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2021 5th International Conference on Green Composite Materials and Nanotechnology, GCMN 2021

作者： Sun, Qinyue Fu, Jizhu Zhang, Heng Yang, Huihui Wang, Yumin Xiong, Yi Zeng, Wei Wang, Faniu Xu, Chao National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information Engineering Anhui University Anhui Hefei230601 China Science and Technology Institute Key Laboratory of Textile Fiber and Products Ministry of Education Laboratory for Electron Microscopy Wuhan Textile University Hubei Wuhan430073 China School of Physics and Technology Moe Key Laboratory of Artificial Micro- and Nano-Structures and Center for Electron Microscopy Wuhan University Hubei Wuhan430072 China

Versatile sensors have broad application prospects in human motion detection, health monitoring, wearable electronic devices and flexible electronic skin and other emerging fields. In this work, the enhanced hydrogel was prepared by freezing and thawing process with calcium ion crosslinking. This composite material shows excellent flexibility and elasticity, and after being cut in half, it can automatically heal well in a short time without external force. It shows great potential in flexible and wearable devices. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Hydrogels

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Recent developments on life cycle assessment of building materials 20th

Recent developments on life cycle assessment of building mat...

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20th Chinese Materials Conference, CMC 2019

作者： Liu, Ning Liu, Yu Gong, Xianzheng Hao, Liwei Gao, Feng Li, Xiaoqing Zheng, Yan National Engineering Laboratory for Industrial Big-data Application Technology Beijing100124 China Beijing University of Technology the Key Laboratory of Advanced Functional Materials Ministry of Education of China Beijing100124 China Beijing Building Materials Academy of Sciences Research State Key Laboratory of Solid Waste Reuse for Building Materials Beijing100041 China

ISBN: (纸本)9783035715668

In recent years, the building materials industry in China has made great progress in the R&D of energy conservation, emission reduction and cleaner production technologies, in order to implement sustainable development policy. Life cycle assessment (LCA) is one of the mainstream method to analyze the environmental impact of product during its life cycle, which plays an important role on ecological design of building materials and development of green manufacture technology in recent year. This paper reviewed the LCA studies of building materials. Firstly, the development of China's building materials industry and technical framework of LCA standardized by ISO14040/14044 were introduced. Moreover, the typical LCA case studies of cement, glass, ceramics, wall materials, insulation materials and other building materials were reviewed. At last, some prospects for future research and development in this field were put forward. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Life cycle

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Identification of winter wheat plantation based on sentinel-2 imagery

Identification of winter wheat plantation based on sentinel-...

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2019 ASABE Annual International Meeting

作者： Zhang, Dongyan Fang, Shengmei Duan, Hongrui Zhang, Huihui She, Bao Ding, Yang Yang, Yuying National Engineering Research Center for Agro-Ecological Big Data Analysis and Application Anhui University Hefei China Water Management and Systems Research Unit USDA Agricultural Research Service Fort CollinsCO United States School of Surveying and Mapping Anhui University of Science and Technology Huainan China

As an important food crop in the world, remote sensing identification of winter wheat (Triticum Aestivum L.) and extraction of planting areas are the basis of growth monitoring, disaster assessment and yield prediction. ESA Sentinel-2A/B satellite has significant advantages in crop identification with its high spatial resolution and short revisit period. In this study, northern and central Anhui, the main wheat production area in Anhui Province in China, were selected as the study area to explore the identification algorithm of winter wheat under different planting conditions. Based on the variation curve of the normalized difference vegetation index (NDVI) time series in the key phenological period of winter wheat, the specificity of its greenness was explored, and the screening rules were constructed accordingly. The spatial distribution of winter wheat in the study area was screened out by Decision Tree algorithm, and the extraction effect was improved by using a cultivated land distribution product. The extraction effect was evaluated by means of random samples, and the extraction area was tested with reference to the county-level wheat planting area data recorded in the statistical yearbook. The results showed that the estimation accuracy of winter wheat area in northern Anhui counties was 86.86%, and the Kappa coefficient was 0.80 (the Omission was 8.48%, the Commission was 9.58%). The estimation accuracy of winter wheat area in central Anhui counties was 80.00%, and the Kappa coefficient was 0.62 (the Omission was 17.30%, the Commission was 40.20%). The overall extraction effect is inferior to that of the main producing areas in northern Anhui. This study provides a valuable reference for mapping wheat production under fragmented and complicated land surface conditions, which will further contribute to decision-making by government and relevant departments. © 2019 ASABE Annual International Meeting. All rights reserved.

