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In this paper, we propose an automatic tumor detection algorithm in MRI brain images based on significance modeling based on directional features.Firstly, the MRI brain image is preprocessed to remove the interference of the skull region in the image.Then, directional-feature-based saliency detection is used to increase the contrast of the lesion area to achieve more accurate extraction of the tumor image area.A large number of experiments have been carried out on the brain image data sets, and compared with the mainstream automatic tumor detection methods, the effectiveness of the proposed algorithm has been proved.

In this paper, control variable comparative test was employed to study the effect of the vertical greening of the envelope structure on the indoor thermal environment of Zhengzhou city. Two rooms with exactly the same structure except for the vertical greening were used as the experimental group and the reference group. The experimental results found that when vertical greening was adopted, the average temperature of the outer surface of the wall was decreased by 7.6 °C and 0.4 °C during the day and night, while the average indoor air temperature was decreased by 1.8 °C and 0.1 °C respectively. Therefore, we also found out that the average indoor air relative humidity of green vertical room was increased by 3.9% and 0.2% during the day and night with respect to the reference room. It shows out that vertical greening can effectively alleviate overheating, stabilize indoor environmental humidity, and improve the indoor thermal environment significantly.