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检索条件"任意字段=Conference on Visual Data Exploration and Analysis IV"

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Tracing Identity exploration Trajectories with Quantitative Ethnographic Techniques: A Case Study 1st

Tracing Identity Exploration Trajectories with Quantitative ...

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1st International conference on Quantitative Ethnography, ICQE 2019

作者： Foster, Aroutis Shah, Mamta Barany, Amanda Talafian, Hamideh Drexel University PhiladelphiaPA19104 United States Elsevier Inc. PhiladelphiaPA19103 United States

ISBN: (纸本)9783030332310

This paper is situated in a 5-year NSF CAREER project awarded to test and refine Projective Reflection (PR) as a theoretical and methodological framework for facilitating learning as identity exploration in play-based environments. 54 high school students engaged in Virtual City Planning, an iteratively refined course that provided systematic and personally-relevant opportunities for play, curricular, reflection and discussion activities in Philadelphia Land Science, a virtual learning environment, and in an associated curriculum enacted in a STEM museum-classroom. In-game logged data and in-class student data were examined using Epistemic Network analysis. An illustrative case study revealed visual and interpretive patterns in students’ identity exploration. The change was reflected in their knowledge, interest and valuing, self-organization and self-control, and self-perception and self-definition (KivSSSS) in relation to the roles explored from the start of the intervention (Starting Self), during (Exploring role-specific Possible Selves), and the end (New Self). © Springer Nature Switzerland AG 2019.

关键词： Students

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Total Technology Space Map as a Digital Platform 52

Total Technology Space Map as a Digital Platform

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52ndHawaii International conference on System Sciences (HICSS)

作者： Luo, Jianxi Singapore Univ Technol & Design SUTD SUTD MIT Int Design Ctr Data Driven Innovat Lab Singapore Singapore

ISBN: (纸本)9780998133126

A strand of recent studies utilized complete patent databases and classification systems to construct large network maps of patent technology classes, which might approximate the total technology space. It has been argued that such maps are useful for competitive intelligence analysis, technology road mapping, innovation decision support, and so on in the literature. In this paper, we illustrate the InnoGPS system to integrate such a map with various map-based visual analytic functions for technology navigation, positioning, neighborhood exploration, path finding and information retrieval. These analytics are either descriptive, predictive or prescriptive. During the process of developing InnoGPS, we have conceived a wide spectrum of other potential applications of the total technology space map for consumers, business, education and so on. These possibilities together with the difficulty to construct an accurate technology space representation suggest the strategic value to develop the total technology space map as a digital platform for any applications to discover, manage or represent any data, information and knowledge related to technologies, and to nurture an ecosystem of developers and users.

关键词： Competitive intelligence

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GraphVR: A Virtual Reality Tool for the exploration of Graphs with HTC Vive System 22

GraphVR: A Virtual Reality Tool for the Exploration of Graph...

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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： Capece, Nicola Erra, Ugo Grippa, Jari Univ Basilicata Dipartimento Matemat Informat & Econ Potenza Italy

ISBN: (纸本)9781538672020

This work examines the use of virtual reality to visualize and interact with three-dimensional graphs. We developed the design to be as natural and intuitive as possible, through analysis, study, and use of several layout algorithms, which allow the nodes of a graph to be positioned to reduce entropy levels. We chose to use this schematic visualization of graphs because it can describe the graphical data synthetically and the links between the data while presenting the data in a visual format. The application was developed entirely using Unreal Engine version 4, and the visualization was performed using the head-mounted display HTC Vive.

关键词： Virtual Reality Graph exploration Human Computer Interaction

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SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party visualization

SMAP: A Joint Dimensionality Reduction Scheme for Secure Mul...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Jiazhi Xia Tianxiang Chen Lei Zhang Wei Chen Yang Chen Xiaolong Zhang Cong Xie Tobias Schreck School of Computer Science and Engineering Central South University State Key Lab of CAD&CG Zhejiang University I4 data Pennsylvania State University University Park PA Facebook Graz University of Technology

ISBN: (数字)9781728180090

ISBN: (纸本)9781728180106

Nowadays, as data becomes increasingly complex and distributed, data analyses often involve several related datasets that are stored on different servers and probably owned by different stakeholders. While there is an emerging need to provide these stakeholders with a full picture of their data under a global context, conventional visual analytical methods, such as dimensionality reduction, could expose data privacy when multi-party datasets are fused into a single site to build point-level relationships. In this paper, we reformulate the conventional t-SNE method from the single-site mode into a secure distributed infrastructure. We present a secure multi-party scheme for joint t-SNE computation, which can minimize the risk of data leakage. Aggregated visualization can be optionally employed to hide disclosure of point-level relationships. We build a prototype system based on our method, SMAP, to support the organization, computation, and exploration of secure joint embedding. We demonstrate the effectiveness of our approach with three case studies, one of which is based on the deployment of our system in real-world applications.

