Fashion and Textiles最新文献

In the post-pandemic era, integrating e-commerce and deep learning technologies is critical for the fashion industry. Automatic classification of women’s pants presents challenges due to diverse styles and complex backgrounds. This study introduces an optimized Swin Transformer model enhanced by the Global Attention Mechanism (GAM) to improve classification accuracy and robustness. A novel dataset, FEMPANTS, was constructed, containing images of five main trouser styles. Data preprocessing and augmentation were applied to enhance the model's generalization. Experimental results demonstrate that the improved model achieves a classification accuracy of 99.12% and reduces classification loss by 34.6%. GAM enhances the model's ability to capture global and local features, ensuring superior performance in complex scenarios. The research results not only promote the automation process in the fashion industry but also provide references for other complex image classification problems. This study highlights advancements in fashion e-commerce, offering practical applications for inventory management, trend analysis, and personalized recommendations, while paving the way for future innovations in deep learning-based image recognition.

Fashion plays a critical role in self-expression and confidence-building, but adolescents with adolescent idiopathic scoliosis (AIS) have limited fashion choices when they wear a spinal brace that is bulky and rigid underneath their clothing. Spinal braces also have a significant impact on their self-and body-images, social life, and overall quality of life. This study proposes a morphing torso mannequin that accurately measures the interface pressure between the brace and skin, and evaluates the effectiveness of scoliosis braces, thus eliminating the need for ongoing X-rays and ensuring patient safety. The constructed mannequin replicates the AIS torso by using a validated finite element model and 3D-printing and molding techniques. A comparison of the in-brace effects on the morphing mannequin shows significant improvements in spinal alignment and reductions in Cobb’s angles (5.2° and 2.2°), which is consistent with clinical X-ray images. The large correlation coefficient (0.95) between the mannequin and clinical results confirms its ability to simulate the corrective effects of spinal bracing accurately. The proposed morphing mannequin provides valuable information for applying appropriate pressure to halt the progression of spinal curvature while maximizing the wear comfort for AIS patients. Additionally, the mannequin allows for the assessment of clothing fit, thus simulating the effects of wearing a brace and enabling fashion designers to create garments that accommodate the unique physical profile of AIS patients.

This study aimed to analyze those factors affecting the adhesion between substrate fabrics and 3D printing filaments by evaluating the influence of fabric surface characteristics, fiber composition, yarn type, and the fabric’s structure. The results showed that among nylon, PET, and cotton, nylon demonstrated the highest peel strength; however, overall, surface characteristics had a more significant impact on adhesion than fiber composition, and in terms of yarn type, fabrics made from staple fibers had higher peel strength than those made from filament yarns, which is probably due to the rougher surface of staple yarns enhancing adhesion. Regarding fabric structure, among woven, knitted, and nonwoven fabrics, nonwoven fabrics demonstrated the highest peel strength, confirming that the structure and density of the fabric play a crucial role in adhesion. It was also found conclusively that fabric surface roughness and porosity affect peel strength significantly, with rougher surfaces and higher porosity leading to increased adhesion. This is because rougher surfaces provide more area for adhesion, and higher porosity allows the molten 3D filament to penetrate more easily between the fibers, thereby improving adhesion. This study provides practical guidelines for improving the adhesion characteristics of 3D-printed composite fabrics.

Textile electrode is capable of measuring the myoelectric potentials of skeletal muscles such as electromyography (EMG), owing to their outstanding low weight, flexibility, breathability, and comfort properties. Nonetheless, textile surfaces often exhibit intermittent adhesion between the electrode surface and the skin, which can result in fluctuations in electrical resistivity due to the inherent characteristics of textiles. This study aimed to suggest the solutions to improve adhesive of textile electrode for the improvement of electrode performance with high quality signal by minimizing these intermittent contacts. For this, an adhesive intermediate, two different conductive materials, between the skin and the textile electrode was introduced to improve the instability skin contact, respectively. To assess the impact of various adhesive intermediates on knitted electrodes, two different types of adhesive intermediates were utilized: a conductive hydrogel-based adhesive intermediate and a conductive paste-based adhesive intermediate. Moreover, the durability of knitted electrodes with adhesive intermediate was evaluated by assessing the changes of signal quality during drying time for 180 min. As a results of sEMG measurement, it was confirmed that the sEMG signal was stably detecting by applying the adhesive intermediate. Both types of adhesive intermediate significantly increased the signal acquisition performance of knitted electrodes by more than threefold. After five washing cycle, the knitted electrodes with two types of adhesive intermediate maintained approximately 80% of their initial SNR values. Therefore, the use of the adhesive intermediate presented in this study not only improves the performance of the electrode but also ensures reusability.

The surface area of the working electrode plays a crucial role in determining the sensor’s performance, especially in enzymatic sensors. Increasing the surface area of the working electrode has a significant impact on the sensor’s functionality. This research focused on developing textile-based sensors using a multi-layer concept, employing the direct coating method. Two different sensors which are multilayer textile-based sensor (MTBS) and single-layer textile-based sensor (STBS) were prepared, while commercial screen-printed carbon electrode (SPCE) was also used as a comparison. The measurements were carried out using potassium ferricyanide solutions with concentrations of 0.01 M, 0.02 M, 0.03 M, 0.04 M, and 0.05 M at a voltage of 1 V, with a maximum duration up to the end of the measurement and a time interval of 0.5 s. According to the research findings, the fluid spreading speed of the SPCE is the lowest when compared to the spreading speeds of the MTBS and STBS. Specifically, the fluid spreading speed of the SPCE is 4.3 times slower than that of the STBS and 51 times slower than that of the MTBS. Utilizing a multi-layer concept with specific coatings can lead to better-performing sensors in terms of stability and sensitivity. The MTBS exhibits the greatest sensitivity, as indicated by its linear equation slope of 717.230 µA µM⁻¹ cm⁻².

