Textile technologies are revolutionising with Industry 4.0. This research aims to introduce a novel real-time monitoring system in the knitting sector using the Internet of Things and machine learning technologies to measure and display productivity precisely through an interactive dashboard. Sensors were integrated into a circular knitting machine to track productivity and performance. A comparative statistical analysis through three processing phases demonstrates the high accuracy and precision of the current system, as evidenced by minimum variance and error values. The t-test results validate a non-significant difference between actual and device-measured production. Thus, it enables real-time monitoring, preventive maintenance, and cost-effective quality in knitting machines.

Based on the balanced scorecard, starting from the IT strategic goal of digital transformation, this paper deconstructs the strategic goal into four dimensions: “finance”, “customer”, “internal process”, and “learning and growth”. According to the characteristics of textile and garment enterprises, this paper puts forward the performance evaluation index system for the digital transformation of textile and garment enterprises. Using this evaluation index system, we collected data from 201 textile and garment enterprises by questionnaire and evaluated their digital transformation performance. The results show that all effective sample enterprises have performed well on the first-level performance indicators of digital transformation. However, variance analysis shows a significant difference after grouping the samples by size. Large enterprises are relatively best, followed by medium-sized enterprises, and small enterprises rank third. Because the small enterprises have relatively weak performance in terms of “internal processes”, “learning, and growth” dimensions. In addition, the analysis of variance also found that the more developed the economy in the region where the enterprise is located, the better its performance in the “customer” dimension. In terms of evaluating the second-level performance indicators for all effective sample enterprises, the performance of the “internal process”, “customer”, and “learning and growth” dimensions is good. However, the performance of the “financial” dimension is poor, with the highest performance weight. Textile and garment enterprises should fully play the role of digital transformation in the “financial” dimension. From the evaluation results of the third-level performance indicators for all effective sample enterprises, “expansion of products or services”, “reduced number of customer complaints”, and “the frequency of enterprise business and violation risk is reduced” have higher weights. Still, the ranking of performance evaluation values is lower. These third-level performance indicators are specific indicators that textile and garment enterprises should focus on and actively improve in digital transformation.

There is a severe lack of research on the heat transfer mechanisms for various populations, with most studies primarily concentrating on adults. This study aimed to investigate the difference in the convective heat transfer coeffient (hc) of the whole and individual body parts between infant and adult under ventilation. A numerical model for heat transfer between the human body and the environment was developed and validated against experiments involving a baby thermal manikin. The temperature and airflow fields surrounding the human body and the value of hc were simulated under seven air velocities ranging from 0.1 m/s to 2.5 m/s. The results indicated that, under natural ventilation, the overall hc for infants and adults was 4.82 W/m²·K and 4.29 W/m²·K, respectively. Infants exhibited higher regional hc values at their surface than adults, especially on their hands and feet. This discrepancy was more pronounced as the air velocity increased. Furthermore, regression equations were developed for the two body sizes to establish the connection between hc and air velocity. These findings contribute to a better understanding of the complex interplay between body size and convective heat transfer, providing fundamental data for enhancing the accuracy of infant thermal response predictions by incorporating more precise boundary conditions.

This paper uses a combination of alginate impression and body surface tracing to study the skin deformation mechanism of upper limbs in alpine skiing, and the sleeve pieces were divided into 5 regions combined with the characteristics of human heat and sweat. The thickness, permeability and constant elongation of 7 kinds of elastic fabrics commonly used in tight sports clothing were tested to provide a quantitative basis for fabric compatibility in different zones. The results showed that the skin deformation in the elbow joint area was significant, the transverse changes were mostly stretching, and the longitudinal changes were mostly contraction; the characteristics of heat and sweat in upper limbs were distinct, which could be divided into shoulders, upper arms and below the elbow joint; the order of fabric permeability is as follows: 6 > 3 > 7 > 4 > 1 > 2 > 5, the order of warp tensile elastic modulus is as follows: 7 > 6 > 1 > 5 > 2 > 4, the order of weft tensile elastic modulus is as follows: 1 > 3 > 7 > 6 > 5 > 2 > 4; the abc zones of the sleeve are dominated by the demand for air permeability, which is compatible with 3#, 7# and 6# fabrics respectively, the de zones are dominated by the demand for tensile elasticity, which is compatible with 4# and 2# fabrics respectively.

Based on the image and textual data, the characteristics of the style, structure and pattern of the costumes in the Tang tomb murals were analysed using garment engineering. The size of each part of the costumes was inferred using the proportion method, and a set of formulas was summarised. Based on comparing three kinds of pattern extraction algorithms, the Canny operator combined with the morphology algorithm was optimal for pattern extraction for costume restoration. 3D virtual technology was used to digitally restore the costumes of the tomb murals of YanFei. The effect of costume restoration was evaluated according to the rank sum operation method and questionnaire results.

Sanitary napkins are indispensable personal care products for women. China is the largest market for feminine hygiene products in the world. China’s sanitary napkin industry is also large and stable, with annual sales reaching billions. However, despite the promise and potential of China’s sanitary napkin industry, there are few studies on it. In this study, anchored on industrial organisation theory and the structure-conduct-performance (SCP) paradigm, the characteristics of China’s sanitary napkin industry will be explored through three specific aspects: structure, conduct, and performance. Structure refers to the degree and nature of competition for products and services of an industry. Conduct is the market policies sellers adopt to achieve certain objectives, such as pricing and non-pricing. Performance is the outcomes reflecting the effects of market operation. The analysis will be conducted from the three aspects respectively. The results demonstrate that: (i) the market type of China’s sanitary napkin industry has shifted from competition to oligopoly V and has highly advertising-dependent product differentiation;(ii) cost-plus pricing conduct is adopted, and advertising sponsorship and channels construction have become a focus in this industry; (iii) the profit level of China’s sanitary napkin industry is relatively high but declining, and the industry scale structure needs to be improved. This study provides a theoretical perspective on the current standing of China’s sanitary napkin industry, which can assist the industry in growing steadily.

Near-field communication (NFC) is a short-distance wireless data transmission technology with potential for wearable sensors. Xu et al. (2020) developed a battery-free smart textile patch with an NFC antenna and a temperature sensor (STP-NFC) [1]. To address potential issues with the testing protocol that could affect the accuracy and precision of temperature measurement from the STP-NFC, a validation experiment was conducted at a fixed room temperature of 20 ℃. This was done using a commercial IR imager to compare the results with the STP-NFC results. Results showed excellent accuracy with an average temperature of 21.50 ℃ and a difference of only 0.36 ℃ from an IR imager’s reading. The STP-NFC also had excellent precision with a small standard deviation of 0.83. Optimal performance was achieved with a 6 mm distance, a 150-second time interval, and a 4-second scanning duration for each scan. Additionally, the gage repeatability and reproducibility (R&R) study has been conducted to assess the STP-NFC measurement system’s consistency, and the STP-NFC’s reproducibility has been demonstrated. These results have implications for developing reliable wearable medical monitoring devices using NFC technology.