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检索条件"任意字段=2025 International Conference on Visual Analytics and Data Visualization, ICVADV 2025"

共 614 条记录，以下是251-260 订阅

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Framework for Quick visuals Insight Discovery in the data Workflows

Framework for Quick Visuals Insight Discovery in the Data Wo...

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international conference on Computer and Communications Technologies (ICCCT)

作者： S Sivamurugan S Susila Sakthy Department of Artificial Intelligence and Data Science Sri Sairam Engineering College Chennai Department of Information Technology Sri Sairam Engineering College Chennai India

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

data-driven decision-making growth demands rapid frameworks to discover visual insights which bring value to data pipelines. Decision-making processes require time-sensitive visualization and interpretation because standard data analysis approaches handle limited amounts of data effectively. The survey investigates multiple frameworks and methodologies that improve visual analytics through interactive visualization methods and automated insights generation as well as large-scale data processing platforms. The research investigates modern visualization methods based on deep learning models as well as explainable AI (XAI) systems that produce insights and adaptive dashboards which are evaluated for their advantages and barriers. The survey analyses the problems that stem from handling large-scale data dimensions as well as maintaining interpretability and achieving optimal computation speeds. Future research focuses on generative AI as a tool to improve visualization methods and federated learning to maintain confidential analytics while edge computing provides immediate results. This paper gathers recent innovation progress to deliver researchers and practitioners complete understanding about developing visual insight discovery trends and innovations in data workflow applications.

关键词： Deep learning Surveys Technological innovation Accuracy data analysis Explainable AI visual analytics Decision making data visualization Real-time systems

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Leveraging visual analytics to Explore Bike Imbalance in Localised Operational Environments 6th

Leveraging Visual Analytics to Explore Bike Imbalance in L...

引用

6th international conference on communication and computational technologies, ICCCT 2024

作者： Mugabi, Samuel Onen, Simon Marvin, Ggaliwango Ndibatya, Innocent Makerere University Kampala Uganda

ISBN: (纸本)9789819774258

Bike-sharing platforms are becoming increasingly popular in urban transit systems worldwide. However, maintaining a balance between bike availability and user demand is crucial for a convenient user experience and operational efficiency. This study focuses on identifying bike imbalance within bike-sharing platforms, particularly the Digital Bikes service at Makerere University. The paper examines the presence of bike imbalance at a highly trafficked docking station within the platform and suggests using data visualisation and analytic methods to address it. The study proposes various metrics for detecting imbalance and uses data visualisations to clearly represent the surplus and deficits of bikes in a bike-sharing network. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bicycles

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FlintstonesSV++: Improving Story Narration using visual Scene Graph 8

FlintstonesSV++: Improving Story Narration using Visual Scen...

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8th international Workshop on Narrative Extraction From Texts, Text2Story 2025

作者： Kapuriya, Janak Buitelaar, Paul Insight Research Ireland Centre for Data Analytics Data Science Institute Univeristy of Galway Ireland

Recent advancements in text-to-image, text-to-video, and large language models have significantly enhanced the performance of various downstream tasks. In the field of Story visualization, models have been developed to generate coherent image sequences from storylines composed of multiple scenes. These innovations have largely relied on benchmark datasets such as FlintstonesSV and PororoSV, which provide essential resources for tasks like Story visualization and Story Continuation. However, our analysis identifies several limitations in the FlintstonesSV dataset that restrict the performance of models trained on it. To address these limitations, we introduce FlintstonesSV++, an enhanced version of the FlintstonesSV dataset. FlintstonesSV++ leverages visual Scene Graphs and Large Language Models to enrich storylines with factual details, further validated by human reviewers. By fine-tuning text-to-story generation models on FlintstonesSV++, we demonstrate substantial improvements, achieving a 5.2% average increase in alignment scores and a 5.72% boost in image generation quality compared to models trained on the original dataset. Moreover, a qualitative comparative analysis highlights the superior performance of FlintstonesSV++ compared to the original dataset. The FlintstonesSV++ dataset marks a significant advancement in enabling tasks such as Story visualization and Story Continuation. To support further research in story-based visual content generation, we made the code and dataset publicly available. © 2025 Copyright for this paper by its authors.

