Fashion and Textiles最新文献

This study delves into the dissemination of K-Style in Vietnam, highlighting the multifaceted role of influencers in co-creating Korean culture through vivid videos that embrace and customize K-Style. Our study reveals the interconnectedness of K-Style practice elements (grooming material, styling competence, imagery meaning) and practice systems. We contribute to the understanding of ‘style’ as a concept connected to ethnic contexts and processes. By aligning practice elements, ‘non-carriers’ contribute to constructing the image of ‘Korean style’. Overseas social influencers hold more significant sway over local consumers, adapting to their sociocultural and ethnic characteristics. This study unveils the process through which everyday life accumulates through practice and eventually forms into culture by analyzing the discourse of influencers naturally present in daily life. Our research offers several significant contributions: (1) A topological approach to the hybridization of the K-Style was employed by analyzing real-time cultural transformation captured in videos. (2) Additionally, the process of cultural diffusion by Vietnamese influencers for Korean culture was identified, thus laying the groundwork for future research on consumption culture migration and evolution.

With the recent expansion of the applicability of artificial intelligence into the creative realm, attempts are being made to use AI (artificial intelligence) in the garment development system in various ways, both in academia and the fashion business. Several IT companies have developed and possess AI-based garment design technologies that utilize StyleGAN2 for image transformation. However, they are not widely utilized in the fashion business. Since fashion brands need to create numerous designs to launch new garment products for at least two seasons per year, the adoption of AI-based garment design generation technology can be one way to increase work efficiency. Therefore, this research aims to collect and analyze existing cases of AI-based garment design tools in order to identify the similarities and differences between the garment development processes of human designers and the existing AI-based garment design tools. Based on this analysis, the research aims to develop an AI-based garment development system that takes into consideration the garment development process of human designers, incorporating fashion domain knowledge.

The purpose of this research was to investigate perceptions of risks and benefits associated with popular risky fashion practices (tanning and wearing stilettos) among young adult women. Objectives were to (a) determine if fashion interest predicted benefit perceptions among young women, (b) determine the role of antecedents (fashion interest, risk perceptions, benefit perceptions, consumption emotions) in predicting the behavioral frequency of risky fashion practices, and (c) explore the extent to which tanning and wearing stilettos are similar/different in underlying mechanisms. Undergraduate women were emailed a link to a Qualtrics online survey and a total of 671 provided usable responses; 328 were tanners and 343 wore stilettos. Benefits tapped the attractiveness and fashionability that is expected from engaging in tanning and wearing stilettos, while risks focused on health risks such as melanoma or joint damage associated with tanning or wearing stilettos. Path analyses and decomposition of effects found that fashion interest was positively related to frequency of wearing stilettos, but was not related directly to tanning frequency. Fashion interest was a significant driver of perceived benefits for both risky behaviors. Benefit perceptions increased positive emotion and risk perceptions increased negative emotion; only positive emotion influenced the frequency of risky fashion practices. For both tanning and wearing stilettos, perceived benefits increased risky fashion practice frequency both directly and indirectly through positive emotion. However, perceived risks decreased fashion practice frequency only directly. Thus, perceived benefits outweigh perceived risks among women who engage in these risky fashion practices.

The use of artificial intelligence to predict body dimensions rather than measuring them by stylists or 3D scanners permits to obtain easily all measurements of individual consumers and can consequently reduce costs of population survey campaigns. In this paper, we have compared several models of machine learning to predict about 30 measurements used in fashion industry to construct clothes from 6 easy-to-measure body dimensions and demographic information. The four types of models we have studied are linear regressions, random forests, gradient boosting trees and support vector regressions. To construct and train them we have used anthropometric measurements of 9000 adult individuals of the French population collected by the French Institute of Textiles and Clothing (IFTH) during a national measurement campaign collected between 2003 and 2005. We have analyzed the model prediction performance in terms of individual and global predictions as well as the effect of the training dataset size and the importance of the input features. The linear and the support vector regressions have given the best results with respect to evaluation metrics, predicted distributions and have required less training data than tree-based models. It turns out that the weight and height have been the most important input features for the models considered while the hip girth has been the less important among the input measurements. Since the set of body dimensions used in fashion industry and the morphology depend on the gender, we have decided to treat men and women separately and to compare them.

This study aimed to develop a method for measuring the dynamic drapability of fabrics using a reciprocating motion device that mimics the movement created by shaking a piece of fabric. Five types of fabrics were selected based on their drape coefficients and weights, and the lengths of fabrics were determined based on skirt length (50 cm) and dress length (100 cm). The width and speed of the reciprocating motion were considered as the experimental variables. Results of reciprocating motion-based fabric movement analysis revealed that the number of nodes, the position of the first node, amplitude, total length, and area are significant factors for measuring dynamic drapability. It was found that the longer fabrics had more nodes, enabling measurement of various types of fabrics. Furthermore, it was found that a wider reciprocation width under the same speed and a faster reciprocation speed with the same width favorably demonstrated dynamic drapability, resulting in proportionality between the reciprocating motion and the force transmitted to the fabric. Movement analysis of seven selected conditions and additional samples showed that the optimal condition was a 100-mm reciprocation width and a 150-rpm speed and that the first node’s position is the most significant factor for a dynamic drapability. To verify the proposed measurement method, measuring four pairs of fabrics with similar drape coefficients but different shapes showed that as fabric weight increased, the node moved downward, despite similar drape coefficient values. This confirms that the proposed method can overcome the limitations of the existing drape coefficient.

