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Autism Spectrum Disorder Identification from visual exploration of Images 1

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22nd International conference on Image analysis and Processing (ICIAP)

作者： Bolpagni, Marco Setti, Francesco Univ Verona Dept Comp Sci Verona Italy Univ Verona Dept Engn Innovat Med Verona Italy

ISBN: (数字)9783031431487

ISBN: (纸本)9783031431470;9783031431487

Autism Spectrum Disorder (ASD) affects 1 in 77 children in Italy, but the diagnostic process is slow and costly. As autistic individuals exhibit different gaze patterns from healthy controls in visual exploration of images and semantic interpretation, these are promising biomarkers to exploit in diagnosis. This study aims at developing a model to assist in the diagnosis of ASD using gaze data when static images are presented to the subjects. We first propose a set of features, each one motivated by psychological studies and findings. Then we apply a feature selection mechanism based on Boruta algorithm with SHAP values. Finally we use CatBoost to perform binary classification, and a strategy to optimize model hyperparameters using a multivariate Tree Parzen Estimator. We validated our model on the popular Saliency4ASD dataset, outperforming state of the art models tested with the same protocol by more than 3% in accuracy. We also provide an in-depth analysis of the feature importance and we show how these results are in line with the psychological literature.

关键词： Autism Spectrum Disorder Eye tracking CatBoost

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Cyber-Physical visual Management Systems in the Digital Lean Manufacturing World

Cyber-Physical Visual Management Systems in the Digital Lean...

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IFIP WG 5.7 International conference on Advances in Production Management Systems (APMS) - Smart Manufacturing and Logistics Systems - Turning Ideas into Action

作者： Romero, David Zanchi, Matteo Powell, Daryl J. Gaiardelli, Paolo Tecnol Monterrey Monterrey Mexico Univ Bergamo Bergamo Italy Norwegian Univ Sci & Technol Trondheim Norway

ISBN: (纸本)9783031164118;9783031164101

The importance of visual Management (or "Mieruka" as it is called in Japanese) has been largely demonstrated over the last few years, especially when it comes to the creation and management of data-rich environments for effective and efficient data-driven decision-making, such as digital lean smart factories. Although the different functions of visual systems are already known by the scientific community, further analysis of the capabilities and benefits provided by these tools, especially when enhanced with modern digital technologies, has yet to be provided. Therefore, this paper aims to frame a list of capabilities of the current physical visual systems, and their cyber/digital equivalents, according to a reference framework called the "7Is", which was extracted from a review of the current literature available. This may serve as a valid common reference for future research on this topic.

关键词： Digital manufacturing Smart manufacturing Lean manufacturing Digital lean manufacturing visual management Mieruka Digitalization

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Self-touch and other spontaneous behavior patterns in early infancy

Self-touch and other spontaneous behavior patterns in early ...

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IEEE International conference on Development and Learning (ICDL)

作者： Khoury, Jason Popescu, Sergiu T. Gama, Filipe Marcel, Valentin Hoffmann, Matej Czech Tech Univ Fac Elect Engn Dept Cybernet Prague Czech Republic

ISBN: (数字)9781665413114

ISBN: (纸本)9781665413114

Children are not born tabula rasa. However, interacting with the environment through their body movements in the first months after birth is critical to building the models or representations that are the foundation for everything that follows. We present longitudinal data on spontaneous behavior of three infants observed between about 8 and 25 weeks of age in supine position. We combined manual scoring of video recordings with an automatic extraction of motion data in order to study infants' behavioral patterns and developmental progression such as: (i) spatial distribution of self-touches on the body, (ii) spatial patterns and regularities of hand movements, (iii) midline crossing, (iv) preferential use of one arm, and (v) dynamic patterns of movements indicative of goal-directedness. From the patterns observed in this pilot data set, we can speculate on the development of first body and peripersonal space representations. Several methods of extracting 3D kinematics from videos have recently been made available by the computer vision community. We applied one of these methods on infant videos and provide guidelines on its possibilities and limitations-a methodological contribution to automating the analysis of infant videos. In the future, we plan to use the patterns we extracted from the recordings as inputs to embodied computational models of learning of body representations in infancy.

关键词： self-exploration self-touch body exploration kinematics goal-oriented behavior reaching development

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Identification of Expert Tower Controller visual Scanning Patterns in Support of the Development of Automated Training Tools 14th

Identification of Expert Tower Controller Visual Scanning Pa...

