Технологические базы: понятие и проблемы формирования

Improving Reconstructive Surgery through Computational Modeling of Skin Mechanics

The purpose of computer vision is to extract useful information from images. Image features such as occluding contours, edges, flow, brightness, and shading provide geometric and photometric constraints on the surface shape and reflectance of physical objects in the scene. In this thesis, two novel techniques are proposed for surface reflectance extraction and surface recovery. They integrate geometric and photometric constraints in images of a rotating object illuminated under a collinear light source (where the illu- minant direction of the light source lies on or near the viewing direction of the camera). The rotation of the object can be precisely controlled. The object surface is assumed to be C2 and its surface reflectance function is uniform. The first technique, called the photogeometric technique, uses geometric and photometric constraints on surface points with surface normal perpendicular to the image plane to calculate 3D locations of surface points, then extracts the surface reflectance function by tracking these surface points in the images. Using the extracted surface reflectance function and two images of the surface, the technique recovers the depth and surface orientation of the surface simultaneously. The second technique, named the wire-frame technique, further exploits geometric and photometric constraints on the surface points with surface orientation coplanar with the viewing direction and the rotation axis to extract a set of 3D curves. The set of 3D curves comprises a wire frame on the surface. The depth and surface orientation between curves on the wire frame can be interpolation by using geometric or photometric methods. The surface reflectance function can be extracted from the points on the wire frame and used for photometric interpolation. The wire-frame technique is superior because it does not need the surface reflectance function to extract the wire frame. It also works on piecewise uniform surfaces and requires only that the light source be coplanar with the viewing direction and the rotation axis. In addition, by interpolating the depth and surface orientation from a dense wire frame, the surface recovered is more accurate. The two techniques have been tested on real images of surfaces with different reflectance properties and geometric structures. The experimental results and comprehensive analysis show that the proposed techniques are efficient and robust. As an attempt to extend our research to computer graphics, work on extracting the shading function from real images for graphics rendering shows some promising results.

This dissertation is concerned with surface representations which record surface properties as a function of surface orientation. The Extended Gaussian Image (EGI) of an object records the variation of surface area with surface orientation. When the object is polyhedral, the EGI takes the form of a set of vectors, one for each face, parallel to the outer surface normal of the face. The length of a vector is the area of the corresponding face. The EGI uniquely represents convex objects and is easily derived from conventional models of an object. An iterative algorithm is described which converts an EGI into an object model in terms of coordinates of vertices, edges, and faces. The algorithm converges to a solution by constrained optimization. There are two aspects to describing shape for polyhedral objects: first, the way in which faces intersect each other, termed the adjacency structure, and, second, the location of the faces in space. The latter may change without altering the former, but not vice versa. The algorithm for shape recovery determines both elements of shape. The continuous support function is described in terms of the area function for curves, permitting a qualitative comparison of the smoothness of the two functions. The next Section describes a method of curve segmentation based on extrema of the support function. Because the support function varies with translation, its behaviour under translation is studied, leading to proposals for several candidate centres of support. The study of these ideas suggests some interesting problems in computational geometry. The EGI has been applied to determine object attitude, the rotation in 3-space bringing a sample object into correspondence with a prototype. The methods developed for the inversion problem can be applied to attitude determination. Experiments show attitude determination using the new method to be more robust than area matching methods. The method given here can be applied at lower resolution of orientation, so that it is possible to sample the space of attitudes more densely, leading to increased accuracy in attitude determination. The discussion finally is broadened to include non-convex objects, where surface orientation is not unique. The generalizations of the EGI do not support shape reconstruction for arbitrary non-convex objects. However, surfaces of revolution do allow a natural generalization of the EGI. The topological structure of regions of constant sign of curvature is invariant under Euclidean motion, and may be useful for recognition tasks.

