303 results about "Information layer" patented technology

The invention discloses a semantic judicial contract compliance automatic generation and examination system based on a DIKWP artificial consciousness model. The system is constructed according to five layers of data, information, knowledge, wisdom and intention, wherein the data layer integrates multi-source information; the information layer enables terms to be semantized and disambiguated; the knowledge layer performs rule matching and compliance judgment by using a legal knowledge graph; the wisdom layer automatically corrects the risk terms based on a fair principle and performs scene simulation; and the intention layer is embedded into targets of all parties to ensure that the contract is consistent with the compliance intention. The system process covers the whole process from intention analysis, knowledge reasoning to intelligent generation and intention negotiation, and finally a compliance contract and an audit report are output. The system is provided with a multi-language semantic adaptation and intelligent negotiation interface, and convenient access can be realized through an API (Application Program Interface). The system realizes integration of contract generation and review, intention driving and decision interpretability, can effectively reduce compliance cost and dispute risks, and is suitable for multiple scenes such as finance, e-commerce, government purchase and the like.

The invention discloses an advertisement information flow management method and platform applied to multivariate visual design, and belongs to the technical field of advertisement design, and the method specifically comprises the steps: dividing a screen interface into dynamic grid regions, and carrying out the comprehensive calculation based on user interaction behaviors and content semantic features, mapping the dynamic grid region into a semantic gravitational field representing user attention distribution; generating an initial advertisement container in a low-gravitational area at the edge of the screen, driving the container to migrate to a high-gravitational area according to the intensity gradient distribution of the semantic gravitational field, performing path optimization in the migration process, and dynamically adjusting the form of the container according to the visual density of a matched target area; dynamically adjusting the parameters of the advertisement container according to the semantic features of the native content of the target area and the real-time interaction behavior of the user; the cognitive load of the user is evaluated in real time according to the interaction behavior of the user on the surface of the advertisement container, information level folding is triggered when cognitive overload is detected, and secondary information or all information of the advertisement is dynamically hidden.

The invention belongs to the technical field of electric power information physical system security, and discloses an urban power grid information physical system security situation early warning method based on cross-space risk propagation. A power grid physical layer and information layer coupling model and a cellular space false data injection attack model are constructed, and a fault cross-space propagation mechanism is simulated through an event-driven cellular automaton theory; an integrated kernel extreme learning machine model is adopted to predict the operation state of the power grid, multi-dimensional data fusion is realized through a radial basis kernel function, and an integrated structure is adopted to fuse a plurality of model prediction results so as to improve the model prediction precision; and establishing an early warning system including voltage out-of-limit, line overload and load loss indexes, and dynamically distributing weights and dividing early warning grades in combination with an entropy weight method. According to the method, the problem of low precision of urban power grid security situation early warning under multivariate disturbance is solved, and the accuracy and robustness of security situation early warning can be effectively improved.

The invention relates to the technical field of robot navigation, and particularly provides a multi-layer map construction method for substation inspection navigation, which comprises the following steps: generating a point cloud map according to three-dimensional point cloud data of a substation, and marking passable areas, obstacle positions and road topological structures to obtain a geometric information layer; identifying the type of the equipment according to the image data of the equipment of the transformer substation, and generating a priority label of the equipment based on the type of the equipment to obtain an equipment information layer; according to the topographic relief degree matrix of the transformer substation, dividing the transformer substation environment into a flat area, a non-flat area and an obstacle area to obtain a topographic information layer; and carrying out space alignment on the geometric information layer, the equipment information layer and the topographic information layer to obtain a multi-layer map with a unified coordinate system. The problems that in the prior art, a transformer substation inspection map is single in information dimension, poor in reliability and not beneficial to inspection are solved.

The invention discloses infrared night vision AR (Augmented Reality) intelligent glasses based on multispectral fusion, and relates to the technical field of infrared intelligent application. High-precision scene perception in a low-light / light-free environment is realized by fusing dual-channel data of low-light imaging and infrared thermal imaging and combining cross-modal feature matching and dynamic pose compensation; an environment detail structure is restored by a low-light image enhancement technology, thermal feature targets such as organisms are accurately recognized through thermal imaging target segmentation, and a three-dimensional environment model with space geometric information and target attributes is constructed through heterogeneous feature fusion; and dynamically adjusting the display transparency of the key target in the AR view field through a virtual information layer adaptive mixing mechanism driven by a hot target attribute, and finally outputting a virtual-real fused enhanced view, thereby breaking through the illumination limitation of the traditional AR glasses, and improving the visual effect of the AR glasses. And immersive augmented reality experience with panoramic detail perception and hot target accurate positioning is provided for the user in a dark environment.

