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12th Annual conference on Towards Autonomous Robotic Systems, TAROS 2011

ISBN: (纸本)9783642232312

The proceedings contain 62 papers. The special focus in this conference is on Towards Autonomous Robotic Systems. The topics include: Deformation-Based Tactile Feedback Using a Biologically-Inspired Sensor and a Modified Display;design and Control of an Upper Limb Exoskeleton Robot RehabRoby;distributed Motion Planning for Ground Objects Using a Network of Robotic Ceiling Cameras;evaluating the Effect of Robot Group Size on Relative Localisation Precision;instance-Based Reinforcement Learning Technique with a Meta-learning Mechanism for Robust Multi-Robot Systems;locomotion Selection and Mechanical Design for a Mobile Intra-abdominal Adhesion-Reliant Robot for Minimally Invasive Surgery;mapping with Sparse Local Sensors and Strong Hierarchical Priors;multi-rate visual Servoing Based on Dual-Rate High Order Holds;optimal Path Planning for Nonholonomic Robotic Systems via Parametric Optimisation;A General Classifier of Whisker data Using Stationary Naive Bayes: Application to BIOTACT Robots;probabilistic Logic Reasoning about Traffic Scenes;real-World Reinforcement Learning for Autonomous Humanoid Robot Charging in a Home Environment;robot Routing Approaches for Convoy Merging Maneuvers;sensing with Artificial Tactile Sensors: An Investigation of Spatio-temporal Inference;short-Range Radar Perception in Outdoor Environments;smooth Kinematic Controller vs. Pure-Pursuit for Non-holonomic Vehicles;supervised Traversability Learning for Robot Navigation;Task Space Integral Sliding Mode Controller Implementation for 4DOF of a Humanoid BERT ii Arm with Posture Control;Towards Autonomous Energy-Wise RObjects;towards Safe Human-Robot Interaction;a Navigation System for a High-Speed Professional Cleaning Robot;towards Temporal Verification of Emergent Behaviours in Swarm Robotic Systems;walking Rover Trafficability - Presenting a Comprehensive analysis and Prediction Tool;coordination in Multi-tiered Robotic Search.

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Volume visualization and exploration Based on Semi-automatic Multidimensional Transfer Function Design

Volume Visualization and Exploration Based on Semi-automatic...

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International conference on Knowledge and Systems Engineering (KSE)

作者： Tran Van Long University of Transport and Communications Hanoi Vietnam

exploration and analysis of scalar and multivariate volume data play an important role in different domains from physical simulations to medical treatments. In visual analytics of volumetric data sets we need to define a multidimenional transfer functions. This is a challenging task because of the difficulty in understanding multiple attribute spaces and displaying in physical three dimension space. Frequently, the transfer function is designed based on mapping one or two dimensional space to color properties (RGB) and opacity (A). We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy. We also provide a clustering method that operates on density rather than individual records. We compute density in the given multidimensional multivariate space. Clusters are formed by areas of high density. We present an approach that automatically computes a hierarchical tree of high density clusters. To visually represent the cluster hierarchy, we present a 2D radial layout that supports an intuitive understanding of the distribution structure of the multidimensional multivariate data set. We apply a semi-automatic coloring scheme based on the 2D radial layout of the hierarchical cluster tree encoding hue, saturation, and value of the HSV color space. The system support an easily method to define the multidimensional transfer function over entire multidimensional attributes space. Finally, the surface extract by applying marching cube methods.

关键词： Transfer functions data visualization Clustering algorithms Rendering (computer graphics) Image color analysis Partitioning algorithms Density functional theory

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G-PARE: A visual analytic tool for comparative analysis of uncertain graphs

G-PARE: A visual analytic tool for comparative analysis of u...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Hossam Sharara Awalin Sopan Galileo Namata Lise Getoor Lisa Singh Computer Science Department University of Maryland College Park USA Computer Science Department George town University Washington DC DC USA

There are a growing number of machine learning algorithms which operate on graphs. Example applications for these algorithms include predicting which customers will recommend products to their friends in a viral marketing campaign using a customer network, predicting the topics of publications in a citation network, or predicting the political affiliations of people in a social network. It is important for an analyst to have tools to help compare the output of these machine learning algorithms. In this work, we present G-PARE, a visual analytic tool for comparing two uncertain graphs, where each uncertain graph is produced by a machine learning algorithm which outputs probabilities over node labels. G-PARE provides several different views which allow users to obtain a global overview of the algorithms output, as well as focused views that show subsets of nodes of interest. By providing an adaptive exploration environment, G-PARE guides the users to places in the graph where two algorithms predictions agree and places where they disagree. This enables the user to follow cascades of misclassifications by comparing the algorithms outcome with the ground truth. After describing the features of G-PARE, we illustrate its utility through several use cases based on networks from different domains.

