37 results about "Standard product" patented technology

Systems, methods, and other embodiments associated with a centralized product catalog with standardization from independent data sources are described. In one embodiment, a computing system is configured to access and download product information for a plurality of products that is maintained in a non-standard format. Metadata is identified and extracted. Feature vectors may be generated from the metadata and used to predict and assign class codes to products. The product attributes are extracted from each product, which include a non-standard product description. The non-standard product description is converted into a standardized text description. Standardized records are generated for each product record and a centralized database is generated with the standardized records.

The present application relates to an information processing method, device, computing equipment and medium. The present application obtains first difference information representing the difference between the standard product cost of a product component of a target product and the first theoretical product cost of the product component, and obtains second difference information representing the difference between the standard product cost of the product component and the second theoretical product cost of the product component, determines difference adjustment information based on the first difference information and the second difference information, adjusts the first cost information obtained by the material ledger module based on the difference adjustment information to obtain second cost information that is closer to the actual cost of the target product, improves the accuracy of the calculated actual component cost, and reduces the occurrence of distortion of the calculated actual component cost.

The invention discloses a full-automatic double-sided synchronous labeling system based on multi-axis robot cooperative control, and relates to the technical field of production supervision. The production line image data of the production line are obtained through the multi-view structure optical camera, the scene mapping space is established, the production line image data are mapped to the scene mapping space for space calibration to obtain the real-time production scene data, and then the production line three-dimensional structure model is established according to the real-time production scene data. A standard product labeling position is set in the three-dimensional structure model, and then according to the spatial position relation between the standard product labeling position and the product model, the position or shape of the machined product is adjusted through the industrial robot; and real-time surface light transmittance of the two sides of the processed product is collected, the two sides of the processed product are labeled according to the real-time surface light transmittance when labeling countdown is finished, a non-shadow label image of the labeling position of the product is collected through a line-scan digital camera, and whether labeling is qualified or not is judged according to the non-shadow label image.

The invention discloses a parameter cooperative control system based on yeast extract enzymolysis reaction, and relates to the field of microbiological detection analysis, and the method comprises the following steps: carrying out enzymolysis reaction digital simulation by taking an expected quality index of a yeast extract as a processing constraint, and generating a standard hydrolysis degree curve and a standard product accumulation curve; setting an adaptive adjustment time step length based on a preset reaction stage, and obtaining a feedback adjustment time period sequence, a standard hydrolysis degree sequence and a standard product cumulant sequence; and based on the feedback adjustment time period sequence, taking an approximation standard hydrolysis degree sequence and a standard product cumulant sequence as a parameter cooperative control target, carrying out iterative optimization on enzymolysis control parameters in the enzymolysis reaction process, and obtaining an optimal enzymolysis control parameter sequence to carry out iterative regulation and control on enzymolysis reaction equipment. The problems that an existing enzymolysis reaction control method depends on experience or simple experimental design, the reaction process is difficult to accurately control, the product quality is unstable, and the yield is low are solved.

The application discloses a method for determining the content of DMPP in compound fertilizer, comprising the following steps: S1, standard working solution preparation; S2, sample pretreatment; S3, chromatography-mass spectrometry detection; S4, quantitative analysis. In view of the quantitative error caused by the matrix effect, the application proposes to prepare a gradient standard working solution by using a blank fertilizer matrix extract, to eliminate the physical and chemical property difference between the sample and the standard product through matrix matching, and to improve the accuracy of the calibration curve. Secondly, in order to strengthen the purification effect of the complex matrix sample, a C18 solid-phase extraction column is introduced to combine with a methanol-water system for elution, and the activation and redissolution conditions are optimized, so that the non-polar interferents such as lipids and pigments are effectively removed, the NY / T3423-2019 water extraction system is compatible, the ESI + / MRM mode is adopted, and the sensitivity and anti-interference ability are significantly better than those of HPLC-UV; the method is suitable for research / internal control / confirmation, and if used for supervision sampling / arbitration, method verification and recognition need to be completed in advance.

The application discloses a front-end project secondary development method, equipment and medium, and the method comprises the following steps: adjusting the initial product code of the front-end project in the Git library to obtain standard product code; the standard product code can support secondary development; obtaining the standard product code from the Git library, cloning the standard product code, and determining the cloned standard product code as the initial code for secondary development; based on the user customization demand and the initial code, the specified page of the front-end project is secondarily developed to obtain a secondary development page; under the pre-set folder of the front-end project, a file in a specified format is newly created, the route of the secondary development page is configured in the file according to the specified format, and a secondary development route configuration file is obtained; and the secondary development route configuration file is parsed through a pre-set script template file to generate a secondary development route script file. The secondary development of the front-end framework project is realized.