The invention provides a railway vehicle production line digital twin system and method, and the system comprises a physical space layer which is used for obtaining the state information of a railway vehicle physical production line in real time; the information layer is used for performing information conversion and analysis on the state information of the railway vehicle physical production line to obtain processed railway vehicle production line information; and the virtual space layer is used for updating the railway vehicle virtual production line model based on the processed railway vehicle production line information, so that the railway vehicle virtual production line model corresponds to the railway vehicle physical production line. Through the digital twinning technology, digital transformation of the railway vehicle manufacturing industry is promoted, the production efficiency is improved, quality control is optimized, the maintenance cost is reduced, and the production flexibility is enhanced.

The invention discloses a transmission type communication system and method based on low-frequency carrier waves and high-frequency modulation. The transmission type communication system and method are suitable for complex medium environments such as deep sea, strata and biological tissues. Aiming at the contradiction that the traditional low-frequency communication bandwidth is insufficient and the high-frequency communication penetrating power is poor, according to the scheme, a low-frequency carrier wave (30Hz-100kHz) and a high-frequency modulation signal (such as OFDM (Orthogonal Frequency Division Multiplexing) and 256QAM (Quadrature Amplitude Modulation)) are fused through a nonlinear signal superposition technology to generate a composite carrier wave signal, long-distance penetration is realized by utilizing the low attenuation characteristic of the low-frequency carrier wave, and meanwhile, the data rate is improved through high-frequency modulation. Application scenes comprise deep sea detection (300-meter high-definition video return), a brain-computer interface (implantable antenna transmission neural signal) and an intelligent power grid (underground pipe network monitoring). Through the physical layer-information layer collaborative design, the physical boundary limitation of traditional communication is broken through, and high penetrability, high bandwidth and strong anti-interference capability are achieved.

The invention specifically relates to a federated learning-based distributed dyeing machine anomaly detection method, and relates to the technical field of industrial equipment anomaly detection and federated learning, and the method comprises the steps: compressing an obtained weight difference value, encrypting the weight difference value, and transmitting the weight difference value to a federated server; according to the method, a CNN-LSTM mixed structure is adopted for model training, space and time sequence characteristics are considered, and dyeing machine multi-sensor data association and abnormal hysteresis characteristics are adapted; incremental training and small-batch training strategies are adopted to solve the problem of computing power memory limitation of edge equipment, so that the model can be locally and stably trained in the dyeing machine, and network dependence is avoided; a compression transmission link, a dynamic sparse adaptation process stage and hierarchical quantification distinguishing of information levels are performed, so that the data volume is compressed, the transmission efficiency is guaranteed, key information is reserved, the federal learning process is stably operated in an industrial environment, and a dyeing machine production scene is comprehensively adapted from data processing to model training deployment; and a solid support is provided for abnormal detection landing.

The invention relates to the field of data management, and provides an equipment label information hierarchical storage method and device based on a prefix tree structure, the method comprises the following steps: caching equipment label information into a memory in the prefix tree structure, the prefix tree structure being a data structure combining a prefix tree and a linked list, each cached node holds a pointer pointing to a child node storage space on a disk; when the amount of data cached in the memory reaches a preset threshold value, newly adding or modifying the equipment label information cached in the prefix tree into a physical log file; after the newly-added or modified operation is completely written into the physical log file, the equipment label information in the memory is stored in the prefix tree file, and the prefix tree file is stored on a disk by adopting a structure of fusing a prefix tree with a B + tree. According to the invention, the problem of overlarge memory consumption of a full-memory storage scheme in the prior art is solved, and the memory occupation is obviously reduced.

