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1st IEEE Colombian Caribbean conference, C3 2023

作者： Llumiquinga, Jose Cuenca, Erick Sallaberry, Arnaud Yachay Tech University Urcuquí Ecuador University of Montpellier Cnrs Amis Paul-Valéry University of Montpellier Lirmm Montpellier France

ISBN: (纸本)9798350341799

Information visualization is a field of visual data analysis that focuses on working with abstract information. It also incorporates interactions that make it easier for users to assimilate and understand the information presented quickly. This work focuses on developing TweetVis, a visualization tool that follows the fundamentals of Twitter data analysis. In particular, TweetVis makes it possible to explore Twitter conversations over time, as these conversations exert significant influence in the social and political spheres, underlining the importance of their analysis and exploration. To access Twitter conversations, use is made of the official Twitter API. Once the data is collected, it goes through a processing process that turns it into a graph, where the nodes represent the tweets, and the links denote the interactions between them. TweetVis allows users to explore conversations generated from a tweet interactively over time. Finally, this tool's effectiveness is tested in a real case, analyzing the tweet generated by a public figure. © 2023 IEEE.

关键词： visualization

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Research on the application of Virtual Reality Technology in the Field of Higher Art Education Teaching 24

Research on the application of Virtual Reality Technology in...

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16th International conference on Education Technology and Computers

作者： Zhang, Manyu Jiang, Xiaodong Tianjin Acad Fine Arts Tianjin Peoples R China

ISBN: (纸本)9798400717819

In order to solve the current shortcomings in the teaching of VR-integrated art majors, the creator teaching method is to apply virtual reality technology to the design and practical teaching of art courses. The innovation of this study is reflected in three aspects. Firstly, virtual reality technology is organically combined with traditional ancient architecture in experimental teaching and applied to art teaching courses. In this way, the subjective initiative and leading role of students in teaching can be given full play. This method can play a positive role in promoting students' practical ability and innovation ability. Secondly, the model approach of VR simulation experiments to fully demonstrate traditional architecture is proposed. This paper discusses how to successfully embed art visuals and place VR at the forefront of a progressive curriculum. This study conducted in a Chinese context used Fine Art students (62) as respondents to apply VR technology to their subject area. Part of the raw data was collected by completing a questionnaire, followed by a visual regression (rs = 2.67, p < .0001). The basic data analysis showed that VR allows students to absorb information quickly compared to the usual teaching methods. This method can play an effective role in scientifically evaluating the effectiveness of teaching and targeting improvements. In conclusion, the digital humanities creator pedagogy has been fully applied in the design and practice teaching of art students.

关键词： Virtual Reality Digital Humanities Tradition arts Thematic exploration

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QVis: A visual Analytics Tool for Exploring Noise and Errors in Quantum Computing Systems 4

QVis: A Visual Analytics Tool for Exploring Noise and Errors...

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4th IEEE International conference on Quantum Computing and Engineering, QCE 2023

作者： Steed, Chad A. Chae, Junghoon Dasgupta, Samudra Humble, Travis S. Oak Ridge National Laboratory Oak Ridge United States

ISBN: (纸本)9798350343236

We present the preliminary design and results of QVis, a visual analytics tool for exploring quantum device performance data. QV is helps uncover temporal and multivariate variations in noise properties of quantum devices. We describe the implementations of these methods as well as applications to the analysis of a 127-qubit data set derived from the IBM washington processor over a 16-month period. Both human-interactive and semi-automated analytic methods are included to address requirements for visual exploration, thresholding, and clustering techniques. Our application of QVis to real-world scenarios demonstrates the ability to reveal noteworthy patterns in the behavior of the critical characterization metrics. © 2023 IEEE.

关键词： visualization

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A Survey of visualization and analysis in High-Resolution Connectomics

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COMPUTER GRAPHICS FORUM 2022年第3期41卷 573-607页

作者： Beyer, Johanna Troidl, Jakob Boorboor, Saeed Hadwiger, Markus Kaufman, Arie Pfister, Hanspeter Harvard Univ Visual Comp Grp Cambridge MA 02138 USA SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA King Abdullah Univ Sci & Technol Visual Comp Ctr Thuwal Saudi Arabia

The field of connectomics aims to reconstruct the wiring diagram of Neurons and synapses to enable new insights into the workings of the brain. Reconstructing and analyzing the Neuronal connectivity, however, relies on many individual steps, starting from high-resolution data acquisition to automated segmentation, proofreading, interactive data exploration, and circuit analysis. All of these steps have to handle large and complex datasets and rely on or benefit from integrated visualization methods. In this state-of-the-art report, we describe visualization methods that can be applied throughout the connectomics pipeline, from data acquisition to circuit analysis. We first define the different steps of the pipeline and focus on how visualization is currently integrated into these steps. We also survey open science initiatives in connectomics, including usable open-source tools and publicly available datasets. Finally, we discuss open challenges and possible future directions of this exciting research field.

