Comments on ‘‘Modeling fractional stochastic systems as non-random fractional dynamics driven Brownian motions

Applied Mathematical Modelling, Vol.33

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Cournot competition between a non-profit firm and a for-profit firm with uncertainty

In this paper, we consider a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analyze the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.

Machine learning Vasicek model calibration with Gaussian processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.

Treatment of relapsing chronic infections of the respiratory tract: a comparative study of the effectiveness of non specific immunotherapy with the immunoadjuvant p40 and of vaccinotherapy

The treatment of relapsing chronic infections (RCI) encounters many difficulties. In the present study, the use of the immuno adjuvant P40 either alone or in association with vaccinotherapy for the treatment of RCI turned out to be very effective, whereas vaccinotherapy alone was not. It is hypothesized that cell-mediated immunity may play a major role in controlling RCI, since the clinical improvement of the patients kept up with the positivation of previously negative skin tests carried out with either the specific infecting agent or with recall-anti gens.

A coherent approach to non-integer order derivatives

Signal Processing, vol. 86, nº 10

Digital-domain self-calibration technique for video-rate pipeline A/D converters using Gaussian white noise

Electronics Letters Vol.38, nº 19

Occurrence of campylobacter jejuni in diarrhoeic and non-diarrhoeic children in Sao Paulo, Brazil

Campylobacter jejuni was looked for in the feaces of 262 children, beeing 189 with acute diarrhoea, 31 with chronic diarrhoea and 42 controls. The organism was isolated from 14 (7.4%), 2 (6.5%) and 6 (14.3%) of the children, and each group, respectively.

Low-voltage low-power CMOS analogue circuits for Gaussian and uniform noise generation

IEEE International Symposium on Circuits and Systems, MAY 25-28, 2003, Bangkok, Thailand. (ISI Web of Science)

Multi-bit sigma-delta modulators with enhanced dynamic-range using non-linear DAC for hearing aids

15th IEEE International Conference on Electronics, Circuits and Systems, Malta

Non-volatile analysis in fruits by laser resonant ionization spectrometry: application to resveratrol (3,5,4 -trihydroxystilbene) in grapes

Applied Physics B Lasers and Optics, vol.71

Numerical solution of a PDE system with non-linear steady state conditions that translates the air stripping pollutants removal

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Avaliação do potencial eólico para geração de energia eléctrica

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.