This study integrates literature analysis and quantitative data mining (K-prototypes, hierarchical clustering) to classify Chinese paper-cutting's core features (modeling, techniques, cultural implications), revealing inherent classification rules and cultural connotations for application in digital preservation and innovative design strategies. The results show that K-prototypes algorithm can effectively integrate paper-cutting techniques and cultural semantic features (silhouette coefficient = 0.75), and divide 128 samples into three categories: Class 1 (n = 46) is mainly composed of high-complexity symmetrical patterns, which carries the Confucian philosophical metaphor of the golden mean; Class 2 (n = 43) is characterized by the theme of life engraved in the positive engraving, which reflects the Taoist view of nature; Class 3 (n = 39) takes folk symbols as the core and embodies the collective cultural memory. The research results not only fill the shortcomings of the existing qualitative analysis, but also provide a theoretical basis and method support for the digital protection of traditional art and cultural and creative industries, and at the same time promote the integration of traditional culture and modern science and technology, and promote the development of cultural and creative industries.

This paper focuses on tight-fitting sportswear as the research subject and investigates the dynamic influence of comfort perception on overall comfort. By developing a comprehensive evaluation system that encompasses both subjective and objective measures of comfort, this study systematically reveals the interactive mechanisms and dynamic characteristics of multi-dimensional comfort perceptions, including heat and humidity comfort, compression comfort, touch comfort, among others. The findings indicate that (1) local comfort levels fluctuate over time, with varying weights influencing overall comfort; (2) during 6 km/h exercise, key local discomfort sensations impacting overall comfort include restraint feelings of shank, stuffy feeling (cool feeling) of shank, restraint feeling of thigh, etc.; (3) there are significant correlations between stuffy feeling with sticky body feeling and humidity feeling respectively; additionally, notable correlations exist between sticky body feeling with humidity feeling and rough feeling. This study offers provides a more scientific basis for optimizing tight-fitting sportswear design.

In order to improve the precision of clothing development of fast fashion brands, consumers’ sense of experience, and brand loyalty, a design method of clothing pattern is proposed by combining Kansei engineering theory and improved particle swarm optimization (IPSO)–back propagation neural network (BPNN) model. First, based on the theory of Kansei engineering, the perceptual image experiment of clothing patterns was designed, and the mean value of perceptual image evaluation of clothing patterns by young consumers was obtained through an online questionnaire survey. Second, based on the IPSO and the BPNN, the nonlinear correlation mapping model between the design elements of clothing pattern and consumers’ perceptual image is established. Finally, based on the calculation of target image weight by analytic hierarchy process (AHP) method and IPSO-BPNN model, the optimal combination of clothing pattern design elements under the requirement of multi-target image is output. Taking the paper-cut pattern of sweater shirt as an example, the feasibility of this research method is verified. The research not only helped the designer to design a costume pattern that meet the individual emotional needs of consumers, but also provided a clear design index and reference, and made the costume design process more targeted, precise, and intelligent.

As a unique intangible cultural heritage in Chinese traditional culture, paper-cut art is now facing the dilemma of inheritance and development, and with the death of paper-cut artists and the damage and loss of paper-cut works, some paper-cut types also disappear. Therefore, the digital protection of paper-cut art is urgent. This research is based on the improved genetic algorithm adaptive optimization of Canny operator threshold and Grab-Cut algorithm to achieve intelligent extraction and segmentation of intangible cultural heritage paper-cut patterns. First, the collected paper-cut images are smoothed by bilateral filtering to improve the image quality. Second, based on the Canny operator optimized by the improved genetic algorithm, the overall contour of the paper-cut pattern is extracted. Then, the Grab-Cut algorithm is designed to segment the contours of decoupage design elements in a targeted way, and the vector image is processed by CDR software to obtain an independent editable vector image. Finally, the contour extraction experiments of different kinds of paper-cut images are compared by different algorithms. The results show that the method proposed in this article can effectively detect the true edge of the pattern in paper-cut images and complete the extraction of the pattern contour, and the accuracy of the segmentation pixels of each design element of paper-cut pattern is greater than 96 per cent. It provides a new method for the digital protection and innovative application of intangible cultural heritage paper-cut art.

