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Towards Mixed Societies of Chickens and Robots

Towards Mixed Societies of Chickens and Robots

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IEEE/RSJ International conference on Intelligent Robots and Systems

作者： Gribovskiy, Alexey Halloy, Jose Deneubourg, Jean-Louis Bleuler, Hannes Mondada, Francesco Ecole Polytech Fed Lausanne Sch Engn Robot Syst Lab 1 Lausanne Switzerland Univ Libre Bruxelles Unit Social Ecol Brussels Belgium

ISBN: (纸本)9781424466757

To design, to study, and to control mixed animals-robots societies is a challenging field of scientific exploration that can bring new frameworks to study individual and collective behaviors in animal and mixed robot-animal societies. In the Chicken Robot project we aim at developing a mobile robot, able to collaborate with a group of chicks and to control certain group behaviors. The first research step is to build formal models of relevant animal behaviors by performing ethological experiments. Hence, one of the principal tasks is to design a setup equipped with appropriate monitoring tools. In this paper, we present a toolset for running chick-robot experiments and analyzing results. It includes an autonomous PoulBot robot and an experimental setup, able to autonomously record experimental video and audio data, to detect displacements of chicks and robots, to detect their calling activity and to provide robots with these data. We also present a visual data analysis system to extract behavioral features of individual chicks using the variational Bayesian Gaussian mixture model classification with a particle filters based prediction of future positions of chicks. We show how these tools are currently used to carry out chick-robot experiments, to collect behavioral data and to extract animal behavioral features that allow us to build behavioral models bound to be implemented in the robot.

关键词： Bayes methods Gaussian processes animals-robots societies autonomous PoulBot robot behavioral feature extraction behavioural sciences chicken robot project mobile robot mobile robots particle filtering (numerical methods) particle filters based prediction scientific exploration variational Bayesian Gaussian mixture model classification visual data analysis system

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visually representing geo-temporal differences

Visually representing geo-temporal differences

引用

1st IEEE conference on visual Analytics Science and Technology, VAST 10

作者： Hoeber, Orland Wilson, Garnett Harding, Simon Enguehard, René Devillers, Rodolphe Department of Computer Science Memorial University Canada Department of Geography Memorial University Canada

ISBN: (纸本)9781424494866

data sets that contain geospatial and temporal elements can be challenging to analyze. In particular, it can be difficult to determine how the data have changed over spatial and temporal ranges. In this poster, we present a visual approach for representing the pair-wise differences between geographically and temporally binned data. In addition to providing a novel method for visualizing such geotemporal differences, GTdiff provides a high degree of interactivity that supports the exploration and analysis of the data. ©2010 IEEE.

关键词： data visualization

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visual exploration of Stream Pattern Changes Using a data-Driven Framework

Visual Exploration of Stream Pattern Changes Using a Data-Dr...

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6th International Symposium on visual Computing

作者： Xie, Zaixian Ward, Matthew O. Rundensteiner, Elke A. Worcester Polytech Inst Dept Comp Sci Worcester MA USA

ISBN: (纸本)9783642172731

When using visualization techniques to explore data streams, an important task is to convey pattern changes. Challenges include: (1) Most data analysis tasks require users to observe the pattern change over a long time range;(2) The change rate of patterns is not a constant, and most users are normally more interested in bigger changes than smaller ones. Although distorting the time axis as proposed in the literature can partially solve this problem, most of these are driven by the user. This is however not applicable to streaming data exploration tasks that normally require near real-time responsiveness. In this paper, we propose a data-driven framework to merge and thus condense time windows having small or no changes. Only significant changes are shown to users. Juxtaposed views are discussed for conveying data pattern changes. Our experiments show that our merge algorithm preserves more change information than uniform sampling. We also conducted a user study to confirm that our proposed techniques can help users find pattern changes more quickly than via a non-distorted time axis.

关键词： Conveying

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VAST 10 - IEEE conference on visual Analytics Science and Technology 2010, Proceedings

VAST 10 - IEEE Conference on Visual Analytics Science and Te...

