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5th International Workshop on Statistical Physics and Mathematics for Complex Systems, SPMCS 2017

作者： Liu, Zhi Kang, Lingyun Su, Zhu Liu, Sannyuya Sun, Jianwen National Engineering Research Center for E-Learning Central China Normal University Wuhan China National Engineering Laboratory for Technology of Big Data Applications in Education Central China Normal University Wuhan China

The social interaction behaviors of group learning have obtained a lot of attention from researches, and social network analysis (SNA) plays a critical role in exploring collective interactive patterns. In this paper, we investigated the experimental data from the discussion forum of "Discourse analysis" course in a university learning platform. By calculating learners social characteristics, we explored the relationship between social characteristics and academic achievements, as well as the differences between various achieving learners. The results show that there exist strong positive correlations between most social characteristics and academic achievements, and the majority of high-achieving learners are located at the core position of the network. In addition, the high-achieving learners exhibited more active participations in discussions and received more posts compared with middle- and low-achieving learners. © Published under licence by IOP Publishing Ltd.

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Medical Image Segmentation Using Deep Learning: A Survey

arXiv

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arXiv 2020年

作者： Wang, Risheng Lei, Tao Cui, Ruixia Zhang, Bingtao Meng, Hongying Nandi, Asoke K. The School of Electronic Information and Artificial Intelligence The Shaanxi Joint Laboratory of Artificial Intelligence Shaanxi University of Science and Technology Xi'An710021 China The 'Laboratory of Hepatobiliary Surgery First Affiliated Hospital' 'National Engineering Laboratory of Big Data Algorithm and Analysis Technology Research' Xi'an Jiaotong University Xi'An710049 China The School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China The Department of Electronic and Electrical Engineering Brunel University London UxbridgeUB8 3PH United Kingdom

Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. In this paper, we present a comprehensive thematic survey on medical image segmentation using deep learning techniques. This paper makes two original contributions. Firstly, compared to traditional surveys that directly divide literatures of deep learning on medical image segmentation into many groups and introduce literatures in detail for each group, we classify currently popular literatures according to a multi-level structure from coarse to fine. Secondly, this paper focuses on supervised and weakly supervised learning approaches, without including unsupervised approaches since they have been introduced in many old surveys and they are not popular currently. For supervised learning approaches, we analyze literatures in three aspects: the selection of backbone networks, the design of network blocks, and the improvement of loss functions. For weakly supervised learning approaches, we investigate literature according to data augmentation, transfer learning, and interactive segmentation, separately. Compared to existing surveys, this survey classifies the literatures very differently from before and is more convenient for readers to understand the relevant rationale and will guide them to think of appropriate improvements in medical image segmentation based on deep learning approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

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Wheat yellow rust monitoring method based on Sentinel-2 image and BPNN model

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural engineering 2019年第17期35卷 178-185页

作者： Huang, Linsheng Jiang, Jing Huang, Wenjiang Ye, Huichun Zhao, Jinling Ma, Huiqin Ruan, Chao National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University 230601 China Sanya Institute of Remote Sensing Sanya572029 China Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing100094 China

Wheat yellow rust is a deadly disease of winter wheat and its timely and accurate detection at regional scale is critical to ameliorate infectious yield loss and safeguard wheat production. With the development in remote sensing technology, satellite imagery with high spatial resolution and high revisiting frequency has become increasingly accessible. Remote sensing data has a unique advantage over traditional method in detecting crop diseases and controlling their spreading, including simple operation, real-time detection, high spatiotemporal resolution and targeting specific-disease, especially the multispectral satellite imagery which covers a wide range of wave bands and provides rich information related to crop diseases at regional scale. Compared to conventional broad band satellite imagery, the Sentinel-2 is a sensor with three wave bands within the edge of the red light which are sensitive to crop diseases. In this study, a Sentinel-2 image acquired in May 12, 2018 was used to extract 26 characteristic variables related to wheat yellow rust, including 3 visible bands (blue, green and red) reflectance variables, one near infrared band, 3 red-edge bands, 14 broad-bands and 5 red-edge vegetation indices. An approach combining K-means and ReliefF algorithm is proposed to filter these features. We first used the RelieF algorithm to calculate the weight of each feature and filter out 10 features most relevant to the disease. The feature with maximum weight was then taken as the initial center of the K-Means algorithm, and other features were added to form a cluster in descending order of their weight. The combination of features with the highest clustering accuracy was taken as the final input variable to the model. The optimal features, including enhanced vegetation index (EVI), structure intensive pigment index (SIPI), simple ratio index (SR), normalized red-edge2 index(NREDI2), normalized red-edge3 index (NREDI3), three wide-band vegetation indices and 2 red ed