This study investigated the antimicrobial efficacies of fabrics (100% cotton and 100% silk) dyed with an ethanol extract of Gardenia jasminoides (G. jasminoides). More specifically, these fabrics were dyed using a G. jasminoides extract with a dye bath ratio of 1:20 at 40–60 °C for 60 min, followed by post-mordanting. The concentrations of the aluminum sulfate, copper sulfate, and ferrous sulfate mordants were each set to 3% (o.w.f.). The samples were mordanted using a mordant bath ratio of 1:30 at 40 °C for 20 min. The iron mordant slightly increased the dye uptake (K/S) of the cotton fabric but did not increase the dye uptake (K/S) of the silk fabric. The antimicrobial efficacies of the dyed fabrics against methicillin-resistant Staphylococcus aureus (MRSA) ATCC 33591 were determined to be 99.8 and 87.8% for the cotton and silk fabrics, respectively. The inhibitory effects of the cotton and silk fabrics against MRSA were 30.5 × and 167.3 × the inoculum size, respectively, indicating the superior inhibitory effect of the dyed cotton fabric. These results suggest that the fabrics dyed with G. jasminoides extract may possess antibacterial activity against antimicrobial-resistant bacteria.

This study aims to explore effective dust removal methods for the improvement of clothing care systems by analyzing the fabric movement caused by the twist motion and examining its influence on dust removal performance. The finite element method simulation was used to model the tension at different vertical and horizontal positions of the fabric as a spring array, to calculate the fabric movements at each position over time when a twisting force was applied and enable comparison with experiments. When observing the fabric movement due to the twist motion with actual fabrics, silk showed the greatest movement, followed by cotton and linen. Cotton experienced decreasing force from the top to the bottom, with increased amplitude at the bottom due to fluttering caused by the bottom not being fixed. When examining the fabric movement according to the velocity, slower velocity did not effectively transmit twist force to the bottom, while faster velocity resulted in more small movements. The analysis revealed that greater force at faster velocity led to better dust removal performance. Therefore, for efficient dust removal, the force transmitted to the fabric should be increased. Most dust is removed within the first 10 min, so exerting a strong force for a short duration is important.

This study investigates the impact of 3D printed midsoles with biomimetic structures of varying densities on plantar pressure during static and dynamic motions. The midsoles were designed with three densities of Tyson polygon (TS) structures: 1TS, 2TS, and 3TS. Plantar pressure tests were conducted on midsoles during static and dynamic motions such as walking, running, and jumping. The data were analyzed based on hypotheses related to samples, motions, and 10 plantar pressure zones. As results, for static motion, all midsoles improved pressure distribution and reduced peak pressure compared to barefoot conditions, with 1TS being the most effective. During dynamic motions, 1TS and 2TS effectively distributed plantar pressure in the midfoot and heel areas, while 3TS provided better support and stability during high-intensity activities like jumping. Statistical analysis revealed that 1TS offered comfort and flexibility but lacked support, 2TS balanced support and cushioning, and 3TS provided superior support and stability but reduced elasticity during jumps. In dynamic motions, 1TS excelled in walking, and 2TS performed best in high-intensity activities such as running and jumping. In the meta areas (M2 and M3), 1TS reduced pressure by over 30% during walking and nearly 40% during running, while 3TS showed similar reductions during jumping, with BF showing higher pressures compared to running. Thus, this study highlights the effectiveness of 1TS and 2TS in reducing pressure in the meta and midfoot areas, emphasizing the importance of selecting the right midsole density for optimal comfort and performance across different activities.

In order to optimize the design of three-dimensional tubular woven (3DTW), a design method and matrix model of 3DTW were proposed based on normal loom, where 3D woven was used as tube wall and the weaving method of tubular fabric was applied. Herein, 3D woven was used as the tube wall to obtain the face weave diagram, and the back weave diagram was subsequently obtained by the “negative flip” method. According to the method of layering weaving, the structure diagram of 3DTW could be determined. In order to obtain back weave matrix, the elements in the face weave matrix were replaced and reordered by MATLAB function, and Kronecker product operation was used to achieve the proportional embedding of the face and the back weave matrix and the assignment of the face warp by lifting point elements when weaving the back weft. Finally, the weave matrix of 3DTW was obtained. The proposed design method and matrix model can improve the design efficiency and reduce weaving cost of 3DTW, which could provide a reference for the design and preparation of 3DTW.

Astronauts wear liquid perfused garments inside their outer spacesuits for regulating body temperature. The present study explored relationships between local heat production from the upper arm and body morphology while wearing liquid perfused sleeve. Heat extraction from the upper arm of 19 subjects (8 males and 11 females) during three different exercise modes (running at 6–8 km∙h⁻¹, cycling at 40–55 W, and arm ergometer at 10–20 W) and rest has been investigated. The total body fat (27.5 ± 7.2%), body mass index (24.4 ± 2.7 kg·m⁻²), arm surface area (589 ± 90 cm²), and arm volume (1300 ± 300 mL) were considered as covariates. Subjects wore a liquid perfused sleeve over the upper arm (left) with the water inlet temperature of 24.0 ± 0.3 °C and the heat extraction was calculated using the water flow rate and temperature differences. Heat extraction from the upper arm showed no significant differences among the three exercises. During cycling, there was a negative relationship between heat extraction and total body fat (r = − 0.527, P < 0.05). Heat extraction was more related to the arm volume (P < 0.05) than the surface area of the upper arm, which was significant only for the male group in the cycling mode. For the female group, heat extraction was related to upper arm temperature in the cycling and arm exercise modes (for both exercises P < 0.05). These results can be applied to improve liquid cooling garments for astronauts, considering their body morphology and sex.