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40th Computer Graphics International conference (CGI)

作者： Liang, Song Liu, Ruihang Qian, Jiansheng China Univ Min & Technol Sch Mines Xuzhou Peoples R China China Univ Min & Technol Xuhai Coll Xuzhou Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou Peoples R China

ISBN: (纸本)9783031500688;9783031500695

Contrary to natural images with randomized content, advertisements contain abundant emotion-eliciting manufactured scenes and multi-modal visual elements with highly related semantics. However, little research has evaluated the interrelationships of advertising vision and affective perception. The absence of advertising data sets with affective labels and visual attention benchmarks is one of the most pressing issues that have to be addressed. Meanwhile, growing evidence indicates that eye movements can reveal the internal states of human minds. Inspired by these, we use a high-precision eye tracker to record the eye-moving data of 57 subjects when they observe 1000 advertising images. 7-score opinion ratings for the five advertising attributes (i.e., ad liking, emotional, aesthetic, functional, and brand liking) are then collected. We further make a preliminary analysis of the correlation among advertising attributes, subjects' visual attention, eye movement characteristics, and personality traits, obtaining a series of enlightening conclusions. To our best knowledge, the proposed dataset is the largest advertising image dataset based on eye tracking and with multiple personalized affective tags. It provides a new exploration space and data foundation for multimedia visual analysis and affection computing community. The data are available at: https://***/lscumt/EAID.

关键词： Advertising Affective computing Eye movement analysis

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The Power of visual Storytelling: Analyzing Customer Personalities with Tableau 15

The Power of Visual Storytelling: Analyzing Customer Persona...

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15th International conference on Ubiquitous and Future Networks (ICUFN)

作者： Menaka, Jadov Poulose, Alwin Indian Inst Sci Educ & Res Thiruvananthapuram IIS Sch Data Sci Thiruvananthapuram 695551 Kerala India

ISBN: (纸本)9798350385304;9798350385298

The customer personality analysis serves as an in-depth exploration into the realm of a company's ideal customers, meticulously examining their characteristics, behaviors, and preferences. This paper's analytical approach aims to empower businesses by unraveling the intricacies of customer bases and enabling the customization of products based on diverse customer segments' specific needs and concerns. By leveraging advanced visualization techniques like histograms, bar charts, donut charts, and table charts within Tableau, this study seeks to enhance the understanding of customer attributes, facilitating more targeted and effective marketing strategies. Understanding customers is pivotal for businesses seeking to tailor their products and marketing efforts. Customer personality analysis delves into the wealth of data available, allowing for a nuanced understanding of customer segments. The objective is to shift from a generalized approach to a more targeted one, where resources are allocated efficiently and marketing efforts are tailored to resonate with specific customer groups.

关键词： Customer Personality analysis visualization Techniques data visualization Intelligent data Analytics data Analytics Techniques Interactive dashboards Decision-making Customer Behavior Campaign Metrics Demographics

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An Improvement on exploration Step of Whale Optimization Algorithm with Levy Distribution for Classification Problems 5

An Improvement on Exploration Step of Whale Optimization Alg...

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5th International conference on Big data Analytics and Practices (IBDAP)

作者： Pravesjit, Sakkayaphop Kantawong, Krittika Kamkhad, Natdanai Sabaipom, Saksit Monchanuan, Jantawan Jitkongchuen, Duangjai Thammano, Arit Longpradit, Panchit Univ Phayao Sch Informat & Commun Technol Phayao Thailand Big Data Inst Bangkok Thailand King Mongkuts Inst Technol Ladkrabang Fac Informat Technol Ladkrabang Thailand Mahidol Univ Fac Social Sci & Humanities Salaya Nakhon Pathom Thailand

ISBN: (纸本)9798350391749

The proposed system represents an enhanced movement in search of food of Whale Optimization Algorithm (WOA), based on Levy distribution for image classification of grape leaf disease. In the preprocessing, the proposed system uses convolution kernels to transform images into input data within the range of (0,1). Thereafter, the Levy distribution is incorporated into the WOA model as an exploration search mechanism. A grape leaf dataset from the Plant Village project (***), consisting of 4062 labeled images with dimensions of 256 by 256 pixels and divided into four classes -healthy, Black Rot, Black Measles, and Isariopsis leaf spot -is used to evaluate the performance of the proposed system. Experimental results show that the proposed system is better than visual Geometry Group (VGG16), Gray Level Co-occurrence Matrix (GLCM) with SVM, Low contrast haze reduction-neighborhood component analysis with SVM, and whale optimization algorithm (WOA).

