprises the following steps: acquiring dam monitoring station data; performing hydrological sensor network setting on the dam monitoring station data to obtain dam hydrological sensor network data; performing ultrasonic water level change trend analysis on the dam hydrological sensor network data to generate an ultrasonic water level change trend chart; performing breach node sensing on the dam hydrological sensor network data according to the ultrasonic water level change trend chart to generate breach node data and breach prediction node data; and according to the breach node data, macroscopic disaster risk analysis is carried out on the breach area, and a breach area macroscopic disaster risk schematic diagram is generated. According to the invention, through real-time data integration, comprehensive risk assessment, unmanned aerial vehicle monitoring, dynamic prediction model and multi-party cooperative response, the accuracy and response speed of breach rapid situation awareness are improved.

The invention discloses a general thermal power plant machine room DCS equipment data transmission method, equipment, a medium and a product, and relates to the field of data transmission, and the method comprises the steps: after a configuration file is defined, analyzing the configuration file, building a connection with general thermal power plant machine room DCS equipment according to a communication parameter and a mapping table, and based on a user request, according to a to-be-acquired data item list, obtaining a data item list; and reading data from the general thermal power plant machine room DCS equipment to obtain original data, processing the original data based on regulations of a communication protocol, and setting a retransmission mechanism and an error processing mechanism to obtain a data reading result. According to the application, the increase and decrease of the data volume become more convenient, the problems of delay and low efficiency in the big data transmission process can be solved, and the problem of data loss or damage caused by the influence of noise and interference is avoided.

The invention relates to a construction method of an anti-typhoon sea wave sea-crossing steel trestle and platform adjacent to a residential building. The construction method comprises the steps that firstly, deep fusion application of BIM and VR is conducted; step 2, surveying and setting out; step 3, embedding steel bars and pouring strip-shaped concrete; fourthly, the steel pipe piles are transported and lengthened; fifthly, steel pipe piles are driven; sixthly, parallel connection and diagonal bridging construction is conducted; seventhly, bearing beams are installed; eighthly, longitudinal beams are installed; ninthly, the distribution beams are installed; tenthly, bridge deck slabs and guardrails are installed; and 11, an intelligent monitoring and early warning system.

The invention discloses a multi-unmanned aerial vehicle air combat advantage competition strategy generation method based on a graph attention network. The method comprises the following steps: a, representing air combat observation data as a topological graph; b, according to the topological graph, adopting a graph attention neural network as a strategy model, and combining priori knowledge to obtain an abstract relation graph representing an air combat relation; and c, carrying out maneuvering decision making according to the abstract relation graph. According to the invention, a graph attention network and a method for establishing an abstract relation graph are adopted to learn a strategy which is more beneficial to cooperation; and the air combat relationship and communication among the unmanned aerial vehicles are enhanced, so that the finally output actions achieve effective cooperation.

The invention discloses a scientific research partner recommendation method based on an attention mechanism and a graph neural network, and provides an academic partner recommendation model AGNNRec based on the graph neural network and the attention mechanism. According to the method, a recommendation model is constructed based on a graph neural network, a context path is introduced to capture a high-order relationship between nodes, a multi-head relationship attention mechanism is introduced to learn embedded vectors of node high-order neighbors in parallel, and finally, recommendation of partners is completed by using a cosine similarity algorithm. Experiments are carried out on the model on a self-built data set and a public data set DBLP respectively, in the experiment using the DBLP data set, the effects of the model on Precision (at) 5 and NDGG (at) 5 are improved by 19.07% and 1.17% respectively, and the effectiveness of AGNNRec in science and technology partner recommendation tasks is shown.

The invention discloses a lake and reservoir inflow and outflow scheduling scheme optimization method and system based on a three-dimensional hydrodynamic force-water quality-water ecological model, and the method comprises the steps: firstly constructing a three-dimensional hydrodynamic force-water quality-water ecological model of a target lake and reservoir, setting a scheduling constraint, a scoring constraint, a scoring single item, and a comprehensive scoring weight by a decision maker, stratified sampling and one-dimensional uniform random sampling are carried out on each flow range of a water replenishing port, a flow outlet and a water suction pump station which can be regulated and controlled manually according to scheduling constraints set by a decision maker, and a plurality of inflow and outflow scheduling schemes are generated; and performing big data mining on the model calculation results of all the access flow scheduling schemes, performing comprehensive scoring according to the scoring single item and the comprehensive scoring weight, and selecting the access flow scheduling scheme with the highest comprehensive score as an optimal scheduling scheme for recommendation. The method has the advantages of high simulation precision, flexible decision support, multi-target comprehensive balance and the like, and a scientific and efficient technical solution can be provided for lake and reservoir inflow and outflow scheduling.

