Prabal Kumar Majumdar - Academia.edu (original) (raw)

Papers by Prabal Kumar Majumdar

Different periodic faults in yarns create different designs on fabric depending on the wavelength... more Different periodic faults in yarns create different designs on fabric depending on the wavelength. In this paper, attempts have been made to develop a software program in Microsoft Visual Basic (version 6) to obtain some special effects or designs on fabrics by varying the wavelength of periodic faults. Definite periodic faults are not possible right at this moment, so the faults have been imitated with color effects. Diamond, twill, striped, three dimensional effect, etc. designs can be produced by using this program. Some mathematical functions have been obtained from the software program to create diamond or striped effects on fabrics. Diamond like shapes obtained from the software program have been practically verified on single jersey plain weft-knitted cotton fabrics on a flat-bed machine and found true to a certain extent. Distortions are observed in the design at higher fabric widths due to the uneven tie-dyeing of the fabric by the capillary action of the dye solution used. An attempt has also been made to develop another software program to specify the necessary sequence of colors for a specific length along the continuous weft yarn in a repeat for producing particular design effects or figures on fabrics.

Improving Comfort in Clothing, 2011

Journal of the Textile Institute, 2014

A simplified model of a filled-in jute bag in the form of composite shell of three segments, each... more A simplified model of a filled-in jute bag in the form of composite shell of three segments, each of which is generated by surface of revolution, is assumed. The development and distribution of stresses in the different portions of the composite shell under the action of uniform internal pressure is calculated using membrane theory. The portion subjected to maximum stress and the controlling factors in the failure of bag, such as bag dimension and width/length ratio of bag, are identified. These findings corroborate the observations related to failure of filled jute bags in actual use.

Indian Journal of Fibre & …, 2008

The effect of compressive load on tensile behaviour of jute needle-punched nonwoven fabric has be... more The effect of compressive load on tensile behaviour of jute needle-punched nonwoven fabric has been studied with special reference to crack or void generation. A test box is designed to apply compressive load on the fabric during testing in horizontal cloth tensile tester. The ...

Autex Research Journal, 2005

AUTEX Research Journal, Vol. 5, No2, June 2005 © AUTEX ... DETERMINATION OF THE TECHNOLOGICAL VAL... more AUTEX Research Journal, Vol. 5, No2, June 2005 © AUTEX ... DETERMINATION OF THE TECHNOLOGICAL VALUE OF COTTON FIBRE: A COMPARATIVE STUDY OF THE TRADITIONAL AND MULTIPLE-CRITERIA DECISION-MAKING APPROACHES ... Abhijit Majumdar1, Prabal ...

The effect of dynamic loading on jute and jute-polypropylene blended needle-punched nonwoven fabr... more The effect of dynamic loading on jute and jute-polypropylene blended needle-punched nonwoven fabrics has been studied. It is observed that with the increase in cycles of dynamic loading, the thickness loss increases with diminishing rate up to a certain limit and thereafter it does not change. Thickness loss decreases with the increase in punch density, depth of needle penetration and area density up to a minimum value beyond which it increases. The recovery fro m compression increases with the increase in above parameters. As the proportion of polypropylene fibre increases in the blend with jute, the thickness loss as well as relaxation fro m compression increases. Chemically texturized jute fibre, fi bre laying technique and hessian re inforcement have a great effe ct on thickness loss as well as recovery from compression due to dynamic loading.

Eri/acrylic blended yarn has been prepared at different blend ratio in ring spinning system follo... more Eri/acrylic blended yarn has been prepared at different blend ratio in ring spinning system following draw-frame blending technique. The Box and Behnken design for three variables and three levels has been used to study the influence of count of the yarn spun (Ne), twist multiplier and proportion of eri fibre in the blends on some important tensile properties of the yarns produced. The chosen level of variables remaining within the industrially acceptable limits shows that fibre parameters and yarn parameters are the determining factors to influence yarn tensile properties.

