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35 results about "Specific labelling" patented technology

Cloud file management method based on structured label and taking an object ascore

The invention provides a cloud file management method based on a structured label and taking an object as a core, and the method comprises the following steps: S101, determining a target object, decomposing the object into a structured label tree group, and carrying out the structured label configuration of the object; s102, decomposing the file into a structured label tree group according to thecharacteristics of the file, and performing structured label configuration on the file; s103, associating the file with one or more specific label nodes in the object label configuration to form object-file label association configuration, and storing the object-file label association configuration in a database; and S104, establishing a file cloud management platform, managing objects, files andlabel data through the file cloud management platform, and jointly searching label names through a plurality of keywords to obtain a file set taking the input keywords as themes, thereby achieving thepurpose of multi-dimensional classified management of the files. According to the method, reliable file cloud platform management is adopted to meet the requirement for file integrated management, and the requirements for reliability, safety, uniqueness and the like of file management are met.
Owner:POWERCHINA HUADONG ENG COPORATION LTD

Manganese metal organic framework (MOF) biological composite material and application thereof in detection of food-borne pathogenic bacteria

InactiveCN113372439ASensitive electrochemical impedance signal responseStable structureImmunoglobulinsMaterial resistanceMicrosphereMetal-organic framework
The invention discloses a manganese metal organic framework (MOF) biological composite material and application thereof in detection of food-borne pathogenic bacteria. The manganese MOF biological composite material is formed by carrying out covalent coupling on Mn-MOF-74 nanometer microspheres and a specific biological recognition material; and the particle size of the Mn-MOF-74 nanometer microspheres is 200 to 300 nm. The manganese MOF biological composite material disclosed by the invention is an impedance type electrochemical immunosensor, which is sensitive in electrochemical impedance signal response, stable in structure and capable of specifically recognizing a target pathogenic bacterium-listeria monocytogenes, wherein Mn-MOF-74 crystals are uniform in size, good in biocompatibility and easy to modify; the prepared manganese MOF biological composite material has specific labelling capability on target bacteria and is easily reduced by hydrogen peroxide to generate manganese ions with good conductivity; and a listeria monocytogenes electrochemical detection technology developed by using the biological composite material has the advantages of simple operation, low detection limit and efficient and rapid detection process.
Owner:CHINA AGRI UNIV

Method of labelling interferons with peg

InactiveUS20120128629A1High activityImprove protein stabilityNervous disorderPeptide/protein ingredientsHydrazoneKetone
A method of site specific labelling of an interferon molecule is provided. The method comprises the steps: a) providing a label molecule comprising a PEG moiety having an aldehyde or ketone moiety; b) providing an interferon molecule having a C terminal hydrazide moiety; and c) allowing the aldehyde or ketone moiety of the PEG moiety to react with the C terminal hydrazide of the interferon molecule to form a labelled interferon molecule, which comprises a PEG moiety attached to the C terminus of the interferon molecule via a hydrazone bond. Interferon molecules labelled using such a method are also described.
Owner:ALMAC SCI SCOTLAND

Error intercepted word screening method and system based on n-gram model

The invention discloses an error intercepted word screening method and system based on an n-gram model, and relates to the technical field of network security. The method comprises the steps: acquiring audio translation text data intercepted based on an intercepted word under a specific label; processing the text data through the n-gram model, and screening out data which is not stored in the specific label from the text data as backspacing information; and determining a sentence containing the error intercepted word according to the backspacing information. The method is suitable for interception of forbidden words and sensitive words, especially for interception of the forbidden words and the sensitive words of audio translation text data, can quickly find out mistakenly intercepted sentences and mistakenly intercepted words, and can improve and optimize a forbidden word bank subsequently according to the obtained mistakenly intercepted words; therefore, the interception accuracy of the corresponding intercepted words and the overall interception accuracy are improved.
Owner:北京数美时代科技有限公司

Hierarchical label extraction method based on bidirectional Transformer model

The invention discloses a hierarchical label extraction method based on a bidirectional Transformer model. The hierarchical label extraction method comprises the following steps: obtaining a feature vector through unsupervised pre-training text data; further adjusting and optimizing the feature vector by using a bidirectional Transformer model; in combination with a multi-layer label knowledge base system, performing supervised training on the nested Multi-Class classification model by utilizing softmax and a manual labeling label; and finally, outputting a hierarchical prediction label. According to the invention, a bidirectional Transformer model is adopted, and multi-level labels are combined and nested into a multi-class classification model for learning and training. According to the method, the learning of the multi-level classification labels of the text is realized, and the method can be used for automatic labeling (a plurality of specific labels in a certain field) of the network public opinion text and case analysis (layer-by-layer deepening of case skills) in a police service platform, so that the three-dimensional labeling of the text data is realized.
Owner:WUHAN YANGTZE COMM IND GRP
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