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

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Did Somebody Say 'Gest-IT'? A Pilot exploration of Multimodal data Management 10

Did Somebody Say 'Gest-IT'? A Pilot Exploration of Multimoda...

引用

10th Italian conference on Computational Linguistics, CLiC-it 2024

作者： Pannitto, Ludovica Albanesi, Lorenzo Marion, Laura Martines, Federica Maria Caruso, Carmelo Bianchini, Claudia S. Masini, Francesca Mauri, Caterina Alma Mater Studiorum University of Bologna Italy University of Poitiers FoReLLIS Laboratory France

The paper presents a pilot exploration of the construction, management and analysis of a multimodal corpus. Through a three-layer annotation that provides orthographic, prosodic, and gestural transcriptions, the Gest-IT resource allows to investigate the variation of gesture-making patterns in conversations between sighted people and people with visual impairment. After discussing the transcription methods and technical procedures employed in our study, we propose a unified CoNLL-U corpus and indicate our future steps. © 2024 CEUR-WS. All rights reserved.

关键词： Information management

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Exploring data Workers’ Behaviours in data Quality Discovery 44

Exploring Data Workers’ Behaviours in Data Quality Discover...

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44th International conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： Chen, Tianwa Demartini, Gianluca Indulska, Marta Sadiq, Shazia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Business School The University of Queensland Brisbane Australia

ISBN: (纸本)9781713893622

The rise of data re-purposing has resulted in an unprecedented opportunity to create new value from existing data assets. Unlike previous approaches that relied on well-understood data quality requirements, this open-ended setting demands a discovery-oriented approach. Despite a growing market of tools that assist with data exploration and profiling, data quality discovery continues to drain the time of data workers due to its cognitively demanding and contextual nature. Accordingly, we study data quality discovery through purpose-built experimental platforms that mimic typical data exploration platforms, and explore implicit sensemaking behaviours of data workers when required to write code or use available functions, by exploiting eye-tracking and log data. Our analysis of visual scanning and attention patterns reveals various sensemaking loops amongst data workers with different performance levels in different settings. Our findings provide insights for researchers and tool designers to consider how to support different data workers in data quality discovery. Copyright © 2023 Tianwa Chen, Gianluca Demartini, Marta Indulska, Shazia Sadiq.

关键词： Eye tracking

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Fine-Tuning Large Language Models for Automatic Font Skeleton Generation: exploration and analysis 17th

Fine-Tuning Large Language Models for Automatic Font Skelet...

引用

17th Asian conference on Computer Vision, ACCV 2024

作者： Liu, Yuxuan Fujii, Yasuhisa Zhu, Xinru Nohara, Kayoko School of Environment and Society Institute of Science Tokyo Tokyo Japan Google DeepMind Tokyo Japan

ISBN: (纸本)9789819609079

Despite the pivotal role that font skeletons could play in typeface research and font design, the availability of font skeleton data is sparse and limited. This research explores the possibility of using Large Language Models (LLMs) to generate font skeleton data based on font outline data. Our method represents font skeletons and font outlines as sequences of text tokens derived from SVG commands, and formulates the font skeleton task as a language modeling task predicting the token sequence for a font skeleton given the token sequence of a font outline. As a first attempt, we fine-tuned GPT-3.5 on a dataset of 8,213 Japanese font outlines and corresponding skeletons. Both quantitative and qualitative evaluations show the effectiveness of the approach in terms of rasterized pixel distance, Chamfer distance, and visual analysis. Our proposed method achieved average results of 14.678 for rasterized pixel distance and 1.713 for Chamfer distance, both better than the baseline method (PolyVectorization). In visual analysis, we found better generation results for complex shapes which logograms such as Chinese characters tend to have, than for the simple shapes of syllabograms such as Japanese kana, phonograms such as Latin alphabets, and symbols. Although our fine-tuned model has limitations in generating the skeletons of other font styles, this research establishes a foundation for the automatic generation of font skeletons using LLMs, setting the stage for future work on automatic skeleton generation and the wider application of font skeletons in typography. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Musculoskeletal system

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Exploring data Workers’ Behaviours in data Quality Discovery 34

Exploring Data Workers’ Behaviours in Data Quality Discover...

