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Specific Index System of Ecological Balanced Fertilization for Maize

Meteorological and Environmental Research 2020年第5期11卷 62-68页

作者： keyu LIN Hongyan ZHENG Zhiping HUANG Jian DING Changhong MI Shutian LIU Xianda HOU Shuojin WANG Ling LU Yanlin HOU Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology Nanning Normal UniversityNanning 530001China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal UniversityNanning 530001China Key Laboratory of Environment Change and Resources Use in Beibu Gulf(Nanning Normal University) Nanning 530001China Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191China

This paper studied the index system of ecological balanced fertilization for maize by data mining method based on data of"3414 fertilizer field trials"of maize by published papers from national soil testing and recommendation since *** results and conclusions were as follows.①Soil nutrient content could not be used as indicator of fertilizer application of maize.②The conceptual model of N conversion rate of maize for plot was Y N≈a+b×optimum production-c×optimum fertilizer amount of N-d×optimum phosphorus application amount-e×optimum potassium application amount-f×temperature in growth season-g×rainfall in growth *** conceptual model of P conversion rate of maize for plot was Y P≈a+b×optimum phosphorus application amount-c×optimum nitrogen application amount-d×optimum potassium application *** conceptual model of K conversion rate of maize for plot was Y K≈a+b×optimum yield-c×optimum nitrogen application amount-d×optimum phosphorus application amount-e×optimum potassium application amount-f×temperature in growth season-g×rainfall in growth season.③The conceptual model of the optimum fertilizer amount of N of maize for plot was Y N≈a+b×optimum phosphorus application amount+c×optimum potassium application amount+d×temperature in growing season+e×rainfall in growing season,and the conceptual model of the optimum fertilizer amount of P was Y P≈a+b×optimum nitrogen application amount,and the conceptual model of the optimum fertilizer amount of K was Y K≈a+b×optimum nitrogen application amount+c×temperature in growth season+d×rainfall in growth season-e×optimum yield.④The conceptual model of relative abundance-deficiency value of soil N of maize for plot was that Y N≈a,and the conceptual model of relative abundance-deficiency value of soil P was Y P≈a,and the conceptual model of relative abundance-deficiency value of soil K was Y K≈a+b×optimum nitrogen application amount+c×optimum phosphorus application amount.

关键词： Optimum yield Optimum fertilization amount Nutrient conversion rate Fertilizer utilization ratio Relative abundance-deficiency value of soil nutrient

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Self-to-self transitions in open quantum systems:the origin and solutions

Self-to-self transitions in open quantum systems:the origin ...

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第三十九届中国控制会议

作者： Fang Gao Yaoxiong Wang Qing Gao Dewen Cao Feng Shuang College of Electrical Engineering Guangxi University Institute of Intelligent Machines Chinese Academy of Sciences School of Automation Science and Electrical Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University University Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University

The information of quantum pathways can be extracted in the framework of the Hamiltonianencoding and Observable-decoding *** closed quantum systems,only off-diagonal elements of the Hamiltonian in the Hilbert space is required to be encoded to obtain the desired *** open quantum systems,environment-related terms will appear in the diagonal elements of the Hamiltonian in the Liouville *** diagonal encodings have to be performed to differentiate different pathways,which will lead to self-to-self transitions and inconsistency of pathway amplitudes with Dyson *** this work,a well-designed transformation is proposed to avoid the counterintuitive transitions and the inconsistency,with or without control *** simulations show that the method are consistent with Dyson expansion.

关键词： Self-to-self transitions in open quantum systems:the origin and solutions origin

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Comparison of the Index System of Ecological Balanced Fertilization for Three Crops

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Meteorological and Environmental Research 2020年第5期11卷 76-90页

作者： Xianda HOU Hongyan ZHENG Shuojin WANG Shutian LIU Zhiping HUANG Jian DING Changhong MI Ling LU Yanlin HOU Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology Nanning Normal UniversityNanning 530001China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal UniversityNanning 530001China Key Laboratory of Environment Change and Resources Use in Beibu Gulf(Nanning Normal University) Nanning 530001China Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191China

This paper conducted comparative study of the index system of ecological balanced fertilization for rice,wheat and maize by data mining method based on data of"3414 fertilizer field trials"of rice,wheat and maize by published papers from national soil testing and recommendation since *** main conclusions of this paper were as follow:①since the three crops all belonged to Gramineae,they were consistent in variation trends of fertilizer utilization ratio,nutrient conversion rate,relative abundance-deficiency value of soil nutrient,optimum fertilization amount in most cases.②Due to the influence of the economic production,biological production,different water conditions in paddy field and dry farmland,length of growing season,cropping system(one year before and after the rotation)and so on,sometimes the laws of four aspects above mentioned for the three crops had opposite and gradient variations.

