Study concerning nonlinear mixing of radio frequency signals in steel structures Final report

Locating technique for nonlinear interference source of radio frequency signals in steel structur

Junction range finder

Electronic system locates interferences in radar reception. System utilizes well known frequency-modulated continuous-wave technique to locate objects with nonlinear impedances. FM transmitter generates signal through bandpass filter which eliminates higher order harmonics around carrier frequency

Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

Listening for the Echoes: Radical Listening as Educator-Activist Praxis

Using a postformal approach to co/autoethnography, the authors examine narrative reflections of their own teaching practice to draw forth implications for radical listening as educator-activist praxis. By using the controlling metaphor of noise, the authors illuminate the challenges of listening radically amidst the “white noise” of hegemony. The authors demonstrate radical listening as echoes of an imperfect praxis of being and becoming that must be revisited repeatedly over time

Distance Dependent Infinite Latent Feature Models

Latent feature models are widely used to decompose data into a small number of components. Bayesian nonparametric variants of these models, which use the Indian buffet process (IBP) as a prior over latent features, allow the number of features to be determined from the data. We present a generalization of the IBP, the distance dependent Indian buffet process (dd-IBP), for modeling non-exchangeable data. It relies on distances defined between data points, biasing nearby data to share more features. The choice of distance measure allows for many kinds of dependencies, including temporal and spatial. Further, the original IBP is a special case of the dd-IBP. In this paper, we develop the dd-IBP and theoretically characterize its feature-sharing properties. We derive a Markov chain Monte Carlo sampler for a linear Gaussian model with a dd-IBP prior and study its performance on several non-exchangeable data sets.Comment: 28 pages, 9 figure

Sources of variation in developmental language disorders: evidence from eye-tracking studies of sentence production

Skilled sentence production involves distinct stages of message conceptualization (deciding what to talk about) and message formulation (deciding how to talk about it). Eye-movement paradigms provide a mechanism for observing how speakers accomplish these aspects of production in real time. These methods have recently been applied to children with autism spectrum disorder (ASD) and specific language impairment (LI) in an effort to reveal qualitative differences between groups in sentence production processes. Findings support a multiple-deficit account in which language production is influenced not only by lexical and syntactic constraints, but also by variation in attention control, inhibition and social competence. Thus, children with ASD are especially vulnerable to atypical patterns of visual inspection and verbal utterance. The potential to influence attentional focus and prime appropriate language structures are considered as a mechanism for facilitating language adaptation and learning

On the well-posedness for the Ideal MHD equations in the Triebel-Lizorkin spaces

In this paper, we prove the local well-posedness for the Ideal MHD equations in the Triebel-Lizorkin spaces and obtain blow-up criterion of smooth solutions. Specially, we fill a gap in a step of the proof of the local well-posedness part for the incompressible Euler equation in \cite{Chae1}.Comment: 16page