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检索条件"任意字段=IEEE Information Visualization Conference/IEEE Visualization Conference"

共 54122 条记录，以下是581-590 订阅

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Understanding Space Weather Through Storytelling Data visualization 14

Understanding Space Weather Through Storytelling Data Visual...

引用

14th ieee Integrated STEM Education conference, ISEC 2024

作者： Brantley, Angela Herbert, Katherine G. Anu, Vaibhav K. Hagiwara, Sumi Robila, Stefan A. Wang, Jason T.L.

ISBN: (纸本)9798350352801

Many students have difficulty understanding graphs. It may not be that they are not interested in what can be learned from a graph, rather how information is presented in a graph can be confusing. The project will focus on utilizing graphic design principles to create visual representations that effectively communicate the complex and nature of space weather. Through the incorporation of scientific data and research on solar activities, students will employ design elements such as layout, color theory, typography, and illustration to represent the various aspects of solar weather. The primary goal of this project is to create a simpler way to communicate information using visuals to understand the effect of solar activities on our planet. By merging scientific knowledge with creative design skills, students are encouraged to create informative and visually compelling materials such as infographics, posters, animations, and interactive digital media through an app. These visual representations will aim to clarify the causes, consequences, and predictive measures related to solar weather events. © 2024 ieee.

关键词： Data visualization

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visualization of Comorbidities in Inflammatory Bowel Diseases through Networks

Visualization of Comorbidities in Inflammatory Bowel Disease...

引用

2024 ieee International conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Vallelunga, Rosarina Milano, Marianna Spagnuolo, Rocco Giubilei, Lidia Suraci, Evelina Cannataro, Mario Luzza, Francesco University of Catanzaro Department of Health Sciences Italy University of Catanzaro Department of Experimental and Clinical Medicine Italy University of Catanzaro Department of Medical and Surgical Sciences Italy

ISBN: (纸本)9798350386226

Inflammatory Bowel Diseases (IBD), including Crohn's Disease (CD) and Ulcerative Colitis (UC), are chronic conditions characterized by a complex network of comorbidities that significantly impact patients' quality of *** this study, we employed a Network visualization approach to explore the comorbidities associated with IBD, using data extracted from the clinical records of patients at the Digestive Pathophysiology Unit of the University Hospital 'Renato Dulbecco'.By constructing networks, we mapped and compared the comorbidities of Crohn's Disease and Ulcerative Colitis, considering gender differences as well. The graphs produced offer a clear view clearly shows the major comorbidities and their distribution, highlighting significant differences between the two diseases and across *** visual approach facilitates a better understanding of the complexity of clinical interactions in IBD, suggesting new perspectives for personalized and multidisciplinary therapeutic approaches in managing these diseases. © 2024 ieee.

关键词： Comorbidities Crohn's Disease Inflammatory Bowel Disease (IBD) Network visualization Ulcerative Colitis

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Adaptive Anomaly Detection in Dynamic Graph Networks

Adaptive Anomaly Detection in Dynamic Graph Networks

引用

2024 International visualization, Informatics and Technology conference, IVIT 2024

作者： Mir, Aabid Ahmad Zuhairi, Megat F. Musa, Shahrulniza Namoun, Abdallah Universiti Kuala Lumpur Malaysian Institute of Information Technology Malaysia Islamic University of Madinah Faculty of Computer and Information Systems Saudi Arabia

ISBN: (纸本)9798350354447

Over the past few years, the detection of anomalies in dynamic graph networks has attracted substantial attention worldwide because of its applications in various fields such as cybersecurity, financial fraud detection, and social network analysis. Traditional methods may not be as adaptive to the dynamic nature of such networks, as it requires more efficient and scalable solutions. To mitigate the issue, a Variational Graph Convolutional Network (V-GCN) is proposed. It is an approach that combines variational autoencoders (VAEs) with graph convolutional networks (GCNs) for anomaly detection in dynamic graph data to enhance anomaly detection. The methodology involves developing a V-GCN architecture that combines the capabilities of VAEs and GCNs, applying an adaptive learning strategy to update model parameters in real time, and carrying out experiments using standard datasets. The experimental results indicate that the anomaly detection performance considerably enhanced using the proposed model. It outperforms the baseline methods, where the V-GCN attains an AUC-ROC of 95%, an average precision of 92%, an F1 score of 91%, and an anomaly score of 94%. © 2024 ieee.

