Defect Detection Using Unanimous Vote Among Mahalanobis Classifiers for Each Color Component

In manufacturing industries, product inspection is automated and the use of image data is increasingly being employed for defect detection. A manufacturing company in Japan produces an item and inspects the produced products using image data. Reducing the error rate is important in product inspection because poor inspection of products might lead to the delivery of defective products to consumers (consumer’s risk) and strict inspection increases production cost (producer’s risk). To reduce the error rate, we highlighted fault points using a two-dimensional moving range filter and discriminated defect production through a unanimous vote among Mahalanobis classifiers for each color component. For results, we achieved a lower error rate than the current system. This research is an empirical study of how to use image data in defect detection.     

Residents’ attitudes toward future tourism development in terms of community well-being and attachment

This study explores residents’ attitudes toward future tourism development based on their community well-being (CWB) and community attachment. Focusing on the case of Gamcheon Culture Village in Busan, South Korea, which was developed during an urban regeneration project in 2009, an exploratory factor analysis was conducted. The main findings of this study are: (1) CWB is supported by five variables including income effects, social participation, safety service, infrastructure service, and environmental effect; (2) not only does CWB influence community attachment but attachment also effects residents’ attitudes; and (3) the most effective variable of CWB is income effect, and safety service for community attachment. These results can help to provide effective strategies to encourage residents to have positive attitudes about further tourism development in a community-based tourism destination.     

Broadband Demand Analysis for Network Building

An increase of broadband demand is forecasted by transitional methods that consider the effect of this increase through many factors, such as customer requirement diversification, and new service introduction and deployment under competition. Broadband demand forecasting has become important for closing the digital divide, promoting regional developments, and constructing networks economically; therefore, a demand forecast model that considers the mechanisms of market structure is necessary. In this paper, a demand analysis method for broadband access combining macro- and micro-data mining is proposed, and the service choice behaviour of customers is introduced as a customer model not only to express the macro trend of market structure, but also to consider area marketing. The proposed method can estimate the potential demand, determine the point at which broadband demand growth peaks in a specified area, and support a decision for ultra high-speed broadband access facility installation.     

Compensating Wage Differentials with Unemployment: Evidence from China

We estimate the economic value of mortality risk in China using the compensating-wage-differential method. We find a positive and statistically significant correlation between wages and occupational fatality risk. The estimated effect is largest for unskilled workers. Unemployment reduces compensation for risk, which suggests that some of the assumptions under which compensating wage differentials can be interpreted as measures of workers’ preferences for risk and income are invalid when unemployment is high. Workers may be unwilling to quit high-risk jobs when alternative employment is difficult to obtain, violating the assumption of perfect mobility, or some workers (e.g., new migrants) may be poorly informed about between-job differences in risk, violating the assumption of perfect information. These factors suggest our estimates of the value per statistical life (VSL) in China, which range from approximately US$30,000 to US$100,000, may be biased downward. Alternative estimates adjust for heterogeneity of risk within industry by assuming that risk is concentrated among low-skill workers. These estimates, which are likely to be biased downward, range from US$7,000 to US$20,000.      

Perceptions of determinants of job selection in the hospitality and tourism industry: The case of Korean university students

ABSTRACT

This study explores the key factors influencing potential employees in the hospitality and tourism industry and examines whether causal relationships between behavioral attitudes, subjective norms, and perceived behavioral control influence students' job selection. The study suggests that the career decision-making process is related to job selection. A total of 307 responses were analyzed. The results explain individual students' attitudes toward a behavior and perceived behavioral control in the context of their job selection. Attitudes toward a behavior and job selection had significant effects on career decisions. On the other hand, opinions of significant others had no significant effect. Perceived behaviors required to decide on jobs had a significant effect on job selection intentions. Students with internship experience were likely to form positive attitudes toward the hospitality and tourism industry, suggesting internships to be a useful source of a stronger relationship between the industry and job aptitudes of students in hospitality and tourism programs. The results have important implications.