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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331-340 订阅

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PacketEye (Automated sniffer and data analytics)

PacketEye (Automated sniffer and Data Analytics)

引用

Advancement in Computation & Computer Technologies (InCACCT), international conference on

作者： Pingal Saha Anusree Das Jyoti Khandelwal Department of Computer Science and Engineering University of Engineering & Management Jaipur Rajasthan

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

A tool called a packet sniffer is used to intercept and examine network traffic, which is crucial for contemporary network security and monitoring. This study presents a unified packet sniffing solution that can capture and analyze TCP, DNS, and HTTP traffic and more, whereas traditional research mainly concentrated on particular protocols or restricted applications. Clear graphs are used to display traffic trends after the tool aggregates packet data into 1-minute intervals. For instance, power fluctuations peak at approximately 1500 seconds, while packet rates stabilize at 800 packets per minute. This method improves visibility and security by increasing the effectiveness and efficiency of real-time monitoring and traffic analysis.

关键词： Fluctuations data analysis data visualization Telecommunication traffic Network security data aggregation Market research Real-time systems HTTP Monitoring

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ParkView: visualizing Monotone Interleavings

ParkView: Visualizing Monotone Interleavings

引用

Pacific (formerly Asia-Pacific APVIS) visualization Symposium

作者： Thijs Beurskens Steven Van Den Broek Arjen Simons Willem Sonke Kevin Verbeek Tim Ophelders Michael Hoffmann Bettina Speckmann TU Eindhoven TU Eindhoven Utrecht University ETH Zürich

ISBN: (数字)9798331505813

ISBN: (纸本)9798331505820

Merge trees are a powerful tool from topological data analysis that is frequently used to analyze scalar fields. The similarity between two merge trees can be captured by an interleaving: a pair of maps between the trees that jointly preserve ancestor relations in the trees. Interleavings can have a complex structure; visualizing them requires a sense of (drawing) order which is not inherent in this purely topological concept. However, in practice it is often desirable to introduce additional geometric constraints, which leads to variants such as labeled or monotone interleavings. Monotone interleavings respect a given order on the leaves of the merge trees and hence have the potential to be visualized in a clear and comprehensive *** this paper, we introduce ParkView: a schematic, scalable encoding for monotone interleavings. ParkView captures both maps of the interleaving using an optimal decomposition of both trees into paths and corresponding branches. We prove several structural properties of monotone interleavings, which support a sparse visual encoding using active paths and hedges that can be linked using a maximum of 6 colors for merge trees of arbitrary size. We show how to compute an optimal path-branch decomposition in linear time and illustrate ParkView on a number of real-world datasets.

关键词： Human computer interaction Hands visualization Image color analysis Network topology visual analytics Time series analysis data visualization Encoding Topology

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Dynamic Quality Management in Wind Power Construction: Integrating Digital Twins with BIM and IoT

Dynamic Quality Management in Wind Power Construction: Integ...

引用

Electronics, Energy Systems and Power Engineering (EESPE), IEEE international conference on

作者： Xiaodan Yuan Silu Wang Xu Zhao Jinzhou Electric Power Supply Company State Grid Liaoning Electric Power Supply Co. Ltd Jinzhou China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

The increasing complexity of wind power construction projects necessitates advanced quality management systems to address real-time challenges effectively. This paper introduces a digital twin-based framework integrating Building Information Modeling (BIM) and Internet of Things (IoT) technologies to enhance quality management. IoT sensors provide continuous, real-time data acquisition from personnel, materials, equipment, inspection, methods, and the environment, while BIM offers a spatial platform for visualization and analysis. The system's architecture includes automated data collection, parametric information integration, and predictive analytics, enabling comprehensive and proactive quality control. Preliminary results from pilot implementations highlight significant improvements in material efficiency, response times to quality issues, and stakeholder collaboration, demonstrating the system's potential for scalable and adaptive applications in wind power construction.

关键词： Scalability Collaboration Wind power generation Real-time systems Digital twins Internet of Things Time factors Stakeholders Predictive analytics Quality management

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Spatiotemporal-Aware visual Captioning using Vision-Language Pre-Training Model

Spatiotemporal-Aware Visual Captioning using Vision-Language...

引用

international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shuai Wu Weidong Yang Shuyan Wu School of Computer Science Fudan University China Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Current visual captioning technologies typically transform 3D/2D visual information into one-dimensional sequential data and employ language models to generate corresponding descriptions. This approach, however, compromises the spatiotemporal information in visual data, making it difficult for models to capture temporal variations and the relative spatial relationships between objects. To address this issue, we propose STPos-VC, a pre-trained vision-language model that maps visual information from the visual vector space to the textual vector space through a visual-text mapper and generates natural language descriptions using a decoder. The mapper incorporates three-dimensional rotational position encoding, which effectively preserves the relative spatiotemporal positional relationships. Furthermore, we pre-train the model on a mixed dataset comprising images and videos through a visual question-answering framework, enabling the model to perform well even with small sample sizes. Experimental results across multiple datasets demonstrate that, compared to existing methods, STPos-VC achieves superior performance in both general-purpose and domain-specific applications.