The invention relates to the technical field of product data management, in particular to a preserved duck egg production whole-process traceability method and system based on a block chain, and the method comprises the steps: registering raw material eggs in batches, gathering and capturing key parameters such as cellaring temperature and humidity, feed liquid alkalinity and the like in production, and generating a process witness which cannot be tampered; a double-rail treatment normal form composed of an execution rail and a learning rail is used for processing witness, the execution rail conducts real-time intervention according to the operation standard, and the learning rail conducts iterative optimization on the predictive model; and finally, associating the process data with a subsequent supply chain transfer event, and aggregating to form a supply chain decision sand table which can be used for simulation and deduction. According to the invention, refined data management and closed-loop control in the production process are combined, and isolated production management is improved to an integrated supply chain collaborative decision-making level through data association and sand table deduction penetrating through the whole chain, so that the quality control precision and management decision-making level of the non-standard product supply chain are systematically improved.

The invention discloses a method for high-throughput screening of active components of a natural product based on equilibrium dialysis-mass spectrometry, which comprises the following steps: adding a protein solution on one side of an activated and moist 96-hole microdialysis plate, and adding a to-be-detected solution of a traditional Chinese medicine crude extract on the other side of the activated and moist 96-hole microdialysis plate; respectively recovering samples from the upper solution and the lower solution of the incubated 96-hole microdialysis plate, adding methanol, mixing, standing to precipitate denatured protein, centrifuging to remove precipitate, and taking supernate for LC-MS (liquid chromatography-mass spectrometry) analysis; and carrying out characteristic peak annotation through LC-MS data of the supernate, comparing with a standard product database, and carrying out differential analysis and screening to obtain the required active ingredients of the natural product. According to the method for screening the active ingredients of the natural product, the equilibrium dialysis technology, a high-throughput screening device and mass spectrometry are combined, and the efficient, accurate and anti-interference screening effect is achieved.

The invention belongs to the technical field of nanofiber manufacturing, and discloses a preparation method of a PS nanofiber standard product with a specific size and uniform dispersion. The PS nanofiber standard product is prepared through electrostatic spinning, frozen slicing and dispersion treatment in sequence; after spinning parameters are limited, freezing slicing and dispersing treatment are carried out, and a PS nanofiber standard product solution with the average diameter being 100-500 nm, the average length being 5-20 microns and the dispersity reaching the standard can be obtained; a fluorescent agent, a gadolinium contrast agent and Fe3O4 are respectively added, and a labeled PS nanofiber standard product solution with the average diameter of 100-500 nm, the average length of 5-20 microns and the standard dispersity can be obtained by adjusting spinning parameters. The material is reasonable in component design, simple and controllable in preparation process and low in production cost, and can be industrially produced and applied on a large scale.

The invention discloses a commodity information processing method, device and equipment. Comprising the following steps: acquiring a determined SPU (Standard Product Unit) as a target SPU when a plurality of different commodities are mixed and weighed; determining a plurality of minimum stock units (SKUs) which establish an association relationship with the target SPU in advance as a target SKU set; a weighing image collected in the mixing weighing process is obtained; according to the target SKU set, in the weighing image, identifying target SKUs to which the commodities belong, and commodity amounts corresponding to the target SKUs to which the commodities belong; and determining commodity inventory change information according to the target SKU to which each target SKU belongs and the commodity amount corresponding to the target SKU.

The invention discloses a quality detection system and method based on artificial intelligence, and the system comprises an intelligent detection device which is used for scanning one or more to-be-detected products, and obtaining the two-dimensional or three-dimensional product information of the one or more to-be-detected products; the cloud server is used for analyzing and comparing the obtained two-dimensional or three-dimensional product information of the one or more to-be-detected products with standard product information stored in the cloud server through cloud computing so as to judge whether the one or more to-be-detected products are qualified or not and generate a detection report; and the front-end electronic equipment is used for receiving and displaying the detection report and sending the standard product information to the cloud server. The to-be-detected product is scanned through the head-mounted intelligent detection equipment, two hands are not occupied, the detection information of the product is set in advance in the cloud end, the scanned product can be compared, analyzed and detected along with rotation of the head, and the method is efficient, convenient and rapid.

