323results about How to "Add depth" patented technology

The invention relates to the technical field of multi-agent systems, and discloses a multi-agent and multi-mode alignment interaction method and system for a review scene, and the method comprises the steps: mapping real-time multi-mode data into a local belief vector through a heterogeneous agent cluster, and calculating the spatial divergence to determine a global cognitive entropy; interaction time sequence gating logic based on entropy flow differential is established, and active alignment is triggered when the global cognitive entropy is larger than a convergence threshold value and a first-order derivative is smaller than a damping threshold value; according to the method, through entropy flow differential control and an active semantic disturbance closed loop, decision oscillation of the multi-agent system in the non-cooperative environment is eliminated, and the reliability of the multi-agent system in the non-cooperative environment is improved. Mathematical convergence of the belief state in an adversarial disguise scene is realized, and the system identification precision in a complex interactive game is improved.

The invention discloses an automatic compiling method and device for a test case, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: carrying out the structural analysis of a demand document for creative and creative transformation, and extracting the demand information of the demand document; the code warehouse is connected to obtain the source code and performs static analysis to generate code logic; establishing a semantic association mapping table of the demand information and the code logic, generating a test scene library according to the semantic association mapping table, and automatically generating a test case according to the parameter type and the constraint rule; and performing multi-dimensional verification on the generated test case to generate a verification result, and adjusting the priority of the test case according to the verification result. The method has the technical effects of improving marginal scene coverage depth and breadth, improving test case writing efficiency and accuracy, reducing manual dependence, and optimizing test case quality and execution pertinence.

The invention provides a multi-path information retrieval method and system based on a language model and uncertainty evaluation. The multi-path information retrieval method comprises the following steps: receiving a user query; performing semantic analysis on user query by using a pre-trained language model so as to output a quantitative uncertainty index in an unsupervised manner; dynamically determining a quantity ratio for controlling query generation and a balance parameter for controlling result sorting based on the index; based on the user query and the strategy parameters, generating and executing two groups of differential queries at least comprising exploratory queries and utilizable queries to obtain multiple paths of retrieval results; and combining multiple paths of results, and carrying out dynamic balance reordering between the correlation and diversity of the results according to balance parameters by adopting an ordering mechanism. According to the method, the retrieval strategy can be adaptively adjusted according to the uncertainty of query, and the coverage degree and diversity of results are remarkably improved.

The invention discloses a server test environment guarantee method and system based on dynamic simulation, a storage medium and computer equipment. The method comprises the steps that the air inlet temperature, real-time power consumption and heat dissipation strategy signals of a tested server and the actual environment temperature of an incubator are collected in real time; dynamically setting the temperature of the air inlet of the tested server as the target environment temperature of the incubator, and calculating the real-time temperature deviation between the actual environment temperature and the target environment temperature; if the real-time temperature deviation exceeds a preset threshold value, a dynamic PID control algorithm is triggered, a basic control quantity is obtained through calculation according to the real-time temperature deviation through the dynamic PID control algorithm, a dynamic compensation quantity is obtained through calculation according to the target environment temperature, the real-time power consumption and the heat dissipation strategy signal, and the heat dissipation strategy signal is obtained based on the basic control quantity and the dynamic compensation quantity. Generating a temperature control instruction of the incubator; according to the temperature control instruction, a refrigerating or heating device of the incubator is dynamically adjusted so as to guarantee the test environment of the tested server.

The invention discloses a time interference double-target electrical stimulation system, which comprises a signal generation unit used for generating multiple paths of carrier signals and adjusting the frequency, amplitude and / or phase of the carrier signals; the current output unit is used for converting the multiple paths of carrier signals into multiple paths of carrier currents, and electrical isolation and intermodulation suppression are provided between the multiple paths of carrier currents; the electrode unit is electrically connected with the current output unit and comprises a plurality of electrodes and a position subunit, the plurality of electrodes are used for receiving the multi-channel carrier current so as to discharge in an attached target area, and the position subunit is used for determining the attaching position of each electrode; and the control unit is used for controlling the discharge of the plurality of electrodes, detecting the impedance and carrier current at the plurality of electrodes to assist the position subunit in determining the fitting position and detecting the frequency and / or phase of the plurality of carrier current to control the signal generation unit to adjust the frequency and / or phase of each path of carrier signal. The system realizes independent stimulation of two target spots in a hardware-level time interference mode, has signal output with high stability and low mutual interference, and can perform real-time feedback regulation and safety protection.

