22 resultados para Inverse Rendering

em Universidad Politécnica de Madrid


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The optimum quality that can be asymptotically achieved in the estimation of a probability p using inverse binomial sampling is addressed. A general definition of quality is used in terms of the risk associated with a loss function that satisfies certain assumptions. It is shown that the limit superior of the risk for p asymptotically small has a minimum over all (possibly randomized) estimators. This minimum is achieved by certain non-randomized estimators. The model includes commonly used quality criteria as particular cases. Applications to the non-asymptotic regime are discussed considering specific loss functions, for which minimax estimators are derived.

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The solubility parameters of two SBS commercial rubbers with different structures (lineal and radial), and with slightly different styrene content have been determined by inverse gas chromatography technique. The Flory–Huggins interaction parameters of several polymer–solvent mixtures have also been calculated. The influence of the polymer composition, the solvent molecular weight and the temperature over these parameters have been discussed; besides, these parameters have been compared with previous ones, obtained by intrinsic viscosity measurements. From the Flory–Huggins interaction parameters, the infinite dilution activity coefficients of the solvents have been calculated and fitted to the well-known NRTL model. These NRTL binary interaction parameters have a great importance in modelling the separation steps in the process of obtaining the rubber.

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Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-based and an ANFIS-based solution to the inverse kinematics problem are evaluated. Materials and methods: Both the multilayer perceptron-based and the ANFIS-based inverse kinematics methods have been trained with three-dimensional Cartesian positions corresponding to the end-effector of healthy human upper limbs that execute two different activities of the daily life: "serving water from a jar" and "picking up a bottle". Validation of the proposed methodologies has been performed by a 10 fold cross-validation procedure. Results: Once trained, the systems are able to map 3D positions of the end-effector to the corresponding healthy biomechanical configurations. A high mean correlation coefficient and a low root mean squared error have been found for both the multilayer perceptron and ANFIS-based methods. Conclusions: The obtained results indicate that both systems effectively solve the inverse kinematics problem, but, due to its low computational load, crucial in real-time applications, along with its high performance, a multilayer perceptron-based solution, consisting in 3 input neurons, 1 hidden layer with 3 neurons and 6 output neurons has been considered the most appropriated for the target application.

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Sequential estimation of the success probability p in inverse binomial sampling is considered in this paper. For any estimator pˆ , its quality is measured by the risk associated with normalized loss functions of linear-linear or inverse-linear form. These functions are possibly asymmetric, with arbitrary slope parameters a and b for pˆ

p , respectively. Interest in these functions is motivated by their significance and potential uses, which are briefly discussed. Estimators are given for which the risk has an asymptotic value as p→0, and which guarantee that, for any p∈(0,1), the risk is lower than its asymptotic value. This allows selecting the required number of successes, r, to meet a prescribed quality irrespective of the unknown p. In addition, the proposed estimators are shown to be approximately minimax when a/b does not deviate too much from 1, and asymptotically minimax as r→∞ when a=b.

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Inverse bremsstrahlung has been incorporated into an analytical model of the expanding corona of a laser-irradiated spherical target. Absorption decreases slowly with increasing intensity, in agreement with some numerical simulations, and contrary to estimates from simple models in use up to now, which are optimistic at low values of intensity and very pessimistic at high values. Present results agree well with experimental data from many laboratories; substantial absorption is found up to moderate intensities,say below IOl5 W cm-2 for 1.06 pm light. Anomalous absorption, wher, included in the analysis, leaves practically unaffected the ablation pressure and mass ablation rate, for given absorbed intensity. Universal results are given in dimensionless fom.

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Sequential estimation of the success probability $p$ in inverse binomial sampling is considered in this paper. For any estimator $\hatvap$, its quality is measured by the risk associated with normalized loss functions of linear-linear or inverse-linear form. These functions are possibly asymmetric, with arbitrary slope parameters $a$ and $b$ for $\hatvap < p$ and $\hatvap > p$ respectively. Interest in these functions is motivated by their significance and potential uses, which are briefly discussed. Estimators are given for which the risk has an asymptotic value as $p \rightarrow 0$, and which guarantee that, for any $p \in (0,1)$, the risk is lower than its asymptotic value. This allows selecting the required number of successes, $\nnum$, to meet a prescribed quality irrespective of the unknown $p$. In addition, the proposed estimators are shown to be approximately minimax when $a/b$ does not deviate too much from $1$, and asymptotically minimax as $\nnum \rightarrow \infty$ when $a=b$.

