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SSRN 2023年

作者： Lin, Yunhong Chang, Ruicheng Yao, Zhengyu Chen, Zhong He, Hongming Guangzhou Metro Design and Research Institute Co. Ltd Guangdong Guangzhou China Faculty of Land Resources Engineering Kunming University of Science and Technology Kunming630093 China School of Geographic Sciences East China Normal University Shanghai200241 China Key Laboratory of Geographic Information Science Ministry of Education East China Normal University Shanghai200241 China Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural Resources Shanghai200241 China

The resolution of engineering risks and problems during the shield machine launching process has become a crucial research topic in the industry. To address this issue, we conducted a study on a newly launching hood system for unconsolidated soil conditions. Based on the concept of active pressurization and using a new sealing device, we applied an active pressurized sealing system throughout the construction process from the shield breakthrough door to the ring beam of the door. The research results demonstrated that the newly launching hood system is suitable for various unconsolidated soil layers and shield machine sizes, with three models of 20m, 40m, and above 40m water pressure. By using the technology of pressurizing the soil before turning the cutterhead to grind the surrounding structure, a good sealing effect was achieved. Moreover, station end settlement data showed that the use of the newly launching hood system does not have a negative impact on the surrounding environment during construction. The launching hood system for tunnel shield provides an excellent solution for the risks faced in shield machine operations. © 2023, The Authors. All rights reserved.

关键词： Grinding (machining)

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Maize Crop Row Recognition Algorithm Based on Improved Unet Network

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SSRN 2022年

作者： Diao, Zhihua Guo, Peiliang Zhang, Baohua Zhang, Dongyan Yan, Jiaonan He, Zhendong Zhao, Suna Zhao, Chunjiang School of Electrical Information Engineering Zhengzhou University of Light Industry Zhengzhou450002 China College of Artificial Intelligence Nanjing Agricultural University Nanjing211800 China National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei230601 China Information Technology Research Center Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China

The accurate identification of the centerlines of crop rows represents the core principle of agricultural robot visual navigation technology. However, few existing deep-learning-based maize crop row centerline recognition algorithms generally have limitations such as poor robustness and weak adaptability. To mitigate these issues, this study proposes a centerline detection algorithm based on a convolutional neural network. The U-shaped Network (UNet) – a traditional semantic segmentation network – was enhanced to create the Atrous Spatial Pyramid Pooling UNet (ASPP-UNet) network for maize crop row and background segmentation, and the improved vertical projection method was subsequently employed to measure the crop rows’ feature points. Finally, the least squares method was used to fit the centerlines. Experimental results yielded the Mean Intersection Over Union (MIoU), Mean Pixel Accuracy (MPA), Mean Precision (MP), and Mean Recall (MR) metrics of ASPP-UNet network to be 83.23%, 90.18%, 91.79%, and 90.18% respectively. These figures represent respective increases of 10.03%, 11.86%, 9.43% and 11.24% compared to the Fully Convolutional Network (FCN), and 7.80%, 5.52%, 2.71%, and 5.52% compared to the UNet. Furthermore, the average fitting time and angle error of the improved vertical projection method were reduced to 65 ms and 4.57°, compared to 80 ms and 6.12°in the traditional vertical projection method, and 86 ms and 5.67°in the left and right edge centerline method. Likewise, the accuracy of proposed method increased to 91.79%, compared to 87.21% and 90.16% of the two aforementioned methods, respectively. Therefore, the proposed method successfully meets the accuracy and real-time demands of agricultural robot vision navigation, and can function effectively under varying environmental pressures. © 2022, The Authors. All rights reserved.

关键词： Agricultural robots

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A novel deep learning–based framework for five-day regional weather forecasting

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Atmospheric and Oceanic Science Letters 2025年

作者： Congqi Cao Ze Sun Lanshu Hu Liujie Pan Yanning Zhang National Engineering Laboratory for Integrated Aero–Space–Ground–Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an China Shaanxi Provincial Meteorological Observatory Xi’an China