The invention discloses a CVE-ATTamp (Cascade Vector Enhanced ATTamp) for a network security scene. The invention discloses a CK association fusion RAG construction method, and relates to the technical field of network security. The method comprises the following steps: (1) carrying out structured analysis and vectorization on CVE vulnerability information data, extracting features and fusing CVSS scores to carry out semantic embedding; (2) ATTamp; semantic modeling of a CK threat matrix is carried out, and a threat semantic space containing tactical level information is constructed; (3) heterogeneous knowledge association and graph construction: calculating cross-domain semantic similarity and establishing logic mapping between vulnerabilities and tactics in combination with expert rules to form a heterogeneous knowledge graph; and (4) attack logic-oriented RAG retrieval and generation: retrieving a key attack path sub-graph based on a hybrid scoring mechanism, and driving a large model to generate a security analysis report with logic depth. According to the method, attack logic is stored through mapping, so that the problems that the traditional RAG lacks inference ability and security data fragmentation are solved, and the accuracy and tactical value of automatic threat analysis are remarkably improved.

The invention relates to the technical field of intelligent manufacturing and industrial internet of things, in particular to an intelligent real-time production line regulation and control system and method based on digital twinning, and the system comprises a state sensing and collection module which is used for obtaining the real-time operation parameters of production equipment, material flow state information and environment disturbance characteristics of a production line; the digital twin modeling module is used for fusing multi-source data, constructing accurate mapping of a production line physical entity and a virtual model through a twin model driven by dynamic data, and predicting a performance degradation trend and a disturbance propagation path of production line equipment in real time; the intelligent decision-making module is used for generating a production line real-time scheduling strategy through a distributed collaborative reinforcement learning algorithm and outputting a production line regulation and control instruction set; and the real-time regulation and control feedback module executes production line regulation and control actions through a multi-target dynamic balance algorithm and automatically generates a production line production optimization report with equipment health degree compensation. Therefore, the problems of static model construction, lagging of a decision mechanism, lack of regulation and control feedback and the like in the prior art are solved.

The invention discloses a power production event type identification and grade evaluation method based on artificial intelligence, and belongs to the field of power safety production, and the method comprises the steps: receiving event description information inputted by a user, extracting event key elements through a natural language understanding model, converting the event key elements into query vectors, and obtaining the query vectors; searching related knowledge fragments in a pre-constructed electric power professional knowledge base, combining the event description information, the key elements and the knowledge fragments into enhanced cue words, inputting the enhanced cue words into a large language model subjected to field fine tuning, and finally, performing comprehensive analysis by the large language model to obtain the enhanced cue words. And generating a structured research and judgment result containing the event type, the level, the research and judgment basis and the submission requirement. According to the method, accurate and efficient research and judgment of the electric power security event are realized by fusing the retrieval enhancement generation technology and the field fine tuning large model, and interpretability and traceability of a conclusion are ensured by outputting research and judgment basis through the requirement model.

The invention discloses a virtual simulation data intelligent generation and enhancement method based on deep learning. The method comprises the following steps: step 1, collecting and converging multi-source heterogeneous simulation data; 2, simulation data preprocessing and feature extraction; step 3, constructing and configuring a depth generation model; step 4, iterative training and optimization of the depth generation model; step 5, intelligently generating and synthesizing new simulation data; step 6, generating data quality verification and enhancement feedback; step 7, carrying out controllability adjustment and directional enhancement on the generated data; and 8, model online learning and data generation closed-loop optimization are carried out. The method can automatically learn the internal law and distribution of the simulation data, efficiently generate highly-vivid and diversified new simulation data meeting specific requirements, and deeply enhance the existing limited data, thereby significantly reducing the simulation data acquisition cost, improving the data quality and richness, and improving the simulation data acquisition efficiency. And powerful data support is provided for development and test of a virtual simulation system and simulation-based AI model training.

