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I am what i eat: Identity & critical thinking in an online health forum for kids 13

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I am what i eat: Identity & critical thinking in an online h...

31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013

作者： Parker, Andrea Grimes McClendon, Ian Grevet, Catherine Ayo, Victoria Chung, Won Taek Johnson, Veda Mynatt, Elizabeth D. College of Computer and Information Science College of Health Sciences Northeastern University 360 Huntington Ave. Boston MA 02115 United States School of Interactive Computing GVU Center Georgia Institute of Technology 85 5th St. NW Atlanta GA 30308 United States Department of Pediatrics School of Medicine Emory University 49 Jesse Hill Jr. Dr. Atlanta GA 30303 United States

ISBN: (纸本)9781450318990

As kids encounter food advertisements, it is important that they be able to critically evaluate the message's claims, the healthiness of the promoted product and their desire for it. To explore how technology might help kids develop these skills, we created an online forum called TalkBack that encourages children to critically analyze the messaging in food ads and their attitudes towards marketed foods. We evaluated TalkBack with twenty-eight middle school students in a summer camp program. We discuss how participants appeared to project and protect their sense of self through their interaction with TalkBack. We also describe the limited analytic depth of their forum contributions and suggest directions for HCI research that attempts to encourage critical thinking and health promotion in adolescents. Copyright © 2013 ACM.

关键词： Social networking (online)

A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness

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arXiv 2018年

作者： Gietzen, Thomas Brylka, Robert Achenbach, Jascha Hebel, Katjazum Schömer, Elmar Botsch, Mario Schwanecke, Ulrich Schulze, Ralf RheinMain University of Applied Sciences Computing for New Media Wiesbaden Germany Bielefeld University Computer Graphics Group Bielefeld Germany University Medical Center of the Johannes Gutenberg University Mainz Department of Prosthetic Dentistry Mainz Germany Johannes Gutenberg University Mainz Institute of Computer Science Mainz Germany University Medical Center Johannes Gutenberg University Mainz Section of Oral Radiology Mainz Germany

In this paper, we present a method for automated estimation of a human face given a skull remain. The proposed method is based on three statistical models. A volumetric (tetrahedral) skull model encoding the variations of different skulls, a surface head model encoding the head variations, and a dense statistic of facial soft tissue thickness (FSTT). All data are automatically derived from computed tomography (CT) head scans and optical face scans. In order to obtain a proper dense FSTT statistic, we register a skull model to each skull extracted from a CT scan and determine the FSTT value for each vertex of the skull model towards the associated extracted skin surface. The FSTT values at predefined landmarks from our statistic are well in agreement with data from the literature. To recover a face from a skull remain, we first fit our skull model to the given skull. Next, we generate spheres with radius of the respective FSTT value obtained from our statistic at each vertex of the registered skull. Finally, we fit a head model to the union of all spheres. The proposed automated method enables a probabilistic face-estimation that facilitates forensic recovery even from incomplete skull remains. The FSTT statistic allows the generation of plausible head variants, which can be adjusted intuitively using principal component analysis. We validate our face recovery process using an anonymized head CT scan. The estimation generated from the given skull visually compares well with the skin surface extracted from the CT scan itself. Copyright © 2018, The Authors. All rights reserved.

关键词： Statistics

Social media emotion macroscopes reflect emotional experiences in society at large

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arXiv 2021年

作者： Garcia, David Pellert, Max Lasser, Jana Metzler, Hannah Graz University of Technology Institute of Interactive Systems and Data Science Department of Computer Science and Biomedical Engineering Graz8010 Austria Complexity Science Hub Vienna Vienna1080 Austria Medical University of Vienna Center for Medical Statistics Informatics and Intelligent Systems Vienna1090 Austria Medical University of Vienna Department of Social and Preventive Medicine Center for Public Health Vienna1090 Austria

Social media generate data on human behaviour at large scales and over long periods of time, posing a complementary approach to traditional methods in the social sciences1. Millions of texts from social media can be processed with computational methods to study emotions2,3 over time and across regions4,5. However, recent research has shown weak correlations between social media emotions and affect questionnaires at the individual level6,7 and between static regional aggregates of social media emotion and subjective well-being at the population level8, questioning the validity of social media data to study emotions. Yet, to date, no research has tested the validity of social media emotion macroscopes to track the temporal evolution of emotions at the level of a whole society. Here we present a pre-registered prediction study that shows how gender-rescaled time series of Twitter emotional expression at the national level substantially correlate with aggregates of self-reported emotions in a weekly representative survey in the United Kingdom. A follow-up exploratory analysis shows a high prevalence of third-person references in emotionally-charged tweets, indicating that social media data provide a way of social sensing the emotions of others9 rather than just the emotional experiences of users. These results show that, despite the issues that social media have in terms of representativeness10 and algorithmic confounding11, the combination of advanced text analysis methods with user demographic information in social media emotion macroscopes can provide measures that are informative of the general population beyond social media users. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

