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5th International conference on Autonomous Infrastructure, Management, and Security, AIMS 2011

5th International Conference on Autonomous Infrastructure, M...

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5th International conference on Autonomous Infrastructure, Management, and Security, AIMS 2011

ISBN: (纸本)9783642214837

The proceedings contain 22 papers. The special focus in this conference is on Autonomous Infrastructure, Management, and Security. The topics include: Policy-Based pricing for heterogeneous wireless access networks;Decision engine for SIP based dynamic call routing;Evaluation of the resource requirements of SNMP agents on constrained devices;Carrier ethernet OAM: An overview and comparison to IP OAM;using diffusive load balancing to improve performance of peer-to-peer systems for hosting services;on the dimensioning of an aggregation service for P2P service overlay networks;impact of dynamics on situated and global aggregation schemes;towards Self-adaptive monitoring framework for integrated management;a novel approach to support the visual exploration and management of heterogeneous home area network devices and services;efficient distributed signature analysis;estimating bandwidth requirements using flow-level measurements;using of time characteristics in data flow for traffic classification;intrusion detection in open peer-to-peer multi-agent systems;Econometric feedback for runtime risk management in VoIP architectures;finding and analyzing evil cities on the internet;autonomous service composition in symbiotic networks;An SLA Support system for cloud computing;autonomic management for personalized handover decisions in heterogeneous wireless networks;optimising P2P overlays for pervasive environments;towards vulnerability prevention in autonomic networks and systems.

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AIAA Infotech at Aerospace conference and Exhibit 2011

AIAA Infotech at Aerospace Conference and Exhibit 2011

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AIAA Infotech at Aerospace conference and Exhibit 2011

ISBN: (纸本)9781600869440

The proceedings contain 225 papers. The special focus in this conference is on Infotech at Aerospace. The topics include: L1 adaptive control of uncertain nonlinear systems in the presence of output limits;combined EDL-mobility planning for planetary missions;automated battery swap and recharge to enable persistent UAV missions;low cost autopilot system for unmanned aerial vehicles;globally optimized scheduling for space object tracking;safety effects of shared resources in multicore processors;multiple intruder autonomous avoidance flight test;adaptive control with filtered state feedback;adaptive control using residual mode filters applied to wind turbines;condition-based health management (CBHM) architectures;data clustering for training set selection;intelligent systems for space situational awareness;the CAOS-D architecture for conjunction analysis;coordinated mapping and exploration for autonomous soaring;adaptation for center tracon automation system (CTAS);IV and V of a space robotic mission's fault protection system;enabling future robotic missions with multicore processors;structuring the organization for large scale integrated hazard analysis;the unmanned autonomous aircraft control system (UAACS);tensegrity structure as the control base of a flight simulator;scalable fault management for space missions;design of an optical applique sensor interface module (O-ASIM);the evolving paradigm for aerospace sensor networks;unmanned sense and avoid radar (USTAR);unmanned sense and avoid radar (USTAR);flying unmanned aircraft;fault management guiding principles;integrated systems health management for intelligent systems;system health management theory and design strategies;practical passive ranging with IRST for 2 UAVS;on-board visual tracking with unmanned aircraft system (UAS);switched beam antenna concept for small mobile platforms;emerging directions in aerospace software V and V;performance assessment, trust, and decision support;intelligent algorithms for m

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SolarMap: Multifaceted visual Analytics for Topic exploration

SolarMap: Multifaceted Visual Analytics for Topic Exploratio...

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IEEE International conference on data Mining (ICDM)

作者： Nan Cao David Gotz Jimeng Sun Yu-Ru Lin Huamin Qu Hong Kong University of Science and Technology Hong Kong China IBM Thomas J. Watson Research Center USA Harvard University Northeastern University USA

Documents in rich text corpora often contain multiple facets of information. For example, an article from a medical document collection might consist of multifaceted information about symptoms, treatments, causes, diagnoses, prognoses, and preventions. Thus, documents in the collection may have different relations across each of these various facets. Topic analysis and exploration for such multi-relational corpora is a challenging visual analytic task. This paper presents Solar Map, a multifaceted visual analytic technique for visually exploring topics in multi-relational data. Solar Map simultaneously visualizes the topic distribution of the underlying entities from one facet together with keyword distributions that convey the semantic definition of each cluster along a secondary facet. Solar Map combines several visual techniques including 1) topic contour clusters and interactive multifaceted keyword topic rings, 2) a global layout optimization algorithm that aligns each topic cluster with its corresponding keywords, and 3) 2) an optimal temporal network segmentation and layout method that renders temporal evolution of clusters. Finally, the paper concludes with two case studies and quantitative user evaluation which show the power of the Solar Map technique.