This study analyzed the functional design by investigating the distribution of clothing pressure of cycling knee brace using a three-dimensional virtual clothing program. Based on the average body size of Korean men in their 40 s, clothing pressure in wearing and cycling condition were collected on five knee brace products. According to the results, bonding fabric products had a high possibility of increasing inconvenience, as they had a higher clothing pressure at all measurement points and soared in motion application. It could be adjusted differently depending on the location by mixing materials or using details, so the design with thick pile fabric or velcro strap fastening added more pressure to the lower part of the knee. The length and circumference size also affected the clothing pressure. The design with tight upper and lower circumference pressured excessively the legs and rolled up and clumped together, while the one with loose lower circumference lacked the sufficient strength to support the knees. Also, the design with a curved outline due to the difference in the length of the front and back, increased the clothing pressure on the lower thigh or the upper calf. Therefore, the functional design of cycling knee braces requires comprehensive consideration of material thickness and structure, detailed size of length and circumference, fastening details, to reduce the pressure at the center and top of the knee and to support the lower part with proper pressure, as reflecting the pressure on the body location that come into contact during the motion.

Based on the social contract theory and social exchange theories, this study examined the Corporations’ social responsibility (CSR) gaps perceived by fashion firms’ internal (i.e., employees) and external (i.e., consumers) stakeholders. In addition, to more deeply understand employees’ perspectives, this study empirically measured the CSR performance gap between employees’ expectations for the CSR standards the industry should achieve and employees’ perceptions of their employers’ CSR performance. This study then explored how the extent of negative incongruence (i.e., when the employer’s CSR performance does not meet the employee’s CSR standards) influenced employees’ attitudes and behaviors with the moderating role of the employees’ work experience. For this, we selected two global fashion firms: H&M and Nike. Through an online survey, 865 usable responses were collected (H&M retail employee n = 158, consumer n = 275; Nike retail employee n = 157, consumers n = 275). One-way Analysis of Variance and a post hoc test showed that the consumer groups for H&M and Nike indicated significantly lower levels of CSR perceptions than those of the employees of each brand. Moreover, the results of structural equation modeling revealed that negative incongruence between the expected industry standard and perceptions of the firm's performance in the area of CSR discouraged organizational commitment, which in turn decreased organizational citizenship behavior and increased turnover intentions. The moderating effect of work experiencewas not found. The originality of this study is that it quantitatively examined both internal and external stakeholders’ CSR perceptions and employees’ CSR perception gaps. The findings provide valuable academic and managerial implications.

This study analyzed fabric drapability in one, two, and three dimensions to provide an assessment method reflecting real conditions. One-dimensional analysis of drapability involved observing the fabric movement by reciprocating motion. The movement appeared differently depending on the fabric characteristics, and the shape and location of the node showed differently, which were considered to be influenced by the weight of the sample along with the drape coefficient. Two-dimensional analysis identified the significant factors for the drape information. This examination confirmed that, even if drape factors were similar, differences in draped shape were observed based on the factors related to node shapes. Three-dimensional analysis, using a 3D scanner, involved the use of the mean distances between draped samples and the standard truncated cone, their standard deviation, and the coefficient of variation. The coefficient of variation was high in the groups wherein the shape of the drape was irregular. In the 3D analysis, the distances between samples and the standard truncated cone were expressed in colors to intuitively deliver the drape information. To determine a factor that could indicate drapability among the factors derived from each dimension, the existing drape coefficient was employed for correlation analysis. Three pairs of samples with similar drape coefficients but different drape shapes were selected to verify the above results. In conclusion, one-dimensional node location, two-dimensional standard deviation of node severity, and three-dimensional coefficient of variation were shown to effectively demonstrate the drape characteristic that the drape coefficient could not indicate.

This study aimed to develop a human-touch smart armband that can transport emotional tactile stimuli to individuals in distant places. To simulate human touch stimuli, a soft pneumatic actuator (SPA) which we refer to in this study as “SPA touch,” of size 7 cm × 7 cm and thickness 0.3 cm was designed using fabric and silicone with nine touch points, which can be individually inflated and allocated within the actuator. The use of thermoplastic polyurethane-coated fabric as a backing material helps obtain one-side inflation toward the skin effectively. By controlling the position and duration time of the inflation of the nine touch points, three basic touch modes (“Touch,” “Double touch,” and “Drag”) and three emotional tactile gestures (“Patting,” “Hugging,” and “Caressing”) were programmed using Python. The evaluation of the operating performance of the basic touch modes and emotional tactile gestures showed that “SPA touch” could properly create and transmit touch stimulation remotely. The human-touch smart armband developed in the process of this study can be used for novel tele-haptic communication with individuals in distant places, such as nursing homes.

This study fabricated and evaluated the textile-type electrodes for application to smartwear that can measure surface electromyography(sEMG). It was manufactured by lock stitch(LS) and moss stitch(MS), and the stitch distance was prepared as 1, 2, or 3 mm. The surface and compression property was measured by using the Kawabata evaluation system, and the sheet resistance and skin-electrode impedance were analyzed. The coefficient of friction(MIU) of the MS was larger than that of the LS. On the other hand, the geometrical roughness(SMD) showed a smaller value. When the same load was applied, the compressive range of the MS was larger than the LS. When it was manufactured as a leg sleeve and worn, the conductive path could be increased as the loops made of conductive yarn become flat as the loops adhere to the skin by the pressure of clothing. Accordingly, the skin-electrode impedance decreased by increasing the area in contact with the skin. As the results of the RMS(root-mean-square), the LS was higher than the MS in a stable. Nevertheless, the SNR(signal-to-noise ratio) value was lower than that of the MS because movement generated noise during operation. Therefore, more stable signal acquisition is possible when applying MS. It is expected that could be applied to producing smartwear for sEMG measurements with superior sEMG signal acquisition performance while having a softer touch and flexibility.