The invention relates to the technical field of smart tourism, in particular to a personalized scenic spot content generation method, system and device based on a multi-modal knowledge graph and a medium, and the method comprises the steps: collecting multi-modal data of a scenic spot, and constructing a structured multi-modal scenic spot knowledge graph based on the multi-modal data; obtaining personalized data provided by the tourist, and constructing a personalized portrait of the tourist based on the personalized data; in response to an operation of acquiring an image in a scenic spot, identifying the scenery in the image, and extracting a corresponding initial knowledge subset from the multi-modal scenic spot knowledge graph according to an identification result; performing personalized screening and expansion on the knowledge nodes in the initial knowledge subset by calculating the matching degree between the knowledge nodes in the initial knowledge subset and the tourist interest in the personalized portrait of the tourist, and dynamically binding multi-modal resources to generate a personalized knowledge graph; and presenting the personalized knowledge graph. According to the invention, the multi-mode scenic spot knowledge experience of which the structure is matched with the interest and the knowledge background can be provided for tourists.

The application discloses a kind of emotion evaluation and intervention method and system based on multi-modal data.Through terminal synchronous acquisition voice, face, screen tremor and so on multi-modal data;Reaction mode vector is generated based on context information and data verification fusion;The composite emotional state of user is determined using emotional emergence model.At the same time, personalized emotional causal diagram is constructed and updated, and the enhanced state vector is generated by extracting key causal path features.The vector is input into the intervention agent to output intervention actions;After execution, the emotional state is evaluated again and the reward is calculated, and the system model is updated online.The application realizes accurate emotion evaluation and closed-loop adaptive intervention that strikes the root.

The present application relates to the technical field of pipe network data digital management, in particular to a multi-modal fusion pipe network data digital archive intelligent management system, the present application extracts the features of inspection images, equipment nameplate texts and on-site recordings through parallel special models, generates unified multi-modal feature embedding using cross-modal alignment and attention mechanism, automatically discovers the internal structure of data and extracts theme labels through density clustering and theme generation model, trains a double-branch classifier to realize category determination and theme labeling of new data, then stores the classified and labeled data in combination with data fingerprints in a distributed manner, introduces a blockchain verification mechanism to store operation logs on the chain for evidence, finally constructs a knowledge graph, supports users to perform multi-hop association search and full life cycle operation traceability through a visual interface, and improves the automation level and data security of pipe network archive management.

The invention provides a lightweight human shape detection method and device based on improved RTDETR, a medium and a product, and the method comprises the steps: obtaining a data set for human shape detection, and dividing the data set into a training set, a verification set and a test set; an improved RTDETR model is constructed, an ES Block is used in the improved RTDETR model to replace a Basic Block in the RTDETR feature extraction network before improvement, and the ES Block comprises an OfficientVIT Block and a SimAM attention module which are connected in sequence; the NWD Loss is used as a loss function of the improved RTDETR model; training the improved RTDETR model by using a training set, verifying the improved RTDETR model by using a verification set and testing the improved RTDETR model by using a test set to obtain a trained improved RTDETR model; and inputting the to-be-detected image into the trained improved RTDETR model for reasoning to obtain a human shape detection result of the to-be-detected image. By means of the technical scheme, the human shape detection precision and small target human shape detection in a security and protection monitoring complex scene can be improved.

The invention relates to the technical field of knowledge maps, can be applied to an intelligent traffic operation management scene, and discloses an intelligent decision-making method, device, equipment and medium based on a semantic knowledge map, and the method comprises the steps: carrying out the analysis, cleaning and complementation of multi-source heterogeneous data, and generating a standardized event flow under a unified space-time reference; constructing a semantic knowledge graph containing entities, attributes, relationships and business logic, injecting the standardized event streams into the graph to complete pattern matching, generating a structured knowledge packet and realizing business logic updating; and scene analysis is carried out based on the structured knowledge packet and the semantic knowledge graph, an analysis result is output, a decision suggestion is generated, and closed-loop processing from data to decision is realized. According to the method, multi-source data is converted into structured knowledge and semantic reasoning is introduced, so that the analysis result can support decision generation, and the semantic understanding ability and decision support efficiency of data fusion are improved.