关键词： dataset Improvement Large Language Models Large Multimodal Models Narrative Resources Story Narrative Generation Storyline visualization visual Scene Graphs

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Enhancing Pavement Condition Assessment: A Comprehensive Review of Affordable Sensing Technologies for Cycle Tracks 11

Enhancing Pavement Condition Assessment: A Comprehensive Rev...

引用

11th international conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2025

作者： Garcia, Jeziel Antonio Ayala Shah, Syed Baig, Muhammad Hassam Qureshi, Waqar Shahid Ullah, Ihsan School of Computer Science University of Galway Galway Ireland Insight SFI Research Centre for Data Analytics University of Galway Galway Ireland

ISBN: (纸本)9789897587450

This paper explores the potential of low-cost sensing technologies for assessing the condition of cycling track pavement. As cycling gains popularity, the demand for efficient pavement maintenance solutions increases. Machine survey-based pavement condition assessment often relies on expensive, specialized equipment, which is not always suitable for cycle tracks due to limited budgets and accessibility, hence the need for low-cost solutions. The integration of low-cost sensing technologies and data collection, such as inertial measurement units (IMUs), low-cost imaging sensors, and crowdsourced data collection, presents a promising alternative for cycle track pavement surface assessment. This paper highlights the advantages of employing out-of-the-shelf devices such as smartphones with GPS, cameras, and IMU, or action cameras with GPS and IMU to collect images, their location, and vehicle vibration in a specific orientation. This data is then used to estimate pavement roughness, detect surface distress, and compute pavement surface condition. Literature reviews reveal a significant gap in the utilization of these technologies for cycle tracks, suggesting a promising area for further research and application. Furthermore, it proposes a software framework for data collection and visualization to combine these technologies to enhance the efficiency and reliability of pavement assessment for cycling infrastructure at a lower cost than machine-based pavement assessment and faster and more quantitative than manual surveys. This paper emphasizes the need for more practical and scalable solutions that support the maintenance of sustainable transportation systems. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Budget control

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From Local to Remote: Scaling VisIVO visual analytics for Large-Scale Astrophysical data visualization

From Local to Remote: Scaling VisIVO Visual Analytics for La...

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Euromicro conference on Parallel, Distributed and Network-Based Processing

作者： Giuseppe Tudisco Fabio Vitello Eva Sciacca Ugo Becciani Osservatorio Astrofisico di Catania Istituto Nazionale di Astrofisica (INAF) Catania Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

As the Square Kilometre Array (SKA) radio telescopes approach full operation, they are set to generate hundreds of petabytes of data annually, offering unprecedented resolution and detail in astrophysical observations. This massive influx of data presents significant challenges in terms of storage, processing, analysis and visualization. Scientific visualization becomes essential in this context, enabling researchers to interpret complex, high-dimensional datasets and extract valuable insights. This paper presents the latest developments of VisIVO visual analytics, an interactive visualization tool that is evolving to meet the needs of the SKA and similar large-scale astrophysical projects such as the James Webb Space Telescope and the Atacama Large Millimeter/submillimeter Array (ALMA). Originally designed as a desktop application, VisIVO is transitioning to a client-server architecture, allowing it to efficiently run remote visualization pipelines on remote servers. This shift significantly enhances the tool’s ability to handle large scale datasets, facilitating real-time, interactive analysis of complex data. This work also explores how VisIVO visual analytics can distribute computational workloads across multiple nodes in high-performance computing (HPC) clusters for parallel visualization pipelines, enabling advanced and interactive techniques to derive meaningful insights from the vast volumes of data generated by next-generation observatories.