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1st IEEE conference on visual Analytics Science and Technology, VAST 10

ISBN: (纸本)9781424494866

The proceedings contain 63 papers. The topics discussed include: DimStiller: workflows for dimensional analysis and reduction;visual exploration of classification models for risk assessment;improving the visual analysis of high-dimensional datasets using quality measures;iVisClassifier: an interactive visual analytics system for classification based on supervised dimension reduction;finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators;a visual analytics approach to model learning;multidimensional data dissection using attribute relationship graphs;two-stage framework for a topology-based projection and visualization of classified document collections;VizCept: Supporting synchronous collaboration for constructing visualizations in intelligence analysis;and diamonds in the rough: social media visual analytics for journalistic inquiry.

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Where would you go on your next vacation?a framework for visual exploration of attractive places

Where would you go on your next vacation?a framework for vis...

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2nd International conference on Advanced Geographic Information Systems, Applications and Services

作者： Kisilevich, Slava Mansmann, Florian Bak, Peter Keim, Daniel Tchaikin, Alexander Univ Konstanz Dept Comp Sci & Informat D-7750 Constance Germany

ISBN: (纸本)9780769539515

Tourists face a great challenge when they gather information about places they want to visit. Geographically tagged information in the form of Wikipedia pages, local tourist information pages, dedicated web sites and the massive amount of information provided by Google Earth is publicly available and commonly used. But the processing of this information involves a time consuming activity. Our goal is to make search for attractive places simpler for the common user and provide researchers with methods for exploration and analysis of attractive areas. We assume that an attractive place is characterized by large amounts of photos taken by many people. This paper presents a framework in which we demonstrate a systematic approach for visualization and exploration of attractive places as a zoomable information layer. The presented technique utilizes density-based clustering of image coordinates and smart color scaling to produce an interactive visualizations using Google Earth Mashup1. We show that our approach can be used as a basis for detailed analysis of attractive areas. In order to demonstrate our method, we use real-world geo-tagged photo data obtained from Flickr2 and Panoramio3 to construct interactive visualizations of virtually every region of interest in the world.

关键词： Density maps heat maps density-based clustering geovisualization

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Multidimensional data dissection using attribute relationship graphs

Multidimensional data dissection using attribute relationshi...

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1st IEEE conference on visual Analytics Science and Technology, VAST 10

作者： Weaver, Chris School of Computer Science and Center for Spatial Analysis University of Oklahoma United States

ISBN: (纸本)9781424494866

visual exploration and analysis is a process of discovering and dissecting the abundant and complex attribute relationships that pervade multidimensional data. Recent research has identified and characterized patterns of multiple coordinated views, such as cross-filtered views, in which rapid sequences of simple interactions can be used to express queries on subsets of attribute values. In visualizations designed around these patterns, for the most part, distinct views serve to visually isolate each attribute from the others. Although the brush-and-click simplicity of visual isolation facilitates discovery of many-to-many relationships between attributes, dissecting these relationships into more fine-grained one-to-many relationships is interactively tedious and, worse, visually fragmented over prolonged sequences of queries. This paper describes: (1) a method for interactively dissecting multidimensional data by iteratively slicing and manipulating a multigraph representation of data values and value co-occurrences;and (2) design strategies for extending the construction of coordinated multiple view interfaces for dissection as well as discovery of attribute relationships in multidimensional data sets. Using examples from different domains, we describe how attribute relationship graphs can be combined with cross-filtered views, modularized for reuse across designs, and integrated into broader visual analysis tools. The exploratory and analytic utility of these examples suggests that an attribute relationship graph would be a useful addition to a wide variety of visual analysis tools. ©2010 IEEE.

关键词： Information systems

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Value-of-Information based Middleware for Autonomic Querying of Distributed Sensor databases

Value-of-Information based Middleware for Autonomic Querying...