关键词： CCS Concepts • Human-centered computing → visualization systems and tools Scientific visualization • Applied computing → Life and medical sciences Systems biology

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data Insights Nexus-Innovative Platform for Dynamic Modeling and visual Analytics 7

Data Insights Nexus-Innovative Platform for Dynamic Modeling...

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7th International conference on Inventive Computation Technologies, ICICT 2024

作者： Nagaraj, P. Muneeswaran, V. Gopal Reddy, B. Venu Naga Ramya Sri, P. Gayathri, N. Dastagiri Reddy, T. Venkata Kalasalingam Academy of Research And Education Department of Computer Science And Engineering Virudhunagar Krishnankoil India Kalasalingam Academy of Research And Education Department of Electronics And Communication Engineering Virudhunagar Krishnankoil India

ISBN: (纸本)9798350359299

The study explores the terrain of data analysis by delving into data Insights Nexus, a comprehensive system at the forefront of this field. The application integrates machine learning modeling, dynamic 2D/3D visualization, and robust anomaly detection within a unified framework. User-friendly interfaces empower effortless construction, fine-tuning, and deployment of intricate machine-learning models for deep insights from complex datasets. Advanced 2D/3D visualization transforms data relationships into visually intuitive representations. Furthermore, the system employs state-of-the-art anomaly detection, bolstering result accuracy by identifying elusive irregularities and outliers. data Insights Nexus, as a pioneering solution, holds the potential to redefine data exploration and analysis across diverse research domains. It not only enhances efficiency but also offers unprecedented effectiveness in dealing with complex data. This research meticulously explores its components, applications, and potential impacts, providing invaluable insights for data analysts and researchers. The application represents a groundbreaking tool that promises to revolutionize research methodologies, enabling researchers to uncover new facets of data-driven discoveries. © 2024 IEEE.

关键词： visualization

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Scientometric analysis of Building Energy analysis in the Construction During 2005–2022

Scientometric Analysis of Building Energy Analysis in the Co...

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International conference on Civil Engineering Innovative Development in Engineering Advances, ICC-IDEA 2023

作者： Nakkeeran, G. Krishnaraj, L. Department of Civil Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India

ISBN: (纸本)9789819962327

The aim of this paper is to carry out a comprehensive review of 921 papers in the Scopus database on "building energy analysis using BIM" from 2005 to 2022. Using a systematic approach to the primary data in each document, we gather the various types of publications, citations, and predictions. visual analysis software Biblioshiny 2.0 is used to show the evolution of publications. There are guidelines for selecting documents for citation analysis. All of these factors are considered when assigning ranks based on citation count, the total number of documents and the average number of citations per document. Author-keywords and analysis of the data were used to identify software development hotspots and trends for building energy analysis. Bibliometric analysis is beneficial to building energy analysis researchers. Building energy analysis publications are studied extensively in a bibliometric study. To aim researchers in software for building energy analysis exploration, scholars should be aware of this field's hotspots’ current and future state. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Architectural design

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DM-Vis: A Graph-Based data Reconnaissance System for Multi-domain Urban data 41st

DM-Vis: A Graph-Based Data Reconnaissance System for Multi...

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41st Computer Graphics International conference, CGI 2024

作者： Wang, Hesong Wang, Song Wang, Yanru Long, Hao School of Computer Science and Technology Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9783031818059

As urbanization accelerates, data on the diverse aspects of urban life, including the environment, finance, and transportation, are increasing exponentially. Single-domain data analysis falls short for complex tasks, necessitating multi-source data integration to offer decision-makers a holistic view of interconnections and trends. However, challenges arise in effectively representing data associations and swiftly identifying relevant datasets. This paper proposes techniques to integrate multi-domain urban data relationships and facilitate the acquisition of target datasets. We introduce a method to transform data entities into association graphs and a data extraction method to aid users in understanding data relationships and acquiring target datasets. Using these methods, we developed DM-Vis, a data reconnaissance visual analysis system, to facilitate data integration and exploration from multiple sources. Real-data case studies and positive feedback from users and experts validate the utility and reliability of our approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data extract data integration data reconnaissance multi-domain data query embedding