关键词： Radio astronomy visual analytics High performance computing Pipelines data visualization Computer architecture Telescopes Arrays Servers Usability

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Enhancing Observability: Real-Time Application Health Checks 2nd

Enhancing Observability: Real-Time Application Health Checks

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28th international conference on Enterprise Design Operations and Computing

作者： Eichhorn, Tim Moreira, Joao Luiz Rebelo Pires, Luis Ferreira Meertens, Lucas Univ Twente Drienerlolaan 5 NL-7522 NB Enschede Netherlands CAPE Grp Transportctr 16 NL-7547 RW Enschede Netherlands

ISBN: (纸本)9783031790584;9783031790591

Log management and application health monitoring practices are cumbersome and often still require significant human intervention to prevent inaccurate data and information. Existing technologies like Elasticsearch and Grafana offer opportunities to automate and improve these practices. This paper reports on a design solution aimed at enhancing log categorization, anomaly detection, and real-time application health reporting for CAPE Groep's service application. The proposed solution leverages Elasticsearch's Machine Learning capabilities and Grafana's dynamic visualization tools, alongside a newly developed dashboard named Horus, to centralize log data and automate monitoring processes. Preliminary results indicate that the proposed solution significantly improves the accuracy and timeliness of health reports, reduces manual intervention, and provides comprehensive real-time insights into application performance. This paper outlines the requirements, architectural design, and phased implementation plan, demonstrating the potential to streamline operations, enhance service delivery, and support future more stringent scalability requirements.

关键词： Observability Application monitoring Log Management Log analytics Elasticsearch Dashboard

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Conceptualizing Change Activities in Process Mining 2nd

Conceptualizing Change Activities in Process Mining

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28th international conference on Enterprise Design Operations and Computing

作者： Knoblich, Steven Pfahlsberger, Lukas Mendling, Jan Humboldt Univ Rudower Chaussee 25 D-12489 Berlin Germany

ISBN: (纸本)9783031790584;9783031790591

In an increasingly dynamic world, business processes must be able to respond to frequently occurring and random changes during their execution. Consequently, this means that the process models must be able to handle this complexity and enable process analysts to derive the right conclusions quickly. However, current approaches in the field of process mining do not distinguish between process activities associated with change and those with routine. This condition leads to more complicated, overloaded, and sometimes misguided process visualizations that make it difficult for analysts to evaluate them. In this paper, we address the research problem by conceptualizing a new type of process activity that we call change activity which we base on causal knowledge. We thereby extend the causal process mining approach with another important aspect for handling random occurrences of events. We evaluated our findings through a survey of process mining experts from research and practice. Our results indicate that a dedicated visualization of change activities reduces the complexity of process visualizations. In addition, unimportant information is hidden and important information is highlighted so that analysts can make better assessments.

关键词： Change Activities Causal Process Mining visual analytics

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CiteSpace-Based Knowledge Mapping Analysis of Green Logistics Research in China 11th

CiteSpace-Based Knowledge Mapping Analysis of Green Logistic...

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11th international conference on Energy Engineering and Environmental Engineering

作者： Chen, Ningning Song, Shiyuan Xie, Yu Zhang, Shuo Jinan Univ Sch Management Sci & Engn Jinan 250022 Shandong Peoples R China China Railway 14th Bur Grp Logistics Corp Ltd Tianjin 300450 Peoples R China

ISBN: (纸本)9783031762109;9783031762086;9783031762079

In this study, 557 journal articles on the topic of green logistics included in the CNKI database between 2001 and 2023 were subjected to visualization and analysis using CiteSpace software. By analyzing the number of articles published in recent years, the source of literature, the co-occurrence of keywords, and the clustering, a knowledge map of this field of research in China was constructed. The findings of the study indicate that the collaboration between authors and institutions in this research domain in China is not yet characterized by a high level of proximity, exhibiting a tendency towards extensive dispersion and limited concentration. The research focus has gradually shifted from the theoretical to the practical level of exploration over time. A summary and analysis of the emergent words reveals that the dominant research directions in this field are the circular economy and the green economy. Additionally, the aggregation of the logistics industry represents a novel research topic.