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14th International conference on Virtual, Augmented and Mixed Reality (VAMR) Held as Part of the 24th International conference on Human-Computer Interaction (HCii)

作者： Crutchfield, Jerry Kang, Ziho Fraga, Ricardo Palma Lee, Junehyung FAA Civil Aerosp Med Inst Oklahoma City OK 73169 USA Univ Oklahoma Sch Ind & Syst Engn Norman OK 73019 USA

ISBN: (纸本)9783031060151;9783031060144

Researchers from the Federal Aviation Administration's (FAA) Civil Aerospace Medical Institute and from the University of Oklahoma's School of Industrial and Systems Engineering are studying the characteristics of expert tower controller visual scanning behavior in support of the FAA's exploration of ways to enhance controller training. Training enhancements potentially include the use of advanced simulation tools (such as virtual reality systems) to teach controller trainees critical scanning skill(s). We collected eye-tracking data from controller subject matter experts while they controlled simulated air traffic scenarios in a high fidelity tower cab simulator. In this paper, we describe the methodology used to collect and analyze the data as well as summarize the results of the analyses. These results may inform the design of scanning training tools. Furthermore, we summarize lessons learned from our use of simulation and our methods of collecting performance measures that may be useful for those developing scanning training tools that will also use simulation. Our findings suggest that training tools should continue to trainwhat is taught in today's curriculum regarding scanning, to frequently scan "hot spots" such as both ends of an active runway, and to prioritize traffic at the airfield before traffic occurring farther out. Our findings also suggest that controllers could be taught to use different scanning patterns based on the ATC task they are currently carrying out and to use these patterns consistently.

关键词： Air traffic control Aviation Eye-tracking Simulation Training Virtual reality

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data visualization in Transforming Raw data into Compelling visual Narratives

Data Visualization in Transforming Raw Data into Compelling ...

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Trends in Quantum Computing and Emerging Business Technologies (TQCEBT), International conference on

作者： Prithu Sarkar Yadavalli Devi Priya Pravina B. Patel Prasanta Chatterjee Biswas Sreenivasulu Arigela Sravanthi Sallaram Amity School of Communication Amity University Kolkata Computer Science and Engineering Vignan's Institute of Information Technology Duvvada Vishakapatanam Andhra Pradesh Department of Computer Science Ganpat University Mehsana Gujarat India CDOE Parul University Vadodara Mohan Babu University Tirupati Andhra Pradesh Department of Computer Science and Engineering St.Martin's Engineering College

ISBN: (数字)9798350384277

ISBN: (纸本)9798350384284

One of the main ways to evaluate information is through visual learning, which traditionally combines textual reading with visual aids like graphical representations. However, separating the visual method of learning to distinguish between text and visuals has been suggested in light of advancements in learning styles. The ability to swiftly create complex visual information and inexpensively distribute it digitally is another way that technology has improved visual presentation. The purpose of this research paper is to conduct a detailed investigation of the Virtualization of data, storytelling, and data visualization’s Narrative, understand how Instruments and methods are used in visualization, and select the appropriate tool for presenting visual data stories and upcoming projects. To address this purpose, this research has reviewed a wide range of different journals and articles to gather information about data visualization, storytelling, and data narratives. Based on the analysis, this research paper finds an all-encompassing perspective on the visual data narrative process, incorporating the phases of discovering insights (data exploration), developing these insights into a tale (creating a story), and sharing this story with others (telling a story). Through the pursuit of these novel research directions, visualizations can facilitate more potent data storytelling.

关键词： visualization Quantum computing Instruments data visualization Market research Virtualization Business

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ICEVis: Interactive Clustering exploration for tumor sub-region analysis in multiparametric cancer imaging 22

ICEVis: Interactive Clustering Exploration for tumor sub-reg...

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15th International Symposium on visual Information Communication and Interaction, VINCI2022

作者： Mörth, Eric Eichner, Tanja Haldorsen, Ingfrid Bruckner, Stefan Smit, Noeska N. Dept. of Informatics Mmiv UiB/HUS Norway Faculty of Informatics / Mmiv Norway Tu Vienna UiB Austria Mmiv Dept. of Clinical Medicine Hus / UiB Norway

ISBN: (纸本)9781450398077

Tumor tissue characteristics derived from imaging data are gaining importance in clinical research. Tumor sub-regions may play a critical role in defining tumor types and may hold essential information about tumor aggressiveness. Depending on the tumor's location within the body, such sub-regions can be easily identified and determined by physiology, but these sub-regions are not readily visible to others. Regions within a tumor are currently explored by comparing the image sequences and analyzing the tissue heterogeneity present. To improve the exploration of such tumor sub-regions, we propose a visual analytics tool called ICEVis. ICEVis supports the identification of tumor sub-regions and corresponding features combined with cluster visualizations highlighting cluster validity. It is often difficult to estimate the optimal number of clusters;we provide rich facilities to support this task, incorporating various statistical measures and interactive exploration of the results. We evaluated our tool with three clinical researchers to show the potential of our approach. © 2022 Owner/Author.

关键词： Tumors

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Learning Semantics for visual Place Recognition Through Multi-scale Attention 21st

Learning Semantics for Visual Place Recognition Through Mult...