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conference on Cyber Security, Situation Management, and Impact Assessment ii;and visual Analytics for Homeland Defense and Security ii

作者： Sukumar, Sreenivas R. Shankar, Mallikarjun Oak Ridge Natl Lab Oak Ridge TN 37830 USA

ISBN: (纸本)9780819481733

With particular focus on distributed situational awareness in defense and security applications, we propose a value-of-information based middleware framework as a paradigm shift from crawl-index based centralized search. The proposed approach seeks to improve efficiency in search and retrieval by transforming sensors into programmable information points and enabling ubiquitous data and software flows through the infrastructure of the distributed network. We explain the different components of such a middleware framework to organize, tag and notify emerging spatial, temporal and causal patterns from the sensor measurements. We conclude the paper with a brief discussion on the top-down programming model that can realize the framework as a reconfigurable sensor query system.

关键词： sensor query systems search and retrieval distributed querying distributed data analysis

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Poster: Translating cross-filtered queries into questions

Poster: Translating cross-filtered queries into questions

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1st IEEE conference on visual Analytics Science and Technology, VAST 10

作者： Nafari, Maryam Weaver, Chris School of Computer Science Center for Spatial Analysis University of Oklahoma United States

ISBN: (纸本)9781424494866

Complex combinations of coordinated multiple views are increasingly used to design tools for highly interactive visual exploration and analysis of multidimensional data. While complex coordination patterns provide substantial utility through expressive querying, they also exhibit usability problems for users when learning required interaction sequences, recalling past queries, and interpreting visual states. As visual analysis tools grow more sophisticated, there is a growing need to make them more understandable as well. Our long-term goal is to exploit natural language familiarity and literacy to directly facilitate individual and collaborative use of visual analysis tools. In this poster, we present work in progress on an automatically generated query-to-question user interface to translate interactive states during visual analysis into an accompanying visual log of formatted text. Our effort currently focuses on a symmetric and thus relatively simple coordination pattern: cross-filtered views. We describe our current thinking about query-to-question translation in a typical cross-filtered visualization of movies, people, and genres in the Internet Movie database. ©2010 IEEE.

关键词： Coordination reactions

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SyncPro : A Synchronized visualization Tool for Differential analysis of Proteomics data Sets

SyncPro : A Synchronized Visualization Tool for Differential...

引用

IEEE International conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Yung, Ling Sing Yang, Chao Dakna, Mohammed Mischak, Harald Yu, Weichuan Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China Mosa Diagnost & Therapeut Hannover Germany

ISBN: (纸本)9781424483044

In the comparative proteomics studies, visualization has become an emerging technique in the analysis. It provides an intuitive overview of large-scale mass spectrometry data sets with possibilities to further explore data details at different levels. While different visualization tools have already been developed, they are often designed to handle one or a few mass spectrometry data sets. Apparently, this is not enough as many proteomics studies involve many samples. It is much desired to simultaneously visualize all data sets in order to better examine data sets. In this paper, we present a visualization tool named SyncPro for differential analysis of multiple pre-processed proteomics data sets. It offers features to (i) compare many dIlta sets simultaneously;(ii) facilitate data exploration through selection and extraction;(iii) quickly judge the quality of selected features. Our proposed method further enhances the functions of existing visualization tools.

关键词： visualization Proteomics Mass Spectrometry

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Interactive exploration of hierarchical density clusters in gene expression data

Interactive exploration of hierarchical density clusters in ...

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2nd International conference on Knowledge and Systems Engineering, KSE 2010

作者： Van Long, Tran Linsen, Lars University of Transport and Communications Hanoi Viet Nam Jacobs University Bremen Bremen Germany

ISBN: (纸本)9780769542133

Clustering gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we present an effective clustering algorithm for gene expression data. The clustering algorithm is based on the analysis of data's density distribution. We propose an intersecting partition of gene expression data into the supports of data points. Density clusters are maximally connected regions at certain density levels, and thus, can be organized in a hierarchical structure. For interactive visual exploration, we use a 2D radial layout of the hierarchical density cluster tree with linked as well as embedded views of parallel coordinates and heatmaps. Our system supports the understanding of the distribution of density clusters and the patterns of the density clusters. Experimental results for common gene expression data sets shows the effectiveness and scalability of the algorithm. © 2010 IEEE.

关键词： Clustering algorithms

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