In this study a procedure for input uncertainty quantification (UQ) in computational fluid dynamics (CFD) simulations is proposed. The suggested procedure has been applied to a test case. The test case concerns the modeling of a heavy gas release into an atmospheric boundary layer over a barrier. The following uncertain parameters are investigated in their respective intervals: release velocity (18 m/s, 22 m/s), release temperature (270 K, 310 K) and the atmospheric boundary layer velocity (3 m/s, 7 m/s). The Stochastic Collocation (SC) method is used to perform the probabilistic propagation of the uncertain parameters. The uncertainty analysis was performed with two sets of sampling grids (full and sparse grids) for the uncertain parameters. The results show which of the selected uncertain parameters have the largest impact on the dispersed gas plume and the local concentrations in the gas cloud. Additionally, using sparse grids shows potential to reduce the computational effort of the uncertainty analysis.

A maximum likelihood method for estimating remote surface orientation from multi-static acoustic, optical, radar, or laser images is presented. It is assumed that the images are corrupted by signal-dependent noise, known as speckle, arising from complex Gaussian field fluctuations, and that the surface properties are effectively Lambertian. Surface orientation estimates for a single sample are shown to have biases and errors that vary dramatically depending on illumination direction. This is due to the signal-dependent nature of speckle noise and the nonlinear relationship between surface orientation, illumination direction, and fluctuating radiance. The minimum number of independent samples necessary for maximum likelihood estimates to become asymptotically unbiased and to attain the lower bound on resolution of classical estimation theory are derived, as are practical design thresholds.

FEM-MILL: a finite element based 3D transient milling simulation environment for process plan verification and optimization

When interpreting a shaded surface image the observer must infer a three-dimensional shape from a two-dimensional image. The principal monocular cues used in this process are surface orientation and apparent depth. Four shading algorithms were compared, ranging from pure depth to pure surface orientation with two intermediates. Eight observers assessed these algorithms using 40 sets of images showing test objects derived from emission computed axial tomograms, X-ray computed tomograms and simulated data. The results demonstrated a highly significant preference (p less than 0.01) for surface orientation over depth information for all observers and both imaging modalities. The coefficient of concordance showed that the observers were in good agreement as to the rank order of the algorithms, with significant agreement (p less than 0.05) for 37 of the 40 sets of images. The overall preferred algorithm was based on a local polynomial fitting procedure and contained primarily surface information. This shading algorithm was extended to include colour, which was used both as an arbitrary surface property to identify parts of a complex object and as a means of conveying temporal information. Further extension of the algorithm to the display of transparent surfaces was facilitated by an illumination model based on purely isotropic light. This enabled even irregular surfaces to be displayed as transparent objects, and was combined with opaque shading for displaying nested surfaces in nuclear magnetic resonance data.

Effects of surface orientation of alumina supports on the catalytic functionality of molybdenum sulfide catalysts

Surface segregation theory admits that the degree of surface enrichment depends on surface orientation through the anisotropy of surface properties such as surface energy. This prediction was tested by determining the surface composition of several grains of different surface orientation in a polycrystalline Ni–Au alloy foil. A scanning Auger microprobe provided Auger point analyses which were used to determine the surface segregation characteristics of individual (randomly oriented) grains, while selected area electron channeling patterns, obtained with a scanning electron microscope, allowed the surface orientation of each grain to be determined. A strong anisotropy of gold surface enrichment was observed; for example,the gold surface concentration at 700°C varied by as much as an order of magnitude over the range of surface orientations investigated. A plot of the variation in surface composition within the standard stereographic triangle showed trends that are comparable with the known anisotropy of surface energy in fcc metals. It is concluded that the coupling of the above experimental techniques provides a powerful tool for the study of such phenomena.