This research aims to explore the application of artificial intelligence-generated content (AIGC) technology in traditional Chinese paper-cut design and promote the protection and inheritance of traditional Chinese paper-cut culture. First, the paper-cut works of paper-cut artist are analyzed to extract the characteristic factors of her design styles. Second, based on the characteristics of the paper-cut style, a dedicated dataset for model training is constructed and passed into the fine-tuning network to train and generate a Low-Rank Adaptation (LoRA) fine-tuning model with the design style characteristics of the paper-cut artists. Finally, the paper-cut LoRA model is combined with the stable diffusion model to complete the intelligent design practice of traditional paper-cut. Through experimental verification, the paper-cut model trained in this research can effectively realize the migration design of traditional paper-cut artists' design style and improve the efficiency of paper-cut design. This research proposes a paper-cut style generation method based on AIGC, which provides a new perspective for the protection and development of paper-cut culture. This method reduces the difficulty of paper-cut design, optimizes the design process, and improves design efficiency, providing technical support for the sustainable development of paper-cut art. At the same time, it also has important significance and value for the digital inheritance and innovation of other intangible cultural heritage.

With globalization and modernization accelerating, the protection of intangible cultural heritage faces significant challenges. Chinese paper-cutting, a cultural treasure, has become a key focus due to its unique value and exquisite craftsmanship. However, inheritance is threatened by aging practitioners, skill loss, and market decline. This highlights the urgent need for digital preservation and the creation of a cultural gene bank. This paper proposes a dual strategy: digital preservation and cultural gene decoding. High-precision data acquisition and image processing technologies enable detailed documentation and conservation of paper-cutting techniques and imagery. Additionally, artificial intelligence and machine learning are used to decode and classify cultural genes, systematically building a cultural gene bank to support continuity and innovation. A case study examines technical, resource, and ethical challenges in digital preservation, addressing data standardization, intellectual property protection, and cultural integrity. Looking ahead, this paper explores technological innovation and cross-cultural collaboration to enhance market applications and encourage social engagement with paper-cutting. These efforts provide a theoretical foundation and practical strategies for safeguarding live transmission and global cultural heritage.

In order to solve the problem of mismatch between consumers’ personalized needs and clothing pattern design, a method of clothing pattern image design was proposed based on Kansei engineering theory to obtain a perceptual consumer image. Then, a correlation model between clothing pattern design elements and perceptual images of young people was established through the quantitation theory type I, and the mapping relationship between the two and the degree of influence on consumer preference was presented by the diagram method. The paper-cut pattern of a T shirt is taken as an example to verify the feasibility of this research method. The results show that it not only provides designers with clear design indicators and references, but also makes the design process more objective and scientific.

In order to design Fujian paper-cut patterns that meet the perceptual needs of consumers and better inherit and develop them in modern society, a Fujian paper-cut pattern image design method based on perceptual engineering and the Whale Optimization Algorithm optimized BP neural network (WOA-BP) neural network is proposed. First, based on the theory of Kansei engineering, six representative paper-cut pattern samples and their main modeling features were determined through questionnaire survey, multi-dimensional scaling analysis, cluster analysis, and analytic hierarchy process. Second, the semantic difference method is used to obtain the perceptual image evaluation value of the representative paper-cut pattern, and combined with the principal component analysis method, the representative image vocabulary is extracted. Finally, the WOA-BP neural network is used to construct the mapping relationship between consumers' perceptual images and paper-cut pattern modeling features, and calculate the paper-cut pattern modeling code combinations corresponding to consumers' image needs. At the same time, the paper- cut pattern design using the image vocabulary 'modern-traditional' as an example verifies the feasibility of the method in this article. Compared with the existing method of designing paper-cut patterns based solely on the subjective experience of the designer, the method of this article can correlate the perceptual needs of consumers with the corresponding modeling characteristics of paper-cut patterns, making the design of paper-cut patterns targeted, precise and intelligent.