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34th Australasian conference on Information Systems, ACIS 2023

关键词： Eye tracking

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Modeling analysis of carbon sequestration in visual forests 3

Modeling analysis of carbon sequestration in visual forests

引用

3rd International conference on Machine Learning and Big data Analytics for IoT Security and Privacy, SPIoT2023

作者： Liu, Chunyan Han, Yao Gao, Shan Harbin Cambridge University Harbin150069 China

Forests are the largest pool of carbon in terrestrial ecosystems and are important for climate change mitigation. By analyzing the carbon sequestration process of forest ecosystem, the carbon sequestration amount of forest can be modeled as a nonlinear function, and the mechanism of forest carbon sequestration can be discussed on this basis. The research first introduced the relevant theories of forest carbon sequestration, followed by the preparation of the visualization system construction based on the research area and data sources, and then the construction of the visualization system, and finally carried out the simulation verification. The results show that the system is effective and accurate. © 2023 The Authors. Published by Elsevier B.V.

关键词： Carbon

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Identifying the Correlation between Alzheimer and type 2 Diabetes 26

Identifying the Correlation between Alzheimer and type 2 Dia...

引用

26th International conference Information visualisation (iv)

作者： Francese, Rita Frasca, Maria Risi, Michele Tortora, Genoveffa Univ Salerno Dept Comp Sci Fisciano Italy

ISBN: (纸本)9781665490078

In recent years it has been assessed that in people with type 2 diabetes the likelihood of developing Alzheimer's disease increases by more than 50%. The purpose of the analysis proposed in this paper is to identify visually the correlation between Alzheimer's disease and type 2 diabetes and determine whether Alzheimer's disease is a form of brain diabetes mellitus. A dataset containing genomic microarray data relating to the two diseases is used for the analysis. First, we conduct an exploratory analysis using clustering techniques to perform a first screening of the samples and divide them into two different clusters. Then, we propose a predictive model for the classification and identify the genes equally expressed in the two types of samples. This makes it possible to select genes with significant values for the research in progress, on which pathway analysis must be performed to identify the classes they belong to. We also study the gene expression alterations of genes belonging to a specific pathway to determine if the differential expression is statistically significant. We provide a visual representation of connections in the pathways of both the diseases. Results indicate that there is a set of genes of significant importance for both type 2 diabetes and Alzheimer's disease, but that there is also a significant correlation with other neurodegenerative diseases. Consequently, it is possible to define the Alzheimer's disease as a form of cerebral diabetes mellitus.

关键词： Diabetes Alzheimer Genomic data Clustering Pathway Pathway visualization

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A Pipeline for Immersive data visualization in CAVE Systems

A Pipeline for Immersive Data Visualization in CAVE Systems

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Challa, Koundinya Jaiswal, Chandra Pendem, Abhinav Gokaraju, Balakrishna North Carolina A&T State University Dept. Computational Data Science and Engineering Greensboro United States

ISBN: (纸本)9798331504847

Virtual Reality (VR) has transformed data visualization by enabling immersive and interactive experiences. CAVE (Cave Automatic Virtual Environment) systems provide a unique platform for exploring complex datasets in an intuitive, spatially immersive manner. However, a standardized pipeline for developing VR scripts tailored to CAVE-based data visualization remains underexplored. This paper presents a structured pipeline for creating and deploying immersive data visualization in CAVE systems, specifically using the WorldViz Prism CAVE environment. Our approach facilitates seamless integration of multi-dimensional datasets, enabling real-time interaction with 27 visual graphs within a single VR scene. The system allows dynamic graph manipulation, interactive exploration, and enhanced user engagement. By streamlining VR script development, this pipeline improves accessibility for researchers and practitioners, fostering a more intuitive understanding of complex datasets. Experimental results demonstrate the effectiveness of this approach in enhancing data interpretability and decision-making. © 2025 IEEE.

关键词： Video analysis

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data-driven visual analytics of Human Mobility data and green cover using Image Processing for Smart Cities 3

Data-driven visual analytics of Human Mobility data and gree...