关键词： data visualization Dimensionality reduction data privacy Task analysis Privacy Hospitals Distributed databases

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GeoMultivis: Helping decision-making through interactive visualizations from geospatial multivariate data 25

GeoMultivis: Helping decision-making through interactive vis...

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25th Americas conference on Information Systems, AMCIS 2019

作者： Signoretti, Wagner Manssour, Isabel Silveira, Milene Pontifícia Universidade Católica do Rio Grande do Sul Brazil

The amount of geospatial data that are daily generated through mobile phones, GPS and other technologies, could help in the process of decision-making. We can find datasets with several attributes associated with specific geographic coordinates, such as open government, meteorological and social network data. The visual exploration of such data facilitates to communicate how different attributes correlate to geographical locations by layering these attributes over maps. However, the analysis and knowledge discovery of several attributes associated with a specific location is not a trivial task. In this scenario, we introduce GeoMultivis, a set of interactive visualizations that combines multivariate data and geospatial localization. It integrates a map with clustered charts and coordinated multiple views, offering a way to interactively apply different filters and analyze several attributes, updating all the related visual representations. We demonstrate its applicability through three real-cases studies. Our main contribution is the interactive visualizations to support the visual analysis of geospatial multivariate data and its application to real cases, helping to find patterns and insights that could support decisions makers to improve social issues in the future. © 2019 Association for Information Systems. All rights reserved.

关键词： Decision making

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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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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Andrea Bönsch Marcel Jonda Jonathan Ehret TorstenW. Kuhlen Visual Computing Institute RWTH Aachen University Germany

ISBN: (数字)9781728165325

ISBN: (纸本)9781728165332

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： Computational modeling data models Graphical user interfaces Analytical models Navigation data visualization Solid modeling

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Estimating wheel slip of a planetary exploration rover via unsupervised machine learning

Estimating wheel slip of a planetary exploration rover via u...

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IEEE Aerospace conference

作者： Kruger, Justin Rogg, Arno Gonzalez, Ramon Stanford Univ Stanford CA 94305 USA NASA Ames Res Ctr Moffett Field CA 94035 USA Robon Worldwide Tech Startup Calle Extremadura 5 Roquetas De Mar 04740 Almeria Spain

ISBN: (纸本)9781538668542

Planetary exploration rovers often encounter imperfect traction and wheel slip, which negatively impacts navigation and in the worst case can result in permanent immobilization. Recent studies have applied machine learning to estimate rover wheel slip, which this paper extends via the implementation of three unsupervised learning algorithms: self-organizing maps, k-means clustering, and autoencoding. Unsupervised learning is preferred since labelled training data may be risky or time-consuming to obtain on site;each algorithm classifies the rover's current slip state into one of several discrete categories. Proprioceptive sensors are used to avoid added complexity and prevent a reliance on visual odometry. The algorithms are validated using sensor data from a planetary rover driving on a sandy incline, and performance is evaluated for different velocities, sensor inputs, slip classes, algorithm parameters, and data filters. Self-organizing maps (SOM) demonstrate the best slip classification accuracy, achieving 97% immobilization detection in the ideal two-class case. At rover-like speeds of 0.10 m/s, 88% accuracy is demonstrated for three classes. For ten slip classes, 71% accuracy is obtainable. Compared to SOM, k-means loses 530% accuracy and autoencoders lose 2-10% accuracy. SOM is most computationally intensive while k-means is least. An analysis of significant parameters for algorithm tuning displays accuracy benefits of up to 25%, and mis-classifications can be further reduced by modifying class boundaries. The algorithms are generic and can be trained for different terrain, environment or vehicle parameters, and although some labelled data is needed to directly associate unsupervised clusters with slip classes, it is significantly less than what a fully-supervised algorithm requires. Unsupervised learning is thus considered promising for robust real-time rover slip estimation.