关键词： visualization Closed captioning Transforms Signal processing Encoding Vectors data models Spatiotemporal phenomena Speech processing Videos

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The P3 Explorer: An Open database of Performance, Portability, and Productivity

The P3 Explorer: An Open Database of Performance, Portabilit...

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Euromicro conference on Parallel, Distributed and Network-Based Processing

作者： Matthew A. Smith Steven A. Wright Zaman Lantra Gihan Mudalige Department of Computer Science University of York York UK Department of Computer Science University of Warwick Coventry UK

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

This paper introduces a web-based tool designed to organise and present visual representations of performance, portability, and productivity (P3) data from previously published scientific studies. The P3 Explorer operates as both an open repository of application performance data and a data dashboard, providing visual heuristic analyses of performance portability and developer productivity, created using Intel’s P3 Analysis library. The goal of the project is to create a community-led database of P3 studies to better inform application developers of alternative approaches to developing new applications that target high performance on diverse hardware, considering the productivity of the developer. In this paper, we evaluate our tool using a recently published study outlining a performance portable domain-specific language for particle-in-cell applications.

关键词： Productivity visualization Pipelines data visualization Metadata Libraries Reproducibility of results Hardware visual databases Domain specific languages

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Web-Based Framework for Evaluating Clustering Algorithms Across Multiple datasets

Web-Based Framework for Evaluating Clustering Algorithms Acr...

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Multi-Agent Systems for Collaborative Intelligence (ICMSCI), international conference on

作者： Gyanendar Kumar Tiwari Kshitij Singh Dorathi Jayaseeli J D Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

This research study develops a web-based framework to compare clustering algorithms based on multiple datasets, assess the performance of algorithmic based on dataset characteristics and clustering objectives. The framework designed to support such widely used algorithms such as KM, DBSCAN and Hierarchical Clustering, offers visual and quantitative analysis for performance comparison. This platform was designed to make it easier for users to try out various algorithms and different parameter settings and thus, help them to choose the best clustering methods for a range of data types. This work impacts that greater understanding of how effective clustering is based on different data structures and application contexts by providing a useful framework for data driven research and analysis.

关键词： Measurement visualization Statistical analysis Heuristic algorithms Industry applications Clustering algorithms data visualization Real-time systems Optimization Gaussian mixture model

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Leveraging National Science data Fabric Services to Train data Scientists 24

Leveraging National Science Data Fabric Services to Train Da...

引用

Proceedings of the SC '24 Workshops of the international conference on High Performance Computing, Network, Storage, and Analysis

作者： Michela Taufer Heberth Martinez Aashish Panta Paula Olaya Jack Marquez Amy Gooch Giorgio Scorzelli Valerio Pascucci University of Tennessee Knoxville USA University of Utah Salt Lake City USA

ISBN: (纸本)9798350355543

We document an interactive half-day tutorial in which participants explore the advanced applications of National Science data Fabric (NSDF) services and strategies for comprehensive scientific data analysis. Targeting researchers, students, developers, and scientists, the tutorial provides valuable insights into managing and analyzing large datasets, particularly those exceeding 100TB. Participants gain hands-on experience by constructing modular workflows, leveraging public and private data storage and streaming solutions, and deploying sophisticated visualization and analysis dashboards. The tutorial emphasizes NSDF's role in supporting visualization conference themes by providing scalable visualization and visual analytics solutions. Our tutorial includes an overview of NSDF's capabilities, addressing common data analysis challenges, and intermediate hands-on exercises using NSDF services for Earth science data. Advanced applications cover handling and visualizing massive datasets requiring high-resolution data management. By the end of the session, attendees have a deeper understanding of integrating NSDF services into their research workflows, enhancing data accessibility, sharing, and collaborative scientific discovery. Our tutorial aims to advance knowledge in data-intensive computing and empower participants to harness the full potential of NSDF in their respective fields.

关键词： data analysis

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NAV: A Comparative Analysis Tool for Nsight Systems GPU Traces 33

NAV: A Comparative Analysis Tool for Nsight Systems GPU Trac...

