13results about How to "Identifiable" patented technology

This invention provides an application of the peptide Nod-T3 in the preparation of drugs for treating lung diseases. The Nod-T3 peptide is derived from human protein and has a significant inhibitory effect on chronic lung inflammation and fibrosis caused by smoking. It can be used to treat COPD and other smoking-related lung diseases. It also has high biocompatibility and low toxicity, and has the potential and development value to become a new type of peptide drug.

The present application relates to the field of coating parameter self-optimization, and discloses a coating process parameter self-optimization system and method fusing model self-learning, wherein a coating process parameter self-optimization method fusing model self-learning comprises the following steps: collecting process parameters, production conditions, equipment power states and detection result data of multiple batches of coating production in real time; aligning and correlating the data according to the process sequence to form a unique mapping relationship; reversely determining corresponding process parameter nodes and working condition node sets to generate a consistency index; jointly comparing the consistency index and the corresponding data chain distribution to output corresponding working condition drift identifiers; introducing the consistency index and the working condition drift identifiers as constraint conditions into a parameter update model to output a constrained parameter update result; and writing the corresponding new round of detection results into the unique mapping relationship to generate an incremental updated mapping relationship and a reachable state space. The present application has the advantage of improving the stability of the optimization result.

The invention relates to the technical field of energy consumption management, in particular to an enterprise energy consumption data driven multi-dimensional carbon neutralization path simulation and decision-making system which comprises an energy consumption data sensing module, an index linkage recognition module, a path structure adjustment module, a control instruction deployment module and a simulation decision induction module. According to the method, the energy consumption data structure with linkage characteristics is constructed through merging and time sequence alignment of the multi-dimensional data of the equipment output power, the product unit energy consumption and the regional carbon emission intensity, the path structure is dynamically adjusted according to the index triggering direction after the data hopping state is identified, and stage path replacement is realized through number matching; and generating an equipment execution instruction by combining the load corresponding to the path number and the control parameter, and synchronously completing comparison and iteration of the simulation path, so that the generation process of the carbon neutralization path has dynamic response capability, jump identification capability and path evolution capability, and the real-time cooperation efficiency between a carbon emission reduction strategy and an energy consumption execution strategy is remarkably improved.

This invention proposes a symmetrically arranged cross-wing unmanned aerial vehicle (UAV) system, relating to the field of UAVs. It includes a fuselage structure, a power module, and a flight control module. The fuselage structure comprises a cylindrical fuselage and four wings symmetrically arranged in a cross pattern around the cylindrical surface of the fuselage; the four wings are arranged in an X-shape or a cross shape. The power module includes motors and propellers. The motors are located at the wingtips, with their output shafts aligned with the fuselage axis and facing the tail of the fuselage. The propellers are connected to the motor output shafts. The flight control module is located inside the fuselage and is used to control the output speed of the four motors. This system combines the advantages of a quadcopter FPV and a fixed-wing UAV, generating lift from the wings while also cruising and sprinting in fixed-wing form. Furthermore, by changing the motor speeds, it can control the pitch, yaw, and roll attitude of the UAV, eliminating the need for separate control surfaces, thus simplifying the structure and reducing costs.

This invention relates to the field of image processing technology, and more particularly to a method and system for assessing the quality of prefabricated construction based on image processing. The method includes the following steps: after removing the EVA transport protective padding that came with the prefabricated construction components, a panoramic image of the component splicing surface is captured using an industrial camera to obtain an original image containing the natural adhesion marks of the padding; multi-scale edge enhancement processing is performed on the original image to extract the contour data of the adhesion marks, and the global flatness of the component splicing surface is calculated based on the deformation features of the contour data; an industrial camera is used in a ring array to capture images of the pre-reserved grouting holes in the components, and the grouting hole boundaries are extracted after contour sharpening processing of the images; the three-dimensional axis of the grouting holes is constructed by combining the reflective features of the inner sidewalls of the holes. This invention achieves accurate detection and standardized assessment of the quality of prefabricated components through multi-polarized light sources and ring camera imaging technology, ultimately improving the accuracy of construction quality assessment.

The application discloses a pedestrian re-identification method and device integrating multi-head self-attention and convolution. The proposed double-layer multi-head self-attention (DL-MHSA) divides a feature matrix by a grid, and decomposes the MHSA into two layers, the first layer only calculates the features in a single grid, and the second layer calculates the overall features on the basis of the grid, and the two-step operation reduces the calculation complexity; the DL-MHSA is introduced into the OSNet, the features of different scales and global features are fused, the model can obtain more recognizable features for the input pictures, and the pedestrian re-identification performance is improved; and the model is pre-trained by using a large-scale unlabeled pedestrian dataset, the model obtains high-level semantics beneficial to the task, the performance of subsequent fine-tuning training on a labeled dataset is improved, and the generalization capability of the model is stronger.

This invention provides a multi-agent traceable decision-making system and method for environmental data mining, belonging to the interdisciplinary field of artificial intelligence and environmental informatics. The system includes: a task complexity assessment module, a multi-agent conditional collaboration module, an arbitrator triggering and adjudication module, an environmental knowledge graph module, a feedback learning optimization module, and a decision tracing and visualization module. The method includes the following steps: Step 1: Task complexity assessment and collaboration mode allocation; Step 2: Parallel processing and dynamic collaboration of two intelligent analysts; Step 3: Consistency check and arbitration triggering; Step 4: Arbitrator adjudication and weight integration; Step 5: Human expert correction and weight optimization feedback; Step 6: Decision tracing and weight visualization. This invention enables more accurate decision optimization, significantly improves the professionalism and accuracy of decision-making, and possesses the ability to proactively identify and prevent potential problems.

