381results about How to "High transparency" patented technology

The invention provides a land unmanned equipment semantic preserving large model deployment method and system, and relates to the technical field of navigation control. According to the deployment method, a preliminary control suggestion is directly output through a lightweight fusion model, optimization fusion is carried out through an MPC framework, underlying dynamics and environmental constraints, and seamless connection from semantics to control is achieved; in combination with a VILO odometer and instance segmentation, a global map containing dynamic obstacle semantic information is constructed and updated in real time, and an accurate context is provided for planning and decision making; model pruning, knowledge distillation and edge calculation scheduling are adopted, so that a complex multi-modal semantic model can run in real time on an embedded platform; the decision basis from instruction analysis to control execution is recorded and visualized in the whole process, and the transparency and credibility of the system are improved; on-line re-planning, multi-stage fault detection and switching strategies are integrated, and the robustness of the system in a dynamic environment and an abnormal condition is remarkably improved.

The invention discloses an enhanced generation query method and system based on multi-granularity retrieval and reinforcement learning strategies. According to the method, semantic analysis is carried out on an original query by utilizing a large language model, the original query is decomposed into a plurality of sub-problems, and each sub-problem generates a query vector; in the multi-granularity vector knowledge base, respectively executing vector similarity retrieval on the query vector of each sub-problem to obtain a related document fragment vector of each sub-problem under each granularity, and further generating a multi-granularity vector set of each sub-problem; weighting the multi-granularity vector set of each sub-problem to obtain a comprehensive context information block, determining the weight of the multi-granularity vector set of each sub-problem through a multi-arm reinforcement learning strategy, and inputting the comprehensive context information block into a large language model to output a query result. According to the method, the retrieval accuracy is improved through semantic decomposition and multi-granularity knowledge collaborative retrieval, results are intelligently integrated through a self-learning mechanism, and lightweight self-adaptive optimization is achieved.

The invention provides an OPC UA information model automatic construction method based on a knowledge graph and a large language model. The method comprises the steps of obtaining an unstructured industrial text, performing semantic analysis on the unstructured industrial text, and extracting a main body entity, an object entity, a method entity and attribute information thereof according to a predefined hierarchical tuple structure; calling an industrial field knowledge graph in real time to perform semantic enhancement on an extraction result; performing similarity calculation and evaluation on an enhanced result, and performing information fusion and duplicate removal based on a similarity evaluation result to obtain an entity-attribute set; generating a tree-shaped hierarchical structure framework by using a large language model, and calling a knowledge graph to perform structural integrity verification; semantic association between the entity-attribute set and the tree structure framework is analyzed, attributes and methods are mapped to corresponding structure nodes, and a mapping reasoning process is output in a natural language form; converting the mapped model structure into a format of XML (Extensive Makeup Language) grammar, and executing automatic compliance check and repair; by designing a progressive task chain of information extraction, semantic fusion, model construction, interpretable mapping and standardized output, a set of complete understanding-enhancement-construction-verification automation system is constructed.

The invention discloses a power battery pack health state monitoring system, and relates to the field of battery pack health state monitoring, and the system comprises a vehicle information input module which is used for receiving vehicle unique identification information inputted by a user; the standard data acquisition module is used for acquiring historical operation and charging and discharging data corresponding to the unique identification information of the vehicle from a cloud data source; the data fusion and feature construction module is used for constructing a battery state evaluation feature set; the battery health assessment module is used for constructing a battery pack health state assessment model and outputting a battery health state assessment result; the safety risk grading module is used for carrying out grading evaluation on the potential safety risk of the vehicle battery; and the report generation and display module is used for generating a structured detection report. The method has the advantages that the full life cycle of the power battery pack from real-time health state accurate evaluation to future safety risk grading early warning is realized, and intelligent monitoring can be explained.

The invention relates to the technical field of power system carbon emission analysis, and discloses a carbon flow closed-loop traceability and allocation method, system, equipment and medium considering network loss, which comprises the following steps: analyzing network loss components contributed by each load, and establishing quantitative correlation between load power consumption behaviors and network loss power; and then, constructing an equivalent lossless network, reasonably allocating the carbon emission corresponding to the network loss to a load side, and introducing a renewable energy carbon reduction load mechanism to quantify the carbon emission reduction benefit of the renewable energy. The method aims to improve the accuracy and rationality of carbon flow allocation in the whole link, and provides reliable support for low-carbon scheduling and carbon market mechanism design of a power system.

