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We present a methodology for optimising designs written in high-level descriptions, combining mathematical modelbased transformations with syntax-driven pattern-matching transformations, showing how the two kinds of transformation can benefit each other. We evaluate this methodology by implementing an instance, combining a model-based transformation for data reuse with pattern-based transformations to improve its output. Results for three benchmarks show the implemented framework can improve system performance by up to 57 times.

Bicycle is widely used in Japan by people of all age groups in daily usage, which may significantly ease traffic congestion. Responding to the cyclists increasing, the method to assess the quality of bicycle travel become necessary. Previous studies reported several approaches to obtain evaluation methods. However, cycleway evaluation in Japan is still far behind the evaluation methods developed in Europe or America. This paper concentrated on familiarizing readers with two methods for evaluating the quality of bicycle facilities and then presenting some proposals of cycleway evaluation in Japan referencing to these two methods. The first method, Bicycle Compatibility Index (BCI), is used to evaluate the road environment for cycling according to the road characteristics by statistical analysis. The second method, Bicycle Level of Service (BLOS), also represents an evaluation of safety for bicyclists. Both of the above methods offered equations of comfort and safety perceptions of bicyclists according to cycling environments. By introducing these methods in combination, this paper enables the readers to maximize the comparative advantages of both BCI and BLOS. The comparison includes sensitivity of variables and the development of both methods. Then we applied BCI and BLOS to evaluate the target roadways in Kumamoto, Japan.

Previous studies have identified that environmental awareness correlates with the choice of bicycle travel. However, few studies have considered the relationships with different types of healthy behaviors and environmental behaviors. This study examined the relationships between several healthy and environmental behaviors and the choice of bicycle commute using survey data. A total of 803 residents participated in this questionnaire survey. Using factor analysis, we constructed latent factors of healthy behaviors and environmental behaviors. Using a binary logistic regression model, we examined the relationship between latent factors and cycling usage, controlling for demographic characteristics. Factor analysis revealed three latent factors of healthy behaviors: “healthy diet”, “avoiding tobacco or overdrinking”, and “physical activity”. The latent factors of environmental behaviors were as follows: “household behavior” and “purchasing behavior”. The results showed that “avoiding tobacco or overdrinking”, “physical activity” and “purchasing behavior” correlated positively with bicycle commuting. Differences were also observed in relation to demographic characteristics.