The invention discloses a tumor standardized whole-course management system based on digitization, and relates to the technical field of medical information. Comprising a personnel management module, a system management module, a diagnosis and treatment specification module, a tumor specification diagnosis and treatment training and examination module, a TNM staging module, an anti-tumor drug prescription right oriented application module, an anti-tumor drug data real-time monitoring module, a tumor treatment medical record supervision module and a tumor medical conjoined module. According to the method, the working efficiency of a team is improved by managing the individual information and role authority of medical personnel, the treatment scheme is optimized by analyzing the TNM stage data, the information transparency is improved by submitting the prescription right application, and the anti-tumor drug use data of the tumor patient is monitored in real time, so that the anti-tumor effect of the patient is improved. The medical staff can know the use condition of the medicine, the medical records of the tumor patients are randomly selected for spot check, the medical record recording and processing quality is continuously improved, a medical conjoined platform interface is constructed, and the operation efficiency of the whole medical conjoined is improved.

The invention provides a double-screen different-display real-time translation machine implementation method and device, and the method comprises the following steps: 1, obtaining and starting a double-screen different-display real-time translation machine, and initializing an SOC SSD2386 chip, two touch screens, a plurality of microphones distributed near the two touch screens and a storage unit of the double-screen different-display real-time translation machine; by adopting a double-screen different display technology, the target language text information can be respectively and clearly displayed on the touch screen of the opposite user, so that the situation of image disorder caused by mixed display of multiple languages on the same screen is avoided, the information reading speed and accuracy of the user are greatly improved, and the communication fluency and efficiency are ensured; according to the method, the target language text information is individually set according to the display preference of the user, the font size, the color and the like are adjusted, and only the translation result required by the opposite user is displayed, so that the interference of irrelevant information on the user is effectively avoided, the user experience is improved, and the smooth communication is promoted.

The invention relates to the technical field of wireless communication, in particular to a communication and rate optimization method and system of an ARIS-assisted ISAC-NOMA system. Channel fading gains from a user terminal to an ARIS node and from the ARIS node to a DFRC-BS node, a steering vector when a DFRC-BS node antenna array sends a sensing signal and a complex path loss coefficient of the sensing signal are obtained, the DFRC-BS node sends the sensing signal, the user terminal sends an uplink communication signal, and the DFRC-BS node receives a sensing target echo signal and a communication signal at the same time; a continuous interference elimination technology is adopted for the communication sensing mixed signals, and the communication sum rate and the sensing signal-to-noise ratio are calculated; and iteratively solving an optimization problem by using an alternating optimization algorithm to obtain the maximum communication and rate of the system. Compared with the traditional method, the method provided by the invention can realize higher communication rate and better sensing performance in different scenes, and has higher practical application value.

The invention relates to an unsupervised region representation learning method and system for learning urban region embedding, and belongs to the technical field of urban calculation and intelligent systems. The method specifically comprises the following steps: S1, constructing a regional mixed graph network, and capturing pairing and grouping relationships among regions by using multi-modal data; s2, graph and hypergraph comparative learning is executed, and discriminative representation of region nodes and a high-order relation between regions are learned from graph and hypergraph structures through a parallel comparative learning module; s3, cross-module comparative learning is carried out, information exchange between graph and hypergraph node representation is promoted through a controller assembly, and the learning ability of the model is enhanced; and S4, optimizing model parameters, and generating more effective region embedding through joint optimization of graph loss, hypergraph loss and cross-module loss so as to support various downstream tasks. According to the technical scheme provided by the invention, the accuracy and efficiency of urban area analysis are improved, and the capturing capability of the model on complex interaction between the areas is enhanced.

