380results about How to "Achieve interaction" patented technology

The invention provides an explosion-proof power distribution cabinet control method and system based on situation awareness, and relates to the technical field of power distribution cabinets, and the method comprises the steps: obtaining the associated power equipment information of a target power distribution cabinet; analyzing the connection relation of the same-level equipment to generate an equipment network topology structure; acquiring use scene information, and generating an operation configuration parameter set; acquiring an operation condition data set; judging whether a running configuration parameter set is met or not; if yes, performing real-time state monitoring to obtain state monitoring information of the target power distribution cabinet; inputting a situation awareness prediction model to carry out abnormal state prediction to obtain an abnormal state prediction coefficient; and judging whether an abnormal state prediction coefficient threshold value is met or not, and if yes, generating a first emergency processing instruction to perform emergency processing. According to the method, the problems of low data acquisition and processing efficiency and poor timeliness and safety of power distribution cabinet control due to lack of accurate prediction of abnormal states in a traditional method are solved.

The invention discloses an electroencephalogram signal feature extraction method and system based on self-adaptive time-frequency feature collaboration, relates to the field of electroencephalogram signal processing, and solves the problems that in existing electroencephalogram signal feature extraction, fusion is carried out in a simple splicing or averaging mode, complementarity and correlation between time domain and frequency domain features are not fully considered, and time domain and frequency domain features are not fully considered. In order to solve the problems of insufficient overall characterization capability and classification performance of signals and the like, the method comprises the following steps: acquiring electroencephalogram signal data, preprocessing the electroencephalogram signal data, constructing a dynamic residual network in combination with dynamic convolution, and training a model based on the preprocessed electroencephalogram signal data; performing a contrast test on the dynamic residual network and other deep learning network models, and designing an adaptive time-frequency collaborative network model to fuse time-domain features and frequency-domain features in the model; and electroencephalogram signal feature extraction based on adaptive time-frequency feature cooperation is completed. The method is also suitable for the field of electroencephalogram signal feature extraction and fusion.

The invention discloses a complex target recognition method based on a deep twin self-attention network, and relates to the technical field of target recognition methods. According to the method, a twin network based on a sliding window multi-head self-attention transformation mechanism is applied, the global modeling capability of a feature extraction network and the acquisition efficiency of long-distance semantic information are enhanced, and the bottom-layer feature extraction capability and the abstract effect of advanced semantic information are improved; the twin network personalized modeling improves the feature segmentation effect; the whole network forms a U-shaped structure, a local symmetric encoder and decoder structure is adopted, global context information is supplemented, and semantic information space association is enhanced; a residual link is added, so that the deep network is trained efficiently, and the recognition precision is enhanced; and adaptive image feature scale input processing is added, and adaptive scale transformation is performed on the input image, so that an accurate end-to-end semantic segmentation result is realized, and multi-scale input is realized to enhance the generalization ability and accuracy of a network model.

The embodiment of the invention provides a media content generation method and device, a storage medium and a program product, and the method comprises the steps: displaying dialogue content in a dialogue window of a first interface, generating target media content according to the dialogue content, and presenting a trigger control of the target media content in the dialogue window, wherein the trigger control is at least used for triggering presentation of the target media content. According to the media content generation method provided by the embodiment of the invention, the information interaction between the user and the system is realized by adopting the dialogue mode, and then the target media content conforming to the creation intention of the user is generated based on the obtained dialogue content, so that the learning cost of the user is reduced, the operation is simple, and the intelligent level of media content generation is improved.

The invention discloses a hyperspectral and multispectral image fusion method and system based on an improved Transform, and the method comprises the steps: carrying out the up-sampling of a hyperspectral image, and extracting the potential features of the hyperspectral image; multi-scale features of the hyperspectral image and the multi-spectral image are respectively extracted by using a double-branch structure, and global feature extraction is carried out on feature maps through a multi-layer deformable convolution crossover Transform; and adding the extracted features according to the same direction, splicing the features in a channel dimension, and gradually reconstructing a multispectral image through cascade up-sampling. The invention provides a new method based on an up-sampling recursive sub-network and a multilayer deformable convolutional cross Transformer (URSMDCT) for hyperspectral and multispectral image fusion, potential features and multiscale features of the image can be fully extracted, and spectral information and spatial information are effectively fused.

