A computer program called IMD is described. IMD is used for modeling the optical properties ~reflectance, transmittance, electric-field intensities, etc.! of multilayer films, i.e., films consisting of any number of layers of any thickness. IMD includes a full graphical user interface and affords modeling with up to eight simultaneous independent variables, as well as parameter estimation ~incl...

An efficient method is proposed for the evaluation of theabsorption and the transport scattering coefficients from atime-resolved reflectance or transmittance distribution. Theprocedure is based on a library of Monte Carlo simulations and is fastenough to be used in a nonlinear fitting algorithm. Tests performedagainst both Monte Carlo simulations and experimental measurements ontissue phantoms...

BACKGROUND Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. METHODS We designed and implemented a method that fits an inv...

This work focuses on the precise quantification of bubble streams from underwater gas seeps. The performance of the snake based method and of ellipse fitting with the CMA-ES non-linear optimization algorithm is evaluated. A novel improved snake based method is presented and the optimal choice of snake parameters is studied. A Kalman filter is used for bubble tracking. The deviation between the ...

State-space modeling and Bayesian analysis are both active areas of applied research in fisheries stock assessment. Combining these two methodologies facilitates the fitting of state-space models that may be nonlinear and have non-normal errors, and hence it is particularly useful for the modeling of fisheries dynamics. Here, this approach is demonstrated by fitting a non-linear surplus product...

We describe the process of fitting a phenomenological model for the spiking behavior of a zebra-fish neuron using the IPOPT routines described in Wächter and Biegler 2006. These routines provide a computationally efficient methods for estimating parameters in nonlinear differential equations. However, convergence to global solutions is not guaranteed and we describe a number of strategies that ...

This paper is about fitting multivariate normal mixture distributions subject to structural equation modeling. The general model comprises common factor and structural regression models. The introduction of covariance and mean structure models reduces the number of parameters to be estimated in fitting the mixture and enables one to investigate a variety of substantive hypotheses concerning the...

An important family of blind equalization algorithms identify a communication channel model based on fitting higher order cumulants, which poses a nonlinear optimization problem. Since higher order cumulant-based criteria are multimodal, conventional gradient search techniques require a good initial estimate to avoid converging to local minima. We present a novel scheme which uses genetic algor...

Amongst possible choices for identifying complicated processes for prediction, simulation, and approximation applications, high-order Takagi-Sugeno (TS) fuzzy models are fitting tools. Although they can construct models with rather high complexity, they are not as interpretable as first-order TS fuzzy models. In this paper, we first propose to use Deformed Linear Models (DLMs) in consequence pa...

During the flood development in an oil field, the creep characteristic of mudstone is one of the important factors causing casing damage. In this study, based on the theory of fractional order differential and taking into account the creep damage evolution rules, a fractional nonlinear creep-damage model is proposed to reflect the instantaneous deformation in loading processes and the accelerat...