16results about How to "Effective interaction" patented technology

The invention discloses an image fusion method based on a double-branch feature decoupling auto-encoder, and belongs to the field of computer vision and image processing. According to the method, for the problems of modal pollution and structural distortion in infrared and visible light image fusion, structural semantic information and high-frequency texture details of a source image are extracted respectively by constructing a content feature coding module and a detail feature coding module, and feature decoupling is achieved. And performing deep fusion on the decoupled features by using an adaptive feature weighting mechanism, and reconstructing a fused image with infrared target saliency and visible light detail definition through a shared decoder. According to the method, an end-to-end two-stage training strategy is adopted for optimization, complex prior or post-processing is not needed, the effects of improving the fused image contrast, edge preservation and target recognition performance are remarkable, and the method is suitable for the fields of weak light monitoring, intelligent perception, unmanned system navigation and the like.

This invention discloses a low-light scene analysis method based on multimodal feature fusion and clustering, belonging to artificial intelligence technology. It constructs a single-branch feature extraction network based on Transformer; a multimodal feature interaction and fusion module to achieve multimodal feature interaction and fusion; a multimodal fusion feature clustering module to cluster the features after multimodal interaction and fusion, utilizing the semantic and spatial distances between different features to achieve clustering while simultaneously downsampling the features, mitigating the problem of loss of detailed edge information in structured downsampling; and a multi-scale feature aggregation and decoding module to receive feature information from the encoding network and classify each feature pixel according to the semantic distance of the multi-scale features. This invention can fully utilize visible light and thermal image information and can be applied to scene analysis and navigation of unmanned systems in diverse and complex low-light scenes.

The invention belongs to the technical field of biological genes, and discloses a method for identifying RNA interaction protein based on a Turbo ID technology and an MCP / MS2 system, the method can be used for identifying protein interacting with RNA in vitro or in vivo, and the method specifically comprises the following steps: firstly, respectively constructing RNA expression vectors inserted with MS2 tags, then constructing fusion protein vectors expressing MCP-Turbo ID, and finally constructing fusion protein vectors for expressing MCP-Turbo ID; the method comprises the following steps of: inserting RNA (Ribonucleic Acid) into an MS2 tag, transgenosis into a plant receptor by utilizing an agrobacterium tumefaciens mediated genetic transformation method to obtain a transgenic plant material expressing MCP-Turbo ID, combining the RNA inserted with the MS2 tag with the MCP-Turbo ID in vivo / in vitro by utilizing a hybridization or in-vitro incubation method, further enabling the Turbo ID to be adjacent to the RNA, biotinylating the RNA binding protein, and obtaining a transgenic plant material expressing the MCP-Turbo ID. And then enriching biotinylated protein by adopting streptavidin magnetic beads, and identifying and analyzing through Western Blot and mass spectrometry. The method not only solves the problem that the interaction protein of specific RNA in a living cell environment cannot be effectively identified in the prior art, but also can capture a transient or low-affinity RNA-protein interaction relationship.

This invention discloses a pet drying system with an interactive module and its usage method. The pet drying system includes a housing with a pet-containing cavity inside. The housing has an opening that connects to the pet-containing cavity, and a door for opening and closing the opening. It also includes a human-pet interaction module and a pet autonomous entry / exit module. The human-pet interaction module includes an interactive window, and the pet autonomous entry / exit module includes a pet autonomous entrance / exit. The interactive window and the pet autonomous entrance / exit are located on the housing and are respectively connected to the pet-containing cavity. This pet drying system with an interactive module allows for effective interaction between the user and the pet, and also enhances safety.

The application discloses an interactive method and device, a terminal device and a computer readable storage medium. The method comprises: acquiring video stream data played by a user; identifying the video stream data and extracting a key scene; when the key scene is not a predetermined scene, sending scene video data corresponding to the key scene to a cloud end, and interacting with the user based on first interactive content data returned by the cloud end, wherein the cloud end is used to generate the first interactive content data based on the scene video data. The method of the application can reduce the computing pressure of the client through the functional division and collaborative cooperation of the client and the cloud end, improve the accuracy of scene identification and the relevance of interactive content, realize efficient and intelligent interaction in a complex video playing scene, and improve the user experience.