An environment multi-parameter monitoring base station capable of being used for long-term seafloor work is laid to the seafloor through a mother ship in a cable mode, energy is supplied through a dissolved oxygen seawater battery, long-term seafloor environment in-situ monitoring operation is carried out through carried universal and special instruments and equipment, a shore-based instruction is received to adjust a monitoring strategy, and the monitoring base station is used for monitoring the seafloor environment. Monitoring data is transmitted back to the shore-based laboratory in real time; the monitoring base station comprises a rack system, a monitoring system, a control system, a communication system, an energy supply system and a laying and recycling system; the monitoring system is used for completing in-situ monitoring operation on the influence of a seabed biochemical environment and benthos by adopting a general monitoring instrument and an extended special instrument; and the communication system is used as a signal transmission medium to perform parallel and uplink and downlink data transmission and instruction issuing so as to realize networking between the base station and each node around the base station and interaction and communication between the base station and a water surface buoy or a ship.

The invention provides a dynamic spreading factor anti-interference method based on annealing Q learning. The method comprises the following steps: determining an information transmission rate according to a spreading factor; determining system throughput and an optimization target according to the signal-to-noise ratio of the receiving end; determining a state space, an action space, a state transition probability matrix and rewards in the decision process; calculating a reward obtained by the selection action according to a broadband spectrum sensing result; the interference condition at the current moment is obtained through broadband spectrum sensing; deciding a spreading factor of the next time slot according to the Q value table; the user selects the action of the next time slot according to the decision information and updates the state; the award obtained by selecting the corresponding action is calculated according to the broadband spectrum sensing result; selecting the spreading factor of the next time slot according to the Q value table, and updating the Q value of the selection action in the state; and the user makes the most anti-interference strategy in a dynamic interference environment. According to the method, the system throughput is maximized, and time delay and overhead caused by channel switching are avoided.

The invention provides a music generation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a text prompt word transmitted by a user, and enabling the text prompt word to be used for determining a music element of to-be-generated music; processing the text cue word by adopting a music score generation model to generate an initial music score; modifying the initial music score according to the modification opinion transmitted by the user until no modification opinion is generated, and obtaining a target music score; and processing the target music score by adopting a music generation model to generate target music. According to the invention, the controllability of the generated music is improved.

The invention discloses a power equipment detection method and system, and relates to the technical field of power equipment detection, and the method comprises the steps: inputting a power equipment image into a trained enhanced target detection model; the trained enhanced target detection model comprises a backbone network, a neck network and a head network; performing multi-level feature extraction enhancement on the power equipment image through the backbone network to generate a low-level feature, a middle-level feature and a high-level feature; inputting the low-layer features, the middle-layer features and the high-layer features into a neck network for feature pyramid fusion, and outputting a plurality of fusion features; and respectively detecting each fusion feature by using a head network, adding elements one by one, and determining a detection result of the power equipment. The electrical equipment image is detected through the enhanced target detection model with an improved structure, so that the feature extraction capability is enhanced, the interaction of multi-scale information is realized, the accuracy and robustness of target detection are improved, and the detection reliability of the electrical equipment is improved.

The invention relates to a rotary inertial navigation digital twinning system and a construction method thereof. The rotary inertial navigation digital twinning system comprises a rotary inertial navigation digital twinning physical model layer, a rotary inertial navigation digital twinning geometric model layer, a multi-source information data acquisition layer, a decision control layer and a diagnosis and prediction analysis layer. Data information collection and transmission of a rotary inertial navigation system entity can be completed, association and interaction between a twin virtual body and the entity are achieved, iterative optimization of model parameters can be achieved through the decision control module, and finally prediction and evaluation of the overall operation state of the system and the performance of the digital twin inertial navigation system are achieved in the diagnosis and prediction analysis module.