Deep learning–based methods have become alternatives to traditional numerical weather prediction systems, offering faster computation and the ability to utilize large historical datasets. However, the application of deep learning to medium-range regional weather forecasting with limited data remains a significant challenge. In this work, we propose three key solutions: (1) motivated by the need to improve model performance in data-scarce regional forecasting scenarios, we innovatively apply semantic segmentation models, to better capture spatiotemporal features and improve prediction accuracy; (2) recognizing the challenge of overfitting and the inability of traditional noise-based data augmentation methods to effectively enhance model robustness, we introduce a novel learnable Gaussian noise mechanism that allows the model to adaptively optimize perturbations for different locations, ensuring more effective learning; and (3) to address the issue of error accumulation in autoregressive prediction, as well as the challenge of learning difficulty and the lack of intermediate data utilization in one-shot prediction, we propose a cascade prediction approach that effectively resolves these problems while significantly improving model forecasting performance. Our method achieves a competitive result in The East China Regional AI Medium Range Weather Forecasting Competition . Ablation experiments further validate the effectiveness of each component, highlighting their contributions to enhancing prediction performance. 深度学习逐渐替代传统数值天气预报 (NWP) 系统, 但在数据有限的中期天气预报中仍面临挑战.为此, 本文提出三项创新:首先, 引入语义分割模型增强时空特征捕捉能力, 提高预测精度;其次, 设计可学习的高斯噪声机制, 解决过拟合问题并突破传统噪声增强的局限性;最后, 提出级联预测方法, 平衡预测精度与误差控制, 缓解自回归预测的误差累积问题.该方法在华东区域AI中期气象预报竞赛中表现优异, 实验验证了各模块的有效性, 其中语义分割降低温度预测误差9.3%, 噪声机制提升降水预测F1-score 6.8%, 级联策略减少风速预测均方误差12.5%.此研究为数据受限的区域气象预报提供了新路径.

关键词： Weather forecasting Deep learning Semantic segmentation models Learnable Gaussian noise Cascade prediction 天气预报深度学习语义分割模型可学习高斯噪声级联预测

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Example-based web page recoloring method

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Frontiers of Computer Science 2020年第5期14卷 229-231页

作者： Yonghao Long Zhihao Zang Xiangping Chen Fan Zhou Xiaonan Luo School of Data and Computer Science National Engineering Research Center of Digital LifeSun Yat-sen UniversityGuangzhou510006China Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion The School of Communication and DesignSun Yat-sen UniversityGuangzhou510006China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China

1 Introduction The user interface(UI)is very important for a software product,and a well-designed UI will attract users and make a good *** has been shown that color plays an important role in invoking emotional reactions[1],influencing usability[2],forming first impressions[3],and affecting the energy cost of the UI[4].Generating satisfying color schemes has high requirements for experience,aesthetic,and creative inspiration of designers[5].

关键词： web coloring satisfying

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Research on trans-region integrated traffic emergency dispatching technology based on multi-agent

Research on trans-region integrated traffic emergency dispat...

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作者： Yang, Tingyu Peng, Xiaoqian Chen, Dingjun Yang, Feiyu Muneeb Abid, Malik School of Transportation and Logistics Southwest Jiaotong University Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest JiaoTong University Chengdu China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest Jiaotong University Chengdu China Department of Civil Engineering College of Engineering and Technology University of Sargodha Sargodha Pakistan

With the increasingly close links between provinces and municipalities, the complexity and social connectivity of emergencies have gradually increased. How to realize the rapid and scientific dispatch of emergency resources based on the comprehensive transportation network has become a realistic need. However, due to barriers in management and communication between different administrative regions and different modes of transportation, emergency resource scheduling can only be carried out in the region, and the utilization of integrated traffic channels is insufficient to form a good multimodal transport system. The multi-agent system has strong self-organization ability, learning ability and reasoning ability, which solves problems in the fields of dynamic decision-making and micro-simulation and provides ideas for solving the problem of comprehensive traffic emergency dispatching across regions. In this paper, the multi-agent system is introduced into the research of the task assignment problem of trans-regional comprehensive traffic emergency materials dispatching, based on the traditional bidding rules, the emergency dispatch task assignment rules are proposed and multi-agent trans-regional comprehensive traffic emergency dispatching model based on improved bidding rules is established. The simulation results show that the proposed method can break the regional barrier and form a multimodal transport scheme for emergency materials from the reserve point to the demand point under the minimum generalized time cost, providing decision support for emergency dispatch. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Multi agent systems

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An Adaptive Irregular Convolution U-Net for Reconstructing Ancient Channel of the Yellow River

An Adaptive Irregular Convolution U-Net for Reconstructing A...