Research Journal of Textile and Apparel, 2010

This paper presents a comprehensive review of soft computing applications in the domain of fabric... more This paper presents a comprehensive review of soft computing applications in the domain of fabrics and clothing. In the last two decades, soft computing techniques, such as artificial neural network, fuzzy logic and genetic algorithm, have been used abundantly for fabrics and clothing modelling, manufacturing, quality control and marketing. This review is aimed at presenting a compendium of research work done so far on the applications of soft computing techniques in fabrics and clothing science and engineering. In the beginning of the paper, a brief introduction of soft computing techniques is provided. Then, the applications of soft computing methods in fabric property modelling (tensile, bending, shear, drape, handle, comfort, thickness and compression, air permeability, porosity, etc.) are provided. In the subsequent sections, soft computing applications for fabric defect identification in static and dynamic conditions, fabric classification, fabric engineering, machine control ...

Journal of The Institution of Engineers (India): Series E, 2013

This paper presents a comparative analysis of two modeling methodologies for the prediction of ai... more This paper presents a comparative analysis of two modeling methodologies for the prediction of air permeability of plain woven handloom cotton fabrics. Four basic fabric constructional parameters namely ends per inch, picks per inch, warp count and weft count have been used as inputs for artificial neural network (ANN) and regression models. Out of the four regression models tried, interaction model showed very good prediction performance with a meager mean absolute error of 2.017 %. However, ANN models demonstrated superiority over the regression models both in terms of correlation coefficient and mean absolute error. The ANN model with 10 nodes in the single hidden layer showed very good correlation coefficient of 0.982 and 0.929 and mean absolute error of only 0.923 and 2.043 % for training and testing data respectively.

Journal of Natural Fibers, 2014

Ranking and selection of textile fabrics for a particular end-use requirement is a complex task. ... more Ranking and selection of textile fabrics for a particular end-use requirement is a complex task. In this article, an attempt has been made to develop a simple index of handloom fabric quality, which can be used for selecting fabrics for a specified end use. The Analytic Hierarchy Process (AHP) and Multiplicative Analytic Hierarchy Process (MAHP) of multi-criteria decision making (MCDM) have been used for ranking 25 handloom cotton fabrics in terms of their overall quality value considering their applicability as summer clothing materials. The rank correlation between the rankings elicited from two MCDM methods was found to be 0.926 which implies that the rankings given by AHP and MAHP are in high degree of agreement with each other and any of the two methods can be chosen for ranking of fabrics.

Journal of The Institution of Engineers (India): Series E, 2013

Eri silk is one of the four varieties of silk available in India which has excellent thermal insu... more Eri silk is one of the four varieties of silk available in India which has excellent thermal insulation property. With a view to explore its blending possibilities with polyester, manufacturing of eri/polyester blended yarn at different blend ratio in ring spinning system has been successfully performed following drawframe blending technique. The Box and Behnken design of experiment for three variables and three levels has been used to study the influence of count of the yarn spun (Ne), twist multiplier and proportion of eri fibre in the blends on some important tensile properties of the yarns produced. The chosen level of variables remaining within the industrially acceptable limits shows that fibre character and yarn parameters are the determining factors to influence yarn tensile properties. Validity of Hamburger model for the prediction of blended yarn tenacity has also been assessed for the blended yarn produced.

A novel approach of cotton fibre grading and selection has been proposed by using the Tcchnique f... more A novel approach of cotton fibre grading and selection has been proposed by using the Tcchnique for Order Preference by Similarity to Ideal Solution (TOPSIS) method of Multi-Criteria Decision Making (MCDM). Cotton bales were grouped into different categories based on their quality values determined by TOPSIS method and Spinning Consistency Index (SCI). Laydowns were then formed by random and frequency relative picking algorithms from 1200 real cotton bales with known HVI properties. Computer simulation results demonstrate that the frequency relative picking of TOPSIS and SCI are capable to reduce the between laydown variability of major cotton properties.

The breaking elongation of rotor-spun yarns has been predicted by using linear regression, artifi... more The breaking elongation of rotor-spun yarns has been predicted by using linear regression, artificial neural network and neuro-fuzzy models. Cotton fibre properties measured by high volume instrument and yarn count have been used as inputs to the prediction models. Prediction accuracy is found to be better for artificial neural network and neuro-fuzzy models than that for regression model. The relative importance of yarn count and cotton fibre properties to rotor yarn elongation has also been studied. Yarn count and cotton fibre micronaire are found to be dominant input factors influencing the breaking elongation of rotor-spun yarns.