The hydraulic jump phenomenon is a beneficial tool in open channels for dissipating the extra energy of the flow. The sequent depth ratio and hydraulic jump length critically contribute to designing hydraulic structures. In this research, the capability of the Support Vector Machine (SVM) and Gaussian Process Regression (GPR) as kernel-based approaches was evaluated to estimate the features of submerged and free hydraulic jumps in channels with rough elements and various shapes, followed by comparing the findings of the GPR and SVM models and the semi-empirical equations. The results represented the effect of the geometry (i.e., steps and roughness elements) of the applied appurtenances on hydraulic jump features in channels with appurtenances. Moreover, the findings confirmed the significance of the upstream Froude number in the estimating of sequent depth ratio in submerged and free hydraulic jumps. In addition, the immersion was the highest contributing variable regarding the submerged jump length on sloped smooth bed and horizontal channels. Based on the comparisons among kernel-based approaches and the semi-empirical equations, kernel-based models showed better performance than these equations. Finally, an uncertainty analysis was conducted to assess the dependability of the best applied model. The results revealed that the GRP model possesses an acceptable level of uncertainty in the modeling process.

Conventional methods in robot vision use the intensity of light reflected or emitted by objects in order to perform object recognition. However, information contained in the polarization of the light can often aid in the determining of surface properties such as roughness, index of refraction, and spatial orientation. Imaging of such surface properties would facilitate image segmentation and classification of objects in military target recognition, environmental monitoring, oceanography, forestry, agriculture, and automated assembly. Physics Innovations Inc. is developing a thermal imaging technique where, in each image pixel, three Stokes parameters are sensed simultaneously and at video frequencies. The Stokes parameters are intensity I, percent of polarization P, and angle of the plane of polarization (phi) . Although infrared, thermal intensity images of terrestrial scenes have low contrast, images of P and (phi) are expected to have high contrast. In this paper the Physics Innovations sensor is described. We also discuss our evolution of the performance of a prototype sensor. Images of I, P, and (phi) from the prototype sensor demonstrate that, for common man-made objects with smooth surfaces, surface orientation can be derived. Surface orientations can be measured in the same image frame as temperature distribution. From our results using the prototype sensor, we conclude that three-dimensional information, in addition to thermal information, can be derived from polarization-sensitive, thermal imaging.

We have studied nucleation and crystal growth of calcium carbonate on hard surfaces, i.e. stainless steel and silica, at different temperatures, in relation to the corresponding bulk processes, using scanning electron microscopy (SEM), X-ray diffraction (XRD), and ellipsometry. In the bulk solution, a mixture of all three calcium carbonate crystalline polymorphs, calcite, aragonite, and vaterite, as well as amorphous particles was observed at 25 °C, while at 55 °C aragonite and calcite crystals dominated. On surfaces only calcite crystals were observed at 25 °C, whereas aragonite and calcite crystal adsorbed on the surfaces at 55 °C. Two kinds of nucleation and adsorption mechanism of CaCO3 crystals on hard surfaces were observed, depending on the surface orientation (vertical or horizontal, i.e., subject to sedimentation) in the bulk solution. A model for the relation between interfacial layer structure, the substrate, and the solution crystallization is discussed based on the observed difference in deposition between type of surfaces and surface orientation. In addition, the effect of magnesium ion on the morphology of calcium carbonate crystals is discussed.