In order to understand consumers’ cognition of clothing style and design clothing products more in line with people’s emotional needs, a garment style perceptual image prediction model based on PSO-BP neural network was constructed by taking professional dress as an example. Firstly, the professional dress samples were screened and the style design elements were deconstructed and coded. The Kansei engineering theory and factor analysis method were used to determine the representative adjectives, so as to reduce the cognitive dimension of the target users for the style characteristics and perceptual image of the dress. Then, using the sample style design element code as the input layer and the user’s perceptual image evaluation score as the output layer, the PSO-BP neural network’s perceptual image prediction model for professional dress styles is constructed. Finally, the sample data were input into the PSO-BP model, BP neural network and GA-BP model for simulation and calculation, and the error analysis of the results proved that the PSO-BP prediction model is effective and advanced. Designers can use this model to quickly transform customers’ perceptual needs with dress style design elements, so as to improve the scientificity of design decision-making and better meet customer needs.

Abstract A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperature and humidity of other key parts from the temperature and humidity data of some parts of the human body when wearing tight sportswear, so as to realize the temperature and humidity data prediction of all key points of the human body. The temperature and humidity of different people wearing tights were collected by DHT sensors. The experimental results show that the LSTM neural network structure proposed has higher prediction accuracy than other algorithms, and the model evaluates the feasibility of temperature and humidity data of tights in a state of motion, which facilitates the study of dynamic thermal and humid comfort and reduces the time cost of analyzing the temperature and humidity distribution and changing the law during human movement. It will effectively promote the study of temperature and humidity changes when people wear sports tights, provide theoretical reference for the study of human skin temperature in the field of sports medicine, and provide practical guidance for the application of human skin temperature changes in sports clothing production, diagnosis and prevention of sports injuries.

四平戏由明代中叶的弋阳腔演变而来,在历史长河中较好地保留了明代独特的声腔艺术形式,被戏剧史专家称为"中国戏剧活化石".随着时代的变迁,四平戏在现代社会的传承和发展受到阻碍.为了更好地传承和发展四平戏文化,文章尝试通过挖掘、分析四平戏元素特色,并采用现代设计手法将其融入到文创产品中,以使四平戏文化元素以新的形式融入现代生活,同时促进文创产品发展.

In order to understand consumers' perceptual cognition of Zhangpu paper-cut patterns and grasp the innovative application direction. The four design elements of paper-cut patterns were extracted by morphological analysis, and representative perceptual vocabulary were selected using Kansei engineering theory and factor analysis, then the design elements and perceptual evaluation scores of representative words are used as the input and output data of the GWO-BP neural network, respectively, to establish an intelligent model that can predict consumers' perceptual cognition of paper-cut patterns. To verify the superiority of the model, the predicted result of BP and FA-BP are compared with GWO-BP neural network. The results show that although the convergence speed of the GWO-BP model is slightly lower than that of the FA-BP model, its prediction accuracy is significantly better than other algorithms. Designers can use the model to quickly redesign the paper-cut pattern to better meet the aesthetic needs of modern consumers.

四平戏由明代中叶的弋阳腔演变而来,它较好地保留了明代的声腔艺术形式,被戏剧史专家称为"中国戏剧活化石".文章对非遗四平戏的传承发展进行了研究,并结合地方村民的反馈,提出可行性思路.最后得出结论,在服装设计中的创新应用等对非遗四平戏带来了有益的影响,对传承中国非遗文化有着重要意义.

文章从地方本科高校服装设计专业课程改革入手,分析福建地域文化与地方本科高校服装设计专业课程的融合现状以及福建地域文化作为地方本科高校服装设计专业课程资源开发利用的价值,结合地方本科高校服装设计专业课程类型,探讨福建地域文化资源在地方本科高校服装设计专业课程中的开发、利用策略.通过高校服装设计专业课程内容与福建地域文化紧密融合,使服装设计专业课程质量得到有效提高,与地域文化的活态传承互利共赢.

Abstract Focusing on the mechanism of "human-sport-clothing" system, this paper studies people-oriented sports comfort, and analyzes the influence of different tights combinations (i.e. tights and tights with different fabrics) and the effect of exercise status on the human body parts and overall comfort. In addition, because there are many impact indicators of comfort and the relationship is complicated, it is difficult for general models to deal with this relationship, which leads to the low accuracy of comfort prediction model. To solve this problem, this paper proposes an efficient intelligent prediction model, namely a new hybrid model based on PSO and CS algorithm. The results show that different fabric combinations have significant effects on local and overall comfort under different sports conditions. PSO-CS hybrid model is superior to PSO and CS model in predicting local and global comfort.

