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December 21, 2020 May Yen, Francesco Colella, Harri Kytomaa, Boyd Allin, Alex Ockfen
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Contact Burn Injuries Part I: The influence of object thermal mass

This paper is the first of a two-part series that discusses a numerical methodology that relies on the concept of cumulative equivalent exposure to evaluate contact burn injury thresholds.
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December 21, 2020 May Yen, Francesco Colella, Harri Kytomaa, Boyd Allin, Alex Ockfen
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Contact Burn Injuries Part II: The influence of object shape, size, contact resistance, and applied heat flux

This paper is the second of a two-part series that discusses a numerical methodology that relies on the concept of cumulative equivalent exposure to evaluate contact burn injury thresholds. In Part I, the effect of a finite thermal mass is analyzed for an infinite plate of several finite thicknesses. In Part II, the sensitivities to object shape, size, thickness, contact resistance and applied heat flux are considered.
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November 9, 2020 Aakar Gupta, Majed Samad, Kenrick Kin, Per Ola Kristensson, Hrvoje Benko
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Investigating Remote Tactile Feedback for Mid-Air Text-Entry in Virtual Reality

In this paper, we investigate the utility of remote tactile feedback for freehand text-entry on a mid-air Qwerty keyboard in VR. To that end, we use insights from prior work to design a virtual keyboard along with different forms of tactile feedback, both spatial and non-spatial, for fingers and for wrists.
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October 19, 2020 Jun Gong, Aakar Gupta, Hrvoje Benko
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Acustico: Surface Tap Detection and Localization using Wrist-based Acoustic TDOA Sensing

In this paper, we present Acustico, a passive acoustic sensing approach that enables tap detection and 2D tap localization on uninstrumented surfaces using a wrist-worn device. Our technique uses a novel application of acoustic time differences of arrival (TDOA) analysis.
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October 17, 2020 Justin Cheng, Moira Burke, Bethany de Gant
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Country Differences in Social Comparison on Social Media

Social comparison is a common focus in discussions of online social media use and differences in its frequency, causes, and outcomes may arise from country or cultural differences. To understand how these differences play a role in experiences of social comparison on Facebook, a survey of 37,729 people across 18 countries was paired with respondents’ activity on Facebook.
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September 26, 2020 Edbert J. Sie, Hui Chen, E-Fann Saung, Ryan Catoen, Tobias Tiecke, Mark A. Chevillet, Francesco Marsili
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High-sensitivity multispeckle diffuse correlation spectroscopy

Cerebral blood flow is an important biomarker of brain health and function as it regulates the delivery of oxygen and substrates to tissue and the removal of metabolic waste products. Moreover, blood flow changes in specific areas of the brain are correlated with neuronal activity in those areas. Diffuse correlation spectroscopy (DCS) is a promising noninvasive optical technique for monitoring cerebral blood flow and for measuring cortex functional activation tasks. However, the current state-of-the-art DCS adoption is hindered by a trade-off between sensitivity to the cortex and signal-to-noise ratio (SNR).
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September 7, 2020 Devi Parikh, Larry Zitnick
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Exploring Crowd Co-creation Scenarios for Sketches

As a first step towards studying the ability of human crowds and machines to effectively co-create, we explore several human-only collaborative co-creation scenarios. The goal in each scenario is to create a digital sketch using a simple web interface.
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September 7, 2020 X. Alice Li, Devi Parikh
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Lemotif: An Affective Visual Journal Using Deep Neural Networks

We present Lemotif, an integrated natural language processing and image generation system that uses machine learning to (1) parse a text-based input journal entry describing the user’s day for salient themes and emotions and (2) visualize the detected themes and emotions in creative and appealing image motifs.
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September 7, 2020 Devi Parikh
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Predicting A Creator’s Preferences In, and From, Interactive Generative Art

We train machine learning models to predict a subset of preferences from the rest. We find that preferences in the generative art form cannot predict preferences in other walks of life better than chance (and vice versa). However, preferences within the generative art form are reliably predictive of each other.
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September 7, 2020 Gunjan Aggarwal, Devi Parikh
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Neuro-Symbolic Generative Art: A Preliminary Study

As a preliminary study, we train a generative deep neural network on samples from the symbolic approach. We demonstrate through human studies that subjects find the final artifacts and the creation process using our neurosymbolic approach to be more creative than the symbolic approach 61% and 82% of the time respectively.
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