To provide a commodity sales data processor and a program capable of supporting the purchase of a special commodity.SOLUTION: A commodity sales data processing apparatus according to an embodiment includes a first acquisition module configured to acquire commodity identification information of a commodity purchased by a customer, a calculation module configured to calculate, when the commodity corresponding to the commodity identification information is a nonstandard commodity set to be sold at a discount, a contribution amount by multiplying a subtraction amount for the discount by a ratio relating to a donation set in advance by the customer, a processing module configured to execute processing relating to sales of the nonstandard commodity based on a subtraction price obtained by subtracting a remaining amount obtained by subtracting the contribution amount from the subtraction amount from a price of the nonstandard commodity, and a management module configured to cumulatively manage the contribution amount in association with customer identification information of the customer.SELECTED DRAWING: Figure 13

This invention discloses an online defect detection system for fabric labels and care labels, belonging to the technical field of detection systems. The invention includes an image acquisition module for acquiring images of fabric labels and care labels to be inspected, and a sample management module for pre-acquiring standard product samples and setting exposure parameters. The images to be inspected acquired by the image acquisition module are transmitted to an image comparison module, which compares the images to be inspected with the standard product samples and sends the comparison results to a defect judgment module, which identifies defect information in the images to be inspected. This invention achieves fully automated online inspection of fabric labels and care labels, replacing inefficient and unreliable manual visual inspection, significantly improving inspection efficiency and accuracy. Through the combination of image comparison and a multi-dimensional defect judgment module, it can accurately identify various defects such as typos, numerical errors, graphic defects, and dimensional deviations, providing comprehensive detection capabilities.

The invention relates to the field of collaborative production, in particular to a wooden furniture standard product collaborative production solution. The method comprises the following steps: S1, obtaining information of a current tenant order and order production load information, judging whether delivery on schedule can be satisfied according to the load information of the order, and if order products which can be delivered on schedule are not processed, continuing normal execution by a system; s2, issuing a collaborative production task for orders which cannot be delivered on time; s3, other tenants check and bid the released production tasks; s4, the publisher selects a cooperation party according to the quotation information and the delivery time information; and S5, the collaboration party completes and delivers according to the order task requirement. According to the invention, through standardization of order products and supervision and control of the process, the collaboration party needs to carry out collaborative processing according to the requirements of the publisher, the product quality is ensured, the consumed time is short, and delivery can be carried out in a set construction period.

The application discloses a method for identifying the authenticity or year of brewed wine based on dynamic light scattering, comprising the following steps: (1) taking a brewed wine standard product, adding different exogenous substances into the brewed wine standard product respectively, dissolving and mixing uniformly, and then performing membrane treatment to obtain a standard product sample; (2) determining the hydrodynamic average radius of each exogenous substance in the standard product sample by dynamic light scattering, and obtaining the hydrodynamic average radius basic data of the corresponding exogenous substance in the standard product; (3) taking a to-be-detected brewed wine, and performing the same treatment as steps (1) and (2) on the to-be-detected brewed wine to obtain the hydrodynamic average radius data of the corresponding exogenous substance in the to-be-detected brewed wine; and (4) comparing the hydrodynamic average radius data of the corresponding exogenous substance in the to-be-detected brewed wine with the hydrodynamic average radius basic data of the corresponding exogenous substance in the standard product, and identifying the authenticity or year of the to-be-detected brewed wine. The application has the advantages of small sampling amount, simple sample pretreatment and analysis process, and less interference in the detection process.

This application discloses a product defect detection method and related apparatus. The product defect detection method includes: extracting features from an actual product image and a standard product image respectively, obtaining actual product features and standard product features, where the actual product image is taken of the target product in its actual state, and the standard product image is taken of the target product in its standard state; stitching the actual product features and standard product features along the channel direction to obtain stitched product features; using a distance metric model based on the stitched product features to obtain a distance map between the actual product image and the standard product image; and determining whether the target product in its actual state has a defect based on the distance map. This solution can improve the accuracy of product defect detection results and save storage space and computational overhead.

The application discloses a method for preparing fine fusaric acid, which comprises the following steps: toxin production culture, sample extraction, preliminary purification, reverse-phase preparation, gel chromatography separation and normal-phase preparation. The method for preparing fine fusaric acid provided by the application improves material steady state and preparation efficiency, greatly reduces production cost, and has a purity of more than 99%, and can be used as a standard product for fine fusaric acid detection, prevention and control and toxicology research in food and feed.

The application discloses a method for determining total soybean isoflavone in food, which realizes quantitative conversion of various soybean isoflavone glycosides in the sample into corresponding aglycones by extraction under alkaline conditions and hydrolysis of glucosidase; the method realizes determination of low-concentration soybean isoflavone in the sample and effectively shortens the detection period by applying ultra-high performance liquid chromatography tandem triple quadrupole mass spectrometry; and methodological research shows that the method has a lower detection limit and higher accuracy. Since the application realizes determination of total quantity of 12 kinds of soybean isoflavones in the sample by only 3 kinds of soybean isoflavone aglycones, the use cost of standard products is reduced to only 1 / 3 of the original on the basis of originally needing to use at least 6 kinds of isoflavone standard products. In addition, total soybean isoflavone is calculated in terms of aglycone, which can more accurately reflect the actual biological activity level on the one hand, and can also avoid the inconsistency of the total isoflavone result caused by the non-uniform use of glycosides or aglycones on the other hand.

