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黑龙江科学 2025年第9期16卷 29-33页

作者：张萍滕春玲广西医科大学第一附属医院感染性疾病科南宁530021

借助文献计量学与可视化分析方法梳理国内实习护生案例教学法的研究现状,明确其研究热点与发展趋势,为该领域的深入研究与教学实践提供参考。以CNKI数据库为数据源,检索建库至2024年12月31日期间与实习护生案例教学法相关的学术期刊、... 详细信息

借助文献计量学与可视化分析方法梳理国内实习护生案例教学法的研究现状,明确其研究热点与发展趋势,为该领域的深入研究与教学实践提供参考。以CNKI数据库为数据源,检索建库至2024年12月31日期间与实习护生案例教学法相关的学术期刊、硕博论文及会议论文,使用CiteSpace 5.5.R2软件进行可视化分析。结果显示,2007—2024年,国内关于实习护生案例教学法的文献发文量呈波动上升趋势,2013年后增长明显。作者、机构间合作关系松散,护理院校与医院合作较多。关键词以“护生”为核心,时间线图显示研究从基础教育实习向教学方法等方向拓展,后期趋于多元化、精细化。实习护生案例教学法受关注度呈波动上升趋势,在教学方法创新、神经内科与医院感染教学等方面正展开前沿探索。

关键词：实习护生案例教学法文献计量学可视化分析

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Application of Assistive Technologies in Rehabilitation of the visually Impaired

Application of Assistive Technologies in Rehabilitation of t...

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AHFE International conference on Ergonomics in Design

作者： Bueno de Oliveira, Taina A. Moura, Joao Wojcikiewicz, Felipe Maia, Luiz Nickel, Elton Ferreira, Marcelo Gomes Univ Estado Santa Catarina UDESC Florianopolis SC Brazil

ISBN: (纸本)9783319605821;9783319605814

This article brings together studies aimed at the use of assistive technologies during the rehabilitation and/or support processes of people with total and/or partial visual impairments (whether congenital or acquired) and how the difficulties and limitations arising from this framework can be overcome through the recognition and exploration of the individual abilities and skills to perform tasks, through the use of AT. The methodological processes adopted in the research were conducted through observations and systematic comparative analyzes to recognize the patterns of behavior of individuals with visual impairment during the execution of their activities. The data analysis was performed to identify and compare the factors that contribute to the difficulties and successes in the application of assistive technologies for the rehabilitation of visually impaired people. It's hoped that, at the end of these studies, their results may explain how AT contribute to improve quality of life to people with disabilities.

关键词： Assistive technologies Rehabilitation visual impairment

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SPOT: Open source visual data analytics platform for high-dimensional scientific data 14

SPOT: Open source visual data analytics platform for high-di...

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14th IEEE International conference on E-Science (E-Science)

作者： Diblen, F. Attema, J. J. Bakhshi, R. Stienen, B. Hendriks, L. Caron, S. Netherlands ESci Ctr Sci Pk 140 NL-1098 XG Amsterdam Netherlands Radboud Univ Nijmegen Inst Math Astro & Particle Phys IMAPP Nijmegen Netherlands

ISBN: (纸本)9781538691564

One of the most challenging tasks in the field of information visualization is to design tools for high-dimensional scientific data. Existing visual data analytics tools either require expert knowledge (e.g. programming) or they are commercial tools such as Dash [1], Spotfire [2] and Tableau [3]. Spot provides a user-friendly, interactive data exploration environment for high-dimensional data sets [4]. The main focus of Spot is on scientific use, with the aim to facilitate open science [5], data sharing and reuse [6]. For example, iDARK project (https://***/project/idark), which aims to collect existing dark matter models, will be using Spot in order to allow researchers to compare the particle physics data sets (see http://***). This abstract gives an overview of main features of Spot, an open source data analytics platform, and its capabilities.

关键词： visualization data analysis data visualization Software databases Tools High energy physics

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Coupling Story to visualization: Using Textual analysis as a Bridge Between data and Interpretation 18

Coupling Story to Visualization: Using Textual Analysis as a...