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IEEE SENSORS

作者： Zhishun Guo Jianhui Zhao Ning Li Lin Wu College of Computer and Information Engineering Henan University Kaifeng China Henan. Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng China

The lower reaches of the ancient Yellow River (AYR) migrated very frequently, like a loong swinging its tail on the land of China. This paper, based on Gaofen-3 full-polarization synthetic aperture radar (SAR) data, analyzed scattering characteristics of archaeolandscapes, which provided reliable evidences for the existence of AYR between Lankao and Sui County. Then, an adaptive irregular convolution kernel U-Net (AICK-U-Net) was proposed to reconstruct the part of channel of AYR, based on the image obtained by polarization decomposition, and the precision reached 96.21%. In summary, polarization decomposition and neural network in spaceborne SAR field, provided new insights for detecting and reconstructing archaeolandscapes.

关键词： Convolution Spaceborne radar Neural networks Scattering Sensors Rivers Reliability

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Bicycle Crossing Design and Signal Control Optimization for the Symmetric Intersection

Bicycle Crossing Design and Signal Control Optimization for ...

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International Conference on Transportation Information and Safety (ICTIS)

作者： Yexin Lin Yugang Liu Liying Tang Shuai Zheng Bin Chen Hongtai Yang School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu China Institute of Transportation Development Strategy &#x0026 Planning of Sichuan Province Chengdu China

ISBN: (纸本)9781665497145

The symmetric intersection (SI) is a type of unconventional intersection that could increase capacity of the intersection. Although this type of intersection is promising, the bicycle crossing method has not been designed for SI, which prevents it from implementation. In this study, we propose three bicycle crossing designs for the purpose of eliminating the conflict between bicycles and vehicles, and optimize the corresponding signal timing. The first is to reverse the bicycle lane on the right-hand-traffic arterial, so that left-turning bicycles can pass at any time, which can reduce the flow of bicycles through the conflicting area of the intersection. The second is to use an advanced stop line, which moves the stop line backwards and sets up a bicycle waiting area in the front to reduce the conflict between bicycles and vehicles. The third is to set up an exclusive phase for bicycles to separate vehicles and bicycles. A linear programming model that maximizes the capacity of the intersection for vehicles considering constraints such as signal phase and cycle duration is established to calculate the signal timing. A case study is performed to determine the optimal signal timing of each condition. The results show that the scheme of advanced stop lines could reduce delays and increase capacity of the intersection for bicycles, but the capacity for vehicles is reduced, and thus should be used when the traffic demand of motor vehicles is not high. In the condition of high-throughput vehicles, the exclusive phase for bicycles perform better.

关键词： Transportation Bicycles Programming Linear programming Safety Delays Optimization

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Water footprint evaluation of the production of float flat glass 21st

Water footprint evaluation of the production of float flat g...

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21st Chinese Materials Conference, CMC 2020

作者： Wu, Yiling Gong, Xianzheng Liu, Yu Li, Xiaoqing Tian, Xiaofei Wang, Hongtao Ye, Changxing College of Materials Science and Engineering Beijing University of Technology No. 100 Ping Le Yuan Chaoyang District Beijing100124 China National Engineering Laboratory for Industrial Big-data Application Technology No. 100 Ping Le Yuan Chaoyang District Beijing100124 China China Quality Certification Center Section 9 No.188 the south fourth Ring West Road Beijing100070 China Ningbo CNECO Environmental Technology Co. Ltd. Ningbo China

ISBN: (纸本)9783035717389

The ISO14046 water footprint evaluation method was used in this study to calculate the water shortage footprint and water degradation footprint in plate glass production, in order to improve the water efficiency and management level in the production process of plate glass in China. A certain enterprise in Hebei province was selected for investigation in 2018. The results show that the water shortage footprint generated by the production of flat glass was 0.435 m3 H2Oeq/weight box. The proportion at raw material production stage was the largest, being 86%, so the water consumption control in raw material mining and the circulating water system should be strengthened and improved to reduce the fresh water consumption. Water degradation footprint in flat glass industry mainly consisted of eutrophication and acidification footprints. The eutrophication footprint was calculated as 0.027 kgNO3-eq/weight box, and water acidification footprint was 0.271 kgSO2eq/weight box. The largest proportion occurred at flat glass production stage. It should be paid attention at this stage, to update the relatively clean production equipments and add the waste gas processing steps to reduce pollution discharge. © 2021 Trans Tech Publications Ltd, Switzerland.

