Mobile Robot Local Predictive Control under Perception Constraints

This research extends a previously developed work concerning about the use of local model predictive control in mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The platformused is a differential driven robot with a free rotating wheel. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are also introduced. In this sense, monocular image data provide an occupancy grid where safety trajectories are computed by using goal attraction potential fields

Generation and nonlinear evolution of shore-oblique/transverse sand bars

The coupling between topography, waves and currents in the surf zone may selforganize to produce the formation of shore-transverse or shore-oblique sand bars on an otherwise alongshore uniform beach. In the absence of shore-parallel bars, this has been shown by previous studies of linear stability analysis, but is now extended to the finite-amplitude regime. To this end, a nonlinear model coupling wave transformation and breaking, a shallow-water equations solver, sediment transport and bed updating is developed. The sediment flux consists of a stirring factor multiplied by the depthaveraged current plus a downslope correction. It is found that the cross-shore profile of the ratio of stirring factor to water depth together with the wave incidence angle primarily determine the shape and the type of bars, either transverse or oblique to the shore. In the latter case, they can open an acute angle against the current (upcurrent oriented) or with the current (down-current oriented). At the initial stages of development, both the intensity of the instability which is responsible for the formation of the bars and the damping due to downslope transport grow at a similar rate with bar amplitude, the former being somewhat stronger. As bars keep on growing, their finite-amplitude shape either enhances downslope transport or weakens the instability mechanism so that an equilibrium between both opposing tendencies occurs, leading to a final saturated amplitude. The overall shape of the saturated bars in plan view is similar to that of the small-amplitude ones. However, the final spacings may be up to a factor of 2 larger and final celerities can also be about a factor of 2 smaller or larger. In the case of alongshore migrating bars, the asymmetry of the longshore sections, the lee being steeper than the stoss, is well reproduced. Complex dynamics with merging and splitting of individual bars sometimes occur. Finally, in the case of shore-normal incidence the rip currents in the troughs between the bars are jet-like while the onshore return flow is wider and weaker as is observed in nature.

Parametric Approach to Blind Deconvolution of Nonlinear Channels

A parametric procedure for the blind inversion of nonlinear channels is proposed, based on a recent method of blind source separation in nonlinear mixtures. Experiments show that the proposed algorithms perform efficiently, even in the presence of hard distortion. The method, based on the minimization of the output mutual information, needs the knowledge of log-derivative of input distribution (the so-called score function). Each algorithm consists of three adaptive blocks: one devoted to adaptive estimation of the score function, and two other blocks estimating the inverses of the linear and nonlinear parts of the channel, (quasi-)optimally adapted using the estimated score functions. This paper is mainly concerned by the nonlinear part, for which we propose two parametric models, the first based on a polynomial model and the second on a neural network, while [14, 15] proposed non-parametric approaches.

A Fast Gradient Approximation for Nonlinear Blind Signal Processing

When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose.

Post-Nonlinear Mixtures and Beyond

Although sources in general nonlinear mixturm arc not separable iising only statistical independence, a special and realistic case of nonlinear mixtnres, the post nonlinear (PNL) mixture is separable choosing a suited separating system. Then, a natural approach is based on the estimation of tho separating Bystem parameters by minimizing an indcpendence criterion, like estimated mwce mutual information. This class of methods requires higher (than 2) order statistics, and cannot separate Gaarsian sources. However, use of [weak) prior, like source temporal correlation or nonstationarity, leads to other source separation Jgw rithms, which are able to separate Gaussian sourra, and can even, for a few of them, works with second-order statistics. Recently, modeling time correlated s011rces by Markov models, we propose vcry efficient algorithms hmed on minimization of the conditional mutual information. Currently, using the prior of temporally correlated sources, we investigate the fesihility of inverting PNL mixtures with non-bijectiw non-liacarities, like quadratic functions. In this paper, we review the main ICA and BSS results for riunlinear mixtures, present PNL models and algorithms, and finish with advanced resutts using temporally correlated snu~sm

Constraints on effective field theory parameters for the Lambda N -> NN transition

The relation between the low-energy constants appearing in the effective field theory description of the Lambda N -> NN transition potential and the parameters of the one-meson-exchange model previously developed is obtained. We extract the relative importance of the different exchange mechanisms included in the meson picture by means of a comparison to the corresponding operational structures appearing in the effective approach. The ability of this procedure to obtain the weak baryon-baryon-meson couplings for a possible scalar exchange is also discussed.

