3,981 research outputs found
Environmental and workplace contamination in the semiconductor industry: implications for future health of the workforce and community.
The semiconductor industry has been an enormous worldwide growth industry. At the heart of computer and other electronic technological advances, the environment in and around these manufacturing facilities has not been scrutinized to fully detail the health effects to the workers and the community from such exposures. Hazard identification in this industry leads to the conclusion that there are many sources of potential exposure to chemicals including arsenic, solvents, photoactive polymers and other materials. As the size of the semiconductor work force expands, the potential for adverse health effects, ranging from transient irritant symptoms to reproductive effects and cancer, must be determined and control measures instituted. Risk assessments need to be effected for areas where these facilities conduct manufacturing. The predominance of women in the manufacturing areas requires evaluating the exposures to reproductive hazards and outcomes. Arsenic exposures must also be evaluated and minimized, especially for maintenance workers; evaluation for lung and skin cancers is also appropriate
On the maximum size of an anti-chain of linearly separable sets and convex pseudo-discs
We show that the maximum cardinality of an anti-chain composed of
intersections of a given set of n points in the plane with half-planes is close
to quadratic in n. We approach this problem by establishing the equivalence
with the problem of the maximum monotone path in an arrangement of n lines. For
a related problem on antichains in families of convex pseudo-discs we can
establish the precise asymptotic bound: it is quadratic in n. The sets in such
a family are characterized as intersections of a given set of n points with
convex sets, such that the difference between the convex hulls of any two sets
is nonempty and connected.Comment: 10 pages, 3 figures. revised version correctly attributes the idea of
Section 3 to Tverberg; and replaced k-sets by "linearly separable sets" in
the paper and the title. Accepted for publication in Israel Journal of
Mathematic
The Combinatorial World (of Auctions) According to GARP
Revealed preference techniques are used to test whether a data set is
compatible with rational behaviour. They are also incorporated as constraints
in mechanism design to encourage truthful behaviour in applications such as
combinatorial auctions. In the auction setting, we present an efficient
combinatorial algorithm to find a virtual valuation function with the optimal
(additive) rationality guarantee. Moreover, we show that there exists such a
valuation function that both is individually rational and is minimum (that is,
it is component-wise dominated by any other individually rational, virtual
valuation function that approximately fits the data). Similarly, given upper
bound constraints on the valuation function, we show how to fit the maximum
virtual valuation function with the optimal additive rationality guarantee. In
practice, revealed preference bidding constraints are very demanding. We
explain how approximate rationality can be used to create relaxed revealed
preference constraints in an auction. We then show how combinatorial methods
can be used to implement these relaxed constraints. Worst/best-case welfare
guarantees that result from the use of such mechanisms can be quantified via
the minimum/maximum virtual valuation function
From Random Matrices to Stochastic Operators
We propose that classical random matrix models are properly viewed as finite
difference schemes for stochastic differential operators. Three particular
stochastic operators commonly arise, each associated with a familiar class of
local eigenvalue behavior. The stochastic Airy operator displays soft edge
behavior, associated with the Airy kernel. The stochastic Bessel operator
displays hard edge behavior, associated with the Bessel kernel. The article
concludes with suggestions for a stochastic sine operator, which would display
bulk behavior, associated with the sine kernel.Comment: 41 pages, 5 figures. Submitted to Journal of Statistical Physics.