关键词： Predictive models data visualization Uncertainty Machine learning algorithms Prediction algorithms data models visualization

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Ragu: A Free Tool for the analysis of EEG and MEG Event-Related Scalp Field data Using Global Randomization Statistics

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2011年第unknown期2011卷 938925-938925页

作者： Koenig, Thomas Kottlow, Mara Stein, Maria Melie-Garcia, Lester Univ Bern Univ Hosp Psychiat Bern Dept Psychiat Neurophysiol CH-3000 Bern 60 Switzerland Cuban Neurosci Ctr Neuroinformat Dept Havana 15202 Cuba

We present a program (Ragu;Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type ii errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

关键词： DIAGNOSTIC imaging software RANDOMIZATION (Statistics) ELECTROENCEPHALOGRAPHY MAGNETOENCEPHALOGRAPHY GRAPHICAL user interfaces (Computer systems) DIAGNOSTIC imaging equipment SCALP

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Organic facies variation from well data on the coaly pliocene units, the central part of Turkey (Karapinar-Konya)

Organic facies variation from well data on the coaly pliocen...

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11th International Multidisciplinary Scientific Geoconference and EXPO, SGEM 2011

作者： Özçelik, Orhan Tüze, Zeynep Altunsoy, Mehmet Hökerek, Selin Erik, Nazan Yalçin Taka, Mehmet Acar, Ferhat Department of Geological Engineering Akdeniz University Turkey Institute of Science Akdeniz University Turkey Department of Geological Engineering Cumhuriyet University Turkey General Directorate of Mineral Research and Exploration Turkey Metropolitan Municipality Turkey

Some 100 core samples of coal and coaly units from the Pliocene succession (Hotami{dotless}ş Formation) were collected from well KK-147, in the southern part of Central Turkey (Karapi{dotless}nar-Konya). 30 samples were screened for total organic carbon (TOC) content. Selected samples were then analyzed by Rock-Eval Pyrolysis. visual kerogen analysis and vitrinite reflectance measurements were also undertaken. Detailed data from thick Pliocene sediments made it possible to construct an organic facies framework using different zonations. Organic facies type C, CD and D were identified in the investigated units. The main composition in the organic matter of the sediments are woody (80%), with minor portions of planty (8%), amorphous (6%) and coaly (6%) in the investigation well. Alteration colors of these materials are yellow and dark yellow. Spore colors of these samples are yellow and dark yellow (SCI: 3-4). Organic facies C is related to clayeysandy coal and coal lithofacies. This facies is composed of organic matter with average values of HI around 144 (equivalent to Type ii/iiI Kerogene), TOC around 15.94 and S2 between 11.98 and 30.10 mg HC/g sample. Organic facies C is the "gas-prone" facies. The organic matter is dominated by terrestrial debris in various stages of oxidization. Sediments of organic facies C were commonly deposited on Tertiary and Mesozoic shelves and slopes of the continantel margins. Most coals are organic facies C. The organic faces CD is related to the clayey coal, coal and claystone lithofacies. This facies is characterized by average values of HI around 89 (equivalent to Type iiI Kerogene), TOC around 15.7%, and an average of S2 of 15.18 mg HC/g of rock. The CD facies reflects a mixture of source materials including terrestrial plant detrius, reworked and fine grained amophous organic matter. An organic facies D, associated with the coal, claystone, clayey limestone lithofacies, displays values of HI around 26 (equivalent to Type iiI Kero

关键词： Coal

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Layered TimeRadarTrees

Layered TimeRadarTrees

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International conference on Information visualisation (IV)

作者： Michael Burch Markus Hoferlin Daniel Weiskopf Visualization Research Center University of Stuttgart Germany

We introduce a novel technique for visualizing dense time-varying directed and weighted multi-graphs with an additional hierarchical organization of the graph nodes. Combining Indented Tree Plots and TimeRadarTrees, we show the temporal evolution of relations in a static view. The graph edges are layered around thumbnail wheels consisting of color-coded sectors that are representatives of the graph nodes. These sectors generate implicit representations of graph edges. Start and target vertices are perceived by inspecting the color coding of sectors in the context of other sectors and their orientations. The technique puts emphasis on newer relations and hence, these are mapped to a larger display space in the radial diagram. The benefit of our technique is reduction of visual clutter from which node-link diagrams typically suffer. The visualization focuses on an easy exploration of trends, countertrends, periodicity, temporal shifts, and anomalies in time-varying relational data. We demonstrate the usefulness of the approach by applying it to dense dynamic graph data acquired from a soccer match of the 2D Soccer Simulation League.