关键词： Extraction

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A new classification method of SAR image based on OGMRF-RC model 5

A new classification method of SAR image based on OGMRF-RC m...

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IET International Radar Conference 2020, IET IRC 2020

作者： Li, Yuan Guo, Zhishun Wu, Lin Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475000 China College of Environment and Planning Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

Synthetic Aperture Radar (SAR) image classification is a key technique and research focus in the application of remote sensing. This paper proposes a new classification method of SAR image based on Object-based Gaussian-Markov Random Field model with Region Coefficients (OGMRF-RC), the new method use Fuzzy Probability (FP) represents the region's category probability, FP is obtained by regional posterior probability and edge information of neighborhood. Use FP to replace the unique class label of the region, which avoids the parameters estimation inaccurate of the feature field caused by the unique initial class label. And the parameter calculation method of feature field takes into account the feature information of all regions in the image. In this paper, we take the area around Baliwan in Kaifeng as study area, Sentinel-1 is used as the remote sensing data sources. FCM, K-means, classic MRF and OGMRF-RC are used as contrast methods, the experimental result demonstrates the accuracy of our method is better than these methods. © 2020 Institution of engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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Differentiable Feature Aggregation Search for Knowledge Distillation

arXiv

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arXiv 2020年

作者： Guan, Yushuo Zhao, Pengyu Wang, Bingxuan Zhang, Yuanxing Yao, Cong Bian, Kaigui Tang, Jian Peking University China Technology Inc National Engineering Laboratory for Big Data Analysis and Applications DiDi AI Labs

Knowledge distillation has become increasingly important in model compression. It boosts the performance of a miniaturized student network with the supervision of the output distribution and feature maps from a sophisticated teacher network. Some recent works introduce multi-teacher distillation to provide more supervision to the student network. However, the effectiveness of multi-teacher distillation methods are accompanied by costly computation resources. To tackle with both the efficiency and the effectiveness of knowledge distillation, we introduce the feature aggregation to imitate the multi-teacher distillation in the single-teacher distillation framework by extracting informative supervision from multiple teacher feature maps. Specifically, we introduce DFA, a two-stage Differentiable Feature Aggregation search method that motivated by DARTS in neural architecture search, to efficiently find the aggregations. In the first stage, DFA formulates the searching problem as a bi-level optimization and leverages a novel bridge loss, which consists of a student-to-teacher path and a teacher-to-student path, to find appropriate feature aggregations. The two paths act as two players against each other, trying to optimize the unified architecture parameters to the opposite directions while guaranteeing both expressivity and learnability of the feature aggregation simultaneously. In the second stage, DFA performs knowledge distillation with the derived feature aggregation. Experimental results show that DFA outperforms existing distillation methods on CIFAR-100 and CINIC-10 datasets under various teacher-student settings, verifying the effectiveness and robustness of the design. Copyright © 2020, The Authors. All rights reserved.