关键词： Graph neural networks

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Review of High-Dimensional and Complex Data visualization 7

Review of High-Dimensional and Complex Data Visualization

引用

7th ieee International conference of Computer Science and information Technology, ICOSNIKOM 2023

作者： Hasugian, Paska Marto Mawengkang, Herman Sihombing, Poltak Efendi, Syahril University of Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia

ISBN: (纸本)9798350360752

In the age of big data, high-dimensional and complex data create significant challenges for data visualization. This research analyzes their impact on visualization techniques. Increasing data dimensions make traditional methods struggle to depict complex structures and patterns. This study comprehensively explores challenges arising from high dimensionality and data complexity in visualization. By examining various techniques and their suitability for such data, we aim to reveal the pros and cons of each approach in conveying essential information. Additionally, this research investigates using dimension reduction techniques to tackle the complexities of the data. The effectiveness of these techniques in preserving crucial information while enhancing visualization quality is evaluated. Some of the models examined include Multidimensional Scaling (MDS), which projects data into a lower-dimensional space to maintain distance relationships but does not consider class labels. MDS operates with a distance matrix but is sensitive to data that do not conform to distance metrics and can yield suboptimal projections in high-dimensional space. Principal Component Analysis (PCA) focuses on dimension reduction by maximizing data variance but does not consider class labels. PCA requires high-dimensional data and cannot handle non-linear structures. Linear Discriminant Analysis (LDA) is used for classification by maximizing inter-class distances, minimizing intra-class distances, and requiring class labels. However, LDA works well only under the assumptions of normal distribution and fulfilled class variance differences. Conversely, t-SNE and UMAP reveal data cluster structures. t-SNE is computationally complex and sensitive to parameters, while UMAP performs faster. t-SNE interprets data with topological and network context, suited for data with strong topological structures but requiring deep domain knowledge. Each method has its uses and limitations, depending on analysis goa

关键词： visualization

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LLM-Powered Multi-Actor System for Intelligent Analysis and visualization of IEC 61499 Control Systems 50

LLM-Powered Multi-Actor System for Intelligent Analysis and ...

引用

50th Annual conference of the ieee Industrial Electronics Society, IECON 2024

作者： Xavier, Midhun Laikh, Tatiana Patil, Sandeep Vyatkin, Valeriy Department of Computer Science Electrical and Space Engineering Lulea Tekniska Universitet Sweden Department of Electrical Engineering and Automation Aalto University Espoo Finland

ISBN: (纸本)9781665464543

This paper introduces an innovative multiactor framework that harnesses the potential of LLMs to augment the functionalities of ICS. By integrating conversational AI technologies, this framework significantly improves human-machine interactions, enabling sophisticated analysis and visualization of intricate data sets. The core of the system comprises specialized LLM actors that interact through a LangGraph-based multiactor framework, addressing various aspects of IEC 61499 control systems including PLC code analysis, SQL query execution, and data visualization. This integration enables operators to interact with the control system using natural language, significantly reducing technical barriers and enhancing the accessibility and usability of complex industrial systems. © 2024 ieee.

关键词： Control system analysis

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Spatial Augmented Reality for Heavy Machinery using Laser Projections

Spatial Augmented Reality for Heavy Machinery using Laser Pr...

引用

ieee conference on Virtual Reality and 3D User Interfaces (VR)

作者： Kernbauer, Thomas Tschulik, Maximilian Fleck, Philipp Arth, Clemens Graz Univ Technol Inst Comp Graph & Vis Graz Austria

ISBN: (纸本)9798350374490;9798350374506

Operating heavy machinery is challenging and can pose safety hazards for the operator and bystanders. Although commonly used augmented reality (AR) devices, such as head-mounted or head-up displays, can provide occupational support to operators, they can also cause problems. Particularly in off-highway scenarios, i.e., when driving machines in bumpy environments, the usefulness of current AR devices and the willingness of operators to wear them are limited. Therefore, we explore how laser-projection-based AR can help the operator facilitate their tasks and enhance safety. For this, we present a compact hardware unit and introduce a flexible and declarative software system. Furthermore, we examine the calibration process to leverage a camera projector setup and outline a process for creating images suitable for display by a laser projector from a set of line segments. Finally, we showcase its ability to provide efficient instructions to operators and bystanders and propose concrete applications for our setup.

关键词： Human-centered computing visualization visualization design and evaluation methods

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Research on Fast Analysis Model of Power Big Data Integrating 3D Data visualization Scene 3

Research on Fast Analysis Model of Power Big Data Integratin...

引用

2023 ieee 3rd International conference on Data Science and Computer Application, ICDSCA 2023

作者： Qingrui, Lin Bixing, Lin Shuze, Gao Jiangping, Yang Chaowang, Wu State Grid Info-Telecom Great Power Science and Technology Co. Ltd. Fujian Fuzhou350000 China

ISBN: (纸本)9798350341546

After determining large-scale power data and spatial scenarios, a new analysis model is constructed for 3D visualization scenarios. In this model, big data mining and 3D visualization technology are organically integrated, information fusion and fuzzy tomographic analysis method are adopted to realize efficient mining of power big data, and 3D rendering algorithm based on attribute reduction is used to improve the real-time performance of power 3D scene rendering. The visual feature reconstruction technology is used to realize the visual reconstruction of the 3D scene of power big data in the distribution network. The experiment shows that the data visualization management method can realize the efficient mining of power big data and real-time rendering of 3D model. © 2023 ieee.

