Assessment of the final metrological characteristics of a MOEMS-based NDIR spectrometer through system modeling and data processing

A model of a miniaturized non-dispersive infrared (NDIR) gas analysis system, aiming to predict the final system specifications, is presented. It comprises the different elements of the NDIR detector, including a surface micromachined Fabry-Perot tunable filter. These models have been used to estimate the response of the NDIR system to different gas mixtures. Multivariate regression methods like partial least squares allow recovering the true sample composition from the IR absorption spectra measured with the NDIR system, despite the limited selectivity of the filter. Combining model and data processing permits to predict the effect on the final system specification of design parameters. Here, we compare the effect of the technology used for the filter on the system errors.     

Stability analysis of network-based cooperative resource allocation strategies

Resource allocation involves deciding how to divide a resource of limited availability among multiple demands in a way that optimizes current objectives. In this brief paper we focus on one type of distributed resource allocation problem where via an imperfect communication network multiple processors can share the load presented by multiple task types. We introduce asynchronous “cooperative” resource allocation strategies, and show that they lead to a bounded cumulative demand.     

Nonpathological Lyapunov functions and discontinuous Carathéodory systems

Differential equations with discontinuous right-hand side and solutions intended in Carathéodory sense are considered. For these equations, sufficient conditions which guarantee both Lyapunov stability and asymptotic stability in terms of nonsmooth Lyapunov functions are given. An invariance principle is also proven.     

Finding feasible mold parting directions using graphics hardware

We present new programmable graphics hardware accelerated algorithms to test the 2-moldability of geometric parts and assist with part redesign. These algorithms efficiently identify and graphically display undercuts as well as minimum and insufficient draft angles. Their running times grow only linearly with respect to the number of facets in the solid model, making them efficient subroutines for our algorithms that test whether a tessellated CAD model can be manufactured in a two-part mold. We have developed and implemented two such algorithms to choose candidate directions to test for 2-moldability using accessibility analysis and Gauss maps. The efficiency of these algorithms lies in the fact that they identify groups of candidate directions such that if any one direction in the group is undercut-free, all are, or if any one is not undercut-free, none are. We examine trade-offs between the algorithms' speed, accuracy, and whether they guarantee that an undercut-free direction will be found for a part if one exists.     

Bullwhip reduction for ARMA demand: The proportional order-up-to policy versus the full-state-feedback policy

A ‘proportional’ order-up-to policy reacting to ARMA demand is analyzed using stochastic optimal control theory. This policy is compared with a full-state-feedback order-up-to policy. Necessary conditions for an optimum of a weighted sum of the inventory and the ordering variances for both policies are formulated. Based on this a relatively simple expression for the ‘full-state’ policy is derived. The comparison between the two policies demonstrates that the ‘intuitively’ designed proportional policy does not fulfill the objective of controlling both the inventory and ordering variance for all parameter values of the demand model as well as the full-state-feedback policy. The full-state-feedback policy outperforms the proportional policy in several aspects.     

Aerobic degradation by white‐rot fungi of trichloroethylene (TCE) and mixtures of TCE and perchloroethylene (PCE)

BACKGROUND: Trichloroethylene (TCE) and perchloroethylene (PCE) are considered among the most important groundwater pollutants around the world. These compounds are usually found together in polluted environments but little is known about the ability of microorganisms to simultaneously degrade TCE and PCE. RESULTS: Data showed that several species of white‐rot fungi, including Trametes versicolor, Ganoderma lucidum, and Irpex lacteus, degrade substantial levels of TCE in pure culture. T. versicolor was chosen for further study since it degraded higher levels of TCE than the other organisms. Initial glucose concentration and reoxygenation of samples increased the amount of TCE dechlorination, but no significant difference in percentage TCE degradation was observed. T. versicolor was able to degrade 34.1 and 47.7% of PCE and TCE added as mixtures (containing 5 and 10 mg L⁻¹, respectively). CONCLUSIONS: The degradation ability of TCE was extended to other species of white‐rot fungi. Percentage degradation as well as chloride release from mixtures of TCE and PCE showed that T. versicolor degrades mixtures of TCE and PCE almost as well as its ability to degrade individually added TCE or PCE. The results suggest the potential promise of T. versicolor for bioremediation of TCE and PCE in the environment. Copyright © 2008 Society of Chemical Industry     

Kinetic modelling of textural changes in ready-to-eat breakfast cereals during soaking in semi-skimmed milk

Summary Ready‐to‐eat breakfast cereals immersed in milk undergo undesirable changes in texture because of sudden moisture uptake. The textural changes are ascribable to a plasticizing effect of water, which modifies the mechanical strength of products by softening the starch/protein matrix. In this work, some textural parameters of different cereal flakes were derived from the force–displacement curves monitored during 300 s of immersion in milk. Hardness loss, deformability increment and changes in the force–displacement curve profile were calculated and plotted against soaking time. The application of a sugar coating process to a model cereal flake increased the initial product hardness and improved the preservation of the textural parameters during immersion. The Peleg model closely fitted the experimental data, with regression coefficients from 0.967 to 0.999.     

Data decomposition using independent component analysis with prior constraints

In many data analysis problems, it is useful to consider the data as generated from a set of unknown (latent) generators or sources. The observations we make of a system are then taken to be related to these sources through some unknown function. Furthermore, the (unknown) number of underlying latent sources may be less than the number of observations. Recent developments in independent component analysis (ICA) have shown that, in the case where the unknown function linking sources to observations is linear, such data decomposition may be achieved in a mathematically elegant manner. In this paper, we extend the general ICA paradigm to include a very flexible source model, prior constraints and conditioning on sets of intermediate variables so that ICA forms one part of a hierarchical system. We show that such an approach allows for efficient discovery of hidden representation in data and for unsupervised data partitioning.