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23rd International conference on Intelligent User Interfaces (IUI)

作者： Metoyer, Ronald Zhi, Qiyu Janczuk, Bart Scheirer, Walter Univ Notre Dame Notre Dame IN 46556 USA

ISBN: (纸本)9781450349451

Online writers and journalism media are increasingly combining visualization (and other multimedia content) with narrative text to create narrative visualizations. Often, however, the two elements are presented independently of one another. We propose an approach to automatically integrate text and visualization elements. We begin with a writer's narrative that presumably can be supported with visual data evidence. We leverage natural language processing, quantitative narrative analysis, and information visualization to (1) automatically extract narrative components (who, what, when, where) from data-rich stories, and (2) integrate the supporting data evidence with the text to develop a narrative visualization. We also employ bidirectional interaction from text to visualization and visualization to text to support reader exploration in both directions. We demonstrate the approach with a case study in the data-rich field of sports journalism.

关键词： narrative visualization text analysis text visualization interaction deep coupling

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Unsteady Flow visualization via Physics Based Pathline exploration

Unsteady Flow Visualization via Physics Based Pathline Explo...

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International conference on visualisation, VIS

作者： Duong B. Nguyen Lei Zhang Robert S. Laramee David Thompson Rodolfo Ostilla Monico Guoning Chen University of Houston Swansea University Mississippi State University

ISBN: (纸本)9781728149424

This work proposes to analyze the time-dependent characteristics of the physical attributes measured along pathlines derived from unsteady flows, which can be represented as a series of time activity curves (TAC). A new TAC-based unsteady flow visualization and analysis framework is proposed. The center of this framework is a new event-based distance metric (EDM) that compares the similarity of two TACs, from which a new spatio-temporal, hierarchical clustering of pathlines based on their physical attributes and an attribute-based pathline exploration are proposed. These techniques are integrated into a visual analytics system, which has been applied to a number of unsteady flow in 2D and 3D to demonstrate its utility.

关键词： Measurement Market research Correlation Two dimensional displays data visualization Kernel Physics

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Big textual data: how to find relevant information (with low cost)? 18

Big textual data: how to find relevant information (with low...

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10th International conference on Management of Digital EcoSystems (MEDES)

作者： Jouis, Christophe Shafei, Bilal Univ Sorbonne Nouvelle Paris France An Najah Natl Univ French Dept Nablus Palestine

ISBN: (纸本)9781450356220

Obviously, it is not useful to accumulate large amounts of information if we cannot find a particular piece of information. Also, extracting relevant and targeted information from textual data on large digital media, and if they are heterogeneous and multilingual, is certainly not a new problem. However, the current methods prove to be expensive and the results are too often inappropriate, too numerous and not very presentable for the user. In addition to current methods, we propose an original method: Contextual exploration. This is the EC3 software. EC3 does not need syntactic analysis, statistical analysis nor a "general" ontology. EC3 uses only small ontologies called "linguistic ontologies" that expresses the language of knowledge. This is why EC3 works very quickly on large corpus, which components can be both whole and short text: SMS to books. At the output, EC3 offers a dynamic visual representation of results. EC3 has been tested on very large digitized corpus provided by the French Labex OBVIL "Observatory of the Literary Life", in partnership with the National Library of France.

关键词： Big Textual data Extraction of Pertinent Information data Mining for Information Retrieval Big data analysis EC3 Contextual exploration

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LDSScanner: Exploratory analysis of Low-Dimensional Structures in High-Dimensional datasets

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2018年第1期24卷 236-245页

作者： Xia, Jiazhi Ye, Fenjin Chen, Wei Wang, Yusi Chen, Weifeng Ma, Yuxin Tung, Anthony K. H. Cent South Univ Changsha Hunan Peoples R China Zhejiang Univ Hangzhou Zhejiang Peoples R China Zhejiang Univ Finance & Econ Hangzhou Zhejiang Peoples R China Natl Univ Singapore Singapore Singapore

Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS). We propose a new LTSD-GD view, which is constructed by mapping LTSD and GD to the x axis and y axis using 1D multidimensional scaling, respectively. Unlike traditional dimensionality reduction methods that preserve various kinds of distances among points, the LTSD-GD view presents the distribution of pointwise LTS (x axis) and the variation of LTS in structures (the combination of x axis and y axis). We design and implement a suite of visual tools for navigating and reasoning about intrinsic structures of a high-dimensional dataset. Three case studies verify the effectiveness of our approach.