关键词： Neurons Clustering algorithms Wheels Self-organizing feature maps Sensors Estimation Machine learning

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ImWeb: Cross-Platform ImmersiveWeb Browsing for Online 3D Neuron database exploration 24

ImWeb: Cross-Platform ImmersiveWeb Browsing for Online 3D Ne...

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24th ACM International conference on Intelligent User Interfaces (IUI)

作者： Fulmer, Willis Mahmood, Tahir Li, Zhongyu Zhang, Shaoting Huang, Jian Lu, Aidong Univ N Carolina Charlotte NC 28223 USA Univ Tennessee Knoxville TN USA

ISBN: (纸本)9781450362726

Web services have become one major way for people to obtain and explore information nowadays. However, web browsers currently only offer limited data analysis capabilities, especially for large-scale 3D datasets. This project presents a method of immersive web browsing (ImWeb) to enable effective exploration of multiple datasets over the web with augmented reality (AR) techniques. The ImWeb system allows inputs from both the web browser and AR and provides a set of immersive analytics methods for enhanced web browsing, exploration, comparison, and summary tasks. We have also integrated 3D neuron mining and abstraction approaches to support efficient analysis functions. The architecture of ImWeb system flexibly separates the tasks on web browser and AR and supports smooth networking among the system, so that ImWeb can be adopted by different platforms, such as desktops, large displays, and tablets. We use an online 3D neuron database to demonstrate that ImWeb enables new experiences of exploring 3D datasets over the web. We expect that our approach can be applied to various other online databases and become one useful addition to future web services.

关键词： Immersive web browsing augmented reality visual analytics online database 3D neuron exploration

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Urdu Sentiment Corpus (v1.0): Linguistic exploration and visualization of Labeled dataset for Urdu Sentiment analysis

Urdu Sentiment Corpus (v1.0): Linguistic Exploration and Vis...

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International conference on Information Science and Communication Technology (ICISCT)

作者： Muhammad Yaseen Khan Muhammad Suffian Nizami Center for Language Computing Mohammad Ali Jinnah University Karachi Pakistan

ISBN: (数字)9781728168999

ISBN: (纸本)9781728169002

The significance of the labeled dataset is not obscure from artificial intelligence practitioners. We have seen much phenomenal work, in natural language processing, for many languages (like English, Chinese, and Arabic, etc.), due to the reason for the availability of substantial data. For the Urdu language, despite the third largest spoken language in the world, very little research work is shown; hence, it is adjudged as a `morphologically rich' but `resource-poor' language. Further, the researchers working on Urdu natural language processing are in a quandary due to the lack of availability of labeled/annotated datasets. This paper shares the data, “Urdu Sentiment Corpus” (USC), and insights therein, of Urdu tweets for the sentiment analysis and polarity detection. The dataset is consisting of tweets, such that it casts a political shadow and presents a competitive environment between two separate political parties versus the government of Pakistan. Overall, the dataset is comprising over 17, 185 tokens with 52% records as positive, and 48 % records as negative. This paper shares the visual insights (from document-level to word-level) into the textual similarities, manifold-learning, etc. In addition to it, this paper also presents a Part-of-Speech wise analysis and an unpretentious technique for the extraction of sentiment lexicons from the corpus.

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Investigating aesthetics to afford more ‘felt’ knowledge and ‘meaningful’ navigation interface designs

Investigating aesthetics to afford more ‘felt’ knowledge a...

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International conference on Information visualisation (iv)

作者： Fiona Carroll Maggie Webb Simon Cropper School of Technologies Cardiffmet University Cardiff Wales School of Psychological Sciences The University of Melbourne Melbourne Australia

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

Aesthetically manipulating the visual variables of a navigation interface design has the potential for substantial improvements in the interpretation of, and subsequent navigational choices made resulting from that design. This paper reports on a study that explores how an `optimal' path is understood across fifteen different types of route map designs for ten cities (approximately 150 route map designs in total). We are interested in how participants make sense of the route map, and subsequently choose an optimal pathway. The findings show that participants who experience certain aesthetically designed route maps are more inclined to meaningfully link information and create connections. By more deeply understanding people's perceptions of the aesthetics of a navigation problem space - particularly the ways in which people value and connect with aesthetic elements and how these impact the decisions made - a novel insight into individuals' understanding of data visualisation and how aesthetics affect is achieved.

关键词： visualization Uncertainty Navigation Shape Urban areas Sensors Task analysis

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