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11th International conference on the Theory and Application of Diagrams (Diagrams)

作者： Bosveld-de Smet, Leonie Houben, Daniel Univ Groningen Groningen Netherlands

ISBN: (纸本)9783030542498;9783030542481

In this paper we investigate the effectiveness and efficiency of two two-dimensional static visual representations of spatio-temporal data, a map-based and a Gantt-based diagram, in their support of various information retrieval tasks. The map-based diagram is characterized by a natural spatial arrangement of locations on a schematic map. The Gantt-based one represents time naturally as a linearly ordered set of time intervals from left to right. A within-subject empirical experiment has been conducted, in which participants were asked to verify queries about persons, locations, and time intervals. The formulation of the queries was based on (i) Bertin's three reading levels, (ii) certain cognitive operations, and (iii) different syntactic orders of expressions denoting persons, locations and times. Response correctness and response time were recorded. With respect to response accuracy, both diagrams support viewers well in nearly all information retrieval tasks. Regarding efficiency, the map-based diagram elicited significantly faster response times than the Gantt-based one, except for queries with time in focus. The results suggest that map-based diagrams require less search and reasoning effort of viewers to retrieve the information asked for in the task types used in this study.

关键词： Information visualization Spatio-temporal data Map Gantt chart data exploration tasks Reading levels Cognitive operations

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24th Pacific-Asia conference on Knowledge Discovery and data Mining (PAKDD)

作者： Zhou, Xinyi Wu, Jindi Zafarani, Reza Syracuse Univ EECS Dept Data Lab Syracuse NY 13244 USA

ISBN: (纸本)9783030474362;9783030474355

Effective detection of fake news has recently attracted significant attention. Current studies have made significant contributions to predicting fake news with less focus on exploiting the relationship (similarity) between the textual and visual information in news articles. Attaching importance to such similarity helps identify fake news stories that, for example, attempt to use irrelevant images to attract readers' attention. In this work, we propose a Similarity-Aware FakE news detection method (SAFE) which investigates multi-modal (textual and visual) information of news articles. First, neural networks are adopted to separately extract textual and visual features for news representation. We further investigate the relationship between the extracted features across modalities. Such representations of news textual and visual information along with their relationship are jointly learned and used to predict fake news. The proposed method facilitates recognizing the falsity of news articles based on their text, images, or their "mismatches." We conduct extensive experiments on large-scale real-world data, which demonstrate the effectiveness of the proposed method.

关键词： Fake news Multi-modal analysis Neural networks Representation learning

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Towards a Graphical User Interface for Exploring and Fine-Tuning Crowd Simulations

Towards a Graphical User Interface for Exploring and Fine-Tu...

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27th IEEE conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Boensch, Andrea Jonda, Marcel Ehret, Jonathan Kuhlen, Torsten W. Rhein Westfal TH Aachen Visual Comp Inst Aachen Germany

ISBN: (纸本)9781728165325

Simulating a realistic navigation of virtual pedestrians through virtual environments is a recurring subject of investigations. The various mathematical approaches used to compute the pedestrians' paths result, i.a., in different computation-times and varying path characteristics. Customizable parameters, e.g., maximal walking speed or minimal interpersonal distance, add another level of complexity. Thus, choosing the best-fitting approach for a given environment and use-case is non-trivial, especially for novice users. To facilitate the informed choice of a specific algorithm with a certain parameter set, crowd simulation frameworks such as Menge [3] provide an extendable collection of approaches with a unified interface for usage. However, they often miss an elaborated visualization with high informative value accompanied by visual analysis methods to explore the complete simulation data in more detail which is yet required for an informed choice. Benchmarking suites such as SteerBench [14] are a helpful approach as they objectively analyze crowd simulations, however they are too tailored to specific behavior details. To this end, we propose a preliminary design of an advanced graphical user interface providing a 2D and 3D visualization of the crowd simulation data as well as features for time navigation and an overall data exploration.

关键词： H.5.2 [User Interfaces]: User Interfaces Graphical user interfaces (GUI)

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Towards an effective user interface for data exploration, data quality assessment and data integration

Towards an effective user interface for data exploration, da...

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International conference on Semantic Computing

作者： Rolando Hanlon Marguerite Barry Fergal Marrinan Declan O'Sullivan ADAPT Centre Trinity College Dublin Dublin Ireland ADAPT Centre University College Dublin Dublin Ireland Sonas Innovation Dublin Ireland

ISBN: (数字)9781728188997

ISBN: (纸本)9781728189000

Domain professionals (e.g. medical professionals) find it difficult to directly interact with Linked data datasets in order to undertake common tasks that they typically need to do in order to explore their research hypotheses. We propose the development of a tool that integrates the common tasks involved through one user interface to support data exploration, data quality assessment and data integration. To initiate the necessary user-centered design process, we have designed an electronic storyboard to start the user requirements and user research, and evaluated this storyboard through an experiment in which four participants, identified as medical professionals in the healthcare domain, use the electronic storyboard to complete tasks regarding data exploration, data quality and data integration at the schema level. Preliminary findings indicate that the designed user interface will not be directly useful for the medical professionals but rather will be more useful for team members within the team of those medical professionals.

