66 results about "Standard product" patented technology

The invention relates to the field of artificial intelligence, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a digital life cycle management method, device and equipment of a product and a medium, and the method comprises the steps: collecting product associated data of different dimensions, carrying out the demand integration analysis, and generating product demand information; inputting the product demand information into a generative adversarial network for product scheme generation processing to obtain a product design scheme; performing semantic analysis on the product design scheme to generate corresponding standard product information; performing feature matching on the standard product information and different customer groups, determining a target product of each customer group and pushing marketing information; and when a purchase request is received, performing pricing evaluation according to request customer information and request product information in the purchase request, and returning a dynamic pricing result to the customer. The full life cycle management from demand to sales is realized by processing the multi-dimensional product associated data, and the life cycle management efficiency of the product is improved.

The invention discloses a multiple semantic analysis commodity name pairing and mutual recognition method, which comprises the following steps: S1, creating a synonym mapping library containing standard commodity names and synonyms corresponding to the standard commodity names; s2, inputting a commodity name, and if matching succeeds, extracting a standard name; s3, if matching is not carried out in S2, character string similarity calculation is carried out, and an editing distance and word vector similarity algorithm is involved; s4, if matching does not occur in the step S3, semantic analysis is conducted through a deep learning model, and if the similarity is larger than or equal to 0.9 or classification labels are consistent, it is judged that the commodities are the same commodities; s5, if the input name is not matched in S4, listing the input name into a to-be-audited list, and performing manual auditing; and S6, updating the mapping library and the model parameters according to the auditing result or the business data, including adding the commodity name association relationship to the mapping library and updating the model. The problem that commodity names are difficult to pair and recognize in large-scale commodity information management is effectively solved, and then a new research direction and application prospects are provided for the field of commodity data processing in the future.

Qualification decisioning systems and techniques are described. For instance, a system receives user information that is indicative of a user's income stream and / or asset(s). The system receives product qualification criteria data corresponding to products, with different products corresponding to different product-specific qualification criteria. The product qualification criteria data can change over time. The system dynamically analyzes the user information and the product qualification criteria data using a trained machine learning (ML) model in real-time as the user information and the product qualification criteria data continue to be received. The trained ML model identifies a subset of the plurality of products that the user qualifies for at a specific time. The system outputs recommendations for the subset of the plurality of products. The system dynamically trains the trained ML model further, using the recommendations and the user information as training data, to update the trained ML model for future qualification decisions.

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 present invention discloses a method, device and storage medium for non-invasive modification of a standard product. The method comprises: initializing a customized engineering project; constructing a control inversion replacement combination annotation in the customized engineering project, wherein the control inversion replacement combination annotation is used to mark a customized class; sorting a candidate component list to obtain an ordered component list, wherein the ordered component list includes standard product components and customized components, and the customized components include customized classes; constructing a target scanning strategy; performing configuration modification processing on the customized engineering project; in the customized engineering project after the configuration modification processing, using the target scanning strategy to perform scan registration processing on the ordered component list to obtain a class definition register; instantiating the registration class in the class definition register to obtain a first non-invasive modification result. The present invention realizes non-invasive modification and improves decoupling and efficiency. The present invention can be widely applied in the field of computer technology.

The present invention belongs to the technical field of zearalenone extraction and relates to a method for extracting zearalenone from corn steep liquor to prepare a crude standard. The method comprises centrifuging corn steep liquor containing ZEN to obtain a supernatant; treating the supernatant using a PA66 membrane to obtain a PA66 membrane enriched with ZEN; eluting the PA66 membrane enriched with ZEN to obtain an eluate; and purifying the eluate by rotary evaporation to obtain a crude ZEN standard. The PA66 membrane is used to enrich and extract ZEN from ZEN-contaminated corn byproducts, achieving an enrichment and extraction efficiency exceeding 90%, providing a reliable and effective method for the high-value utilization of corn byproducts. The PA66 membrane is used to efficiently and selectively adsorb and enrich ZEN to initially prepare a crude ZEN standard, providing a new approach to the preparation of ZEN standard products.

