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

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visual Analytics for Profiling Land Use Changes 36

Visual Analytics for Profiling Land Use Changes

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36th SIBGRAPI conference on Graphics, Patterns and Images (SIBGRAPI)

作者： Santos, Claudio Hosseini, Maryam Rulff, Joao Miranda, Fabio Wilson, Luc Silva, Claudio Ferreira, Nivan Lage, Marcos Univ Fed Fluminense Niteroi RJ Brazil MIT Cambridge MA USA NYU New York NY USA Univ Illinois Chicago IL USA Kohn Pedersen Fox Associates PC New York NY USA Univ Fed Pernambuco Recife Brazil

ISBN: (纸本)9798350338737;9798350338720

The growth of cities calls for regulations and zoning rules on how each piece of urban space will be used. Tracking land use can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of the shape and the attributes of land units. The complex nature of land-use data, however, makes the analysis of such data challenging and time-consuming. To address these challenges, we propose URBAN CHRONICLES, a visual analytics system that enables interactive exploration of land-use changes. Using New York City's Primary Land Use Tax Lot Output (PLUTO), we show the system's capabilities to explore the data from several years at different scales. URBAN CHRONICLES supports on-the-fly aggregation and filtering operations that leverage the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. Finally, we demonstrate the system's utility through case studies that analyze the impact of Hurricane Sandy on land use attributes and the effects of rezoning plans in Brooklyn.

关键词： visual analytics

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Navigating Exascale Operational data Analytics: From Inundation to Insight

Navigating Exascale Operational Data Analytics: From Inundat...

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2024 Workshops of the International conference for High Performance Computing, Networking, Storage and analysis, SC Workshops 2024

作者： Shin, Woong Osborne, Tim Karimi, Ahmad Maroof Palumbo, Rachel May, Alex Lester, Corwin Hines, Jesse Sattar, Naw Safrin Huk, Leah Simmerman, Scott Brewer, Wesley Miller, Jeffrey Adamson, Ryan Kuchar, Olga Prout, Ryan Wang, Feiyi Atchley, Scott Oral, Sarp Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350355543

In this paper, we address the challenges in achieving sustainable data-driven efficiency by providing a detailed exploration of the end-to-end operational data analytics (ODA) framework that evolved through two generations of supercomputer systems at the Oak Ridge Leadership Computing Facility (OLCF). This framework addresses large data streams ingested from heavily instrumented HPC environment that accumulates multi-terabytes per day. We outline the multifaceted data life cycle across HPC procurement, operations, and research & development, identifying key obstacles and design decisions that shape effective strategies in building and supporting data pipelines end-to-end. By sharing key insights and lessons learned from our experience, we offer recommendations for the HPC community on enabling sustainable operational data analytics and beyond. Our contributions aim to bridge the gap between potential and real benefits of operational data, guiding future efforts towards integrated and sustainable operational intelligence in high-performance computing environments. © 2024 IEEE.

关键词： data Analytics data Governance HPC Post-Exascale Challenges Machine Learning Applications Monitoring Operational data Analytics Telemetry visual Analytics

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Task-based Quantitative Evaluation of the Concordance Mosaic visualization 26

Task-based Quantitative Evaluation of the Concordance Mosaic...

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26th International conference Information visualisation (iv)

作者： Sheehan, Shane Masoodian, Masood Luz, Saturnino Univ Edinburgh Usher Inst Edinburgh Scotland Aalto Univ Sch Arts Design & Architecture Espoo Finland

ISBN: (纸本)9781665490078

Researchers working in areas such as lexicography, translation studies, and computational linguistics, use a combination of automated and semi-automated tools to analyze the content of text corpora. Concordancing - or the arranging of passages of a textual corpus in alphabetical order according to user-defined keywords - is one of the oldest and still most widely used forms of text analysis. Concordance Mosaic is an interactive concordance visualization which emphasises quantitative information such as word frequency. While Concordance Mosaic is in active use by humanities scholars, no quantitative evaluation of the technique exists. In this paper, the Concordance Mosaic is quantitatively evaluated in comparison to a typical concordance browser. The comparison is evaluated using speed and accuracy on identified corpus analysis actions.

关键词： visualization in humanities text visualization document data visualization visual knowledge discovery quantitative evaluation

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Vanessa : visual Connotation and Aesthetic Attributes Understanding Network for Multimodal Aspect-based Sentiment analysis

Vanessa : Visual Connotation and Aesthetic Attributes Unders...

