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International conference on Information visualisation (iv)

作者： Alfonso Guarino Nicola Lettieri Delfina Malandrino Pietro Russo Rocco Zaccagnino Computer Science Department University of Salerno Fisciano (SA) Italy National Institute for Public Policy Analysis Rome Italy

The paper presents ongoing research aiming to ease the interaction with large amounts of public sector data. The project focuses on the development of a modular online platform for both desktop and mobile devices exploiting visual Analytics to offer citizens, researchers and policymakers crosscutting reading of heterogeneous information. We experiment new ways to integrate, analyze, and visualize administrative, legal, and economic data as they appear to be a powerful ally not only to increase the transparency of government activities but also to enhance evidence-based policy making and agenda setting.

关键词： data visualization Tools Economics Law data mining visual analytics

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Making machine intelligence less scary for criminal analysts: reflections on designing a visual comparative case analysis tool

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visual COMPUTER 2018年第9期34卷 1225-1241页

作者： Jentner, Wolfgang Sacha, Dominik Stoffel, Florian Ellis, Geoffrey Zhang, Leishi Keim, Daniel A. Middlesex Univ Data Intens Syst London England Univ Konstanz Univ Str 10 D-78464 Constance Germany Univ Konstanz Data Anal & Visualizat Grp Univ Str 10 D-78464 Constance Germany

A fundamental task in criminal intelligence analysis is to analyze the similarity of crime cases, called comparative case analysis (CCA), to identify common crime patterns and to reason about unsolved crimes. Typically, the data are complex and high dimensional and the use of complex analytical processes would be appropriate. State-of-the-art CCA tools lack flexibility in interactive data exploration and fall short of computational transparency in terms of revealing alternative methods and results. In this paper, we report on the design of the Concept Explorer, a flexible, transparent and interactive CCA system. During this design process, we observed that most criminal analysts are not able to understand the underlying complex technical processes, which decrease the users' trust in the results and hence a reluctance to use the tool. Our CCA solution implements a computational pipeline together with a visual platform that allows the analysts to interact with each stage of the analysis process and to validate the result. The proposed visual analytics workflow iteratively supports the interpretation of the results of clustering with the respective feature relations, the development of alternative models, as well as cluster verification. The visualizations offer an understandable and usable way for the analyst to provide feedback to the system and to observe the impact of their interactions. Expert feedback confirmed that our user-centered design decisions made this computational complexity less scary to criminal analysts.

关键词： Crime intelligence analysis visual analytics Clustering System design Human-computer interaction Sequential pattern mining Text analysis Dimensionality reduction

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analysis on the performance of VIO according to Trajectory Planning of UAV

Analysis on the performance of VIO according to Trajectory P...

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International conference on Control, Automation and Systems ( ICCAS)

作者： EungChang Mason Lee Hyun Myung School of Electrical Engineering KI-AI KI-R Korea Advanced Institute of Science and Technology Daejeon Korea

ISBN: (数字)9788993215205

ISBN: (纸本)9781728185620

Recently, Unmanned Aerial Vehicles (UAVs) have been widely researched to accomplish tasks such as structural inspection, drone racing, and exploration of an unknown environment. To make the most of UAV and correctly estimate its pose with inexpensive and light-weight sensors such as Inertial Measurement Unit (IMU) and cameras, visual Inertial Odometry (VIO) has been intensively researched. There were a few analyses on the performance of VIO methods where only estimated pose error and utilization of the computing resources were considered. However, the performance of them according to trajectory planning was not treated. Trajectory planning can be one of the main reasons for the drift of localization from VIO since the sensors acquire the data at their sampling rates. In this paper, we analyze the performance of VIO on various trajectories that have different orders of polynomials for the desired position over time and hence different velocity, acceleration, and the first, second derivative of acceleration, using simulator which reflects the real dynamics of UAV. As a result, the higher the order of polynomial for trajectory, the better performance of VIO can be observed.

关键词： Trajectory Acceleration Cameras visualization Trajectory planning State estimation Pose estimation

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25th International conference on MultiMedia Modeling, MMM 2019

25th International Conference on MultiMedia Modeling, MMM 20...

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25th International conference on MultiMedia Modeling, MMM 2019

ISBN: (纸本)9783030057152

The proceedings contain 119 papers. The special focus in this conference is on MultiMedia Modeling. The topics include: From Movement to Events: Improving Soccer Match Annotations;multimodal Video Annotation for Retrieval and Discovery of Newsworthy Video in a News Verification Scenario;integration of exploration and Search: A Case Study of the M 3 Model;face Swapping for Solving Collateral Privacy Issues in Multimedia Analytics;exploring the Impact of Training data Bias on Automatic Generation of Video Captions;fashion Police: Towards Semantic Indexing of Clothing Information in Surveillance data;CNN-Based Non-contact Detection of Food Level in Bottles from RGB Images;personalized Recommendation of Photography Based on Deep Learning;two-Level Attention with Multi-task Learning for Facial Emotion Estimation;SCOD: Dynamical Spatial Constraints for Object Detection;user Interaction for visual Lifelog Retrieval in a Virtual Environment;query-by-Dancing: A Dance Music Retrieval System Based on Body-Motion Similarity;joint visual-Textual Sentiment analysis Based on Cross-Modality Attention Mechanism;deep Hashing with Triplet Labels and Unification Binary Code Selection for Fast Image Retrieval;incremental Training for Face Recognition;Character Prediction in TV Series via a Semantic Projection Network;a Test Collection for Interactive Lifelog Retrieval;SEPHLA: Challenges and Opportunities Within Environment - Personal Health Archives;Athens Urban Soundscape (ATHUS): A dataset for Urban Soundscape Quality Recognition;v3C – A Research Video Collection;STMP: Spatial Temporal Multi-level Proposal Network for Activity Detection;image Aesthetics Assessment Using Fully Convolutional Neural Networks;detecting Tampered Videos with Multimedia Forensics and Deep Learning;improving Robustness of Image Tampering Detection for Compression.