At least one processor may receive user data indicating a scope of work and predicting at least one resource required to complete the scope of work. The predicting may include processing the user data with a machine learning (ML) process. The at least one processor may determine at least one provisioning property of the at least one resource and apply the at least one provisioning property to a standard product offering, thereby creating a customized product offering commensurate with the scope of work. The at least one processor may perform processing responsive to a user request using the customized product offering.

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 lentivirus integration site standard substance and a preparation method thereof, the standard substance is gDNA with clear insertion site and integration frequency, and the standard substance comprises a monoclonal single integration site standard substance, a monoclonal multi-integration site standard substance and a multi-cloning multi-integration site standard substance. The standard substance prepared by the method disclosed by the invention can effectively overcome the defects that a universal detection standard substance is lacked in the market, the accuracy and the sensitivity of the method cannot be verified, and data among laboratories cannot be compared with each other.

The utility model relates to the technical field of conveying equipment, in particular to a non-standard product conveying mechanism which comprises a conveying mechanism body and non-standard products, the conveying mechanism body comprises a conveying device and a stable support, and the conveying device is connected with the stable support; a plurality of supporting frames are arranged at the lower end of the conveying device. An adjusting device, an identifying and grabbing device and a rear conveying platform are arranged on the stable support in a matched mode. By means of the anti-skid conveying belt, the adjustable guide rod, the recognizing and grabbing device and the stable supporting structure, stable conveying and accurate grabbing of different non-standard products are achieved, the misoperation risk is reduced, the production automation degree and stability are improved, and the production efficiency and the enterprise competitiveness are effectively improved.

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.

Qualification decisioning systems and techniques are described. For instance, a system receives user information that is indicative of a user's income stream and / or asset(s). The system receives product qualification criteria data corresponding to products, with different products corresponding to different product-specific qualification criteria. The product qualification criteria data can change over time. The system dynamically analyzes the user information and the product qualification criteria data using a trained machine learning (ML) model in real-time as the user information and the product qualification criteria data continue to be received. The trained ML model identifies a subset of the plurality of products that the user qualifies for at a specific time. The system outputs recommendations for the subset of the plurality of products. The system dynamically trains the trained ML model further, using the recommendations and the user information as training data, to update the trained ML model for future qualification decisions.

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 discloses a multi-channel endotoxin detection control method and system, and relates to the technical field related to data processing, the method comprises the following steps: carrying out multi-channel endotoxin nephelometry detection on a plurality of samples and a plurality of standard substances to obtain a plurality of sample and a plurality of standard substance detection results, and the temperature parameter distribution of the multi-channel position is acquired in the detection process. And performing detection result deviation prediction according to the temperature parameter distribution to obtain detection deviation distribution. A plurality of actual standard product detection deviations are obtained through calculation according to the standard product detection results, and a plurality of implicit detection deviations are obtained through calculation according to the actual standard product detection deviations and the standard product detection deviations. According to the multiple implicit detection deviations, multiple implicit influence categories are obtained, deviation influence rates of the multiple implicit influence categories are obtained, deviation control compensation is carried out in combination with the multiple sample detection deviations, and multiple compensation sample detection results are obtained. The technical problem that in the prior art, multi-channel endotoxin detection is poor in accuracy and reliability of detection results is solved.

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 relates to a cream dosage form sensory evaluation standard substance and application thereof, the standard substance comprises a combination of at least two of a standard substance 1, a standard substance 2 or a standard substance 3, and the composition of the three standard substances is limited. The standard product provided by the invention can simultaneously meet skin feeling scores of low, medium and high skin feeling test related parameter scores, and can be applied to sensory evaluation of cream dosage forms as a reference, so that subjective score differences among different evaluators are reduced, and the stability and repeatability of test data are improved.