引用

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

作者： Shama, Ethan Grant, Ryan E. Queen's University Electrical and Computer Engineering Department KingstonON Canada

ISBN: (纸本)9798331524937

High-performance computing (HPC) and data centers increasingly rely on Graphics Processing Units (GPUs) in large supercomputers. Yet, this reliance poses challenges in quickly understanding the performance impacts of code changes. This paper introduces NAV, a versatile tool designed to rapidly analyze and compare GPU performance traces. Built upon NVIDIA's NsightTM Systems (NSYS), NAV enhances NSYS's capabilities by accelerating visualization for large traces, increasing the variety of data representation formats, and adding comparative analysis capabilities. Our tool, NAV, provides complimentary functions on top of NSYS to quickly access performance data and perform comparative analysis. NAV offers detailed visual and written representations of traces at various granularity levels and efficiently handles large trace files through parallelization. It extracts trace data 1.15 to 3.5 times faster than comparable NSYS recipes for typical developer trace sizes, automating the generation of valuable data representations and streamlining workload analysis. This paper outlines NAV's key features and functionalities, demonstrating its effectiveness through use cases that highlight its benefits for rapid application analysis and assessing the impact of code changes. © 2025 IEEE.

关键词： data visualization

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Adaptive Computer Vision Solutions for Individuals with Special Needs

Adaptive Computer Vision Solutions for Individuals with Spec...

引用

Computational Intelligence Approaches and Applications (ICCIAA), international conference on

作者： Issam Jebreen Shadi Nashwan Ahmad Al-Qerem Ali Mohd Ali Mohammad A Al Khaldy Mohammed Rajab Faculty of Information Technology Middle East University Jordan Computer Science Department Zarka University Jordan College of Engineering Technology Al-Balqa Applied University Jordan Business Intelligence Data Analytics University of Petra Amman Jordan University Headquarter University Of Anbar Iraq

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

With the rapid evolution of artificial intelligence (AI) and computer vision, assistive technologies have become increasingly adept at supporting individuals with special needs. This paper provides a comprehensive examination of two critical areas: AI-powered visual assistance systems for the visually impaired and sign language recognition and generation frameworks for the Deaf and hard-of-hearing communities. We review the latest research trends, algorithms, and tools, highlighting emerging deep learning architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and Transformers in both domains. We then propose a unified framework that leverages edge computing, multimodal learning, and advanced human-computer interaction (HCI) techniques to address challenges such as real-time object recognition, complex gesture capture, data scarcity, and cultural variations in sign languages. We further detail an experimental design and set of results that demonstrate the feasibility and benefits of these approaches, followed by a discussion of ethical considerations, limitations, and future directions. Our goal is to illustrate a path toward more inclusive AI systems that offer robust solutions for accessibility, ultimately bridging communication gaps and fostering independence for individuals with special needs [1]–[11].

关键词： Sign language Computer vision visualization Ethics visual impairment Assistive technologies Transformers Real-time systems Object recognition Artificial intelligence

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Automating Aeronautical Information Management: A Geospatial Big data Approach in India

Automating Aeronautical Information Management: A Geospatial...

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Integrated Communications, Navigation and Surveillance conference, ICNS

作者： Arvind V. Lal S. V. Satish Yogendra Rohilla Sandeep Mittal Bhuvanamitra S SatSure Analytics India Private Limited Bangalore India Airports Authority of India New Delhi India

ISBN: (数字)9798331534738

ISBN: (纸本)9798331534745

The Indian National Electronic Terrain Repository for Aviation, or iNetra, is a comprehensive geospatial big data platform designed to revolutionize aeronautical data management for the Airports Authority of India (AAI), which is the airport developer and sole Air Navigation Service Provider in India. SatSure developed this multi-module system, which helps transition from traditional paper-based processes to an automated, digital workflow aligned with international Civil Aviation Organization (ICAO) standards and recommended practices. The platform integrates advanced technologies, including high-resolution satellite imagery, PostgreSQL database management, and Geographic Information System (GIS) functionalities, for efficient data acquisition, processing, storage, and visualization. Some of the key modules include Electronic Terrain and Obstacle data (eTOD), Aerodrome Mapping database (AMDB), and Electronic Charting (eCharting), deployed across five international airports in India. iNetra addresses critical challenges in aeronautical data management by providing dynamic, time-stamped, and validated data ingestion capabilities. The global standards which the system upholds are supported by strong data security protocols, such as a 32-bit Cyclic Redundancy Check. Seamless data exchange, removal of redundant operations, and the support for transforming an Aeronautical Information Service into an Aeronautical Information Management and thus make iNetra mark a technological frontier in the evolution of aviation information management in India.

关键词： Technological innovation Automation Digital transformation Pipelines Manuals Big data Airports Geospatial analysis visual databases Artificial intelligence

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