The invention relates to the technical field of cerebral apoplexy rehabilitation, in particular to a cerebral apoplexy patient upper limb rehabilitation evaluation system which comprises a motion capture module, an analysis module, a processing module, a training module, a feedback module, an optimization module and a sharing module. The analysis module performs analysis according to the data acquired by the motion capture module; the processing module formulates a training plan according to the analyzed illness state; the training module is used for training the patient according to the evaluation result; the feedback module is used for feeding back the training effect; according to the system, the training result of the patient can be comprehensively evaluated in real time, the training plan is adjusted in time according to the rehabilitation progress of the patient, the rehabilitation plan and the training mode are continuously optimized, the optimization module can gradually adapt to the individual difference and rehabilitation requirements of the patient, more accurate rehabilitation suggestions are provided, and the rehabilitation efficiency is improved. Therefore, the rehabilitation effect is obviously improved.

The invention relates to a waveform optimization method for a dual-function radar system, and the method comprises the following steps: obtaining parameters of the dual-function radar system, and building a communication model and a radar model of the dual-function radar system; calculating a direct component of the dual-function radar base station received by the user side and a reflection component of the intelligent reflection surface through a communication model, and calculating a signal to interference plus noise ratio according to the direct component and the reflection component; a target response matrix from the intelligent reflecting surface to the detection target is established through a radar model, and the radar model comprises a transmitting wave beam and a passive wave beam; the Cramer-Rao bound minimization of target angle information sensed by a dual-function radar system is taken as an optimization target, a signal to interference plus noise ratio is taken as a constraint, an optimization expression is established, a transmitting beam and a passive beam are alternately optimized, and an optimization result and the minimum Cramer-Rao bound are obtained. Compared with the prior art, the method has the advantages of low calculation complexity, high communication performance and the like.

The invention discloses a client information management method and system based on real estate transaction, relates to the technical field of client information management, and solves the technical problem that client information management cannot be evaluated according to a real-time product demand trend, so that client types cannot be distinguished according to different demand trend stages in the prior art. Specifically, a demand trend evaluation unit evaluates the demand trend of a real-time sales product, collects demand trend information, substitutes the demand trend information into a formula to obtain a demand trend evaluation coefficient in a real-time circulation stage, and deduces that the current circulation stage is in a purchaser market or a supplier market according to coefficient comparison; a customer stage analysis unit performs customer stage analysis according to the real-time circulation stage, obtains the speed-to-time ratio information of a supplier and the speed-to-time ratio information of a purchaser, deduces whether a current customer is a customer in a knowing stage or a customer in an intention stage according to information comparison, and correspondingly sends the customer to a customer information management platform; the label classification setting unit performs label classification setting on clients.

The invention relates to the technical field of data mining, in particular to a method and a system for generating a printed circuit board design drawing. The method comprises the following steps: obtaining customer demands, structuring the customer demands into circuit board design demand data, and then carrying out mode clustering to obtain design demand mode data; acquiring a historical design log, performing circuit board hierarchical design clustering based on the historical design log to obtain historical hierarchical design data, and performing wiring structure topology analysis to form a wiring structure model set; quantifying a wiring demand, obtaining wiring demand data based on demand mode data, and matching the hierarchical wiring structure model set to form a matching model; the layout component is used for carrying out component layout on the matched wiring structure model, generating component layout data and planning the direction of a signal line to form a hierarchical structure model; and performing electromagnetic interference simulation, optimizing the hierarchical structure model based on simulation data to balance heat flow, and finally generating a circuit board design drawing. The design efficiency of the circuit board can be improved.

The invention belongs to the technical field of digital economy monitoring, and particularly relates to a digital economy monitoring method based on a block chain technology, and the method comprises the following steps: 1, constructing a digital economy co-creation platform based on a block chain, and enabling the digital economy co-creation platform to comprise a plurality of participants and a supervisor; 2, a plurality of participants jointly generate values through resource integration in the value co-creation process based on the digital economic co-creation platform, and a value network structure is constructed based on a block chain; 3, in the value network structure, dividing a value co-creation process into a value resource selection stage, a value resource acquisition stage and a value win-win stage through analysis and function definition of a resource subject; and step 4, the supervisor supervises whether the establishment process of the digital economic co-creation platform and the value co-creation process of the plurality of participants based on the digital economic co-creation platform are abnormal in real time. According to the invention, all participants share innovative resources, and the resource sharing safety performance is high.