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2024 conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Xiao, Luwei Mao, Rui Zhang, Xulang He, Liang Cambria, Erik School of Computer Science and Technology East China Normal University Shanghai China College of Computing and Data Science Nanyang Technological University Singapore

ISBN: (纸本)9798891761681

Prevailing research concentrates on superficial features or descriptions of images, revealing a significant gap in the systematic exploration of their connotative and aesthetic attributes. Furthermore, the use of cross-modal relation detection modules to eliminate noise from comprehensive image representations leads to the omission of subtle contextual information. We present Vanessa, a visual connotation and aesthetic Attributes understanding network for multimodal aspect-based sentiment analysis. It incorporates a multi-aesthetic attributes aggregation (MA3) module that models intra- and inter-dependencies among bi-modal representations as well as emotion-laden aesthetic attributes. Moreover, we devise a self-supervised contrastive learning framework to explore the pairwise relevance between images and text via the Gaussian distribution of their CLIP scores. By dynamically clustering and merging multimodal tokens, Vanessa effectively captures both implicit and explicit sentimental cues. Extensive experiments on two widely adopted benchmarks verify Vanessa's effectiveness. © 2024 Association for Computational Linguistics.

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visualization analysis of Metaverse Research Situation Based on CiteSpace 2

Visualization Analysis of Metaverse Research Situation Based...

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2nd International conference on Frontiers of Communications, Information System and data Science, CISDS 2023

作者： Zhu, Weiqiao Li, Defang Guangzhou Maritime University Guangzhou China Guangzhou Vocational College of Technology &Business Guangzhou China

ISBN: (纸本)9798350381474

Using the CiteSpace visual knowledge map analysis method, this paper conducts a comprehensive quantitative analysis of the literature on metaverse research from 2000 to 2023, which was collected from the Web of Science database. The analysis focuses on the time distribution, spatial distribution, research hotspots, and frontier trends. Currently, both domestic and international research in the field of metaverse is experiencing a prosperous period of theoretical deliberation and practical exploration. The cutting-edge research topics are primarily centered around virtual reality, digital twinning, blockchain, and other related fields. Additionally, there is still a need for further development in terms of technical layout, standards, and regulations. © 2023 IEEE.

关键词： Virtual reality

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Saliency of Omnidirectional Videos with Different Audio Presentations: Analyses and dataset 15

Saliency of Omnidirectional Videos with Different Audio Pres...

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15th International conference on Quality of Multimedia Experience (QoMEX) - Towards Sustainable and Inclusive Multimedia Experiences

作者： Singla, Ashutosh Robotham, Thomas Bhattacharya, Abhinav Menz, William Habets, Emanuel A. P. Raake, Alexander TU Ilmenau Audiovisual Technol Grp Ilmenau Germany Int Audio Labs Erlangen Erlangen Germany

ISBN: (纸本)9798350311730

There is an increased interest in understanding users' behavior when exploring omnidirectional (360 degrees) videos, especially in the presence of spatial audio. Several studies demonstrate the effect of no, mono, or spatial audio on visual saliency. However, no studies investigate the influence of higher-order (i.e., 4th-order) Ambisonics on subjective exploration in virtual reality settings. In this work, a between-subjects test design is employed to collect users' exploration data of 360 degrees videos in a free-form viewing scenario using the Varjo XR-3 Head Mounted Display, in the presence of no, mono, and 4th-order Ambisonics audio. Saliency information was captured as head-saliency in terms of the center of a viewport at 50 Hz. For each item, subjects were asked to describe the scene with a short free-verbalization task. Moreover, cybersickness was assessed using the simulator sickness questionnaire at the beginning and at the end of the test. The head-saliency results over time show that with the presence of higher-order Ambisonics audio, subjects concentrate more on the directions sound is coming from. No influence of audio scenario on cybersickness scores was observed. From the analysis of the verbal scene descriptions, it was found that users were attentive to the omnidirectional video, but only for the 'no audio' scenario provided minute and insignificant details of the scene objects. The audiovisual saliency dataset is made available following the open science approach already used for the audiovisual scene recordings we previously published. The data is sought to enable training of visual and audiovisual saliency prediction models for interactive experiences.

关键词： visual saliency audiovisual saliency spatial audio 360 degrees video 4th-order Ambisonics

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Design of a University Book Push System Based on Big data 4

Design of a University Book Push System Based on Big Data

引用

4th International conference on Computer Science and Management Technology, ICCSMT 2023

作者： Sheng, Liqiang Xia, Hui Li, Xiangquan School of Information Engineering Jingdezhen University Jingdezhen333000 China

ISBN: (纸本)9798400709517

In response to the existing university book recommendation systems that mostly recommend readers based on library resources and lack exploration of recommended books, this paper proposes a system service architecture that accurately pushes both readers and libraries simultaneously. The system is designed using technologies such as web spiders, big data, NLP, and visual analysis. The system integrates reader data entry, web crawler, user profile, book similarity measurement, and intelligent push functions. Book managers can use the system to push books accurately and discover recommended books. The system fully utilizes book attribute data and reader attribute data, avoiding common cold start issues in recommendation systems, and providing support for improving the service level of the library and scientifically allocating collection resources. © 2023 ACM.