The invention discloses a special first-aid medicine and article storage and distribution construction system and method. The system comprises an Internet of Things module, a multi-subject cooperation module, an inter-hospital cooperation module, a cloud computing platform module, a block chain module, an intelligent scheduling center module, a storage network module and an emergency response module. The method comprises the steps of 1, demand integration and joint purchase; step 2, storage network construction and inventory optimization; step 3, intelligent scheduling and path planning; 4, emergency response and cross-mechanism deployment are carried out; 5, whole-process tracing and data uploading are carried out; step 6, performance monitoring and continuous optimization; according to the invention, a special first-aid medicine and article storage and distribution construction system is designed, and standardized data interaction and close cooperation among medical institutions, suppliers and logistics enterprises are realized by establishing a multi-subject cooperation mechanism such as joint purchase, inventory sharing, emergency allocation and performance monitoring. The joint purchasing module gathers the purchasing demands of the medical institutions in the region.

This invention provides a maltodextrin with good encapsulation performance and moisture resistance, and its preparation method. This invention belongs to the field of food processing technology. The preparation method of the maltodextrin with good encapsulation performance and moisture resistance provided by this invention includes the following steps: (1) adding 4-α-glycosyltransferase to a waxy cassava starch slurry for a first-stage enzymatic hydrolysis, inactivating the enzyme, and obtaining a waxy cassava starch slurry; (2) after heat preservation treatment of the waxy cassava starch slurry, adding a heat-resistant starch branching enzyme solution for a second-stage enzymatic hydrolysis, inactivating the enzyme, and obtaining a macrocyclic dextrin slurry; (3) centrifuging the macrocyclic dextrin slurry to remove impurities, freeze-drying, and obtaining maltodextrin with good encapsulation performance and moisture resistance. The maltodextrin prepared by the method of this invention has good encapsulation and adsorption performance, extremely high water solubility and slow digestion characteristics, and also has the advantages of low viscosity, high transparency, non-retrogradation, strong freeze-thaw stability, and good moisture resistance.

The invention discloses a semitransparent skin-nourishing face cream based on a medium-temperature hot pot process and a preparation method and application thereof, belongs to the technical field of cosmetics, and aims at solving the problems that in the prior art, in the face cream preparation process, a high-temperature processing process can destroy the activity of natural extracts; and the technical problem of how to enable the face cream to be semitransparent through formula system combination is solved. The preparation method of the semitransparent skin-care face cream based on the medium-temperature hot pot process comprises the following steps: putting a phase A into an emulsifying pot, and stirring and heating to 80-85 DEG C; adding the phase B into the emulsifying pot, stirring and heating to 80-85 DEG C, and then cooling to 60-65 DEG C; sequentially adding the phase A, the phase B, the phase C and the phase D into an emulsifying pot to enable the materials to be uniform, and cooling the materials to 53-57 DEG C to obtain cream; and filling the cream to obtain the prepared semitransparent skin-nourishing face cream based on the medium-temperature thermal tank process. The semitransparent face cream is prepared by designing a component compounding system.

The application provides a kind of electric vehicle charger remote efficient metering verification method, it is related to electric vehicle charging equipment electric energy metering verification technical field, including in the charger production factory or nearby setting up charger metering verification laboratory, factory shipment fixed point verification is carried out;Charger connection device, charger detection equipment, monitoring equipment, remote operation facilities and safety facilities are arranged in the verification laboratory, and verification cloud platform is deployed in the remote operation facilities, the application sets up charger metering verification laboratory in the production factory or nearby, and adopts the virtual load verification mode that voltage source is separated from current source, simulates high voltage and large current working condition under low power condition, replaces the verification mode that traditional field needs to be configured with high-power physical load, so as to avoid the use of special detection vehicle and heavy load equipment, effectively reduces the equipment volume and construction cost, improves the equipment utilization.

