Search results

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.

With the rapid low-carbon transformation in China, the industrial approach and labor structure of mining enterprises are undergoing constant changes, leading to an increasing psychological dilemma faced by coal miners. This study aims to reveal the relationship and mechanism of factors influencing the psychological dilemma of miners, and to provide optimal intervention strategies for the safety and sustainable development of employees and enterprises.

To effectively address the complex issue of the psychological dilemma faced by miners, this study identifies and constructs five-dimensional elements, comprising 20 indicators, that influence psychological dilemmas. The relational mechanism of action of factors influencing psychological dilemma was then elucidated using an integration of interpretive structural modeling and cross-impact matrix multiplication.

Industry dilemma perception is a “direct” factor with dependent attributes. The perceptions of management response and relationship dilemmas are “root” factors with driving attributes. Change adaptation dilemma perception is a “susceptibility” factor with linkage attributes. Work dilemma perception is a “blunt” factor with both dependent and autonomous attributes.

The aforementioned findings offer a critical theoretical and practical foundation for developing systematic and cascading intervention strategies to address the psychological dilemma mining enterprises face, which contributes to advancing a high-quality coal industry and efficient energy development.

The purpose of this paper is to investigate the relationship between potential affecting factors and the local communities’ willingness to pay (WTP) for housing earthquake insurance (HEI) in the context of ethnic minority communities.

A literature review was done to identify possible factors affecting WTP for HEI. Fieldwork was conducted in 2017 in Dali Minority Autonomous Prefecture, where the first Chinese HEI was launched in 2015. Interviews were done in two earthquake-prone counties, as the main ethnic minority communities in the area. A total of 536 questionnaires were collected and used as empirical data for testing the impacts mechanism.

Respondents’ risk perception, risk exposure, self-prevention behaviors, government aid, insurance experience and sociodemographic characteristics were hypothesized as theoretical indicators correlated to WTP for HEI. Empirical analysis results predict that WTP for HEI is significantly influenced by risk perception, insurance experience, government aid, and age and out-migrating labors. It is evident that higher risk perception and more insurance experience lead to stronger desire for HEI coverage. However, dependency on government aid negatively affects WTP for HEI. Moreover, WTP for HEI is negative in relation to age and out-migrating labors. Surprisingly, ethnic-culture factors were not statistically significant to WTP for HEI.

This paper is an attempt to identify and verify factors affecting WTP for HEI, bridging the gap of inadequate research on WTP for HEI in ethnic minority communities.

This article reviews and discusses issues in the translation of international brand names to Chinese, and provides a framework for international brand managers who want to expand into China. Linguistic differences between Chinese and English are wide and deep, making translation of brand names difficult. Cultural context, pronunciation, written vs. oral language, and the meaning of characters are just a few examples of such difficulties. We discuss four global product‐naming strategic alternatives available to country/brand managers, along with their usage. The four approaches include (1) dual extension, (2) brand meaning extension, (3) brand feeling extension, and (4) dual adaptation. We also provide examples of brands utilizing the different approaches.

In view of high consumption situation of raw materials in the apparel industry due to unique and diversified style, the purpose of this paper is to investigate the application of pattern transformation between clothing and tent, explore the feasibility of extending multi-functional product and provide experimental demonstration for realizing 5R (Reduce, Reevaluate, Reuse, Recycle, Rescue) design goal of garment product.

According to the results of market research, in order to make single product have the functions of both outdoor couple clothing and simple tent, the planar patterns of clothing and tent are compared and transformed to make them compatible with each other, then the removable multi-functional design and technique processing are adopted.

It was found that outdoor clothing and tent with similar application occasions and raw materials could realize the assumption of multi-functional product. Their combination has the functions of both clothing and tent by wearing and assembling.

By means of this transformation design, the diversification and enjoyment of garment styles and functions can be realized. This helps to improve the energy efficiency of raw materials and accessories by increasing the frequency of product reuse and sharing. In addition, the enjoyment design of products also helps to lead and promote ecological consumption.

Reviewing a dozen of fiscal stimulus packages in developed countries, this paper analyzes one common strategy that has found widespread support in these stimulus packages and its relevance for developing countries: investing in broadband and next‐generation networks, as a counter‐cyclical tool to create jobs and provide the foundation for economic recovery and long‐term sustained growth.

The paper looks at the various impacts broadband investment is expected to have: short‐term job creation and aggregate demand effects, and long‐term productive activities in other sectors of the economy. Moreover, broadband investment is more fiscally sound than other public spending stimulus options, in the sense of coming closer to, or in some cases actually being, self‐financing.

Several factors highlight the potential of broadband infrastructure as an important area of public investment during economic downturn, an option also open to policymakers in developing countries. Spending initiatives on next‐generation telecommunications networks at a time when labor market conditions are particularly weak can help preserve jobs and head off a potential burden on social safety nets. Bringing forward longer‐term aggregate spillover effects of broadband can improve the productivity of the entire economy and is consistent with enhancing longer‐run growth and development. Public support also “crowds in” private investment when access to private financing is decreasing and more expensive.

