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5th International conference on Advanced Computing and Communication Systems (ICACCS)

作者： Lakshmi, Ch. Jaya Prasanti, K. Kalpana, S. VR Siddhartha Engn Coll Vijayawada India

ISBN: (纸本)9781538695333

In the recent days, wide range of research has been carried out on visual enhancement of under images in submarine and military operations to discover submerged structural designing and sea floor exploration. But, diving in the deep ocean for a long time has increased the difficulties for analysis of underwater images. Further, other factors such as scattering resulting from presence of particles inside the water and blurring effects reduce the quality of images being captured by underwater optic camera. There are several algorithms have been introduced to improve the visual quality of deep water images. Therefore, in this project, a novel algorithm based on bidirectional Empirical Mode Decomposition (BEMD) to enhance the visual quality of the underwater images will be implemented and comparison of data with conventional enhancement technique will be illustrated. The implementation will be done using MATLAB software.

关键词： visual enhancement Image Processing Scattering effects Illumination conditions BEMD

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visualization for Quality Healthcare: Patient Flow exploration

Visualization for Quality Healthcare: Patient Flow Explorati...

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IEEE International conference on Big data (Big data)

作者： Domova, Veronika Sander-Tavallaey, Shiva Linkoping Univ Vasteras Sweden ABB Corp Res Vasteras Sweden

ISBN: (纸本)9781728108582

The health and medical institutes and hospitals are facing several challenges in the short and long term, i.e. demographic changes, demands on improving quality, limited resources and cost requirements. To cope with these challenges, the health care sector needs to become more efficient, while maintaining and improving the quality of care. Efficient and transparent information flow across the whole system plays a key role even in this context. Being able to analyze the patient flows as the first step will provide the possibility to more efficiently manage medical resources and better serve incoming patients. In this work, we have developed a web-based portal for interactive analysis of patient flow data to assist hospital authorities to improve and optimize the time and quality of the provided services. The developed tool facilitates short and long term optimization of resource allocation by analyzing the past, as well as current, patient flows, identifying bottlenecks and exploring the reasons for the occurred waiting times.

关键词： Medical data visual analytics Temporal event visualization Patient flow Patient trails

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visual Anomaly Detection in Event Sequence data

Visual Anomaly Detection in Event Sequence Data

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IEEE International conference on Big data (Big data)

作者： Guo, Shunan Jin, Zhuochen Chen, Qing Gotz, David Zha, Hongyuan Cao, Nan East China Normal Univ Dept Software Engn Shanghai Peoples R China Tongji Univ Coll Design & Innovat Shanghai Peoples R China Univ N Carolina Sch Informat & Lib Sci Chapel Hill NC 27515 USA

ISBN: (纸本)9781728108582

Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When applied to the analysis of event sequence data, the task of anomaly detection can be complex because the sequential and temporal nature of such data results in diverse definitions and flexible forms of anomalies. This, in turn, increases the difficulty in interpreting detected anomalies. In this paper, we propose an unsupervised anomaly detection algorithm based on Variational AutoEncoders (VAE) to estimate underlying normal progressions for each given sequence represented as occurrence probabilities of events along the sequence progression. Events in violation of their occurrence probability are identified as abnormal. We also introduce a visualization system, EventThread3 (ET3), to support interactive exploration and interpretations of anomalies within the context of normal sequence progressions in the dataset through comprehensive one-to-many sequence comparison. Finally, we quantitatively evaluate the performance of our anomaly detection algorithm and demonstrate the effectiveness of our system through a case study.

关键词： data visualization visual analytics event sequence data anomaly detection

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Design and Implementation of a Spring Boot-Based data Collection System

Design and Implementation of a Spring Boot-Based Data Collec...

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International conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Liu xuchen Li chaoyu College of Internet of Things University of Hohai Changzhou China

ISBN: (数字)9781728165172

ISBN: (纸本)9781728165189

With the advent of the artificial intelligence era, the breakthrough of core algorithms and the improvement of computing power, the need for learning samples and data support is also increasing. The exploration and practice of visual cognition and behavioral cognition also require a large amount of data material as the basis [1]. To provide high quality raw materials for machine learning, we designed and implemented a Spring Boot-based data collection system for artificial intelligence, enabling everyone on the Internet to participate in the growth of the artificial intelligence industry.

