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The purpose of this paper is to overcome the shortcomings of the marked method in identifying the number of regions in binary images, and to present a new algorithm to identify the number of bars.

Identifying the number of bars automatically is widely used in the lumbering, iron, and steel industry. The marked methods need complex signing and have to scan the binary image several times. An algorithm that uses two chain lists to identify the number of bars is presented. It uses the characteristic of the chain list. When scanning the binary image, it creates two chain lists and then the number and the central position of the bar based on the relations of created chain lists can be determined.

Test results have indicated this algorithm is feasible and effective on recognizing the number of bars.

When the connected area has too many pixels in the binary images, recognizing its number needs much more time.

The paper presents a very useful approach for identifying the number of the bar, in the lumbering and steel industry.

The purpose of this paper is to examine the effects of distribution channels on demand for apparel, home textiles, and other textiles (including shoes) in urban China.

The estimation procedure used in this study is implemented in three steps: first, the price/unit value information is estimated; second, the parameters for a set of demand systems are estimated; and third, the J‐test and likelihood ratio testing are used to determine the most suitable model for the data set.

The results indicate that households spend more on apparel than home textiles and other textile products if they purchase textile products from small stores. It also indicates that they would spend more on home textiles and other textiles if they purchase from chain stores and supermarkets.

The estimation of Chinese textile consumption presents a significant challenge to both academic researchers and industry, due to China's large population, income inequality, different consumption channels, and other related issues. First, the results presented in the paper provide a clear indication for textile producers, exporters, and others to choose their distribution channels to target specific customers; second, the disaggregated textile expenditure and price elasticity estimates from this article can be used in various analytical procedures (i.e. simulation models) to evaluate the welfare effects of domestic policies and international trade policies. Quantification of the welfare impacts of domestic policies and international trade policies would be more meaningful if disaggregate textile elasticity estimates are used in simulation models.

The purpose of this paper is to examine the adverse selection in participation in the New Rural Cooperative Medical Scheme (NRCMS), as well as in outpatient and inpatient service utilization, in Chaoyang, Beijing, China.

Probit model is established to test whether the rural Hukou family member in Combined Household (CH) is statistically different from the Pure Rural Household (PRH) in enrollment in NRCMS. Seemingly Unrelated Regression (SUR) model is adopted to examine the difference in the utilization of outpatient and inpatient between the rural Hukou family members in the two kinds of households.

This paper finds that the rural Hukou family member in CH has more probability to enroll in NRCMS than the counterpart in PRH. In the period of six months, the rural Hukou family member in CH exceeds PRH by 0.73 times in outpatient visit number per capita. The former average spends yuan 157 more in outpatient service and is reimbursed yuan 53 more from NRCMS than the latter. Moreover, on average, rural Hukou family member has no difference in the inpatient service utilization between the two kinds of households in the period of 12 months.

This is the first study to empirically test the adverse selection in China's medical insurance market from the perspective of two different types of households, which are CH and PRH.

The paper aims to measure the effects of market liberalization on Chinese farmers' crop planting decisions.

The effects are measured using a censored, two‐stage, least‐square regression.

The results show that the effects of market liberalization on planting decisions are more significant in the case of crops with minimum support price (rice, wheat, and corn) than in the case of crops where planting decision is determined by market prices (cotton and soybean). The effects appear to be different across regions and time zones and more significant in 1993 than in 2005.

The result suggests that market liberalization along the past ten years achieved significant effects in Chinese farmers planting decision. This outcome should be taken into consideration when evaluating and implementing future Chinese agricultural policy income‐based interventions as a means to meet domestic food security goals and increase farmers' income level.

This paper explores the role of traditional Chinese medicine (TCM) as a tourism recovery drawcard to boost China's inbound tourism after COVID-19.

This paper employed a mixed method involving a cross-disciplinary literature review along with reflections from experts in TCM and health communication to inform tourism management. Specifically, this paper examines TCM and its potential benefits as a medical tourism drawcard to combat COVID-19. The selected literature focusses on the image and merits of TCM to frame how this medical philosophy can be used to position China as a tourist destination. Reflections on the use of TCM as a tourism marketing tool can guide promotional strategies from the Chinese government and destination managers during and after COVID-19.

The Chinese government, the tourism industry (e.g. destination managers), the media and tourists must focus on three aspects of the role of TCM: to provide medical benefits to travellers amid COVID-19 and beyond, elevate China as a destination for global medical tourists and be leveraged as a tool for economic recovery.

The paper builds a tourism recovery framework for stakeholders to adopt tailored TCM communication strategies to boost its inbound tourism programme.

This paper is the first academic paper to review TCM comprehensively and critically in relation to China tourism and post-COVID-19 recovery measures.