9,060 research outputs found
A finite difference solution for the cylindrical expansion of a gas cloud into vacuum
Finite difference method for solution of cylindrical expansion of gas cloud into vacuu
Network Lasso: Clustering and Optimization in Large Graphs
Convex optimization is an essential tool for modern data analysis, as it
provides a framework to formulate and solve many problems in machine learning
and data mining. However, general convex optimization solvers do not scale
well, and scalable solvers are often specialized to only work on a narrow class
of problems. Therefore, there is a need for simple, scalable algorithms that
can solve many common optimization problems. In this paper, we introduce the
\emph{network lasso}, a generalization of the group lasso to a network setting
that allows for simultaneous clustering and optimization on graphs. We develop
an algorithm based on the Alternating Direction Method of Multipliers (ADMM) to
solve this problem in a distributed and scalable manner, which allows for
guaranteed global convergence even on large graphs. We also examine a
non-convex extension of this approach. We then demonstrate that many types of
problems can be expressed in our framework. We focus on three in particular -
binary classification, predicting housing prices, and event detection in time
series data - comparing the network lasso to baseline approaches and showing
that it is both a fast and accurate method of solving large optimization
problems
Towards Interpretable Deep Learning Models for Knowledge Tracing
As an important technique for modeling the knowledge states of learners, the
traditional knowledge tracing (KT) models have been widely used to support
intelligent tutoring systems and MOOC platforms. Driven by the fast
advancements of deep learning techniques, deep neural network has been recently
adopted to design new KT models for achieving better prediction performance.
However, the lack of interpretability of these models has painfully impeded
their practical applications, as their outputs and working mechanisms suffer
from the intransparent decision process and complex inner structures. We thus
propose to adopt the post-hoc method to tackle the interpretability issue for
deep learning based knowledge tracing (DLKT) models. Specifically, we focus on
applying the layer-wise relevance propagation (LRP) method to interpret
RNN-based DLKT model by backpropagating the relevance from the model's output
layer to its input layer. The experiment results show the feasibility using the
LRP method for interpreting the DLKT model's predictions, and partially
validate the computed relevance scores from both question level and concept
level. We believe it can be a solid step towards fully interpreting the DLKT
models and promote their practical applications in the education domain
Theory of pressure acoustics with boundary layers and streaming in curved elastic cavities
The acoustic fields and streaming in a confined fluid depend strongly on the
acoustic boundary layer forming near the wall. The width of this layer is
typically much smaller than the bulk length scale set by the geometry or the
acoustic wavelength, which makes direct numerical simulations challenging.
Based on this separation in length scales, we extend the classical theory of
pressure acoustics by deriving a boundary condition for the acoustic pressure
that takes boundary-layer effects fully into account. Using the same
length-scale separation for the steady second-order streaming, and combining it
with time-averaged short-range products of first-order fields, we replace the
usual limiting-velocity theory with an analytical slip-velocity condition on
the long-range streaming field at the wall. The derived boundary conditions are
valid for oscillating cavities of arbitrary shape and wall motion as long as
the wall curvature and displacement amplitude are both sufficiently small.
Finally, we validate our theory by comparison with direct numerical simulation
in two examples of two-dimensional water-filled cavities: The well-studied
rectangular cavity with prescribed wall actuation, and the more generic
elliptical cavity embedded in an externally actuated rectangular elastic glass
block.Comment: 18 pages, 5 figures, pdfLatex, RevTe
Optical conductivity for a dimer in the Dynamic Hubbard model
The Dynamic Hubbard Model represents the physics of a multi-band Hubbard
model by using a pseudo-spin degree of freedom to dynamically modify the
on-site Coulomb interaction. Here we use a dimer system to obtain analytical
results for this model. The spectral function and the optical conductivity are
calculated analytically for any number of electrons, and the distribution of
optical spectral weight is analyzed in great detail. The impact of polaron-like
effects due to overlaps between pseudo-spin states on the optical spectral
weight distribution is derived analytically. Our conclusions support results
obtained previously with different models and techniques: holes are less mobile
than electrons.Comment: 11 pages, 4 figure
Field evolution of the magnetic structures in ErTiO through the critical point
We have measured neutron diffraction patterns in a single crystal sample of
the pyrochlore compound ErTiO in the antiferromagnetic phase
(T=0.3\,K), as a function of the magnetic field, up to 6\,T, applied along the
[110] direction. We determine all the characteristics of the magnetic structure
throughout the quantum critical point at =2\,T. As a main result, all Er
moments align along the field at and their values reach a minimum. Using
a four-sublattice self-consistent calculation, we show that the evolution of
the magnetic structure and the value of the critical field are rather well
reproduced using the same anisotropic exchange tensor as that accounting for
the local paramagnetic susceptibility. In contrast, an isotropic exchange
tensor does not match the moment variations through the critical point. The
model also accounts semi-quantitatively for other experimental data previously
measured, such as the field dependence of the heat capacity, energy of the
dispersionless inelastic modes and transition temperature.Comment: 7 pages; 8 figure
A finite difference solution for the two- dimensional expansion of a finite cylindrical gas cloud into a vacuum
Interaction of radial and axial rarefaction waves investigated by considering expansion of finite length cylindrical gas cloud into vacuu
Ground State and Resonances in the Standard Model of Non-relativistic QED
We prove existence of a ground state and resonances in the standard model of
the non-relativistic quantum electro-dynamics (QED). To this end we introduce a
new canonical transformation of QED Hamiltonians and use the spectral
renormalization group technique with a new choice of Banach spaces.Comment: 50 pages change
Establishing operant conflict tests for the translational study of anxiety in mice
Rationale
In conflict-based anxiety tests, rodents decide between actions with simultaneous rewarding and aversive outcomes. In humans, computerised operant conflict tests have identified response choice, latency, and vigour as distinct behavioural components. Animal operant conflict tests for measurement of these components would facilitate translational study.
Objectives
In C57BL/6 mice, two operant conflict tests for measurement of response choice, latency, and vigour were established, and effects of chlordiazepoxide (CDZ) thereon investigated.
Methods
Mice were moderately diet-restricted to increase sucrose reward salience. A 1-lever test required responding under medium-effort reward/threat conditions of variable ratio 2–10 resulting in sucrose at p = 0.7 and footshock at p = 0.3. A 2-lever test mandated a choice between low-effort reward/threat with a fixed-ratio (FR) 2 lever yielding sucrose at p = 0.7 and footshock at p = 0.3 versus high-effort reward/no threat with a FR 20 lever yielding sucrose at p = 1.
Results
In the 1-lever test, CDZ (7.5 or 15 mg/kg i.p.) reduced post-trial pause (response latency) following either sucrose or footshock and reduced inter-response interval (increased response vigour) after footshock. In the 2-lever test, mice favoured the FR2 lever and particularly at post-reward trials. CDZ increased choice of FR2 and FR20 responding after footshock, reduced response latency overall, and increased response vigour at the FR2 lever and after footshock specifically.
Conclusions
Mouse operant conflict tests, especially 2-lever choice, allow for the translational study of distinct anxiety components. CDZ influences each component by ameliorating the impact of both previous punishment and potential future punishment
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