Deep Learning With Effective Hierarchical Attention Mechanisms in Perception of Autonomous Vehicles

Autonomous vehicles need to gather and understand information from their surroundings to drive safely. Just like how we look around and understand what\u27s happening on the road, these vehicles need to see and make sense of dynamic objects like other cars, pedestrians, and cyclists, and static objects like crosswalks, road barriers, and stop lines. In this dissertation, we aim to figure out better ways for computers to understand their surroundings in the 3D object detection task and map segmentation task. The 3D object detection task automatically spots objects in 3D (like cars or cyclists) and the map segmentation task automatically divides maps into different sections. To do this, we use attention modules to help the computer focus on important items. We create one network to find 3D objects such as cars on a highway, and one network to divide different parts of a map into different regions. Each of the networks utilizes the attention module and its hierarchical attention module to achieve comparable results with the best methods on challenging benchmarks. We name the 3D object detection network as Point Cloud Detection Network (PCDet), which utilizes LiDAR sensors to obtain the point cloud inputs with accurate depth information. To solve the problem of lacking multi-scale features and using the high-semantic features ineffectively, the proposed PCDet utilizes Hierarchical Double-branch Spatial Attention (HDSA) to capture high-level and low-level features at the same time. PCDet applies the Double-branch Spatial Attention (DSA) at the early stage and the late stage of the network, which helps to use the high-level features at the beginning of the network and obtain the multiple-scale features. However, HDSA does not consider global relational information. This limitation is solved by Hierarchical Residual Graph Convolutional Attention (HRGCA). PCDet applies the HRGCA module, which contains both graph and coordinate information, to not only effectively acquire the global information but also efficiently estimate contextual relationships of the global information in the 3D point cloud. We name the map segmentation network as Multi-View Segmentation in Bird\u27s-Eye-View (BEVSeg), which utilizes multiple cameras to obtain multi-view image inputs with plenty of colorful and textured information. The proposed BEVSeg aims to utilize high-level features effectively and solve the common overfitting problems in map segmentation tasks. Specifically, BEVSeg utilizes an Aligned BEV domain data Augmentation (ABA) module to flip, rotate, and scale the BEV feature map and repeat the same process on its ground truths to address overfitting issues. It further incorporates the hierarchical attention mechanisms, namely, HDSA and HRGCA, to effectively capture high-level and low-level features and to estimate global relationships between different regions in both the early stage and the late stage of the network, respectively. In general, the proposed HDSA is able to capture the high-level features and help utilize the high-level features effectively in both LiDAR-based 3D object detection and multiple camera-based map segmentation tasks, i.e. PCDet and BEVSeg. In addition, we proposed a new effective HRGCA to further capture global relationships between different regions to improve both 3D object detection accuracy and map segmentation performance

Study on Rural Landscape Design Method under the Background of the Population Diversification

Population diversification phenomena becomes quite common in villages located in China's developed coastal area. Based on the analysis of the traditional rural society and its landscape characteristics, and in consideration of diversified landscape requirements due to the population diversification, with dual ideas of heritage and innovation, methods for rural landscape design were explored by taking Duxuao Village in Zhejiang Province of China as an example

Will Rural Collective-Owned Commercial Construction Land Marketization Impact Local Governments’ Interest Distribution? Evidence from Mainland China

To promote the harmonious human-land relationships and increased urban-rural interaction, rural collective-owned commercial construction land (RCOCCL) marketization reform in some pilot areas was a new attempt by the Chinese Central Government in 2015. In this areas, a novel interest distribution system was established with the land right adjustment and the corresponding local governments were likely to benefit through taxation and land appreciation adjustment fund. This study proposed the hypothesis that the RCOCCL marketization reform would improve local government revenue, and explored the actual effect based on panel census data of county-level administrative units from 2010 to 2018. We applied the difference-in-difference (DID) method to analyze the causal effect of this reform on fiscal revenue with 29 pilot areas selected as the treatment group and 1602 county-level units as the control group. The empirical results of the optimized DID robustness test models and the Heckman two-step method showed that the RCOCCL marketization reform does not have a significant impact because of lower land circulation efficiency, the transfer of land transaction costs, and the policy implementation deviations. Thus, weakening the administrative intervention of local governments in the RCOCCL marketization is essential to the land market development in China

Will Rural Collective-Owned Commercial Construction Land Marketization Impact Local Governments’ Interest Distribution? Evidence from Mainland China

To promote the harmonious human-land relationships and increased urban-rural interaction, rural collective-owned commercial construction land (RCOCCL) marketization reform in some pilot areas was a new attempt by the Chinese Central Government in 2015. In this areas, a novel interest distribution system was established with the land right adjustment and the corresponding local governments were likely to benefit through taxation and land appreciation adjustment fund. This study proposed the hypothesis that the RCOCCL marketization reform would improve local government revenue, and explored the actual effect based on panel census data of county-level administrative units from 2010 to 2018. We applied the difference-in-difference (DID) method to analyze the causal effect of this reform on fiscal revenue with 29 pilot areas selected as the treatment group and 1602 county-level units as the control group. The empirical results of the optimized DID robustness test models and the Heckman two-step method showed that the RCOCCL marketization reform does not have a significant impact because of lower land circulation efficiency, the transfer of land transaction costs, and the policy implementation deviations. Thus, weakening the administrative intervention of local governments in the RCOCCL marketization is essential to the land market development in China

Correction: Lin, Y., et al. Road Extraction from Very-High-Resolution Remote Sensing Images via a Nested SE-Deeplab Model. Remote Sens. 2020, 12, 2985

The authors wish to make the following correction to this paper [...