关键词： Optimum yield Optimum fertilization amount Nutrient conversion rate Fertilizer utilization ratio Relative abundance-deficiency value of soil nutrient

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Summary on the Index System of Ecological Balanced Fertilization for Maize

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Meteorological and Environmental Research 2020年第5期11卷 55-61页

作者： Hongyan ZHENG Shutian LIU Xianda HOU Shuojin WANG Zhiping HUANG Jian DING Changhong MI Ling LU Yanlin HOU Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191China Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology Nanning Normal UniversityNanning 530001China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal UniversityNanning 530001China Key Laboratory of Environment Change and Resources Use in Beibu Gulf(Nanning Normal University) Nanning 530001China

This paper studied the index system of ecological balanced fertilization for maize by data mining method based on data of"3414 fertilizer field trials"of maize by published papers from national soil testing and recommendation since *** results and conclusions were as follows:①the optimum N,P and K fertilization amounts of maize were within the normal range,and the application of this standard could not cause obvious non-point source pollution.②The conversion rates of N,P and K of maize were respectively higher than their respective utilization ratios under the optimum fertilization amount.③At present,the soil N for maize was in an absence state,and soil P and K were in a state of not obvious lack.④Optimum N,P and K fertilization amounts were significantly negatively correlated with their respective conversion ratios,respectively,and it provided a quantitative scientific basis for calculating the optimum fertilization amount according to the nutrient conversion *** province can use this significant relationship to guide the determination of the average optimal fertilization amounts of N,P and K and the optimal production in the province.⑤The research results of nutrient conversion rate showed that any excessive application of N,P and K would reduce their own nutrient conversion rates,and may also reduce the conversion rates of other *** characteristics of crops absorbing N,P and K proportionally required that soil nutrients must be balanced in order to obtain high production,and fertilization was only the main means to regulate soil nutrient balance.

关键词： Optimum yield Optimum fertilization amount Nutrient conversion rate Fertilizer utilization ratio Relative abundance-deficiency value of soil nutrient

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Improved small gain conditions for input-to-state stability with respect to measurement functions: Discrete time networked system

Improved small gain conditions for input-to-state stability ...

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IEEE Conference on Decision and Control

作者： Yuanqiu Mo Changbin Yu Soura Dasgupta Westlake Institute for Advanced Study Westlake University Hangzhou China College of Artificial Intelligence and Big Data Shandong First Medical University & Shandong Academy of Medical Sciences Jinan China Institute for Intelligent Robots Fudan University Shanghai China Shandong Computer Science Center Shandong Provincial Key Laboratory of Computer Networks China Faculty of Engineering & the Built Environment University of Johannes-Burg Johannesburg South Africa University of Iowa Iowa City Iowa USA

ISBN: (纸本)9781665436601

In this paper we study input-to-state stability with respect to measurement functions for discrete time networked systems. In such a networked system, the trajectory of each subsystem is affected by another in each time step, and this constraining system may change from step to step. We derive small gain conditions of input-to-state stability with respect to measurement functions for this type of discrete time networked system relying on the construction of dissipative-form finite time Lyapunov function. These conditions loosen those presented in [1] and [2]. Finally, we demonstrate the applicability of our results by applying them to the stability analysis of a distributed graph algorithm which does not satisfy the conditions of [1] and [2].

关键词： Network topology Conferences Gain measurement Stability analysis Time measurement Trajectory Topology

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Single Object Tracking for Dynamic Programming based on Fine-grained Network

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Journal of Physics: Conference Series 2020年第1期1576卷

作者： Jianguo Jiang Kaiyuan Jin Jingjing Wu Meibin Qi Qian Wang Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei 230601 China

Single target tracking has always been a key and challenging research field in computer vision. Currently, an increasing number of researchers are focusing on extracting better tracking features and designing the best tracker. This paper proposes a new single target tracking network that uses fine-grained features and dynamic programming (DPFNet). In order to extract superior features, we added an attention module to the regression network enabling us to extract finer-grained and discriminative features to achieve regression. Besides, we did observe that different objects have varying moving rates; for different moving targets, the magnitude of the changes in target position within two adjacent frames is not the same either. Although an area search of 4 times the target's size can be applied to most objects, targets with large position changes may appear in other image areas outside the search area and the target would not be located as a result. Aiming at solving this problem, when designing the tracker, this paper analyzes some of the indicators for predicting the location and uses the analysis results to determine whether the search area is appropriate, so as to dynamically adjust the extent of the search area thereby significantly improving the tracking function. In other words, the size of the search area can be dynamically recalibrated for different images. Subsequent experiments prove that the method put forward in this paper achieves State-of-the-Art results.

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A study on the uncertainty of convolutional layers in deep neural networks

arXiv

引用

arXiv 2020年

作者： Shen, Haojing Chen, Sihong Wang, Ran Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University ShenzhenGuangdong518060 China College of Mathematics and Statistics Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

This paper shows a Min-Max property existing in the connection weights of the convolutional layers in a neural network structure, i.e., the LeNet. Specifically, the Min-Max property means that, during the back propagation-based training for LeNet, the weights of the convolutional layers will become far away from their centers of intervals, i.e., decreasing to their minimum or increasing to their maximum. From the perspective of uncertainty, we demonstrate that the Min-Max property corresponds to minimizing the fuzziness of the model parameters through a simplified formulation of convolution. It is experimentally confirmed that the model with the Min-Max property has a stronger adversarial robustness, thus this property can be incorporated into the design of loss function. This paper points out a changing tendency of uncertainty in the convolutional layers of LeNet structure, and gives some insights to the interpretability of convolution. © 2020, CC-BY.

