It has been observed in photoelectric devices that stresses and strains can cause inhomogeneous distribution of the refractive index which affects their performance. The purpose of this paper is to study the stress ef...
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It has been observed in photoelectric devices that stresses and strains can cause inhomogeneous distribution of the refractive index which affects their performance. The purpose of this paper is to study the stress effect on the behavior of optical waveguide sensor containing a dielectric film sandwiched between a linear substrate and a nonlinear cladding. The cladding refractive index profile is assumed to have Kerr like intensity dependence. The effective refractive indices and mode shapes of the optical waveguide sensor subject to different stress states are calculated analytically. The effect of such variation on the light intensity and implications on the sensor sensitivity are investigated. It is found that stress can affect the optical sensitivity performance.
Presently, an increased interest is apparent for the development of integrated human-like smell and taste sensing capabilities, e.g. for chemical, paper pulp, food, and medicine applications. This paper will present a...
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Presently, an increased interest is apparent for the development of integrated human-like smell and taste sensing capabilities, e.g. for chemical, paper pulp, food, and medicine applications. This paper will present an original sensor fusion method based on human expert opinions about smell and taste and measurement data from artificial nose and taste sensors. The "electronic nose" consists of an array of gas sensors with different selectivity patterns, signal handling and a sensor signal pattern recognition and decision strategy. The "electronic tongue" which was developed for the taste analysis of liquids is based on pulse voltammetry. measurement data from the artificial smell and taste sensors are used to produce sensor-specific opinions about these two human-like sensing modalities. This is achieved by a team of artificial neural networks and conventional signal handling which approximates a Bayesian decision strategy for classifying the sensor information. Further, a fusion algorithm based on the maximum likelihood principle provides a combination of the smell and respectively taste opinions, into an overall integrated opinion similar to human beings. The proposed integrated smell- and taste-sensing method is then illustrated by an application of real world measurements in the food industry.
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