关键词： Distillation

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A review on water footprint research of materials industry 20th

A review on water footprint research of materials industry

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20th Chinese Materials Conference, CMC 2019

作者： Chen, Hualong Liu, Yu Gong, Xianzheng Hao, Liwei Sun, Boxue Li, Xiaoqing National Engineering Laboratory for Industrial Big-data Application Technology Beijing100124 China Beijing University of Technology the Key Laboratory of Advanced Functional Materials Ministry of Education of China Beijing100124 China Beijing Building Materials Academy of Sciences Research State Key Laboratory of Solid Waste Reuse for Building Materials Beijing100041 China

ISBN: (纸本)9783035715668

The scarcity of water resource has become one of major issues that constrain economic development and urbanization process in China. The water footprint is a comprehensive indicator used to measure water consumption and pollution that is widely used in global or regional studies. The previous practices showed that water footprint analysis was an effective tool to achieve sustainable utilization of water resources by guiding the development of water-saving technology and product. This paper reviewed the progress of water footprint research in materials industry including related theory, method and application. Firstly, the basic concept of water footprint was introduced. Secondly, the current accounting and assessment methods of water footprint and their applicable fields were summarized. Thirdly, the case studies on the water footprint of metallic materials, nonmetallic materials and chemical materials were reviewed to analyze its guidance significance on the sustainable development of water resources. At last, some suggestions for future research on the water footprint of materials were proposed. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Chemical analysis

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Relationship between Logistics Firm Size and Business Diversification: An Empirical Study of Chongqing, Area in China

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Open Journal of Statistics 2021年第1期11卷 1-18页

作者： Nannan He Wanshan Wu Sijing Liu School of Transportation and Logistics Southwest Jiaotong University Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China National United Engineering Laboratory of Integrated and Intelligent Transportation Chengdu China

This paper aims to explore the relationship between logistics firm size and business diversification, especially in micro- and small-sized enterprises, and assess the diversification process of Chongqing logistics enterprises using new data source. It is intended to contribute to theoretical research on diversification in the emerging logistics industry based on resource-based view (RBV) and factor production theory. We innovatively establish the logistics business classification system, then measure the degree and direction of diversification of logistics enterprises based on mean narrow-spectrum diversification-based product count methods. The empirically shows that there are a growing number of highly-diversified logistics enterprises in general, with an average annual increase of 14.23%. Especially after 2008, small and medium-sized enterprises developed towards related diversification while micro-sized enterprises came to the opposite conclusion. For them, creating unrelated diversified business is a crucial way to generate a competitive advantage. Unlike the conclusions derived from other industries, small-sized logistics enterprises are prone to try a new business, both related and unrelated, for better survival and performance. And changes in the firm size of medium and large-sized enterprises have little impact on the development of the business diversification.

关键词： Business Diversification Logistics Firm Size RBV Logistics Business Classification System

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Environmental analysis on co-processing of domestic waste in cement kiln 20th

Environmental analysis on co-processing of domestic waste in...

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20th Chinese Materials Conference, CMC 2019

作者： Yang, Xue Lin, Xinping Wang, Yanjing Liu, Yu Hao, Liwei Sun, Boxue National Engineering Laboratory for Industrial Big-data Application Technology Beijing100124 China Beijing University of Technology The Key Laboratory of Advanced Functional Materials Ministry of Education of China Beijing100124 China Beijing Building Materials Academy of Sciences Research State Key Laboratory of Solid Waste Reuse for Building Materials Beijing100041 China

ISBN: (纸本)9783035715668

The annual output of domestic waste has exceeded 400 million tons in China since 2016, which causes an urgent demand on harmless disposal in the current rapid process of urbanization. Compared with traditional disposal means (e.g. incineration and landfill), co-processing with cement production seems to be a better chose to meet the requirements of domestic waste treatment (i.e. harmless, volume reduction, waste utilization). However, co-processing technology also has some negative impact (e.g. extra energy consumption for pretreatment of domestic waste), so the environmental feasibility of domestic waste co-processing in cement kiln should be verified. In this paper, the influences caused by domestic waste co-processing on the cement clinker products including resource/energy consumption, as well as the pollutant emissions were quantify based on the investigation of typical plants in China. Moreover, the environment impact between landfill treatment and co-processing scenario were compared using life cycle assessment (LCA) method. The result shows that the energy consumption and CO2 emission per ton cement clinker production increased by 3.6% and 0.8% after co-process domestic waste, respectively. Furthermore, compared with sanitary landfill treatment, the co-processing in cement kiln will increase the impact of FFP, but reduce GWP and HTP impacts, especially significantly decrease the impact of LOP and SOP, bring in a good beneficial on material saving and energy saving. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Life cycle