Changes in this revision: recomputed Monte Carlo simulations, added reference
[19], fit into margins, performed minor editin
Eigenvalue distributions for some correlated complex sample covariance matrices
The distributions of the smallest and largest eigenvalues for the matrix
product , where is an complex Gaussian matrix
with correlations both along rows and down columns, are expressed as determinants. In the case of correlation along rows, these expressions are
computationally more efficient than those involving sums over partitions and
Schur polynomials reported recently for the same distributions.Comment: 11 page
Random Matrix Theory Analysis of Cross Correlations in Financial Markets
We confirm universal behaviors such as eigenvalue distribution and spacings
predicted by Random Matrix Theory (RMT) for the cross correlation matrix of the
daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been
reported for New York Stock Exchange in previous studies. It is shown that the
random part of the eigenvalue distribution of the cross correlation matrix is
stable even when deterministic correlations are present. Some deviations in the
small eigenvalue statistics outside the bounds of the universality class of RMT
are not completely explained with the deterministic correlations as proposed in
previous studies. We study the effect of randomness on deterministic
correlations and find that randomness causes a repulsion between deterministic
eigenvalues and the random eigenvalues. This is interpreted as a reminiscent of
``level repulsion'' in RMT and explains some deviations from the previous
studies observed in the market data. We also study correlated groups of issues
in these markets and propose a refined method to identify correlated groups
based on RMT. Some characteristic differences between properties of Tokyo Stock
Exchange and New York Stock Exchange are found.Comment: RevTex, 17 pages, 8 figure
Affine Subspace Representation for Feature Description
This paper proposes a novel Affine Subspace Representation (ASR) descriptor
to deal with affine distortions induced by viewpoint changes. Unlike the
traditional local descriptors such as SIFT, ASR inherently encodes local
information of multi-view patches, making it robust to affine distortions while
maintaining a high discriminative ability. To this end, PCA is used to
represent affine-warped patches as PCA-patch vectors for its compactness and
efficiency. Then according to the subspace assumption, which implies that the
PCA-patch vectors of various affine-warped patches of the same keypoint can be
represented by a low-dimensional linear subspace, the ASR descriptor is
obtained by using a simple subspace-to-point mapping. Such a linear subspace
representation could accurately capture the underlying information of a
keypoint (local structure) under multiple views without sacrificing its
distinctiveness. To accelerate the computation of ASR descriptor, a fast
approximate algorithm is proposed by moving the most computational part (ie,
warp patch under various affine transformations) to an offline training stage.
Experimental results show that ASR is not only better than the state-of-the-art
descriptors under various image transformations, but also performs well without
a dedicated affine invariant detector when dealing with viewpoint changes.Comment: To Appear in the 2014 European Conference on Computer Visio
Error analysis of free probability approximations to the density of states of disordered systems
Theoretical studies of localization, anomalous diffusion and ergodicity
breaking require solving the electronic structure of disordered systems. We use
free probability to approximate the ensemble- averaged density of states
without exact diagonalization. We present an error analysis that quantifies the
accuracy using a generalized moment expansion, allowing us to distinguish
between different approximations. We identify an approximation that is accurate
to the eighth moment across all noise strengths, and contrast this with the
perturbation theory and isotropic entanglement theory.Comment: 5 pages, 3 figures, submitted to Phys. Rev. Let
Schubert Polynomials for the affine Grassmannian of the symplectic group
We study the Schubert calculus of the affine Grassmannian Gr of the
symplectic group. The integral homology and cohomology rings of Gr are
identified with dual Hopf algebras of symmetric functions, defined in terms of
Schur's P and Q-functions. An explicit combinatorial description is obtained
for the Schubert basis of the cohomology of Gr, and this is extended to a
definition of the affine type C Stanley symmetric functions. A homology Pieri
rule is also given for the product of a special Schubert class with an
arbitrary one.Comment: 45 page
Noise Dressing of Financial Correlation Matrices
We show that results from the theory of random matrices are potentially of
great interest to understand the statistical structure of the empirical
correlation matrices appearing in the study of price fluctuations. The central
result of the present study is the remarkable agreement between the theoretical
prediction (based on the assumption that the correlation matrix is random) and
empirical data concerning the density of eigenvalues associated to the time
series of the different stocks of the S&P500 (or other major markets). In
particular the present study raises serious doubts on the blind use of
empirical correlation matrices for risk management.Comment: Latex (Revtex) 3 pp + 2 postscript figures (in-text
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