Correlations between aesthetic preferences of river and landscape characters

Some landscape characters put great influences on the aesthetic preferences of a river. Finding out these characters will provide for river landscape design and management with explicit keystones. In this paper, 23 sample areas of rivers were selected in Xuzhou, China, and 15 landscape characters of rivers were identified. The photos taken at the sample areas were as stimuli, and undergraduate students were respondents. The results demonstrate that the aesthetic preferences of photos judged one-by-one and judged together receive similar results; the preference scores of deflective views are significantly higher than the ones of opposite views; for urban rivers, “river accessibility” and “number of colours” are reliably positive predictors to aesthetic preferences, “wood diversity index” and “plants on water” are negative ones; for rural rivers, “coverage of riparian vegetation”, “perspective” and “wood diversity index” are reliably positive predictors to aesthetic preferences. First published online: 14 Dec 201

Research on Collaborative Design of Performance-Refined Zero Energy Building: A Case Study

Building Information Modeling (BIM), as an auxiliary design platform, is increasingly adopted in construction projects. However, it is not widely applied in the collaborative design of zero energy buildings (ZEBs), due to the cross-discipline and complex features of ZEB projects and lack of research on the procedure and method of collaborative design in this field. This paper introduces a BIM-based collaborative design method for ZEBs. From the perspective of the technical requirements of ZEBs, the study elaborates the application of a BIM-based collaborative design method among specialists from different disciplines in passive design, renewable energy utilization and active design. The feasibility of this method is verified by the actual design and construction of the T&A House in Solar Decathlon China (SDC) competition. The research results show that the BIM-based collaborative design method can facilitate the completion of a construction project and achieve the expected goal of zero energy consumption in ZEBs

Research on Collaborative Design of Performance-Refined Zero Energy Building: A Case Study

Building Information Modeling (BIM), as an auxiliary design platform, is increasingly adopted in construction projects. However, it is not widely applied in the collaborative design of zero energy buildings (ZEBs), due to the cross-discipline and complex features of ZEB projects and lack of research on the procedure and method of collaborative design in this field. This paper introduces a BIM-based collaborative design method for ZEBs. From the perspective of the technical requirements of ZEBs, the study elaborates the application of a BIM-based collaborative design method among specialists from different disciplines in passive design, renewable energy utilization and active design. The feasibility of this method is verified by the actual design and construction of the T&A House in Solar Decathlon China (SDC) competition. The research results show that the BIM-based collaborative design method can facilitate the completion of a construction project and achieve the expected goal of zero energy consumption in ZEBs

Bridging LTLf Inference to GNN Inference for Learning LTLf Formulae

Learning linear temporal logic on finite traces (LTLf) formulae aims to learn a target formula that characterizes the high-level behavior of a system from observation traces in planning. Existing approaches to learning LTLf formulae, however, can hardly learn accurate LTLf formulae from noisy data. It is challenging to design an efficient search mechanism in the large search space in form of arbitrary LTLf formulae while alleviating the wrong search bias resulting from noisy data. In this paper, we tackle this problem by bridging LTLf inference to GNN inference. Our key theoretical contribution is showing that GNN inference can simulate LTLf inference to distinguish traces. Based on our theoretical result, we design a GNN-based approach, GLTLf, which combines GNN inference and parameter interpretation to seek the target formula in the large search space. Thanks to the non-deterministic learning process of GNNs, GLTLf is able to cope with noise. We evaluate GLTLf on various datasets with noise. Our experimental results confirm the effectiveness of GNN inference in learning LTLf formulae and show that GLTLf is superior to the state-of-the-art approaches

Horizontal Heat Impacts of a Building on Various Soil Layer Depths in Beijing City

There is a lot of research on the urban thermal environment, mainly on air temperature. However, fewer studies focus on soil temperature that is influenced by built environment, especially on the horizontal heat impacts from buildings. In this research, soil temperature was investigated at different depths in Beijing, China, to compare the differences between two locations. One was next to the building and the other was far away from the building (10 m). The locations are referred to as site A and site B, respectively. These two sites were chosen to compare the differences in soil temperatures between them to present the horizontal heat impact from facade. The results show that facades caused horizontal heat impacts on the soil at different depths in the winter, spring, and summer. Basically, facades functioned as heat sources to the soil surrounding them. The mean temperature differences between the two sites were 3.282, 4.698 and 0.316 K in the winter, spring and summer, respectively. Additionally, the thermal effects of the buildings were not only exhibited as higher soil temperatures but the temporal appearance of the maximum and minimum temperature was also influenced. Buildings functioned as heat sources to heat soil in the winter and spring and stabilized soil temperature so that it would not fluctuate too much in the summer. Additionally, the coefficient of variation indicates that buildings primarily increased the soil temperature in the winter and spring and stabilized the soil temperature in the summer