The invention discloses an intelligent detection method and system for garment quality inspection, and relates to the technical field of computer vision and intelligent manufacturing. The method comprises the following steps: carrying out pixel-level feature analysis on two-dimensional image data, identifying a sewing line and a printing area, and mapping the sewing line and the printing area to a unified space coordinate system; reconstructing the three-dimensional surface form of the garment based on a stereoscopic vision algorithm, and calculating the dimensional deviation of key parts; converting the spectral data into a CIELAB color space, and carrying out optical distortion correction on local chromatic aberration in combination with a three-dimensional curvature; and under a unified space coordinate system, performing correlation analysis on the stitches, the dimensional deviation and the corrected space distribution, identifying a composite defect which cannot be judged by a single defect, generating a correlation defect identifier, and finally forming a quality report. The technical problems that in the prior art, local chromatic aberration is easily influenced by three-dimensional curved surface deformation and optical distortion of ready-made clothes, information such as dimensional deviation, sewing and printing defects and the local chromatic aberration is isolated, comprehensive correlation analysis is lacked, and consequently the detection accuracy is insufficient are solved.

The application provides a laser impact combined surface modification method for a bearing raceway surface, a pre-processing raceway region and a retainer matching surface, the raceway region reserving a processing allowance layer; a constraint layer is applied to the raceway region; the raceway region is micro-scale laser impact strengthened for at least 3 times without an absorption protective layer, a deep and uniform plastic strengthening layer is formed; the processing allowance layer is removed; an absorption protective layer is attached to the retainer matching surface; and array-arranged oil storage pits are formed on the retainer matching surface through laser impact forming. The method can form a plastic strengthening layer on the raceway region surface through micro-scale laser impact strengthening, can significantly improve the rolling contact fatigue performance and wear performance of the bearing, and can form oil storage pits on the retainer matching surface through laser impact forming, the oil storage pits can lock lubricating oil through the surface tension of the oil, and the problem of insufficient lubrication of the bearing raceway surface is solved.

The utility model discloses a kind of live pig slaughtering process carcass bacterium-reducing equipment, it is related to slaughtering bacterium-reducing technical field, including first baffle, second baffle, water pump, water supply line and motor, the first baffle inside is provided with cleaning mechanism, the cleaning mechanism includes water pump, cleaning roller, motor, water supply line and high pressure spray head, the high pressure spray head is set below water supply line, the water supply line is set above water pump, the motor is installed above cleaning roller, cleaning mechanism is through the double action of high pressure spray head water spraying and cleaning roller mechanical friction, realize the stereoscopic removal of carcass surface stain and bacteria.

The application discloses a network type energy storage power station capacity planning and configuration optimization method based on multi-source data, relates to the technical field of configuration optimization, and comprises the following steps: calculating the cavity length and cavity height of a subsurface cavity based on the sound wave response signal of a corridor ground surface structure; calculating the cavity risk coefficient of a target corridor based on the cavity length and cavity height; calculating the updated discharge depth based on the cavity risk coefficient and the planning discharge depth in an electric station design parameter table; generating a shadow band section of the target corridor, marking the energy storage units of the energy storage power station as high-risk units or low-risk units based on the shadow band section; calculating the high-risk power sum of all the high-risk units, and calculating the high-risk capacity sum of all the high-risk units based on the updated discharge depth. The application can improve the reliability of the operation safety of the power station.

The invention discloses an abnormal behavior identification method based on a visual large model and a cognitive Agent, and relates to the technical field of computer vision, and the method comprises the steps: collecting an RGB image and an infrared thermal imaging IR image in a monitoring scene, and extracting a human body key point sequence; performing time sequence difference processing on the key point sequence, and constructing a skeleton velocity vector containing a motion trend; inputting the skeleton velocity vector into a Mamba model, adjusting model parameters by using a selective state space mechanism, and carrying out long-time-sequence modeling on the action sequence; predicting the speed variation of the next frame by adopting a residual prediction architecture and reconstructing a human body posture; and calculating an abnormal score according to the prediction error, triggering a cognitive Agent when the score exceeds a preset threshold value, calling a visual large model (VLM) to perform semantic analysis on the current scene environment, and generating a natural language warning containing an abnormal type and an environmental cause. According to the method, the forgetting problem of a traditional model in a long sequence and the jitter problem of a prediction action are solved.