The utility model relates to the field of electric power system and high voltage switch equipment discloses vacuum circuit breaker with signal feedback mechanism, including arc extinguishing chamber, the bottom fixedly connected with mechanism box of arc extinguishing chamber, the outside of mechanism box is provided with quick -witted connection mechanism, the top fixedly connected with voltage transformer of quick -witted connection mechanism, the outside fixedly connected with base of mechanism box, the outside of base is provided with quick -witted break mechanism, quick -witted connection mechanism includes support connecting plate, the outside fixedly connected with air cylinder no.

The present application belongs to the field of advanced coating and preparation, and particularly relates to a high-transparent and scratch-resistant multifunctional antistatic coating and a preparation method thereof. The present application provides a high-transparent and scratch-resistant antistatic coating, raw materials of the antistatic coating comprising fluorion-containing silsesquioxane monomer, functional monomer and catalyst; wherein the functional monomer is a crosslinking agent or an anti-crystallization agent. The coating obtained by the present application has a light transmittance of >98% (550 nm); a surface pencil hardness of greater than 9H, no scratches after more than 1000 times of steel wool rubbing; a surface resistivity of about 10 8 ~10 9 Ω / sq, and a fast electrostatic discharge rate.

This invention discloses a high-transparency, high-haze polypropylene material and its preparation method. The material is prepared by mass ratios of 93.2-98 parts polypropylene, 1-4 parts light diffusing agent, 0.2-0.6 parts α-nucleating agent, 0.2-0.6 parts β-nucleating agent, 0.2-0.4 parts antioxidant, 0.2-0.6 parts dispersant, and 0.2-0.6 parts light stabilizer. The nucleating agent is a compound of α-nucleating agent and β-nucleating agent in a mass ratio of 2-5:2-6. By adding specific proportions of α-nucleating agent and β-nucleating agent, this invention induces the polypropylene molecular chains to arrange themselves in a specific manner, thereby forming different spherical (α-crystal form) and rod-shaped (β-crystal form) crystal structures. This causes optical fibers that pass through the material surface and into the matrix to undergo multiple refractions before penetrating the matrix, thus increasing the path length of light within the material and enabling the material to maintain high transparency while exhibiting higher haze.

The utility model discloses a core taking machine for processing optical lenses, which comprises a core taking machine body, a shell and a transparent cover plate, the transparent cover plate is positioned on the surface of the shell, and a water injection component for injecting water into the transparent cover plate is mounted in the shell; a water injection assembly is arranged in the shell, a cleaning assembly used for being matched with the water injection assembly to clean the transparent cover plate is arranged in the shell, and one end of the cleaning assembly is communicated with one end of the water injection assembly. Long-term accumulation of stains on the transparent cover plate is avoided, the transparency of the transparent cover plate is effectively recovered, and an operator can more clearly observe the processing condition of a lens in the core taking machine, so that the transparency of the transparent plastic plate is improved, the service life of the transparent plastic plate is prolonged, the replacement frequency caused by residual stains is reduced, and the production efficiency is improved. And the production cost is reduced.

This invention discloses a composite transparent film and its preparation method, relating to the technical field of polymer materials. The preparation method of the composite transparent film includes the following steps: (1) melting and blending vermiculite and fluororubber to obtain fluorinated vermiculite; then mixing the fluorinated vermiculite and mica evenly to obtain composite clay; (2) mixing polyvinyl alcohol solution, composite clay, and SESC lignin evenly to obtain a precursor solution, wherein the mass ratio of polyvinyl alcohol, composite clay, and SESC lignin is 45:45:(8-12); then spreading and drying the precursor solution on a substrate by casting, followed by heat treatment to obtain the composite transparent film. The composite transparent film of this invention possesses excellent water vapor barrier properties, ultraviolet absorption capacity, good transparency, high mechanical strength, and weather resistance.

This invention discloses a knowledge- and data-driven time series forecasting method and system, belonging to the field of industrial time series forecasting technology. To address the technical problems of existing technologies when processing strongly non-stationary data, such as key signal attention dilution, systematic underestimation of peak amplitude, incomplete capture of multi-scale dynamic patterns, and difficulty in embedding physical domain knowledge, this invention constructs standardized multi-dimensional time series data, performs heterogeneous feature grouping and parallel encoding to obtain multiple sets of feature representations, then extracts and integrates features from multiple sources to obtain intermediate state features, and finally performs multi-branch prediction and adaptive weighted fusion based on the intermediate state features to obtain the final time series forecast result. This invention can achieve active focusing on abrupt events in industrial sequences and accurate characterization of extreme value amplitudes, significantly improving prediction accuracy, physical consistency, and robustness to extreme conditions.

