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arXiv 2024年

作者： Wang, Lei Shan, Huanyuan Nie, Lin Liu, Dezi Yan, Zhaojun Li, Guoliang Cheng, Cheng Xie, Yushan Qu, Han Zheng, Wenwen Kang, Xi Purple Mountain Observatory Chinese Academy of Sciences No. 10 Yuan Hua Road Nanjing210023 China Department of Information Engineering Wuhan Institute of City Hubei Wuhan430083 China Shanghai Astronomical Observatory Nandan Road 80 Shanghai200030 China National Basic Science Data Center Building No.2 4 Zhongguancun South 4th Street Haidian District Beijing190 China Zhejiang University Purple Mountain Observatory Joint Research Center for Astronomy Zhejiang University Hangzhou327 China South-Western Institute for Astronomy Research Yunnan University Kunming650500 China The Shanghai Key Lab for Astrophysics Shanghai Normal University Shanghai200234 China Chinese Academy of Sciences South America Center for Astronomy National Astronomical Observatories CAS Beijing100101 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Key Laboratory of Radio Astronomy and Technology Chinese Academy of Sciences A20 Datun Road Chaoyang District Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China

We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms. Our approach not only allows for the anti-aliasing of the images but also enables PSF deconvolution, resulting in enhanced restoration of extended sources, the highest PSNR, and reduced ringing artefacts. To test our method, we conducted numerical simulations that replicated observation runs of the CSST/VST telescope and compared our results to those obtained using previous algorithms. The simulation showed that our method outperforms previous approaches in several ways, such as restoring the profile of extended sources and minimizing ringing artefacts. Additionally, because our method relies on the inherent advantages of least squares fitting, it is more versatile and does not depend on the local uniformity hypothesis for the PSF. However, the new method consumes much more computation than the other approaches. © 2024, CC BY.

关键词： Anti-aliasing

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ReCoSa: Detecting the relevant contexts with self-attention for multi-turn dialogue generation

arXiv

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arXiv 2019年

作者： Zhang, Hainan Y., Lan L., Pang J., Guo X., Cheng CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

In multi-turn dialogue generation, response is usually related with only a few contexts. Therefore, an ideal model should be able to detect these relevant contexts and produce a suitable response accordingly. However, the widely used hierarchical recurrent encoder-decoder models just treat all the contexts indiscriminately, which may hurt the following response generation process. Some researchers try to use the cosine similarity or the traditional attention mechanism to find the relevant contexts, but they suffer from either insufficient relevance assumption or position bias problem. In this paper, we propose a new model, named ReCoSa, to tackle this problem. Firstly, a word level LSTM encoder is conducted to obtain the initial representation of each context. Then, the self-attention mechanism is utilized to update both the context and masked response representation. Finally, the attention weights between each context and response representations are computed and used in the further decoding process. Experimental results on both Chinese customer services dataset and English Ubuntu dialogue dataset show that ReCoSa significantly outperforms baseline models, in terms of both metric-based and human evaluations. Further analysis on attention shows that the detected relevant contexts by ReCoSa are highly coherent with human's understanding, validating the correctness and interpretability of ReCoSa. Copyright © 2019, The Authors. All rights reserved.

关键词： Signal encoding

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Reduced collatz dynamics is periodical and the period equals 2 to the power of the count of x/2

TechRxiv

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TechRxiv 2020年

作者： Ren, Wei School of Computer Science China University of Geosciences Wuhan China Key Laboratory of Network Assessment Technology CAS Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Guizhou Provincial Key Laboratory of Public Big Data Guizhou University Guizhou China

We propose Reduced Collatz Conjecture that is equivalent to Collatz Conjecture but is easier to explore, because reduced dynamics is more primitive than original dynamics and presents better structures (e.g., period and ratio). Reduced dynamics (that are occurred computation sequence from a starting integer to the first integer less than the starting integer) is the component of original dynamics (from a starting integer to 1). Reduced dynamics of x is represented by a sequence of computation that is either (3*x+1)/2 or x/2, because 3*x+1 is always even and followed by x/2. We prove that reduced dynamics is periodical and its period equals 2 to the power of the count of x/2. More specifically, if there exists reduced dynamics of x, then there exists reduced dynamics of x+P, where P equals 2L and L is the total count of x/2 computations in reduced dynamics of x (equivalently, L is the length of the sequence). © 2020, CC BY.