The invention relates to the technical field of renewable energy consumption, in particular to a vehicle-hydrogen-steel collaborative green hydrogen fluctuation stabilizing method and system, a physical layer is provided with a wind-solar power generation device, an electrolytic hydrogen production device, a hydrogen storage buffer tank, a steel heat supply device, an electric vehicle and a V2G charging pile which are connected with one another through a hydrogen conveying pipeline and a power cable; the information layer takes the central regulation and control platform as a core, collects wind-solar power, hydrogen yield, steel hydrogen consumption and electric vehicle SOC by using sensors, and transmits the collected power, hydrogen yield, steel hydrogen consumption and electric vehicle SOC to the central regulation and control platform; the central regulation and control platform executes a hierarchical dynamic fluctuation regulation and control mechanism; when the fluctuation range of the hydrogen yield does not exceed a set value, the hydrogen is stabilized by controlling the hydrogen storage buffer tank to charge and discharge hydrogen; and when the fluctuation amplitude exceeds a set value, a V2G system is started, and stabilizing is carried out by controlling charging and discharging of the electric vehicle. On the premise that the special energy storage cost is not greatly increased, stable and low-cost supply of green hydrogen is achieved, and energy conservation and emission reduction of steel and other high-energy-consumption industries are achieved.

The invention provides a DIKWP semantic modeling method. Complex problems of an enterprise are converted into a five-layer linkage semantic map. The method comprises the following steps: 1, cleaning multi-source heterogeneous data to form nodes by a data layer; (2) information layer construction domain ontology clarification concepts and constraints; (3) the knowledge layer aligns with the knowledge base to infer and complement the relationship to generate a knowledge graph; (4) the wisdom layer outputs scheme elements, benefits and risks based on decision rules; and (5) modeling each intention layer refining strategic target constraint layer. Full-link semantic mapping from data to intention is achieved, consistency and accuracy of problem definition are improved, cross-department implicit causality is mined, it is ensured that a scheme is accurately aligned with a strategic target, an interpretable semantic basis is provided for automatic scheme generation, scene simulation and optimization decision, and the method has remarkable commercial application value.

The invention discloses an atmospheric pollution case system, a case analysis method and a medium, and the system comprises a basic information layer which is used for storing the whole-process feature data and treatment measure data of a pollution event; the logic analysis layer is used for carrying out quality control on the data, carrying out source analysis and cause analysis on the whole-process feature data of the pollution event after the quality control, and carrying out effect evaluation on the treatment measures after the quality control; and the comprehensive decision-making layer is used for comparing historical cases according to the retrieval conditions and matching similar historical cases, and finding out treatment measures corresponding to the similar historical cases according to the similar historical cases, or formulating targeted new treatment measures according to the corresponding treatment measures. The invention provides a'basic information-logical analysis-comprehensive decision 'three-layer progressive architecture case library, so that other modules can be conveniently expanded on the architecture of the case library subsequently; and multi-source data are systematically integrated, so that the problem of fragmentation of existing case data is solved.

A system for an infographic display of an image analysis, said system comprising: a processor; a non-transitory storage element coupled to the processor; encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the system to: receive at least one image frame; localize at least one of a present tooth, dental, or non-dental condition inside the received image frame and identify it by at least one of a number, name, or short-hand; extract the at least one identified tooth, dental, or non-dental condition within the received image; classify the at least one tooth, dental, or non-dental condition based on the extracted; and represent results of the at least one classified area of interest in at least one of three layers, wherein the layers are an image-based layer, infographic-based layer, or an informational layer.

The invention discloses an automatic video generation system and method based on AI Agent multi-mode cooperative control. The system comprises a demand acquisition module used for acquiring multi-modal generation demand information; the hierarchical intention analysis and dynamic graph construction module is used for generating an intention graph with priorities and constraint conditions; the multi-scale space-time capsule scene generation module is used for generating multi-scale space-time capsule modeling information; the physical-semantic joint constraint verification module is used for acquiring the verified modeling information; the space-time consistency optimization and content fusion module is used for acquiring a video frame sequence after space-time consistency optimization; and the dynamic code rate video synthesis and output module is used for generating a video file. Through dynamic adaptive architecture and global joint optimization, the problems of stiffness and separation of a traditional video generation technology are solved, and full-process intelligent control from multi-mode input to high-quality video output is realized.