The invention discloses a wood structure building information classification coding and data automatic identification mapping system and method, and the method comprises the steps: 1, creating a traditional wood structure building component-level model, and building a traditional wood structure building database; 2, performing overall view projection on the traditional wood structure building component-level model, matching the model with a traditional wood structure building database, and outputting a regulation code so as to screen corresponding data; 3, picking up the split components, performing isolated view projection, performing feature fuzzy matching with the simplified data pool, screening and defining the components, and outputting identification codes; 4, the traditional wood structure building is subjected to space division and tagging, and positioning codes of the components are generated; 5, the code segments are called according to purposes to be combined, and component codes are formed; and 6, integrating component parameters to carry out attribute addition and mapping, and endowing construction codes. The invention relates to the technical field of historic building information management, and can solve the technical problems in traditional wooden structure building information management in the prior art.

The invention provides a device networking method and system based on an IPv6 protocol, and the method comprises the steps: reading a sequence number in a unique identifier of a device when the device is registered, combining the sequence number with bytes generated by a random number generator to generate a network card identifier and a local link address, triggering a multicast neighbor request, splicing the multicast neighbor request with a router IPv6 network address prefix to form a device IPv6 address, and transmitting the IPv6 address to the device; registering identifier information to the system, and setting the object to complete registration; during IPv6 network address change monitoring of the equipment, an ICMP6 protocol routing announcement is intercepted, and when a router network prefix is changed, a new prefix and a network card identifier are used for regenerating and re-registering an IPv6 address; in the aspect of system functions, registration information is received, related contents are registered, parameters are set remotely, user and equipment management is carried out, and equipment management covers multiple functions such as software remote online upgrading; address management can be simplified, the use threshold and cost are reduced, the equipment management function is enhanced, the dynamic address processing efficiency is improved, and the defects in the prior art are overcome.

The invention relates to the technical field of invisible orthodontic appliance wearing monitoring and adjusting systems, in particular to an invisible orthodontic appliance wearing monitoring and adjusting system and method based on computer vision, and the system comprises a cloud storage module which is used for storing initial oral data and re-consultation oral data of a patient; the cloud processing module is used for analyzing the oral cavity picture uploaded by the patient and executing analysis software; the client module is used for managing an electronic medical record of a patient, providing treatment information, obtaining an analysis result and generating personalized feedback; according to the invention, a computer vision algorithm is combined with oral medical knowledge, so that not only can the position change of teeth be accurately identified and tracked, but also the judgment ability of the device can be continuously optimized through a deep learning algorithm. Meanwhile, the cloud computing architecture adopted by the invention enables the system to process mass data, and powerful data support is provided for formulating a personalized treatment scheme.

The invention discloses a hyperspectral image classification method and a hyperspectral image classification device based on a double-branch multi-scale CNN (Convolutional Neural Network) and a memory enhancement Transform. The method specifically comprises the following steps: step 1, acquiring and preprocessing hyperspectral image data; and step 2, inputting the data after the step 1 into a double-branch multi-scale CNN feature extraction module, and fully extracting spatial features and spatial-spectrum combined features of the hyperspectrum. And step 3, transmitting the data after the step 2 into a memory module, performing detail memory and global memory on the data by MT1, and performing normal memory and important feature memory on the data by MT2. 4, the data obtained in the step 2 and the data obtained in the step 3 serve as input and are transmitted into a memory Transform; and 5, finally, a classification result is obtained through an mlp-head layer. According to the method, rich spatial features and spectral features of the hyperspectrum can be fully combined, and the classification precision and the classification performance of the hyperspectral image are improved.

The invention discloses an AI-based customer behavior analysis and prediction system and method, and the system comprises a data collection module which is used for automatically collecting customer behavior data from a plurality of data sources; the data processing module is used for cleaning and standardizing the collected data so as to facilitate analysis; the AI model training module is used for training a machine learning model by utilizing the processed data; the prediction analysis module is used for predicting future behaviors of the customer by using the trained AI model; the user interface module is used for displaying a prediction result and allowing a user to adjust prediction parameters; the report generation module is used for automatically generating a report containing prediction information according to the selection of the user; the customer behavior data can be automatically collected from multiple data sources, the customer behavior mode can be learned and recognized through advanced data processing and the AI model training module, the prediction accuracy can be improved, the user experience can be improved, and enterprises can better adapt to market changes and customer requirements.