Journal of The Institution of Engineers (India): Series E, 2014

The process of fabric engineering which is generally practised in most of the textile mills is ve... more The process of fabric engineering which is generally practised in most of the textile mills is very complicated, repetitive, tedious and time consuming. To eliminate this trial and error approach, a new approach of fabric engineering has been attempted in this work. Data sets of construction parameters [comprising of ends per inch, picks per inch, warp count and weft count] and three fabric properties (namely drape coefficient, air permeability and thermal resistance) of 25 handloom cotton fabrics have been used. The weights and biases of three artificial neural network (ANN) models developed for the prediction of drape coefficient, air permeability and thermal resistance were used to formulate the fitness or objective function and constraints of the optimization problem. The optimization problem was solved using genetic algorithm (GA). In both the fabrics which were attempted for engineering, the target and simulated fabric properties were very close. The GA was able to search the optimum set of fabric construction parameters with reasonably good accuracy except in case of EPI. However, the overall result is encouraging and can be improved further by using larger data sets of handloom fabrics by hybrid ANN-GA model.

Textile Research Journal, 2004

This paper presents a comparative study of three modeling methodologies for predicting the breaki... more This paper presents a comparative study of three modeling methodologies for predicting the breaking elongation of ring spun cotton yarns. Constituent cotton fiber properties and yarn count are used as inputs to these models. The predictive powers of the three different models—mathematical, statistical, and artificial neural network—are estimated and com pared. The relative importance of various cotton fiber properties measured by a high volume instrument is also investigated using the artificial neural network model.

Journal of the Textile Institute, 2005

This paper presents a new multi-criteria decision-making approach to determine the quality value ... more This paper presents a new multi-criteria decision-making approach to determine the quality value of cotton fibre. Major cotton fibre properties were considered and their relative importance or weights were determined by a typical pair-wise comparison method. Cotton fibres were ranked according to their relative closeness with respect to the best and worst possible alternatives. This ranking was compared with the

Journal of the Textile Institute, 2005

This paper presents the application of a hybrid neuro-fuzzy system for the prediction of cotton y... more This paper presents the application of a hybrid neuro-fuzzy system for the prediction of cotton yarn strength from HVI fibre properties. The proposed system possesses the advantages of both artificial neural networks and fuzzy logic, and is thus more intelligent. HVI fibre test results are used to train the neuro-fuzzy inference system and its prediction performance is compared with those

Journal of the Textile Institute, 2006

Engineering of spun yarns having specific tensile, evenness and hairiness characteristics is a lo... more Engineering of spun yarns having specific tensile, evenness and hairiness characteristics is a long-cherished dream of spinning technologists. Selection of suitable raw materials at minimum cost and optimisation of process parameters are the two major tasks to be achieved to manufacture engineered yarn. Advent of high-speed fibre-testing machines and development of powerful modelling tools such as artificial neural network (ANN) have provided a great impetus in the yarn engineering research. This article demonstrates the feasibility of yarn engineering by developing a yarn-to-fibre 'reverse' model, using ANN. This approach is entirely different from the prevailing forward models, which predict the properties of final yarn using the fibre properties as inputs. The cost minimisation of cotton fibre mix was ensured by using the classical linear programming approach in combination with ANN. The engineered yarns demonstrated good agreement with the target yarn properties.

Fibers and Polymers, 2004

In many engineering applications, the final decision is based on the evaluation of a number of al... more In many engineering applications, the final decision is based on the evaluation of a number of alternatives in terms of a number of criteria. This problem may become very intricate when the selection criteria are expressed in terms of different units or the pertinent data are difficult to be quantified. The Analytic Hierarchy Process (AHP) is an effective way in

Experimental Thermal and Fluid Science, 2013

ABSTRACT This paper presents the prediction of thermal resistance of handloom cotton fabrics by a... more ABSTRACT This paper presents the prediction of thermal resistance of handloom cotton fabrics by artificial neural network models using four primary fabric construction parameters, i.e. ends per inch (EPI), picks per inch (PPI), warp count and weft count as the inputs. ANN model with seven nodes in the single hidden layer exhibited the overall best performance with coefficient of determination of 0.90 and 0.86 and mean absolute error of only 5.13% and 4.23% during training and testing respectively. The importance of fabric construction parameters on the thermal resistance of fabrics was also analyzed by the developed ANN model. Weft count, EPI and warp count were found to be the first three most important fabric constructional parameters in descending order of importance in predicting thermal resistance of plain woven cotton fabrics. (c) 2013 Elsevier Inc. All rights reserved.

