Predicting Bursting Strength of Plain Knitted Fabrics using ANN
In this study, the effects of yarn parameters, on the bursting strength of the plain knitted fabrics were examined with the help of artificial neural networks. In order to obtain yarns having different properties such as tenacity, elongation, unevenness, the yarns were produced from six different types of cotton. In addition to cotton type, yarns were produced in four different counts having three different twist coefficients. Artificial neural network (ANN) was used to analyze the bursting strength of the plain knitted fabrics. As independent variables, yarn properties such as tenacity, elongation, unevenness, count, twists per inch together with the fabric property number of wales and courses per cm were chosen. For the determination of the best network architecture, three levels of number of neurons, number of epochs, learning rate and momentum coefficient were tried according to the orthogonal experimental design. After the best neural network for predicting the bursting strength of the plain knitted fabrics was obtained, statistical analysis of the obtained neural network was performed. Satisfactory results for the prediction of the bursting strength of the plain knitted fabrics were gained as a result of the study.
A study on subjective assessment of knit fabric by ANFIS
The purpose of this study was to examine the effects of the structural properties of plain knit fabrics on the subjective perception of textures, sensibilities, and preference among consumers. This study, then, aimed to provide useful information with respect to planning and designing knitted fabrics by predicting the subjective characteristics analyzed according to their structural properties. For this purpose, we employed statistical analysis tools, such as factor and regression analysis and an adaptive-network-based fuzzy inference system(ANFIS), thereby combining the merits of fuzzy and neural networks and presupposing a non-linear relationship. Through factor analysis, we also categorized the subjective textures into ‘roughness’, ‘softness’, ‘bulkiness’ and ‘stretch-ability’ with R2=70.32 %: and categorized the sensibilities into ‘Stable/Neat’, ‘Natural/Comfortable’ and ‘Feminine/Elegant’ with R2=68.12 %. We analyzed subjective textures, sensibilities, and preference with ANFIS, assuming non-linear relationships; consequently, we were able to generate three or four fuzzy rules using wool/rayon fiber content and loop length as input data. The textures of roughness and softness exhibited a linear relationship, but other subjective characteristics demonstrated a non-linear input-output relationship. Compared with linear regression analysis, the ANFIS exhibited had higher predictive power with respect to predicting subjective characteristics.
Hygroscopic Expansion of some Casting Investments
CREDIT is generally given to Taggart1 for introducing the cast gold inlay to the dental profession. Although he realized that gold shrinks when cooled from molten state to solid state of room temperature, the investment available to him did not supply sufficient compensation. In 1910, Van Horn2 published a paper dealing with a method by which he obtained the compensation by means of wax expansion. The next major research in connection with this problem was the work of Coleman3 at the National Bureau of Standards. He determined the gold shrinkage to be 1.25 per cent and presented a casting technic with compensation values of quantitative nature. The total compensation for the gold shrinkage was obtained by the combination of the setting and thermal expansion of the mold. This procedure is the general practice followed at the present time for compensation. There are some disadvantages to this method. Skinner has indicated the difficulty of obtaining smooth castings and the improper compensation for the casting shrinkage.4 It has been found by Hollenback5 and Scheu6a that castings made at a high temperature are rougher than those made at a low temperature (450° C.), depending upon the great difference in thermal expansion between plaster of Paris and silica, which causes a poor union of the fine particles. This may also result in friability and there may be some warpage due to the differential expansion. A method which provides sufficient compensation at a low mold temperature is the hygroscopic casting technic.b Wilson7 showed that certain plasters expand as much as 0.0044 inch to the inch by taking up moisture from the air. With this information at hand, Scheula, b tested some commercial investment to determine what results the addition of moisture would have. He found6b: (1) All of the casting investments that were tested expanded. (2) The thicker the mix, the greater the expansion. (3) A mix with hot water expanded more than one with cold water. (4) The time at which the mix is placed in the water is of great importance. It was found that if the mix is placed in the water early, it would not expand so much as when placed in a little later. It was also found that if the mix was placed in the water after a certain time, it could not expand to the maximal amount. (5) The temperature of the water in which the mix is placed is important, for two reasons; (a) the temperature of the water controls slightly the expansion of the investment, and (b) water at a temperature of 1000 F. slightly softens the wax pattern so that the fine margins are not marred while expansion is taking place. The mix should remain in the water at least 20 minutes to obtain the full expansion, after which time no further expansion is obtained.