关键词： Task analysis Springs data collection Artificial intelligence databases Information management

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An exploration Into Online Impression Management and the Selective Self-Presentation Strategies of Generation Z on Instagram 6

An Exploration Into Online Impression Management and the Sel...

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6th European conference on Social Media (ECSM)

作者： Heffernan, Brian Rooney, Tara Technol Univ Dublin Dublin Ireland

ISBN: (纸本)9781912764235

The aim of this research is to investigate how and why individuals selectively self-present and manage impressions on Instagram. The research adopted a qualitative approach in the form of six in-depth semi-structured interviews. Given the visual nature of Instagram, photo-elicitation was also incorporated into the interview process to derive responses that unveiled participant's beliefs, views and attitudes (Meo 2010). Textual data was analysed using Strauss and Corbin's (1990) Grounded Theory Coding while visuals were analysed using Rose's (2016) visual analysis method. We conclude that Generation Z are motivated to manage impressions and selectively self-present on Instagram to archive experiences, present a desirable lifestyle, improve self-esteem, enhance self-concept and promote personality. The findings of this research provide insight into the complexities of online self-presentation and the motivations for engaging in this process.

关键词： online self-presentation computer-mediated communications Instagram impression management

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VaBank: visual Analytics for Banking Transactions

VaBank: Visual Analytics for Banking Transactions

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International conference on Information visualisation (IV)

作者： Catarina Maçãs Evgheni Polisciuc Penousal Machado University of Coimbra Centre for Informatics and Systems of the University of Coimbra Coimbra Portugal

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

To analyse and detect fraudulent patterns in banking transactions, most fraud analysts use spreadsheets which makes the overall process time-consuming and complex. In this article, we propose a visualization tool that aims to ease the analysis of banking transactions over time and the detection of the transactions' topology and of suspicious behaviours. Our main contributions are: (i) a user-centred visual tool, developed with the aid of fraud experts; (ii) a method that characterises the transactions topology through a self-organising algorithm; (iii) the visual characterisation of transactions through complex glyphs; and (iv) a user study to assess the tool effectiveness.

关键词： visual analytics data visualization Banking Companies Tools Topology Task analysis

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Effective visual exploration of Variables and Relationships in Parallel Coordinates Layout 10

Effective Visual Exploration of Variables and Relationships ...

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14th International Joint conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) / 10th International conference on Information visualization Theory and Applications (IVAPP)

作者： Kaur, Gurminder Karki, Bijaya B. Louisiana State Univ Sch Elect Engn & Comp Sci Baton Rouge LA 70803 USA

ISBN: (纸本)9789897583544

We present two innovative ways of enhancing parallel coordinates axes to better understand all variables and their interrelationships in high-dimensional datasets. Histogram and circle/ellipse plots based on uniform (linear) and non-uniform frequency/density mappings are adopted to visualize distributions of numerical and categorical data values. These plots are, particularly, helpful in emphasizing data values of low frequencies as well as those with similar frequencies. Color-mapped axis stripes are designed to visually connect numerical variables irrespective of their locations (adjacent or nonadjacent axes) in the parallel coordinates layout so that correlations can be fully realized in the same display. Distribution plots and axis stripes are integrated to further facilitate exploratory analysis of multivariate data with respect to a complete variable set.

关键词： Parallel Coordinates Multivariate data visualization Frequency Distribution Correlations

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基于CiteSpace的翻白草治疗糖尿病相关文献可视化分析

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光明中医 2024年第7期39卷 1262-1265页

作者：李英红滕曼刘桂华江春花(指导) 吴晨曦华北理工大学中医学院河北唐山063210

目的研究翻白草治疗糖尿病近23年的发展现状,分析总结研究热点与发展趋势,为该领域学者提供参考资料。方法检索中国知网、万方、维普三大数据库中翻白草治疗糖尿病相关文献,检索年限为2000年—2022年,利用CiteSpace 6.2.R2软件生成知... 详细信息