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Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

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CAAI Transactions on Intelligence technology 2023年第3期8卷 987-1001页

作者： Zichao Zhang Jian Chen Xinyu Xu Cunjia Liu Yu Han College of Engineering China Agricultural UniversityBeijingChina Jiangsu Province and Education Ministry Co‐sponsored Synergistic Innovation Center of Modern Agricultural Equipment Jiangsu UniversityZhenjiangChina Key Laboratory of Spatial‐temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghaiChina Department of Aeronautical and Automotive Engineering Loughborough UniversityLoughboroughLeicestershireUK College of Water Resources and Civil Engineering China Agricultural UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijingChina Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhenChina

The binocular stereo vision is the lowest cost sensor for obtaining 3D *** the weakness of long‐distance measurement and stability,the improvement of accuracy and stability of stereo vision is urgently required for application of precision *** address the challenges of stereo vision long‐distance measurement and stable perception without hardware upgrade,inspired by hawk eyes,higher resolution perception and the adaptive HDR(High Dynamic Range)were introduced in this *** the function from physiological structure of‘deep fovea’and‘shallow fovea’of hawk eye,the higher resolution reconstruction method in this paper was aimed at ac-curacy *** by adjustment of pupils,the adaptive HDR method was proposed for high dynamic range optimisation and stable *** various light conditions,compared with default stereo vision,the accuracy of proposed algorithm was improved by 28.0%evaluated by error ratio,and the stability was improved by 26.56%by disparity *** fixed distance measurement,the maximum improvement was 78.6%by standard *** on the hawk‐eye‐inspired perception algorithm,the point cloud of orchard was improved both in quality and *** hawk‐eye‐inspired perception algorithm contributed great advance in binocular 3D point cloud recon-struction in orchard navigation map.

关键词： adaptive high dynamic range binocular stereo vision hawk‐eye‐inspired perception point cloud of orchard super‐resolution generative adversarial network

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A hybrid modeling approach incorporating physical modeling and deep learning for multiphase flow simulation 84

A hybrid modeling approach incorporating physical modeling a...

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84th EAGE Annual Conference and Exhibition

作者： Wang, Y. Zhang, J. Du, S. Yan, B. Song, H. Wang, J. Xie, C. China Texas A&M University United States University of Science and Technology Beijing China National & Local Joint Engineering Laboratory for Big-Data Analysis and Computing Technology King Abdullah University of Science and Technology Saudi Arabia Computer Network Information Center Chinese Academy of Sciences China

ISBN: (纸本)9781713884156

Multiphase flows are of great importance for the sustainable utilization of geological resources and ecological protection. Numerical simulation, as a general and powerful approach for multiphase flow modeling, faces great computational challenge for large scale and heterogeneous problems. This study explores the possibility of a hybrid modeling architecture for nonlinear multiphase flow, which integrates physical modeling and deep learning approaches. By breaking down the coupled system into pressure and saturation equations, we construct novel solvers using a physics-guided U-net and Fourier Neural Operator instead of the traditional time-consuming implicit pressure solver. The coupling of our carefully designed solver for pressure and explicit solver for saturation provides a new perspective for modeling large scale complex multiphase flows. Our results demonstrate that this hybrid modeling architecture exhibits superior predictive performance for pressure and saturation, with relative error about 0.2% and 0.6%, respectively. More importantly, our hybrid solver can improve computational efficiency by several orders of magnitude compared to traditional numerical simulation workflows. Our work showcases that the proposed hybrid modeling approach incorporating physical modeling and deep learning is promising to provide a more flexible and powerful alternative for multiphase flow modeling in geological formations. © 2023 84th EAGE Annual Conference and Exhibition. All rights reserved.

关键词： Multiphase flow

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