The invention belongs to the technical field of distributed cluster cooperative control, and particularly discloses a distributed privacy protection formation control method and system based on state decomposition, a multi-unmanned-vehicle system is divided into an information layer and a physical layer, the information layer is responsible for operating a dynamic average consistency algorithm, calculating the target position of each unmanned vehicle, and calculating the target position of each unmanned vehicle; according to the formation geometric center estimation, the physical layer utilizes the target position calculated by the information layer to further calculate the following required running speed of the unmanned vehicle according to the actual position. Comprising the following steps: performing decomposition configuration on the initial state of the unmanned vehicle; auxiliary cooperative variables are designed to perform distributed iterative calculation, so that the anti-interference capability of the system in a complex communication environment is remarkably improved; and converting a cooperative calculation result into a linear speed control instruction and an angular speed control instruction to realize accurate formation control of the multi-unmanned vehicle system. According to the method, the problem that state information leakage and noise robustness are difficult to consider in traditional cooperative control in cooperation of multiple unmanned vehicle systems is solved.

The invention provides a power plant DCS data acquisition interface automatic configuration method and system. The method comprises the following steps: acquiring a production process diagram file from a DCS upper computer, and analyzing and extracting measuring point information based on a DCS type; generating a structured lexicographical order through lexical analysis, and screening target measurement points according to a preset rule to generate a measurement point list; adopting a Myers difference algorithm to compare the states of the measuring point lists, and dynamically updating the interface program acquisition range; and transmitting the measuring point list, the process diagram and the real-time data to a management information layer MIS across a safety area, and synchronously checking configuration consistency based on a digital twinborn model. According to the method, automatic extraction of the measuring points is realized through a regular expression and a DOM analysis technology, dynamic key encryption and an incremental updating mechanism are combined, the problems of low manual configuration efficiency, updating lag and cross-regional data islands are solved, the accuracy and synchronous real-time performance of measuring point configuration are remarkably improved, and the method is suitable for large-scale popularization and application. And safe and reliable digital support is provided for power plant production monitoring and information management.

The embodiment of the application discloses a dynamic event classification method and device, the method comprises the following steps: obtaining at least one correlation degree between m kinds of dynamic events according to n dimensions, grouping the m kinds of dynamic events according to the at least one correlation degree to obtain a plurality of groups; the m kinds of dynamic events are events causing changes in a dynamic information layer of the high-precision map, and n and m are integers greater than 1; wherein a first kind of dynamic event in the m kinds of dynamic events belongs to a first group in the plurality of groups; according to the obtained first dynamic event being the first kind of dynamic event, it is determined that the first dynamic event belongs to the first group. The application can save resource overhead when storing and managing dynamic events of a high-precision map, and improve storage and management efficiency.

The present invention discloses a personalized printed anti-counterfeiting label with an optical holographic pattern and an anti-uncovering effect, comprising a carrier layer, a partial release pattern layer, an optical structure layer, a molded structure layer, a holographic pattern layer, an adhesive layer, a base paper layer, an ink absorption layer, and a personalized information layer. The present invention can realize the personalized printing and production of high-grade anti-counterfeiting labels, and the anti-counterfeiting label has a significant metallic luster and an embedded holographic pattern, so that on-site security personnel can quickly and accurately identify the label by visual inspection. When an external force is used to uncover or peel off the personalized printed anti-counterfeiting label, customized handwriting or pattern will be left on the carrier that needs to be anti-counterfeited, and the label will be deformed and broken and cannot be used again, thereby achieving the anti-uncovering and anti-transferring effect of the label.

The application discloses a deep residual network model for coal gangue identification, a coal gangue identification method and a system. The model comprises a 3*3 convolution layer, a first mixed attention layer, a first Layer layer, a second Layer layer, a third Layer layer, a fourth Layer layer, a second mixed attention layer, a processing layer, a full connection layer and a Softmax layer. The 3*3 convolution layer is used for extracting shallow feature information of a target data set. Through processing of the first mixed attention layer, a first mixed weight feature map is obtained. Through processing of a plurality of convolution layers, a second mixed weight feature map is obtained. Through processing of the second mixed attention layer, a third mixed weight feature map is obtained. Through Dropout processing of the processing layer, a fourth mixed weight feature map is obtained. Through processing of the full connection layer, coal gangue information is obtained. The Softmax layer is used for outputting a coal gangue identification result. The application can effectively improve the coal gangue identification accuracy.