关键词： Navigation visual communication data integrity data integration User interfaces Task analysis Medical diagnostic imaging

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InChorus: Designing Consistent Multimodal Interactions for data visualization on Tablet Devices 20

InChorus: Designing Consistent Multimodal Interactions for D...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Srinivasan, Arjun Lee, Bongshin Riche, Nathalie Henry Drucker, Steven M. Hinckley, Ken Microsoft Res Redmond WA 98052 USA Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781450367080

While tablet devices are a promising platform for data visualization, supporting consistent interactions across different types of visualizations on tablets remains an open challenge. In this paper, we present multimodal interactions that function consistently across different visualizations, supporting common operations during visual data analysis. By considering standard interface elements (e.g., axes, marks) and grounding our design in a set of core concepts including operations, parameters, targets, and instruments, we systematically develop interactions applicable to different visualization types. To exemplify how the proposed interactions collectively facilitate data exploration, we employ them in a tablet-based system, InChorus that supports pen, touch, and speech input. Based on a study with 12 participants performing replication and fact-checking tasks with InChorus, we discuss how participants adapted to using multimodal input and highlight considerations for future multimodal visualization systems.

关键词： Multimodal interaction data visualization tablet devices pen touch speech

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visual exploration of intracranial aneurysm blood flow adapted to the clinical researcher

Visual exploration of intracranial aneurysm blood flow adapt...

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23rd Eurographics conference on visualization, EuroVis 2021

作者： Behrendt, B. Engelke, W. Berg, P. Beuing, O. Hotz, I. Preim, B. Saalfeld, S. Department of Simulation and Graphics University of Magdeburg Germany Department of Science and Technology Linköping University Sweden Department of Fluid Dynamics and Technical Flows University of Magdeburg Germany Research Campus STIMULATE Germany Institute of Neuroradiology University Hospital Magdeburg Germany

ISBN: (纸本)9783038681472

Rupture risk assessment is a key to devise patient-specific treatment plans of cerebral aneurysms. To understand and predict the development of aneurysms and other vascular diseases over time, both hemodynamic flow patterns and their effect on the vessel surface need to be analyzed. Flow structures close to the vessel wall often correlate directly with local changes in surface parameters, such as pressure or wall shear stress. However, especially for the identification of specific blood flow characteristics that cause local startling parameters on the vessel surface, like elevated pressure values, an interactive analysis tool is missing. In order to find meaningful structures in the entirety of the flow, the data has to be filtered based on the respective explorative aim. Thus, we present a combination of visualization, filtering and interaction techniques for explorative analysis of blood flow with a focus on the relation of local surface parameters and underlying flow structures. In combination with a filtering-based approach, we propose the usage of evolutionary algorithms to reduce the overhead of computing pathlines that do not contribute to the analysis, while simultaneously reducing the undersampling artifacts. We present clinical cases to demonstrate the benefits of both our filter-based and evolutionary approach and showcase its potential for patient-specific treatment plans. © 2021 The Author(s) Eurographics Proceedings © 2021 The Eurographics Association.

关键词： Hemodynamics

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The visualization of Cross-media Knowledge Graph of Tang and Song Poetry

The Visualization of Cross-media Knowledge Graph of Tang and...

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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter), ACIS International Winter conference on

作者： Wenjuan Jiang Chunfang Li Changti Wu School of Computer Science and Cybersecurity Communication University of China Beijing China

ISBN: (纸本)9781665418430;9781665448260

The special grammar and abstruse rhetoric of Tang and Song poetry doomed the diversity of poetry research. In order to help scholars explore the information space of poetry, we took into account the breadth and depth of learning, combined with heterogeneous data sources such as poetry, videos, textbooks, knowledge graph and other media sources, and carried out visual modeling. We provide a visual and informative platform to demonstrate the potential power of visualization. It supports comprehensive search capabilities for multiple types of data, online generation of poets' knowledge graphs. Relationship diagram, word cloud diagram, pie chart and other visual charts are displayed on the platform, so that users can complete exploratory visual analysis by dragging, clicking and typing.