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3rd IEEE International conference on Intelligent Technologies, CONIT 2023

作者： Ramanathan, Sivasubramanian Syed, Kulsoom Chavan, Tejaswini B. Tech Computer Science & Business Systems SVKMs NMIMS Navi Mumbai Mumbai India School of Technology Management & Engineering SVKMs NMIMS Navi Mumbai Mumbai India

ISBN: (纸本)9798350338607

This research paper presents an approach to data-driven visual analytics of human mobility data using Kernel Density Estimation visualized through heatmaps, highlighting the need for exploration of forecasting methods and intuitive visualizations using the ARIMA model. A specific geographic area is chosen for the demonstration of the scope of the proposed system. The system is a web application developed using Streamlit, an open-source python framework. To effectively implement the smart city concept, it is crucial to integrate diverse IoT systems, data sources, data streams, and analytical tools into a unified and seamless platform that facilitates the collection, analysis and presentation of information related to urban systems and subsystems. We propose taking into consideration several attributes when analyzing human mobility patterns, such as vehicle/traffic density, modes of transport, transport data, demographics, latitude, and longitude. Additionally, the system utilizes image processing as an efficient method for calculating urban green cover using morphological operations that are computationally cheaper and easy to use as compared to traditional surveys that are time and resource intensive. This information is used to develop smart plans to sustain or increase green cover in select areas, leading to the creation of sustainable and green smart cities. © 2023 IEEE.

关键词： Smart city

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Audio Perception in Robotic Assistance for Human Space exploration: A Feasibility Study

Audio Perception in Robotic Assistance for Human Space Explo...

引用

IEEE Aerospace conference

作者： Sewtz, Marco Friedl, Werner Bauer, Adrian Koepken, Anne Lay, Florian Bechtel, Nicolai Schmaus, Peter Triebel, Rudolph Lii, Neal Y. German Aerosp Ctr DLR Inst Robot & Mechatron Muenchener Str 20 D-82234 Wessling Germany

ISBN: (纸本)9781665490320

Future crewed missions beyond low earth orbit will greatly rely on the support of robotic assistance platforms to perform inspection and manipulation of critical assets. This includes crew habitats, landing sites or assets for life support and operation. Maintenance and manipulation of a crewed site in extraterrestrial environments is a complex task and the system will have to face different challenges during operation. While most may be solved autonomously, in certain occasions human intervention will be required. The telerobotic demonstration mission, Surface Avatar, led by the German Aerospace Center (DLR), with partner European Space Agency (ESA), investigates different approaches offering astronauts on board the International Space Station (ISS) control of ground robots in representative scenarios, e.g. a Martian landing and exploration Site. In this work we present a feasibility study on how to integrate auditory information into the mentioned application. We will discuss methods for obtaining audio information and localizing audio sources in the environment, as well as fusing auditory and visual information to perform state estimation based on the gathered data. We demonstrate our work in different experiments to show the effectiveness of utilizing audio information, the results of spectral analysis of our mission assets, and how this information could help future astronauts to argue about the current mission situation.

关键词： Robotics

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Unmasking Public Perception: A Mixed-Methods exploration of Social Media Discourse on U.S. Illegal Immigration

Unmasking Public Perception: A Mixed-Methods Exploration of ...

引用

2024 IEEE International conference on Big data, Bigdata 2024

作者： Sazzed, Salim Ullah, Sharif Georgia Southern University Department of Computer Science GA United States University of Central Arkansas Department of Computer Science and Engineering ConwayAR United States

ISBN: (纸本)9798350362480

With illegal immigration remaining a contentious issue in the United States, understanding public perception - particularly as expressed on social media - is vital for informed policymaking and advocacy. This study investigates the discourse surrounding illegal immigration in the U.S. through both quantitative and qualitative analyses of data from Reddit. We identify key themes and perspectives on four critical aspects: (i) U.S. policy toward illegal immigration, (ii) strategies for mitigating illegal immigration, (iii) issues arising from illegal immigration, and (iv) hostile rhetoric targeting undocumented immigrants. Additionally, we conduct emotion analysis to ascertain prevalent emotional responses within the discourse. Our findings reveal both challenges and perceived benefits associated with lenient border policies, including difficulties in monitoring extensive border areas and the exploitation of low-wage labor. We observe a wide range of suggested measures to reduce illegal migration, including stringent actions against employers of undocumented workers, proposals to abolish birthright citizenship, and calls for increased legal migration. Emotion analysis indicates significant levels of anger and disgust expressed in the comments. Furthermore, we document instances of anti-immigrant rhetoric, some of which are inhumane and include calls for violence against undocumented individuals. This research provides valuable insights into societal attitudes toward illegal immigration, informing policymakers and advocacy groups in their decision-making. © 2024 IEEE.

关键词： Crime

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