Constraints on effective field theory parameters for the Lambda N -> NN transition

The relation between the low-energy constants appearing in the effective field theory description of the Lambda N -> NN transition potential and the parameters of the one-meson-exchange model previously developed is obtained. We extract the relative importance of the different exchange mechanisms included in the meson picture by means of a comparison to the corresponding operational structures appearing in the effective approach. The ability of this procedure to obtain the weak baryon-baryon-meson couplings for a possible scalar exchange is also discussed.

Energy relaxation in nonlinear one-dimensional lattices

We study energy relaxation in thermalized one-dimensional nonlinear arrays of the Fermi-Pasta-Ulam type. The ends of the thermalized systems are placed in contact with a zero-temperature reservoir via damping forces. Harmonic arrays relax by sequential phonon decay into the cold reservoir, the lower-frequency modes relaxing first. The relaxation pathway for purely anharmonic arrays involves the degradation of higher-energy nonlinear modes into lower-energy ones. The lowest-energy modes are absorbed by the cold reservoir, but a small amount of energy is persistently left behind in the array in the form of almost stationary low-frequency localized modes. Arrays with interactions that contain both a harmonic and an anharmonic contribution exhibit behavior that involves the interplay of phonon modes and breather modes. At long times relaxation is extremely slow due to the spontaneous appearance and persistence of energetic high-frequency stationary breathers. Breather behavior is further ascertained by explicitly injecting a localized excitation into the thermalized arrays and observing the relaxation behavior.

Wishes or Constraints? Mothers' Labour Force Participation and its Motivation in Switzerland

The aim of this article is to estimate the impact of various factors related to role conflict theory and preference theory on the reduction of women's labour force participation after their transition to parenthood. Objective and subjective dimensions of women's labour force participation are assessed. The empirical test is based on a survey of couples with children in Switzerland. Results show that compared to structural factors associated with role conflict reduction, preferences have little impact on mothers' labour force participation, but explain a good deal of their frustration if the factual situation does not correspond to their wishes. Structural factors, such as occupation, economic resources, childcare, and an urban environment, support mothers' labour force participation, whereas active networks and a home centred lifestyle preference help them to cope with frustrations.

Simulating maize phenology as a function of air temperature with a linear and a nonlinear model

The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.

Liberties and constraints of the normative approach to evaluation and decision in forensic science: a discussion towards overcoming some common misconceptions

At a time when disciplined inference and decision making under uncertainty represent common aims to participants in legal proceedings, the scientific community is remarkably heterogenous in its attitudes as to how these goals ought to be achieved. Probability and decision theory exert a considerable influence, and we think by all reason rightly do so, but they go against a mainstream of thinking that does not embrace-or is not aware of-the 'normative' character of this body of theory. It is normative, in the sense understood in this article, in that it prescribes particular properties, typically (logical) coherence, to which reasoning and decision making ought to conform. Disregarding these properties can result in diverging views which are occasionally used as an argument against the theory, or as a pretext for not following it. Typical examples are objections according to which people, both in everyday life but also individuals involved at various levels in the judicial process, find the theory difficult to understand and to apply. A further objection is that the theory does not reflect how people actually behave. This article aims to point out in what sense these examples misinterpret the analytical framework in its normative perspective. Through examples borrowed mostly from forensic science contexts, it is argued that so-called intuitive scientific attitudes are particularly liable to such misconceptions. These attitudes are contrasted with a statement of the actual liberties and constraints of probability and decision theory and the view according to which this theory is normative.