关键词： Eutrophication

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Pansharpening via Frequency-Aware Fusion Network with Explicit Similarity Constraints

arXiv

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arXiv 2022年

作者： Xing, Yinghui Zhang, Yan He, Houjun Zhang, Xiuwei Zhang, Yanning National Engineering Laboratory for Integrated Aerospace-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an710072 China Research Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518057 China Information Center of Yellow River Conservancy Commission Henan Zhengzhou China

The process of fusing a high spatial resolution (HR) panchromatic (PAN) image and a low spatial resolution (LR) multispectral (MS) image to obtain an HRMS image is known as pansharpening. With the development of convolutional neural networks, the performance of pansharpening methods has been improved, however, the blurry effects and the spectral distortion still exist in their fusion results due to the insufficiency in details learning and the frequency mismatch between MS and PAN. Therefore, the improvement of spatial details at the premise of reducing spectral distortion is still a challenge. In this paper, we propose a frequency-aware fusion network (FAFNet) together with a novel high-frequency feature similarity loss to address above mentioned problems. FAFNet is mainly composed of two kinds of blocks, where the frequency aware blocks aim to extract features in the frequency domain with the help of discrete wavelet transform (DWT) layers, and the frequency fusion blocks reconstruct and transform the features from frequency domain to spatial domain with the assistance of inverse DWT (IDWT) layers. Finally, the fusion results are obtained through a convolutional block. In order to learn the correspondence, we also propose a high-frequency feature similarity loss to constrain the HF features derived from PAN and MS branches, so that HF features of PAN can reasonably be used to supplement that of MS. Experimental results on three datasets at both reduced- and full-resolution demonstrate the superiority of the proposed method compared with several state-of-the-art pansharpening models. The codes are available at https://***/YinghuiXing/FAFNet. Copyright © 2022, The Authors. All rights reserved.

关键词： Remote sensing

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Low-Temperature Growing Anatase TiO2/SnO2 Multi-dimensional Heterojunctions at MXene Conductive Network for High-Efficient Perovskite Solar Cells

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Nano-Micro Letters 2020年第3期12卷 199-217页

作者： Linsheng Huang Xiaowen Zhou Rui Xue Pengfei Xu Siliang Wang Chao Xu Wei Zeng Yi Xiong Hongqian Sang Dong Liang National Engineering Research Center for Agro‑Ecological Big Data Analysis and Application School of Electronics and Information EngineeringAnhui UniversityNo.111 Jiulong RoadHefei 230601People’s Republic of China Science and Technology Institute Hubei Key Laboratory of Biomass Fibers and Eco‑Dyeing and FinishingWuhan Textile UniversityWuhan 430073People’s Republic of China School of Physics and Technology MOE Key Laboratory of Artificial Micro‑and Nano‑Structures and Center for Electron MicroscopyWuhan UniversityWuhan 430072People’s Republic of China Department of Physics King’s College LondonThe StrandLondon WC2R 2LSUK

A multi-dimensional conductive heterojunction structure,composited by TiO2,SnO2,and Ti3C2TX MXene,is facilely designed and applied as electron transport layer in efficient and stable planar perovskite solar *** on an oxygen vacancy scramble effect,the zero-dimensional anatase TiO2 quantum dots,surrounding on two-dimensional conductive Ti3C2TX sheets,are in situ rooted on three-dimensional SnO2 nanoparticles,constructing nanoscale TiO2/SnO2 *** fabrication is implemented in a controlled lowtemperature anneal method in air and then in N2 *** the optimal MXene content,the optical property,the crystallinity of perovskite layer,and internal interfaces are all facilitated,contributing more amount of carrier with effective and rapid transferring in *** champion power conversion efficiency of resultant perovskite solar cells achieves 19.14%,yet that of counterpart is just 16.83%.In addition,it can also maintain almost 85%of its initial performance for more than 45 days in 30–40%humidity air;comparatively,the counterpart declines to just below 75%of its initial performance.

关键词： In situ fabrication Multi-dimensional heterojunction Oxygen vacancy scramble effect Electron transport layer Perovskite solar cells

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