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A synthetic aperture radar sea surface distribution estimation by n-order bézier curve and its application in ship detection

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Acta Oceanologica Sinica 2016年第9期35卷 117-125页

作者： LANG Haitao ZHANG Jie WANG Yiduo ZHANG Xi MENG Junmin School of Science Beijing University of Chemical Technology Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science &Technology The First Institute of Oceanography State Oceanic Administration

To dates,most ship detection approaches for single-pol synthetic aperture radar（SAR） imagery try to ensure a constant false-alarm rate（CFAR）.A high performance ship detector relies on two key components：an accurate estimation to a sea surface distribution and a fine designed CFAR ***,a novel nonparametric sea surface distribution estimation method is developed based on n-order bézier *** estimate the sea surface distribution using n-order bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of bézier curve and the number m of sample ***,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order bézier curve is combined with a cell averaging CFAR（CA-CFAR）.To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is *** experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 *** terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric *** terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.

关键词： bézier curve nonparametric method ship detection sea surface distribution synthetic aperture radar

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Real-time manifold regularized context-aware correlation tracking

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Frontiers of Computer Science 2020年第2期14卷 334-348页

作者： Jiaqing FAN Huihui SONG Kaihua ZHANG Qingshan LIU Fei YAN Wei LIAN Jiangsu Key Laboratory of Big Data Analysis Technology(B-DAT) Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Nanjing University of Information Science&TechnologyNanjing 211800China Department of Computer Science Changzhi UniversityChangzhi 046011China

Despite the demonstrated success of numerous correlation filter(CF)based tracking approaches,their assumption of circulant structure of samples introduces significant redundancy to learn an effective *** this paper,we develop a fast manifold regularized context-aware correlation tracking algorithm that mines the local manifold structure information of different types of ***,different from the traditional CF based tracking that only uses one base sample,we employ a set of contextual samples near to the base sample,and impose a manifold structure assumption on ***,to take into account the manifold structure among these samples,we introduce a linear graph Laplacian regularized term into the objective of CF ***,the optimization can be efficiently solved in a closed form with fast Fourier transforms(FFTs),which contributes to a highly efficient *** evaluations on the OTb100 and VOT2016 datasets demonstrate that the proposed tracker performs favorably against several state-of-the-art algorithms in terms of accuracy and ***,our tracker is able to run in real-time with 28 fps on a single CPU.

关键词： visual tracking manifold regularization correlation filter graph Laplacian

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Fabrication and magnetic properties of 4SC(NH_2)_2–Ni_(0.97)Cu_(0.03)Cl_2 single crystals

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Chinese Physics b 2015年第12期24卷 541-544页

作者：陈丽敏郭颖刘旭光解其云陶志阔谌静周玲玲刘春生 Key Laboratory of Radio Frequency and Micro-Nano Electronics of Jiangsu Province Jiangsu Key Laboratory of Big Data Analysis Technology Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Hefei National Laboratory for Physical Sciences at Microscale University of Science and Technology of China

Single crystals of 4SC（NH2）2–Ni1-xCux Cl2（x = 0.03）（Cu-DTN） containing spin S = 1/2 Cu^2＋and S = 1 Ni^2＋cations are synthesized by slow evaporation methods. Structural characterization demonstrates that the Cu-DTN is of a tetrahedral structure with lattice parameter c being 9.0995 A, which is 1.32% expansion compared with that of parent material DTN due to the larger radius of the Cu ion. Direct current（DC） susceptibility measurements show that both the antiferromagnetic exchange interaction at low temperature and the large anisotropy of susceptibilities are suppressed after doping the Cu ion, which could be related to the structural distortion and the increase of the super-exchange paths in Cu-DTN.