The first problem which arises when studying a topological classification of A-homeomorphisms with nontrivial basic sets is the problem to find a suitable topological invariant which can adequately reflect the restriction of the diffeomorphism to the basic set as well as the embedding of the basic sets to the ambient manifold. Let \(f,~f'\) be orientation preserving A-diffeomorphisms of orientable compact manifolds \(M^n,~{M}^{\prime n}\) (possibly with boundary) respectively and let \(f,~f'\) have nontrivial basic sets \(\varLambda ,~\varLambda '\) respectively which are in the interior of the manifold. The problem is to find necessary and sufficient conditions of existence of a homeomorphism \(h:M^n\rightarrow M^{\prime n}\) such that \(hf|_{\varLambda }=f'h|_{\varLambda }\). We show that the problem of topological conjugacy for arbitrary 2-dimensional and 1-dimensional basic sets as well as 0-dimensional basic sets without pairs of conjugated points can be reduced to the analogues problem for widely situated basic sets on an orientable surface with boundary (possibly empty) which is called a canonical support of the basic set. The study of the latter is essentially based on the investigation of the asymptotic properties of the stable and unstable manifolds of the points of the basic sets on the universal cover. The suggested method solves the problem of realization of arbitrary 1-dimensional basic sets as well as 0-dimensional basic sets without pair of conjugated points by constructing a so called hyperbolic diffeomorphism on the support of the basic set such that it has an invariant locally maximal set on the intersection of two geodesic laminations. We show that the restriction of the diffeomorphism f to the basic set is a factor of the restriction of the hyperbolic diffeomorphism to the intersection of the respective laminations. If the basic set is widely situated on the torus then for it a hyperbolic automorphism of the torus (Anosov diffeomorphism) is uniquely defined and it is a factor of the initial diffeomorphism. If the diffeomorphism f is structurally stable then the support of the basic set can be constructed in such a way that the restriction of the initial diffeomorphism to it consists of exactly one nontrivial basic set and of finitely many hyperbolic periodic points belonging to the boundary of the support. This and the results on the classification of the Morse-Smale diffeomorphisms enable us to construct a complete topological invariant for important classes of structurally stable diffeomorphisms on surfaces whose non-wandering sets contain a nontrivial 1-dimensional basic set (attractor or repeller). Such a class was studied for instance in [8]. The presentation of the results in this chapter follows the papers [2, 6, 7, 8, 9, 10, 11, 12, 16, 17] and it is in many concepts related to the papers [1, 4, 5, 14, 15].

Series of two-dimensional Auger electron intensity angular distributions (AIAD) were measured from a polycrystalline iron surface using a focused soft X-ray beam and a display-type analyzer. The Fe(110) surface was polycrystallized by annealing up to the Martensitic transition temperature in an ultrahigh vacuum condition. After cooling the sample to room temperature, the crystal orientations of the 21 × 21 scanned points were determined by Fe LMM AIAD measurements. Domain formation of sub mm size was confirmed. The domains oriented in the [001] direction were found adjacent to the domain oriented in the [110] direction, suggesting that the Martensitic transition progressed according to the Bain relationship. The chemical and magnetic properties of domains with different surface orientations were characterized by combining diffraction measurements with X-ray absorption spectroscopy techniques. We show here how the surface oxidation reaction as well as the magnetization axis depend on the surface orientation.

Estimating spectral plane-of-array (POA) solar irradiance on inclined surfaces is an important step in the design and performance evaluation of both photovoltaic and concentrated solar plants. This work introduces a fast, line-by-line spectral, Monte Carlo (MC) radiative transfer model approach to simulate anisotropic distributions of shortwave radiation through the atmosphere as photon bundles impinge on inclined surfaces. This fast Monte Carlo approach reproduces the angular distribution of solar irradiance without the undesirable effects of spatial discretization and thus computes detailed POA irradiance values on surfaces at any orientation and also when surfaces are subjected to the anisotropic ground and atmospheric scattering. Polarization effects are also easily incorporated into this approach that can be considered as direct numerical simulation of the physics involved. Here, we compare our Monte Carlo radiative transfer model with the most widely used empirical transposition model, Perez4, under various conditions. The results show that the Perez4 model reproduces the more detailed Monte Carlo simulations with less than 10% deviation under clear skies for all relevant surface tilt and azimuth angles. When optically thin clouds are present, observed deviations are larger, especially when the receiving surface is strongly tilted. Deviations are also observed for large azimuth angle differences between the receiving surface and the solar position. When optically thick clouds are present, the two models agree within 15% deviation for nearly all surface orientation and tilt angles. The overall deviations are smaller when compared with cases for optically thin clouds. The Perez4 model performs very well (∼6.0% deviation) in comparison with the detailed MC simulations for all cases, thus validating its widespread use for practical solar applications. When detailed atmospheric profiles and cloud optical properties are available, the proposed fast Monte Carlo radiative model reproduces accurate spectral and angular POA irradiance levels for various atmospheric and cloud cover conditions, surface orientations, and different surface and ground properties.