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arXiv 2021年

作者： Durrive, Jean-Baptiste Lesaffre, Pierre Ghosh, Tuhin Blancard, Bruno Regaldo-Saint Institut de Recherche en Astrophysique et Planétologie Université Toulouse III - Paul Sabatier Observatoire Midi-Pyrénées Centre National de la Recherche Scientifique UMR5277 France Laboratoire de Physique de l’ÉNS École Normale Supérieure de Paris Centre National de la Recherche Scientifique FR684 Université Paris Diderot-Paris 7 Sorbonne Université UMR8023 France Centre for Mathematical Plasma-Astrophysics Celestijnenlaan 200B Leuven3001 Belgium KU Leuven Belgium School of Physical Sciences National Institute of Science Education and Research HBNI JatniOdisha752050 India Observatoire de Paris PSL University Sorbonne Université LERMA Paris75014 France

We investigate the potential of a recently proposed model for 3D compressible MHD turbulence (Chevillard et al. 2010;Durrive et al. 2021) to be used as a tool to characterize statistically 2D and 3D turbulent data. This model is parametrized by a dozen of free (intuitive, physically motivated) parameters, which control the statistics of the fields (density, velocity and magnetic fields). The present study is a proof of concept study: (i) we restrict ourselves to the incompressible hydrodynamical part of the model, (ii) we consider as data centroid velocity maps, and (iii) we let only three of the free parameters vary (namely the correlation length, the Hurst parameter and the intermittency parameter). Within this framework, we demonstrate that, given a centroid velocity map, we can find in an automated manner (i.e. by a Markov Chain Monte Carlo analysis) values of the parameters such that the model resembles the given map, i.e. which reproduces its statistics fairly well. Hence, thanks to this procedure, one may characterize statistically, and thus compare, various turbulent data. In other words, we show how this model may be used as a metric to compare observational or simulated data sets. In addition, because this model is numerically particularly fast (nearly 500 times faster than the numerical simulation we use to generate our reference data) it may be used as a surrogate model. Finally, by this process we also initiate the first systematic exploration of the parameter space of this model. Doing so, we show how the parameters impact the visual and the statistical properties of centroid velocity maps, and exhibit the correlations between the various parameters, providing new insight into the model. Copyright © 2021, The Authors. All rights reserved.

关键词： Turbulence

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BD 2019 - Proceedings of the 3rd conference on Biographical data in a Digital World 2019

BD 2019 - Proceedings of the 3rd Conference on Biographical ...

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3rd conference on Biographical data in a Digital World, BD 2019

The proceedings contain 10 papers. The topics discussed include: a quantitative analysis of biographical data from Ainm, the Irish-language biographical database;reconstructing data for modelling collective biography: a case of zemstvo deputies in Russia in the second half of XIX century;linked data - a paradigm shift for publishing and using biography collections on the semantic web;data exchange in practice: towards a prosopographical API;mining the biographical dictionary of Republican China. From print to network exploration;large-scale data harvesting for biographical data;reassembling the lives of Finnish prisoners of the second world war on the semantic web;and exiled but not forgotten: investigating commemoration of musicians in Vienna after 1945 through visual analytics.

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SilkViser: A visual Explorer of Blockchain-based Cryptocurrency Transaction data

SilkViser: A Visual Explorer of Blockchain-based Cryptocurre...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Zengsheng Zhong Shuirun Wei Yeting Xu Ying Zhao Fangfang Zhou Feng Luo Ronghua Shi School of Computer Sciences and Engineering Central South University China Chongqing Engineering Technology Research Center for Information Management in Development Chongqing Technology and Business University China

ISBN: (数字)9781728180090

ISBN: (纸本)9781728180106

Many blockchain-based cryptocurrencies provide users with online blockchain explorers for viewing online transaction data. However, traditional blockchain explorers mostly present transaction information in textual and tabular forms. Such forms make understanding cryptocurrency transaction mechanisms difficult for novice users (NUsers). They are also insufficiently informative for experienced users (EUsers) to recognize advanced transaction information. This study introduces a new online cryptocurrency transaction data viewing tool called SilkViser. Guided by detailed scenario and requirement analyses, we create a series of appreciating visualization designs, such as paper ledger-inspired block and blockchain visualizations and ancient copper coin-inspired transaction visualizations, to help users understand cryptocurrency transaction mechanisms and recognize advanced transaction information. We also provide a set of lightweight interactions to facilitate easy and free data exploration. Moreover, a controlled user study is conducted to quantitatively evaluate the usability and effectiveness of SilkViser. Results indicate that SilkViser can satisfy the requirements of NUsers and EUsers. Our visualization designs can compensate for the inexperience of NUsers in data viewing and attract potential users to participate in cryptocurrency transactions.