The invention discloses a vehicle network interaction flow optimization method based on information and physical fusion, and belongs to the technical field of intelligent traffic and energy internet crossing. Comprising the steps that a vehicle network is divided into a plurality of grid areas, and each grid area comprises physical layer operation data and information layer operation data; constructing a vehicle network diagram structure, and calculating the schedulable potential of the EV in the stay duration of the charging station; according to the schedulable potential and the information layer operation data of the EV in the stay time of the charging station, the method aims at minimizing the peak-valley difference, maximizing the renewable energy consumption, the vehicle network interaction income and the operation income. Constructing an objective function of the multi-objective flow optimization model, an EV charging and discharging power constraint, an EV battery charge state constraint, a charging pile capacity constraint and a power grid safety constraint; and solving the multi-target traffic optimization model to obtain a vehicle network interaction traffic optimization result. According to the method, the prediction error of the EV arrival time is reduced, and the V2G flow regulation and control are refined.

The application belongs to the technical field of network security, and particularly relates to a CPS attack path reconstruction method and system based on a kill chain model clustering. CPS information layer and physical layer operation data are collected, a feature vector is generated through time window fusion, a feature subspace is divided based on the four stages of the kill chain, candidate clusters are obtained by clustering the data of each stage, high-confidence clusters are screened in combination with time concentration and behavior intensity, a causal diagram is constructed according to time proximity and cross-layer correlation, and complete reconstruction of the attack path is realized; the application adapts to the cross-layer coupling characteristics of CPS, improves the accuracy of attack stage division and path reconstruction, and can provide reliable support for attack tracing and defense strategy formulation.

The invention discloses a color-printable anti-counterfeiting traceable irradiation indication label and a production process thereof, and belongs to the technical field of medical supplies. A label body comprises an irradiation indicating ink layer from top to bottom, solvent type irradiation color-changing ink is adopted, the irradiation indicating ink layer turns red from yellow when the irradiation dose is 5 kGy, and the irradiation indicating ink layer turns chestnut red when the irradiation dose is 100 kGy; the isolation ink layer covers the lower portion of the irradiation indication ink layer, and the edge of the isolation ink layer expands outwards by 0.5 mm-2mm; an irradiation dose grade comparison color block is printed on the irradiation indication description information layer; the anti-counterfeiting traceability information layer contains an ultraviolet invisible variable two-dimensional code; the alcohol-friction-resistant coating is composed of water-based ink-absorbing polyurethane resin and wear-resistant filler; according to the invention, the dose level of irradiated products can be rapidly judged, and the unique two-dimensional code on each label is combined with a data management platform of an enterprise, so that a product tracing function can be realized.

This invention relates to the field of inkjet control technology, and discloses an intelligent inkjet control system, method, robot, and storage medium. The method first acquires the surface contour data and color information of the object to be inkjetted using a laser rangefinder, constructing a surface feature vector. Then, it determines the target inkjet area through a region suitability assessment. Next, it acquires the semantic information of the inkjet content, calculates the semantic element weights, and generates inkjet parameter constraints, including droplet size thresholds and information hierarchy presentation rules, based on the target area range. Subsequently, it generates an intelligent inkjet scheme based on the constraints, controlling the inkjet device to form the target pattern. Finally, it generates the movement path of a mobile robotic arm based on a cubic spline interpolation algorithm, applying the target pattern to the target area. This method can adapt to complex surface morphologies and diverse materials, precisely control the inkjet process, ensure accurate pattern presentation and stable adhesion, and improve inkjet effect and information transmission effectiveness.

This application discloses an automated video generation system and method based on AI Agentic multimodal collaborative control. The system includes: a requirement acquisition module for acquiring multimodal generation requirement information; a hierarchical intent parsing and dynamic graph construction module for generating an intent graph with priorities and constraints; a multi-scale spatiotemporal capsule scene generation module for generating multi-scale spatiotemporal capsule modeling information; a physical-semantic joint constraint verification module for acquiring verified modeling information; a spatiotemporal consistency optimization and content fusion module for acquiring a spatiotemporally consistent optimized video frame sequence; and a dynamic bitrate video synthesis and output module for generating video files. This application overcomes the rigidity and separation problems of traditional video generation technologies through a dynamic adaptive architecture and global joint optimization, achieving intelligent control throughout the entire process from multimodal input to high-quality video output.