关键词： Green logistics CiteSpace Scientific knowledge graph visual analytics

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Enabling Collaboration and Empowering data-Driven Decisions for Well Interventions Through the Adoption of a Fully Integrated, Cloud-Based data Delivery Platform

Enabling Collaboration and Empowering Data-Driven Decisions ...

引用

2025 international Petroleum Technology conference, IPTC 2025

作者： Tymons, T. Lutchman, D. Lorwongngam, A. Author, F.G. Scott, C. EV Offshore Limited Aberdeen United Kingdom BP Hess Corporation Kuala Lumpur Malaysia

ISBN: (纸本)9781959025436

Whether oil and gas, geothermal, solution mining or capture and disposal, the process of delivering, managing and optimizing wells is a highly data-driven process, and engineers use data to support decision making relating to the design and operation of wells for a range of purposes including performance, longevity, risk management, and safety. While the quality and variety of data types and sources has increased significantly over time, the systems employed to manage this data have, until recently, placed limitations as to how data can be used, and the value of the information that can be extracted from it as a result. This paper will demonstrate the benefits and value created by the application of an integrated cloud-based data storage, visualization and analysis platform, to the management and optimization of asset integrity and production performance. The paper will focus on real-world applications and case studies to reveal how the information system can be used to assist management decision-making across the complete life-cycle of critical assets and infrastructure. We will reveal how downhole data is transmitted directly from field locations to a cloud-based platform where it is securely stored and catalogued, where it is instantly available to an access-controlled user group, from any location globally via a standard web browser. The system enables immediate on-screen viewing and interaction with the host data. If required, further information may be derived through the integration of multiple datasets and/or data processing and computation, with detailed statistical analysis provided by integrated data analytics and reporting modules. Through the presentation of case studies, and comparison with conventional workflows, we will demonstrate how the implementation of an end-to-end digital data delivery process can be used to connect field and office locations, thereby enabling critical information to be disseminated to multiple stakeholders simultaneously. We

关键词： Risk management

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From Local to Remote: Scaling VisIVO visual analytics for Large-Scale Astrophysical data visualization 33

From Local to Remote: Scaling VisIVO Visual Analytics for La...

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33rd Euromicro international conference on Parallel, Distributed, and Network-Based Processing, PDP 2025

作者： Tudisco, Giuseppe Vitello, Fabio Sciacca, Eva Becciani, Ugo Osservatorio Astrofisico di Catania Catania Italy

ISBN: (纸本)9798331524937

As the Square Kilometre Array (SKA) radio telescopes approach full operation, they are set to generate hundreds of petabytes of data annually, offering unprecedented resolution and detail in astrophysical observations. This massive influx of data presents significant challenges in terms of storage, processing, analysis and visualization. Scientific visualization becomes essential in this context, enabling researchers to interpret complex, high-dimensional datasets and extract valuable insights. This paper presents the latest developments of VisIVO visual analytics, an interactive visualization tool that is evolving to meet the needs of the SKA and similar large-scale astrophysical projects such as the James Webb Space Telescope and the Atacama Large Millimeter/submillimeter Array (ALMA). Originally designed as a desktop application, VisIVO is transitioning to a client-server architecture, allowing it to efficiently run remote visualization pipelines on remote servers. This shift significantly enhances the tool's ability to handle large scale datasets, facilitating real-time, interactive analysis of complex data. This work also explores how VisIVO visual analytics can distribute computational workloads across multiple nodes in high-performance computing (HPC) clusters for parallel visualization pipelines, enabling advanced and interactive techniques to derive meaningful insights from the vast volumes of data generated by next-generation observatories. © 2025 IEEE.

关键词： Cluster computing

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