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There is general agreement within the scientific community in considering Biology as the science with more potential to develop in the XXI century. This is due to several reasons, but probably the most important one is the state of development of the rest of experimental and technological sciences. In this context, there are a very rich variety of mathematical tools, physical techniques and computer resources that permit to do biological experiments that were unbelievable only a few years ago. Biology is nowadays taking advantage of all these newly developed technologies, which are been applied to life sciences opening new research fields and helping to give new insights in many biological problems. Consequently, biologists have improved a lot their knowledge in many key areas as human function and human diseases. However there is one human organ that is still barely understood compared with the rest: The human brain. The understanding of the human brain is one of the main challenges of the XXI century. In this regard, it is considered a strategic research field for the European Union and the USA. Thus, there is a big interest in applying new experimental techniques for the study of brain function. Magnetoencephalography (MEG) is one of these novel techniques that are currently applied for mapping the brain activity1. This technique has important advantages compared to the metabolic-based brain imagining techniques like Functional Magneto Resonance Imaging2 (fMRI). The main advantage is that MEG has a higher time resolution than fMRI. Another benefit of MEG is that it is a patient friendly clinical technique. The measure is performed with a wireless set up and the patient is not exposed to any radiation. Although MEG is widely applied in clinical studies, there are still open issues regarding data analysis. The present work deals with the solution of the inverse problem in MEG, which is the most controversial and uncertain part of the analysis process3. This question is addressed using several variations of a new solving algorithm based in a heuristic method. The performance of those methods is analyzed by applying them to several test cases with known solutions and comparing those solutions with the ones provided by our methods.

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Several groups all over the world are researching in several ways to render 3D sounds. One way to achieve this is to use Head Related Transfer Functions (HRTFs). These measurements contain the Frequency Response of the human head and torso for each angle. Some years ago, was only possible to measure these Frequency Responses only in the horizontal plane. Nowadays, several improvements have made possible to measure and use 3D data for this purpose. The problem was that the groups didn't have a standard format file to store the data. That was a problem when a third part wanted to use some different HRTFs for 3D audio rendering. Every of them have different ways to store the data. The Spatially Oriented Format for Acoustics or SOFA was created to provide a solution to this problem. It is a format definition to unify all the previous different ways of storing any kind of acoustics data. At the moment of this project they have defined some basis for the format and some recommendations to store HRTFs. It is actually under development, so several changes could come. The SOFA[1] file format uses a numeric container called netCDF[2], specifically the Enhaced data model described in netCDF 4 that is based on HDF5[3]. The SoundScape Renderer (SSR) is a tool for real-time spatial audio reproduction providing a variety of rendering algorithms. The SSR was developed at the Quality and Usability Lab at TU Berlin and is now further developed at the Institut für Nachrichtentechnik at Universität Rostock [4]. This project is intended to be an introduction to the use of SOFA files, providing a C++ API to manipulate them and adapt the binaural renderer of the SSR for working with the SOFA format. RESUMEN. El SSR (SoundScape Renderer) es un programa que está siendo desarrollado actualmente por la Universität Rostock, y previamente por la Technische Universität Berlin. El SSR es una herramienta diseñada para la reproducción y renderización de audio 2D en tiempo real. Para ello utiliza diversos algoritmos, algunos orientados a sistemas formados por arrays de altavoces en diferentes configuraciones y otros algoritmos diseñados para cascos. El principal objetivo de este proyecto es dotar al SSR de la capacidad de renderizar sonidos binaurales en 3D. Este proyecto está centrado en el binaural renderer del SSR. Este algoritmo se basa en el uso de HRTFs (Head Related Transfer Function). Las HRTFs representan la función de transferencia del sistema formado por la cabeza y el torso del oyente. Esta función es medida desde diferentes ángulos. Con estos datos el binaural renderer puede generar audio en tiempo real simulando la posición de diferentes fuentes. Para poder incluir una base de datos con HRTFs en 3D se ha hecho uso del nuevo formato SOFA (Spatially Oriented Format for Acoustics). Este nuevo formato se encuentra en una fase bastante temprana de su desarrollo. Está pensado para servir como formato estándar para almacenar HRTFs y cualquier otro tipo de medidas acústicas, ya que actualmente cada laboratorio cuenta con su propio formato de almacenamiento y esto hace bastante difícil usar varias bases de datos diferentes en un mismo proyecto. El formato SOFA hace uso del contenedor numérico netCDF, que a su vez esta basado en un contenedor más básico llamado HRTF-5. Para poder incluir el formato SOFA en el binaural renderer del SSR se ha desarrollado una API en C++ para poder crear y leer archivos SOFA con el fin de utilizar los datos contenidos en ellos dentro del SSR.