Different periodic faults in yarns create different designs on fabric depending on the wavelength... more Different periodic faults in yarns create different designs on fabric depending on the wavelength. In this paper, attempts have been made to develop a software program in Microsoft Visual Basic (version 6) to obtain some special effects or designs on fabrics by varying the wavelength of periodic faults. Definite periodic faults are not possible right at this moment, so the faults have been imitated with color effects. Diamond, twill, striped, three dimensional effect, etc. designs can be produced by using this program. Some mathematical functions have been obtained from the software program to create diamond or striped effects on fabrics. Diamond like shapes obtained from the software program have been practically verified on single jersey plain weft-knitted cotton fabrics on a flat-bed machine and found true to a certain extent. Distortions are observed in the design at higher fabric widths due to the uneven tie-dyeing of the fabric by the capillary action of the dye solution used. An attempt has also been made to develop another software program to specify the necessary sequence of colors for a specific length along the continuous weft yarn in a repeat for producing particular design effects or figures on fabrics.

Improving Comfort in Clothing, 2011

Journal of the Textile Institute, 2014

A simplified model of a filled-in jute bag in the form of composite shell of three segments, each... more A simplified model of a filled-in jute bag in the form of composite shell of three segments, each of which is generated by surface of revolution, is assumed. The development and distribution of stresses in the different portions of the composite shell under the action of uniform internal pressure is calculated using membrane theory. The portion subjected to maximum stress and the controlling factors in the failure of bag, such as bag dimension and width/length ratio of bag, are identified. These findings corroborate the observations related to failure of filled jute bags in actual use.

Indian Journal of Fibre & …, 2008

The effect of compressive load on tensile behaviour of jute needle-punched nonwoven fabric has be... more The effect of compressive load on tensile behaviour of jute needle-punched nonwoven fabric has been studied with special reference to crack or void generation. A test box is designed to apply compressive load on the fabric during testing in horizontal cloth tensile tester. The ...

Autex Research Journal, 2005

AUTEX Research Journal, Vol. 5, No2, June 2005 © AUTEX ... DETERMINATION OF THE TECHNOLOGICAL VAL... more AUTEX Research Journal, Vol. 5, No2, June 2005 © AUTEX ... DETERMINATION OF THE TECHNOLOGICAL VALUE OF COTTON FIBRE: A COMPARATIVE STUDY OF THE TRADITIONAL AND MULTIPLE-CRITERIA DECISION-MAKING APPROACHES ... Abhijit Majumdar1, Prabal ...

The effect of dynamic loading on jute and jute-polypropylene blended needle-punched nonwoven fabr... more The effect of dynamic loading on jute and jute-polypropylene blended needle-punched nonwoven fabrics has been studied. It is observed that with the increase in cycles of dynamic loading, the thickness loss increases with diminishing rate up to a certain limit and thereafter it does not change. Thickness loss decreases with the increase in punch density, depth of needle penetration and area density up to a minimum value beyond which it increases. The recovery fro m compression increases with the increase in above parameters. As the proportion of polypropylene fibre increases in the blend with jute, the thickness loss as well as relaxation fro m compression increases. Chemically texturized jute fibre, fi bre laying technique and hessian re inforcement have a great effe ct on thickness loss as well as recovery from compression due to dynamic loading.

Eri/acrylic blended yarn has been prepared at different blend ratio in ring spinning system follo... more Eri/acrylic blended yarn has been prepared at different blend ratio in ring spinning system following draw-frame blending technique. The Box and Behnken design for three variables and three levels has been used to study the influence of count of the yarn spun (Ne), twist multiplier and proportion of eri fibre in the blends on some important tensile properties of the yarns produced. The chosen level of variables remaining within the industrially acceptable limits shows that fibre parameters and yarn parameters are the determining factors to influence yarn tensile properties.

Research Journal of Textile and Apparel, 2010

This paper presents a comprehensive review of soft computing applications in the domain of fabric... more This paper presents a comprehensive review of soft computing applications in the domain of fabrics and clothing. In the last two decades, soft computing techniques, such as artificial neural network, fuzzy logic and genetic algorithm, have been used abundantly for fabrics and clothing modelling, manufacturing, quality control and marketing. This review is aimed at presenting a compendium of research work done so far on the applications of soft computing techniques in fabrics and clothing science and engineering. In the beginning of the paper, a brief introduction of soft computing techniques is provided. Then, the applications of soft computing methods in fabric property modelling (tensile, bending, shear, drape, handle, comfort, thickness and compression, air permeability, porosity, etc.) are provided. In the subsequent sections, soft computing applications for fabric defect identification in static and dynamic conditions, fabric classification, fabric engineering, machine control ...