This is one of the few studies with a focus on the emerging broadband network, its impact on economy and the role of the public sector in rolling out next‐generation networks, during economic downturn and in general. A detailed summary of broadband initiatives in more than a dozen developed countries is provided in the paper.

Drawing on the literature of chief technology officer (CTO) and trusting relationship theory, the purpose of this paper is to investigate the impact of trusting relationship of CTO‐chief executive officer (CEO) on the CTO's participation in technology strategy, based on empirical study of Chinese high‐tech firms, in order to maximize CTO's strategic decision‐making role. Taking into account the weight of power in Chinese culture, this study takes CTO's power distribution as moderator, to study whether it strengthens the impact of trusting relationship of CTO‐CEO on CTO's participation in technology strategy.

CTOs of high‐tech firms from Shanghai, Jiangsu, Shenzhen, Zhejiang and Beijing are taken as samples. A questionnaire survey is conducted by using random sampling method.

The results show that trusting relationships of CTO‐CEO has a significant positive impact on CTO's participation in technology strategy. The two dimensions of trusting relationships of CTO‐CEO, cognitive trust and emotional trust also have a significant positive impact on CTO's participation in technology strategy and each dimension of CTO's power distribution has a significant moderating effect on partial paths.

The results are analyzed from both the data level and theoretical level. Conclusions on the management inspiration of CEO and CTO in high‐tech firms are drawn.

Survival (default) data are frequently encountered in financial (especially credit risk), medical, educational, and other fields, where the “default” can be interpreted as the failure to fulfill debt payments of a specific company or the death of a patient in a medical study or the inability to pass some educational tests.

This paper introduces the basic ideas of Cox's original proportional model for the hazard rates and extends the model within a general framework of statistical data mining procedures. By employing regularization, basis expansion, boosting, bagging, Markov chain Monte Carlo (MCMC) and many other tools, we effectively calibrate a large and flexible class of proportional hazard models.

The proposed methods have important applications in the setting of credit risk. For example, the model for the default correlation through regularization can be used to price credit basket products, and the frailty factor models can explain the contagion effects in the defaults of multiple firms in the credit market.

Genetic algorithms have been extensively used in different domains as a type of robust optimization method. They have a much better chance of achieving global optima than conventional gradient‐based methods which usually converge to local sub‐optima. However, convergence speeds of genetic algorithms are often not good enough at their current stage. For this reason, improving the existing algorithms becomes a very important aspect of accelerating the development of the algorithms. Three improved strategies for genetic algorithms are proposed based on Holland’s simple genetic algorithm (SGA). The three resultant improved models are studied empirically and compared, in feasibility and performance evaluation, with a set of artificial test functions which are usually used as performance benchmarks for genetic algorithms. The simulation results demonstrate that the three proposed strategies can significantly improve the SGA.

In China, more than 80,000 people have been diagnosed with COVID-19, and more than 3,000 people have lost their lives. It seems that there will be more deaths since the epidemic is not over. All the Chinese provinces have reported the COVID-19 cases. This chapter aims to explore the trend of COVID-19 treatment efficiency in Chinese provinces using the data released daily by China Center for Disease Control and Prevention. Since China Center for Disease Control and Prevention began to release data daily from January 24 to March 12, we have more than 40 groups of daily data for 31 provinces in China mainland. In the calculation, we take the daily data of each province as a sample and then we have more than 1,200 samples in this study.

We use additive two-stage data envelopment analysis as an efficiency evaluation tool to calculate the COVID-19 treatment efficiency. In our framework, the first stage is to understand the infection rate and the second stage is to evaluate the treatment efficiency. In the first stage for the tth day, we use total population (p) and number of people infected in the previous day (inf _t−1) as the inputs and cumulative number of people infected in the current day (inf _t ) as the output. In the second stage for the tth day, we use cumulative number of people infected in the current day (inf _t ) as the input and cumulative death in the current day (death _t ) and cumulative recovery in the current day (recov _t ) as the outputs. Some techniques on how to deal with undesirable outputs such as inf _t and death _t are employed in this study.

After we have the infection rate and treatment efficiency for the samples more than 1,200, we analyze the COVID-19 treatment efficiency and its development trend from January 24 to March 12 in 34 regions of China from static and dynamic aspects. The results show that, on the whole, the overall efficiency and phased efficiency of COVID-19 treatment efficiency in all regions of China are relatively high, which reflects the key factor for the Chinese government to quickly control the epidemic in the short term. Relatively speaking, the average efficiency value in the infection stage (first stage) is lower than the average efficiency value in the healing stage (second stage), which shows that the focus of anti-epidemic in China should be early detection and prevention rather than treatment process. In terms of trend, the total efficiency of COVID-19 treatment in each region shows a trend of “increasing first and then decreasing.” Our analysis indicates that in the initial stage, the continuous increase of various resources leads to the rise of the total efficiency, while in the later stage, the rapid decline of the number of infected people leads to the decrease of the total efficiency. Based on the results of the efficiency analysis, this study provides corresponding management implications and policy suggestions, hoping to provide some enlightenment and suggestions for the anti-epidemic work of other countries in the severe environment where the epidemic is spreading rapidly.