关键词： Remote sensing

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A Wavelet-CNN-LSTM Model for Tailings Pond Risk Prediction

arXiv

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arXiv 2020年

作者： Yang, Jun Li, Qing Sun, Yixuan Wang, Wei Li, Linchao Wang, Xuwei Jia, Shengyao Tong, Renyuan National and Local Joint Engineering research center for Disaster Monitoring Technologies and Instruments China Jiliang University Hangzhou310051 China Zhejiang Provincial Key Laboratory of Intelligent Manufacturing Quality Big Data Traceability Analysis and Application China Jiliang University Hangzhou310051 China Zhejiang PeckerAI Technology. Ltd Hangzhou310018 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China

Tailings ponds are places for storing industrial waste. The saturation line is the key factor of quantifying the safety of tailings pond. Existing saturation line time-series prediction methods are mainly based on statistical models or shallow machine learning models. Although these models aim to capture the time dependence of the sequence data, the channel and temporal are even unavailable in principle. In this paper, we presents a two-stage forecasting method, which embeds the channel and temporal attention into a hybrid CNN-LSTM model to predict the saturation line. In the first stage, the discrete wavelet transform (DWT) is applied to capture the refined sequence information. In the second stage, the CNN-LSTM model is utilized to learn the basic spatial and temporal features in the time series. Furthermore, the channel and temporal attention model are embedded into CNN-LSTM model to enhance the feature extracting ability in channel and temporal dimension. Consequently, our proposed model is shown to outperform classic models on five real-world datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Forecasting

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Award for Outstanding Comprehensive Mini-Challenge 2 Solution - RadiationMonitor: An Interactive System for Visualizing and Exploring Spatial-Temporal data

Award for Outstanding Comprehensive Mini-Challenge 2 Solutio...

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IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Datong Wei Hanning Shao Zijing Tan Chenlu Li Zhixian Lin Xiaoju Dong Xiaoru Yuan Key Laboratory of Machine Perception Ministry of Education School of EECS Peking University Weinberg College of Arts and Sciences Northwestern University School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University National Engineering Laboratory for Big Data Analysis and Application Peking University

In this paper, we proposed RadiationMonitor, an interactive system for visualizing and exploring spatial-temporal data from static and mobile sensors. We use pixel-based time-series visualization for event presentation, and the trajectories of mobile sensors are discretized to display the spatial distribution of sensor readings. Our system provides cross-filtering and detail-on-demand interactions, which allow users to investigate data from both spatial and temporal aspects.

关键词： Sensor systems Pollution measurement data visualization Uncertainty Image color analysis Measurement uncertainty Awards

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Author Correction: Mapping annual 10-m soybean cropland with spatiotemporal sample migration

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Scientific data 2024年第1期11卷 565页

作者： Hongchi Zhang Zihang Lou Dailiang Peng Bing Zhang Wang Luo Jianxi Huang Xiaoyang Zhang Le Yu Fumin Wang Linsheng Huang Guohua Liu Shuang Gao Jinkang Hu Songlin Yang Enhui Cheng Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. University of Chinese Academy of Sciences Beijing 100094 China. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. pengdl@***. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. pengdl@***. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. University of Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. Jiangxi Nuclearindustry Surveying and Mapping Institute Group Co. Ltd Nanchang 330038 China. College of Land Science and Technology China Agricultural University Beijing 100083 China. Geospatial Sciences Center of Excellence Department of Geography Geospatial Sciences South Dakota State University Brookings SD 57007 USA. Department of Earth System Science Tsinghua University Beijing 100084 China. Institute of Applied Remote Sensing & Information Technology Zhejiang University Hangzhou 310058 China. National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei 230601 China. Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai 200120 China.

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Analyses of geographical observations in the Heihe River Basin: Perspectives from complexity theory

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Journal of Geographical Sciences 2019年第9期29卷 1441-1461页

作者： Gao Jianbo FANG Peng YUAN Lihua State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Institute of Complexity Science and Big Data Technology Guangxi UniversityNanning 530004China Wuhan National Laboratory for Optoelectronics Key Laboratory of In formation Storage SystemEngineering Research Center of Data Storage Systems and TechnologyMinistry of Education of ChinaSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Center for GeoData and Analysis Faculty of Geographical ScieneeBeijing Normal UniversityBeijing 100875China

Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been *** adequately analyze these available data and data to be further collected in future,we present a perspective from complexity *** concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process *** adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal *** SDLE is illustrated to determine intermittent chaos from river flow data.

