6,410 research outputs found
Robust seismic velocity change estimation using ambient noise recordings
We consider the problem of seismic velocity change estimation using ambient
noise recordings. Motivated by [23] we study how the velocity change estimation
is affected by seasonal fluctuations in the noise sources. More precisely, we
consider a numerical model and introduce spatio-temporal seasonal fluctuations
in the noise sources. We show that indeed, as pointed out in [23], the
stretching method is affected by these fluctuations and produces misleading
apparent velocity variations which reduce dramatically the signal to noise
ratio of the method. We also show that these apparent velocity variations can
be eliminated by an adequate normalization of the cross-correlation functions.
Theoretically we expect our approach to work as long as the seasonal
fluctuations in the noise sources are uniform, an assumption which holds for
closely located seismic stations. We illustrate with numerical simulations and
real measurements that the proposed normalization significantly improves the
accuracy of the velocity change estimation
Abstract Interpretation of Supermodular Games
Supermodular games find significant applications in a variety of models,
especially in operations research and economic applications of noncooperative
game theory, and feature pure strategy Nash equilibria characterized as fixed
points of multivalued functions on complete lattices. Pure strategy Nash
equilibria of supermodular games are here approximated by resorting to the
theory of abstract interpretation, a well established and known framework used
for designing static analyses of programming languages. This is obtained by
extending the theory of abstract interpretation in order to handle
approximations of multivalued functions and by providing some methods for
abstracting supermodular games, in order to obtain approximate Nash equilibria
which are shown to be correct within the abstract interpretation framework
Braess's Paradox in Wireless Networks: The Danger of Improved Technology
When comparing new wireless technologies, it is common to consider the effect
that they have on the capacity of the network (defined as the maximum number of
simultaneously satisfiable links). For example, it has been shown that giving
receivers the ability to do interference cancellation, or allowing transmitters
to use power control, never decreases the capacity and can in certain cases
increase it by , where is the
ratio of the longest link length to the smallest transmitter-receiver distance
and is the maximum transmission power. But there is no reason to
expect the optimal capacity to be realized in practice, particularly since
maximizing the capacity is known to be NP-hard. In reality, we would expect
links to behave as self-interested agents, and thus when introducing a new
technology it makes more sense to compare the values reached at game-theoretic
equilibria than the optimum values.
In this paper we initiate this line of work by comparing various notions of
equilibria (particularly Nash equilibria and no-regret behavior) when using a
supposedly "better" technology. We show a version of Braess's Paradox for all
of them: in certain networks, upgrading technology can actually make the
equilibria \emph{worse}, despite an increase in the capacity. We construct
instances where this decrease is a constant factor for power control,
interference cancellation, and improvements in the SINR threshold (),
and is when power control is combined with interference
cancellation. However, we show that these examples are basically tight: the
decrease is at most O(1) for power control, interference cancellation, and
improved , and is at most when power control is
combined with interference cancellation
Investigating the Role of Current Strength in tDCS Modulation of Working Memory Performance in Healthy Controls
Transcranial direct current stimulation (tDCS) is a brain stimulation technique that has the potential to improve working memory (WM) deficits in many clinical disorders. The aim of this study was to investigate the role of current strength on the ability of anodal tDCS to improve WM, and secondly to investigate the time course of effects. Twelve healthy participants underwent three stimulation sessions consisting of 20 min of either 1 mA anodal tDCS, 2 mA anodal tDCS, or sham tDCS to the left dorsolateral prefrontal cortex (DLPFC) localized via F3, all whilst completing a WM task. Intra-stimulation and post-stimulation WM performances were measured using the n-back and Sternberg tasks respectively. Results revealed no significant improvements in participants’ accuracy, but a significant interaction was found with respect to current strength and time for accurate reaction time. The finding provides partial support for the hypothesis, in that it appears current strength may affect aspects of WM performance. However, more research is needed, and a higher difficulty level of WM tasks is one of the suggestions discussed for future research
Circular Networks from Distorted Metrics
Trees have long been used as a graphical representation of species
relationships. However complex evolutionary events, such as genetic
reassortments or hybrid speciations which occur commonly in viruses, bacteria
and plants, do not fit into this elementary framework. Alternatively, various
network representations have been developed. Circular networks are a natural
generalization of leaf-labeled trees interpreted as split systems, that is,
collections of bipartitions over leaf labels corresponding to current species.
Although such networks do not explicitly model specific evolutionary events of
interest, their straightforward visualization and fast reconstruction have made
them a popular exploratory tool to detect network-like evolution in genetic
datasets.
Standard reconstruction methods for circular networks, such as Neighbor-Net,
rely on an associated metric on the species set. Such a metric is first
estimated from DNA sequences, which leads to a key difficulty: distantly
related sequences produce statistically unreliable estimates. This is
problematic for Neighbor-Net as it is based on the popular tree reconstruction
method Neighbor-Joining, whose sensitivity to distance estimation errors is
well established theoretically. In the tree case, more robust reconstruction
methods have been developed using the notion of a distorted metric, which
captures the dependence of the error in the distance through a radius of
accuracy. Here we design the first circular network reconstruction method based
on distorted metrics. Our method is computationally efficient. Moreover, the
analysis of its radius of accuracy highlights the important role played by the
maximum incompatibility, a measure of the extent to which the network differs
from a tree.Comment: Submitte
Efficiency in Multi-objective Games
In a multi-objective game, each agent individually evaluates each overall
action-profile on multiple objectives. I generalize the price of anarchy to
multi-objective games and provide a polynomial-time algorithm to assess it.
This work asserts that policies on tobacco promote a higher economic
efficiency
Race/Ethnicity, Gender, Weight Status, and Colorectal Cancer Screening
Background.
The literature on colorectal cancer (CRC) screening is contradictory regarding the impact of weight status on CRC screening. This study was intended to determine if CRC screening rates among 2005 National Health Interview Survey (NHIS) respondent racial/ethnic and gender subgroups were influenced by weight status. Methods. Univariable and multivariable logistic regression analyses were performed to determine if CRC screening use differed significantly among obese, overweight, and normal-weight individuals in race/ethnic and gender subgroups. Results. Multivariable analyses showed that CRC screening rates did not differ significantly for individuals within these subgroups who were obese or overweight as compared to their normal-weight peers. Conclusion. Weight status does not contribute to disparities in CRC screening in race/ethnicity and gender subgroups
The Complexity of Nash Equilibria in Simple Stochastic Multiplayer Games
We analyse the computational complexity of finding Nash equilibria in simple
stochastic multiplayer games. We show that restricting the search space to
equilibria whose payoffs fall into a certain interval may lead to
undecidability. In particular, we prove that the following problem is
undecidable: Given a game G, does there exist a pure-strategy Nash equilibrium
of G where player 0 wins with probability 1. Moreover, this problem remains
undecidable if it is restricted to strategies with (unbounded) finite memory.
However, if mixed strategies are allowed, decidability remains an open problem.
One way to obtain a provably decidable variant of the problem is restricting
the strategies to be positional or stationary. For the complexity of these two
problems, we obtain a common lower bound of NP and upper bounds of NP and
PSPACE respectively.Comment: 23 pages; revised versio
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