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The use of image graph in the medical data analyzing 1

The use of image graph in the medical data analyzing

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1st IEEE International conference on Advances in data-Driven Analytics and Intelligent Systems, ADACIS 2023

作者： Laghridat, Charifa Essalih, Mohamed Mounir, Ilham Cadi Ayyad University Lapssii The Safi's Graduate School of Technology Marrakesh Morocco Mohammed v University in Rabat Lrit Cnrst Urac 29 Rabat It Center Faculty of Sciences Morocco

ISBN: (纸本)9798350344158

Medical data analysis is a critical process aimed at extracting valuable insights and knowledge from complex healthcare information. It plays a vital role in enhancing diagnostics, treatment planning, and medical research. In this context, medical images serve as a fundamental source of information, providing visual representations of anatomical structures and pathological conditions. Image processing techniques, utilizing mesh-based representations, offer unique opportunities for advancing the analysis of medical *** article presents a new method for analyzing medical data based on the concept of meshing. By representing medical images as undirected graphs, the proposed approach enables efficient exploration and analysis of spatial relationships. © 2023 IEEE.

关键词： Medical imaging

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Rich Screen Reader Experiences for Accessible data visualization

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COMPUTER GRAPHICS FORUM 2022年第3期41卷 15-27页

作者： Zong, Jonathan Lee, Crystal Lundgard, Alan Jang, JiWoong Hajas, Daniel Satyanarayan, Arvind MIT Cambridge MA 02139 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA UCL London England

Current web accessibility guidelines ask visualization designers to support screen readers via basic non-visual alternatives like textual descriptions and access to raw data tables. But charts do more than summarize data or reproduce tables;they afford interactive data exploration at varying levels of granularity-from fine-grained datum-by-datum reading to skimming and surfacing high-level trends. In response to the lack of comparable non-visual affordances, we present a set of rich screen reader experiences for accessible data visualization and exploration. Through an iterative co-design process, we identify three key design dimensions for expressive screen reader accessibility: structure, or how chart entities should be organized for a screen reader to traverse;navigation, or the structural, spatial, and targeted operations a user might perform to step through the structure;and, description, or the semantic content, composition, and verbosity of the screen reader's narration. We operationalize these dimensions to prototype screen-reader-accessible visualizations that cover a diverse range of chart types and combinations of our design dimensions. We evaluate a subset of these prototypes in a mixed-methods study with 13 blind and visually impaired readers. Our findings demonstrate that these designs help users conceptualize data spatially, selectively attend to data of interest at different levels of granularity, and experience control and agency over their data analysis process. An accessible HTML version of this paper is available at: http://***/pubs/rich-screen-reader-vis-experiences.

关键词： CCS Concepts • Human-centered computing → visualization design and evaluation methods Accessibility design and evaluation methods

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Exploring Deep Learning-Based visual Localization Techniques 3

Exploring Deep Learning-Based Visual Localization Techniques

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2023 IEEE 3rd International conference on data Science and Computer Application, ICDSCA 2023

作者： Yu, Zhuoyi Maynooth University International Engineering College Fuzhou University Fuzhou China

ISBN: (纸本)9798350341546

This comprehensive review paper explores the state of the art in visual localization and navigation, drawing on the principles and methodologies of three significant deep learning networks: visual Localization Network (VLocNet), Deep Fusion Network (DFNet), and Hybrid Frontend Network (HFNet). Each of these networks demonstrates the application of deep learning to spatial awareness and navigation tasks in unique and significant ways. Rather than an exhaustive dissection of these networks, the paper provides an encompassing overview, illuminating their underlying principles, architectural design, and their relative performance within the field. Additionally, the paper delves into the practical implications of these networks, examining their applications in diverse real-world scenarios. It underlines this examination with a comprehensive analysis of existing literature and experimental results, intended to impart a profound understanding of these networks' strengths, limitations, and potential application areas. Ultimately, this review aims to present a valuable compass to researchers navigating the evolving landscape of advancements in visual localization and navigation, thereby fostering enriched understanding and facilitating future exploration and development in this compelling field. © 2023 IEEE.

关键词： Computer vision Deep learning Object recognition Robotics visual localization Convolutional neural networks

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