The invention discloses an unmanned express delivery vehicle control system and method based on operation state perception, and relates to the field of unmanned express delivery vehicle control systems. The method comprises the following steps: acquiring vehicle-mounted data in a driving period through a vehicle-mounted sensor array, performing time alignment and validity marking on the vehicle-mounted data to obtain a data quality label, constructing an evidence item set based on the data quality label, generating a sub-portrait label set according to the evidence item set, and displaying the sub-portrait label set in the driving period. And generating a portrait parameter set based on the sub-portrait label set through a preset priority rule and a persistence judgment strategy. Although the scheme has excellent performance in the aspects of improving system adaptability, safety, dynamic decision-making capability, reviewable performance and resource utilization efficiency, the problems of sensor faults, data loss, real-time data processing bottleneck, label interpretation errors and the like may influence the real-time response and decision-making precision of the system in a complex or extreme environment. Therefore, the overall performance and stability are reduced, especially under the condition of high load or low signal.

The invention discloses a credit information service method based on the Internet, and the method comprises the following steps: 1, an enterprise carries out the construction of a credit information system through the entrustment of a third-party credit investigation mechanism, and carries out the full collection of the credit information data of related business departments through the authorization of the third-party credit investigation mechanism; 2, indexes are selected in combination with the characteristics of the enterprises and the departments of the enterprises, all the indexes are divided into qualitative indexes and quantitative indexes by adopting a qualitative and quantitative combined method, and a credit evaluation index system is constructed; 3, business credit information of all departments of the enterprise and information mastered by calling terminals and credit third-party mechanisms from other interfaces are shared and publicized; the credit information state of the enterprise is a dynamic process, real-time updating of departments and other terminal users generating the credit information in the enterprise can be guaranteed based on the dynamic process, and the method has the advantages of improving the transparency of the credit of the enterprise and improving the service management efficiency.

A proxy value allocation and instant settlement system for atomic tasks is disclosed. The task decomposition module is configured to receive complex tasks and decompose them into multiple atomic subtasks using a directed acyclic graph (DAG) algorithm. Each atomic subtask is bound to a dynamic identity identifier of the executor proxy. A value weight allocation module, connected to the task decomposition module, is configured to calculate the value weight and corresponding settlement amount for each atomic subtask based on preset indicators. A fund locking module, connected to the value weight allocation module, is configured to pre-lock the total task funds at a distributed settlement node using a smart contract and set release conditions. This invention, by utilizing the DAG construction unit within the task decomposition module during the task initiation phase, can decompose complex macro-objectives into a set of atomic subtasks with independent executability and verifiability, eliminating the risks of identity theft and responsibility shirking during task execution and laying the foundation for subsequent settlement.

This application relates to the field of hydrosilylation, and in particular to a highly efficient catalyst for hydrosilylation reactions and its preparation method. This application provides a method for preparing a microcapsule-form catalyst, which first modifies methyl-terminated hydroxyl silicone oil with silazane, and then forms a microcapsule coating system with paraffin, thereby improving the release performance of the microcapsule coating system, so that the catalyst has low reactivity in the early stage of release, thereby improving the uniformity of the reaction process inside the silicone rubber, and thus improving the transparency and overall strength of the silicone rubber.

This invention discloses a black-based blue-spotted glaze with an earthworm-like pattern and its preparation method. The glaze consists of a body, a black base glaze, and a blue-spotted glaze from the inside out. The raw materials for the black base glaze are: feldspar, calcite, calcium borate, dolomite, talc, barium carbonate, quartz, bentonite, zirconium silicate, rutile, cobalt oxide, manganese oxide, and iron oxide. The raw materials for the blue-spotted glaze are: feldspar, limestone, alumina, talc, barium sulfate, Datong clay, zinc oxide, quartz, and titanium dioxide. The preparation method includes: 1. Wet ball milling the black base glaze raw materials to obtain a black base glaze slurry; 2. Wet ball milling the blue-spotted glaze raw materials to obtain a blue-spotted glaze slurry; 3. Bisque firing the body; 4. Applying the black base glaze slurry to the body and drying it; 5. Applying the blue-spotted glaze slurry to the body and drying it; 6. Oxidation firing and reduction firing of the body, followed by natural cooling to obtain the black-based blue-spotted glaze. The raw material formula of this invention is reasonable and environmentally friendly, which can improve the mechanical properties of the glaze; the preparation method is simple and the yield is high.

