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8th International conference on Sciences of Electronics, Technologies of Information and Telecommunication, SETIT 2018

作者： Kessentini, Mouna Jeffers, Esther University of Picardie Jules Verne 10 Placette Lafleur Amiens Cédex80027 France

ISBN: (纸本)9783030210045

The visualization of high dimensional data has an important role to play as an artifact supporting exploratory data analysis. There is growing evidence of the effectiveness of information visualization as it provides help in understanding data, increases the level of cognitive functioning and performs pattern recognition. This paper deals with the usefulness of Self-Organizing Map (SOM) neural network in the area of the banking sector. We want to show how SOM can be useful to convert huge amounts of financial data into valuable information used to speed up the decision-making process and facilitate data analysis for deeper understanding © 2020, Springer Nature Switzerland AG.

关键词： Self organizing maps

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The Galactic bulge exploration ii. Line-of-sight velocity templates for single-mode RR Lyrae stars

arXiv

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arXiv 2024年

作者： Prudil, Z. Smolec, R. Kunder, A. Koch-Hansen, A.J. Dékány, I. European Southern Observatory Karl-Schwarzschild-Strasse 2 Garching bei München85748 Germany Astronomisches Rechen-Institut Zentrum für Astronomie der Universität Heidelberg Mönchhofstr. 12-14 HeidelbergD-69120 Germany Nicolaus Copernicus Astronomical Centre Polish Academy of Sciences Bartycka 18 Warszawa00-716 Poland Saint Martin's University 5000 Abbey Way SE LaceyWA98503 United States

We present a new set of tools to derive systemic velocities for single-mode RR Lyrae stars from visual and near-infrared spectra. We derived scaling relations and line-of-sight velocity templates using both APOGEE and Gaia spectroscopic products combined with photometric G-band amplitudes. We provide a means to estimate systemic velocities for the RR Lyrae subclasses, RRab and RRc. Our analysis indicates that the scaling relation between the photometric and line-of-sight velocity amplitudes is nonlinear, with a break in a linear relation occurring around ≈ 0.4 mag in both the V-band and G-band amplitudes. We did not observe such a break in the relation for the first-overtone pulsators. Using stellar pulsation models, we further confirm and examine the nonlinearity in scaling relation for the RRab subclass. We observed little to no variation with stellar parameters (mass, metallicity, and luminosity) in the scaling relation between the photometric and line-of-sight velocity amplitudes for fundamental-mode pulsators. We observed an offset in the scaling relation between the observations and stellar pulsation models, mainly in the low-amplitude RR Lyrae regime. This offset disappears when different sets of convective parameters are used. Thus, the Fourier amplitudes obtained from the photometry and line-of-sight velocity measurements can be utilized to constrain convective parameters of stellar pulsation models. The scaling relations and templates for APOGEE and Gaia data accurately predict systemic velocities compared to literature values. In addition, our tools derived from the Gaia spectra improve the precision of the derived systemic velocities by approximately 50 percent and provide a better description of the uncertainty distribution in comparison with previous studies. Our newly derived tools will be used for RR Lyrae variables observed toward the Galactic bulge. Copyright © 2024, The Authors. All rights reserved.

关键词： Photometry

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Multisensorial tangible user interface for immersive storytelling: A usability pilot study with a visually impaired child 1

Multisensorial tangible user interface for immersive storyte...

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1st Workshop on Technology Enhanced Learning Environments for Blended Education - The Italian e-Learning conference, teleXbe 2021

作者： Somma, Federica Di Fuccio, Raffaele Lattanzio, Lavinia Ferretti, Francesco Natural and Artificial Cognition Laboratory Department of Humanistic Studies University of Naples Federico II Naples80138 Italy Rome00185 Italy Roma Tre University Rome00154 Italy