The invention discloses a multi-dimensional physical simulation method and system based on large construction equipment, and relates to the technical field of digital assembly type construction. The method comprises the following steps: acquiring dynamic parameters of large-scale construction equipment and physical attribute parameters of prefabricated parts, constructing a multi-dimensional physical simulation model based on MATLAB, and constructing a high-fidelity virtual construction environment containing a construction site model, an equipment model and a component model through IsaacSim; a simulation model is used for calculating a hoisting track and load data, and the hoisting track and the load data are transmitted to IsaacSim through ROS standardization to complete virtual simulation; real data are collected through a multi-mode sensor and transmitted to a digital twin platform through a cloud server, the platform fuses simulation and real data, and a deviation calculation and dynamic calibration algorithm is adopted to carry out comparative analysis to generate a safety assessment result and early warning information. The system correspondingly comprises a multi-dimensional physical modeling unit, a virtual simulation unit, a sensor unit, a cloud server unit, a communication transmission unit and a digital twin platform unit, precise simulation, real-time monitoring and intelligent early warning of hoisting operation are achieved, and support is provided for construction safety and fine management.

The application discloses a fault diagnosis method based on an adaptive time-frequency fusion gated attention network and belongs to the technical field of equipment fault diagnosis. The method comprises the following steps: an adaptive time-frequency domain fusion network model (ATFFNet) is constructed, the model mainly comprises three modules of double-branch feature extraction, time-frequency information fusion and pooling fusion, a time-domain branch and a time-frequency branch cooperative feature extraction framework is constructed to realize joint modeling of multi-source information; an adaptive frequency band division and multi-scale feature enhancement mechanism is introduced in the time-frequency branch to improve the representation ability of complex frequency components and local degradation characteristics, and the representation ability of the model to time-frequency characteristics and weak fault characteristics in a non-stationary signal is improved; meanwhile, a gated attention fusion module is designed to realize effective interaction and adaptive aggregation of cross-branch and cross-band information, so that the diagnosis precision, robustness and generalization ability of the model in a multi-sensor scene are improved.

The invention relates to the field of antibodies useful in therapeutic and diagnostic applications targeting cd127, the alpha chain of the il7 receptor, and in particular provides humanized monoclonal antibodies against cd127, especially human cd127, their therapeutic uses and diagnostic applications.

The invention discloses a low-illumination image enhancement method based on gradient perception and intermediate frequency guidance, which mainly constructs a double-branch encoder-decoder network model in an HVI color space so as to effectively recover image texture details, suppress noise and improve color fidelity under a low-illumination condition. Firstly, an RGB image is converted into an HVI color space, and two branches of HV and I are separated; secondly, in the encoding process of an encoding layer, a gradient guide channel attention module is adopted to enhance detail perception, and meanwhile, deformable cross-branch fusion attention is adopted between middle-layer features and in a decoding layer to achieve cross-branch dynamic information interaction; in a bottleneck layer, an intermediate frequency guided multi-scale frequency domain enhancement module is adopted to perform intermediate frequency guided amplitude feature enhancement and phase maintenance in a frequency domain; and finally, reconstructing the enhanced HVI image through a symmetric decoder, carrying out residual connection on the HVI image and the initial HVI image, and inversely transforming the HVI image back to the RGB space to obtain a recovered image. Compared with the prior art, the method has better image visual quality.

The test hydraulic system comprises a portal frame, a Z-axis loading mechanism, an X-axis loading mechanism and a Y-axis loading mechanism, wherein the Z-axis loading mechanism, the X-axis loading mechanism and the Y-axis loading mechanism are mounted on the portal frame; the loading mechanism for loading in the pedaling direction of the foot type robot comprises a supporting frame, a loading oil cylinder, a stroke reducing assembly and a hydraulic control module. The loading oil cylinder is fixedly installed on the supporting frame and connected with the hydraulic control module, and the hydraulic control module is suitable for providing back pressure when a piston rod of the loading oil cylinder stretches out; the stroke reducing assembly is installed on the supporting frame and connected with a piston rod of the loading oil cylinder through a traction end, and the stroke reducing assembly is used for reducing the stroke of the foot type robot according to a set proportion and then pulling the piston rod of the loading oil cylinder. The device has the advantages that the stroke reducing assembly is adopted for transmission instead of directly acting on the loading oil cylinder in a pedaling mode, the stability problem of the piston rod caused by the long stroke of the loading oil cylinder is avoided, meanwhile, the size of the supporting frame is effectively reduced, and cost is reduced.

The invention relates to a live broadcast interaction method and device, computer equipment, a computer readable storage medium and a computer program product, and relates to the technical field of computers. The method comprises the following steps: displaying a reservation page of interactive live broadcast of a target account; the reservation page comprises an interaction control; displaying an interactive interface in response to a trigger operation for the interactive control; submitting first information corresponding to the interactive live broadcast based on the interactive interface; wherein the first information comprises topic information, and the topic information is used for guiding the target account to plan the live broadcast content of the interactive live broadcast. By adopting the method, topics interested by audiences are collected through information interaction before broadcasting, so that the target account can conveniently plan the live broadcast content, the pertinence and attraction of the live broadcast content are improved, and the satisfaction of the audiences is improved. The interaction control is arranged on the reservation page, so that the user can effectively interact with the anchor before playing, and the sense of participation of the user is improved.