Purpose In order to help companies better grasp the perceptual needs of consumers for patterns, so as to carry out more accurate product pattern development and recommendation, this research develops a product pattern design system based on computer-aided design. Design/methodology/approach First, use the Kansei engineering theory and method to obtain the user's perceptual image, and deconstruct and encode the pattern based on the morphological analysis method, then through the BP neural network to construct the mapping relationship between the user's perceptual image and the pattern design elements, and finally calculate and find the corresponding design code combination according to the design goal to guide the pattern design. Findings Taking costume paper-cut patterns as an example, the feasibility of this system is verified, the design system can well reflect the user's perceptual image in the pattern design and improve the efficiency of pattern customization service. Originality/value Compared with the traditional method that relies on the designer's personal experience to propose a design plan, this research provides scientific and intelligent design methods for product pattern design.

In order to study the comfort of tight-fitting sportswear in winter, this paper designed a series of motions, and explored the distribution of comfort perception under different sports conditions by evaluating the wearing perception of human body. Finally, through the acquired experimental data, intelligent prediction models were established, and the prediction results were visualized, which makes the comfort distribution more intuitive. The results show that there are great differences in the parts that affect the overall comfort perception under different sports conditions; different ages subjects have different perceptions of comfort; Particle Swarm Optimization-Cuckoo Search-Adaptive Network-based Fuzzy Inference System has better prediction accuracy, and could replace the wearing trials.

To study the upper body characteristics of young men, the body circumference, length, width, thickness, and angle of young men aged 18–25 and 26–35 years were collected to comprehensively characterize the concave and convex features of the front, back, and side of the human body. The Cuckoo Search-Density Peak intelligent algorithm was used to extract the feature factors of the upper body of men, and to cluster them. To verify the effectiveness of the intelligent algorithm, the clustering results of Cuckoo Search-Density Peak, Density Peak, Particle Swarm Optimization-Density Peak algorithm, Ant Colony Optimization-Density Peak algorithm, Genetic Algorithm-Density Peak algorithm, and Artificial Bee Colony-Density Peak algorithm were evaluated by Silouette and F-measures, respectively. The results show that the Cuckoo Search-Density Peak algorithm has the best clustering results and is superior to other algorithms. There are some differences in somatotype characteristics and somatotype indexes between young men aged 18–25 and 26–35 years.

In order to improve the efficiency and accuracy of predicting the thermal and moisture comfort of skin-tight clothing (also called skin-tight underwear), principal component analysis(PCA) is used to reduce the dimensions of related variables and eliminate the multicollinearity relationship among variables. Then, the optimized variables are used as the input parameters of the coupled intelligent model of the genetic algorithm (GA) and back propagation (BP) neural network, and the thermal and moisture comfort of different tights (tight tops and tight trousers) under different sports conditions is analysed. At the same time, in order to verify the superiority of the genetic algorithm and BP neural network intelligent model, the prediction results of GA-BP, PCA-BP and BP are compared with this model. The results show that principal component analysis (PCA) improves the accuracy and adaptability of the GA-BP neural network in predicting thermal and humidity comfort. The forecasting effect of the PCA-GA-BP neural network is obviously better than that of the GA-BP, PCA-BP, BP model, which can accurately predict the thermal and moisture comfort of tight-fitting sportswear. The model has better forecasting accuracy and a simpler structure.

为探究影响服装接缝强力的因素,以 6 种不同组织结构的常用服装面料为研究对象,选取 4 种缝型、3 种涤纶缝纫线和4 针/cm的 301 线迹,设计正交试验,分别测试面料的经向和纬向接缝强力.试验结果表明:面料、缝线和缝型对织物接缝强力都有影响.根据多元回归分析,面料自身性能中的经纬向断裂强力显著影响织物的接缝强力,除此之外面料的纬密、厚度也对接缝强力有影响;缝型和缝线强力显著影响织物接缝强力,面料用缝型 T4 缝线 L3 缝合的试样的经纬向接缝强力都大于缝型T1 缝线 L1 缝合的试样.