共查询到20条相似文献,搜索用时 15 毫秒
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Elena Zudilova-Seinstra Ning Yang Lilit Axner Adianto Wibisono Dmitry Vasunin 《Service Oriented Computing and Applications》2008,2(4):187-201
With the era of Grid computing, data driven experiments and simulations have become very advanced and complicated. To allow specialists from various domains to deal with large datasets, aside from developing efficient extraction techniques, it is necessary to have available computational facilities to visualize and interact with the results of an extraction process. Having this in mind, we developed an Interactive Visualization Framework, which supports a service-oriented architecture. This framework allows, on one hand visualization experts to construct visualizations to view and interact with large datasets, and on the other hand end-users (e.g., medical specialists) to explore these visualizations irrespective of their geographical location and available computing resources. The image-based analysis of vascular disorders served as a case study for this project. The paper presents main research findings and reports on the current implementation status. 相似文献
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The emergent behavior of complex systems, which arises from the interaction of multiple entities, can be difficult to validate, especially when the number of entities or their relationships grows. This validation requires understanding of what happens inside the system. In the case of multi-agent systems, which are complex systems as well, this understanding requires analyzing and interpreting execution traces containing agent specific information, deducing how the entities relate to each other, guessing which acquaintances are being built, and how the total amount of data can be interpreted. The paper introduces some techniques which have been applied in developments made with an agent oriented methodology, INGENIAS, which provides a framework for modeling complex agent oriented systems. These techniques can be regarded as intelligent data analysis techniques, all of which are oriented towards providing simplified representations of the system. These techniques range from raw data visualization to clustering and extraction of association rules. 相似文献
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提出了一种新型的人工免疫网络模型TSIN。通过应用包括克隆选择、基于合作的变异以及抗体抑制在内的免疫算子,抗体种群从单一的个体逐步分化繁殖成为有效的聚类。这些聚类既能够准确地表示原始数据集在形态空间中的分布特性,又能够较好地拟合局部分布形态,这些都为高维数据的分析提供了良好的基础。描述了TSIN学习算法的总体框架,详细分析了其中的关键环节。仿真实验表明,TSIN具有良好的数据分析能力,且较传统的自组织神经网络方法更能体现数据中蕴含的拓扑关系和分布特性。 相似文献
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Lu Jiaju 《International journal of remote sensing》2013,34(12):1895-1907
Abstract A method of extracting different crop information more effectively, by applying principal component analysis to a three-dimensional three-date Landsat TM data space, has been developed. Landsat TM data obtained on 7 June, 9 July and 26 August 1984 were used to examine the approach, and the results fully demonstrated its advantages over other methods of keeping classification accuracy without any calibrations for multitemporal Landsat data. 相似文献
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Monotone data flow analysis frameworks 总被引:1,自引:0,他引:1
Summary We consider a generalization of Kildall's lattice theoretic approach to data flow analysis, which we call monotone data flow analysis frameworks. Many flow analysis problems which appear in practice meet the monotonicity condition but not Kildall's condition called distributivity. We show that the maximal fixed point solution exists for every instance of every monotone framework, and that it can be obtained by Kildall's algorithm. However, whenever the framework is monotone but not distributive, there are instances in which the desired solution—the meet over all paths solution — differs from the maximal fixed point. Finally, we show the nonexistence of an algorithm to compute the meet over all paths solution for monotone frameworks.Work supported by NSF grant GJ-1052. 相似文献
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This paper proposes a new hierarchical clustering method using genetic algorithms for the analysis of gene expression data. This method is based on the mathematical proof of several results, showing its effectiveness with regard to other clustering methods. Genetic algorithms applied to cluster analysis have disclosed good results on biological data and many studies have been carried out in this sense, although most of them are focused on partitional clustering methods. Even though there are few studies that attempt to use genetic algorithms for building hierarchical clustering, they do not include constraints that allow us to reduce the complexity of the problem. Therefore, these studies become intractable problems for large data sets. On the other hand, the deterministic hierarchical clustering methods generally face the problem of convergence towards local optimums due to their greedy strategy. The method introduced here is an alternative to solve some of the problems existing methods face. The results of the experiments have shown that our approach can be very effective in cluster analysis of DNA microarray data. 相似文献
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LUDOVIC ANDRES WILLIAM A. SALAS DAVID SKOLE 《International journal of remote sensing》2013,34(5):1115-1121
A signal processing technique is presented and applied to annual patterns of the Global Vegetation Index (GVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) to examine the frequency distribution of the multi-temporal signal. It is shown that frequencies of the signal are linked to integrated GVI, seasonal variability and subseasonal variability of the land cover type. These characteristics are used to derive a land cover classification. 相似文献
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Eufrásio de A. Lima Neto Francisco de A. T. de Carvalho 《Pattern Analysis & Applications》2017,20(3):809-824
This paper introduces a nonlinear regression model to interval-valued data. The method extends the classical nonlinear regression model in order to manage interval-valued datasets. The parameter estimates of the nonlinear model considers some optimization algorithms aiming to identify which one presents the best accuracy and precision in the prediction task. A detailed prediction performance study comparing the proposed nonlinear method and other linear regression methods for interval variables is presented based on K-fold cross-validation scheme with synthetic interval-valued datasets generated on a Monte Carlo framework. Moreover, two suitable real interval-valued datasets are considered to illustrate the usefulness and the performance of the approaches presented in this paper. The results suggested that the use of the nonlinear method is suitable for real datasets, as well as in the Monte Carlo simulation study. 相似文献
