Nowadays, the popularity of the internet has continuously increased. Predicting human body dimensions intelligently would be beneficial to improve the precision and efficiency of pattern making for enterprises in the apparel industry. In this study, a new predictive model for estimating body dimensions related to garment pattern making is put forward based on radial basis function (RBF) artificial neural networks (ANNs). The model presented in this study was trained and tested using the anthropometric data of 200 adult males between the ages 20 and 48. The detailed body dimensions related to pattern making could be obtained by inputting four easy-to-measure key dimensions into the RBF ANN model. From the simulation results, when spreading parameter σ and momentum factor α were set to 0.012 and 1, the three-layer model with 4, 72, and 8 neurons in the input, hidden, and output layers, respectively, showed maximum accuracy, after being trained by a dataset with 180 samples. Moreover, compared with a classic linear regression model and the back propagation (BP) ANN model according to mean squared error, the predictive performance of the RBF ANN model put forward in this study was better than the other two models. Therefore, it is feasible for the presented predictive model to design garment patterns, especially for tight-fitting garment patterns like activewear. The estimating accuracy of the proposed model would be further improved if trained by more appropriate datasets in the future.
More metal fiber content of blended electromagnetic shielding (EMS) fabric results in higher shielding effectiveness (SE) of the fabric. However, there is little information about the influence of the metal fiber content on the SE considering the fabric structure. This study constructs an index of metal fiber content per unit area (MFCPUA), and discusses the influence of the metal fiber content on the SE of the EMS fabric when fabric parameters are changed. Computations for the MFCPUA and the thickness and porosity of the metal fiber arrangement are given, and then experiments are designed to test the SE of different EMS fabric samples. According to the experimental results, the influence of the MFCPUA on the SE is analyzed and influence mechanism is discussed when the fabric weaves, emission frequencies and weft and warp densities are changed. The results show that the MFCPUA and the SE are in positive increase relation; the frequency and the SE are in the negative increase relation when the metal fiber content is unchanged. The influence of the fabric weave type on the SE depends on the length of the yarn floats; the SE values of fabric with the same weave are the same when the MFCPUA is the same regardless of the fabric density.
Electromagnetic radiation is becoming increasingly serious around our living environment, which seriously endangers people's health and interferes with the operation of electronic equipment. The research and development of anti-electromagnetic radiation fabric have drawn more and more attention. However, the influencing rules and mechanisms of conductive fiber content, fabric tightness, warp–weft density, conductive yarn arrangement, weave type, and electromagnetic wave frequency on fabric electromagnetic shielding effectiveness have not been clarified. Therefore, in this study, a series of fabrics containing stainless steel fibers were produced. Meanwhile, the influencing rules of various factors on electromagnetic shielding effectiveness and the quantitative relationship between some factors and electromagnetic shielding effectiveness were discussed. The results showed that all factors had different degrees of influence on electromagnetic shielding effectiveness, and the relationship between electromagnetic shielding effectiveness and electromagnetic wave frequency could be approximately expressed as: [Formula: see text]. At the same time, the influencing mechanisms of various factors on electromagnetic shielding effectiveness were analyzed in combination with fabric microstructure and macrostructure, the intrinsic parameters of the fabric and the electromagnetic shielding effectiveness mechanism. The results are expected to provide a reference for the establishment of electromagnetic shielding fabric model and enterprise production.
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