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Data-intensive spatial filtering in large numerical simulation datasets 12

Data-intensive spatial filtering in large numerical simulati...

引用

Supercomputing Conference

作者： Kalin Kanov Randal Burns Greg Eyink Charles Meneveau Alexander Szalay Department of Computer Science Johns Hopkins University USA Department of Applied Math and Statistics Johns Hopkins University USA Department of Mechanical Engineering Johns Hopkins University USA Department of Physics and Astronomy Johns Hopkins University USA

ISBN: (纸本)9781467308045

We present a query processing framework for the efficient evaluation of spatial filters on large numerical simulation datasets stored in a data-intensive cluster. Previously, filtering of large numerical simulations stored in scientific databases has been impractical owing to the immense data requirements. Rather, filtering is done during simulation or by loading snapshots into the aggregate memory of an HPC cluster. Our system performs filtering within the database and supports large filter widths. We present two complementary methods of execution: I/O streaming computes a batch filter query in a single sequential pass using incremental evaluation of decomposable kernels, summed volumes generates an intermediate data set and evaluates each filtered value by accessing only eight points in this dataset. We dynamically choose between these methods depending upon workload characteristics. The system allows us to perform filters against large data sets with little overhead: query performance scales with the cluster's aggregate I/O throughput.

关键词： Kernel Computational modeling mathematical model Numerical simulation Spatial databases Numerical models

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Semi-supervised Graph Embedding-based Feature Extraction and Adaptive Kernel-based Classification for computer-aided Detection in CT Colonography

Semi-supervised Graph Embedding-based Feature Extraction and...

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IEEE Nuclear Science Symposium and Medical Imaging Conference

作者： Lei Fan Bowen Song Xianfeng Gu Zhengrong Liang Departments of Radiology and Computer Science Stony Brook University Stony Brook NY USA Departments of Radiology and Applied Math and Statistics Stony Brook University Stony Brook NY USA Department of Computer Science Stony Brook University Stony Brook NY USA Departments of Radiology Computer Science and Biomedical Engineering Stony Brook University Stony Brook NY USA

Feature extraction and classification are two important parts in computer-aided detection (CAD) of abnormalities. For feature selection, typically we are interested in determining which, of a large number of potentially redundant or noisy features, are most discriminative for classification. Graph embedding is a relatively new category of feature selection methods. It uses a graph structure to model the geometric and discriminant structure of the data manifold. It has obvious advantages over other conventional feature selection methods like Principal Component Analysis (PCA). However, it does not properly incorporate prior labeling information like Partial Least Square (PLS) does. In this paper, we deal with feature selection for CAD of colonic polyps with graph embedding method in a semi-supervised style (SemiGE), which considers the label information as additional constraints. Specifically, we constrain the space of solutions that we explore only to contain embedding results which are consistent with the labels. Experiments were conducted on patients' datasets to compare its performance with other conventional and popular feature selection methods. The results illustrated that this presented SemiGE strategy outperforms all other exciting feature selection methods, such as PCA, PLS, etc. On the other hand, the well-known support vector machine (SVM) classifier has been widely used in CAD of colonic polyps in computed tomography conlonography (CTC). Several kernel functions have been implemented for the SVM classifier. Each kernel function affects noticeably to the classifying performance and variable performance has been observed among the kernel functions. A traditional implementation strategy and all the previous applications of SVM only preselect a kernel function (e.g., RBF, Sigmoid, .etc). This kind of pre-selection approach fails to provide a kernel function which is adaptive to the experimental data. In this paper, we introduce an improved SVM-based classifi

关键词： CAD ROC AUC

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Analyzing environmental samples in nuclear safeguards evaluation by a cumulative belief degrees approach 9

Analyzing environmental samples in nuclear safeguards evalua...