Haptic and multisensory exploration helps blind children to create mental images and abstract mental processes;it is crucial, then, to organize the learning environment so that they can interact with objects through different sensorimotor channels. Storytelling and narratives are useful practices to develop linguistic, cognitive, emotional and social skills and visually impaired children need to participate in the narrative experience using their body, manipulating objects, listening but also smelling and tasting. New methodologies for interactive storytelling, such as a multisensory Tangible User Interface (TUI), could sustain innovative educative and cognitive interventions to listen and stimulate narratives of children with visual impairments, since the residual senses and abilities are supported and compensated. The purpose of this article is both to describe a multisensory TUI-based methodology developed for the enhancement of the storytelling activity and to present a first usability and engagement pilot study based on a prototype. One 6-years old visually impaired child participated in the study. The procedure involved a TUI pre-training phase and the storytelling phase, in which the participant listened to and interacted with a TUI-augmented story. data, such as participants’ behavior, satisfaction, engagement and TUI’s usability, were collected through observations and specific questionnaires adapted to the participant. Results of the pilot study showed a good level of usability and overall engagement, but above all it allowed us to highlight strengths and weaknesses that we need to address for the improvement of the technology. Future studies’ directions are discussed. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Surveys

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Toward Improving the Evaluation of visual Attention Models: a Crowdsourcing Approach

Toward Improving the Evaluation of Visual Attention Models: ...

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International Joint conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Zanca, Dario Melacci, Stefano Gori, Marco Univ Siena Siena Italy

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169262

Human visual attention is a complex phenomenon. A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient locations (spatial distribution of the fixations), when they look in those locations to understand the temporal development of the exploration (temporal order of the fixations), and how they move from one location to another with respect to the dynamics of the scene and the mechanics of the eyes (dynamics). State-of-the-art models focus on learning saliency maps from human data, a process that only takes into account the spatial component of the phenomenon and ignore its temporal and dynamical counterparts. In this work we focus on the evaluation methodology of models of human visual attention. We underline the limits of the current metrics for saliency prediction and scanpath similarity, and we introduce a statistical measure for the evaluation of the dynamics of the simulated eye movements. While deep learning models achieve astonishing performance in saliency prediction, our analysis shows their limitations in capturing the dynamics of the process. We find that unsupervised gravitational models, despite of their simplicity, outperform all competitors. Finally, exploiting a crowd-sourcing platform, we present a study aimed at evaluating how strongly the scanpaths generated with the unsupervised gravitational models appear plausible to naive and expert human observers.

关键词： visual attention models evaluation scanpath fixations saliency crowd-sourcing

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Relationship Types in visual Analytics 20

Relationship Types in Visual Analytics

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6th International conference on Computer and Technology Applications, ICCTA 2020

作者： Shabdin, Nur Izzati Ya'acob, Suraya Sjarif, Nilam Nur Amir Advance Informatics Department Universiti Teknologi Malaysia Razak Faculty Technology and Informatics Malaysia

ISBN: (纸本)9781450377492

visual analytics are practically an application of the task of transforming the data into meaningful and reliable information in order to synthesize the knowledge about the data. Recently, organizations collect large data with aim of extracting useful information for organizational usage for better decision making. When the organization have a large and complex information, it leads to more complex relationship between the variables in the data. As a consequence, the visual analytics representation must be able to show, visualize and handle for more complex relationship of data. However, the research found the lack of relationship research in current visual analytics that lead difficulties to guide and design new relationship representation. Thus, this research aim to recognize, discover and categorize relationships types of visual analytics in representing a set of analytical data. Design Science Research Methodology has been used as research method for this study. It consists of two activities which are i). identify the visual analytic relationship context and its challenge and ii). analysis of relationship in visual analytics representation. At the end, this study is expected to identify and categorize the visual analytics representation according to six relationship types. This identification can help the visual analytics community to understand the primary and basic concept of relationship representation as a guidelines and knowledge for more comprehensive research in the future. © 2020 ACM.

关键词： Decision making

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Overview of the ImageCLEF 2021: Multimedia Retrieval in Medical, Nature, Internet and Social Media Applications 12th

Overview of the ImageCLEF 2021: Multimedia Retrieval in Medi...