关键词： Dynamics

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A reduced collatz dynamics maps to a residue class, and its count of x/2 over count of 3*x+1 is larger than ln3/ln2

TechRxiv

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TechRxiv 2020年

作者： Ren, Wei School of Computer Science China University of Geosciences Wuhan China Key Laboratory of Network Assessment Technology CAS [Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Guizhou Provincial Key Laboratory Public Big Data Guizhou University Guizhou China

We propose Reduced Collatz conjecture and prove that it is equivalent to Collatz conjecture but more primitive due to reduced dynamics. We study reduced dynamics (that consists of occurred computations from any starting integer to the first integer less than it), because it is the component of original dynamics (from any starting integer to 1). Reduced dynamics is denoted as a sequence of "I" that represents (3*x+1)/2 and "O" that represents x/2. Here 3*x+1 and x/2 are combined together because 3*x+1 is always even and thus followed by x/2. We discover and prove two key properties on reduced dynamics: (1) Reduced dynamics is invertible. That is, given a reduced dynamics, a residue class that presents such reduced dynamics, can be computed directly by our derived formula. (2) Reduced dynamics can be constructed algorithmically, instead of by computing concrete 3*x+1 and x/2 step by step. We discover the sufficient and necessary condition that guarantees a sequence consisting of "I" and "O" to be a reduced dynamics. Counting from the beginning of a sequence, if and only if the count of x/2 over the count of 3*x+1 is larger than ln3/ln2, reduced dynamics will be obtained (i.e., current integer will be less than starting integer). © 2020, CC BY.

关键词： Dynamics

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Collatz dynamics is partitioned by residue class regularly

TechRxiv

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TechRxiv 2020年

We propose Reduced Collatz Conjecture that is equivalent to Collatz Conjecture, which states that every positive integer can return to an integer less than it, instead of 1. Reduced Collatz Conjecture should be easier because some properties are presented in reduced dynamics, rather than in original dynamics (e.g., ratio and period). Reduced dynamics is a computation sequence from starting integer to the first integer less than it, and original dynamics is a computation sequence from starting integer to 1. Reduced dynamics is a component of original dynamics. We denote dynamics of x as a sequence of either computations in terms of "I" that represents (3*x+1)/2 and "O" that represents x/2. Here 3*x+1 and x/2 are combined together, because 3*x+1 is always even and followed by x/2. We formally prove that all positive integers are partitioned into two halves and either presents "I" or "O" in next ongoing computation. More specifically, (1) if any positive integer x that is i module 2t (i is an odd integer) is given, then the first t computations (each one is either "I" or "O" corresponding to whether current integer is odd or even) will be identical with that of i. (2) If current integer after t computations (in terms of "I" or "O") is less than x, then reduced dynamics of x is available. Otherwise, the residue class of x (namely, i module 2t) can be partitioned into two halves (namely, i module 2t+1 and i+2t module 2t+1), and either half presents "I" or "O" in intermediately forthcoming (t+1)-th computation. © 2020, CC BY.

关键词： Dynamics

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on the Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2024, The Authors. All rights reserved.

关键词： Biotic

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Space technology:A powerful tool for safeguarding world heritage

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The Innovation 2023年第3期4卷 27-28页

作者： Lei Luo Jie Liu Francesca Cigna Damian Evans Mario Hernandez Deodato Tapete Peter Shadie Athos Agapiou Abdelaziz Elfadaly Min Chen Lanwei Zhu Bihong Fu Ruixia Yang Shahina Tariq Mohamed Ouessar Rosa Lasaponara Xinyuan Wang Huadong Guo International Research Center of Big Data for Sustainable Development Goals(CBAS) Beijing 100094China Key Laboratory of Digital Earth Science Aerospace Information Research Institute(AIR)Chinese Academy of Sciences(CAS)Beijing 100094China International Centre on Space Technologies for Natural and Cultural Heritage(HIST)Under the Auspices of UNESCO Beijing 100094China Institute of Atmospheric Sciences and Climate(ISAC) National Research Council(CNR)00133 RomeItaly École Française d’Extreme-Orient 22 Avenue du Président Wilson75116 ParisFrance International Society for Digital Earth(ISDE) Mexico CityMexico Italian Space Agency(ASI) 00133 RomeItaly Blue Mountains World Heritage Institute 16 Dunmore LaneKatoombaNSW 2780Australia Earth Observation Cultural Heritage Research Lab Department of Civil Engineering and GeomaticsCyprus University of TechnologyPO Box 503296 Limassol 3036Cyprus National Authority for Remote Sensing and Space Sciences Cairo 1564Egypt Key Laboratory of Virtual Geographic Environment Ministry of Education of PRCNanjing Normal UniversityNanjing 210023China COMSATS University Islamabad(CUI) Islamabad 45550Pakistan Institut des Regions Arides(IRA)-Medenine Medenine 4119Tunisia Institute of Methodologies for Environmental Analysis(IMAA) CNRC.da Santa LojaTito Scalo85050 PotenzaItaly

WORLD HERITAGE AND SPACE technology The Convention Concerning the Protection of the World Cultural and Natural Heritage(WHC),adopted by United Nations Educational,Scientific and Cultural Organization(UNESCO)on November 16,1972,aims to ensure the identification,protection,conservation,presentation,and transmission to future generations of the world’s cultural and natural *** WHC works toward these goals by emphasizing the Outstanding Universal Value(OUV)of heritage sites and the unique contribution such places can make to conservation and human development agendas.1 As of the end of January 2023,theWHC has been signed by 194 state parties,covering 1,157 sites(including 900 cultural,218 natural,and 39 mixed properties),55 of which are considered to be in *** sites,totaling an area of more than 370 million hectares are designated as World Heritage(WH)sites(https://***/en/list/).WH sites have played a significant role in the sustainable development of society globally and helped effectively maintain and preserve the cultural diversity and global biodiversity of the Earth.