关键词： Blockchain Bitcoin data visualization Tools data analysis visual analytics data mining

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Tracing Identity exploration Trajectories with Quantitative Ethnographic Techniques: A Case Study 1st

Tracing Identity Exploration Trajectories with Quantitative ...

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1st International conference on Quantitative Ethnography, ICQE 2019

作者： Foster, Aroutis Shah, Mamta Barany, Amanda Talafian, Hamideh Drexel University PhiladelphiaPA19104 United States Elsevier Inc. PhiladelphiaPA19103 United States

ISBN: (纸本)9783030332310

This paper is situated in a 5-year NSF CAREER project awarded to test and refine Projective Reflection (PR) as a theoretical and methodological framework for facilitating learning as identity exploration in play-based environments. 54 high school students engaged in Virtual City Planning, an iteratively refined course that provided systematic and personally-relevant opportunities for play, curricular, reflection and discussion activities in Philadelphia Land Science, a virtual learning environment, and in an associated curriculum enacted in a STEM museum-classroom. In-game logged data and in-class student data were examined using Epistemic Network analysis. An illustrative case study revealed visual and interpretive patterns in students’ identity exploration. The change was reflected in their knowledge, interest and valuing, self-organization and self-control, and self-perception and self-definition (KIVSSSS) in relation to the roles explored from the start of the intervention (Starting Self), during (Exploring role-specific Possible Selves), and the end (New Self). © Springer Nature Switzerland AG 2019.

关键词： Students

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Sentiment analysis from Images of Natural Disasters 20th

Sentiment Analysis from Images of Natural Disasters

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20th International conference on Image analysis and Processing (ICIAP)

作者： Hassan, Syed Zohaib Ahmad, Kashif Al-Fuqaha, Ala Conci, Nicola Univ Trento Trento Italy Hamad Bin Khalifa Univ Doha Qatar

ISBN: (纸本)9783030306458;9783030306441

Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather depends on the application and the end-users. In this article, we tackle a specific facet of social media data processing, namely the sentiment analysis of disaster-related images by considering people's opinions, attitudes, feelings and emotions. We analyze how visual sentiment analysis can improve the results for the end-users/beneficiaries in terms of mining information from social media. We also identify the challenges and related applications, which could help defining a benchmark for future research efforts in visual sentiment analysis.

关键词： Sentiment analysis Natural disasters Multi-label classification CNNs Social media

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Total Technology Space Map as a Digital Platform 52

Total Technology Space Map as a Digital Platform

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52ndHawaii International conference on System Sciences (HICSS)

作者： Luo, Jianxi Singapore Univ Technol & Design SUTD SUTD MIT Int Design Ctr Data Driven Innovat Lab Singapore Singapore

ISBN: (纸本)9780998133126

A strand of recent studies utilized complete patent databases and classification systems to construct large network maps of patent technology classes, which might approximate the total technology space. It has been argued that such maps are useful for competitive intelligence analysis, technology road mapping, innovation decision support, and so on in the literature. In this paper, we illustrate the InnoGPS system to integrate such a map with various map-based visual analytic functions for technology navigation, positioning, neighborhood exploration, path finding and information retrieval. These analytics are either descriptive, predictive or prescriptive. During the process of developing InnoGPS, we have conceived a wide spectrum of other potential applications of the total technology space map for consumers, business, education and so on. These possibilities together with the difficulty to construct an accurate technology space representation suggest the strategic value to develop the total technology space map as a digital platform for any applications to discover, manage or represent any data, information and knowledge related to technologies, and to nurture an ecosystem of developers and users.

关键词： Competitive intelligence

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PLMSys: A Cloud Monitoring System Based on Cluster Performance and Container Logs 1

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13th International conference on Cloud Computing, CLOUD 2020, held as part of the Services conference Federation, SCF 2020

作者： Sun, Yongzhong Ye, Kejiang Xu, Cheng-Zhong Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China State Key Laboratory of IoT for Smart City University of Macau China

ISBN: (数字)9783030596354

ISBN: (纸本)9783030596347

Docker, a kind of lightweight virtualization technology which has the characteristics of resource isolation, rapid deployment and low cost, is widely used in the construction of the cloud services. Docker-based containers has become the important basis of core cloud businesses. In order to manage the large-scale cloud cluster and enforce the quality of cloud services for consumers, monitoring mechanism for the container-based clouds are indispensable. In this paper, we design and implement a cloud monitoring system - PLMSys based on cluster performance and container logs. It provides the following functions: i) Multi-dimensional resources monitoring. PLMSys can monitor the running states of the cluster hosts and containers, including the utilization of CPU, memory, disk and other resources. ii) Container log collection. PLMSys can centrally collect the logs generated by all containers of the cluster. iii) Rule-based exception alerts. PLMSys allows users to define the abnormal state of the hosts and containers by creating rules, and provides multiple alerting methods. iv) Workload analysis and prediction. PLMSys extracts the descriptive statistics from the cluster workloads and uses the time series models to predict the future workloads. v) data monitoring visualization. The system uses rich visual charts to reflect the running states of cluster hosts and containers. By using PLMSys, users can better manage cluster hosts and containers. © 2020, Springer Nature Switzerland AG.