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12th International conference of the CLEF Association (CLEF)

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Ben Abacha, Asma Sarrouti, Mourad Demner-Fushman, Dina Hasan, Sadid A. Kozlovski, Serge Liauchuk, Vitali Cid, Yashin Dicente Kovalev, Vassili Pelka, Obioma de Herrera, Alba Garcia Seco Jacutprakart, Janadhip Friedrich, Christoph M. Berari, Raul Tauteanu, Andrei Fichou, Dimitri Brie, Paul Dogariu, Mihai Stefan, Liviu Daniel Constantin, Mihai Gabriel Chamberlain, Jon Campello, Antonio Clark, Adrian Oliver, Thomas A. Moustahfid, Hassan Popescu, Adrian Deshayes-Chossart, Jerome Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Delemont Switzerland Univ La Rochelle La Rochelle France Natl Lib Med Bethesda MD USA CVS Hlth Wellesley MA USA United Inst Informat Problems Minsk BELARUS Univ Warwick Coventry W Midlands England Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England TeleportHQ Cluj Napoca Romania Wellcome Trust Res Labs London England Pacific Isl Fisheries Sci Ctr Silver Spring MD USA Univ Paris Saclay List CEA Palaiseau France

ISBN: (纸本)9783030852504;9783030852511

This paper presents an overview of the ImageCLEF 2021 lab that was organized as part of the conference and Labs of the Evaluation Forum - CLEF Labs 2021. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2021, the 19th edition of ImageCLEF runs four main tasks: (i) a medical task that groups three previous tasks, i.e., caption analysis, tuberculosis prediction, and medical visual question answering and question generation, (ii) a nature coral task about segmenting and labeling collections of coral reef images, (iii) an Internet task addressing the problems of identifying hand-drawn and digital user interface components, and (iv) a new social media aware task on estimating potential real-life effects of online image sharing. Despite the current pandemic situation, the benchmark campaign received a strong participation with over 38 groups submitting more than 250 runs.

关键词： visual question answering and generation Medical image classification Coral image segmentation and classification Recognition of website user interface components Prediction of effects of online image sharing ImageCLEF lab

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Collaboration Spotting X - A visual Network exploration Tool

Collaboration Spotting X - A Visual Network Exploration Tool

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International conference on Social Networks analysis, Management and Security (SNAMS)

作者： Aleksandar Bobic Jean–Mariele Goff Christian Guetl IPT Department CERN GenevaSwitzerland CoDiS Lab ISDS Graz University of Technology Graz Austria

ISBN: (纸本)9781665494960

Due to many technological advancements, the amount of connected data drastically increased in the last decade. The analysis of this data and the insights it generates show great potential for supporting decision making processes in various industries and aspects of our lives. Multiple visual analytics solutions have been proposed to gain further insights into such data and gain explainable results. However, the majority of existing solutions are either closed sourced, not available or no longer developed. To mitigate the issues above and based on findings from expert interviews conducted using an existing tool, this paper introduces Collaboration Spotting X, a new network-based interactive visual analytics and information retrieval tool prototype. This prototype enables users to explore connected network datasets such as social network data and bibliometric data using multiple visual cues and interactions. Furthermore, to gain an insight into how this prototype is perceived by users and identify further improvements, a preliminary study with a class of 37 computer science graduate students is described. The study findings show that the students perceive Collaboration Spotting X as a useful tool that helps them complete tasks through visualisation and interaction. Additionally, multiple aspects were identified that might have caused users to experience in addition to positive emotions also some negative emotions during usage. These aspects might have also contributed to a lower usability score. Finally, multiple improvement directions have been identified, which will be implemented in future developments.

关键词： Computer science Industries Social networking (online) visual analytics Prototypes Collaboration Security

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Intelligent Blockage Recognition using Cellular mmWave Beamforming data: Feasibility Study

Intelligent Blockage Recognition using Cellular mmWave Beamf...

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GLOBECOM 2022 - 2022 IEEE Global Communications conference

作者： Bram van Berlo Yang Miao Rizqi Hersyandika Nirvana Meratnia Tanir Ozcelebi Andre Kokkeler Sofie Pollin Mathematics and Computer Science Eindhoven University of Technology the Netherlands Radio Systems University of Twente the Netherlands Networked Systems Katholieke Universiteit Leuven Belgium