The invention relates to the technical field of industrial production monitoring, and discloses a VI standard product manufacturing monitoring system based on the Internet of Things. The system comprises a data acquisition module, an intelligent regulation and control module, a quality control module and a remote communication module. The data acquisition module acquires and makes parameters of each stage and judges abnormity, the intelligent regulation and control module adjusts equipment parameters according to abnormal signals, the quality control module monitors the adjustment process and triggers maintenance, and the remote communication module realizes data uploading and instruction receiving. The system is also provided with an environment adaptation module which is linked with the historical database. The system realizes real-time monitoring and intelligent regulation and control of the whole process of VI standard product manufacturing, can improve product quality and production efficiency, reduces cost, is convenient for remote management, optimizes production by means of data analysis, and has important practical value.

The invention discloses a molecular marker group related to false wheat germplasm variety identification. The molecular marker group consists of the following 11 molecular markers: gwm459, barc164, barc324, gwm155, gdm111, cfu 2028, barc91, barc240, gwm495, cfu 2155 and barc198. The molecular marker group for identifying and detecting the wheat variety, the primer group for amplifying the marker group and the kit provided by the invention are simple to operate, and the name of an unknown wheat variety can be identified only through one-time PCR (Polymerase Chain Reaction) operation. According to the present invention, the kit has characteristics of numerous gene locus arrangement, scientific and reasonable arrangement, 103 wheat varieties can be distinguished, the primer pair has high specificity, and the A addition incomplete peak, the non-specific amplification peak and the like cannot appear; the invention also prepares an allele typing standard substance as a test standard for sample typing and quality control, and solves the problem that results obtained on different genetic analyzers are inconsistent.

The application discloses a detection method of phenolic antioxidant additives in insulating oil, and belongs to the technical field of insulating oil detection. The application adopts a nuclear magnetic resonance hydrogen spectrum internal standard method for quantitative detection, directly determines the mixed oil sample, an internal standard substance and a deuterated reagent, and calculates the additive content according to the integral area ratio of characteristic quantitative peaks. The chemical shifts of the characteristic quantitative peaks of the internal standard substance and the characteristic quantitative peaks of the phenolic antioxidant additives in the insulating oil are located in the medium field intensity area of the spectrum, and the chemical shifts are not overlapped. The application overcomes technical difficulties such as complicated pretreatment, interference of complex oil matrix, use of toxic reagents and strong dependence on standard products of traditional methods. The detection method has the advantages of small sample consumption, fast analysis speed, green environmental protection, simple operation and the like, and the detection limit can reach 0.004%, and can realize rapid, accurate and reliable quantitative analysis of the phenolic antioxidant additives in the insulating oil.

This application relates to a project-based bill of materials (BOM) generation and management method and system, belonging to the field of manufacturing information management technology. The method includes: responding to a project creation instruction for a target project, establishing a master project plan and at least one detailed plan associated with the master project plan, the detailed plan describing project-level product configuration requirements; generating a project BOM uniquely corresponding to the target project based on the master project plan and the detailed plan, the project BOM existing independently of the standard product BOM; and generating and outputting production instructions to guide production execution based on the project BOM. This application effectively meets the need for rapid and accurate generation of BOM closely linked to project requirements in project-based delivery scenarios for non-standardized products.

The application discloses a system upgrade early warning method and device, equipment and a storage medium. The method comprises the following steps: obtaining first product configuration information of a customized development product of a system to be upgraded, obtaining second product configuration information of a latest standard product, comparing the first product configuration information with the second product configuration information based on a preset comparison detection strategy, determining whether there is a configuration abnormal item in the customized development product compared with the latest standard product, detecting whether there is a configuration conflict between the customized development product and the latest standard product, and further detecting a system upgrade risk. If there is a configuration abnormal item in the customized development product compared with the latest standard product, an early warning prompt information is sent to inform a user to make a configuration correction, so that the system upgrade risk is effectively avoided, and the system upgrade is ensured to be successful. The embodiment of the application can be applied to enterprise management systems, such as enterprise resource planning systems and OA systems.