The application provides a kind of BOM management system and method based on PLM, it is related to data processing technical field, the BOM management system, comprising: obtaining unit, for obtaining the preparation list of BOM product;Extraction unit is for obtaining corresponding initial material information based on preparation list;Hierarchical analysis unit is for carrying out hierarchical analysis to initial material information, and initial material information is split into multiple different hierarchical combination material information, and combination material information includes multiple basic material information;Updating unit is for analyzing basic material information according to historical material library in historical archive material information, and updating historical material library according to analysis result;And construction unit is for carrying out the preparation information construction of other BOM product by updated historical material library.The management system and method provided by the application can effectively guarantee the security and accuracy when BOM product list entry system and export system.

The invention provides a BOM management system and method based on a PLM, and relates to the technical field of data processing, and the BOM management system comprises an obtaining unit which is used for obtaining a compilation list of BOM products; the extraction unit is used for acquiring corresponding initial material information based on the compilation list; the hierarchical analysis unit is used for performing hierarchical analysis on the initial material information and splitting the initial material information into a plurality of pieces of combined material information of different hierarchies, and the combined material information comprises a plurality of pieces of basic material information; the updating unit is used for analyzing the basic material information according to historical archived material information in the historical material library and updating the historical material library according to an analysis result; and the construction unit is used for constructing compilation information of other BOM products through the updated historical material library. The management system and method provided by the invention can effectively ensure the safety and accuracy when the BOM product list is input into the system and exported from the system.

The invention belongs to the technical field of natural language processing and artificial intelligence, and particularly relates to a nuclear power think tank report multi-dimensional semantic analysis method and system. Comprising the steps of data preprocessing (word segmentation, term recognition and grammar analysis); establishing an adaptive large model, and automatically adjusting an analysis strategy according to report requirements and data source features; applying an information extraction algorithm; a hierarchical information architecture is constructed and is divided into a basic information layer (original data), an analysis information layer (interpretation) and a decision information layer (suggestion) so as to output a support decision in a structured manner. The method has the beneficial effects that compared with a general information extraction patent, the method has obvious differences and advantages. For the terminology of the nuclear power think tank report, the terminology can be accurately understood and processed by establishing a terminology library and a targeted analysis algorithm, and understanding deviation in a general method is avoided.

The invention discloses an internet resource long-term storage management and storage system, which comprises a space-time coding layer which is based on an FPGA (Field Programmable Gate Array) main control chip, comprises a parallelized tensor processing unit and is used for converting digital resources and metadata and context relationships thereof into a space-time coding body with a time self-description capability; the storage unit is used for receiving the space-time coding body from the space-time coding layer and permanently solidifying the space-time coding body in a tamper-resistant physical form; and the four-dimensional continuation control layer is used for dynamically managing the integrity, readability and authenticity of resources in the whole life cycle through an autonomous evolution algorithm and a distributed verification network. Through collaborative innovation of a space-time coding body (an information layer), a holographic cold memory (a physical layer) and a continuation control network (a management and control layer), the basic challenges of long-term storage of Internet resources in the aspects of authenticity, integrity, availability, safety, cost, technical dependence and the like are systematically handled.

This invention relates to the field of automotive autonomous driving control technology, specifically to a software architecture, chassis domain controller, and chassis domain system for autonomous driving. The information layer acquires vehicle fault commands and emergency stop commands. The motion coordination layer triggers vehicle fault modes and emergency stop modes, and acquires emergency stop control signals and longitudinal and lateral vertical control signals. The dynamics control layer acquires dynamics control target quantities based on the emergency stop control signals or longitudinal and lateral vertical control signals; the fault-tolerant control layer performs fault-tolerant control based on vehicle fault information. The actuator control layer converts the dynamics control target quantities and fault-tolerant control target quantities into actual control signals to control the actuators. This software architecture, designed from a centralized perspective, achieves decoupled development of software and hardware, centrally processes all information, and uniformly integrates and schedules functions. It comprehensively considers vehicle, driver, fault, and cross-domain interaction, improving vehicle control accuracy and operational safety.