The invention discloses a micro-channel jet reactor. The micro-channel jet reactor comprises a sample introduction unit, a main mixing unit and a reaction unit which are sequentially communicated, the main mixing unit comprises a first inner pipe and a first outer pipe arranged outside the first inner pipe in a sleeving manner; a first annular space is formed between the first inner pipe and the first outer pipe; the sample introduction unit is communicated with the first inner pipe; a second sample inlet is formed in the first annular space, and a plurality of through holes are formed in the first inner pipe; the reaction unit comprises a second inner pipe and a second outer pipe arranged outside the second inner pipe in a sleeving manner; a second annular space is formed between the second inner pipe and the second outer pipe; the first inner pipe is communicated with the second inner pipe; during use, condensate is arranged in the second annular space. The reactor can effectively improve the mixing uniformity degree of reaction liquid, meanwhile, the reaction temperature is controlled, and the reaction rate and selectivity are ensured.

The invention provides a chatting method and device for multi-agent role playing, and the method comprises the steps: configuring a role for each participant to chat according to a preset role attribute, and enabling the participant to comprise at least two agents or at least one user and at least two agents; session samples containing the role attributes are obtained, and the session samples comprise sample dialogue content between different roles; training a large language model by adopting the session sample so as to enable the large language model to learn a session conforming to role setting and plot development; and inputting the role configured by each participant into the trained large language model, and managing the actual dialogue content among the plurality of participants according to the trained large language model, each participant performing dialogue according to the role attribute of the configured role. According to the invention, interaction among multiple agent roles can be realized.

The invention provides a scene management and intelligent recommendation method and system based on a data space, and the method comprises the steps: selecting a system function in a preset database, and carrying out the matching of a corresponding data type according to the selected system function, making a corresponding data acquisition plan according to system functions and data types; collecting data based on the formulated data collection plan and selecting a data processing model matched with the collected data according to the collected data; processing the collected data to form a feature fusion layer, and introducing an attention mechanism and an inter-channel information transmission mechanism into the selected data processing model to optimize the selected data processing model; and training the optimized data processing model to obtain an attention mechanism weight matrix, and adjusting the obtained attention weight matrix to realize personalized recommendation. The technical problem that the heterogeneous data processing and recommendation ability is insufficient in the related technology is solved.

The utility model provides an intelligent sound box based on three-dimensional gesture recognition control information, and relates to the technical field of sound equipment, the intelligent sound box comprises a housing and an intelligent control mechanism, the intelligent control mechanism is arranged in the housing, and through the arrangement of a power supply assembly, power supply support is provided for the sound equipment through a power supply converter, a storage battery and a multifunctional charging interface. The multifunctional sound box has the functions of power conversion, power storage and charging, meanwhile, the mobility and the use convenience of the sound box are improved, three-dimensional gesture recognition is carried out through the RGB-D camera, interaction between a user and the sound box is achieved, gesture actions of the user are captured through the infrared sensor, and the high pitch unit and the low pitch unit provide the audio output function of the sound box. The wireless transmission module and the Bluetooth module realize wireless connection of the sound box, support different audio sources, and provide core control and processing functions of the sound box through the central intelligent chip, the image processing chip and the audio processor, so that the product is more intelligent.

The invention discloses an interaction method and device of a business system and a third-party database, a medium and a system. The method comprises the following steps: receiving a user request sent by a user in a service system; in the running process of the service system, if it is identified that the service system runs to a preset tangency point, calling a target JavaScript script corresponding to the current preset tangency point through a Naporn engine; the target JavaScript script is executed in a Naporn engine, so that the target JavaScript script is used for being used for interacting with a third-party database, and the third-party database is used for interacting with the third-party database through the target JavaScript script; and performing service response on the user request according to interaction data returned by the target JavaScript script of the preset tangency point. By adopting the technical scheme, decoupling of third-party interface calling and database reading logic can be realized, and the flexibility and maintainability of a software system are improved.