This invention provides a method and apparatus for generating vocabulary memorization content, relating to the field of data processing technology. The method includes: acquiring multidimensional feature data of a target word to be memorized and a target user; wherein the multidimensional feature data includes at least the target user's personalized image features and learning stage identifier; constructing a target scene corpus based on the semantic information of the target word to be memorized; constructing structured prompt information for driving a generative model based on the target word to be memorized, the target scene corpus, and the multidimensional feature data; inputting the structured prompt information into a pre-trained generative artificial intelligence model to generate a dynamic mnemonic comic, and displaying the dynamic mnemonic comic on a terminal device; wherein the dynamic mnemonic comic includes a character image generated based on the personalized image features, and the character image interprets the meaning of the target word to be memorized within the context defined by the target scene corpus.

This invention discloses a real-time evaluation method for photovoltaic panel defects and performance based on multispectral imaging, belonging to the field of computer processing technology. The method includes the following steps: S01, emitting multispectral light including visible light, near-infrared, and thermal infrared bands to the photovoltaic panel, and simultaneously receiving reflection and radiation signals based on the multispectral light to obtain a multispectral image dataset; wherein, the dataset includes visible light images, photoluminescence images in the near-infrared band, and thermal infrared images; S02, performing registration and fusion processing on the multispectral image dataset to generate a registered multispectral fused image. This invention, through multispectral information fusion and intelligent analysis, achieves simultaneous diagnosis of internal and external defects of photovoltaic panels and quantitative evaluation of power generation performance, significantly improving detection efficiency and maintenance accuracy.

The application relates to the technical field of network security, in particular to a Java Restful interface security test method based on static analysis, which comprises the following steps: generating a Jimple intermediate representation of source code of a target Java application; performing data flow analysis based on the Jimple intermediate representation to generate a complete data flow graph; identifying a pollution source and tracking a pollution propagation path on the basis of the data flow graph, judging whether a pollution object reaches a convergence point, and determining a vulnerable interface; extracting an interface routing signature in the pollution analysis process to generate routing signature information; grouping interfaces based on parent routing of the interfaces, performing interface security test in combination with the routing signature information, introducing a reinforcement learning method to dynamically optimize a test strategy, performing parameter variation and attack load injection of a test case on the vulnerable interface; and setting a security monitoring strategy in a dynamic plug-in manner, and completing interface security risk judgment according to recorded logs and the test case.

This invention discloses a method and system for predicting RNA binding protein binding sites on RNA without targeting, relating to the field of bioinformatics. The method includes the following steps: acquiring raw RNA structure data; expanding and filtering the preprocessed data; training an RNA analysis model using the filtered data; processing the RNA to be analyzed using the trained RNA analysis model, calculating the probability that each nucleotide is single-stranded, and obtaining a structure score; identifying low-accessibility regions based on the difference between the structure score output by the RNA analysis model and the structure score calculated by the original method; and identifying potential RNA binding protein binding sites by comparing the signal difference with that of the original method in a single RNA structure detection experiment. This invention utilizes the STONE method to improve the accuracy of RNA structure analysis in low-accessibility regions, and uses the improved difference to infer RBP binding sites, thereby improving the accuracy of RBP binding site identification.

This invention discloses a wind-resistant reinforced intelligent utility pole, which relates to the field of power construction technology. A connecting base is positioned on the upper side of the utility pole and remains fixed thereto. The lighting fixture is fixedly connected to an external support rod, which in turn is fixedly connected to a mounting frame. The mounting frame is inserted from the top of the utility pole, allowing it to mate snugly with the connecting base. A threaded connection exists between the mounting frame and the connecting base, improving installation efficiency and supporting the lighting mechanism. A rotating device is positioned on an annular groove. When the utility pole encounters strong winds, the wind force acts on the rotating device, causing it to rotate and reducing the frontal wind force and wind load. Furthermore, when the utility pole is installed on the adjustment device, the pole aligns the external plate with the U-shaped plate. The external plate and the U-shaped plate are then plugged in and threaded together, enhancing the fixation effect between components.

This invention relates to the field of multimodal sentiment analysis technology, and in particular to a method and system for multimodal sentiment analysis based on sequential translation under uncertain and missing modalities. The method includes: acquiring multimodal sentiment data, including visual, textual, and auditory modalities; constructing a multimodal sentiment analysis model based on sequential translation, firstly by extracting self-attention encoding features of each modality using a Transformer encoder; and then designing a bidirectional sequential translation architecture centered on the textual modality. This invention improves the utilization of textual modal features in the feature fusion process, thereby enhancing the quality of multimodal fusion features and providing strong support for subsequent complex sentiment analysis.

