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Preparation method for paper-making process tobacco sheet and finished product of paper-making process tobacco sheet

ActiveCN103141928AImprove single layer retentionImprove breathabilityTobacco preparationPlant fibrePaper based
The invention belongs to the field of tobacco industry and relates to a preparation method for a functional harm-reduction and tar-reduction paper-making process tobacco sheet and a finished product of the paper-making process tobacco sheet. The preparation method for the paper-making process tobacco sheet comprises the following steps of extracting and concentrating effective components of tobacco; mixing formulas; pulping and blending fibers; manufacturing paper with pulp; dipping, drying and tearing and shaping. The blending process comprises the following steps of: adding non-tobacco plant fiber pulp of which the beating concentration is 3-4 percent and the Schopper-Riegler (SR) beating degree is 18-28 to tobacco mixed fiber pulp, adding filling to a machine chest, regulating the pulping concentration to 2-3 percent by water, and evenly mixing. By the use or the combine use of the filling and the non-tobacco plant fiber pulp, the combustion state of the sheet can be improved while physical properties, such as the air permeability, the retention and the tensile strength of a paper base, are improved, i.e., harmful ingredients of smoke, such as tar and carbon monoxide of the paper-making process tobacco sheet, can be effectively reduced, and hazard indexes of cigarettes are reduced. Meanwhile, technical-economic indicators, such as the speed and the input- output efficiency of a paper machine, also can be improved.
Owner:杭州利群环保纸业有限公司

Query optimization method based on join index in data warehouse

The invention relates to a query optimization method based on a join index in a data warehouse. The method comprises the following steps: creating a fact table foreign key join index based on a dimension table surrogate key; creating a join index update strategy; when a predicate condition exists on a dimension table, making a predicate judgment after direct access to dimension table record through the join index, and performing calculation through a dynamic bitmap join index by reference to a bitmap join index to generate a join bitmap index; when the selection rate on the dimension table is very low, further compressing a dimension table bitmap in order to raise the cache level of dimension table bitmap calculation; and calculating simple memory address access by only using an array-bitmap data structure with a reference bitmap join index calculation method based on co-processor memory calculation. Through adoption of the query optimization method, the calculation performance of the bitmap index can be effectively increased. Moreover, the query optimization method can be combined with high-performance co-processors such as GPU and Intel Xeon Phi TM to accelerate the index calculation performance, and can be widely applied to the field of data warehouses.
Owner:RENMIN UNIVERSITY OF CHINA

SIFT characteristic reducing method facing close repeated image matching

InactiveCN101697232AConvenient and fast near-duplicate image query capabilityGood performanceImage analysisSpecial data processing applicationsConvolutionWeighting coefficient
The invention discloses an SIFT characteristic reducing method facing close repeated image matching, comprising the following steps of carrying out gaussian kernel convolution processing on each image of an image library to obtain image key points; carrying out gaussian uniformization on the contrast ratio and the principal curvature ratio of the key points and linear weighting to obtain significance degree; sequencing from small to large according to the significance degree of the key points, and selecting a number of the key points specified by uses to realize reduction; generating descriptors for the reduced key points according to the positions, the dimensions and the directional information of the reduced key points to obtain SIFT characteristics; establishing an image library index for all SIFT characteristic sets by a partial sensitivity hash technique, and providing query function of the close repeated image matching. The invention utilizes the research and the realization results of an image partial characteristic technique and the partial sensitivity hash technique, can conveniently and fast provide the query ability of the close image matching and enable the users to regulate the weighting coefficient of a reduction algorithm and the upper limit threshold value of the number of the SIFT characteristics according to application requirements so as to provide the best property.
Owner:ZHEJIANG UNIV

Room temperature self-crosslinking polyacrylate pressure-sensitive adhesive and preparation method and application thereof

The invention belongs to the field of room temperature self-crosslinking materials, and discloses a room temperature self-crosslinking polyacrylate pressure-sensitive adhesive and a preparation method and application thereof. The method comprises the steps of preparing a pre-emulsion from 85-95 parts of acrylate soft monomer, 5-15 parts of hard monomer, 2-5 parts of functional monomer, 1.3-4 parts of emulgator and 30-55 parts of deionized water by mass fraction; then heating up the pre-emulsion, the deionized water, an initiator, the emulgator and a PH buffer agent for reaction; dripping a chain transfer agent, the pre-emulsion and an initiator solution when the emulsion shows blue light; adding ketone-containing carbonyl monomer, heating up together and reacting; then cooling down and regulating pH value to be 6.5-7.0; and adding hydrazide monomer, stirring and mixing uniformly, so as to obtain the room temperature self-crosslinking polyacrylate pressure-sensitive adhesive. The room temperature self-crosslinking polyacrylate pressure-sensitive adhesive prepared by the method has excellent indexes like excellent initial adhesive force, excellent persistent viscosity force and excellent peel strength, and can be used for preparing labels with good bond performance.
Owner:SOUTH CHINA UNIV OF TECH
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