The utility model relates to the technical field of food processing, and discloses a continuous frying device for food processing, which comprises a box body, the upper side of the box body is fixedly connected with a fixed cover, the two sides of the upper part of the fixed cover are fixedly connected with motors, the output ends of the motors are fixedly connected with rotating blocks, and the rotating blocks are fixedly connected with rotating shafts. A first rotating plate is fixedly connected to the front side of the rotating block, a second rotating plate is rotatably connected to the first rotating plate through a first rotating shaft, a supporting rod is rotatably connected to the second rotating plate through a second rotating shaft, limiting frames are fixedly connected to the two sides of the front portion of the fixing cover, and the supporting rod is slidably connected to the interior of the limiting frames; the bottom end of the supporting rod is fixedly connected with a fixing frame. According to the utility model, the oil temperature and the frying time of food in the frying process can be accurately controlled, the high-standard product quality requirement can be met, oil smoke and peculiar smell can be effectively removed, and the production environment can be improved.

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.

The utility model discloses a hammer type cyclone mill with high cooling efficiency. The utility model comprises a grinding chamber which is internally provided with a working cavity for accommodating materials to perform crushing work; the air cooling system comprises an air cooling pipeline, the air cooling pipeline is communicated with the working cavity of the grinding chamber, and cold air in the air cooling pipeline can flow to the working cavity; and the liquid cooling system comprises a cooling coil pipe, the cooling coil pipe is located outside the grinding chamber and tightly attached to the grinding chamber, and a flowable refrigerant medium is arranged in the cooling coil pipe and used for conducting heat exchange when working in the grinding chamber, so that the refrigeration effect is achieved. According to the utility model, the cyclone separator is matched with the main machine, the separation cylinder and the filter element cover by adopting the quick joint matching design, so that the cyclone separator is convenient to disassemble and clean; and the sample cup is a standard product provided with a cover and is in threaded connection with the cyclone separator, so that the sample cup is convenient to assemble and disassemble and easy to store, and the working efficiency is improved.

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.

To provide a multi-seller product matching method for a mall that improves matching efficiency. The method includes the steps of: constructing a standard database containing a plurality of standard products; obtaining a first product list consisting of products requested by a user and a second product list consisting of products offered by sellers on the mall based on the standard database; and obtaining a seller combination based on the first product list and the second product list. The seller combination is intended to provide all of the products in the first product list, and each seller in the seller combination has at least one product in the first product list.

The invention belongs to the technical field of electronic commerce recommendation, and provides a recommendation method and system based on product image visual analysis, and the method comprises the steps: carrying out the standardization processing of a product image, obtaining a standard product image, constructing and training an image segmentation model, carrying out the segmentation and interception of the standard product image, obtaining a main body image, and carrying out the recognition of the main body image; the method comprises the following steps: constructing and training a dual-channel depth feature extraction model, performing feature extraction on an obtained main body image and a standard product image, obtaining a dual-channel feature vector group of a product image, generating a product feature library, analyzing a user browsing behavior to judge whether to trigger product recommendation analysis, and if so, judging an analysis strategy of the product recommendation analysis, the recommendation coefficient of the product image is calculated according to the analysis strategy by combining the product feature library, and if the analysis strategy is double-channel calculation and introduces the subject preference weight, a personalized recommendation list is generated according to the recommendation coefficient, the user behavior is analyzed, and the subject preference weight is periodically adjusted.

System for computer-aided portfolio management and resource allocation in organizations, especially projects, characterized by the following features: • that decision options are assigned to one or more product strategy segments (PSS), • that a target percentage share can be assigned to each product strategy segment, • that a non-deletable standard product strategy segment ("Not assigned") is automatically present, the target share of which is dynamically calculated from the difference between 100% and the sum of the user-defined target shares, • that decision options are assigned to this standard segment by default, unless an explicit assignment is made, • that each decision option has an effort measure as a mandatory field, • that an actual distribution of resources per segment is calculated from the effort values ​​and the PSS assignments, • that a deviation value (gap) is determined and visualized from target and actual distributions, • that, in addition, a prioritization of the decision options is generated using evaluation methods (e.g. Pareto analysis, multidimensional evaluation matrix, Strategic Lens) both across strategies and segments.