Measurement of Polycentric County-Level Areas in a Rapid Urbanization Region from a Public Service Perspective

Despite various studies regarding polycentric development at metropolis or even larger spatial scales, there is little systematic analysis regarding the rapid urbanization area at the county-level scale. Therefore, this study explored polycentric development in 52 county-level administrative units in Zhejiang Province, China, from a public service perspective. Based on point-of-interest data, our analysis detected the intra-county urban centers and measured their polycentric characteristics. According to the number, scale, and equilibrium value of intra-county polycentricity, the 52 county-level units were classified into three types using a two-step cluster algorithm method. The empirical results suggest that polycentric characteristics vary in the rapid urbanization area, and the spatial distribution of typological units is characterized by agglomeration. Topographical condition, fixed assets investment, public transportation, and residential consumption ability are highly associated with the classification of polycentric urban areas. The conclusion of this study would help local governments initiate better urban development policies and provide potential research directions for further studies about the relationship of inter-county urban centers

Arbuscular mycorrhizal fungi improve the growth and drought tolerance of Cinnamomum migao by enhancing physio‐biochemical responses

Abstract Drought is the main limiting factor for plant growth in karst areas with a fragile ecological environment. Cinnamomum migao H.W. Li is an endemic medicinal woody plant present in the karst areas of southwestern China, and it is endangered due to poor drought tolerance. Arbuscular mycorrhizal fungi (AMF) are known to enhance the drought tolerance of plants. However, few studies have examined the contribution of AMF in improving the drought tolerance of C. migao seedlings. Therefore, we conducted a series of experiments to determine whether a single inoculation and coinoculation of AMF (Claroideoglomus lamellosum and Claroideoglomus etunicatum) enhanced the drought tolerance of C. migao. Furthermore, we compared the effects of single inoculation and coinoculation with different inoculum sizes (20, 40, 60, and 100 g; four replicates per treatment) on mycorrhizal colonization rate, plant growth, photosynthetic parameters, antioxidant enzyme activity, and malondialdehyde (MDA) and osmoregulatory substance contents. The results showed that compared with nonmycorrhizal plants, AMF colonization significantly improved plant growing status; net photosynthetic rate; superoxide dismutase, catalase, and peroxidase activities; and soluble sugar, soluble protein, and proline contents. Furthermore, AMF colonization increased relative water content and reduced MDA content in cells. These combined cumulative effects of AMF symbiosis ultimately enhanced the drought tolerance of seedlings and were closely related to the inoculum size. With an increase in inoculum size, the growth rate and drought tolerance of plants first increased and then decreased. The damage caused by drought stress could be reduced by inoculating 40–60 g of AMF, and the effect of coinoculation was significantly better than that of single inoculation at 60 g of AMF, while the effect was opposite at 40 g of AMF. Additionally, the interaction between AMF and inoculum sizes had a significant effect on drought tolerance. In conclusion, the inoculation of the AMF (Cl. lamellosum and Cl. etunicatum) improved photosynthesis, activated antioxidant enzymes, regulated cell osmotic state, and enhanced the drought tolerance of C. migao, enabling its growth in fragile ecological environments

Different Arbuscular Mycorrhizal Fungi Established by Two Inoculation Methods Improve Growth and Drought Resistance of Cinnamomum Migao Seedlings Differently

Drought stress is one of the greatest obstacles affecting field crop productivity in arid and semi-arid regions, and its severity and frequency are expected to increase due to human-induced changes to the environment and climate. Drought has led to rocky desertification in Karst regions. Cinnamomum migao is a unique, fast-growing medicinal plant of Southwest China that only thrives in Karst regions. Arbuscular mycorrhizal fungi (AMF) symbiosis alleviates drought stress in plants; however, establishment and function of the symbiotic interaction between AMF host plant in relation to the inoculation method remain unclear. Therefore, we conducted an experiment to investigate the effects of AMF species (Glomus etunicatum and Funneliformis mosseae) and two inoculation methods (seed vs. seedling inoculation) under drought stress on C. migao seedlings, and quantified mycorrhizal colonization, AMF spore density, root vigor, relative water content, C. migao growth, antioxidant enzyme activities, and osmotic adjustment. Inoculation with AMF (G. etunicatum and F. mosseae) positively affected the growth and root vigor of Cinnamomum migao under drought stress, regardless of the inoculation method. Additionally, both AMF species markedly upregulated antioxidant enzyme activities and osmotic adjustment substances, regardless of the inoculation method. Our results showed that the collective stimulatory effect of G. etunicatum is more efficient than that of F. mosseae. AMF application could promote afforestation with C. migao to prevent rocky desertification in Karst regions where water is the greatest limiting factor on plant growth and yield