关键词： Recommender systems

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visual Communication Design of Multi-dimensional Image visualization Fusion System Based on Wavelet Transform 3

Visual Communication Design of Multi-dimensional Image Visua...

引用

3rd IEEE International conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Li, Wenjie Changchun University of Chinese Medicine Art Education Teaching and Research Section of Marxism College Changchun130000 China

ISBN: (纸本)9798350398410

With the rapid development of remote sensing technology, multi-source remote sensing image fusion has become one of the hot issues in remote sensing field in recent years. Aiming at the poor edge registration of images obtained by conventional remote sensing image fusion system, a multidimensional visual fusion system of remote sensing images based on visual communication is designed. CABAC encoder is selected to make data flow and control flow cooperate with each other to obtain feedback data. However, the rapid increase of data also increases the difficulty of comprehensive observation, because the image data obtained by different sensors have their own differences and limitations in spectral information and spatial details, so we want to bring the fusion technology into this field, expand the working range of the system, improve the reliability of the system, obtain a more efficient representation of information and improve the cost performance of the system. Image fusion technology plays an extremely important role in remote sensing, medicine, natural resources exploration, marine resources management, topography analysis, biology and other fields. The left and right focused images, infrared images and visible images are used for simulation experiments, and the objective evaluation indexes of images are used to verify the feasibility of this method. © 2023 IEEE.

关键词： Wavelet transforms

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Extending Instance Space analysis to Algorithm Configuration Spaces

Extending Instance Space Analysis to Algorithm Configuration...

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2024 Genetic and Evolutionary Computation conference Companion, GECCO 2024 Companion

作者： Rasulo, Anthony Smith-Miles, Kate Muñoz, Mario Handl, Julia López-Ibáñez, Manuel The University of Manchester The University of Melbourne Manchester United Kingdom The University of Manchester Manchester United Kingdom

ISBN: (纸本)9798400704956

This paper describes an approach for deriving visual insights about the joint relationship between algorithm performance, algorithm parameters, and problem instance features. This involves the combined analysis and exploration of a 2D instance space, to which instances from some problem space are projected, and a 2D configuration space, to which (algorithm) configurations are projected. Extending on the dimensionality reduction problem solved in Instance Space analysis, we define an optimisation problem for finding projections to these two spaces, with an interpretable relationship between them. Then, we describe the tools developed for probing those spaces in an investigation of the question: What characterises the algorithm configurations that perform best on a selected group of instances (or vice versa)? We demonstrate the use of these tools on synthetic data with known ground truth. © 2024 held by the owner/author(s).

关键词： Consensus algorithm

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Understanding Plant Leaf Diseases: A Review, analysis, exploration of Techniques and Technologies

Understanding Plant Leaf Diseases: A Review, Analysis, Explo...

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2025 International conference on visual Analytics and data visualization, ICVADV 2025

作者： Nagalakshmi, Thirumalasetty Sambasivudu, M. Sai, Thota Siva Ratna Dept. of Cse Telangana India

ISBN: (纸本)9798331521394

Modern agriculture relies on plant leaf disease detection to reduce crop losses and guarantee food security. This study takes a look at the three main types of methods used to identify plant leaf diseases: conventional methods, techniques based on Machine Learning (ML), and methodology based on Deep Learning (DL). Although they provide essential insights, the scalability and precision of traditional methods-which depend on chemical analysis, image processing, and human inspection-are severely lacking. ML techniques, which make use of algorithms such as Random Forests (RF) and Support Vector Machines (SVM), automate feature-based categorization, which improves detection. Automated disease identification with high accuracy has recently been made possible by DL, which uses sophisticated methods like semantic segmentation, object recognition, and transfer learning in conjunction with architectures like Convolutional Neural Networks (CNNs). This study examines all of these approaches in detail, comparing and contrasting their advantages, disadvantages, and possible uses. Emerging developments, such as eXplainable Artificial Intelligence (XAI) and Internet of Things (IoT)-based systems, are also highlighted in the discussion, with an emphasis on how they will influence smart and sustainable agriculture in the future. © 2025 IEEE.

关键词： Semantic Segmentation

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