A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation

Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions. As the practical implementation of ABC requires computations based on vectors of summary statistics, rather than full data sets, a central question is how to derive low-dimensional summary statistics from the observed data with minimal loss of information. In this article we provide a comprehensive review and comparison of the performance of the principal methods of dimension reduction proposed in the ABC literature. The methods are split into three nonmutually exclusive classes consisting of best subset selection methods, projection techniques and regularization. In addition, we introduce two new methods of dimension reduction. The first is a best subset selection method based on Akaike and Bayesian information criteria, and the second uses ridge regression as a regularization procedure. We illustrate the performance of these dimension reduction techniques through the analysis of three challenging models and data sets.Comment: Published in at http://dx.doi.org/10.1214/12-STS406 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Temperature dependence of the coercive field in single-domain particle systems

The magnetic properties of Cu97Co3 and Cu90Co10 granular alloys were measured over a wide temperature range (2 to 300K). The measurements show an unusual temperature dependence of the coercive field. A generalized model is proposed and explains well the experimental behavior over a wide temperature range. The coexistence of blocked and unblocked particles for a given temperature rises difficulties that are solved here by introducing a temperature dependent blocking temperature. An empirical factor gamma arise from the model and is directly related to the particle interactions. The proposed generalized model describes well the experimental results and can be applied to other single-domain particle system.Comment: 7 pages, 8 figures, revised version, accepted to Physical Review B on 29/04/200

DNA-psoralen: single-molecule experiments and first principles calculations

The authors measure the persistence and contour lengths of DNA-psoralen complexes, as a function of psoralen concentration, for intercalated and crosslinked complexes. In both cases, the persistence length monotonically increases until a certain critical concentration is reached, above which it abruptly decreases and remains approximately constant. The contour length of the complexes exhibits no such discontinuous behavior. By fitting the relative increase of the contour length to the neighbor exclusion model, we obtain the exclusion number and the intrinsic intercalating constant of the psoralen-DNA interaction. Ab initio calculations are employed in order to provide an atomistic picture of these experimental findings.Comment: 9 pages, 4 figures in re-print format 3 pages, 4 figures in the published versio

Automatic human activity segmentation and labeling in RGBD videos

Human activity recognition has become one of the most active research topics in image processing and pattern recognition. Manual analysis of video is labour intensive, fatiguing, and error prone. Solving the problem of recognizing human activities from video can lead to improvements in several application fields like surveillance systems, human computer interfaces, sports video analysis, digital shopping assistants, video retrieval, gaming and health-care. This paper aims to recognize an action performed in a sequence of continuous actions recorded with a Kinect sensor based on the information about the position of the main skeleton joints. The typical approach is to use manually labeled data to perform supervised training. In this paper we propose a method to perform automatic temporal segmentation in order to separate the sequence in a set of actions. By measuring the amount of movement that occurs in each joint of the skeleton we are able to find temporal segments that represent the singular actions.We also proposed an automatic labeling method of human actions using a clustering algorithm on a subset of the available features.info:eu-repo/semantics/acceptedVersio

Avaliação da severidade do falso-carvão, Ustilaginoidea Virens (Cooke.) Takah, em cultivares de arroz irrigado de diferentes ciclos biológico e de épocas de semeadura.

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Hydrological and erosion response at micro-plot to -catchment scale following forest wildfire, north-central Portugal

Wildfires can have important impacts on hydrological and soil erosion processes, due to the destruction of vegetation cover and changes to soil properties. According to Shakesby and Doerr (2006), these wildfire effects are: i) much better known at small spatial scales (especially erosion plots) than at the scale of catchments; ii) much better studied with respect to overland flow and streamflow (and, then, especially peak discharges) than to soil erosion. Following up on a precursor project studying runoff generation and the associated soil losses from micro-plot to slope-scale in Portuguese eucalypt forests, the EROSFIRE-II project addresses the connectivity of these processes across hillslopes as well as within the channel network. This is done in the Colmeal study area in central Portugal, where the outlet of an entirely burnt catchment of roughly 10 ha was instrumented with a gauging station continuously recording water level and tubidity, and five slopes were each equipped with 4 runoff plots of < 0,5 m2 (“micro-plot”) and 4 slope-scale plots as well as 1 slope-scale sediment fence. Starting one month after the August 2008 wildfire, the plots were monitored at 1- to 2-weekly intervals, depending on the occurrence of rainfall. The gauging station became operational at the end of November 2008, since the in-situ construction of an H-flume required several weeks. A preliminary analysis of the data collected till the end of 2008, focusing on two slopes with contrasting slope lengths as well as the gauging station: revealed clear differences in runoff and erosion between: (i) the micro-plot and slope-scale plots on the same hillslope; (ii) the two slopes; (iii) an initial dry period and a subsequent much wetter period; (iv) the slopes and the catchment-scale, also depending on the sampling period. These results suggest that the different processes govern the hydrological and erosion response at different spatial scales as well as for different periods, with soil water repellency playing a role during the initial post-fire period. The current presentation will review these preliminary results based on the data collected during the first year after the wildfire