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25th International conference on MultiMedia Modeling, MMM 2019

25th International Conference on MultiMedia Modeling, MMM 20...

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25th International conference on MultiMedia Modeling, MMM 2019

ISBN: (纸本)9783030057091

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A visual Interaction Framework for Dimensionality Reduction Based data exploration

A Visual Interaction Framework for Dimensionality Reduction ...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Cavallo, Marco Demiralp, Cagatay IBM Res Yorktown Hts NY 10598 USA

ISBN: (纸本)9781450356206

Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation to the initial data dimensions, thus making them difficult to interpret. Here we propose a visual interaction framework to improve dimensionality-reduction based exploratory data analysis. We introduce two interaction techniques, forward projection and backward projection, for dynamically reasoning about dimensionally reduced data, We also contribute two visualization techniques, prolines and feasibility maps, to facilitate the effective use of the proposed interactions. We apply our framework to PCA and autoencoder-based dimensionality reductions. Through data-exploration examples, we demonstrate how our visual interactions can improve the use of dimensionality reduction in exploratory data analysis.

关键词： Dimensionality reduction interaction bidirectional binding visual embedding forward projection backward projection PCA autoencoder deep learning proline feasibility map exploratory data analysis what-if analysis Praxis

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Scrollytelling - An analysis of visual Storytelling in Online Journalism 22

Scrollytelling - An Analysis of Visual Storytelling in Onlin...

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22nd International conference Information visualisation (iv) - Biomedical visualization, visualisation on Built and Rural Environments and Geometric Modelling and Imaging

作者： Seyser, Doris Zeiller, Michael Univ Appl Sci Burgenland Informat Technol & Informat Management Eisenstadt Austria

ISBN: (纸本)9781538672020

Scrollytelling - the long-form of articles used in journalism - uses long, narrative types of text (e.g., report, feature) to tell complex stories. Scrollytelling articles published online often use multimedia content, especially information graphics which is a powerful tool to communicate complex information. This study investigates which types of infographics are used for visualizing complex data in long-form journalism published online. The analysis focusses on the utilization of infographics in scrollytelling and how infographics arc integrated in long-form articles.

关键词： scrollytelling storytelling infographics information visualization online journalism online newspaper

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Demonstrating David Meets Goliath: Combining Smartwatches with a Large Vertical Display for visual data exploration

Demonstrating David Meets Goliath: Combining Smartwatches wi...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Horak, Tom Dachselt, Raimund Badam, Sriram Karthik Elmqvist, Niklas Tech Univ Dresden Interact Media Lab Dresden Germany Univ Maryland College Pk MD 20742 USA

ISBN: (纸本)9781450356213

We explore the combination of smartwatches and a large interactive display to support visual data analysis. These two extremes of interactive surfaces are increasingly popular, but feature different characteristics-display and input modalities, personal/public use, performance, and portability. With this demonstration, we present our conceptual framework and its implementation, which enables analysts to explore data items using both devices in combination. Building on a analysis scenario for convicted crimes in Baltimore, our demonstration gives an impression of how the device combination can allow users to develop complex insights more fluidly by leveraging the device roles.

关键词： Cross-device interaction visual analysis data exploration multi-display environment large display smartwatch

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Biclusters Based visual exploration of Multivariate Scientific data

Biclusters Based Visual Exploration of Multivariate Scientif...

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IEEE Scientific visualization conference (Scivis)

作者： He, Xiangyang Tao, Yubo Wang, Qirui Lin, Hai Zhejiang Univ State Key Lab CAD & CG Hangzhou Peoples R China

ISBN: (纸本)9781538668825

This paper proposes a co-analysis framework based on biclusters, i.e., two subsets of variables and voxels with close scalar-value relationships, to guide the visual exploration process of multivariate data. We first automatically extract all meaningful biclusters, each of which only contains voxels with a similar scalar-value pattern over a subset of variables. These biclusters are organized according to their variable sets, and further grouped by a similarity metric to reduce redundancy and encourage diversity during visual exploration. Biclusters are visually represented in coordinated views to facilitate interactive exploration of multivariate data from the similarity between biclusters and the correlation of scalar values with different variables. Experiments demonstrate the effectiveness of our framework in exploring local relationships among variables, biclusters and scalar values in the data.

关键词： Multivariate data bicluster local association

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How augmented reality affects collaborative learning of physics: A qualitative analysis 13

How augmented reality affects collaborative learning of phys...

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13th International conference on Computer Supported Collaborative Learning - A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, CSCL 2019

作者： Unahalekhaka, Apittha Radu, Iulian Schneider, Bertrand Harvard University Graduate School of Education United States

ISBN: (纸本)9781732467231

Augmented reality (AR) is a powerful visualization tool to support learning of scientific concepts across learners of various ages. AR can make information otherwise invisible visible in the physical world in real-time. In this study, we are looking at a subset of data from a larger study (N=120), in which participant pairs interacted with an augmented sound producing speaker. We explored the learning behaviors in eight pairs of learners (N=16) who participated in an unstructured physics activity under two conditions: With or without AR. Comparing behaviors between the two experimental conditions, we found that AR affected learning in four different ways: Participants in the AR condition (1) learned more about visual concepts (ex: Magnetic field structures) but learned less about nonvisual content (ex: Relationship between electricity and physical movement);(2) stopped exploring the system faster than NonAR participants;(3) used less aids in exploration and teaching;and (4) spent less time in teaching their collaborators. We discuss implications of those results for designing collaborative learning activities with augmented reality. © ISLS

关键词： Augmented reality

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