关键词： Convolution

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One for Multiple: Physics-informed Synthetic data Boosts Generalizable Deep Learning for Fast MRI Reconstruction

arXiv

引用

arXiv 2023年

作者： Wang, Zi Yu, Xiaotong Wang, Chengyan Chen, Weibo Wang, Jiazheng Chu, Ying-Hua Sun, Hongwei Li, Rushuai Li, Peiyong Yang, Fan Han, Haiwei Kang, Taishan Lin, Jianzhong Yang, Chen Chang, Shufu Shi, Zhang Hua, Sha Li, Yan Hu, Juan Zhu, Liuhong Zhou, Jianjun Lin, Meijing Guo, Jiefeng Cai, Congbo Chen, Zhong Guo, Di Yang, Guang Qu, Xiaobo Department of Electronic Science Intelligent Medical Imaging R&D Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Xiamen University China Human Phenome Institute Fudan University China Philips Healthcare China Siemens Healthineers Ltd. China United Imaging Research Institute of Intelligent Imaging China Department of Nuclear Medicine Nanjing First Hospital China Shandong Aoxin Medical Technology Company China Department of Radiology The First Affiliated Hospital of Xiamen University China Department of Radiology Zhongshan Hospital Affiliated to Xiamen University China China Department of Cardiology Shanghai Institute of Cardiovascular Diseases Zhongshan Hospital Fudan University China Department of Radiology Zhongshan Hospital Fudan University China Department of Cardiovascular Medicine Heart Failure Center Ruijin Hospital Lu Wan Branch Shanghai Jiaotong University School of Medicine China Department of Radiology Ruijin Hospital Shanghai Jiaotong University School of Medicine China Medical Imaging Department The First Affiliated Hospital of Kunming Medical University China Xiamen Key Laboratory of Clinical Transformation of Imaging Big Data and Artificial Intelligence China Department of Applied Marine Physics and Engineering Xiamen University China Department of Microelectronics and Integrated Circuit Xiamen University China School of Computer and Information Engineering Xiamen University of Technology China Department of Bioengineering Imperial College London United Kingdom

Magnetic resonance imaging (MRI) is a widely used radiological modality renowned for its radiation-free, comprehensive insights into the human body, facilitating medical diagnoses. However, the drawback of prolonged scan times hinders its accessibility. The k-space undersampling offers a solution, yet the resultant artifacts necessitate meticulous removal during image reconstruction. Although Deep Learning (DL) has proven effective for fast MRI image reconstruction, its broader applicability across various imaging scenarios has been constrained. Challenges include the high cost and privacy restrictions associated with acquiring large-scale, diverse training data, coupled with the inherent difficulty of addressing mismatches between training and target data in existing DL methodologies. Here, we present a novel Physics-Informed Synthetic data learning framework for Fast MRI, called PISF. PISF marks a breakthrough by enabling generalized DL for multi-scenario MRI reconstruction through a single trained model. Our approach separates the reconstruction of a 2D image into many 1D basic problems, commencing with 1D data synthesis to facilitate generalization. We demonstrate that training DL models on synthetic data, coupled with enhanced learning techniques, yields in vivo MRI reconstructions comparable to or surpassing those of models trained on matched realistic datasets, reducing the reliance on real-world MRI data by up to 96%. Additionally, PISF exhibits remarkable generalizability across multiple vendors and imaging centers. Its adaptability to diverse patient populations has been validated through evaluations by ten experienced medical professionals. PISF presents a feasible and cost-effective way to significantly boost the widespread adoption of DL in various fast MRI applications. Importantly, it alleviates the ethical and practical challenges associated with in vivo human data acquisitions, opening new horizons for advancing fast MRI technologies. Copyright © 20

关键词： Magnetic resonance imaging

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Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

引用

Computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： Xuting Duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

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Incorporating Hidden Layer representation into Adversarial Attacks and Defences

arXiv

引用

arXiv 2020年

作者： Shen, Haojing Chen, Sihong Wang, Ran Wang, Xizhao Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Guangdong Shenzhen518060 China The College of Mathematics and Statistics Shenzhen University Shenzhen518060 China The Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

In this paper, we propose a defence strategy to improves adversarial robustness incorporating hidden layer representation. The key of this defence strategy aims to compress or filter input’s information including adversarial perturbation. And this defence strategy can be regarded as an activation function which can be applied any kind of neural networks. We also prove theoretically the effectiveness of this defense strategy under certain conditions. Besides, incorporating hidden layer representation we propose three types of adversarial attacks to generate three types of adversarial examples, respectively. The experiments show that our defence method can significantly improve the adversarial robustness of deep neural networks which achieves the state-of-the-art performance even though we do not adopt adversarial training. © 2020, CC BY.

关键词： Deep neural networks

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