V simulační studii (ve výukovém referátu) je po stručném fyziologickém úvodu popsán lineární model izometrické kontrakce kosterního svalu pomocí mechanické analógie. Model se skládá z bloků, z nichž první, generující sílu, představuje kontraktilní aparát a další modelují plastické a elastické vlastnosti svalu na základě pružin a elementů viskozního třeni Platnost modelu je omezena pouze na okolí pracovního bodu činnosti svalu. Výsledky simulace vyjadřují grafy, charakterizující průběh koncentrace vápníkových iontů ve svalu, průběh síly generované svalem a srovnání průběhů této silypři různých periodách budicího signálu. Simulace probíhá v simulačním prostředí MATLAB - SIMULINK, jež tvoří základ výukového simulačního systému, využívaného při výuce předmětu Biokybernetika na katedře kybernetiky FEL, ČVU T v Praze.
After a brief physiological introduction a skeletal nuscle isometric contraction linear model using mezhanical analogy is described in the simulation study. The model consists of blocks; the first of them generaIng force, represents contractile apparatus and the text ones model plastic and elastic muscle qualities on the basis of springs and viscous friction elements. Model validity is limited only on muscle activity working point enviroment The simulation results are presented by graphs characterizing calcium ions in the nuscle concentration course, force generated by muscle course and comparizon of this force courses during various periods of exciting signal The simulation is performed in the MATLAB - SIMULINK environment making the bases of the educational simulation system used by teaching the subject Biocybernetics on the Department of Cybernetics of the Faculty of Electrical Engineering Czech Technical University in Prague.
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique.
- MeSH
- Fuzzy Logic * MeSH
- Humans MeSH
- Linear Models * MeSH
- Recycling * statistics & numerical data MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
A tutorial and spreadsheet for the validation and bottom-up uncertainty evaluation of quantifications performed by instrumental methods of analysis based on linear weighted calibrations is presented. The developed tool automatically assesses if calibrator values uncertainty is negligible given instrumental signal precision, assesses signal homoscedasticity by the Levene's test, guides the selection of weighting factors and evaluates the fitness of the regression model to define the calibration curve. The spreadsheet allows the use of the linear weighted regression model without the need for collecting many replicate signals of calibrators and sample by taking previously developed detailed models of signal precision variation in the calibration interval after adjustments to the daily precision conditions. This tool was successfully applied to the determination of the mass concentration of Cd, Pb, As, Hg, Co, V and Ni in a nasal spray by ICP-MS after samples dilution and acidification. The developed uncertainty models were checked through the analysis of nasal sprays after spiking with known analyte concentration levels. The metrological compatibility between estimated and reference analyte levels for 95% or 99% confidence level supports uncertainty model adequacy. The spiked samples were quantified from many replicate signals but uncertainty evaluation from duplicate calibrator and sample signals was assessed by randomly selecting calibrators and sample signals and by numerically defining a minimum acceptable success rate of the compatibility tests. The developed model was proven adequate to quantify the uncertainty of the studied measurements.
- MeSH
- Calibration MeSH
- Linear Models MeSH
- Uncertainty MeSH
- Nasal Sprays * MeSH
- Spectrum Analysis MeSH
- Publication type
- Journal Article MeSH
Permutation methods are commonly used to test the significance of regressors of interest in general linear models (GLMs) for functional (image) data sets, in particular for neuroimaging applications as they rely on mild assumptions. Permutation inference for GLMs typically consists of three parts: choosing a relevant test statistic, computing pointwise permutation tests, and applying a multiple testing correction. We propose new multiple testing methods as an alternative to the commonly used maximum value of test statistics across the image. The new methods improve power and robustness against inhomogeneity of the test statistic across its domain. The methods rely on sorting the permuted functional test statistics based on pointwise rank measures; still, they can be implemented even for large data. The performance of the methods is demonstrated through a designed simulation experiment and an example of brain imaging data. We developed the R package GET, which can be used for the computation of the proposed procedures.
- MeSH
- Humans MeSH
- Linear Models MeSH
- Brain * diagnostic imaging MeSH
- Neuroimaging * MeSH
- Computer Simulation MeSH
- Research Design MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- MeSH
- Research Support as Topic MeSH
- Linear Models MeSH
- Speech Production Measurement methods MeSH
- Publication type
- Review MeSH
The linear theory of electromigration, including the first-order nonlinear approximation, is generalized to systems with any equilibria fast enough to be considered instantaneous in comparison with the timescale of peak movement. For example, this theory is practically applied in the electrokinetic chromatography (EKC) mode of the CZE. The model enables the calculation of positions and shapes of analyte and system peaks without restricting the number of selectors, the complexation stoichiometry, or simultaneous acid-base equilibria. The latest version of our PeakMaster software, PeakMaster 6-Next Generation, implements the theory in a user-friendly way. It is a free and open-source software that performs all calculations and shows the properties of the background electrolyte and the expected electropherogram within a few seconds. In this paper, we mathematically derive the model, discuss its applicability to EKC systems, and introduce the PeakMaster 6 software.
Springer series in statistics
1st ed. 568 s.