The invention discloses a remote sensing image spatial-spectral fusion method based on a denoising diffusion probability model and a Transform, and the method comprises the steps: designing a three-branch encoder-decoder network structure for spatial-spectral fusion, extracting the spatial feature information of a panchromatic image and the spectral feature information of a multispectral image through employing the denoising diffusion probability model (DDPM) and a Transform network, and carrying out the spatial-spectral fusion of the panchromatic image and the multispectral image. The extracted spatial information and spectral information are integrated into an encoder branch in a layer-by-layer manner so as to realize interaction and effective fusion of the spatial information of the panchromatic remote sensing image and the spectral information of the multispectral remote sensing image, and finally a fusion image with rich spatial information and spectral information is obtained; a large number of experimental results on a public data set show that compared with other representative comparison methods, the method provided by the invention achieves an overall dominant fusion effect in two aspects of subjective visual effect comparison and objective index evaluation.

The invention relates to the technical field of photoelectric communication, in particular to a PWDM (Pulse Width Division Multiplexing) optical device compatible with high and low rates, which comprises a first controller, a second controller is arranged at one end of the first controller, a transmission mechanism is connected between the first controller and the second controller, a processing mechanism is mounted at one end of the first controller, and the processing mechanism is connected with the first controller. A mounting mechanism is mounted on the first controller; through installation of the transmission mechanism, the first controller and the second controller, data processing is facilitated, optical signal receiving and transmitting are achieved, high-speed data transmission is achieved, meanwhile, compatibility of low-speed data transmission is reserved, and therefore the experience that a user uses two rates mutually is met; different optical signals can be further processed, the stability of data transmission is achieved, through connection of the installation mechanism, the equipment is convenient to install and operate, and the equipment can work more stably.

The invention discloses a road construction dustproof evaluation method, which comprises the following steps: constructing a macroscopic traffic flow model based on a cellular automaton, taking a visibility distribution field as an input condition, simulating behavior responses of drivers under different visibility, including vehicle speed selection and vehicle distance maintenance, and obtaining a traffic flow state evolution process in a construction area; the visibility, the vehicle speed and the vehicle distance serve as state input, a deep reinforcement learning algorithm is adopted to train a microscopic driving behavior model, a driving behavior strategy is optimized through a reward and punishment mechanism, and accurate description and prediction of driving behaviors under different visibility conditions are achieved; and calling a preset traffic control strategy library according to the influence degree of the road construction dust on the traffic safety, and selecting a proper traffic control scheme for dust prevention, including adjustment of a lane speed limit value and release of warning information. According to the invention, the traffic safety risk caused by construction dust is effectively reduced, and the road traffic safety is guaranteed.

The invention discloses a liquid recoverable carrier rocket control system and control method, and belongs to the technical field of rocket recovery control. Comprising a flight control combination, a recovery control combination, an inertia measurement combination, a battery, a safety control combination, an engine controller, an optical target camera, a laser range finder, a comprehensive collecting and editing device, a relay measurement and control terminal and a space-based telemetering phased array antenna. The flight control combination and the recovery control combination are arranged in the second rocket sublevel and the first rocket sublevel respectively, partial hot backup is achieved through the two control combinations, and the reliability of the system is improved. In the first-stage flight section with the worst and most dangerous mechanical environment, the recovery control combination can serve as hot backup execution work of the flight control combination, and normal recovery of the first sub-stage cannot be affected even if flight failure is caused by abnormity of the second-stage rocket. Effective control over launch and recovery of the carrier rocket can be met, and a necessary control system is provided for recovery of the carrier rocket.

The embodiment of the invention provides a power grid intelligent equipment data distributed processing and real-time pushing method and system, and belongs to the technical field of power grid data processing. The method comprises the following steps: collecting electric power data, and transmitting the data to an Internet of Things gateway; the Internet of Things gateway directly stores the collected data into the message queue without processing based on a publishing attribute mode of the message queue; persistently storing the relationship between the collected data and the gateway register point location in a relational database, and pre-loading associated data in the relational database into a cache database Redis; associating the obtained data with the mapping relation in the Redis cache, and packaging a unified update message structure; according to the method, updating messages are pushed to different themes, and the system pushing pressure is reasonably distributed to all pushing services by appointing the themes subscribed by different pushing services. According to the method, the operation data of the power system can be timely and effectively acquired, and real-time interaction and updating with the client can be realized.