This utility model belongs to the field of evaporator technology and discloses a high heat exchange efficiency microchannel heat exchange structure ice mold evaporator, including an evaporator body. Multiple microchannel heat exchange tubes are fixedly installed on the inner side of the evaporator body, and multiple microchannel holes are opened at the bottom of the evaporator body. Diversion pipes are fixedly installed on the left and right sides of the evaporator body. The comprehensive application of the microchannel heat exchange structure, inner surface strengthening treatment, and outer surface fin design significantly improves the heat exchange efficiency of the evaporator. Compared with traditional evaporators, the ice-making speed can be increased, producing the same amount of ice in a shorter time, meeting the demand for rapid ice making. High heat exchange efficiency means that, under the same ice-making capacity, the required refrigeration compressor running time is shortened, and energy consumption is reduced. Actual testing shows that using the evaporator of this utility model reduces the energy consumption of the ice-making system, effectively reducing operating costs.

This invention provides a starch-based soft capsule composition, a starch-based soft capsule, and a method for preparing the same, belonging to the field of pharmaceutical technology. The starch-based soft capsule composition is characterized by comprising, by weight, 50-100 parts plant starch, 20-100 parts modified starch, 0.1-5 parts thickener, and 0.1-5 parts plasticizer; the plant starch is pea starch and corn starch in a mass ratio of (10-60):(40-50); the modified starch is modified corn starch and modified potato starch in a mass ratio of (1-5):(1-8). The starch-based soft capsules of this invention have a high seam sealing rate; they exhibit high transparency after long-term storage, are not prone to aging, and have good stability.

The application provides a cross-operator eSIM profile migration method and system, comprising: receiving a profile migration request sent by a user terminal; verifying the profile migration request based on a smart contract, and sending a release notification to a source operator node after verification; receiving release confirmation information and data addressing credentials returned by the source operator node; sending a download notification carrying the data addressing credentials to a target operator node, so that the target operator node downloads and decrypts encrypted configuration data based on the data addressing credentials; receiving reception confirmation information returned by the target operator node, and updating the ownership state of the target profile. The method can reduce the dependence on centralized servers by uniformly processing the profile migration process based on the smart contract by the migration management module, thereby improving the collaborative credibility and state update reliability of cross-operator migration, and further reducing the risk of single point failure, data tampering and difficult traceability of migration history.

The invention discloses a synergistic preparation method and application of carboxylated cellulose nanocrystals and regenerated cellulose, and belongs to the technical field of cellulose nanomaterial preparation. The synergistic preparation method of the carboxylated cellulose nanocrystal and the regenerated cellulose comprises the following steps: carrying out dipping treatment on a cellulose raw material in a Lewis acid solution, then carrying out solid-liquid separation, and collecting a solid-phase component to obtain cellulose slurry; dispersing the cellulose slurry in a polycarboxylic acid solution, reacting, and then filtering and collecting a solid product; treating the solid product by a method I or a method II; the method I comprises the following steps: carrying out separation treatment on the solid product to obtain carboxylated cellulose nanocrystals and regenerated cellulose; and the method II comprises the following steps: washing the solid product, and then carrying out suction filtration to obtain the holocellulose composite membrane.

The application discloses an anchor point guided clustering based data classification method, device and equipment, relates to the technical field of digital data processing, and comprises the following steps: obtaining an original data set to be classified, converting each sample data into a numerical vector, and constructing a data matrix; initializing a clustering center matrix and an anchor point matrix, and setting a fuzzy coefficient; obtaining the anchor point matrix and the clustering center matrix after joint iterative optimization; calculating the fuzzy membership degree of each sample vector; the category with the maximum fuzzy membership degree is taken as the final category label of the sample vector, and the classification results of all sample vectors are output. The application solves the problems that the existing fuzzy clustering method is sensitive to initial conditions, is easy to fall into a suboptimal solution, leads to unstable and inaccurate classification results, and cannot be directly solved by using a gradient descent algorithm, and is difficult to be applied to large-scale data sets, and realizes the enhancement of complex data classification precision and the applicability in different data scale scenes.