关键词： High-dimensional data low-dimensional structure subspace manifold visual exploration

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exploration and Research on the Mixed Teaching Mode of Basic Japanese Course under the Background of Information Technology

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Journal of Physics: conference Series 2021年第4期1852卷

作者： Yarong Wei Fuzhou University of International Studies and Trade Fuzhou China

At present, the general trend of information technology development is changing from the typical technology-driven development mode to the combination of application-driven and technology-driven mode. The development of information technology brings both opportunities and challenges to the reform and innovation of foreign language teaching. This paper starts with features and types of information-based foreign language teaching, to explore the mixed teaching mode of basic Japanese course under the background of information technology. Choose a reasonable teaching platform and teaching resources according to the teaching objectives; make a good teaching design for online autonomous learning for each chapter before class; to do well in offline classroom teaching development and classroom network-assisted teaching; and supplement online learning materials effectively for students after-class learning. Pay more attention to process evaluation, multi-subject evaluation and visual data analysis and evaluation based on big data. Pay attention to the role of games in basic Japanese learning, applying information technology to the teaching of basic Japanese courses and exploring the mixed teaching mode of basic Japanese courses can improve teaching effectiveness in all directions and contribute to the overall improvement of teaching quality.

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xHiPP: eXtended Hierarchical Point Placement Strategy 31

xHiPP: eXtended Hierarchical Point Placement Strategy

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31st conference on Graphics, Patterns and Images (SIBGRAPI)

作者： Dias, Fabio Felix Minghim, Rosane Univ Sao Paulo Inst Ciencias Matemat & Comp Ave Trabalhador Sao Carlense 400 Sao Carlos SP Brazil

ISBN: (纸本)9781538692646

The complexity and size of data have created challenges to data analysis. Although point placement strategies have gained popularity in the last decade to yield a global view of multidimensional datasets, few attempts have been made to improve visual scalability and offer multilevel exploration in the context of multidimensional projections and point placement strategies. Such approaches can be helpful in improving the analysis capability both by organizing visual spaces and allowing meaningful partitions of larger datasets. In this paper, we extend the Hierarchy Point Placement (HiPP), a strategy for multi-level point placement, in order to enhance its analytical capabilities and flexibility to handle current trends in visual data science. We have provided several combinations of clustering methods and projection approaches to represent and visualize datasets;added a choice to invert the original processing order from cluster-projection to projection-cluster;proposed a better way to initialize the partitions, and added ways to summarize image, audio, text and general data groups. The tool's code is made available online. In this article, we present the new tool (named xHiPP) and provide validation through case studies with simpler and more complex datasets (text and audio) to illustrate that the capabilities afforded by the extensions have managed to provide analysts with the ability to quickly gain insight and adjust the processing pipeline to their needs.

关键词： visualization data visualization Force Mathematical model data analysis Tools Layout

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A visual analytics approach for exploration of high-dimensional time series based on Neighbor-Joining Tree 18

A visual analytics approach for exploration of high-dimensio...

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10th International conference on Computer Modeling and Simulation, ICCMS 2018

作者： Rodríguez, Roberto Alfonte, Reynaldo Cuadros, Ana Maria Urquiaga Universidad Nacional de San Agustín Arequipa Peru Zapana Universidad Nacional de San Agustín Arequipa Peru Valdivia Universidad la Salle Arequipa Peru

ISBN: (纸本)9781450363396

High-dimensional time series analysis through visual techniques poses many challenges due to the visualization solutions proposed until now for exploratory tasks are not well-oriented to high volume of data. When the data sets grow large, the visual alternatives do not allow for a good association between similar time series. With the aim to increase more alternatives, we introduce a visual analytic approach based on Neighbor-Joining similarity tree. The proposed approach internally consists of five time series dimension reduction techniques widely used, two wellknown similarity measures and interaction mechanisms to do exploratory analysis of high-dimensional time series data interactively. © 2018 Association for Computing Machinery.

关键词： visualization

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