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Nowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing style and color design via computer language, which aims to edit and control the garment image based on the specified target attributes while preserving other details from the original image. The current image attribute editing model often generates images containing missing or redundant attributes. To address the problem, this paper aims for a novel design method utilizing the Fashion-attribute generative adversarial network (AttGAN) model was proposed for image attribute editing specifically tailored to women’s blouses.

The proposed design method primarily focuses on optimizing the feature extraction network and loss function. To enhance the feature extraction capability of the model, an increase in the number of layers in the feature extraction network was implemented, and the structure similarity index measure (SSIM) loss function was employed to ensure the independent attributes of the original image were consistent. The characteristic-preserving virtual try-on network (CP_VTON) dataset was used for train-ing to enable the editing of sleeve length and color specifically for women’s blouse.

The experimental results demonstrate that the optimization model’s generated outputs have significantly reduced problems related to missing attributes or visual redundancy. Through a comparative analysis of the numerical changes in the SSIM and peak signal-to-noise ratio (PSNR) before and after the model refinement, it was observed that the improved SSIM increased substantially by 27.4%, and the PSNR increased by 2.8%, serving as empirical evidence of the effectiveness of incorporating the SSIM loss function.

The proposed algorithm provides a promising tool for precise image editing of women’s blouses based on the GAN. This introduces a new approach to eliminate semantic expression errors in image editing, thereby contributing to the development of AI in clothing design.

The purpose of this paper is to solve the comprehensive evaluation of the equipment maintainability level based on grey system theory, and make an analysis of the corresponding influencing factors and their prioritization process.

Considering the diversity, uncertainty and small sample size of the influencing factors of the equipment maintainability level, a multilayer evaluation attribute system is set up, and the grey relational method is utilized to assess the equipment's comprehensive maintainability. First, the bottom layer relational coefficient and weighted relational degree are analyzed, and, by means of the focus of relational degree through the bottom layer to top layer, the general evaluation of the equipment maintainability is carried out. Second, the equipment maintainability level and its influencing factors model, i.e. GM(1,N) model are set up, and the prioritization of the influencing factors is achieved through the comparison of the size of the model drive coefficients. Finally, the practical example calculation results show that this method has not only realized a sensible and effective evaluation of the equipment maintainability level, but also provided a prioritization of the influencing factors, which helps to focus attention on the major influencing factors and make this method of significant engineering application value in the improvement of the equipment maintainability level.

The modeling of electronic equipment maintainability level and analysis of its corresponding practical example prove that grey system theory could not only perform a comprehensive evaluation of the equipment maintainability level, but also provide a quantitative analysis of its various influencing factors, whereas, other methods such as fuzzy mathematics, etc. can only make a general evaluation of the equipment maintainability level.

This paper has realized an integral evaluation of the equipment maintainability level and has made an analysis of the prioritization of its various influencing factors. These investigation results could be introduced as a promising innovative idea in the evaluation of the equipments' other performances and the prioritization of its various corresponding influencing factors.

Considering the diversity and uncertainty of influencing factors of the equipment maintainability level, this paper has realized a multilayer evaluation attribute system to perform a comprehensive evaluation of equipment maintainability level by means of weighted grey relational degree model. Furthermore, the prioritization of its various influencing factors is achieved based on the GM(1,N) model.

Since the declaration of reform and market opening from China in 1990, China has drawn much attention from the world thanks to its rapid economic growth and its emergence as the world's major consumer market and the center of the global economy. Moreover, it established the new trade order, making East Asia the center of the new trade trend as it becomes a manufactural and sales stronghold of multinational companies. The Chinese distribution market is expected to show a high growth rate by 2010 and it draws attention as a new business sector which can bring huge profits. However, advancement of the Chinese distribution industry now faces systemic problems and research on such problems is insufficient. Therefore, in this study we will conduct SWOT analysis based on previous studies on the Chinese distribution industry and use it as a ground to propose strategic solutions for development.

Reports a study of 1,304 Chinese brand names of ten types of products in China. These brand names are content analyzed following a linguistic approach which the authors developed from their earlier studies. The ten types of brand names are presented in three broad categories representing the three different developing stages of the consumer product industry in China: brands of traditional products (illustrated by matches and spirits), brands of traditional products with current development (illustrated by bicycles, shoes, and toothpastes), and brands of new and modern products (illustrated by cosmetics, soft drinks, washing machines, refrigerators and TV sets). The conclusion drawn from the analysis is that one of the variables in determining how linguistic principles are being applied to Chinese brand naming is the respective stages of development of such products in the context of the Chinese market economy.