Journal of The Institution of Engineers (India): Series E, 2013

This paper presents a comparative analysis of two modeling methodologies for the prediction of ai... more This paper presents a comparative analysis of two modeling methodologies for the prediction of air permeability of plain woven handloom cotton fabrics. Four basic fabric constructional parameters namely ends per inch, picks per inch, warp count and weft count have been used as inputs for artificial neural network (ANN) and regression models. Out of the four regression models tried, interaction model showed very good prediction performance with a meager mean absolute error of 2.017 %. However, ANN models demonstrated superiority over the regression models both in terms of correlation coefficient and mean absolute error. The ANN model with 10 nodes in the single hidden layer showed very good correlation coefficient of 0.982 and 0.929 and mean absolute error of only 0.923 and 2.043 % for training and testing data respectively.

Journal of Natural Fibers, 2014

Ranking and selection of textile fabrics for a particular end-use requirement is a complex task. ... more Ranking and selection of textile fabrics for a particular end-use requirement is a complex task. In this article, an attempt has been made to develop a simple index of handloom fabric quality, which can be used for selecting fabrics for a specified end use. The Analytic Hierarchy Process (AHP) and Multiplicative Analytic Hierarchy Process (MAHP) of multi-criteria decision making (MCDM) have been used for ranking 25 handloom cotton fabrics in terms of their overall quality value considering their applicability as summer clothing materials. The rank correlation between the rankings elicited from two MCDM methods was found to be 0.926 which implies that the rankings given by AHP and MAHP are in high degree of agreement with each other and any of the two methods can be chosen for ranking of fabrics.

Journal of The Institution of Engineers (India): Series E, 2013

Eri silk is one of the four varieties of silk available in India which has excellent thermal insu... more Eri silk is one of the four varieties of silk available in India which has excellent thermal insulation property. With a view to explore its blending possibilities with polyester, manufacturing of eri/polyester blended yarn at different blend ratio in ring spinning system has been successfully performed following drawframe blending technique. The Box and Behnken design of experiment for three variables and three levels has been used to study the influence of count of the yarn spun (Ne), twist multiplier and proportion of eri fibre in the blends on some important tensile properties of the yarns produced. The chosen level of variables remaining within the industrially acceptable limits shows that fibre character and yarn parameters are the determining factors to influence yarn tensile properties. Validity of Hamburger model for the prediction of blended yarn tenacity has also been assessed for the blended yarn produced.

A novel approach of cotton fibre grading and selection has been proposed by using the Tcchnique f... more A novel approach of cotton fibre grading and selection has been proposed by using the Tcchnique for Order Preference by Similarity to Ideal Solution (TOPSIS) method of Multi-Criteria Decision Making (MCDM). Cotton bales were grouped into different categories based on their quality values determined by TOPSIS method and Spinning Consistency Index (SCI). Laydowns were then formed by random and frequency relative picking algorithms from 1200 real cotton bales with known HVI properties. Computer simulation results demonstrate that the frequency relative picking of TOPSIS and SCI are capable to reduce the between laydown variability of major cotton properties.

The breaking elongation of rotor-spun yarns has been predicted by using linear regression, artifi... more The breaking elongation of rotor-spun yarns has been predicted by using linear regression, artificial neural network and neuro-fuzzy models. Cotton fibre properties measured by high volume instrument and yarn count have been used as inputs to the prediction models. Prediction accuracy is found to be better for artificial neural network and neuro-fuzzy models than that for regression model. The relative importance of yarn count and cotton fibre properties to rotor yarn elongation has also been studied. Yarn count and cotton fibre micronaire are found to be dominant input factors influencing the breaking elongation of rotor-spun yarns.