关键词： magnetic metal-doped magnetic materials susceptibility antiferromagnetic interaction

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Privacy Preserving Distributed bandit Residual Feedback Online Optimization Over Time-Varying Unbalanced Graphs

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2284-2297页

作者： Zhongyuan Zhao Zhiqiang Yang Luyao Jiang Ju Yang Quanbo Ge the School of Automation Nanjing University of Information Science and Technologyand also with Jiangsu Key Laboratory of Big Data Analysis Technology the School of Mechanical Engineering Shanghai Jiao Tong University IEEE

This paper considers the distributed online optimization(DOO) problem over time-varying unbalanced networks, where gradient information is explicitly unknown. To address this issue, a privacy-preserving distributed online one-point residual feedback(OPRF) optimization algorithm is proposed. This algorithm updates decision variables by leveraging one-point residual feedback to estimate the true gradient information. It can achieve the same performance as the two-point feedback scheme while only requiring a single function value query per iteration. Additionally, it effectively eliminates the effect of time-varying unbalanced graphs by dynamically constructing row stochastic matrices. Furthermore, compared to other distributed optimization algorithms that only consider explicitly unknown cost functions, this paper also addresses the issue of privacy information leakage of nodes. Theoretical analysis demonstrate that the method attains sublinear regret while protecting the privacy information of agents. Finally, numerical experiments on distributed collaborative localization problem and federated learning confirm the effectiveness of the algorithm.

关键词： Differential privacy distributed online optimization(DOO) federated learning one-point residual feedback(OPRF) time-varying unbalanced graphs

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An attribute reduction framework for inconsistent decision tables from view of the boundary region

An attribute reduction framework for inconsistent decision t...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Qian, Jin Chang, Yu-Hui Lv, Ping Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou213015 China Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9781509003891

Attribute reduction is one of the key issues for data preprocess in data mining. Many heuristic attribute reduction algorithms based on discernibility matrix have been proposed for inconsistent decision tables. However, these methods are usually computationally time-consuming. To address this issue, the derived consistent decision tables are defined for different definitions of relative reducts. The computations for different reducts of the original inconsistent decision tables are converted into the computations for their corresponding reducts of the derived consistent datasets. The relative discernibility object pair and the more optimal relative discernibility degree from view of the boundary region are designed to accelerate the attribute reduction process. An efficient attribute reduction framework using relative discernibility degree is proposed for large datasets. Experimental results show that our attribute reduction algorithms are effective and feasible for large inconsistent datasets. © 2016 IEEE.

关键词： Decision tables

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Detailed structural,mechanical,and electronic study of five structures for CaF2 under high pressure

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Chinese Physics b 2021年第3期30卷 194-204页

作者： Ying Guo Yumeng Fang Jun Li Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Big Data Analysis TechnologyNanjing University of Information Science and TechnologyNanjing 210044China Mingde New Material Technology Co. LTDAnji 313300China

Detailed density functional theory(DFT)calculations of the structural,mechanical,thermodynamic,and electronicproperties of crystalline CaF2 with five different structures in the pressure range of 0 GPa–150 GPa are performed byboth GGA(generalized gradient approximation)-PbE(Perdew–burke–Ernzerhof)and LDA(local density approximation)-CAPZ(Cambridge Serial Total Energy Package).It is found that the enthalpy differences imply that the fluorite phase→PbCl2-type phase→Ni2In-type phase transition in CaF2 occurs at PGGA1=8.0 GPa,PGGA2=111.4 GPa by usingthe XC of GGA,and PLDA1=4.5 GPa,PLDA2=101.7 GPa by LDA,respectively,which is consistent with previousexperiments and theoretical ***,the enthalpy differences between PbCl2-type and Ni2In-type phases inone molecular formula become very small at the pressure of about 100 GPa,indicating the possibility of coexistence of twophase at high *** may be the reason why the transition pressure of the second phase transition in other reportsis so huge(68 GPa–278 GPa).The volume changed in the second phase transition are also consistent with the enthalpydifference ***,the pressure dependence of mechanical and thermodynamic properties of CaF2 is *** found that the high-pressure phase of Ni2In-type structure has better stiffness in CaF2 crystal,and the hardness of thematerial has hardly changed in the second phase ***,the electronic structure of CaF2 is also analyzed withthe change of *** analyzing the band gap and density of states,the large band gap indicates the CaF2 crystal isalways an insulator at 0 GPa–150 GPa.