ISBN: (纸本)9781665435413

Joint Communication and Sensing (JCAS) is envisioned for 6G cellular networks, where sensing the operation environment, especially in presence of humans, is as important as the high-speed wireless connectivity. Sensing, and subsequently recognizing blockage types, is an initial step towards signal blockage avoidance. In this context, we investigate the feasibility of using human motion recognition as a surrogate task for blockage type recognition through a set of hypothesis validation experiments using both qualitative and quantitative analysis (visual inspection and hyperparameter tuning of deep learning (DL) models, respectively). A surrogate task is useful for DL model testing and/or pre-training, thereby requiring a low amount of data to be collected from the eventual JCAS environment. Therefore, we collect and use a small dataset from a 26 GHz cellular multi-user communication device with hybrid beamforming. The data is converted into Doppler Frequency Spectrum (DFS) and used for hypothesis validations. Our research shows that (i) the presence of domain shift between data used for learning and inference requires use of DL models that can successfully handle it, (ii) DFS input data dilution to increase dataset volume should be avoided, (iii) a small volume of input data is not enough for reasonable inference performance, (iv) higher sensing resolution, causing lower sensitivity, should be handled by doing more activities/gestures per frame and lowering sampling rate, and (v) a higher reported sampling rate to STFT during pre-processing may increase performance, but should always be tested on a per learning task basis.

关键词： Wireless communication Wireless sensor networks visualization Array signal processing Statistical analysis data models Sensors

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Designing for visual data exploration in Multi-Device Environments

Designing for Visual Data Exploration in Multi-Device Enviro...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Horak, Tom Tech Univ Dresden Interact Media Lab Dresden Germany

ISBN: (纸本)9781450359719

Multi-device environments have an enormous potential to enable more flexible workflows during our daily work. At the same time, visual data exploration is characterized as a fragmented sensemaking process requiring a high degree of flexibility. In my thesis, I am aiming to bring these two worlds into symbiosis, specifically for sensemaking with multivariate data visualizations and graph visualizations. This involves three main objectives: (i) understanding the devices' roles in dynamic device ensembles and their relations to exploration patterns, (ii) identifying mechanisms for adapting visualizations for different devices while preserving a consistent perception and interaction, and, finally, (iii) supporting users and developers in designing such distributed visualization interfaces, e.g., through specific guidelines. As specific contributions, it is planned that (i) and (ii) emerge into a design space, while (iii) leads to a set of heuristics. So far, I was able to extensively work on the first objective as well as to touch on the other two.

关键词： visual data analysis cross-device interaction mobile visualization

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Chinese Painting Algorithm: A Study of Scene Characterization by Chromatographic Multiple analysis and Handwriting Co-construction

Chinese Painting Algorithm: A Study of Scene Characterizatio...

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2022 IEEE/WIC/ACM International Joint conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Ziyang Weng Weixin Yan Yidan Hu Zhimo Weng School of Information Management Wuhan University Wuhan China Art Technology Lab Shenzhen Museum of Contemporary Art and Urban Planning Shenzhen China China-Korea Institute of New Media Zhongnan University of Economics and Law Wuhan China

The understanding of scene representation is a deep knowledge service structure strategy arising from the increasing scale of data and the need for complex logic solving. This study proposes a modeling improvement method based on the fusion of complex feature data and exploration behavior trajectory extremes, which effectively utilizes the artistic feature study of the interplay between the unique colorant mixture attachment features of Chinese painting and complex handwriting features as the orientation region, realizes the classification constraint of colorant data through multispectral detection, and characterizes the handwriting as the behavior law, realizes the parametric extraction and then couples the solution encoding to complete the improvement of the algorithm. Since all scenes in Chinese painting are recorded in the bearer medium with handwriting characteristics after mixing Chinese brushes and colorants, the computational model of Chinese painting algorithm proposed in this paper starts from the processing of representation hierarchical structure and painting behavior of various scenes deposited to realize the principle of describing their material deposition goals and information exchange functions. The experimental analysis shows that i. deep knowledge understanding achieves the derivation of sparse feature validity, ii. the coverage calculation obtained by drawing on technological means can vividly describe the implicit characteristics of handwriting behavior, and iii. the improved modeling process has more humanized perceptual habits and enhances the accuracy and robustness of service domain requirements.

关键词： Self-organizing feature maps Distributed databases Prediction algorithms Feature extraction data models Robustness Behavioral sciences

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