Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Sparse probability density function estimation using the minimum integrated square error

We develop a new sparse kernel density estimator using a forward constrained regression framework, within which the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Our main contribution is to derive a recursive algorithm to select significant kernels one at time based on the minimum integrated square error (MISE) criterion for both the selection of kernels and the estimation of mixing weights. The proposed approach is simple to implement and the associated computational cost is very low. Specifically, the complexity of our algorithm is in the order of the number of training data N, which is much lower than the order of N2 offered by the best existing sparse kernel density estimators. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to those of the classical Parzen window estimate and other existing sparse kernel density estimators.

Nuclear moments and differences in mean square charge radii of short-lived neon isotopes by collinear laser spectroscopy

Kernmomente und Kernladungsradien von kurzlebigen NeonIsotopen in der Kette 17-26,28Ne wurden mittels kollinearerLaserspektroskopie am online Massenseparator ISOLDE am CERN(Genf) vermessen. Bei kollinearer Laserspektroskopieverlangt die Bestimmung der Kernladungsradien leichterIsotope aus der Isotopeverschiebung nach einer sehr präzisenKenntnis der Ionenstrahlenergie. Zu diesem Zweck wurde eineneue, auf kollinearer Laserspektroskopie basierende Methodezur Strahlenergiemessung entwickelt und erfolgreich in denExperimenten zu Neon eingesetzt. Die experimentellenErgebnisse werden mit theoretischen Rechnungen im Rahmen desSchalenmodells und von kollektiven Kernmodellen verglichen.

Trends of mean and extreme temperature indices since 1874 at low-elevation sites in the Southern Alps

We describe the recovery of three daily meteorological records for the southern Alps (Domodossola, Riva del Garda, and Rovereto), all starting in the second half of the nineteenth century. We use these new data, along with additional records, to study regional changes in the mean temperature and extreme indices of heat waves and cold spells frequency and duration over the period 1874–2015. The records are homogenized using subdaily cloud cover observations as a constraint for the statistical model, an approach that has never been applied before in the literature. A case study based on a record of parallel observations between a traditional meteorological window and a modern screen shows that the use of cloud cover can reduce the root-mean-square error of the homogenization by up to 30% in comparison to an unaided statistical correction. We find that mean temperature in the southern Alps has increased by 1.4°C per century over the analyzed period, with larger increases in daily minimum temperatures than maximum temperatures. The number of hot days in summer has more than tripled, and a similar increase is observed in duration of heat waves. Cold days in winter have dropped at a similar rate. These trends are mainly caused by climate change over the last few decades.

Video Prioritization for Unequal Error Protection

We analyze the effect of packet losses in video sequences and propose a lightweight Unequal Error Protection strategy which, by choosing which packet is discarded, reduces strongly the Mean Square Error of the received sequence

Petroleomics By Electrospray Ionization Ft-icr Mass Spectrometry Coupled To Partial Least Squares With Variable Selection Methods: Prediction Of The Total Acid Number Of Crude Oils.

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Estatística aplicada à química: dez dúvidas comuns

Ten common doubts of chemistry students and professionals about their statistical applications are discussed. The use of the N-1 denominator instead of N is described for the standard deviation. The statistical meaning of the denominators of the root mean square error of calibration (RMSEC) and root mean square error of validation (RMSEV) are given for researchers using multivariate calibration methods. The reason why scientists and engineers use the average instead of the median is explained. Several problematic aspects about regression and correlation are treated. The popular use of triplicate experiments in teaching and research laboratories is seen to have its origin in statistical confidence intervals. Nonparametric statistics and bootstrapping methods round out the discussion.

Previsões climáticas sazonais sobre o Brasil: avaliação do RegCM3 aninhado no modelo global CPTEC/COLA

Este trabalho avalia o desempenho de previsões sazonais do modelo climático regional RegCM3, aninhado ao modelo global CPTEC/COLA. As previsões com o RegCM3 utilizaram 60 km de resolução horizontal num domínio que inclui grande parte da América do Sul. As previsões do RegCM3 e CPTEC/COLA foram avaliadas utilizando as análises de chuva e temperatura do ar do Climate Prediction Center (CPC) e National Centers for Enviromental Prediction (NCEP), respectivamente. Entre maio de 2005 e julho de 2007, 27 previsões sazonais de chuva e temperatura do ar (exceto a temperatura do CPTEC/COLA, que possui 26 previsões) foram avaliadas em três regiões do Brasil: Nordeste (NDE), Sudeste (SDE) e Sul (SUL). As previsões do RegCM3 também foram comparadas com as climatologias das análises. De acordo com os índices estatísticos (bias, coeficiente de correlação, raiz quadrada do erro médio quadrático e coeficiente de eficiência), nas três regiões (NDE, SDE e SUL) a chuva sazonal prevista pelo RegCM3 é mais próxima da observada do que a prevista pelo CPTEC/COLA. Além disto, o RegCM3 também é melhor previsor da chuva sazonal do que da média das observações nas três regiões. Para temperatura, as previsões do RegCM3 são superiores às do CPTEC/COLA nas áreas NDE e SUL, enquanto o CPTEC/COLA é superior no SDE. Finalmente, as previsões de chuva e temperatura do RegCM3 são mais próximas das observações do que a climatologia observada. Estes resultados indicam o potencial de utilização do RegCM3 para previsão sazonal, que futuramente deverá ser explorado através de previsão por conjunto.