关键词： density functional theory(DFT) high-pressure phase transition coexistence

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Parallel knowledge acquisition algorithm for big data using MapReduce

Parallel knowledge acquisition algorithm for big data using ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin Qian Min Xia Ping Lv Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science & Technology Nanjing China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou China

ISBN: (纸本)9781467372220

With the rapid growth of data volume, knowledge acquisition for big data has become a new challenge. To address this issue, the hierarchical decision table is defined and implemented in this work. The properties of different hierarchical decision tables are discussed under the different granularity of conditional attributes. A novel knowledge acquisition algorithm for big data using MapReduce is proposed. Experimental results demonstrate that the proposed algorithm is able to deal with big data and mine hierarchical decision rules under the different granularity.

关键词： big data Hierarchical Rough Set Knowledge Acquisition MapReduce big data Information Extraction Decision tables

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An attribute reduction framework for inconsistent decision tables from view of the boundary region

An attribute reduction framework for inconsistent decision t...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin Qian Yu-Hui Chang Ping Lv Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science & Technology Nanjing China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou China

ISBN: (纸本)9781509003914

关键词： Cybernetics Acceleration Time complexity Rough sets Heuristic algorithms data mining Algorithm design and analysis

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Automatic salient object segmentation via shape prior based active contour model

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ICIC Express Letters, Part b: Applications 2016年第11期7卷 2491-2496页

作者： Gao, Shangbing Zhang, Youdong Zhou, Jun Zheng, Hao The Key Laboratory for Traffic and Transportation Security of Jiangsu Province Faculty of Computer and Software Engineering No. 1 Meicheng Rd. Huai’an223003 China Jiangsu Provincial Key Laboratory for Advanced Manufacturing Technology Huaiyin Institute of Technology No. 1 Meicheng Rd. Huai’an223003 China Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing Xiaozhuang University No. 3601 Hongjing Ave. Jiangning Dist. Nanjing211171 China

In this paper, we propose a novel model for unsupervised segmentation of viewer's attention object from natural images based on localizing region-based active con-tour (LRAC). Firstly, we proposed the saliency detection model via the multi-scale super-pixel. Then, object-level shape prior is extracted combining saliency with object boundary information. Finally, this contour is improved by the edge-preserving to generate the initial contour for our automatic object segmentation system. In contrast with localiz-ing region-based active contours that require considerable user interaction, the proposed method does not require it, i.e., the segmentation task is ful_lled in a fully automatic manner. Extensive experiments results on a large variety of natural images demonstrate that our algorithm consistently outperforms the popular existing salient object segmenta-tion methods, yielding higher precision and better recall rates. © 2016 ICIC International.

关键词： Image segmentation

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A Region Enhanced Discrete Multi-Objective Fireworks Algorithm for Low-Carbon Vehicle Routing Problem

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Complex System Modeling and Simulation 2022年第2期2卷 142-155页

作者： Xiaoning Shen Jiaqi Lu Xuan You Liyan Song Zhongpei Ge Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Big Data Analysis TechnologySchool of AutomationNanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Trustworthy Autonomous Systems and also with the Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent ComputationDepartment of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

A constrained multi-objective optimization model for the low-carbon vehicle routing problem(VRP)is established.A carbon emission measurement method considering various practical factors is *** minimizes both the total carbon emissions and the longest time consumed by the sub-tours,subject to the limited number of available *** to the characteristics of the model,a region enhanced discrete multi-objective fireworks algorithm is proposed.A partial mapping explosion operator,a hybrid mutation for adjusting the sub-tours,and an objective-driven extending search are designed,which aim to improve the convergence,diversity,and spread of the non-dominated solutions produced by the algorithm,*** low-carbon VRP instances with different scales are used to verify the effectiveness of the new ***,comparison results with four state-of-the-art algorithms indicate that the proposed algorithm has better performance of convergence and distribution on the low-carbon *** provides a promising scalability to the problem size.

关键词： vehicle routing problem carbon emission multi-objective optimization fireworks algorithm region enhanced

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