The invention belongs to the field of electronic product module testing, and discloses an automatic testing system and method for non-standard products, through function extension of an oscilloscope, not only can a test case template be imported, but also parameter adjustment and data acquisition can be carried out, so that the same equipment can meet different requirements of various types of non-standard products, and the testing efficiency is improved. Repeated establishment of a test environment is avoided, and the reuse rate and the utilization rate of test resources are remarkably improved. The pedal serves as an interaction control device, switching on and switching off of a programmable power supply are achieved, display and switching off of an oscilloscope and data interaction of an upper computer can be synchronously controlled, an operator can achieve multi-link linkage through single-point physical actions in the testing process, the operation steps are simplified, and the testing efficiency is improved. And the testing flexibility and the man-machine interaction efficiency are improved.

The application discloses a kind of construction method and device of data set, it is related to deep learning field.The method is used to solve the problem that the construction of existing multi-modal data set needs artificial data collection, leading to poor data quality and large consumption.The method comprises the following steps: selecting a plurality of high-ranking products in a plurality of categories included in a designated website as product seeds; obtaining the SPU (Standard Product Unit) of each product seed by crawling the SKU inventory unit of each product seed through a multi-modal commodity crawler comprising at least text analysis and image recognition; crawling all information of the SPU of each product seed layer by layer according to a hierarchical structure to obtain all SKUs included in the SPU corresponding to each product seed and the fine-grained attributes corresponding to the SKUs; and obtaining the fine-grained candidate group of each product seed by consistently annotating the fine-grained attributes.The method promotes the wide application of artificial intelligence in medical, agricultural, e-commerce and other fields.

This application provides a food conveying inspection method and apparatus based on image recognition, belonging to the field of food production inspection technology. The method includes: inputting target image data into a quality defect prediction model to obtain a quality defect probability value; if the quality defect probability value is greater than or equal to a preset threshold, processing the target image data to obtain target data; matching the target data with multiple reference images in a standard product template database to obtain multiple similarities, wherein the standard product template database stores reference images corresponding to different defect levels; and analyzing the target data based on multiple similarities and difference maps to obtain the inspection result. The food conveying inspection method and apparatus based on image recognition provided in this application can improve the reliability and efficiency of food quality inspection.

Natural-material interfaces are disclosed for articles that include synthetic surfaces which would otherwise come into contact with the body or be frequently handled. Each interface presents a body-contacting surface composed entirely of natural, non-synthetic materials, and is configured to shied or prevent direct contact between the user and underlying synthetic components.Interfaces may take the form of removable, replacement, integrated, or other interface configurations adapted to components such as eyeglass pads, straps, cushions, phone grips, earbuds, steering wheels, or other body-contact surfaces. Materials may include hemp, wool, leather, cork, gold, or other substances derived from plant, animal, or mineral sources. Elements may include synthetic materials, provided they do not contact the body. The invention offers biocompatible, hypoallergenic, and health-safe alternatives for synthetic surfaces. Interfaces may be dimensioned for standard products and provided as kits or standalone units, reducing user exposure to synthetic compounds during use.

The invention provides a construction method of a standard product information base and a related device. The method comprises the following steps: clustering a primary commodity information set to obtain a plurality of commodity clusters; wherein each commodity cluster comprises commodity information of at least one stock unit; the primary commodity information set comprises commodity information of a plurality of stock units; the primary commodity information set comprises commodity information of a specified commodity storage unit and commodity information of a similar commodity storage unit recalled according to an image of the specified commodity storage unit; performing de-duplication processing on the plurality of commodity clusters to obtain a target commodity cluster after de-duplication processing; wherein the target commodity clusters comprise representative commodity information used for representing the target commodity clusters, and the representative commodity information of different target commodity clusters is different; and extracting standard product information from the representative commodity information which is not contained in the specified standard product information base, and adding the standard product information into the specified standard product information base. The accuracy of the standard product information base can be improved to a certain extent.

The application discloses a food impurity online screening method and system based on visual recognition, which pre-trains a general feature encoder offline through a large-scale multi-category food image set, establishes an efficient feature extraction basis, dynamically constructs a product prototype Gaussian mixture model online based on K standard product images to accurately depict the normal distribution, and fuses global probability density and local manifold curvature information when modeling an abnormal score to construct a comprehensive and robust abnormality discrimination basis, effectively solving the missed detection problem of traditional methods for hidden normal product multi-modal distribution abnormalities. In this way, the rapid adaptation capability of the screening system to new product categories is significantly improved, the new product model deployment time and cost are greatly shortened, and the accuracy and system robustness of impurity detection are significantly improved.

1. Name of the product in this design: Packaging Box (Natural Standard Product I). 2. Purpose of this design: For product packaging. 3. The key design feature of this product is its pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.