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SUNMONTUEWEDTHUFRISAT
University Calendar
Events for October
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Mork Family Department Fall Seminars - Thomas Burbey, Virginia Tech
Tue, Oct 05, 2021 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
University Calendar
Mork Family Department Fall Seminars - Thomas Burbey, Virginia Tech
Host: Prof. Birendra Jha
Join Zoom Meeting
https://usc.zoom.us/j/98225952695?pwd=d0NMenhCNkliR1ZIR1lBamRpZHh1UT09
Meeting ID: 982 2595 2695
Passcode: 322435
WebCast Link: https://usc.zoom.us/j/98225952695?pwd=d0NMenhCNkliR1ZIR1lBamRpZHh1UT09
Audiences: Everyone Is Invited
Contact: Greta Harrison
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Mork Family Department Fall Seminars - Oliver Fiehn, UC, Davis
Tue, Oct 12, 2021 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
University Calendar
Mork Family Department Fall Seminars - Oliver Fiehn, UC, Davis
Host: Prof. Nick Graham
Join Zoom Meeting
https://usc.zoom.us/j/98225952695?pwd=d0NMenhCNkliR1ZIR1lBamRpZHh1UT09
Meeting ID: 982 2595 2695
Passcode: 322435
WebCast Link: https://usc.zoom.us/j/98225952695?pwd=d0NMenhCNkliR1ZIR1lBamRpZHh1UT09
Audiences: Everyone Is Invited
Contact: Greta Harrison
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PhD Defense - Danyong Zhao
Tue, Oct 12, 2021 @ 04:00 PM - 06:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD candidate: Dangyong Zhao
Committee:
Jernej Barbic (Chair)
C.-C. Jay Kuo
Yong Chen
Date and Time: 10/12 at 4pm
Acquisition of Human Tissue Elasticity Properties Using Pressure Sensors
Abstract:
Physically based simulation of the human body in three dimensions is important in many applications in computer graphics, animation, virtual reality, virtual commerce, ergonomics and virtual medicine. Finite Element Method (FEM) is a robust and reliable approach to simulate deformable dynamics of three-dimensional elastic structures. However, for quality simulation that matches the behavior of real human tissues, FEM needs accurate material properties that correctly model real relationships between the strains and stresses in the human tissue. This thesis presents methods to capture such nonlinear materials for the human musculo-skeletal tissue (skin, fat, muscles) in vivo, through carefully designed poking experiments, force meters, lasers and ultrasound measuring devices. From our experiments, we obtain ground-truth relationships between the contact force and skin deformation. We then fit material models that best approximate the acquired real-world data.
First, we design a measuring device that can simultaneously capture the skin contact force and the skin deformation, consisting of a force meter and a laser distance measuring device. We design sliding and pivoting joints to rigidly attach the force meter to the laser device, so that diverse human body locations (arm, hand, belly, etc.) can be measured ergonomically and reliably. We also use an ultrasound device to capture the depth of the human subcutaneous fat at different locations; enabling us to generate a 3d model of the fat layer, and optionally also the muscle layer, of the human body.
Second, we propose a novel approach to equivalently convert 3D FEM simulations into 2D simulation, suitable for our material capture. This method permits us to greatly speed up our material optimizations, without losing any accuracy. We validated this approach by comparing the simulation result from 2D equations and the 3D traditional equations. We propose to use natural cubic splines to parameterize the three separable scalar elastic energy density functions based on the Valanis-Landel material model. Based on our novel 2D simulation method and the spline-based non-linear isotropic material, we present an efficient method to compute the gradient of the objective function for optimization and use the conjugate gradient optimization method to optimize the material.
Lastly, we use our acquired materials to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically based contact between the surface and a deformable human. We model the soft deformable human using a layer of FEM deformable tissue surrounding a rigid core, with measured realistic elastic material properties, and large-deformation nonlinear analysis using our material capturing and optimizing method. We define a novel cost function to measure the ergonomics of contact between the human and the supporting surface. We give a stable and computationally efficient contact model that is differentiable with respect to the supporting surface shape. This makes it possible to optimize our ergonomic cost function using gradient-based optimizers. We 3D-print the optimized shoe sole, measure contact pressure using pressure sensors, and demonstrate that the real unoptimized and optimized pressure distributions qualitatively match those predicted by our simulation.