This invention discloses a dynamic pressure-adaptive arterial puncture closure system and method, relating to the field of medical device technology. The system includes: a pressure sensing module for acquiring pressure distribution information at different circumferential locations within the blood vessel and sensing pulsating pressure signals in real time; an intelligent control module electrically connected to the pressure sensing module for receiving and processing the pulsating pressure signals and generating dynamic closure control commands according to a preset adaptive algorithm; and a mechanical execution module electrically connected to the intelligent control module for receiving the dynamic closure control commands and driving the closure element to apply a dynamically adjustable radial closure force to the arterial puncture site. This invention can adapt to the dynamic changes in the patient's blood pressure in real time and automatically. Through a dynamic pressure adaptive mechanism, it achieves a fundamental shift from "static compression" to "dynamic adaptive compression," minimizing vascular wall damage while ensuring hemostasis and significantly reducing the risk of complications.

The utility model discloses a kind of luggage locks, including lock shell, lock hook, first movable rod, button, slider, swing piece, password unlocking device, biometric unlocking device, lock cylinder unlocking device, lock hook is rotatably installed in lock shell;First movable rod is used to move lock hook rotation and open lock;Button is slidably installed in lock shell;Slider, first movable rod and button three one of them and the transmission cooperation of other two;Swing piece is rotatably installed in lock shell, swing piece can prevent slider sliding to restrict button sliding;Password unlocking device and biometric unlocking device are set in lock shell, password unlocking device and biometric unlocking device can all drive swing piece to rotate to unlocking position;Lock cylinder unlocking device can drive first movable rod to move.The luggage lock provided by the utility model has password unlocking, biometric unlocking and lock cylinder unlocking function, and the transmission structure for driving lock hook to rotate and open lock is simpler.

The application relates to the technical field of equipment management, in particular to a full life cycle management system and method of mechanical equipment, which comprises a data analysis module, a feature analysis module, a degradation identification module, a stage determination module and a management early warning module. In the application, a unified operation data set is formed by collecting equipment operation vibration voltage signals and combining the operation duration and the fault duration, comprehensive analysis is performed on the fault cumulative duration fault density change and vibration change in the life cycle operation section, the equipment operation state change trend is identified and the performance degradation section is continuously marked, the degradation section proportion is counted, the performance degradation stage is identified by combining the operation section interval change, the equipment operation load and the highest rotating speed are adjusted on the basis of the identification result, and the degradation stage operation duration is recorded, so that the equipment operation state change has continuous analysis and trend identification capability, and the equipment maintenance arrangement and operation management have stable basis.

This application discloses a training method for a character recognition model, a character recognition method, and related equipment. The training method includes: acquiring a training dataset, which includes sample images and corresponding ground truth labels for the sample images, wherein the ground truth labels are formed by concatenating the positional information of text regions in the sample images and the actual text in the text regions; performing masking processing on the actual text in the ground truth labels to obtain a first mask label; encoding the sample images through an encoding module in the character recognition model to obtain a first image feature vector of the sample images, and performing character recognition on the first image feature vector based on the first mask label through a decoding module in the character recognition model to obtain a first character recognition result corresponding to the sample images; and optimizing the character recognition model based on the ground truth labels corresponding to the sample images and the first character recognition result.

The invention relates to the technical field of metal plate bending processing, in particular to a real-time collision detection method based on self-adaptive bounding boxes and machine learning, which comprises the following steps: firstly, carrying out geometric feature analysis on each three-dimensional model, and calculating the fitting degree between the volume of the model and the volumes of different bounding boxes (sphere, AABB and OBB); and adaptively selecting and constructing an optimal bounding box with the highest space utilization rate. In a real-time detection stage, aiming at an object pair to be detected, 24-dimensional geometrical relationship feature vectors between bounding boxes of the object pair to be detected are extracted, and the 24-dimensional geometrical relationship feature vectors are input into a pre-trained lightweight multilayer perceptron model. The model outputs continuous collision probability values, and three-level intelligent classification (high-probability collision, critical state and safety) is performed according to a preset threshold value, so that scheduling of accurate detection resources is guided. According to the method, the package tightness of the bounding box can be improved from the source, and the boundary condition is accurately pre-judged by utilizing machine learning, so that the efficiency of real-time collision detection is improved while the detection precision is ensured.

This invention discloses an adaptive anomaly removal method and system for flow calibration. The method includes: performing adaptive water level segmentation processing on a cleaned historical water level and flow dataset to obtain several segmented historical water level and flow datasets and constructing several corresponding local calibration models; optimizing the parameters of the several local calibration models according to an improved differential evolution method to obtain their respective optimized local calibration models; inputting each segmented historical water level and flow dataset into its corresponding optimized local calibration model for processing to obtain the calibrated flow sequence for each segment; performing multi-criteria statistical testing on each segmented deviation sequence; if the test is successful, the calibrated flow sequence for each segment is taken as the successfully calibrated flow sequence for that segment; if the test fails, adaptive removal processing is performed until the test is successful. This invention enables automated and high-precision calibration of flow data output by automatic flow meters.