Constraints on Miocene oceanography and climate in the Western and Central Paratethys: O-, Sr-, and Nd-isotope compositions of marine fish and mammal remains

The Paratethys evolved as a marginal sea during the Alpine-Himalayan orogeny in the Oligo-Miocene. Sediments from the northern Alpine Molasse Basin, the Vienna, and the Pannonian Basins located in the western and central part of the Paratethys thus provide unique information on regional changes in climate and oceanography during a period of active Alpine uplift Oxygen isotope compositions of well-preserved phosphatic fossils recovered from the sediments support deposition under sub-tropical to warm-temperate climate with water temperatures of 14 to 28 degrees C for the Miocene. delta(18)O values of fossil shark teeth are similar to those reported for other Miocene marine sections and, using the best available estimates of their biostratigraphic age, show a variation until the end of the Badenian similar to that reported for composite global record. The (87)Sr/(86)Sr isotope ratios of the fossils follow the global Miocene seawater trend, albeit with a much larger scatter. The deviations of (87)Sr/(86)Sr in the samples from the well-constrained seawater curve are interpreted as due to local input of terrestrially-derived Sr. Contribution of local sources is also reflected in the epsilon(Nd) values, consistent with input from ancient crystalline rocks (e.g., Bohemian Massif and/or Mesozoic sediments with epsilon(Nd) < -9. On the other hand, there is evidence for input from areas with Neogene volcanism as suggested by samples with elevated epsilon(Nd) values >-7. Excluding samples showing local influence on the water column, an average epsilon(Nd) value of -7.9 +/- 0.5 may be inferred for the Miocene Paratethys. This value is indistinguishable from the epsilon(Nd) value of the contemporaneous Indian Ocean, supporting a dominant role of this ocean in the Western and Central Paratethys. (C) 2008 Elsevier B.V. All rights reserved.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Tectonomagmatic evolution of Western Amazonia: Geochemical characterization and zircon U-Pb geochronologic constraints from the Peruvian Eastern Cordilleran granitoids

The results of a coupled, in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) U-Pb study on zircon and geochemical characterization of the Eastern Cordilleran intrusives of Peru reveal 1.15 Ga of intermittent magmatism along central Western Amazonia, the Earth's oldest active open continental margin. The eastern Peruvian batholiths are volumetrically dominated by plutonism related to the assembly and breakup of Pangea during the Paleozoic-Mesozoic transition. A Carboniferous-Permian (340-285 Ma) continental arc is identified along the regional orogenic strike from the Ecuadorian border (6 degrees S) to the inferred inboard extension of the Arequipa-Antofalla terrane in southern Peru (14 degrees S). Widespread crustal extension and thinning, which affected western Gondwana throughout the Permian and Triassic resulted in the intrusion of the late- to post-tectonic La Merced-San Ramon-type anatectites dated between 275 and 220 Ma, while the emplacement of the southern Cordillera de Carabaya peraluminous granitoids in the Late Triassic to Early Jurassic (220-190 Ma) represents, temporally and regionally, a separate tectonomagmatic event likely related to resuturing of the Arequipa-Antofalla block. Volcano-plutonic complexes and stocks associated with the onset of the present Andean cycle define a compositionally bimodal alkaline suite and cluster between 180 and 170 Ma. A volumetrically minor intrusive pulse of Oligocene age (ca. 30 Ma) is detected near the southwestern Cordilleran border with the Altiplano. Both post-Gondwanide (30-170 Ma), and Precambrian plutonism (691-1123 Ma) are restricted to isolated occurrences spatially comprising less than 15% of the Eastern Cordillera intrusives. Only one remnant of a Late Ordovician intrusive belt is recognized in the Cuzco batholith (446.5 +/- 9.7 Ma) indicating that the Famatinian arc system previously identified in Peru along the north-central Eastern Cordillera and the coastal Arequipa-Antofalla terrane also existed inboard of this parautochthonous crustal fragment. Hitherto unknown occurrences of late Mesoproterozoic and middle Neoproterozoic granitoids from the south-central cordilleran segment define magmatic events at 691 +/- 13 Ma, 751 +/- 8 Ma, 985 +/- 14 Ma, and 1071-1123 +/- 23 Ma that are broadly coeval with the Braziliano and Grenville-Sunsas orogenies, respectively. Our data suggest the existence of a continuous orogenic belt in excess of 3500 km along Western Amazonia during the formation of Rodinia, its ``early'' fragmentation prior to 690 Ma, and support a model of reaccretion of the Paracas-Arequipa-Antofalla terrane to western Gondwana in the Early Ordovician with subsequent detachment of the Paracas segment in form of the Mexican Oaxaquia microcontinent in Middle Ordovician. A tectonomagmatic model involving slab detachment, followed by underplating of cratonic margin by asthenospheric mantle is proposed for the genesis of the volumetrically dominant Late Paleozoic to early Mesozoic Peruvian Cordilleran batholiths.