关键词： 3D Scene Rendering information Fusion Power Data Three-Dimensional Data Visual Scene

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Research on Multi-Level 3D visualization Monitoring Technology Based on Digital Twins

Research on Multi-Level 3D Visualization Monitoring Technolo...

引用

2025 Asia-Europe conference on Cybersecurity, Internet of Things and Soft Computing, CITSC 2025

作者： Yong, Chenchen Gu, Zhen Zhou, Lei Zhang, Jingyue He, Qing Zhang, Dawei State Grid Shanghai Electric Power Company Marketing Service Center Shanghai China

ISBN: (纸本)9798331504205

This article proposes a multi-level 3D visualization monitoring technology based on digital twins. Through digital twin technology, we need to simulate laboratory environments, monitor and analyze various parameters in real time. The modeling technology of digital twins can be used for health monitoring and fault prediction of laboratory equipment, thereby reducing equipment damage and downtime, and improving the stability and reliability of laboratory operation. Multi level 3D visualization technology allows users to simultaneously view the global layout and detailed information of the laboratory, providing a more comprehensive monitoring perspective and helping to detect and solve problems in a timely manner. The optimized human-computer interaction technology enables monitoring personnel to interact more naturally with the monitoring system, improving work efficiency. © 2025 ieee.

关键词： visualization

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The Pattern and visualization Detection of the Load Profile Data Based on Bootstrap Approach 13

The Pattern and Visualization Detection of the Load Profile ...

引用

13th Mediterranean conference on Embedded Computing (MECO)

作者： Keka, Ilir Cico, Betim AAB Coll Fac Comp Sci Prishtina Kosovo Epoka Univ Dept Comp Engn Tirana Albania

ISBN: (纸本)9798350387568;9798350387575

This work presents an in-depth analysis of load profile data utilizing the bootstrap method, emphasizing the importance of data management and visualization in electricity consumption patterns. By exploring load profiles from different substations, this study leverages various techniques to predict and analyse data patterns and visualizations effectively. Using R language tools, the paper navigates through the bootstrap method, illustrating the approach with visualizations of yearly, weekly, and seasonal data distributions across three substations. It brings to light the variations in electricity demand and highlights the efficiency of the bootstrap method in evaluating errors in statistical measurements without relying on traditional assumptions. The research indicates that modern computing capabilities can effectively execute multiple iterations of the bootstrap method, offering valuable insights into statistical parameters, including variance and standard deviation. In addition, this work provides a framework for understanding energy usage trends over various timescales, essential for pinpointing periods of peak demand.

关键词： visualization bootstrap method correlation trend detection Load profiles

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visualization of potential differences in comprehension by distribution of notes and questions in online programming courses

Visualization of potential differences in comprehension by d...

引用

ieee International conference on Teaching, Assessment and Learning for Engineering (ieee TALE)

作者： Wang, Xiaonan Su, Yancong Sun, Yi Kiyomitsu, Hidenari Ohtsuki, Kazuhiro Shigyo, Kento Kobe Univ Grad Sch Intercultural Studies Kobe Hyogo Japan Xiamen Univ Technol Sch Design & Art Xiamen Peoples R China Kobe Inst Comp Grad Sch Informat Technol Kobe Hyogo Japan Hong Kong Univ Sci & Technol Acad Interdisciplinary Studies Hong Kong Peoples R China

ISBN: (纸本)9781665453318

This study presents an innovative approach to understanding differences in student comprehension in online programming courses by analyzing note-taking and questioning patterns and the distribution of grades. It enables instructing educators to understand learners' learning behaviors better. We designed and developed a system to support online learning that enables students to take notes and ask questions while viewing online courses and allows instructors to grasp overall feedback. We used a visualization method based on the location of notes and questions as they appear in the learning videos to enable instructors to capture their learners' learning better. Visualizing the distribution of notes and questions shows differences among students' note-taking patterns and learning strategies. The underlying comprehension patterns involved lead to differences in the patterns of notes and questions. We compared data from learners in different score bands to verify the correlation between note types and scores. By visualizing and comparing notes with the same type of correlation, the results show the correlation between note types and grades and the potential of the visualization method to analyze students' learning strategies and learning personalities. It provides valuable insights into student engagement, comprehension, and learning strategies, which can inform the development of more effective teaching methods. This study is relevant in the contemporary educational landscape, particularly as many institutions transition to online formats. Detecting student engagement and comprehension levels in these contexts is crucial.

关键词： Computer science education Asynchronous learning Comprehension visualization

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