Journal of The Institution of Engineers (India): Series E, 2014

The process of fabric engineering which is generally practised in most of the textile mills is ve... more The process of fabric engineering which is generally practised in most of the textile mills is very complicated, repetitive, tedious and time consuming. To eliminate this trial and error approach, a new approach of fabric engineering has been attempted in this work. Data sets of construction parameters [comprising of ends per inch, picks per inch, warp count and weft count] and three fabric properties (namely drape coefficient, air permeability and thermal resistance) of 25 handloom cotton fabrics have been used. The weights and biases of three artificial neural network (ANN) models developed for the prediction of drape coefficient, air permeability and thermal resistance were used to formulate the fitness or objective function and constraints of the optimization problem. The optimization problem was solved using genetic algorithm (GA). In both the fabrics which were attempted for engineering, the target and simulated fabric properties were very close. The GA was able to search the optimum set of fabric construction parameters with reasonably good accuracy except in case of EPI. However, the overall result is encouraging and can be improved further by using larger data sets of handloom fabrics by hybrid ANN-GA model.

Textile Research Journal, 2004

This paper presents a comparative study of three modeling methodologies for predicting the breaki... more This paper presents a comparative study of three modeling methodologies for predicting the breaking elongation of ring spun cotton yarns. Constituent cotton fiber properties and yarn count are used as inputs to these models. The predictive powers of the three different models—mathematical, statistical, and artificial neural network—are estimated and com pared. The relative importance of various cotton fiber properties measured by a high volume instrument is also investigated using the artificial neural network model.

Journal of the Textile Institute, 2005

This paper presents a new multi-criteria decision-making approach to determine the quality value ... more This paper presents a new multi-criteria decision-making approach to determine the quality value of cotton fibre. Major cotton fibre properties were considered and their relative importance or weights were determined by a typical pair-wise comparison method. Cotton fibres were ranked according to their relative closeness with respect to the best and worst possible alternatives. This ranking was compared with the

Journal of the Textile Institute, 2005

This paper presents the application of a hybrid neuro-fuzzy system for the prediction of cotton y... more This paper presents the application of a hybrid neuro-fuzzy system for the prediction of cotton yarn strength from HVI fibre properties. The proposed system possesses the advantages of both artificial neural networks and fuzzy logic, and is thus more intelligent. HVI fibre test results are used to train the neuro-fuzzy inference system and its prediction performance is compared with those

Journal of the Textile Institute, 2006

Engineering of spun yarns having specific tensile, evenness and hairiness characteristics is a lo... more Engineering of spun yarns having specific tensile, evenness and hairiness characteristics is a long-cherished dream of spinning technologists. Selection of suitable raw materials at minimum cost and optimisation of process parameters are the two major tasks to be achieved to manufacture engineered yarn. Advent of high-speed fibre-testing machines and development of powerful modelling tools such as artificial neural network (ANN) have provided a great impetus in the yarn engineering research. This article demonstrates the feasibility of yarn engineering by developing a yarn-to-fibre 'reverse' model, using ANN. This approach is entirely different from the prevailing forward models, which predict the properties of final yarn using the fibre properties as inputs. The cost minimisation of cotton fibre mix was ensured by using the classical linear programming approach in combination with ANN. The engineered yarns demonstrated good agreement with the target yarn properties.

Fibers and Polymers, 2004

In many engineering applications, the final decision is based on the evaluation of a number of al... more In many engineering applications, the final decision is based on the evaluation of a number of alternatives in terms of a number of criteria. This problem may become very intricate when the selection criteria are expressed in terms of different units or the pertinent data are difficult to be quantified. The Analytic Hierarchy Process (AHP) is an effective way in

Experimental Thermal and Fluid Science, 2013

ABSTRACT This paper presents the prediction of thermal resistance of handloom cotton fabrics by a... more ABSTRACT This paper presents the prediction of thermal resistance of handloom cotton fabrics by artificial neural network models using four primary fabric construction parameters, i.e. ends per inch (EPI), picks per inch (PPI), warp count and weft count as the inputs. ANN model with seven nodes in the single hidden layer exhibited the overall best performance with coefficient of determination of 0.90 and 0.86 and mean absolute error of only 5.13% and 4.23% during training and testing respectively. The importance of fabric construction parameters on the thermal resistance of fabrics was also analyzed by the developed ANN model. Weft count, EPI and warp count were found to be the first three most important fabric constructional parameters in descending order of importance in predicting thermal resistance of plain woven cotton fabrics. (c) 2013 Elsevier Inc. All rights reserved.