关键词： data visualization

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Self-Supervised Learning of Video-Induced visual Invariances

Self-Supervised Learning of Video-Induced Visual Invariances

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Michael Tschannen Josip Djolonga Marvin Ritter Aravindh Mahendran Neil Houlsby Sylvain Gelly Mario Lucic Google Research Brain Team

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

We propose a general framework for self-supervised learning of transferable visual representations based on Video-Induced visual Invariances (VIVI). We consider the implicit hierarchy present in the videos and make use of (i) frame-level invariances (e.g. stability to color and contrast perturbations), (ii) shot/clip-level invariances (e.g. robustness to changes in object orientation and lighting conditions), and (iii) video-level invariances (semantic relationships of scenes across shots/clips), to define a holistic self-supervised loss. Training models using different variants of the proposed framework on videos from the YouTube-8M (YT8M) data set, we obtain state-of-the-art self-supervised transfer learning results on the 19 diverse downstream tasks of the visual Task Adaptation Benchmark (VTAB), using only 1000 labels per task. We then show how to co-train our models jointly with labeled images, outperforming an ImageNet-pretrained ResNet-50 by 0.8 points with 10× fewer labeled images, as well as the previous best supervised model by 3.7 points using the full ImageNet data set.

关键词： Videos Task analysis visualization Adaptation models data models Benchmark testing Image representation

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CONTRAVIS: Contrastive and visual Topic Modeling for Comparing Document Collections 19

CONTRAVIS: Contrastive and Visual Topic Modeling for Compari...

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World Wide Web conference (WWW)

作者： Le, Tuan V. M. Akoglu, Leman Carnegie Mellon Univ H John Heinz III Coll Pittsburgh PA 15213 USA

ISBN: (纸本)9781450366748

Given posts on 'abortion' and posts on 'religion' from a political forum, how can we find topics that are discriminative and those in common? In general, (1) how can we compare and contrast two or more different (labeled') document collections? Moreover, (2) how can we visualize the data (in 2-d or 3-d) to best reflect the similarities and differences between the collections? We introduce (to the best of our knowledge) the first contrastive and visual topic model, called CONTRAVIS, that jointly addresses both problems: (1) contrastive topic modeling, and (2) contrastive visualization. That is, CONTRAVIS learns not only latent topics but also embeddings for the documents, topics and labels for visualization. CONTRAVIS exhibits three key properties by design. It is (i) Contrastive: It enables comparative analysis of different document corpora by extracting latent discriminative and common topics across labeled documents;(ii) visually-expressive: Different from numerous existing models, it also produces a visualization for all of the documents, labels, and the extracted topics, where proximity in the coordinate space is reflective of proximity in semantic space;(iii) Unified: It extracts topics and visual coordinates simultaneously under a joint model. Through extensive experiments on real-world datasets, we show CONTRAVIS's potential for providing visual contrastive analysis of multiple document collections. We show both qualitatively and quantitatively that CONTRAVIS significantly outperforms both unsupervised and supervised state-of-the-art topic models in contrastive power, semantic coherence and visual effectiveness.

关键词： contrastive topic models visualization comparative text mining

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3D geological model: A geostatistical approach of turbidite deposits, Los Molles FM, Neuquen Basin, Argentina 4

3D geological model: A geostatistical approach of turbidite ...

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4th EAGE conference on Petroleum Geostatistics

作者： Da Silveira, A.S. De Vargas, M.R. Engelke, V. Paim, P.S.G. Morris, M. Faccion, J.E. Universidade do Vale do Rio dos Sinos Petróleo Brasileiro S.A. Exploration and Production Softwares EPS

ISBN: (纸本)9789462822962

A recurrent challenge of geological modeling is bridging the gap between data with different resolution, such as the outcrop with the exploration resolution. By only integrating outcrop data from Arroyo La Jardineira, Neuquén Basin (AR), we integrated the object-based stochastic simulation for four depositional sequences that register a turbidite succession deposited in a deep-marine setting. This study aims (i) to determine a concise geological model derived from a plethora of simulations;(ii) to validate the uses of object-modeling as a constraint to facies distribution, and (iii) to evaluate the uncertainties when the data is scarce. The 3D numerical model allows the quantification of geological parameters, by testing contrasting geological scenarios. A quantitative sedimentological model was build integrating and using data derived from outcrops. The methodology utilized in this work enhanced the outcropping analysis, being a predictive tool to estimate faciological heterogeneities in subsurface explorational models. © EAGE 2019.

关键词： Stochastic models

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