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.     

Households transport-home energy conservation strategies in response to energy price policies: A stated adaptation experiment based on portfolio choices and cross effects designs

This article explores consumer investment choice in long-term energy conservation technology and assesses trade-offs in energy saving behaviour between the housing and transportation domains. The long-term energy conservation choice problem is conceptualized as a portfolio choice problem. Consequently, to measure trade-offs between investments in housing and transport options, a cross effects choice design is developed in which respondents were shown one or more alternate ways to reduce their current energy consumption: (1) investing in new technology in the house, such as solar panels; (2) exchanging the current car for a more energy efficient car; (3) buying a new energy-efficient car, such as EV or solar car; (4) moving house to reduce current travel distances. To help respondents linking these options to their current energy consumption, a new Web-based survey system (SINA) to implement and administer stated adaptation experiments was developed. The system was used to collect two sets of data. First, data about out-of-home and in-home energy consumption, together with detailed time use data, was collected. Second, using a cross effects design, respondents were asked to select a portfolio of energy-saving strategies in response to different energy pricing policy scenarios. Results reported in this paper are based on 572 respondents who completed the survey and responded to seven adaptation questions based on their current energy expenditures. A random parameters logit model is estimated to predict the probability of choosing a particular portfolio of energy-saving options. Estimation results indicate that individuals from different socio-demographic groups exhibit varied preferences. The saving option characteristics, especially cost related characteristics have significant effects on individuals' preferences. Moreover, the results also showed significant effects of choice set composition on energy saving options. Further, the energy pricing policies had showed mixed effects on individual's preferences.     

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.