关键词： visualization Heuristic algorithms Software algorithms data visualization Tag clouds Space exploration Videos

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RadEx: Integrated visual exploration of Multiparametric Studies for Radiomic Tumor Profiling

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COMPUTER GRAPHICS FORUM 2020年第7期39卷 611-622页

作者： Morth, E. Wagner-Larsen, K. Hodneland, E. Krakstad, C. Haldorsen, I. S. Bruckner, S. Smit, N. N. Univ Bergen Dept Informat Bergen Norway Haukeland Hosp Dept Radiol Mohn Med Imaging & Visualizat Ctr Bergen Norway Univ Bergen Dept Clin Med Bergen Norway Norwegian Res Ctr NORCE Bergen Norway Univ Bergen Dept Clin Sci Ctr Canc Biomarkers Bergen Norway

Better understanding of the complex processes driving tumor growth and metastases is critical for developing targeted treatment strategies in cancer. Radiomics extracts large amounts of features from medical images which enables radiomic tumor profiling in combination with clinical markers. However, analyzing complex imaging data in combination with clinical data is not trivial and supporting tools aiding in these exploratory analyses are presently missing. In this paper, we present an approach that aims to enable the analysis of multiparametric medical imaging data in combination with numerical, ordinal, and categorical clinical parameters to validate established and unravel novel biomarkers. We propose a hybrid approach where dimensionality reduction to a single axis is combined with multiple linked views allowing clinical experts to formulate hypotheses based on all available imaging data and clinical parameters. This may help to reveal novel tumor characteristics in relation to molecular targets for treatment, thus providing better tools for enabling more personalized targeted treatment strategies. To confirm the utility of our approach, we closely collaborate with experts from the field of gynecological cancer imaging and conducted an evaluation with six experts in this field.

关键词： CCS Concepts • Applied computing ŕ Health informatics • Human-centered computing ŕ visualization design and evaluation methods

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Feasibility of Machine Learning in Predicting Features Related to Congenital Nystagmus 15th

Feasibility of Machine Learning in Predicting Features Relat...

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15th Mediterranean conference on Medical and Biological Engineering and Computing (MEDICON)

作者： D'Addio, Giovanni Ricciardi, Carlo Improta, Giovanni Bifulco, Paolo Cesarelli, Mario Ist Clin Sci Maugeri IRCCS Naples Italy Univ Hosp Naples Federico II Dept Adv Biomed Sci Naples Italy Univ Hosp Naples Federico II Dept Publ Hlth Naples Italy Univ Naples Federico II DIETI Naples Italy

ISBN: (纸本)9783030316358;9783030316341

Congenital nystagmus is an ocular-motor disease affecting people's visual acuity since their first years of life. Electrooculography is used to perform eye tracking in these patients, giving the possibility to extract a wide variety of parameters. The relationships among all these variables were analysed in the past and the aim of this paper is to perform a new analysis employing more recent techniques, those of machine learning. The electrooculography of 20 patients was recorded, signals were pre-processed, and some parameters were extracted through a custom-made software. Knime analytics platform was chosen in order to build predictive models using Random Forests and Logistic Regression Tree algorithms and some evaluation metrics were computed. The visual acuity and the variability of eye positioning were predicted employing five and six variables, respectively. In terms of coefficient of determination, visual acuity had values over 0.72 and variability of eye positioning over 0.70. Compared to the results obtained without machine learning algorithms during the past years, these values become more valuable. In conclusion, this approach showed its feasibility in detecting relationships among variables related to congenital nystagmus;it could be tested in order to find new and stronger relationships among these variables and be of support for clinicians.

关键词： Nystagmus data mining Biomedical signals

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visual Analytics for the Reduction of Air Pollution on Real-Time data Derived from WSN

Visual Analytics for the Reduction of Air Pollution on Real-...

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Multidisciplinary International conference of Research Applied to Defense and Security (MICRADS)

作者： Quiroz, Dorys Guanochanga, Byron Fuertes, Walter Benitez, Diego Torres, Jenny Tapia, Freddy Toulkkeridis, Theofilos Univ Fuerzas Armadas ESPE Dept Ciencias Comp Sangolqui 1715231B Ecuador USFQ Colegio Ciencias & Ingn Politecn Campus Cumbaya Quito 171200841 Ecuador Escuela Politec Nacl Dept Informat & Ciencias Comp Quito 17012759 Ecuador

ISBN: (纸本)9789811391552;9789811391545

Nowadays, the contaminated and poor air quality that is inhaled by the city population in industrialized cities around the world has led to one of the main causes of premature death due to respiratory diseases. Therefore, the improvement of air quality becomes a priority. In this sense, the current study aimed to design and implement a visual analytics tool, in order to process large data sets, which have been generated by wireless sensor networks (WSN), which measured different environmental pollutants in real time. Hereby, the phases of the CRISP-DM methodology have been applied as a reference to guide the process. In the data preparation phase, programs have been implemented using Python. Then, the results have been stored in collections within a MongoDB database. Furthermore, for the modeling and visual exploration of the data, the Tableau tool has been used. The evaluation of the results allowed to demonstrate certain behavior of air pollutants around the city, such as the increased air pollution levels during daylight hours. Similarly, we discovered that the presence of particulate material PM10 and PM2.5 is directly related to the increase of the Air Quality Index for the city of Quito (IQCA). This leads to the conclusion that our analysis may be useful as a support tool in the decision-making of public policies for the reduction of air pollution.

关键词： Air pollution data mining Wireless sensor networks visual analytics

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