The invention discloses an audio and video system integrated conference system, which belongs to the technical field of remote conferences, and comprises an information authentication module, an audio transmission module, a video transmission module, a conference effect detection module and a comprehensive summary module, the audio transmission module comprises audio acquisition equipment which is responsible for capturing, transmitting and processing audio signals in a conference so as to ensure that participants can clearly hear the sound of each other, and the video transmission module comprises a high-definition camera which is responsible for capturing, transmitting and displaying video signals. According to the audio and video system integrated conference system, audio and video transmission, concentration degree detection and conference content summarization can be realized, the interactivity and effect of a conference are effectively improved, the effect of the audio and video conference is improved, and the participation degree of participants in the conference process is improved.

The invention relates to the field of equipment process control, and discloses a communication method and device for a data acquisition upper computer and process equipment, equipment and a medium, the method is applied to the data acquisition upper computer, and the method comprises the following steps: receiving equipment information and interaction data sent by a plurality of pieces of process equipment through preset communication connection; determining an analysis protocol between the process equipment and the data acquisition upper computer based on the equipment information, and processing the interaction data according to the analysis protocol to obtain analyzed interaction data; obtaining pre-configured parameter information in the data acquisition upper computer, and matching the analyzed interaction data with the parameter information to obtain target parameter information; and constructing a parameter list by using the target parameter information, and sending the parameter list to the process equipment. According to the invention, the problems of measurement channel waste caused by repeated acquisition, easy interference by system matching problem, low communication rate when parameters are many and incapability of guaranteeing data synchronism in parameter acquisition of the vehicle platform process equipment are solved.

The invention discloses an intelligent building engineering management system based on a BIM platform, and relates to the technical field of building engineering management, and the system comprises a BIM model database, a participant interface module, a real-time synchronization module, an automatic notification module, an authority management module and a block chain recording module. According to the intelligent building engineering management system based on the BIM platform, computing resources and storage capacity are flexibly adjusted according to project requirements, and the requirements of projects of different scales are met; the block chain recording module supports a multi-chain synchronization function, and different participants can record on independent chains; therefore, the security of the data is ensured, the expandability of the building engineering management system is improved, and the individual requirements of different participants are met; the automatic notification module adopts a plurality of channel notification modes, and supports a user-defined reminding mode and priority setting of a participant; therefore, information transmission is more flexible and diversified, and working habits and requirements of different participants are met.

A transparent visual power grid operation and maintenance system comprises a data acquisition and preprocessing module which is composed of a sensor network and SCADA system docking unit and a data preprocessing unit; the data processing and analysis module is composed of a fault prediction and diagnosis unit, an operation and maintenance strategy optimization unit and a three-dimensional modeling and dynamic simulation unit; the visual display and user interaction module is composed of an AR / VR interface development unit and a user-defined interface and report generation unit; and the system integration and communication module is composed of a standardized API interface and cloud platform unit and a remote access and cooperation unit, and the scheme of the invention solves the problem that the complexity of power grid operation and maintenance system data causes that detection information is difficult to provide visually, thereby affecting the operation and maintenance work quality and efficiency.

The invention relates to the technical field of information analysis, in particular to an information analysis method and system based on student data traceability. The method comprises the following steps: acquiring a student subject learning quality data set; performing data preprocessing on the student subject learning quality data set to generate a subject learning quality preprocessing data set; performing influence factor screening on the subject learning quality preprocessing data set according to a preset regression analysis model to generate subject influence related factors; utilizing a Fahrenheit combination interval analysis method to carry out deep interval analysis on the subject influence correlation factors, and generating a student subject learning quality strategy; therefore, through influence factor analysis and strategy adjustment of the system, the problem that a traditional education analysis method is lack of individuation and dynamic adjustment is solved, and the scientificity and the implementation effect of education decision making are improved.