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21st International conference on Image analysis and Processing (ICIAP)

作者： Paolicelli, Valerio Tavera, Antonio Masone, Carlo Berton, Gabriele Caputo, Barbara IIT Genoa Italy Politecn Torino Turin Italy CINI Rome Italy

ISBN: (纸本)9783031064302;9783031064296

In this paper we address the task of visual place recognition (VPR), where the goal is to retrieve the correct GPS coordinates of a given query image against a huge geotagged gallery. While recent works have shown that building descriptors incorporating semantic and appearance information is beneficial, current state-of-the-art methods opt for a top down definition of the significant semantic content. Here we present the first VPR algorithm (Code and dataset are available at: https:// ***/valeriopaolicelli/SegVPR) that learns robust global embeddings from both visual appearance and semantic content of the data, with the segmentation process being dynamically guided by the recognition of places through a multi-scale attention module. Experiments on various scenarios validate this new approach and demonstrate its performance against state-of-the-art methods. Finally, we propose the first synthetic-world dataset suited for both place recognition and segmentation tasks.

关键词： visual place recognition Segmentation Attention

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Understanding the Effects of visualizing Missing Values on visual data exploration

Understanding the Effects of Visualizing Missing Values on V...

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IEEE visualization conference (IEEE VIS)

作者： Song, Hayeong Fu, Yu Saket, Bahador Stasko, John Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781665433358

When performing data analysis, people often confront data sets containing missing values. We conducted an empirical study to understand the effect of visualizing those missing values on participants' decision-making processes while performing a visual data exploration task. More specifically, our study participants purchased a hypothetical portfolio of stocks based on a data set where some stocks had missing values for attributes such as PE ratio, beta, and EPS. The experiment used scatterplots to communicate the stock data. For one group of participants, stocks with missing values simply were not shown, while the second group saw such stocks depicted with estimated values as points with error bars. We measured participants' cognitive load involved in decision-making with data with missing values. Our results indicate that their decision-making workflow was different across two conditions.

关键词： Human-centered computing visualization Empiriacal evaluation Missing data

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The Impact of conflicts on data Sharing for Disaster Risk Reduction 20

The Impact of conflicts on Data Sharing for Disaster Risk Re...

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20th Global Information Systems for Crisis Response and Management conference, ISCRAM 2023

作者： Adrot, Anouck Aguerre, Mercedes DRM UMR CNRS 7088 Université Paris-Dauphine PSL France French Red Cross France

ISBN: (纸本)9798218217495

Cross-border regions are particularly exposed to hazards and require cooperation for Disaster Risk Reduction (DRR). Accordingly, multiple countries have been investing in technology and jointly innovate to share and process data against disasters. However, these countries’ capacity to share data depends on the history and the context of the border itself. Going further, conflicts between countries – may they be past, present or future - can radically question and endanger collaborative efforts to share data for DRR. This collaborative research, involving a cohort of master students and an NGO, explores the influence of conflicts on data sharing and cooperation for DRR. Still in progress, this research examines how conflicts affect data sharing and how DRR actors manage them. It is based on exploratory archive analysis of three distinct cases of cross-border DRR collaboration within the EU borders, as well as experts and actors interviewing. Preliminary findings reveal that conflicts affect DRR at three levels: i) actors, ii) interactions with DRR actors, iii) relations between local DRR actors and institutions. The expected contribution of this research is theoretical, practical and pedagogical. © 2023 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

关键词： Information management

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Pheno-Mapper: An Interactive Toolbox for the visual exploration of Phenomics data 21

Pheno-Mapper: An Interactive Toolbox for the Visual Explorat...

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12th ACM conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)

作者： Zhou, Youjia Kamruzzaman, Methun Schnable, Patrick Krishnamoorthy, Bala Kalyanaraman, Ananth Wang, Bei Univ Utah Salt Lake City UT 84112 USA Univ Virginia Charlottesville VA USA Iowa State Univ Ames IA USA Washington State Univ Vancouver WA USA

ISBN: (纸本)9781450384506

High-throughput technologies to collect field data have made observations possible at scale in several branches of life sciences. The data collected can range from the molecular level (genotypes) to physiological (phenotypic traits) and environmental observations (e.g., weather, soil conditions). These vast swathes of data, collectively referred to as phenomics data, represent a treasure trove of key scientific knowledge on the dynamics of the underlying biological system. However, extracting information and insights from these complex datasets remains a significant challenge owing to their multidimensionality and lack of prior knowledge about their complex structure. In this paper, we present Pheno-Mapper, an interactive toolbox for the exploratory analysis and visualization of large-scale phenomics data. Our approach uses the mapper framework to perform a topological analysis of the data, and subsequently render visual representations with built-in data analysis and machine learning capabilities. We demonstrate the utility of this new tool on real-world plant (e.g., maize) phenomics datasets. In comparison to existing approaches, the main advantage of Pheno-Mapper is that it provides rich, interactive capabilities in the exploratory analysis of phenomics data, and it integrates visual analytics with data analysis and machine learning in an easily extensible way. In particular, Pheno-Mapper allows the interactive selection of subpopulations guided by a topological summary of the data and applies data mining and machine learning to these selected subpopulations for in-depth exploration.

关键词： phenomics topological data analysis interactive visualization multidimensional biological data

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