关键词： whale optimization algorithm levy distribution convolution kernel grape leaf disease

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Factors Influencing Generation Z's Cybersecurity Practices: An Empirical analysis 18th

Factors Influencing Generation Z's Cybersecurity Practices: ...

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18th International conference on Implications of Information and Digital Technologies for Development (ICT4D)

作者： Slamet, Ethan Ruhwanya, Zainab Univ Cape Town Cape Town South Africa

ISBN: (纸本)9783031669880;9783031669866;9783031669859

With Generation Z's rise in technology use, recognising their specific cybersecurity risks is vital. Adopting effective cybersecurity practices is essential for their protection, yet the factors influencing these protective behaviours still need further exploration. This study proposed an adapted Theory of Planned Behaviour model, testing it with data from 123 participants. analysis using SPSS for descriptive statistics and PLS-SEM for data evaluation revealed that knowledge and self-efficacy significantly predict Gen Z's cybersecurity practices. Contrarily, their attitudes, awareness, and subjective norms showed no substantial influence on these practices. This research highlights the need for increased practical knowledge and efficacy in cybersecurity measures among Gen Z technology users.

关键词： Cybersecurity practices Generation Z Theory of Planned Behaviour

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visual Analytics of Air Pollution Transmission Among Urban Agglomerations 40th

Visual Analytics of Air Pollution Transmission Among Urban A...

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40th Computer Graphics International conference (CGI)

作者： Chen, Shijie Wang, Song Liu, Yipan Ma, Dongliang Hu, Hao Southwest Univ Sci & Technol Sch Comp Sci & Technol Mianyang 621010 Sichuan Peoples R China

ISBN: (纸本)9783031500749;9783031500756

In field of air quality research, it is essential to scientifically reflect the internal structure of air quality distribution and reveal the dynamic evolution of air pollution. In this study, a novel visual analytics method is proposed to address these challenges. Initially, the spatio-temporal features of air quality data are mined to complete urban agglomeration division based on dimensionality reduction and clustering. Subsequently, the air pollution transmission network (APTN) is constructed through particle transport and correlation analysis. A progressive exploration analysis method based on multidimensional space transformation is then employed to explore the process of air pollution transmission. Furthermore, a visual analytics system is developed to facilitate the interpretation of the results. Finally, we demonstrate the effectiveness of our proposed methodology using real data sets and case studies, and receive positive feedback from domain experts.

关键词： Air pollution Urban agglomerations Air pollution transmission network Multidimensional space transformation visual analytics

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PC-Expo: A Metrics-Based Interactive Axes Reordering Method for Parallel Coordinate Displays

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IEEE Transactions on visualization and Computer Graphics 2023年第1期29卷 712-722页

作者： Tyagi, Anjul Estro, Tyler Kuenning, Geoff Zadok, Erez Mueller, Klaus Stony Brook University Computer Science Department New York United States Harvey Mudd College Computer Science Department ClaremontCA United States

Parallel coordinate plots (PCPs) have been widely used for high-dimensional (HD) data storytelling because they allow for presenting a large number of dimensions without distortions. The axes ordering in PCP presents a particular story from the data based on the user perception of PCP polylines. Existing works focus on directly optimizing for PCP axes ordering based on some common analysis tasks like clustering, neighborhood, and correlation. However, direct optimization for PCP axes based on these common properties is restrictive because it does not account for multiple properties occurring between the axes, and for local properties that occur in small regions in the data. Also, many of these techniques do not support the human-in-the-loop (HIL) paradigm, which is crucial (i) for explainability and (ii) in cases where no single reordering scheme fits the users' goals. To alleviate these problems, we present PC-Expo, a real-time visual analytics framework for all-in-one PCP line pattern detection and axes reordering. We studied the connection of line patterns in PCPs with different data analysis tasks and datasets. PC-Expo expands prior work on PCP axes reordering by developing real-time, local detection schemes for the 12 most common analysis tasks (properties). Users can choose the story they want to present with PCPs by optimizing directly over their choice of properties. These properties can be ranked, or combined using individual weights, creating a custom optimization scheme for axes reordering. Users can control the granularity at which they want to work with their detection scheme in the data, allowing exploration of local regions. PC-Expo also supports HIL axes reordering via local-property visualization, which shows the regions of granular activity for every axis pair. Local-property visualization is helpful for PCP axes reordering based on multiple properties, when no single reordering scheme fits the user goals. A comprehensive evaluation was done with r

关键词： data visualization

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Multiscale visualization: A Structured Literature analysis

