http://nopr.niscair.res.in/handle/123456789/2573 Search the Channel search http://nopr.niscair.res.in/simple-search http://nopr.niscair.res.in/handle/123456789/2616 Title: Computer-aided statistical module for hand-knotted carpets <br/> <br/>Authors: Shakyawar, D B; Gupta, N P; Patni, P C; Arora, R K <br/> <br/>Abstract: This study deals with the development of equations to predict abrasion loss and carpet hand value (CHV) of hand-knotted carpets. Best-fit equation obtained from regression analysis shows that the abrasion loss depends on fibre diameter and number of medullated fibres present in the yarn as well as pile density of carpet. The regression coefficient is found to be 0.47, which is highly significant (p<0.01). The best-fit equation for CHV reveals that it depends on pile height, carpet thickness and pile density. The coefficient of regression is found to be 0.77, which is significant at p<0.01. Based on these equations, a software is developed using C language which can predict abrasion loss and CHV within the range of error ± σ value. <br/> <br/>Page(s): 405-410 http://nopr.niscair.res.in/handle/123456789/2615 Title: Computer-aided textile design ‘LibTex’ <br/> <br/>Authors: Křemenáková, Dana; Mertová, Iva; Kolčavová-Sirková, Brigita <br/> <br/>Abstract: The system LibTex has been used for the prediction of structure, parameters and properties in the line fibre – yarn – fabric. The system contains databases of fibre properties & fabric weaves, and the prediction is based on the complex of theoretical and regression models. The material and technological parameters for different materials, yarns and fabrics are included. The main use of this system is for optimal fabric design based on virtually created fabric. System can be used for the prediction of grey cotton dobby fabric properties for technical and clothing applications. <br/> <br/>Page(s): 400-404 http://nopr.niscair.res.in/handle/123456789/2614 Title: Modeling of compression properties of needle-punched nonwoven fabrics using artificial neural network <br/> <br/>Authors: Debnath, Sanjoy; Madhusoothanan, M <br/> <br/>Abstract: The present study is concerned with the modeling of compression properties of needle-punched nonwoven fabrics produced from polyester and blend of jute-polypropylene fibres with varying fabric weight, needling density and blend ratio of jute and polypropylene fibres. Initial thickness, percentage compression, percentage thickness loss and compression resilience are the compression properties predicted with the help of artificial neural networks. A very good correlation (R2 values) with minimum error between the experimental and the predicted values of compression properties have been obtained by ANN with two and three hidden layers. An attempt has also been made for experimental verification of the predicted values for the input variables not used during the training phase. The prediction of compression properties by artificial neural network model in some particular sample is less accurate due to lack of learning during training phase. <br/> <br/>Page(s): 392-399 http://nopr.niscair.res.in/handle/123456789/2613 Title: Automatic recognition of fabric structures based on digital image decomposition <br/> <br/>Authors: Liqing, L; Jia, Tingting; Chen, Xia <br/> <br/>Abstract: A method to recognize fabric structures automatically based on digital image decomposition has been introduced. The method includes establishing a Wiener filter adapted to the fabric texture. A woven fabric image can be decomposed into horizontal and vertical subimages by using this Wiener filter. These two subimages contain the weft and warp texture information respectively. After thresholding, the gray-level subimages are transformed into binary images, in which the weft or warp floats range periodically. Then the weaving density can be figured out. Based on the preceding work, the positional information of yarns in every single subimage can directly help to enclose every interlacing point. Considering the variety of gray value in each point unit, warp point and weft point can be distinguished. The basic structures for woven fabric (plain, twill and satin) have been evaluated and it is found that the density for woven fabric can be calculated exactly and the structures can be identified clearly. <br/> <br/>Page(s): 388-391