A new computer method for temperature measurement based on an optimal control problem

A new computer method to measure extreme temperatures is presented. The method reduces the measurement of the unknown temperature to the solving of an optimal control problem, using a numerical computer. Based on this method, a new device for temperature measurement is built. It consists of a hardware part that includes some standard temperature sensors and it also has a software section.\ud The problem of temperature measurement, according to this new method, is mathematically modelled by means of the one-dimensional heat equation, with boundary and initial conditions, describing the heat transfer through the device.\ud \ud The principal hardware component of the new device is a rod. The variation of the temperature which is produced near one end of the rod is determined using some temperature measurements in the other end of the rod and the new computer method which is described in this work.\ud \ud This device works as an attenuator of high temperatures and as an amplifier of low temperatures. In fact, it realizes an extension of the standard working range of temperature sensors at very high and very low values.\ud \ud The mathematical model of the device and the computer method are explained in detail and some possible practical implementations and a collection of simulations are also presented

Embedding and customizing templates in cross-disciplinary modeling

In this paper, I develop a template-based analysis to include several elements of processes through which templates are transferred between fields of inquiry. The analysis builds on Justin Price’s identification of the importance of a “landing zone” in the recipient domain, from which “conceptual pressure” may be created. I will argue that conceptual pressure is a characteristic feature of the process of template transfer; that this means that there are costs to the process of transfer as well as benefits; and that it would be reasonable if modelers try to mitigate these costs. I will discuss two such mitigation strategies: ‘conceptual embedding’ and ‘customization’. I illustrate the claims, focusing on the mitigation strategies, with a case study: that of pioneering applications of reaction–diffusion equations in mathematical ecology.</p

The measurement of dilational properties of liquid surfaces

For measurements of viscoelastic properties of monolayer covered interfaces, the longitudinal wave technique is used. The longitudinal wave is generated in the plane of the interface, using a horizontal oscillating barrier. The wave propagation depends on the values of the viscoelastic parameters of the monolayer. The present paper deals with a new method of determining the wave parameters. Using small tracer particles, the displacement of the monolayer, as a function of the distance to the oscillating barrier, is made visible and recorded by video cameras. From these recordings the wave parameters and viscoelastic properties are evaluated. A comparison is made between results obtained with this method and those obtained from the measurements of the varying surface tension. This latter method has until now normally been used to determine the wave parameters. Results on cholesterol and decanoic acid monolayers indicate that both methods lead to similar results within experimental error. It is shown that in case of reflected waves the combination of the results of the two methods, as described earlier by Crone et al., leads to significantly more accurate values of the wave parameters

Population thinking and natural selection in dual-inheritance theory

A deflationary perspective on theories of cultural evolution, in particular dual-inheritance theory, has recently been proposed by Lewens. On this ‘pop-culture’ analysis, dual-inheritance theorists apply population thinking to cultural phenomena, without claiming that cultural items evolve by natural selection. This paper argues against this pop-culture analysis of dual-inheritance theory. First, it focuses on recent dual-inheritance models of specific patterns of cultural change. These models exemplify population thinking without a commitment to natural selection of cultural items. There are grounds, however, for doubting the added explanatory value of the models in their disciplinary context—and thus grounds for engaging in other potentially explanatory projects based on dual-inheritance theory. One such project is suggested by advocates of the theory. Some of the motivational narratives that they offer can be interpreted as setting up an adaptationist project with regard to cumulative change in cultural items. We develop this interpretation here. On it, dual-inheritance theory features two interrelated selection processes, one on the level of genetically inherited learning mechanisms, another on the level of the cultural items transmitted through these mechanisms. This interpretation identifies a need for further modelling efforts, but also offers scope for enhancing the explanatory power of dual-inheritance theory

Estimating 3D Object Parameters from 2D Grey-Level Images

This thesis describes a general framework for parameter estimation, which is suitable for computer vision applications. The approach described combines 3D modelling, animation and estimation tools to determine parameters of objects in a scene from 2D grey-level images. The animation tool predicts images using a 3D model of the scene (virtual reality), describing components like cameras, light sources and objects, and their parameters. The 3D modelling, using primitives like quadrics enables the handling of occlusion. A least squares estimator in combination with the modelling tool is used to estimate the selected parameters from real or animated grey-level images. The non-linear relation between the measurements and the set of parameters is coped with by the iterative application of the linear estimator. The least squares estimation paradigm is applied in a standardised way to the grey-level images of objects by considering the pixels as measurements of the object parameters. Two or more images, even when taken from different points of view, can be included simply by extending the measurement vector. Also the inclusion of a Gaussian filter, to increase the estimator performance by improving the image properties, can be carried out in a natural way

Population thinking and natural selection in dual-inheritance theory

A deflationary perspective on theories of cultural evolution, in particular dual-inheritance theory, has recently been proposed by Lewens. On this ‘pop-culture’ analysis, dual-inheritance theorists apply population thinking to cultural phenomena, without claiming that cultural items evolve by natural selection. This paper argues against this pop-culture analysis of dual-inheritance theory. First, it focuses on recent dual-inheritance models of specific patterns of cultural change. These models exemplify population thinking without a commitment to natural selection of cultural items. There are grounds, however, for doubting the added explanatory value of the models in their disciplinary context—and thus grounds for engaging in other potentially explanatory projects based on dual-inheritance theory. One such project is suggested by advocates of the theory. Some of the motivational narratives that they offer can be interpreted as setting up an adaptationist project with regard to cumulative change in cultural items. We develop this interpretation here. On it, dual-inheritance theory features two interrelated selection processes, one on the level of genetically inherited learning mechanisms, another on the level of the cultural items transmitted through these mechanisms. This interpretation identifies a need for further modelling efforts, but also offers scope for enhancing the explanatory power of dual-inheritance theory

A statistical model to describe invariants extracted from a 3-D quadric surface patch and its applications in region-based recognition

A statistical model, describing noise-disturbed invariants extracted from a surface patch of a range image, has been developed and applied to region based pose estimation and classification of 3D quadrics. The Mahalanobis distance, which yields the same results as a Baysian classifier, is used for the classification of the surface patches. The results, compared with the Euclidean distance, appear to be much more reliabl

A Surface Relief Meter Based on Trinocular Vision

The concept for the relief meter being developed, appears to function well, when used with the artificial images. The described matching criterion leads to high matching percentages, and accurate results. The percentage of mismatches is reduced to practically zero for the tested scenes. Future work will involve evaluation of the algorithm with real agricultural scenes (soil images) and implementation of special hardware for fast execution of the algorith