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Analyzing green view index and green view index best path using Google street view and deep learning
Zhang Jiahao,Hu Anqi 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5
As an important part of urban landscape research, analyzing and studying street-level greenery can increase the understanding of a city’s greenery, contributing to better urban living environment planning and design. Planning the best path of urban greenery is a means to effectively maximize the use of urban greenery, which plays a positive role in the physical and mental health of urban residents and the path planning of visitors. In this paper, we used Google street view to obtain street view images of Osaka City. The semantic segmentation model is adopted to segment the street view images and analyze the green view index (GVI) of Osaka City. Based on the GVI, we take advantage of the adjacency matrix and Floyd–Warshall algorithm to calculate GVI best path, solving the limitations of ArcGIS software. Our analysis not only allows the calculation of specific routes for the GVI best paths but also realizes the visualization and integration of neighborhood urban greenery. By summarizing all the data, we can conduct an intuitive feeling and objective analysis of the street-level greenery in the research area. Based on this, such as urban residents and visitors can maximize the available natural resources for a better life. The dataset and code are available at https://github.com/Jackieam/GVI-Best-Path.
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Gaole Zhang,Wenjun Zhang,Jiahao Li,Xinnan Zhou,Wang Liu,Jianbing Qi 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.5
Anchor joint is conducive to improving the automation level of the shield tunneling method, whose mechanical behavior is still not fully clear due to the complicated interaction among various structural components. In this paper, a refined FEM model is established and adopted to investigate the anchor joints' assembly and tensile performance. The operation principles of the anchor joint are first introduced for better understanding. Then, a detailed description is presented for the developed refined FEM, including the material properties, structural features, and verification. After that, 76 working conditions in total are set, and an in-depth study is conducted to examine the influence of surface roughness, gap sizes, and strength grades on the assembly and tensile behavior of anchor joints both quantitatively and qualitatively. The results show that the surface roughness mainly influences the maximum assembly load and tensile capacity of anchor joints. The gap size obviously impacts both quantitative and qualitative assembly characteristics and tensile behavior for anchor joints, whose effect is more significant than the surface roughness. The strength grade has a different influence on the distinct mechanical behavior of anchor joints. There is a positive correlation between anchor joints' assembly and tensile behavior. To satisfy the requirement of enough tensile capacity and reasonable assembly difficulty, a good solution should be to reach an appropriate balance between the assembly and tensile behavior of anchor joints.
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Yuanxiu Lin,Jiahao Zhang,Lintai Wu,Yunting Zhang,Qing Chen,Mengyao Li,Yong Zhang,Ya Luo,Yan Wang,Xiaorong Wang,Haoru Tang 한국유전학회 2021 Genes & Genomics Vol.43 No.6
Background GDP-D-mannose pyrophosphorylase (GMP) is one of the key enzymes determining ascorbic acid (AsA) biosynthesis. However, little information about GMP genes is currently available for the Rosaceae species, especially in the AsA-riched cultivated octoploid strawberry (Fragaria × ananassa). Objective To identify the all the GMP genes in Rosaceae, as well as the predominant homologues and the role of GMP genes in strawberry AsA accumulation. Methods In the present study, we performed genome-wide identifcation and comprehensive analysis of the duplicated GMP genes in strawberry and other Rosaceae species by bioinformatics methods, the expression of the GMP genes from cultivated strawberry (Fragaria × ananassa, FaGMP) was specifcally analyzed by qPCR. Finally, the FaGMP4 was transiently overexpressed in strawberry to estimate the role of GMP in regulating AsA accumulation in strawberry. Results As results, a total of 28 GMP genes were identifed in the fve Rosaceae species. The origins of duplication events analysis suggested that most GMP duplications in Rosaceae species were generated from whole genome duplication (WGD). The Ka/Ks ratio suggested that FaGMP genes underwent a stabilization selection. qPCR based expression analysis showed diferent patterns of FaGMP paralogs during fruit ripening, while FaGMP4 expressed higher in the variety containing higher AsA. Overexpression of FaGMP4 in strawberry signifcantly enhanced AsA accumulation. Furthermore, the expression of FaGMP4 under the treatment of blue and red light was largely increased in leaves while signifcantly inhibited in fruit. These results revealed the vital role of FaGMP4 in regulating AsA in strawberry.
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Du Jiahao,Huang Xiaoci,Xing Mengyang,Zhang Tao 한국자동차공학회 2023 International journal of automotive technology Vol.24 No.3
LiDAR point cloud semantic segmentation algorithm is crucial to the environmental understanding of unmanned vehicles. At this stage, in autonomous vehicles, effectively integrating the complementary information of LiDAR and camera has become the focus of research. In this work, a network framework (called PI-Seg) for LiDAR point clouds semantic segmentation by fusing appearance features of RGB images is proposed. In this paper, the perspective projection module is introduced to align and synchronize point clouds with images to reduce appearance information loss. And an efficient and concise dual-flow feature extraction network is designed, a fusion module based on a continuous convolution structure is used for feature fusion, which effectively reduces the amount of parameters and runtime performance, and more suitable for autonomous driving scenarios. Finally, the fused features are added to the LiDAR point cloud features as the final output features, and the point cloud category label prediction is realized through the MLP network. The experimental results demonstrate that PI-Seg has a 5.3% higher mIoU score than SalsaNext, which is also a projection-based method, and still has a 1.4% performance improvement compared with the latest Cylinder3D algorithm, and in quantitative analyses the mAP value also has the best performance, showing that PI-Seg is better than other existing methods.