引用

Computational Intelligence Foundations and Applications - 9th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2010

作者： Kabak, Özgür Ruan, Da Boeretang 200 Mol2400 Belgium Department of Industrial Engineering Istanbul Technical University Maçka Istanbul34357 Turkey Department of Applied Math. and Computer Science Ghent University Gent9000 Belgium

ISBN: (纸本)9814324698

In this study we apply a cumulative belief degrees approach to an environmental sampling example in nuclear safeguards evaluation. Transformation formulas for each indicator are defined for distinguishing anthropogenic natural uranium from mineral uranium. An order weighted averaging operator-based aggregation method is proposed to make a final decision. The methodology is illustrated by a numerical example. © 2010 by World Scientific Publishing Co. Pte. Ltd.

关键词： Fuzzy logic

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New construction of ensemble classifiers for imbalanced datasets

New construction of ensemble classifiers for imbalanced data...

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2010 IEEE International Conference on Intelligent Systems and Knowledge engineering, ISKE 2010

作者： Zhai, Yun Yang, Bingru Ma, Nan Ruan, Da School of Information Engineering University of Science and Technology Beijing Beijing China College of Computer Science Liaocheng University Liaocheng China College of Information Beijing Union University Beijing China Department of Applied Math and Computer Science Ghent University Krijgslaan Belgium

ISBN: (纸本)9781424467907

Learning in the presence of data imbalances presents a great challenge to machine learning. Imbalanced data sets represent a significant problem because the corresponding classifier has a tendency to ignore samples which have smaller representation in the training sets. In this paper, we propose an ensemble-based learning algorithm as a new ensemble classifier model called as SVM-C5.0 Ensemble Classifier Model, SCECM. SCECM adopts a differentiated sampling rate algorithm (DSRA) based on an improved Adaboost algorithm and further employs unique classifier-selection strategy, novel classifier integration approach and original classification decision-making method. Comparative experimental results show that the proposed approach improves performance for the minority class while preserving the ability to recognize examples from the majority classes. © 2010 IEEE.

关键词： Data mining

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New Construction of Ensemble Classifiers for Imbalanced Datasets

New Construction of Ensemble Classifiers for Imbalanced Data...

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The 2010 International Conference on Intelligent Systems and Knowledge engineering(第五届智能系统与知识工程国际会议)

作者： Yun Zhai Bingru Yang Nan Ma Da Ruan School of Information Engineering University of Science and Technology Beijing Beijing China Colle School of Information Engineering University of Science and Technology Beijing Beijing China School of Information Engineering University of Science and Technology Beijing Beijing China Colleg Department of Applied Math and Computer Science Ghent University Krijgslaan Belgium

关键词： Classification algorithms Accuracy Support vector machines Training Data mining Educational institutions Machine learning

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Multi-manifold semi-supervised learning

Multi-manifold semi-supervised learning

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12th International Conference on Artificial Intelligence and Statistics, AISTATS 2009

作者： Goldberg, Andrew B. Zhu, Xiaojin Singh, Aarti Xu, Zhiting Nowak, Robert Computer Sciences Dept. University of Wisconsin-Madison Madison WI 53706 United States Department of Applied and Computational Math Princeton University Princeton NJ 08544 United States Department of Elec. and Computer Engineering University of Wisconsin-Madison Madison WI 53706 United States

We study semi-supervised learning when the data consists of multiple intersecting manifolds. We give a finite sample analysis to quantify the potential gain of using unlabeled data in this multi-manifold setting. We then propose a semi-supervised learning algorithm that separates different manifolds into decision sets, and performs supervised learning within each set. Our algorithm involves a novel application of Hellinger distance and size-constrained spectral clustering. Experiments demonstrate the benefit of our multimanifold semi-supervised learning approach. © 2009 by the authors.