The utility model discloses a circulating powder supply system of SLM printing equipment. A lower connector of a residual powder transfer powder tank is connected with a gas circuit powder conveying pipeline; an outlet of the blower is connected to an inlet of the gas circuit powder conveying pipeline; the cyclone separator is connected with an outlet of the gas circuit powder conveying pipeline; a powder outlet of the cyclone separator is connected with an inlet of the powder drying chamber, the powder drying chamber is connected with an inlet of the ultrasonic screening device, and the ultrasonic screening device is connected with the main powder storage tank. An output port in one side of the air bag is connected with an inlet of the arch breaking pipeline, an outlet of the arch breaking pipeline is internally connected with the main powder storage tank, the material supplementing tank, the top powder storage tank and the transfer powder tank, the top powder storage tank is arranged at the top of the SLM printing equipment, and an outlet of the top powder storage tank is connected to an inlet in the top of the SLM printing equipment; the material supplementing tank is connected to the gas circuit powder conveying pipeline; and the SLM printing unit is arranged on the gas circuit powder conveying pipeline. The problem that in the prior art, the efficiency is low due to the fact that powder is manually added or carried to complete the powder supply link of the printing equipment is solved.

The invention discloses a multi-modal sentiment analysis method based on modal focusing, which takes text, visual and audio modals as centers, focuses on each modal one by one, aims to explore how to perform interactive fusion on information of a main modal and other two secondary modals, and provides a multi-modal sentiment analysis method based on modal focusing in a subsequent fusion process. The three main modes are connected in an effective mode to serve as fusion representation of guidance, and more comprehensive and effective multi-mode information is provided for sentiment analysis tasks. Comprising the following steps: (1) shared mask learning: obtaining a shared mask between a primary mode and a secondary mode by training a cross-modal prediction model; (2) a cross-modal interaction stage: performing interactive fusion on the characteristics of the primary and secondary modals by adopting a cross-modal attention mechanism with a shared mask to obtain fusion representation dominated by each modality; and (3) a subsequent fusion stage: endowing the three fusion expressions with respective weights by using a weighted attention mechanism for connection to obtain a final multi-modal fusion vector. According to the method, the feature relation and cross-modal interaction between the primary and secondary modals are fully mined and utilized, so that the condition of multi-modal information imbalance is processed, and a more accurate sentiment analysis result is achieved.

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 a multi-channel voice separation method and device based on multi-scale feature channel fusion. The method comprises the steps that a plurality of multi-channel mixed voice signals with different noise, reverberation and speakers are acquired to form a training data set; constructing a multi-channel voice separation network based on multi-scale feature channel fusion, wherein the multi-channel voice separation network specifically comprises a high-dimensional feature extraction module, a spatial feature extraction module, a multi-scale feature extraction module, a convolution separation network based on feature channel fusion and a voice reconstruction module; inputting the training data set into the multi-channel voice separation network for network training; and inputting a to-be-separated mixed multi-channel voice signal containing noise, reverberation and multiple speakers into the trained multi-channel voice separation network to obtain a single-channel voice signal of each speaker. The method is higher in separation capability and generalization capability.

The invention discloses a fault diagnosis method based on multi-dimensional knowledge migration. The method comprises the following steps: acquiring a source domain data set and a multi-target domain data set; constructing a double-branch neural network model based on guidance of data knowledge and semantic knowledge, training the double-branch neural network model, and optimizing model parameters by taking minimization of a total loss function of the double-branch neural network model as an optimization target; wherein the model comprises M + 1 data knowledge guidance branch networks and M + 1 semantic knowledge guidance branch networks; and performing fault diagnosis tasks of different target domains by using the trained double-branch neural network model. According to the method, the problem of negative migration caused by forced alignment distribution in traditional migration learning can be solved, and effective knowledge migration from a source domain to a multi-target domain is realized from the perspective of multi-dimensional knowledge fusion, interaction and driving; the method can be applied to industrial fault diagnosis tasks of industrial operation and maintenance and rapid migration deployment in various migration learning scenes, and has a good learning effect and generalization ability.