关键词： Layout data visualization visualization Tag clouds data models Kernel Diseases

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Multiresolution Semantic visualization of Network Traffic

Multiresolution Semantic Visualization of Network Traffic

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International conference on Semantic Computing

作者： Alefiya Hussain Arun Viswanathan Information Sciences Institute USC USA

Multiresolution semantic analysis of data involves inferring increasing levels of meaning from data. Due to the large volume and complexity of network data, multi resolution visualizations allow the user to rapidly focus on meaningful and relevant information. Current tools and techniques for visual analysis of network data are limited in their ability to operate at semantically relevant resolutions and impose great cognitive burden on users to manually infer semantics from low-level details. Extending our previous work that allows users to define semantics as abstract models, we apply these models to construct multi resolution visualizations of network traffic data. Our methodology for visual exploration allows the user to rapidly analyze and understand network traces, by providing intuitive and interactive representations of the network. We demonstrate the effectiveness of our approach by applying it to analyzing network trace data from a cyber security incident involving DNS cache poisoning.

关键词： Spatial resolution Semantics data visualization visualization Analytical models Computer crime

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Maleku: An evolutionary visual software analysis tool for providing insights into software evolution

Maleku: An evolutionary visual software analysis tool for pr...

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International conference on Software Maintenance (ICSM)

作者： Antonio González-Torres Roberto Therón Francisco J. García-Peñalvo Michel Wermelinger Yijun Yu Department of Computer Sciences University of Salamanca Spain Department of Computing Open University UK

Software maintenance is a complex process that requires the understanding and comprehension of software project details. It involves the understanding of the evolution of the software project, hundreds of software components and the relationships among software items in the form of inheritance, interface implementation, coupling and cohesion. Consequently, the aim of evolutionary visual software analytics is to support software project managers and developers during software maintenance. It takes into account the mining of evolutionary data, the subsequent analysis of the results produced by the mining process for producing evolution facts, the use of visualizations supported by interaction techniques and the active participation of users. Hence, this paper proposes an evolutionary visual software analytics tool for the exploration and comparison of project structural, interface implementation and class hierarchy data, and the correlation of structural data with metrics, as well as socio-technical relationships. Its main contribution is a tool that automatically retrieves evolutionary software facts and represent them using a scalable visualization design.

关键词： Software Measurement data visualization Engines data mining visual analytics

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Semantically steered visual analysis of highly detailed morphometric shape spaces

Semantically steered visual analysis of highly detailed morp...

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IEEE Symposium on Biological data visualization (BioVis)

作者： Max Hermann Anja C. Schunke Reinhard Klein Institute of Computer Science II University of Bonn Germany Max-Planck-Institute of Evolutionary Biology Plön Germany

A common technique in 3D shape analysis is to describe shape variability using a statistical deformation model (SDM). In contrast to the use of sparse landmark data for volume data this SDM is based on dense registrations of the input shapes. For a valuable exploration of the shape space in the setting of biological morphometrics we identified two prominent objectives for visual investigation. The first objective is to detect possible shape variations between anatomically different groups of individuals. The second is to integrate and exploit expert knowledge about relevant regions on the shapes. To meet the first objective, we advocate the use of dimensionality reduction methods combined with a parameterization defined on user specified classifications. This idea was already successfully applied in data-driven reflectance models and also turns out to be valuable in the context of biological morphometry, as it allows for intuitive exploration of shape variations. The second objective can be achieved by an appropriate weighted linear analysis which delivers a better approximation of shape variations in local neighbourhoods of a user defined region of interest. The methods were applied to real-world biological datasets of rodent mandibles and validated in cooperation with the MPI for Evolutionary Biology. For this purpose, we provide an interactive dynamic visualization of the shape space based on a custom GPU raycaster. A special feature of our implementation is that it builds the SDM directly on dense registrations of the volumes and does thereby not rely on a specific non-rigid registration method.

关键词： Shape Principal component analysis visualization Deformable models Computational modeling Space exploration Semantics

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visualizing Tags with Spatiotemporal References

Visualizing Tags with Spatiotemporal References

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International conference on Information visualisation (IV)

作者： Dinh Quyen Nguyen Christian Tominski Heidrun Schumann Tuan Anh Ta Institute for Computer Science University of Rostock Rostock Germany John von Neumann Institute Vietnam National University-HCMC Ho Chi Minh Vietnam

Nowadays, a great amount of data is created and distributed on the Internet. Tagging has become common practice to structure these data for easy access. Often the data and the associated tags contain spatial and temporal information. In this paper, we develop general design strategies for visualizing spatially and temporally referenced tags similar to tag clouds on maps. Temporal information of tags is encoded through the visual appearance of text or through additional visual artifacts associated with the tags, whereas the location of tags on a map illustrates the spatial references. We demonstrate our solution based on an interactive visualization prototype for the exploration of both spatial and temporal references of Flickr tags.