关键词： Encoding visualization data visualization Image color analysis Animation Layout Organizations

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Projection-Based Image Retrieval Using Class-Specific Metrics

Projection-Based Image Retrieval Using Class-Specific Metric...

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Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI)

作者： Paulo Joia Erick Gomez Nieto Glenda Botelho Joao do Espirito Santo Batista Neto Afonso Paiva Luis Gustavo Nonato ICMC/SME Universidade de Sáo Paulo Sao Carlos Sao Paulo Brazil

Content-based image classification/retrieval based on image descriptors has become an essential component in most database systems. However, most existing systems do not provide mechanisms that enable interactive multi-objective queries, hampering the user experience. In this paper we present a novel methodology capable of accomplishing multi-objective searches while still being interactive. Our approach relies on a combination of class-specific metrics and multidimensional projection to devise an effective and interactive image retrieval system. Besides allowing visual exploration of image data sets, the provided results and comparisons show that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.

关键词： Measurement visualization Feature extraction Image retrieval Helicopters Image color analysis Pipelines

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visual analysis on the research of cross-language information retrieval

Visual analysis on the research of cross-language informatio...

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International conference on Uncertainty Reasoning and Knowledge Engineering (URKE)

作者： Zhao Rongying Chen Rui Center of Studies of Information Resources Wuhan University of China Wuhan China

The authors use the information visualization software - CiteSpace ii to conduct the knowledge mapping based on the data of cross-language information retrieval(CLIR) downloaded from the Web of Science at Institute for Scientific Information (ISI), including SCI, SSCI, and A&HCI. The paper maps the co-citation network mapping to reveal the representative scientists and documents of CLIR. Then draws the term and keyword co-appearance network to analyze the research hotspots of CLIR, and concludes that query translation, query expansion and machine translation are the hot topics of CLIR. At last, we map the research front mapping to analyze the research fronts of CLIR and find that the research fronts and development trend are the methods, strategies, and evaluation of CLIR.

关键词： Information retrieval Libraries Knowledge engineering data visualization visualization Computer science Internet

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TopicView: visually Comparing Topic Models of Text Collections

TopicView: Visually Comparing Topic Models of Text Collectio...

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International conference on Tools for Artificial Intelligence (ICTAI)

作者： Patricia J. Crossno Andrew T. Wilson Timothy M. Shead Daniel M. Dunlavy Scalable Analysis and Visualization Sandia National Laboratories Albuquerque NM USA Data Analysis and Informatics Sandia National Laboratories Albuquerque NM USA

We present Topic View, an application for visually comparing and exploring multiple models of text corpora. Topic View uses multiple linked views to visually analyze both the conceptual content and the document relationships in models generated using different algorithms. To illustrate Topic View, we apply it to models created using two standard approaches: Latent Semantic analysis (LSA) and Latent Dirichlet Allocation (LDA). Conceptual content is compared through the combination of (i) a bipartite graph matching LSA concepts with LDA topics based on the cosine similarities of model factors and (ii) a table containing the terms for each LSA concept and LDA topic listed in decreasing order of importance. Document relationships are examined through the combination of (i) side-by-side document similarity graphs, (ii) a table listing the weights for each document's contribution to each concept/topic, and (iii) a full text reader for documents selected in either of the graphs or the table. We demonstrate the utility of Topic View's visual approach to model assessment by comparing LSA and LDA models of two example corpora.

关键词： data models Vectors Analytical models Bipartite graph Computational modeling visualization Layout

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RNA2DMap: A visual exploration Tool of the Information in RNA's Higher-Order Structure

RNA2DMap: A Visual Exploration Tool of the Information in RN...

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IEEE International conference on Bioinformatics and Biomedicine (BIBM)

作者： Weijia Xu Ame Wongsa Jung Lee Lei Shang Jamie J. Cannone Robin R. Gutell Texas Advanced Computing Center USA Institute for Cellular and Molecular Biology USA School of Information University of Texas at Austin Austin TX USA

A new and emerging paradigm in molecular biology is revealing that RNA is implicated in nearly every aspect of the metabolism in the cell. To enhance our understanding of the function of these RNA molecules in the cell, it is essential that we have a complete understanding of their higher-order structures. While many computational tools have been developed to predict and analyse these higher-order RNA structures, few are able to visualize them for analytical purposes. In this paper, we present an interactive visualization tool of the secondary structure of RNA, named RNA2DMap. This program enables multiple-dimensions of information about RNA structure to be selected, customized and displayed to visually identify patterns and relationships. RNA2DMap facilitates the comparative analysis and understanding of RNAs that cannot be readily obtained with other graphical or text output from computer programs. Three use cases are presented to illustrate how RNA2DMap aids structural analysis.

关键词： RNA data visualization visualization Color Bioinformatics Crystals

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