The invention discloses a construction method, a prediction system and a prediction method of a circular RNA (Ribonucleic Acid) and disease association prediction model based on a shared unit, and association prediction is realized through the constructed circular RNA and disease association prediction model. Comprising the following steps: constructing a circular RNA meta-path network, a circular RNA similarity network, a disease meta-path network and a disease similarity network based on a known associated data set, and respectively carrying out feature extraction on the networks to obtain circular RNA similarity features, circular RNA meta-path features, disease similarity features and disease meta-path features; the similarity features and the meta-path features are simultaneously input to a sharing unit; similarity features output by the sharing unit are input into a multi-layer perceptron to carry out circular RNA and disease association prediction and update model parameters. A sharing unit is designed for the model, and the prediction performance of the model is improved by constructing a similarity network and a meta-path network of circular RNA and diseases and capturing potential cross-view information in a multi-view feature fusion process.

The invention discloses a database parameter adjusting and optimizing method based on parameter type customization optimization, and belongs to the field of database configuration optimizing.The method comprises the steps that a database parameter space is divided into a continuous type parameter subspace and a classified type parameter subspace according to parameter types, and the continuous type parameter subspace and the classified type parameter subspace are projected to a low-dimensional space; a GP model and an SMAC model are used as proxy models in the low-dimensional continuous parametric subspace and the classification parametric subspace respectively to search continuous parametric configuration and classification parametric configuration; interaction between the GP model and the SMAC model is realized through iterative optimization and a context-based communication mechanism; and mapping a parameter configuration result back to a database parameter space for performance evaluation. According to the method, the database parameter tuning performance and efficiency can be effectively improved, and a user is allowed to search database parameter configuration with higher performance in a shorter time.

The invention provides a target tracking method and system based on space channel summation attention, and the method employs a dual-branch feature extraction network based on a space channel summation attention module to carry out image feature extraction, and carries out the processing of a space attention mechanism and a channel attention mechanism in the extraction process. Information interaction between a space domain and a channel domain is achieved, a large amount of structured space information and channel information are obtained, final template features and intermediate search features are obtained, the final template features and the intermediate search features are fused and sent to a head prediction network, and the maximum response position of a tracking target in a search area can be obtained. And target tracking is carried out. According to the method, the advantages of space channel summation attention are fully utilized, so that the tracker can well deal with the difficulties of target shielding, rapid movement, complex background and the like in the tracking process, and more accurate tracking can be realized.

The embodiment of the invention provides a data transmission system based on the Internet of Vehicles, and belongs to the field of expressways. The system comprises a vehicle-mounted module, at least one roadside module connected to the Internet, a cloud module and a security authentication module, wherein the vehicle-mounted module is used for collecting state information of a vehicle; the roadside module is used for collecting real-time information of road conditions, traffic flow and environment; the security authentication module verifies and manages the identities of the vehicle-mounted module, the road side module and the physical user, and if authentication is passed, the data is encrypted by adopting a Hash algorithm and then transmitted; and the cloud module analyzes the uploaded data according to a preset rule and provides personalized services. The data transmission system based on the Internet of Vehicles realizes real-time data transmission and interaction between the vehicle and the road infrastructure and between the vehicle and the cloud platform through cooperative work of all the modules, and adopts an identity verification mechanism and an encryption technology to ensure the security and confidentiality of the data in the transmission process.

The invention provides an equivalent hypergraph construction method for traffic flow prediction. The equivalent hypergraph construction method comprises the following steps: S1, data collection: collecting traffic flow data of each region through a sensor of an intelligent traffic system; s2, data processing: carrying out preprocessing and normalization processing on the collected traffic flow data, and constructing a graph structure of a traffic system and a training graph neural network model; s3, constructing a graph neural network: selecting a GCN as a framework of the graph neural network; s4, client node construction: performing feature fusion on the graph constructed for the local jurisdiction by each client through an attention mechanism; and S5, constructing an equivalent hypergraph: for n clients formed by traffic flow information of n regions, repeating the step S4 to obtain n client nodes, adding edges and weights according to a region adjacency principle to obtain an initial equivalent hypergraph, and continuously training and comparing based on the initial equivalent hypergraph to finally obtain the equivalent hypergraph. The risk of privacy disclosure is reduced, the efficiency of model training is improved, and the prediction precision of the model is improved.