The invention discloses a parking lot operation management system and method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the steps: vehicle feature collection, preprocessing, coding, key management, information storage and similarity verification, and the generation of a high-discrimination virtual identity label through the fusion of visual, millimeter wave radar and acoustic multi-modal data. In combination with adaptive key binding and a dual-path verification mechanism, privacy security is enhanced while identification precision is guaranteed, and the system comprises a vehicle feature acquisition module, a feature preprocessing module, a feature coding module, a key management module, an information storage database and a similarity verification module. The objective of the invention is to solve the problems of identification failure and data security loss in scenes without license plates, temporary license plates or vehicles with similar appearances due to dependence on physical license plates in the prior art.

The invention discloses a cryptographic intelligent question and answer method based on maximum marginal correlation retrieval, and relates to the technical field of natural language process.The method comprises the steps that firstly, a cryptographic field document is subjected to analysis and semantic partitioning, and the integrity of mathematical formulas and algorithm logic is ensured by dynamically calculating text similarity; and information splitting caused by traditional fixed partitioning is avoided. And then, obtaining knowledge fragments which are related to the question and have various contents from the vector database by utilizing a maximum marginal correlation retrieval algorithm, and providing multi-angle reliable contexts for answer generation. And finally, through field adaptive prompt engineering and dynamic parameter adjustment, guiding the large language model to play a role of a cryptography expert based on the retrieved context, and generating an accurate personalized answer meeting the user demand.

The application discloses a pepper seed oil squeezing device, and particularly relates to the technical field of squeezing pretreatment, which comprises a pretreatment box, a movable tooth cavity block, a plurality of tooth gaps, a power unit, a tooth baffle and a linkage assembly. The movable tooth cavity block is slidably arranged in the pretreatment box. The plurality of tooth gaps are arranged on one side of the movable tooth cavity block. The power unit is arranged on the other side of the movable tooth cavity block. The tooth baffle is slidably arranged on the inner wall of the movable tooth cavity block. The tooth baffle is provided with the linkage assembly. The device can simultaneously crush the pepper seeds according to the pre-squeezing extrusion, and synchronously supply the pepper seeds with the biological enzyme solution at different positions according to the crushing power. The device can improve the biological squeezing pretreatment efficiency, and significantly save the energy consumption of the additional driving components, thereby solving the problems of low squeezing pretreatment efficiency and poor energy saving.

This invention relates to the field of power engineering management and control and virtual power plant operation collaboration technology, specifically to a big data-based intelligent management and control system and method for power engineering. It collects and evaluates the quality of multi-source heterogeneous data from power engineering sites to obtain reliable data for engineering risk prediction, while simultaneously extracting feature data related to virtual power plant operation. Furthermore, it identifies and aggregates dispatchable load resources at the engineering site to form standardized virtual load packages. Combining the operational demand signals of the virtual power plant with the engineering risk status, it generates dispatch decision schemes through collaborative optimization calculations. Blockchain technology is used to ensure the reliable storage of dispatch instructions, execution, and result data, and based on this, automatically calculates collaborative benefits. This effectively solves the problem in existing technologies where power engineering management and control data are disconnected from virtual power plant operation, preventing a shift from passive risk warning to proactive value mining.

This invention discloses a method and system for verifying the integrity of approval data in a trusted data space, relating to the field of data security technology. The method includes: assessing and determining an approval risk coefficient and an approval urgency index based on the data attribute information and approval-related characteristics of the data to be approved; calculating and obtaining an appropriate approval time limit based on the approval risk coefficient and approval urgency index; using a time limit shorter than the appropriate approval time limit as an efficiency constraint to optimize the initial approval strategy, selecting the combination of approval nodes and the combination of approval node verification depths corresponding to the minimum predicted approval error probability as the appropriate approval scheme; and performing integrity verification on the data to be approved within the trusted data space according to the appropriate approval scheme. This invention effectively improves the integrity, reliability, and processing efficiency of the entire approval data chain in a trusted data space.