Showing 69 open source projects for "json-java"

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  • 1
    JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
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  • 2
    EyeMap - Eye Movement Data Analyzer
    EyeMap is a visualization and analysis tool for text reading eye movement data. It can process Unicode, proportion/non-proportion and spaced/unspaced reading materials, which supports various languages and experiment methods.
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  • 3
    China School bus

    China School bus

    China School Bus Data Analysis model

    International School Bus Operation Specification
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  • 4
    GRAIL Real Time Location Service (RTLS)
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  • 5
    Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
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  • 6
    DbViz produces plots of data contained in MySQL databases. Data can be viewed by looking at line graphs, xy scatter plots, and bar graphs. This greatly simplifies data analysis.
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  • 7
    A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.
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  • 8
    GmanDA is a GPL software for performing qualitative data analysis on mailing-lists and mboxes. It was developed to ease the work with large scale mailing-list archives taken from Gmane.org
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  • 9
    Java OpenCL Process Virtual Machine. Spring IoC based framework for complex data analysis with OpenCL computing.
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  • 10
    A mini data CUBE to do some embedded data analysis and mining.
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  • 11
    EDAS2 is a web-based environmental quality data management and decision support framework
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  • 12
    GSCope3 performs microarray data analysis to find correlations between BLSOM clusters and any form of omic knowledge expressed in OSML. Includes example metabolic pathway, gene ontology, genome position, transcription and PPI knowledge in OSML format.
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  • 13
    Open2Dprot is an open-source proteomics project for the development of bioinformatic tools for n-dimensional protein expression data analysis of quantified protein expression across multiple samples from research experiments.
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  • 14
    The Canopy project is an initiative to merge and expand the functionality of Perl-speaks-NONMEM (PsN), Census, Xpose and PopED. The goal is to produce a coherent, inclusive and convenient platform for pharmacometric data analysis.
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  • 15
    Microarray Data Analysis System, a Java application, provides an intuitive graphical scripting interface to design analysis protocols and perform normalization and filtering to microarray data by a variety of implemented statistical analysis modules.
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  • 16
    LMS Tools is a set of tools and libraries for administrators and users of learning management systems to perform, for example, portal integration, LMS management or usage data analysis.
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  • 17
    JNeuron is an analysis tool for multi-neuronal spike train analysis. The tool will allow scientists to organize their spike train data analysis into projects. The tool will implement standard spike train analysis algorithms and also datamining algorithms
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  • 18
    A framework for image analysis and data analysis, aimed towards microscopy and the needs of current research.
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  • 19
    BIRBU (BIological Relationship BUilder) is a Java tool for microarray gene expression data analysis. BIRBU identifies biologically significant relationship between genes using microarray data and prior knowledge on relationships between genes.
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