关键词： visualization data visualization Tag clouds Encoding Image color analysis Time frequency analysis Shape

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Observation-level interaction with statistical models for visual analytics

Observation-level interaction with statistical models for vi...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Alex Endert Chao Han Dipayan Maiti Leanna House Scotland Leman Chris North Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Statistics Virginia Polytechnic Institute and State University Blacksburg VA USA

In visual analytics, sensemaking is facilitated through interactive visual exploration of data. Throughout this dynamic process, users combine their domain knowledge with the dataset to create insight. Therefore, visual analytic tools exist that aid sensemaking by providing various interaction techniques that focus on allowing users to change the visual representation through adjusting parameters of the underlying statistical model. However, we postulate that the process of sensemaking is not focused on a series of parameter adjustments, but instead, a series of perceived connections and patterns within the data. Thus, how can models for visual analytic tools be designed, so that users can express their reasoning on observations (the data), instead of directly on the model or tunable parameters? Observation level (and thus “observation”) in this paper refers to the data points within a visualization. In this paper, we explore two possible observation-level interactions, namely exploratory and expressive, within the context of three statistical methods, Probabilistic Principal Component analysis (PPCA), Multidimensional Scaling (MDS), and Generative Topographic Mapping (GTM). We discuss the importance of these two types of observation level interactions, in terms of how they occur within the sensemaking process. Further, we present use cases for GTM, MDS, and PPCA, illustrating how observation level interaction can be incorporated into visual analytic tools.

关键词： data visualization data models visual analytics Analytical models Principal component analysis Layout

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Recognition and analysis of Objects in Medieval Images

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10th Asian conference on Computer Vision (ACCV)

作者： Yarlagadda, Pradeep Monroy, Antonio Carque, Bernd Ommer, Bjoern Heidelberg Univ Interdisciplinary Ctr Sci Comp D-69115 Heidelberg Germany

ISBN: (纸本)9783642228193;9783642228186

Rapid and cost effective digitization techniques have lead to the creation of large volumes of visual data in recent times. For providing convenient access to such databases, it is crucial to develop approaches and systems which search the database based on the representational content of images rather than the textual annotations associated with the images. The success of such systems depends on one key component: category level object detection in images. In this contribution, we study the problem of object detection in the application context of digitized versions of ancient manuscripts. To this end, we present a benchmark image dataset of medieval images with groundtruth information for objects such as `crowns' in the image dataset. Such a benchmark dataset allows for a quantitative comparison of object detection algorithms in the domain of cultural heritage, as illustrated by our experiments. We describe a detection system that accurately localizes objects in the database. We utilize shape information of the objects to analyze the type-variability of the category and to manually identify various sub-categories. Finally, we report a quantitative evaluation of the automatic classification of object into various sub-categories.

关键词： Object detection

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visual analysis of Temporal Trends in Social Networks Using Edge Color Coding and Metric Timelines

Visual Analysis of Temporal Trends in Social Networks Using ...

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IEEE International conference on and IEEE International Confernece on Social Computing (SocialCom) Privacy, Security, Risk and Trust (PASSAT)

作者： Udayan Khurana Viet-An Nguyen Hsueh-Chien Cheng Jae-wook Ahn Xi Chen Ben Shneiderman Department of Computer Science University of Maryland College Park USA Human-Computer Interaction Laboratory University of Maryland College Park USA University of Maryland at College Park College Park MD US

We present Net EvViz, a visualization tool for analysis and exploration of a dynamic social network. There are plenty of visual social network analysis tools but few provide features for visualization of dynamically changing networks featuring the addition or deletion of nodes or edges. Our tool extends the code base of the Node XL template for Microsoft Excel, a popular network visualization tool. The key features of this work are (1) The ability of the user to specify and edit temporal annotations to the network components in an Excel sheet, (2) See the dynamics of the network with multiple graph metrics plotted over the time span of the graph, called the Timeline, and (3) Temporal exploration of the network layout using an edge coloring scheme and a dynamic Time slider. The objectives of the new features presented in this paper are to let the data analysts, computer scientists and others to observe the dynamics or evolution in a network interactively. We presented Net EvViz to five users of Node XL and received positive responses.

关键词： Measurement data visualization Color visualization Layout Twitter

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