13,351 research outputs found
Aperiodic tilings and entropy
In this paper we present a construction of Kari-Culik aperiodic tile set -
the smallest known until now. With the help of this construction, we prove that
this tileset has positive entropy. We also explain why this result was not
expected
Localizing the Latent Structure Canonical Uncertainty: Entropy Profiles for Hidden Markov Models
This report addresses state inference for hidden Markov models. These models
rely on unobserved states, which often have a meaningful interpretation. This
makes it necessary to develop diagnostic tools for quantification of state
uncertainty. The entropy of the state sequence that explains an observed
sequence for a given hidden Markov chain model can be considered as the
canonical measure of state sequence uncertainty. This canonical measure of
state sequence uncertainty is not reflected by the classic multivariate state
profiles computed by the smoothing algorithm, which summarizes the possible
state sequences. Here, we introduce a new type of profiles which have the
following properties: (i) these profiles of conditional entropies are a
decomposition of the canonical measure of state sequence uncertainty along the
sequence and makes it possible to localize this uncertainty, (ii) these
profiles are univariate and thus remain easily interpretable on tree
structures. We show how to extend the smoothing algorithms for hidden Markov
chain and tree models to compute these entropy profiles efficiently.Comment: Submitted to Journal of Machine Learning Research; No RR-7896 (2012
Detection of an anomalous cluster in a network
We consider the problem of detecting whether or not, in a given sensor
network, there is a cluster of sensors which exhibit an "unusual behavior."
Formally, suppose we are given a set of nodes and attach a random variable to
each node. We observe a realization of this process and want to decide between
the following two hypotheses: under the null, the variables are i.i.d. standard
normal; under the alternative, there is a cluster of variables that are i.i.d.
normal with positive mean and unit variance, while the rest are i.i.d. standard
normal. We also address surveillance settings where each sensor in the network
collects information over time. The resulting model is similar, now with a time
series attached to each node. We again observe the process over time and want
to decide between the null, where all the variables are i.i.d. standard normal,
and the alternative, where there is an emerging cluster of i.i.d. normal
variables with positive mean and unit variance. The growth models used to
represent the emerging cluster are quite general and, in particular, include
cellular automata used in modeling epidemics. In both settings, we consider
classes of clusters that are quite general, for which we obtain a lower bound
on their respective minimax detection rate and show that some form of scan
statistic, by far the most popular method in practice, achieves that same rate
to within a logarithmic factor. Our results are not limited to the normal
location model, but generalize to any one-parameter exponential family when the
anomalous clusters are large enough.Comment: Published in at http://dx.doi.org/10.1214/10-AOS839 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Rice Trade Policies and Their Implications for Food Security
There is a strong linkage between the behavior of the rice market and the state of food security in many regions around the world, particularly in Asia, as made evident in the 2007-08 commodity crisis. Rice is a staple for the majority of the population in Asia, where roughly 60% of the close to one billion undernourished people live (FAO, 2010). As Timmer (2010) states, “it is impossible to improve food security in the short run or long run without providing adequate supplies of rice that are accessible to the poor” (p. 2). The rice crisis of 2007-08 showed the crucial role of export and import policies on the behavior of the rice market and its consequences for price stability and food security. Market fundamentals could only explain a minimal part of the skyrocketing increase in rice prices observed (Dawe, 2010). The overarching objective of this study is to assess the impact of international rice trade policies on the patterns of production, consumption, trade, and prices, from an ex-post and ex-ante perspective, and analyze the implications of these policies from a food-security point of view. The RICEFLOW model (Durand-Morat and Wailes, 2010) is used for the assessment. RICEFLOW is a spatial partial equilibrium model of the global rice economy in which the behavior of producers and consumers are specified according to neoclassical economic theory (profit and utility maximizers, respectively). Domestic production and imports are specified as imperfect substitutes following Armington (1969). The model is calibrated to calendar year 2008, the latest available year for which the RICEFLOW database is available. The 2008 RICEFLOW database is disaggregated into 65 country/regions, including the largest producers and traders of rice, and 9 rice commodities defined on two dimensions, (1) milling degrees (paddy, brown, and milled), and (2) type (long grain, medium & short grain, and fragrant). Given the crucial importance of the Armington elasticities and the lack of good estimates on these parameters, systematic sensitivity analysis is conducted on the best available estimates to generate stochastic distributions of the endogenous variables with respect to these behavioral parameters. Results are decomposed in two dimensions, namely, (1) trade policy groups, and (2) countries, to obtain a better idea of the partial effect of policies and or countries applying them. Achieving food security implies guaranteeing access (physical availability and affordability) to safe and nutritious food to the entire population. Improving food security is the key goal of the World Food Summit of 1996 and the first Millennium Development Goal. Food security assessments have traditionally been done either at the macro level (market stability) or micro level (household access). Although the methodology used in this study constrains us to focus on the macro level, it can contribute to an improved understanding of trade policy for regional and global rice supply and, thus, for improved market stability.rice, trade, policies, food security, Agricultural and Food Policy, Food Security and Poverty, International Relations/Trade, F13, Q17, Q18,
Sensitive Product Designation in the Doha Round: The Case of Rice
Effects of sensitive product designation in WTO trade reform on the international rice market are analyzed. General and partial equilibrium frameworks are used. Results suggest large impacts. Among exporters, China and the U.S., major suppliers of the Japanese and South Korean markets, are most negatively affected.Crop Production/Industries,
General and partial equilibrium analysis of the impact of the Central America Free Trade Agreement on the U.S. rice sector
The market conditions proposed by CAFTA are likely to positively impact the U.S. rice sector. Despite the differences in the impact of the agreement, both analytical approaches, namely, partial and general equilibrium modeling, yield results in the same direction. The small difference in the results from both approaches suggests low income and cross-sectoral effects between the U.S. rice sector and other segments of the economy. U.S. rice production is likely to expand to meet an increasing international demand for this commodity. The U.S. rice milling industry should also expect benefits from CAFTA, expanding by 1 percent in the general equilibrium model and up to 8 percent in the partial equilibrium framework.International Relations/Trade,
Benchmarking GEANT4 nuclear models for hadron therapy with 95 MeV/nucleon carbon ions
In carbon-therapy, the interaction of the incoming beam with human tissues
may lead to the production of a large amount of nuclear fragments and secondary
light particles. An accurate estimation of the biological dose deposited into
the tumor and the surrounding healthy tissues thus requires sophisticated
simulation tools based on nuclear reaction models. The validity of such models
requires intensive comparisons with as many sets of experimental data as
possible. Up to now, a rather limited set of double di erential carbon
fragmentation cross sections have been measured in the energy range used in
hadrontherapy (up to 400 MeV/A). However, new data have been recently obtained
at intermediate energy (95 MeV/A). The aim of this work is to compare the
reaction models embedded in the GEANT4 Monte Carlo toolkit with these new data.
The strengths and weaknesses of each tested model, i.e.
G4BinaryLightIonReaction, G4QMDReaction and INCL++, coupled to two di fferent
de-excitation models, i.e. the generalized evaporation model and the Fermi
break-up are discussed
- …