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2022年第12期28卷 4918-4929页

作者： Cakmak, Eren Jaeckle, Dominik Schreck, Tobias Keim, Daniel A. Fuchs, Johannes Univ Konstanz Dept Comp & Informat Sci D-78547 Constance Germany Graz Univ Technol Inst Comp Graph & Knowledge Visualisat A-8010 Graz Austria

Multiscale visualizations are typically used to analyze multiscale processes and data in various application domains, such as the visual exploration of hierarchical genome structures in molecular biology. However, creating such multiscale visualizations remains challenging due to the plethora of existing work and the expression ambiguity in visualization research. Up to today, there has been little work to compare and categorize multiscale visualizations to understand their design practices. In this article, we present a structured literature analysis to provide an overview of common design practices in multiscale visualization research. We systematically reviewed and categorized 122 published journal or conference articles between 1995 and 2020. We organized the reviewed articles in a taxonomy that reveals common design factors. Researchers and practitioners can use our taxonomy to explore existing work to create new multiscale navigation and visualization techniques. Based on the reviewed articles, we examine research trends and highlight open research challenges.

关键词： data visualization Navigation visualization Taxonomy Encoding Molecular biology Libraries Multiscale visualization multiscale navigation multiscale exploration literature analysis taxonomy survey

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Modeling Nonlinear Relationships in Psychometric data Using Variational Autoencoders: Insights from Simulated data 3

Modeling Nonlinear Relationships in Psychometric Data Using ...

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3rd IEEE International conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024

作者： Casella, Monica Milano, Nicola Esposito, Raffaella Marocco, Davide University of Naples Federico Ii Natural and Artificial Cognition Laboratory 'Orazio Miglino' Naples Italy

ISBN: (纸本)9798350378009

Psychometric research relies on latent variables analysis, employing techniques like factor analysis to explore test structures. However, such methods often assume linear dimensionality reduction, not always reflective of psychological data complexities. This paper introduces Artificial Neural Networks (ANNs) as a solution, promising nonlinear exploration of latent space. We implement a Variational Autoencoder (VAE), an ANN which can perform nonlinear dimensionality reduction and distribution learning. We evaluate VAE's performance using two simulated datasets. Results show that VAE are comparable to Factor analysis in linear scenarios, accurately reproducing factor scores. However, in nonlinear scenarios, VAE outperforms Factor analysis by capturing nonlinear relationships and enhancing factor score estimations. This research underscores VAE's utility in advancing latent variable exploration beyond traditional linear methods. © 2024 IEEE.

关键词： Nonlinear simulations

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Proceedings - 2024 IEEE 17th Pacific visualization conference, PacificVis 2024

Proceedings - 2024 IEEE 17th Pacific Visualization Conferenc...

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17th IEEE Pacific visualization conference, PacificVis 2024

ISBN: (纸本)9798350393804

The proceedings contain 43 papers. The topics discussed include: GenLens: a systematic evaluation of visual GenAI model outputs;evaluating how interactive visualizations can assist in finding samples where and how computer vision models make mistakes;MaugVLink: augmenting mathematical formulas with visual links;A-Map: interactive visual exploration of intercity accessibility dynamics based on railway network data;understanding and automating graphical annotations on animated scatterplots;efficient level-crossing probability calculation for Gaussian process modeled data;CommentVis: unveiling comment insights through interactive visualization tool;and GraphFederator: federated visual analysis for multi-party graphs.

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LDViz: A Tool to Assist the Multidimensional exploration of SPARQL Endpoints 1

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17th International conference on Web Information Systems and Technologies (WEBIST)

作者： Menin, Aline Maillot, Pierre Faron, Catherine Corby, Olivier Freitas, Carla Dal Sasso Gandon, Fabien Winckler, Marco Univ Cote Azur CNRS INRIA I3SUMR 7271 Nice France Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (数字)9783031241970

ISBN: (纸本)9783031241963;9783031241970

Over recent years, we witnessed an astonishing growth in production and consumption of Linked data (LD), which contains valuable information to support decision-making processes in various application domains. In this context, data visualization plays a decisive role in making sense of the large volumes of data created every day and in effectively communicating structures, processes, and trends in data in an accessible way. In this paper, we present LDViz, a visualization tool designed to support the exploration of knowledge graphs via multiple perspectives: (i) RDF graph/vocabulary inspection, (ii) RDF summarization, and (iii) exploratory search. We demonstrate the usage and feasibility of our approach through a set of use case scenarios showing how users can perform searches through SPARQL queries and explore multiple perspectives of the resulting data through multiple complementary visualization techniques. We also demonstrate the reach and generic aspects of our tool through an evaluation that tests the support of 419 different SPARQL endpoints.

关键词： Linked data Linked data visualization RDF visualization visual exploratory search SPARQL

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