关键词： Learning algorithms

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Belief rule-based inference methodology to improve nuclear safeguards information evaluation

Belief rule-based inference methodology to improve nuclear s...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Da Ruan Roland Carchon Klaas van der Meer Jun Liu Hui Wang Luis Martinez Department of Applied Math. and Computer Science Ghent University Ghent Belgium Belgian Nuclear Research Center SCK CEN Ghent Belgium Belgian Nuclear Research Center SCK CEN School of Computing and Math. University of Ulster UK Department of Computer Science and Engineering Faculty of Electrical Engineering University of Jaen Jaen Spain

A framework for modeling, analyzing and synthesizing nuclear safeguards information with various uncertainties is proposed by using a newly developed belief rule-base inference methodology (RIMER). After a hierarchical analysis of States' nuclear activities on the basis of the International Atomic Energy Agency (IAEA) physical model, the multi-layer structure of the evaluation model for States' nuclear activities is outlined. The special emphasis is given to the synthesis and evaluation analysis of the physical model indicator information by RIMER, which handles hybrid uncertain information in nuclear safeguards evaluation process. The proposed framework illustrates and clarifies the inference and synthesis formalism from a case study of nuclear safeguards information evaluation.

关键词： Information analysis Erbium computer science Uncertainty Fuzzy logic Nuclear fuels Protocols Information processing Decision making Production systems

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Distributed discrete-time consensus with a time-varying reference state

Distributed discrete-time consensus with a time-varying refe...

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作者： Cao, Yongcan Rent, Wei Li, Yan Department of Electrical and Computer Engineering Utah State University Logan UT 84322 United States Institute of Applied Math School of Math and System Sciences Shandong University Jinan China Department of Electrical and Computer Engineering Utah State University United States

ISBN: (纸本)9781563479458

This paper studies a PD-like discrete-time consensus algorithm with a time-varying reference state that is available to only a subset of the team members. We study the condition on the communication graph, the sampling period, and the control gain to ensure stability and give the quantitative bound of the tracking error. It is shown that the bound of the tracking error is proportional to the sampling period. The benefit of the proposed PD-like discrete-time consensus algorithm is also demonstrated through comparison with an existing P-like discrete-time consensus algorithm. Finally, simulation results are presented as a proof of concept. © 2008 by Yongcan Cao, Wei Ren, and Yan Li.

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Fractional order linear quadratic regulator

Fractional order linear quadratic regulator

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2008 IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications, MESA 2008

作者： Yan, Li YangQuan, Chen Institute of Applied Math School of Mathematics and System Sciences Shandong University Jinan 250100 China Electrical and Computer Engineering Department Utah State University Loaan UT 84322-4120 United States

ISBN: (纸本)9781424423682

In this paper, we formulate the fractional linear quadratic regulator (LQR) problem. The analytical solution of fractional optimal control near the origin and infinity are derived. It is shown that the optimal control to the linear fractional system can be computed through the corresponding fractional Euler-Lagrange equations. Moreover, the analytical analysis of right-sided fractional equation is discussed, which relates to the construction and solution of fractional LQR problems. The matrix Mittag-Leffler function is used here to serve as the fundamental solution of high-dimension linear fractional equations. More detailed discussions about fractional systems and right-sided fractional operators are provided and summarized. Finally, two illustrated simulation results are provided as a proof of concept. © 2008 IEEE.

关键词： Matrix algebra

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Experimental Studies of a Fractional Order Universal Adaptive Stabilizer

Experimental Studies of a Fractional Order Universal Adaptiv...

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IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications, MESA

作者： Shayok Mukhopadhyay Yan Li YangQuan Chen Electrical and Computer Engineering Department Utah State University Logan UT USA Institute of Applied Math School of Mathematics and System Sciences Shandong University Jinan China

This work performs experimental verification of the asymptotic stability of two different types of fractional scalar systems by using universal adaptive stabilization as in. The types of systems verified experimentally are: (I) Fractional dynamics with integer order control strategy (II) Fractional dynamics with fractional order control strategy. The Mittag-Leffler function E alpha (-lambdat alpha ), forallalphaisin (2, 3] and lambda > 0 is used as a Nussbaum function as per [1]. Extensive hardware in the loop simulation of the mathematically developed results have been included in the paper. The results of the experiment serve not only to improve the understanding of fractional order universal adaptive stabilization but also proves that the methodology works well on real world systems.

关键词： Control systems Fractional calculus Adaptive control Hardware Asymptotic stability Programmable control mathematics Analytical models Laboratories Testing

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