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Sequential Modeling of Paper Drying Process to Reduce Thermal Energy Use, Part 2: Simulation Results
Kong Lingbo,Jiahao Li,Ziliang Zhang 한국펄프·종이공학회 2022 펄프.종이기술 Vol.54 No.5
Paper drying is one of the unit operations that consumes the most amount of thermal energy in a papermaking machine. In this paper, a theoretical model for paper drying process was developed using the sequential modeling method based on the conservation laws of mass and energy. Aimed at simulating thermal energy flow, the overall framework of the drying model was constructed according to the specific drying process of a newsprint machine. It was composed of eight basic modules based on their different functions in the paper drying process, i.e., cylinder group module, steam separation module, surface condensation module, fan module, heat recovery module, air heating module, paper sheet module, and hood module. The results showed that it could be used to simulate the material and energy flow of each module, as well as the whole drying process in a more comprehensive manner with integrated thermal energy use and drying performance information. In addition, the effects of operating parameters, such as supply air temperature and exhaust air humidity, on thermal energy use in the newsprint drying process were also simulated. This work also demonstrates that the sequential modeling method is instructive to reduce thermal energy use for the industrial paper drying process.
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Neo-Chinese Style Furniture Design Based on Semantic Analysis and Connection
Jialei Ye,Jiahao Zhang,Liqian Gao,Yang Zhou,Zi Yang Liu,Jianguo Han 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.8
Lately, neo-Chinese style furniture has been frequently noticed by product design professionals for the big part it played in promoting traditional Chinese culture. This article is an attempt to use big data semantic analysis method to provide effective design research method for neo-Chinese furniture design. By using big data mining program TEXTOM for big data collection and analysis, the data obtained from typical websites in a set time period will be sorted and analyzed. On the basis of "neo-Chinese furniture" samples, key data will be compared, classification analysis of overall data, and horizontal analysis of typical data will be performed by the methods of word frequency analysis, connection centrality analysis, and TF-IDF analysis. And we tried to summarize according to the related views and theories of the design. The research results show that the results of data analysis are close to the relevant definitions of design. The core high-frequency vocabulary obtained under data analysis, such as popular, furniture, modern, etc., can provide a reasonable and effective focus of attention for the designs. The result obtained through the systematic sorting and summary of the data can be a reliable guidance in the direction of our design. This research attempted to introduce related big data mining semantic analysis methods into the product design industry, to supply scientific and objective data and channels for studies on design, and to provide a case on the practical application of big data analysis in the industry.
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Hongchao Cui,Jiahao Xu,Jiajia Zhang,Jingjing Lu,Zhenkun li 한국자기학회 2023 Journal of Magnetics Vol.28 No.1
Ferrofluids as a new kind of nano-functional material, possessing both magnetism of solid material and fluidity of liquid material, thus, they have extensive scientific research and engineering application value. To avoid the defects of conventional non- or single silane coupling agent in silicone oil-based ferrofluid preparation, TEOS and KH-792 were introduced as surfactants to modify Fe3O4 magnetic nanoparticles (MNPs). Silicone oil modified by carboxylic acid was used as based liquid because of improved compatibility with surfactants. Silicone oil-based ferrofluid was prepared by high-energy ball milling method, and its rheological properties were studied. The saturated magnetization of the silicon oil based ferrofluid was 142.71 Gs. When external magnetic field was applied, the MNPs formed a chain structure in the microscope. The viscosity of ferrofluid increased with magnetic field and the shear stress rose with shear rate. The viscosity decreased steeply with increasing temperature and shear rate. The viscosity of silicone oil-based ferrofluid was 950 mPa·s at 25 °C and can vary from 2044 mPa·s at 5 °C to 465 mPa·s at 40 °C. The ferrofluid transformed from a Newtonian fluid at zero magnetic field to a shear-thinning pseudoplastic Bingham fluid when an external magnetic field was applied. The viscosity varied from 1.37 to 2.38 × 105 mPa·s at zero shear rate. While, when magnetic field varied from 0 kA/ rose to 160 kA/m, the viscosity increased obviously and this phenomenon became more pronounced as the shear rate decreased. When magnetic field intensity was higher than 64 kA/m, the viscosity increased slowly with increasing shear rates and viscosity curve was close to a straight line at 100 s-1. This study expands the idea of exploring the synthesis of ferrofluids with mixed surfactants. Silicone oil-based ferrofluid is expected to have unique application prospects in the aerospace field, especially in space damping, sealing and biomedicine.
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