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12th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Huang, Huang Yang, Yi Tang, Liang Zhang, Zhang Liu, Nailong Li, Mou Wang, Liang Beijing Inst Control Engn Beijing Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9798350331547

A rover in extraterrestrial exploration works in challenging environment featured by primitive landforms and hidden dangerous areas. Due to the far distance from the rover to Earth, it is one of the most crucial capabilities that the rover can recognize and model the terrain properties efficiently and autonomously. In this paper, we present a Multimodal Off-road Terrain Classification (MOTC) dataset which is collected by a four-wheeled rover equipped with ego-centric visual cameras and inertial measurement unit (IMU). The dataset is generated from a boulder-strewn mock- up of the real Mars at the Intelligent Autonomous System Laboratory in Beijing Institute of Control Engineering. 24,982 images and corresponding sensor sequences are collected and annotated into 3 kinds of surface materials and 3 kinds of scene geometries. Based on the MOTC dataset, a baseline model with a multimodal fusion architecture is proposed for terrain classification. The experiment shows that the features extracted from visual images and from IMU complement each other to achieve improvements of terrain classification accuracy of the challenging extraterrestrial surface.

关键词： terrain classification sensor fusion transformer extraterrestrial exploration

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Confides: A visual Analytics Solution for Automated Speech Recognition analysis and exploration

Confides: A Visual Analytics Solution for Automated Speech R...

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International conference on visualisation, VIS

作者： Sunwoo Ha Chaehun Lim R. Jordan Crouser Alvitta Ottley

ISBN: (数字)9798350354850

ISBN: (纸本)9798350354867

Confidence scores of automatic speech recognition (ASR) outputs are often inadequately communicated, preventing its seamless integration into analytical workflows. In this paper, we introduce Confides, a visual analytic system developed in collaboration with intelligence analysts to address this issue. Confides aims to aid exploration and post-AI-transcription editing by visually representing the confidence associated with the transcription. We demonstrate how our tool can assist intelligence analysts who use ASR outputs in their analytical and exploratory tasks and how it can help mitigate misinterpretation of crucial information. We also discuss opportunities for improving textual data cleaning and model transparency for human-machine collaboration.

关键词： Analytical models Uncertainty visual analytics Human-machine systems Collaboration data visualization Cleaning data models Speech to text Automatic speech recognition

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Proceedings - 2022 26th International conference Information visualisation, iv 2022

Proceedings - 2022 26th International Conference Information...

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26th International conference Information visualisation, iv 2022

ISBN: (纸本)9781665490078

The proceedings contain 70 papers. The topics discussed include: Glyph-based visual analysis of Q-leaning based action policy ensembles on racetrack;clustering ensemble-based edge bundling to improve the readability of graph drawings;visualizing disks and labels with good visibility and correspondence;visualizing temporal data using time-dependent non-decreasing monotone functions;affective color palette recommendations with non-negative tensor factorization;a systematic literature review of solution-space visualization approaches in the context of optimization problems;augmenting the reality of situated visualization;kinematic motion analysis with volumetric motion capture;an overview of the design and development for dynamic and physical bar charts;a flexible pipeline to create different types of data physicalizations;development of a tourist added value service for the city of Madrid;observation and visualization of subjectivity-based annotation tasks;comparing word embeddings through visualization;and relative confusion matrix: efficient comparison of decision models.

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UMAP 2023 - Adjunct Proceedings of the 31st ACM conference on User Modeling, Adaptation and Personalization

UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference o...

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31st ACM conference on User Modeling, Adaptation and Personalization, UMAP 2023

ISBN: (纸本)9781450398916

The proceedings contain 71 papers. The topics discussed include: a multi-factorial analysis of polarization on social media;addressing popularity bias in recommender systems: an exploration of self-supervised learning models;an out-of-the-box application for reproducible graph collaborative filtering extending the Elliot framework;chai wallpaper: a mindfulness-based persuasive intervention for absent-minded smartphone usage;covering covers: characterization of visual elements regarding sleeves;cyclops: looking beyond the single perspective in information access systems;eudaimonic and hedonic qualities as predictors of music videos’ relevance to users: a human-centric study;expected and experienced utility of points of interest in tourism recommender systems;how can we model climbers’ future visits from their past records?;and personalized learning systems for computer science students: analyzing and predicting learning behaviors using programming error data.

