4,760 research outputs found
Overview of Ingard and Maling’s1974 Paper on Physical Principles of Noise Reduction: Energy Considerations, Noise Reducing Elements and Sound Absorbing Materials
Overview of Ingard and Maling’s1974 Paper on Physical Principles of Noise Reduction: Energy Considerations, Noise Reducing Elements and Sound Absorbing Material
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Faculty and student feedback of synchronous distance education in a multi-university learning consortium
The Texas Learning Consortium (TLC) began as a partnership between the foreign language departments at 5 small, private, liberal arts universities, where each specializes in a small number of different world languages to increase the course offerings to their students without the expense of adding additional faculty on every campus. Each university offers their language courses to consortium students in a real-time, interactive, distance education format. In Fall 2017, the consortium expanded beyond foreign languages, and the first engineering course, Statics, was offered in this synchronous, distance format. As background, this paper will provide an overview of the technology used in the classrooms and some of the administrative obstacles that were overcome in scheduling, registration and information technology. The paper will also reflect on the impact of this particular technological implementation on various teaching styles in both foreign language and engineering courses, especially compared to other distance engineering education in the literature, with a purpose of analyzing the model’s suitability for expansion into other engineering courses or a fully accredited consortium based engineering program. Student and faculty satisfaction surveys will additionally provide insight as to whether this distance format is the right fit for campuses used to high-touch learning environments.Cockrell School of Engineerin
Recognizing Focal Liver Lesions in Contrast-Enhanced Ultrasound with Discriminatively Trained Spatio-Temporal Model
The aim of this study is to provide an automatic computational framework to
assist clinicians in diagnosing Focal Liver Lesions (FLLs) in
Contrast-Enhancement Ultrasound (CEUS). We represent FLLs in a CEUS video clip
as an ensemble of Region-of-Interests (ROIs), whose locations are modeled as
latent variables in a discriminative model. Different types of FLLs are
characterized by both spatial and temporal enhancement patterns of the ROIs.
The model is learned by iteratively inferring the optimal ROI locations and
optimizing the model parameters. To efficiently search the optimal spatial and
temporal locations of the ROIs, we propose a data-driven inference algorithm by
combining effective spatial and temporal pruning. The experiments show that our
method achieves promising results on the largest dataset in the literature (to
the best of our knowledge), which we have made publicly available.Comment: 5 pages, 1 figure
Joint Computation and Communication Cooperation for Mobile Edge Computing
This paper proposes a novel joint computation and communication cooperation
approach in mobile edge computing (MEC) systems, which enables user cooperation
in both computation and communication for improving the MEC performance. In
particular, we consider a basic three-node MEC system that consists of a user
node, a helper node, and an access point (AP) node attached with an MEC server.
We focus on the user's latency-constrained computation over a finite block, and
develop a four-slot protocol for implementing the joint computation and
communication cooperation. Under this setup, we jointly optimize the
computation and communication resource allocation at both the user and the
helper, so as to minimize their total energy consumption subject to the user's
computation latency constraint. We provide the optimal solution to this
problem. Numerical results show that the proposed joint cooperation approach
significantly improves the computation capacity and the energy efficiency at
the user and helper nodes, as compared to other benchmark schemes without such
a joint design.Comment: 8 pages, 4 figure
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
Given datasets from multiple domains, a key challenge is to efficiently
exploit these data sources for modeling a target domain. Variants of this
problem have been studied in many contexts, such as cross-domain translation
and domain adaptation. We propose AlignFlow, a generative modeling framework
that models each domain via a normalizing flow. The use of normalizing flows
allows for a) flexibility in specifying learning objectives via adversarial
training, maximum likelihood estimation, or a hybrid of the two methods; and b)
learning and exact inference of a shared representation in the latent space of
the generative model. We derive a uniform set of conditions under which
AlignFlow is marginally-consistent for the different learning objectives.
Furthermore, we show that AlignFlow guarantees exact cycle consistency in
mapping datapoints from a source domain to target and back to the source
domain. Empirically, AlignFlow outperforms relevant baselines on image-to-image
translation and unsupervised domain adaptation and can be used to
simultaneously interpolate across the various domains using the learned
representation.Comment: AAAI 202
Accurate position tracking with a single UWB anchor
Accurate localization and tracking are a fundamental requirement for robotic
applications. Localization systems like GPS, optical tracking, simultaneous
localization and mapping (SLAM) are used for daily life activities, research,
and commercial applications. Ultra-wideband (UWB) technology provides another
venue to accurately locate devices both indoors and outdoors. In this paper, we
study a localization solution with a single UWB anchor, instead of the
traditional multi-anchor setup. Besides the challenge of a single UWB ranging
source, the only other sensor we require is a low-cost 9 DoF inertial
measurement unit (IMU). Under such a configuration, we propose continuous
monitoring of UWB range changes to estimate the robot speed when moving on a
line. Combining speed estimation with orientation estimation from the IMU
sensor, the system becomes temporally observable. We use an Extended Kalman
Filter (EKF) to estimate the pose of a robot. With our solution, we can
effectively correct the accumulated error and maintain accurate tracking of a
moving robot.Comment: Accepted by ICRA202
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