Ventilation behavior in trained and untrained men during incremental test: evidence of one metabolic transition point

This study aimed to describe and compare the ventilation behavior during an incremental test utilizing three mathematical models and to compare the feature of ventilation curve fitted by the best mathematical model between aerobically trained (TR) and untrained ( UT) men. Thirty five subjects underwent a treadmill test with 1 km.h(-1) increases every minute until exhaustion. Ventilation averages of 20 seconds were plotted against time and fitted by: bi-segmental regression model (2SRM); three-segmental regression model (3SRM); and growth exponential model (GEM). Residual sum of squares (RSS) and mean square error (MSE) were calculated for each model. The correlations between peak VO2 (VO2PEAK), peak speed (Speed(PEAK)), ventilatory threshold identified by the best model (VT2SRM) and the first derivative calculated for workloads below (moderate intensity) and above (heavy intensity) VT2SRM were calculated. The RSS and MSE for GEM were significantly higher (p < 0.01) than for 2SRM and 3SRM in pooled data and in UT, but no significant difference was observed among the mathematical models in TR. In the pooled data, the first derivative of moderate intensities showed significant negative correlations with VT2SRM (r = -0.58; p < 0.01) and Speed(PEAK) (r = -0.46; p < 0.05) while the first derivative of heavy intensities showed significant negative correlation with VT2SRM (r = -0.43; p < 0.05). In UT group the first derivative of moderate intensities showed significant negative correlations with VT2SRM (r = -0.65; p < 0.05) and Speed(PEAK) (r = -0.61; p < 0.05), while the first derivative of heavy intensities showed significant negative correlation with VT2SRM (r= -0.73; p < 0.01), Speed(PEAK) (r = -0.73; p < 0.01) and VO2PEAK (r = -0.61; p < 0.05) in TR group. The ventilation behavior during incremental treadmill test tends to show only one threshold. UT subjects showed a slower ventilation increase during moderate intensities while TR subjects showed a slower ventilation increase during heavy intensities.

Full-dimensional analytical ab initio potential energy surface of the ground state of HOI

Extensive ab initio calculations using a complete active space second-order perturbation theory wavefunction, including scalar and spin-orbit relativistic effects with a quadruple-zeta quality basis set were used to construct an analytical potential energy surface (PES) of the ground state of the [H, O, I] system. A total of 5344 points were fit to a three-dimensional function of the internuclear distances, with a global root-mean-square error of 1.26 kcal mol(-1). The resulting PES describes accurately the main features of this system: the HOI and HIO isomers, the transition state between them, and all dissociation asymptotes. After a small adjustment, using a scaling factor on the internal coordinates of HOI, the frequencies calculated in this work agree with the experimental data available within 10 cm(-1). (C) 2011 American Institute of Physics. [doi: 10.1063/1.3615545]

Ventilation behavior during upper-body incremental exercise

Pires, FO, Hammond, J, Lima-Silva, AE, Bertuzzi, RCM, and Kiss, MAPDM. Ventilation behavior during upper-body incremental exercise. J Strength Cond Res 25(1): 225-230, 2011-This study tested the ventilation (V(E)) behavior during upper-body incremental exercise by mathematical models that calculate 1 or 2 thresholds and compared the thresholds identified by mathematical models with V-slope, ventilatory equivalent for oxygen uptake (V(E)/(V) over dotO(2)), and ventilatory equivalent for carbon dioxide uptake (V(E)/(V) over dotCO(2)). Fourteen rock climbers underwent an upper-body incremental test on a cycle ergometer with increases of approximately 20 W.min(-1) until exhaustion at a cranking frequency of approximately 90 rpm. The V(E) data were smoothed to 10-second averages for V(E) time plotting. The bisegmental and the 3-segmental linear regression models were calculated from 1 or 2 intercepts that best shared the V(E) curve in 2 or 3 linear segments. The ventilatory threshold(s) was determined mathematically by the intercept(s) obtained by bisegmental and 3-segmental models, by V-slope model, or visually by V(E)/(V) over dotO(2) and V(E)/(V) over dotCO(2). There was no difference between bisegmental (mean square error [MSE] = 35.3 +/- 32.7 l.min(-1)) and 3-segmental (MSE = 44.9 +/- 47.8 l.min(-1)) models in fitted data. There was no difference between ventilatory threshold identified by the bisegmental (28.2 +/- 6.8 ml.kg(-1).min(-1)) and second ventilatory threshold identified by the 3-segmental (30.0 +/- 5.1 ml.kg(-1).min(-1)), V(E)/(V) over dotO(2) (28.8 +/- 5.5 ml.kg(-1).min(-1)), or V-slope (28.5 +/- 5.6 ml.kg(-1).min(-1)). However, the first ventilatory threshold identified by 3-segmental (23.1 +/- 4.9 ml.kg(-1).min(-1)) or by VE/(V) over dotO(2) (24.9 +/- 4.4 ml.kg(-1).min(-1)) was different from these 4. The V(E) behavior during upper-body exercise tends to show only 1 ventilatory threshold. These findings have practical implications because this point is frequently used for aerobic training prescription in healthy subjects, athletes, and in elderly or diseased populations. The ventilatory threshold identified by V(E) curve should be used for aerobic training prescription in healthy subjects and athletes.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

Transient and Steady-State Analysis of the Affine Combination of Two Adaptive Filters

In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.