目的研究翻白草治疗糖尿病近23年的发展现状,分析总结研究热点与发展趋势,为该领域学者提供参考资料。方法检索中国知网、万方、维普三大数据库中翻白草治疗糖尿病相关文献,检索年限为2000年—2022年,利用CiteSpace 6.2.R2软件生成知识图谱。结果共纳入中文文献155篇,年发文量总体呈波动趋势,文献发文量第一的作者为崔荣军,机构为湖北中医药大学。其中该领域当前热点关键词糖尿病、胰岛素抵抗、翻白草总黄酮等出现频率较高。结论近20年中国学者在翻白草治疗糖尿病领域开展了积极探索,研究的广度和深度在不断延伸。建议加强各机构间有效的交流合作,开展更多高质量研究,争取相关研究不受学科限制、多学科交叉融合,共同发展。

关键词：消渴糖尿病翻白草可视化分析

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Interpreting Distortions in Dimensionality Reduction by Superimposing Neighbourhood Graphs

Interpreting Distortions in Dimensionality Reduction by Supe...

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16th IEEE Symposium on visualization for Cyber Security (VizSec) / IEEE visualization conference (IEEE VIS)

作者： Colange, Benoit Vuillon, Laurent Lespinats, Sylvain Dutykh, Denys Univ Grenoble Alpes INES F-73375 Le Bourget Du Lac France Univ Savoie Mont Blanc Univ Grenoble Alpes CNRS LAMA F-73000 Chambery France

ISBN: (纸本)9781728149417

To perform visual data exploration, many dimensionality reduction methods have been developed. These tools allow data analysts to represent multidimensional data in a 2D or 3D space, while preserving as much relevant information as possible. Yet, they cannot preserve all structures simultaneously and they induce some unavoidable distortions. Hence, many criteria have been introduced to evaluate a map's overall quality, mostly based on the preservation of neighbourhoods. Such global indicators are currently used to compare several maps, which helps to choose the most appropriate mapping method and its hyperparameters. However, those aggregated indicators tend to hide the local repartition of distortions. Thereby, they need to be supplemented by local evaluation to ensure correct interpretation of maps. In this paper, we describe a new method, called MING, for "Map Interpretation using Neighbourhood Graphs". It offers a graphical interpretation of pairs of map quality indicators, as well as local evaluation of the distortions. This is done by displaying on the map the nearest neighbours graphs computed in the data space and in the embedding. Shared and unshared edges exhibit reliable and unreliable neighbourhood information conveyed by the mapping. By this mean, analysts may determine whether proximity (or remoteness) of points on the map faithfully represents similarity (or dissimilarity) of original data, within the meaning of a chosen map quality criteria. We apply this approach to two pairs of widespread indicators: precision/recall and trustworthiness/continuity, chosen for their wide use in the community, which will allow an easy handling by users.

关键词： Evaluation Qualitative Evaluation Non-Spatial data and Techniques Dimensionality Reduction visual analysis and Knowledge Discovery visual Knowledge Discovery

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visual Abstraction of Geographical Point data with Spatial Autocorrelations

Visual Abstraction of Geographical Point Data with Spatial A...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Zhiguang Zhou Xinlong Zhang Zhendong Yang Yuanyuan Chen Yuhua Liu Jin Wen Binjie Chen Ying Zhao Wei Chen School of Information Zhejiang University of Finance and Economics State Key Lab of CAD & CG Zhejiang University School of Computer Sciences and Engineering Central South University

ISBN: (数字)9781728180090

ISBN: (纸本)9781728180106

Scatterplots are always employed to visualize geographical point datasets, which often suffer from an overdraw problem due to the increase of data sizes. A variety of sampling strategies have been proposed to reduce overdraw and visual clutter with the spatial densities of points taken into account. However, informative attributes associated with the points also play significant roles in the exploration of geographical datasets. In this paper, we propose an attribute-based abstraction method to simplify the cluttered visualization of large-scale geographical points. Spatial autocorrelations are utilized to measure the attribute relationships of points in local areas, and a novel attribute-based sampling model is designed to generate a subset of points to preserve both density and attribute characteristics of original geographical points. A set of visual designs and user-friendly interactions are implemented, enabling users to capture the spatial distribution of geographical points and get deeper insights into the attribute features across local areas. Case studies and quantitative comparisons based on the real-world datasets further demonstrate the effectiveness of our method in the abstraction and exploration of large-scale geographical point datasets.

关键词： Correlation visualization data visualization Geospatial analysis Sampling methods Clutter Graphical models

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