WebCast Link: https://usc.zoom.us/j/94230145329
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Thesis Proposal - Ritesh Ahuja "Differentially Private Model Publishing for Location Services.
Thu, Oct 14, 2021 @ 01:30 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
Thesis Proposal - Ritesh Ahuja
"Differentially Private Model Publishing for Location Services."
Time:1:30-3:00pm PST, Oct 14 (Thursday)
Committee: Cyrus Shahabi, Aleksandra Korolova, Bhaskar Krishnamachari, Muhammad Naveed, Srivatsan Ravi
Zoom link: https://usc.zoom.us/j/7125668882
Abstract:
Mobile users share their coordinates with service providers (e.g., Google Maps) in exchange for receiving services customized to their location. The service providers analyze the data and publish powerful machine learning models for location search and recommendation. Even though individual location data are not disclosed directly, the model itself retains significant amounts of specific movement details, which in turn may leak sensitive information about an individual. To preserve individual privacy, one must first sanitize location data, which is commonly done using the powerful differential privacy (DP) concept. However, existing solutions fall short of properly capturing skewness inherent to sparse location datasets, and as a result yield poor accuracy
In this proposal, we first focus on the Spatial Range Count primitive that forms the basis for many important applications such as improving POI placement, or studying disease spread. We propose a neural histogram system (SNH) that models spatial datasets such that important density and correlation features present in the data are preserved, even when DP-compliant noise is added. SNH employs a set of neural networks that learn from diverse regions of the dataset and at varying granularities, leading to superior accuracy. We also devise a framework for effective system parameter tuning on top of public data, which helps practitioners set important system parameters while avoiding privacy leakages.
Finally, we focus on the next-location recommendation task, which is fundamentally more challenging. Learning user-user correlations from trajectory data requires increasing the dimensionality of intermediate layers in the neural network, and in the context of privacy-preserving learning, it increases data sensitivity, and requires a large amount of noise to be introduced. We briefly show that specific model architectures and data handling processes during DP-compliant training can significantly boost learning accuracy by keeping under tight control the amount of noise required to meet the privacy constraint. We conclude by suggesting ways to learn even richer models that can accurately recommend to a user entire location sequences, as opposed to only the next location.
WebCast Link: https://usc.zoom.us/j/7125668882
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Mork Family Department Fall Seminars - William Schneider, Notre Dame
Tue, Oct 19, 2021 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
University Calendar
Mork Family Department Fall Seminars - William Schneider, Notre Dame
Host: Prof. Shaama SharadaLocation: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 101
Audiences: Everyone Is Invited
Contact: Greta Harrison
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USC Day of Making w/ YouTube's Allen Pan, USC Makers, USC Robogals
Sat, Oct 23, 2021 @ 11:00 AM - 02:15 PM
USC Viterbi School of Engineering, Viterbi School of Engineering K-12 STEM Center
University Calendar
Join us for a virtual Day of Making!
Hear from USC students and alumni about their journey in developingmaking skills that combine engineering, robotics, and creativity.
See examples of making projects that turn imaginary objects likesuperhero shields and portal guns into reality
11 -“ 11:50 am Allen Pan, host of YouTube channel "Sufficiently Advanced"
https://tinyurl.com/allenpanregister
https://tinyurl.com/dayofmakingregister
12:15pm -“ 1:00pm
Mini Maker Faire with thUSC Makers
1:15pm -“ 2:15pm
Becoming the Next Generation of Innovators with USC Robogals
More Information: Day of Making.pdf
Location: Register for Webinar
Audiences: Everyone Is Invited
Contact: Katie Mills
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Mork Family Department Fall Seminars - Kevin Solomon, University of Delaware
Tue, Oct 26, 2021 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
University Calendar
Mork Family Department Fall Seminars - Kevin Solomon, University of Delaware
Host: Dr. Stacey Finley
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 101
Audiences: Everyone Is Invited
Contact: Greta Harrison
