1,419 research outputs found
Kantian fractionalization predicts the conflict propensity of the international system
The study of complex social and political phenomena with the perspective and
methods of network science has proven fruitful in a variety of areas, including
applications in political science and more narrowly the field of international
relations. We propose a new line of research in the study of international
conflict by showing that the multiplex fractionalization of the international
system (which we label Kantian fractionalization) is a powerful predictor of
the propensity for violent interstate conflict, a key indicator of the system's
stability. In so doing, we also demonstrate the first use of multislice
modularity for community detection in a multiplex network application. Even
after controlling for established system-level conflict indicators, we find
that Kantian fractionalization contributes more to model fit for violent
interstate conflict than previously established measures. Moreover, evaluating
the influence of each of the constituent networks shows that joint democracy
plays little, if any, role in predicting system stability, thus challenging a
major empirical finding of the international relations literature. Lastly, a
series of Granger causal tests shows that the temporal variability of Kantian
fractionalization is consistent with a causal relationship with the prevalence
of conflict in the international system. This causal relationship has
real-world policy implications as changes in Kantian fractionalization could
serve as an early warning sign of international instability.Comment: 17 pages + 17 pages designed as supplementary online materia
Wavelets and Fast Numerical Algorithms
Wavelet based algorithms in numerical analysis are similar to other transform
methods in that vectors and operators are expanded into a basis and the
computations take place in this new system of coordinates. However, due to the
recursive definition of wavelets, their controllable localization in both space
and wave number (time and frequency) domains, and the vanishing moments
property, wavelet based algorithms exhibit new and important properties.
For example, the multiresolution structure of the wavelet expansions brings
about an efficient organization of transformations on a given scale and of
interactions between different neighbouring scales. Moreover, wide classes of
operators which naively would require a full (dense) matrix for their numerical
description, have sparse representations in wavelet bases. For these operators
sparse representations lead to fast numerical algorithms, and thus address a
critical numerical issue.
We note that wavelet based algorithms provide a systematic generalization of
the Fast Multipole Method (FMM) and its descendents.
These topics will be the subject of the lecture. Starting from the notion of
multiresolution analysis, we will consider the so-called non-standard form
(which achieves decoupling among the scales) and the associated fast numerical
algorithms. Examples of non-standard forms of several basic operators (e.g.
derivatives) will be computed explicitly.Comment: 32 pages, uuencoded tar-compressed LaTeX file. Uses epsf.sty (see
`macros'
Does Aid translate into Bilateral Trade? Findings for Recipient Countries
This paper uses the gravity model of trade to investigate the link between foreign aid and exports in recipient countries. Most of the theoretical work emphasizes the negative impact of aid on recipient countries' exports primarily due to exchange rate appreciation, disregarding possible positive effects of aid in overcoming supply bottlenecks and promoting bilateral trade relations. Our empirical findings -all based on endogeneity-proof techniques (such as Dynamic OLS or more refined techniques) - depend very strongly on whether bilateral trade relations and autocorrelation of the disturbances are controlled for. When not controlling for these phenomena, the impact of aid is quite substantial (especially in Asia, Latin America & Caribbean) but when sound estimation techniques are applied the net impact of aid on recipient countries' exports becomes insignificant in the full 130-country sample and the subsamples: Sub-Saharan Africa & MENA, Asia and Latin America & the Caribbean. However, this rather disappointing finding is in line with the small macroeconomic impact of aid found in earlier studies. --International trade,foreign aid,recipient exports,bilateral trade relations
Wavelet Methods in the Relativistic Three-Body Problem
In this paper we discuss the use of wavelet bases to solve the relativistic
three-body problem. Wavelet bases can be used to transform momentum-space
scattering integral equations into an approximate system of linear equations
with a sparse matrix. This has the potential to reduce the size of realistic
three-body calculations with minimal loss of accuracy. The wavelet method leads
to a clean, interaction independent treatment of the scattering singularities
which does not require any subtractions.Comment: 14 pages, 3 figures, corrected referenc
Social Network Analysis with sna
Modern social network analysis---the analysis of relational data arising from social systems---is a computationally intensive area of research. Here, we provide an overview of a software package which provides support for a range of network analytic functionality within the R statistical computing environment. General categories of currently supported functionality are described, and brief examples of package syntax and usage are shown.
Computational polarimetric microwave imaging
We propose a polarimetric microwave imaging technique that exploits recent
advances in computational imaging. We utilize a frequency-diverse cavity-backed
metasurface, allowing us to demonstrate high-resolution polarimetric imaging
using a single transceiver and frequency sweep over the operational microwave
bandwidth. The frequency-diverse metasurface imager greatly simplifies the
system architecture compared with active arrays and other conventional
microwave imaging approaches. We further develop the theoretical framework for
computational polarimetric imaging and validate the approach experimentally
using a multi-modal leaky cavity. The scalar approximation for the interaction
between the radiated waves and the target---often applied in microwave
computational imaging schemes---is thus extended to retrieve the susceptibility
tensors, and hence providing additional information about the targets.
Computational polarimetry has relevance for existing systems in the field that
extract polarimetric imagery, and particular for ground observation. A growing
number of short-range microwave imaging applications can also notably benefit
from computational polarimetry, particularly for imaging objects that are
difficult to reconstruct when assuming scalar estimations.Comment: 17 pages, 15 figure
Phase Harmonic Correlations and Convolutional Neural Networks
A major issue in harmonic analysis is to capture the phase dependence of
frequency representations, which carries important signal properties. It seems
that convolutional neural networks have found a way. Over time-series and
images, convolutional networks often learn a first layer of filters which are
well localized in the frequency domain, with different phases. We show that a
rectifier then acts as a filter on the phase of the resulting coefficients. It
computes signal descriptors which are local in space, frequency and phase. The
non-linear phase filter becomes a multiplicative operator over phase harmonics
computed with a Fourier transform along the phase. We prove that it defines a
bi-Lipschitz and invertible representation. The correlations of phase harmonics
coefficients characterise coherent structures from their phase dependence
across frequencies. For wavelet filters, we show numerically that signals
having sparse wavelet coefficients can be recovered from few phase harmonic
correlations, which provide a compressive representationComment: 26 pages, 8 figure
Bell-shaped nonstationary refinable ripplets
We study the approximation properties of the class of nonstationary refinable
ripplets introduced in \cite{GP08}. These functions are solution of an infinite
set of nonstationary refinable equations and are defined through sequences of
scaling masks that have an explicit expression. Moreover, they are
variation-diminishing and highly localized in the scale-time plane, properties
that make them particularly attractive in applications. Here, we prove that
they enjoy Strang-Fix conditions and convolution and differentiation rules and
that they are bell-shaped. Then, we construct the corresponding minimally
supported nonstationary prewavelets and give an iterative algorithm to evaluate
the prewavelet masks. Finally, we give a procedure to construct the associated
nonstationary biorthogonal bases and filters to be used in efficient
decomposition and reconstruction algorithms. As an example, we calculate the
prewavelet masks and the nonstationary biorthogonal filter pairs corresponding
to the nonstationary scaling functions in the class and construct the
corresponding prewavelets and biorthogonal bases. A simple test showing their
good performances in the analysis of a spike-like signal is also presented.
Keywords: total positivity, variation-dimishing, refinable ripplet, bell-shaped
function, nonstationary prewavelet, nonstationary biorthogonal basisComment: 30 pages, 10 figure
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