Runoff at the micro-plot and slope scale following wildfire, central Portugal

Through their effects on soil properties and vegetation/litter cover, wildfires can strongly enhance overland flow generation and accelerate soil erosion [1] and, thereby, negatively affect land-use sustainability as well as downstream aquatic and flood zones. Wildfires are a common phenomenon in present-day Portugal, devastating in an average year some 100.000 ha of forest and woodlands and in an exceptional year like 2003 over 400.000 ha. There therefore exists a clear need in Portugal for a tool that can provide guidance to post-fire land management by predicting soil erosion risk, on the one hand, and, on the other, the mitigation effectiveness of soil conservation measures. Such a tool has recently been developed for the Western U.S.A. [3: ERMiT] but its suitability for Portuguese forests will need to be corroborated by field observations. Testing the suitability of existing erosion models in recently burned forest areas in Portugal is, in a nutshell, the aim of the EROSFIRE projects. In the first EROSFIRE project the emphasis was on the prediction of erosion at the scale of individual hill slopes. In the ongoing EROSFIRE-II project the spatial scope is extended to include the catchment scale, so that also the connectivity between hill slopes as well as channel and road processes are being addressed. Besides ERMiT, the principal models under evaluation for slope-scale erosion prediction are: (i) the variant of USLE [4] applied by the Portuguese Water Institute after the wildfires of 2003; (ii) the Morgan–Morgan–Finney model (MMF) [5]; (iii) MEFIDIS [6]. From these models, MEFIDIS and perhaps MMF will, after successful calibration at the slope scale, also be applied for predicting catchment-scale sediment yields of extreme events

Assessing the contribution of shallow and deep knowledge sources for word sense disambiguation

Corpus-based techniques have proved to be very beneficial in the development of efficient and accurate approaches to word sense disambiguation (WSD) despite the fact that they generally represent relatively shallow knowledge. It has always been thought, however, that WSD could also benefit from deeper knowledge sources. We describe a novel approach to WSD using inductive logic programming to learn theories from first-order logic representations that allows corpus-based evidence to be combined with any kind of background knowledge. This approach has been shown to be effective over several disambiguation tasks using a combination of deep and shallow knowledge sources. Is it important to understand the contribution of the various knowledge sources used in such a system. This paper investigates the contribution of nine knowledge sources to the performance of the disambiguation models produced for the SemEval-2007 English lexical sample task. The outcome of this analysis will assist future work on WSD in concentrating on the most useful knowledge sources

Are spectroscopic factors from transfer reactions consistent with asymptotic normalisation coefficients?

It is extremely important to devise a reliable method to extract spectroscopic factors from transfer cross sections. We analyse the standard DWBA procedure and combine it with the asymptotic normalisation coefficient, extracted from an independent data set. We find that the single particle parameters used in the past generate inconsistent asymptotic normalization coefficients. In order to obtain a consistent spectroscopic factor, non-standard parameters for the single particle overlap functions can be used but, as a consequence, often reduced spectroscopic strengths emerge. Different choices of optical potentials and higher order effects in the reaction model are also studied. Our test cases consist of: $^{14}$C(d,p)$^{15}$C(g.s.) at $E_d^{lab}=14$ MeV, $^{16}$O(d,p)$^{17}$O(g.s.) at $E_d^{lab}=15$ MeV and $^{40}$Ca(d,p)$^{41}$Ca(g.s.) at $E_d^{lab}=11$ MeV. We underline the importance of performing experiments specifically designed to extract ANCs for these systems.Comment: 15 pages, 12 figures, Phys. Rev. C (in press

Fluctuations and oscillations in a simple epidemic model

We show that the simplest stochastic epidemiological models with spatial correlations exhibit two types of oscillatory behaviour in the endemic phase. In a large parameter range, the oscillations are due to resonant amplification of stochastic fluctuations, a general mechanism first reported for predator-prey dynamics. In a narrow range of parameters that includes many infectious diseases which confer long lasting immunity the oscillations persist for infinite populations. This effect is apparent in simulations of the stochastic process in systems of variable size, and can be understood from the phase diagram of the deterministic pair approximation equations. The two mechanisms combined play a central role in explaining the ubiquity of oscillatory behaviour in real data and in simulation results of epidemic and other related models.Comment: acknowledgments added; a typo in the discussion that follows Eq. (3) is corrected