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visual Analytics - Climate Change in Social Media

Visual Analytics - Climate Change in Social Media

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International conference on Information visualisation (iv)

作者： Vanessa Kokoschka Cristian A. Secco Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

Climate change is one of the greatest challenges of our time and affects all areas of our society. Climate science is a complex field and the majority of the public does not experience the effects of climate change directly but through media. Social media platforms are among the most important communication channels: millions of people exchange information and interact with content on these platforms every day. For this reason, knowledge about the development of climate communication is relevant for various disciplines, but especially for communication sciences. How social media users interact with content on climate change and what content they consume is important for adapting communication strategies. This enables communicators such as journalists to respond appropriately to user interests and align their content. We contribute with a novel approach to portray climate change behavior of social media, transformer-based speech extraction from web video, transformer-based information extraction and trend analysis, and an interactive visual interface showing topic-specific data and trends.

关键词： Climate change visual analytics Social networking (online) Video on demand Market research data visualization Metadata visual analytics Meteorology

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EuroVis 2022 - 24th Eurographics conference on visualization 2022

EuroVis 2022 - 24th Eurographics Conference on Visualization...

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24th Eurographics conference on visualization, EuroVis 2022

The proceedings contain 44 papers. The topics discussed include: of course it’s political! a critical inquiry into underemphasized dimensions in civic text visualization;visual analytics of contact tracing policy simulations during an emergency response;effective use of Likert scales in visualization evaluations: a systematic review;how accessible is my visualization? evaluating visualization accessibility with chartability;seeing through sounds: mapping auditory dimensions to data and charts for people with visual impairments;ModelWise: interactive model comparison for model diagnosis, improvement and selection;infographics wizard: flexible infographics authoring and design exploration;reusing interactive analysis workflows;leveraging analysis history for improved in situ visualization recommendation;and visual parameter selection for spatial blind source separation.

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Self-touch and other spontaneous behavior patterns in early infancy

Self-touch and other spontaneous behavior patterns in early ...

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IEEE International conference on Development and Learning (ICDL)

作者： Khoury, Jason Popescu, Sergiu T. Gama, Filipe Marcel, Valentin Hoffmann, Matej Czech Tech Univ Fac Elect Engn Dept Cybernet Prague Czech Republic

ISBN: (数字)9781665413114

ISBN: (纸本)9781665413114

Children are not born tabula rasa. However, interacting with the environment through their body movements in the first months after birth is critical to building the models or representations that are the foundation for everything that follows. We present longitudinal data on spontaneous behavior of three infants observed between about 8 and 25 weeks of age in supine position. We combined manual scoring of video recordings with an automatic extraction of motion data in order to study infants' behavioral patterns and developmental progression such as: (i) spatial distribution of self-touches on the body, (ii) spatial patterns and regularities of hand movements, (iii) midline crossing, (iv) preferential use of one arm, and (v) dynamic patterns of movements indicative of goal-directedness. From the patterns observed in this pilot data set, we can speculate on the development of first body and peripersonal space representations. Several methods of extracting 3D kinematics from videos have recently been made available by the computer vision community. We applied one of these methods on infant videos and provide guidelines on its possibilities and limitations-a methodological contribution to automating the analysis of infant videos. In the future, we plan to use the patterns we extracted from the recordings as inputs to embodied computational models of learning of body representations in infancy.

关键词： self-exploration self-touch body exploration kinematics goal-oriented behavior reaching development

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Design and Practice of a Flight data Application System 2

Design and Practice of a Flight Data Application System

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2nd International conference on Big data Engineering and Education, BDEE 2022

作者： Wang, Haozhi Che, Jiumei Zhu, Wenlong Li, Min College of Aeronautics Yantai Nanshan University Yantai China Qingdao New Nanshan Air Training Co. Ltd. Yantai China

ISBN: (数字)9781665481847

ISBN: (纸本)9781665481847

Flight data can not only be applied to safety analysis, condition monitoring and model establishment, but also play a very important role in improving the effect of theory teaching and students' own ability. Based on flight simulation software and visual programming language, a flight data application system is developed in this paper. The system includes three modules: flight status monitoring, verification experiment and data customization. It can realize the objective evaluation of flight skills, the analysis and verification of flight data of theoretical knowledge, as well as the functions of classroom teaching demonstration and independent design experiment of teachers and students. It solves the current situation of insufficient application of simulated flight data in theoretical teaching and students' ability training. The teaching practice shows that the system can improve students' flight technology, deepen their understanding of abstract knowledge, stimulate their independent exploration ability, and assist teachers' classroom teaching, which has high application value. © 2022 IEEE.