The invention belongs to the technical field of data processing, and discloses a training data set generation method and system based on multi-modal data fusion, and the method comprises the steps: carrying out the modal preprocessing of multi-modal original data, and obtaining a cross-modal standardized data set and a multi-dimensional basic feature set; generating a cross-modal fusion feature vector based on the multi-dimensional basic feature set, and determining an actual risk point and associated data of the contract in combination with a preset text risk review rule base; determining a risk label of each actual risk point according to a preset classification standard, and binding the risk labels with associated data through a data unique identifier ID to form a preliminary training data set; and performing optimization processing on the preliminary training data set to finally obtain a training data set for text risk review. The training data set generated by the method has integrity, accuracy, balance and timeliness, and high-quality training samples can be provided for a text legal compliance risk review model.

The utility model belongs to the technical field of automobile electronic equipment, and particularly relates to an automobile pixel screen which comprises a shell, a circuit mainboard, LED lamp beads, a grid display cover, a diffusion film and a PC board. The grid display cover is provided with a grid structure, the grid structure is arranged on one side of the LED lamp beads, the diffusion film is arranged on the grid display cover, and the PC board is arranged on one side of the diffusion film and connected to the shell. According to the automobile pixel screen provided by the invention, the LED lamp beads emit light sources, the light sources pass through the grid display cover, the grid display cover independently presents the light sources emitted by each LED lamp bead through the grid structure, and then the effect of the single LED lamp bead is more uniformly presented through the microstructure of the diffusion film to form an image; the image information can clearly indicate the specific driving plan of the vehicle to pedestrians or other vehicles, misunderstanding and traffic chaos are avoided, the potential risk of traffic accidents is reduced, more information can be displayed, and effective interaction between the vehicle and traffic participants outside the vehicle is achieved.

The invention discloses an optimization regulation and control method for interaction between an industrial load cluster containing multiple production modes and a power grid and a medium, and belongs to the technical field of interaction between the industrial load cluster and the power grid in the multiple production modes. The method comprises the following steps: based on acquired industrial load information, performing data processing through an industrial load data preprocessing model to obtain industrial load parameters; constructing an industrial load operation model of multiple production modes based on the industrial load parameters; based on the industrial load operation model of the multi-production mode, constructing a multi-objective optimization model; and solving the multi-objective optimization model by using a multi-objective optimization algorithm, and outputting an optimized regulation and control operation time sequence result based on the industrial load operation model of the multi-production mode. According to the method, industrial loads of multiple production modes are considered, an aggregation cluster refinement model is established, optimal regulation and control and diversified target requirements between the power grid and the industrial load cluster are achieved, and economic, green and low-carbon coordinated development of the power grid and the industrial loads is promoted.

The application relates to the technical field of robots, and discloses a foldable robot for old-age service, which comprises a trunk structure, the outer wall of the trunk structure is provided with an arm assembly, the bottom of the trunk structure is provided with a waist assembly, the outer wall of the waist assembly is provided with a leg assembly, the top of the trunk structure is provided with a head joint, and the outer wall of the head joint is provided with an interactive screen. The vertical folding design is adopted, the waist assembly is used to realize 180-degree bending, the folding steps are only three, compared with the traditional horizontal folding mode, the vertical folding mode is shorter in time consumption and simpler in operation, the trunk and the arm are closely combined with the leg wheel foot structure after bending, the space utilization rate is obviously improved, the vertical folding mode is perfectly suitable for the storage and placement requirements of small space environments such as home-based old-age care and old-age homes, meanwhile, the auxiliary wheels are unfolded to form a triangular supporting structure with the main wheels, the stability of the robot in indoor ground walking in the old-age care scene is effectively ensured, and the light weight and the motion stability are considered.

The application discloses a drug target interaction prediction method based on protein sequences, comprising the following steps: constructing a drug target database; constructing a target feature extractor based on a pre-trained protein language model; constructing a drug feature extractor based on a pre-trained molecular model; constructing a feature learning method by using a self-attention mechanism, constructing a drug target interaction learning method by using a cross-attention mechanism, constructing a predictor in combination with a linear layer, and building a prediction drug target interaction model; training and optimizing parameters of the drug target interaction prediction model to obtain an optimized drug target prediction model; inputting the drug target into the optimized prediction model to output a prediction result; and finally visualizing the attention score to mark potential active sites and important amino acid residues of the drug and the target. The application realizes the improvement of the prediction accuracy of the interaction between the drug and the target based on the protein sequence, and realizes the explainability of the deep learning model.