关键词： heritage maintain SPACE

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A symmetric uniform formula and sole index method for sieving (twin) primes

TechRxiv

引用

TechRxiv 2020年

作者： Ren, Wei School of Computer Science China University of Geosciences Wuhan430074 China Key Laboratory of Network Assessment Technology CAS Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Guizhou Provincial Key Laboratory of Public Big Data GuiZhou University Guizhou China

All primes can be indexed by k, as primes must be in the form of 6k+1 or 6k-1. In this paper, we explore for the set of k such that either 6k+1 or 6k-1 is not a prime. Our method provides a uniform formula for k that can sieve primes and twin primes as well. The uniform presents symmetry in terms of k that works as single index in sieving. We also propose a new conjecture that is equivalent to Twin Prime Conjecture but possibly be easier to approach by merely exploring of sole index in term of k. The uniform formula for prime sieving are as follows: k ∈ Sl ⇒ 6k−1 6∈ , where Sl = [−I]6I+1 = [I]6I−1\min([I]6I−1), I ∈ . k ∈ Sr ⇒ 6k + 1 6∈ , where Sr = [−I]6I−1 ∪ ([I]6I+1\min([I]6I+1)), I ∈ . © 2020, CC BY.

关键词： Number theory

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Local and global structure-aware entropy regularized mean teacher model for 3d left atrium segmentation 23rd

Local and global structure-aware entropy regularized mean te...

引用

23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Hang, Wenlong Feng, Wei Liang, Shuang Yu, Lequan Wang, Qiong Choi, Kup-Sze Qin, Jing School of Computer Science and Technology Nanjing Tech University Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Department of Radiation Oncology Stanford University StanfordCA94305 United States CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China School of Nursing Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9783030597092

Emerging self-ensembling methods have achieved promising semi-supervised segmentation performances on medical images through forcing consistent predictions of unannotated data under different perturbations. However, the consistency only penalizes on independent pixel-level predictions, making structure-level information of predictions not exploited in the learning procedure. In view of this, we propose a novel structure-aware entropy regularized mean teacher model to address the above limitation. Specifically, we firstly introduce the entropy minimization principle to the student network, thereby adjusting itself to produce high-confident predictions of unannotated images. Based on this, we design a local structural consistency loss to encourage the consistency of inter-voxel similarities within the same local region of predictions from teacher and student networks. To further capture local structural dependencies, we enforce the global structural consistency by matching the weighted self-information maps between two networks. In this way, our model can minimize the prediction uncertainty of unannotated images, and more importantly that it can capture local and global structural information and their complementarity. We evaluate the proposed method on a publicly available 3D left atrium MR image dataset. Experimental results demonstrate that our method achieves outstanding segmentation performances than the state-of-the-art approaches in scenes with limited annotated images. © Springer Nature Switzerland AG 2020.

关键词： Forecasting

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PSNAS-Net: Hybrid gradient-physical optimizationfor efficient neural architecture search in customized medical imaging analysis

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Expert Systems with Applications 2025年 288卷

作者： Zechen, Zheng Xuelei, He Fengjun, Zhao Xiaowei, He School of Information Science and Technology Northwest University No.1 Xuexue Avenue Shaanxi Xi'an710127 China Xi'an Key Lab of Radiomics and Intelligent Perception Northwest University No.1 Xuexue Avenue Shaanxi Xi'an710127 China School of Network and Data Center Northwest University No.1 Xuexue Avenue Shaanxi Xi'an710127 China

Neural architecture search (NAS) facilitates the automated construction of neural networks tailored to specific tasks and requirements, resulting in models that are more closely aligned with the target task's demands. However, in many studies, the extensive design space, high search costs, and time-consuming evaluation calculations render NAS impractical for numerous medical data tasks. Addressing these challenges, this study introduces an efficient algorithm for searching deep learning architectures. Initially, we propose 19 fundamental rules to streamline the design space, thereby reducing its scale. To improve the efficiency of the algorithm, we designed a NAS framework (PSNAS-Net) for convolutional neural networks and VisionTransformer, which consists of two search stages: Firstly, the improved powell algorithm is used to determine the model range, and the population-based simulated annealing algorithm is utilized to expedite the search for the final model. During the neural architecture search process, we consider accuracy, parameters, FLOPs, and model stability as comprehensive evaluation objectives, we designed a robust, flexible, and comprehensive metric for model evaluation. The experimental results demonstrate that PSNAS-Net achieves significantly shorter search times (0.05-1.47 GPU Days) compared to 19 existing NAS methods, while discovering compact models (as small as 0.11M) with superior performance across five medical image benchmarks. This study offers a viable approach for model search that accommodates individualized requirements. © 2025 Elsevier Ltd

关键词： Convolutional neural networks

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