关键词： Heihe River basin geographical observation complexity theory adaptive multiscale filter fractal analysis scale-dependent Lyapunov exponent

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Surface Activation and Ni-S Stabilization in NiO/NiS2for Efficient Oxygen Evolution Reaction

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Angewandte Chemie 2022年第35期134卷

作者： Nan Zhang Yang Hu Li An Qingyu Li Jie Yin Jianyi Li Rui Yang Min Lu Prof. Sen Zhang Prof. Pinxian Xi Prof. Chun-Hua Yan State Key Laboratory of Applied Organic Chemistry Key Laboratory of Nonferrous Metal Chemistry and Resources Utilization of Gansu Province Frontiers Science Center for Rare Isotopes College of Chemistry and Chemical Engineering Lanzhou University Lanzhou 730000 China Contribution: Data curation (lead) Writing - original draft (lead) Contribution: Data curation (lead) Contribution: Data curation (supporting) Contribution: Formal analysis (equal) Department of Chemistry University of Virginia Charlottesville VA 22904 USA Contribution: Writing - review & editing (equal) Contribution: Conceptualization (lead) Investigation (lead) Project administration (lead) Writing - original draft (lead) Writing - review & editing (lead) Beijing National Laboratory for Molecular Sciences State Key Laboratory of Rare Earth Materials Chemistry and Applications PKU-HKU Joint Laboratory in Rare Earth Materials and Bioinorganic Chemistry College of Chemistry and Molecular Engineering Peking University Beijing 100871 China Contribution: Supervision (equal) Writing - review & editing (equal)

Manipulating the active species and improving the structural stabilization of sulfur-containing catalysts during the OER process remain a tremendous challenge. Herein, we constructed NiO/NiS 2 and Fe−NiO/NiS 2 as catalyst models to study the effect of Fe doping. As expected, Fe−NiO/NiS 2 exhibits a low overpotential of 270 mV at 10 mA cm −2 . The accumulation of hydroxyl groups on the surface of materials after Fe doping can promote the formation of highly active NiOOH at a lower OER potential. Moreover, we investigated the level of corrosion of M−S bonds and compared the stability variation of M−S bonds with Fe at different locations. Interestingly, Fe bonded with S in the bulk as the sacrificial agent can alleviate the oxidation corrosion of partial Ni−S bonds and thus endow Fe−NiO/NiS 2 long-term durability. This work could motivate the community to focus more on resolving the corrosion of sulfur-containing materials.

关键词： Activation and Stabilization Fe Cation Doping In Situ Characterization Oxide/Sulfide Heterostructure Oxygen Evolution Reaction

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Synthesis of Bandgap-tunable Transition Metal Sulfides through Gas-phase Cation Exchange-induced Topological Transformation

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Angewandte Chemie 2023年第18期135卷

作者： Pengfei Da Prof. Yao Zheng Yang Hu Zelong Wu Hongyu Zhao Yicheng Wei Linchuan Guo Jingjing Wang Yanping Wei Prof. Shibo Xi Prof. Chun-Hua Yan Prof. Pinxian Xi State Key Laboratory of Applied Organic Chemistry Frontiers Science Center for Rare Isotopes College of Chemistry and Chemical Engineering Lanzhou University Lanzhou 730000 China Contribution: Data curation (lead) Formal analysis (lead) Writing - original draft (lead) Writing - review & editing (lead) School of Chemical Engineering and Advanced Materials The University of Adelaide Adelaide South Australia 5005 Australia Contribution: Conceptualization (equal) Writing - original draft (supporting) Writing - review & editing (supporting) Contribution: Data curation (equal) Contribution: Investigation (equal) Contribution: Methodology (equal) Contribution: Data curation (supporting) Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences Lanzhou 730000 China Contribution: Investigation (supporting) College of Science Gansu Agricultural University Lanzhou 730070 China Institute of Chemical and Engineering Sciences A*STAR 1 Pesek Road Jurong Island 627833 Singapore Beijing National Laboratory for Molecular Sciences State Key Laboratory of Rare Earth Materials Chemistry and Applications PKU-HKU Joint Laboratory in Rare Earth Materials and Bioinorganic Chemistry College of Chemistry and Molecular Engineering Peking University Beijing 100871 China Contribution: Conceptualization (supporting) Resources (equal) Writing - review & editing (equal) Contribution: Conceptualization (lead) Project administration (lead) Resources (equal) Supervision (lead) Writing - original draft (equal) Writing - review & editing (equal)

Oriented synthesis of transition metal sulfides (TMSs) with controlled compositions and crystal structures has long been promising for electronic devices and energy applications. Liquid-phase cation exchange (LCE) is a well-studied route by varying the compositions. However, achieving crystal structure selectivity is still a great challenge. Here, we demonstrate gas-phase cation exchange (GCE), which can induce a specific topological transformation (TT), for the synthesis of versatile TMSs with identified cubic or hexagonal crystal structures. The parallel six-sided subunit (PSS), a new descriptor, is defined to describe the substitution of cations and the transition of the anion sublattice. Under this principle, the band gap of targeted TMSs can be tailored. Using the photocatalytic hydrogen evolution as an example, the optimal hydrogen evolution rate of a zinc-cadmium sulfide (ZCS4) is determined to be 11.59 mmol h −1 g −1 , showing a 36.2-fold improvement over CdS.

关键词： Bandgap engineering Cation Exchange Photocatalytic Hydrogen Evolution Topological Transformation Transition Metal Sulfides

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