The present application relates to the field of polyurethane elastomer material, and particularly relates to a polybutadiene silicone diol, a preparation method thereof and a thermoplastic silicone polyurethane elastomer. The polybutadiene silicone diol with the structure of formula (I) has a moderate solubility parameter, the thermoplastic silicone polyurethane elastomer prepared from the polybutadiene silicone diol has a small degree of phase separation in the molecular chain of the elastomer, the product has unexpectedly good transparency, and in addition, the elastomer has the characteristics of PDMS and CTPB, and has excellent mechanical properties, outstanding low-temperature resilience, aging resistance, surface hydrophobicity and smoothness and other properties.

This invention discloses a method for preparing high-transparency tamarind polysaccharide gum through decolorization and deodorization. A combined purification process of enzymatic hydrolysis-sedimentation-chemical degradation-solvent washing-ultrafiltration is employed. Enzymatic hydrolysis degrades large molecules of proteins and fats in the extract into smaller molecules. Sodium hypochlorite is used for chemical degradation, oxidizing aldehydes and ketones in the extract into carboxylic acids. Finally, organic solvent washing and ultrafiltration purification remove impurities generated during enzymatic hydrolysis and chemical degradation, ultimately yielding high-transparency, odorless tamarind polysaccharide gum. The final product is white, with a transmittance of up to 95.4% at a 1% concentration, and is completely odorless, significantly improving product quality. This preparation process is simple, operates under mild conditions, and is suitable for industrial production.

The application discloses a kind of event relationship explainability analysis method, system, equipment, medium and product based on large language model, it is related to natural language processing technical field, the method includes: constructing counterfactual text pair set for target event relationship type, extract large language model middle layer hidden state and map into sparse activation vector, calculate the activation sensitivity of each base vector to target event relationship, filter out relationship sensitive base vector index set, execute intervention operation to the activation value of each base vector corresponding, reconstruct the hidden state after intervention into the hidden state after intervention, input to large language model subsequent layer, analyze large language model output change, extract the activation value of each base vector of relationship sensitive base vector index set on counterfactual text pair, generate feature vector and corresponding label, train large language model, determine the large language model after training, the transparency and explainability of large language model event relationship extraction process are improved.

The application relates to the field of radiation source identification, and specifically provides a high-explainability radiation source identification method and system, a training set radar pulse signal is acquired, a multi-domain joint time-varying fingerprint feature is extracted based on physical layer modeling, the fingerprint feature is input into a time-frequency double-branch feature fusion network to obtain time-frequency fusion features; the time-frequency fusion features are subjected to signal-level physical consistency enhancement and feature-level mixed enhancement; based on the enhanced features, an end-to-end training is conducted on the time-frequency double-branch feature fusion network through a hierarchical contrast learning framework containing intra-class contrast and inter-class prototype contrast, a radiation source identification model is obtained, and the trained radiation source identification model is used to identify the individual class of a radar pulse signal to be identified. Through the introduction of the physical layer explainable time-varying fingerprint feature, the adaptive double enhancement mechanism and the hierarchical contrast learning framework, the application realizes high-credibility, strong-adaptation and stable-identification radiation source individual identification.

The application relates to the technical field of photoelectric materials and scintillators, and particularly discloses an ionic rare earth complex scintillator glass, a low-temperature melting preparation method thereof and application. The low-temperature melting quenching process is developed, the crystalline ionic europium complex is directly melted and rapidly cooled under the condition of no solvent, and the direct preparation of the ionic rare earth complex transparent scintillator glass is realized. The prepared glass scintillator material has high transparency, high luminous efficiency, high rare earth content and excellent processability, and fundamentally eliminates the light scattering caused by particle agglomeration and phase separation in the traditional composite thin film, and breaks through the concentration quenching limitation. The glass scintillator material shows excellent luminous performance under X-ray excitation, and can significantly improve the imaging resolution and detection sensitivity. The application provides a feasible technical path for the development of a new type of rare earth scintillator material, and has important application prospects in the fields of medical imaging, nondestructive testing and high-energy radiation detection.