Safer Mourad

Stochastic modeling of light scattering with fluorescence using a Monte Carlo-based multiscale approach

This work deals with the efficient and accurate modeling of fluorescence in the context of stochastic Monte Carlo methods for which we propose a novel multiscale method. As in other approaches of this category, the transport theory is employed to describe the physics. The new framework was successfully applied for a quantitative assessment of halftone reflectance measurements with three different devices. It could be demonstrated that the described method is faster than classical Monte Carlo by multiple orders of magnitude, and that it is capable of correctly handling the geometrical device differences. It is also shown that optical dot gain is accurately predicted for the whole ink coverage range.

Statistical approach to determine the effect of combined environmental parameters on conidial development of Trichoderma atroviride (T-15603.1).

Trichoderma atroviride (T‐15603.1) is a promising fungal agent for biological control of wood decay fungi in urban tree wounds. The aim of this work was to determine the combined effects of water activity (aw, 0.998–0.892), temperature (10–30 °C) and pH (3–7) on the development of conidia on low‐nutrient agar (LNA). Lag phase prior to germination (h), germination rates (µm) and germ‐tube elongation were obtained at each set of conditions. The experimental data were used to fit a response surface model for predicting the germination rates of T‐15603.1 and to analyze the effect of the abiotic parameters tested. The polynomial response surface model was mathematically evaluated using graphical plots and several statistical indices (RMSE, %SEP, Af, Bf, pRE). Data analyses showed a highly significant effect on conidial development of aw and temperature (P < 0.001), whereas no significant effect of pH (P ≥ 0.05) was observed. The germination rate dropped and the lag prior to germination increased as the temperature and aw decreased, but T‐15603.1 appeared to be more sensitive to aw reduction than to temperature. The minimum aw level for germination was 0.910 at 15–25 °C, and maximum germination rates were obtained at aw = 0.998, 25–30 °C and pH 5. The response surface model was useful and widely accurate (R2 = 0.983) for predicting the germination rate of T‐15603.1 and complemented the experimental results. These findings contribute to better understanding how combined environmental factors affect the environmental parameter tolerance levels of T‐15603.1 and to the development of an adequate delivery system for optimized application of T‐15603. (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Computing light statistics in heterogeneous media based on a mass weighted probability density function method

Based on the transport theory, we present a modeling approach to light scattering in turbid material. It uses an efficient and general statistical description of the materials scattering and absorption behavior. The model estimates the spatial distribution of intensity and the flow direction of radiation, both of which are required, e.g., for adaptable predictions of the appearance of colors in halftone prints. This is achieved by employing a computational particle method, which solves a model equation for the probability density function of photon positions and propagation directions. In this framework, each computational particle represents a finite probability of finding a photon in a corresponding state, including properties like wavelength. Model evaluations and verifications conclude the discussion.

Classification of Paper Images to Predict Substrate Parameters Prior to Print

An accurate characterization of the substrate is a prerequisite of color management in print. The use of standard ICC profiles in prepress leaves it to the printer to match the fixed substrate characteristics contained in these profiles. This triggers the interest in methods to predict, if a given ink, press and paper combination complies with a given characterization. We present an approach to compare physical and optical characteristics of papers in order to achieve such a prediction of compliance by classification methods. For economical and ecological reasons it is preferable to test paper without printing it. We therefore propose non-destructive methods.