10,059 research outputs found
A Class of Nonconvex Penalties Preserving Overall Convexity in Optimization-Based Mean Filtering
mean filtering is a conventional, optimization-based method to
estimate the positions of jumps in a piecewise constant signal perturbed by
additive noise. In this method, the norm penalizes sparsity of the
first-order derivative of the signal. Theoretical results, however, show that
in some situations, which can occur frequently in practice, even when the jump
amplitudes tend to , the conventional method identifies false change
points. This issue is referred to as stair-casing problem and restricts
practical importance of mean filtering. In this paper, sparsity is
penalized more tightly than the norm by exploiting a certain class of
nonconvex functions, while the strict convexity of the consequent optimization
problem is preserved. This results in a higher performance in detecting change
points. To theoretically justify the performance improvements over
mean filtering, deterministic and stochastic sufficient conditions for exact
change point recovery are derived. In particular, theoretical results show that
in the stair-casing problem, our approach might be able to exclude the false
change points, while mean filtering may fail. A number of numerical
simulations assist to show superiority of our method over mean
filtering and another state-of-the-art algorithm that promotes sparsity tighter
than the norm. Specifically, it is shown that our approach can
consistently detect change points when the jump amplitudes become sufficiently
large, while the two other competitors cannot.Comment: Submitted to IEEE Transactions on Signal Processin
Hydrogen reliquefiers for lunar storage systems
Reliquifier application to eliminate propellant boil off losses in space and lunar storage system
The Influence of Irregularity on the Values of Demand Modifier Factor in ASCE 41-06
In the past two decades, many investigations have been made on the methods related to the seismic retrofitting of the structures. As the real nonlinear behaviors of the elements are considered in these methods, the values of internal forces determined in the members are equal to the real ones. In the structural seismic linear analysis methods the elements behaviors are still assumed linear. In this regard, the passage of structure through yield point borders and the displacement increasing are correspondent to the forces elevation. In FEMA codes, the factors such as demand modifier (m) or increasing capacity ones are presented applying the effects of elements nonlinear behaviors in linear method analysis. In this research the factors recommended in ASCE 41-06 are studied focusing on several symmetrical and asymmetrical concrete moment resisting frame moldings (5, 7 and 10 stories structures) and linear & non linear time history analysis (7 records). In this regard, the method used for scaling earthquake records is the current method presented in UBC97, “nonlinear dynamic analysis (RHA)”. According to this research there is direct relation between irregularity and increasing the amount of distribution among the results. In this way by increasing the eccentricity, difference between obtained results and recommended values will be more than the case with less irregularity
Swiss Supreme Court Refers to the CJEU “Danish cases” in Outbound Dividend Case Involving the Swiss-EU Savings Agreement
Successive Concave Sparsity Approximation for Compressed Sensing
In this paper, based on a successively accuracy-increasing approximation of
the norm, we propose a new algorithm for recovery of sparse vectors
from underdetermined measurements. The approximations are realized with a
certain class of concave functions that aggressively induce sparsity and their
closeness to the norm can be controlled. We prove that the series of
the approximations asymptotically coincides with the and
norms when the approximation accuracy changes from the worst fitting to the
best fitting. When measurements are noise-free, an optimization scheme is
proposed which leads to a number of weighted minimization programs,
whereas, in the presence of noise, we propose two iterative thresholding
methods that are computationally appealing. A convergence guarantee for the
iterative thresholding method is provided, and, for a particular function in
the class of the approximating functions, we derive the closed-form
thresholding operator. We further present some theoretical analyses via the
restricted isometry, null space, and spherical section properties. Our
extensive numerical simulations indicate that the proposed algorithm closely
follows the performance of the oracle estimator for a range of sparsity levels
wider than those of the state-of-the-art algorithms.Comment: Submitted to IEEE Trans. on Signal Processin
Intrinsic localized modes in the charge-transfer solid PtCl
We report a theoretical analysis of intrinsic localized modes in a
quasi-one-dimensional charge-transfer-solid (PtCl). We discuss strongly nonlinear features of resonant Raman
overtone scattering measurements on PtCl, arising from quantum intrinsic
localized (multiphonon) modes (ILMs) and ILM-plus-phonon states. We show, that
Raman scattering data displays clear signs of a non-thermalization of lattice
degrees-of-freedom, manifested in a nonequilibrium density of intrinsic
localized modes.Comment: 4 pages, 4 figures, REVTE
Lagrangian structure of flows in the Chesapeake Bay:Challenges and perspectives on the analysis of estuarine flows
In this work we discuss applications of Lagrangian techniques to study transport properties of flows generated by shallow water models of estuarine flows. We focus on the flow in the Chesapeake Bay generated by Quoddy (see Lynch and Werner, 1991), a finite-element (shallow water) model adopted to the bay by Gross et al. (2001). The main goal of this analysis is to outline the potential benefits of using Lagrangian tools for both understanding transport properties of such flows, and for validating the model output and identifying model deficiencies. We argue that the currently available 2-D Lagrangian tools, including the stable and unstable manifolds of hyperbolic trajectories and techniques exploiting 2-D finite-time Lyapunov exponent fields, are of limited use in the case of partially mixed estuarine flows. A further development and efficient implementation of three-dimensional Lagrangian techniques, as well as improvements in the shallow-water modelling of 3-D velocity fields, are required for reliable transport analysis in such flows. Some aspects of the 3-D trajectory structure in the Chesapeake Bay, based on the Quoddy output, are also discussed
Transparency of 0.2% GdCl3 Doped Water in a Stainless Steel Test Environment
The possibility of neutron and neutrino detection using water Cerenkov
detectors doped with gadolinium holds the promise of constructing very large
high-efficiency detectors with wide-ranging application in basic science and
national security. This study addressed a major concern regarding the
feasibility of such detectors: the transparency of the doped water to the
ultraviolet Cerenkov light. We report on experiments conducted using a 19-meter
water transparency measuring instrument and associated materials test tank.
Sensitive measurements of the transparency of water doped with 0.2% GdCl3 at
337nm, 400nm and 420nm were made using this instrument. These measurements
indicate that GdCl3 is not an appropriate dopant in stainless steel constructed
water Cerenkov detectors.Comment: 17 pages, 11 figures, corrects typos, changes formatting, adds error
bars to figure
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