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In this paper we propose a novel fast random search clustering (RSC) algorithm for mixing matrix identification in multiple input multiple output (MIMO) linear blind inverse problems with sparse inputs. The proposed approach is based on the clustering of the observations around the directions given by the columns of the mixing matrix that occurs typically for sparse inputs. Exploiting this fact, the RSC algorithm proceeds by parameterizing the mixing matrix using hyperspherical coordinates, randomly selecting candidate basis vectors (i.e. clustering directions) from the observations, and accepting or rejecting them according to a binary hypothesis test based on the Neyman–Pearson criterion. The RSC algorithm is not tailored to any specific distribution for the sources, can deal with an arbitrary number of inputs and outputs (thus solving the difficult under-determined problem), and is applicable to both instantaneous and convolutive mixtures. Extensive simulations for synthetic and real data with different number of inputs and outputs, data size, sparsity factors of the inputs and signal to noise ratios confirm the good performance of the proposed approach under moderate/high signal to noise ratios. RESUMEN. Método de separación ciega de fuentes para señales dispersas basado en la identificación de la matriz de mezcla mediante técnicas de "clustering" aleatorio.

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We give necessary and sufficient conditions for the convergence with geometric rate of the common denominators of simultaneous rational interpolants with a bounded number of poles. The conditions are expressed in terms of intrinsic properties of the system of functions used to build the approximants. Exact rates of convergence for these denominators and the simultaneous rational approximants are provided.

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Penguin colonies represent some of the most concentrated sources of ammonia emissions to the atmosphere in the world. The ammonia emitted into the atmosphere can have a large influence on the nitrogen cycling of ecosystems near the colonies. However, despite the ecological importance of the emissions, no measurements of ammonia emissions from penguin colonies have been made. The objective of this work was to determine the ammonia emission rate of a penguin colony using inverse-dispersion modelling and gradient methods. We measured meteorological variables and mean atmospheric concentrations of ammonia at seven locations near a colony of Adélie penguins in Antarctica to provide input data for inverse-dispersion modelling. Three different atmospheric dispersion models (ADMS, LADD and a Lagrangian stochastic model) were used to provide a robust emission estimate. The Lagrangian stochastic model was applied both in ‘forwards’ and ‘backwards’ mode to compare the difference between the two approaches. In addition, the aerodynamic gradient method was applied using vertical profiles of mean ammonia concentrations measured near the centre of the colony. The emission estimates derived from the simulations of the three dispersion models and the aerodynamic gradient method agreed quite well, giving a mean emission of 1.1 g ammonia per breeding pair per day (95% confidence interval: 0.4–2.5 g ammonia per breeding pair per day). This emission rate represents a volatilisation of 1.9% of the estimated nitrogen excretion of the penguins, which agrees well with that estimated from a temperature-dependent bioenergetics model. We found that, in this study, the Lagrangian stochastic model seemed to give more reliable emission estimates in ‘forwards’ mode than in ‘backwards’ mode due to the assumptions made.

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We present a theoretical study of the structural and electronic properties of the M-doped MgIn2S4 ternary spinel semiconductor with M = V, Cr, and Mn. All substitutions, in the normal and in the inverse structure, are analyzed. Some of these possible substitutions present intermediate-band states in the band gap with a different occupation for a spin component. It increases the possibilities of inter-band transitions and could be interesting for applications in optoelectronic devices. The contribution to, and the electronic configuration of, these intermediate bands for the octahedral and tetrahedral sites is analyzed and discussed. The study of the substitutional energies indicates that these substitutions are favorable. Comparison between the pure and doped hosts absorption coefficients shows that this deeper band opens up more photon absorption channels and could therefore increase the solar-light absorption with respect to the host.

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The seriousness of the current crisis urgently demands new economic thinking that breaks the austerity vs. deficit spending circle in economic policy. The core tenet of the paper is that the most important problems that natural and social science are facing today are inverse problems, and that a new approach that goes beyond optimization is necessary. The approach presented here is radical in the sense that it identifies the roots in key assumptions in economic theory such as optimal behavior and stability to provide an inverse thinking perspective to economic modeling, of use in economic and financial stability policy. The inverse problem provides a truly multidisciplinary platform where related problems from different disciplines can be studied under a common approach with comparable results.

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The present work focuses on gypsum mortar manufactu red in traditional kilns and used historically as exterior rendering. A documentation survey has been carried out followed by an experimental analysis using geological techniques. Conclusion shows that traditional gypsum is formed by anhydrite and inert active impurities (crystalline amorphous silica; cl ays and hydraulic phases) produced by the craft manufacture process of the system, in a kiln with a 200ºC to 1000ºC temperature interval, and continuo us fuel supply during 36 hours. Anhydrite together wit h the hydraulic phases set at consecutive time peri ods and with the presence of moisture improve the physi cal and mechanical properties of the final product. The hydration system is of great complexity and sho ws a very slow kinetics when in presence of impurities