关键词： Students

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VEHICLE: Validation and exploration of the Hierarchical Integration of Conflict Event data

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COMPUTER GRAPHICS FORUM 2021年第3期40卷 1-12页

作者： Mayer, B. Lawonn, K. Donnay, K. Preim, B. Meuschke, M. Univ Magdeburg Dept Simulat & Graph Magdeburg Germany Univ Jena Dept Comp Sci Jena Germany Univ Zurich Dept Polit Sci Zurich Switzerland

The exploration of large-scale conflicts, as well as their causes and effects, is an important aspect of socio-political analysis. Since event data related to major conflicts are usually obtained from different sources, researchers developed a semi-automatic matching algorithm to integrate event data of different origins into one comprehensive dataset using hierarchical taxonomies. The validity of the corresponding integration results is not easy to assess since the results depend on user-defined input parameters and the relationships between the original data sources. However, only rudimentary visualization techniques have been used so far to analyze the results, allowing no trustworthy validation or exploration of how the final dataset is composed. To overcome this problem, we developed VEHICLE, a web-based tool to validate and explore the results of the hierarchical integration. For the design, we collaborated with a domain expert to identify the underlying domain problems and derive a task and workflow description. The tool combines both traditional and novel visual analysis techniques, employing statistical and map-based depictions as well as advanced interaction techniques. We showed the usefulness of VEHICLE in two case studies and by conducting an evaluation together with conflict researchers, confirming domain hypotheses and generating new insights.

关键词： CCS Concepts • Human-centered computing → Information visualization Geographic visualization visualization toolkits

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A visual data Science Solution for visualization and visual Analytics of Big Sequential data 25

A Visual Data Science Solution for Visualization and Visual ...

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25th International conference Information visualisation (iv) - AI and visual Analytics and data Science

作者： Leung, Carson K. Wen, Yan Zhao, Chenru Zheng, Hao Jiang, Fan Cuzzocrea, Alfredo Univ Manitoba Dept Comp Sci Winnipeg MB Canada Univ Northern British Columbia UNBC Dept Comp Sci Prince George BC Canada Univ Calabria iDEA Lab Arcavacata Di Rende Italy

ISBN: (纸本)9781665438278

In the current era of big data, huge volumes of valuable data have been generated and collected at a rapid velocity from a wide variety of rich data sources. In recent years, the initiates of open data also led to the willingness of many government, researchers, and organizations to share their data and make them publicly accessible. An example of open big data is healthcare, disease and epidemiological data such as privacy-preserving statistics on patients who suffered from epidemic diseases like the coronavirus disease 2019 (COVID-19). Analyzing these open big data can be for social good. For instance, analyzing and mining the disease statistics helps people to get a better understanding of the disease, which may inspire them to take part in preventing, detecting, controlling and combating the disease. As "a picture is worth a thousand words", having the pictorial representation further enhances people's understanding of the data and the corresponding results for the analysis and mining. Hence, in this paper, we present a visual data science solution for the visualization and visual analytics of big sequential data. We illustrate the ideas through the visualization and visual analytics of sequences of real-life COVID-19 epidemiological data. Our solution enables people to visualize COVID-19 epidemiological data and their temporal trends. It also allows people to visually analyze the data and discover relationships among popular features associated with the COVID-19 cases. Evaluation of these real-life sequential COVID-19 epidemiological data demonstrates the effectiveness of our visual data science solution in enhancing user experience in the visualization and visual analytics of big sequential data.

关键词： information visualization big data sequences data science visual data science data mining data analytics visual analytics COVID-19

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