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de Leeuw W Verschure PJ van Liere R 《IEEE transactions on visualization and computer graphics》2006,12(5):1251-1258
In this paper we propose an approach in which interactive visualization and analysis are combined with batch tools for the processing of large data collections. Large and heterogeneous data collections are difficult to analyze and pose specific problems to interactive visualization. Application of the traditional interactive processing and visualization approaches as well as batch processing encounter considerable drawbacks for such large and heterogeneous data collections due to the amount and type of data. Computing resources are not sufficient for interactive exploration of the data and automated analysis has the disadvantage that the user has only limited control and feedback on the analysis process. In our approach, an analysis procedure with features and attributes of interest for the analysis is defined interactively. This procedure is used for off-line processing of large collections of data sets. The results of the batch process along with "visual summaries" are used for further analysis. Visualization is not only used for the presentation of the result, but also as a tool to monitor the validity and quality of the operations performed during the batch process. Operations such as feature extraction and attribute calculation of the collected data sets are validated by visual inspection. This approach is illustrated by an extensive case study, in which a collection of confocal microscopy data sets is analyzed. 相似文献
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二进制程序数据流静态分析首先将被分析的程序转换成数据流描述标记,确定每个基本块的输入、输出定值集合,结合程序控制流图,建立模块内数据流方程组,通过迭代的方法解数据流方程并推导出函数输入与输出之间的联系,实现函数功能的静态理解。经过实验表明,在不需要额外提示的情况下,能够准确识别二进制形式的字符串拷贝函数。 相似文献
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Mathematical programming is used to dovelop a method for load flow analysis for large power systems such that the computation time is independent of the number of loops. Computational times are shown to compare favourably with existing methods. 相似文献
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Data reconciliation consists in modifying noisy or unreliable data in order to make them consistent with a mathematical model (herein a material flow network). The conventional approach relies on least-squares minimization. Here, we use a fuzzy set-based approach, replacing Gaussian likelihood functions by fuzzy intervals, and a leximin criterion. We show that the setting of fuzzy sets provides a generalized approach to the choice of estimated values, that is more flexible and less dependent on oftentimes debatable probabilistic justifications. It potentially encompasses interval-based formulations and the least squares method, by choosing appropriate membership functions and aggregation operations. This paper also lays bare the fact that data reconciliation under the fuzzy set approach is viewed as an information fusion problem, as opposed to the statistical tradition which solves an estimation problem. 相似文献
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Flemming Nielson 《Acta Informatica》1982,18(3):265-287
Summary It is shown how to express data flow analysis in a denotational framework by means of abstract interpretation. A continuation style formulation naturally leads to the MOP (Meet Over all Paths) solution, whereas a direct style formulation leads to the MFP (Maximal Fixed Point) solution. 相似文献
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《IEEE transactions on pattern analysis and machine intelligence》1990,16(2):129-140
Incremental data flow analysis algorithms have been designed to deal efficiently with change in evolving software systems. These algorithms document the current state of a software system by incorporating change effects into previously derived information describing the definition and use of data in the system. Unfortunately, the performance of these algorithms cannot, in general, be characterized by analytic predictions of their expected behavior. It is possible, however, to observe their performance empirically and predict their average behavior. The authors report on experiments on the empirical profiling of a general-purpose, incremental data flow analysis algorithm. The algorithm, dominator based and coded in C, was applied to statistically significant numbers of feasible, random software systems of moderate size. The experimental results, with quantifiable confidence limits, substantiate the claim that incremental analyses are viable and grow more valuable as a software system grows in size 相似文献
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《Information and Software Technology》2000,42(11):765-775
A large portion of high-level computer programs consists of data declaration. Thus, an increased focus on testing the data flow aspects of programs should be considered. In this paper, we consider testing the data flow in Java programs dynamically. Data flow analysis has been applied for testing procedural and some object-oriented programs. We have extended the dynamic data flow analysis technique to test Java programs and show how it can be applied to detect data flow anomalies. 相似文献
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We present an effective approach to performing data flow analysis in parallel and identify three types of parallelism inherent in this solution process: independent-problem parallelism, separate-unit parallelism and algorithmic parallelism. We present our investigations of Fortran procedures from thePerfect Benchmarks andnetlib libraries, which reveal structural characteristics of program flow graphs that are amenable to algorithmic parallelism. Previously, the utility of algorithmic parallelism had been explored using our parallel hybrid algorithm in the context of solving the Reaching Definitions problem for Fortran procedures. Here we present new refinements that optimize performance by increasing the grain size of the parallelism, to improve communication on distributed-memory machines. The empirical performance of our optimized and unoptimized hybrid algorithms for Reaching Definitions are compared on this large data set using an iPSC/2. Our empirical findings qualitatively validate the usefulness of algorithmic parallelism.This research was supported, in part, by National Science Foundation grants CCR-8920078 and CCR-9023628-1, 2/5. An earlier version of this paper appears inProceedings of the 6th ACM International Conference on Supecomputing (Washington, D.C., July 1992), pp. 236–247. 相似文献
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针对在数据量动态增加的场景下现有的排序算法管理数据导致算法性能大大降低的问题,提出一种16-bit Trie树排序算法.借助邻居节点上存储的链节点指针完成排序,它不仅可以边构建边排序,且引入动态数组可以提高该算法的空间效率.仿真结果表明,传统Trie树支持数据动态更新,但通过遍历Trie树的方式完成排序耗时较多,快速排... 相似文献