Deep Video Representation Learning: A Survey

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arXiv 2024年

作者： Ravanbakhsh, Elham Liang, Yongqing Ramanujam, J. Li, Xin Division of Electrical & Computer Engineering Center for Computation & Technology Louisiana State University Baton RougeLA70803 United States Department of Computer Science and Engineering Texas A&M University College StationTX77843 United States Section of Visual Computing and Interactive Media Texas A&M University College StationTX77843 United States

This paper provides a review on representation learning for videos. We classify recent spatio-temporal feature learning methods for sequential visual data and compare their pros and cons for general video analysis. Building effective features for videos is a fundamental problem in computer vision tasks involving video analysis and understanding. Existing features can be generally categorized into spatial and temporal features. Their effectiveness under variations of illumination, occlusion, view and background are discussed. Finally, we discuss the remaining challenges in existing deep video representation learning studies. © 2024, CC BY-NC-ND.

关键词： Deep learning

RoleSeer: Understanding Informal Social Role Changes in MMORPGs via Visual Analytics

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arXiv 2022年

作者： Xie, Laixin Wu, Ziming Xu, Peng Li, Wei Ma, Xiaojuan Li, Quan School of Information Science and Technology ShanghaiTech University Shanghai China Interactive Entertainment Group Tencent Inc. Shenzhen China User Experience Center NetEase Inc. Hangzhou China College of Creative Design Shenzhen Technology University Shenzhen China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

Massively multiplayer online role-playing games create virtual communities that support heterogeneous "social roles" determined by gameplay interaction behaviors under a specific social context. For all social roles, formal roles are pre-defined, obvious, and explicitly ascribed to the people holding the roles, whereas informal roles are not well-defined and unspoken. Identifying the informal roles and understanding their subtle changes are critical to designing sociability mechanisms. However, it is nontrivial to understand the existence and evolution of such roles due to their loosely defined, interconvertible, and dynamic characteristics. We propose a visual analytics system, RoleSeer, to investigate informal roles from the perspectives of behavioral interactions and depict their dynamic interconversions and transitions. Two cases, experts' feedback, and a user study suggest that RoleSeer helps interpret the identified informal roles and explore the patterns behind role changes. We see our approach's potential in investigating informal roles in a broader range of social games. © 2022, CC BY.

关键词： Visualization

How many matchings cover the nodes of a graph?

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arXiv 2018年

作者： Ferhat, Dehia Ait Király, Zoltán Sebo, András Stauffer, Gautier Mentor Graphics Montbonnot Saint Martin France Eötvös University Department of Computer Science Budapest Hungary CNRS G-SCOP Univ. Grenoble Alpes France Center of Excellence in Supply Chain Innovation and Transportation Kedge Business School Talence France

Given an undirected graph, are there k matchings whose union covers all of its nodes, that is, a matching-k-cover? A first, easy polynomial solution from matroid union is possible, as already observed by Wang, Song and Yuan (Mathematical Programming, 2014). However, it was not satisfactory neither from the algorithmic viewpoint nor for proving graphic theorems, since the corresponding matroid ignores the edges of the graph. We prove here, simply and algorithmically: all nodes of a graph can be covered with k ≥ 2 matchings if and only if for every stable set S we have |S| ≤ k · |N(S)|. When k = 1, an exception occurs: this condition is not enough to guarantee the existence of a matching-1-cover, that is, the existence of a perfect matching, in this case Tutte’s famous matching theorem (J. London Math. Soc., 1947) provides the right ‘good’ characterization. The condition above then guarantees only that a perfect 2-matching exists, as known from another theorem of Tutte (Proc. Amer. Math. Soc., 1953). Some results are then deduced as consequences with surprisingly simple proofs, using only the level of difficulty of bipartite matchings. We give some generalizations, as well as a solution for minimization if the edge-weights are non-negative, while the edge-cardinality maximization of matching-2-covers turns out to be already NP-hard. We have arrived at this problem as the line graph special case of a model arising for manufacturing integrated circuits with the technology called ‘Directed Self Assembly’. Copyright © 2018, The Authors. All rights reserved.

关键词： Undirected graphs

Generative Adversarial Network Model to Classify Human Induced Pluripotent Stem Cell-Cardiomyocytes based on Maturation Level

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Research Square

Research Square 2024年 rs3rs-4061531页

作者： Wu, Ziqian Park, Jiyoon Steiner, Paul R. Zhu, Bo Zhang, John X.J. Thayer School of Engineering Dartmouth College HanoverNH United States Dartmouth Hitchcock Medical Center LebanonNH United States The Department of Computer Science Dartmouth College HanoverNH United States The School of Interactive Computing Georgia Institute of Technology GA United States

Objective: Our study develops a generative adversarial network (GAN)-based method that generates faithful synthetic image data of human cardiomyocytes at varying stages in their maturation process, as a tool to significantly enhance the classification accuracy of cells and ultimately assist the throughput of computational analysis of cellular structure and functions. Methods: Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) were cultured on micropatterned collagen coated hydrogels of physiological stiffnesses to facilitate maturation and optical measurements were performed for their structural and functional analyses. Control groups were cultured on collagen coated glass well plates. These image recordings were used as the real data to train the GAN model. Results: The results show the GAN approach is able to replicate true features from the real data, and inclusion of such synthetic data significantly improves the classification accuracy compared to usage of only real experimental data that is often limited in scale and diversity. Conclusion: The proposed model outperformed four conventional machine learning algorithms with respect to improved data generalization ability and data classification accuracy by incorporating synthetic data. Significance: This work demonstrates the importance of integrating synthetic data in situations where there are limited sample sizes and thus, effectively addresses the challenges imposed by data availability. © 2024, CC BY.

关键词： Classification (of information)

I-MPN: Inductive Message Passing Network for Efficient Human-in-the-Loop Annotation of Mobile Eye Tracking Data

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arXiv 2024年

作者： Le, Hoang H. Nguyen, Duy M.H. Bhatti, Omair Shahzad Kopácsi, László Ngo, Thinh P. Nguyen, Binh T. Barz, Michael Sonntag, Daniel Interactive Machine Learning Department Saarbrücken66123 Germany University of Science VNU-HCM Mathematics and Computer Science Department Ho Chi Minh City Viet Nam Quy Nhon AI Research and Development Center FPT Software Viet Nam Stuttgart70569 Germany Univerity of Stuttgart Machine Learning and Simulation Science Department Stuttgart70569 Germany University of Oldenburg Applied Artificial Intelligence Department Oldenburg26129 Germany

Comprehending how humans process visual information in dynamic settings is crucial for psychology and designing user-centered interactions. While mobile eye-tracking systems combining egocentric video and gaze signals can offer valuable insights, manual analysis of these recordings is time-intensive. In this work, we present a novel human-centered learning algorithm designed for automated object recognition within mobile eye-tracking settings. Our approach seamlessly integrates an object detector with a spatial relation-aware inductive message-passing network (I-MPN), harnessing node profile information and capturing object correlations. Such mechanisms enable us to learn embedding functions capable of generalizing to new object angle views, facilitating rapid adaptation and efficient reasoning in dynamic contexts as users navigate their environment. Through experiments conducted on three distinct video sequences, our interactive-based method showcases significant performance improvements over fixed training/testing algorithms, even when trained on considerably smaller annotated samples collected through user feedback. Furthermore, we demonstrate exceptional efficiency in data annotation processes and surpass prior interactive methods that use complete object detectors, combine detectors with convolutional networks, or employ interactive video segmentation. © 2024, CC BY.

关键词： Object detection

Remote computing environment compensating for brain shift

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computer Aided Surgery 2003年第4期8卷 169-179页

作者： Hastreiter, Peter Engel, Klaus Soza, Grzegorz Wolf, Matthias Ganslandt, Oliver Fahlbusch, Rudolf Greiner, Gnther Ximsky, Christopher Department of Neurosurgery Neurocenter Friedrich Alexander University of Erlangen-Nuremberg D-91054 Erlangen Schwabachanlage 6. Germany Computer Graphics Group University of Erlangen-Nuremberg Erlangen Germany Visualization and Interactive Systems Group University of Stuttgart Erlangen Germany Knowledge Processing Group Bavarian Research Center for Knowledge-Based Systems Erlangen Germany

Objective: Anatomical and functional image data become invalid during an operation due to brain shift. Compensation is achieved by using intraoperative imaging to update anatomical information. To accelerate the registration and visualization of pre- and intraoperative image data, the presented work focuses on remote computing capabilities. The underlying framework efficiently combines local desktop computers and remote high-end graphics workstations exploiting expensive hardware. Methods: By performing all computations on the remote computer, the MR volumes are rigidly aligned via voxel-based registration. Using graphics hardware for acceleration, all interpolation operations are performed with 3D texture-mapping hardware. A new approach then transforms functional markers from preoperative measurements to the intraoperative situation using an automatic tracking algorithm to identify corresponding sulci. Communicating Java viewers are suggested for analyzing the results interactively on a local computer, with all calculations being performed exclusively on the remote computer. Results: The suggested approach was successfully applied in S cases using MR data containing functional markers of MEG and fMRI measurements identifying eloquent brain areas. Remote large-scale graphics hardware was thereby efficiently made available for fast registration and interactive direct volume rendering in neurosurgery. Conclusion: Overall, the presented framework demonstrates efficient access of expensive high- end hardware remotely controlled by thin clients, and further emphasizes the need to compensate for brain shift in functional neuronavigation. © 2003 Informa UK Ltd All rights reserved.

关键词： 3D visualization brain shift registration remote computing