Adaptive cell division for ray tracing

In ray tracing the two most commonly used data structures are the octree and uniform cell division. The octree structure allows efficient adaptive subdivision of space, while taking care of the spatial coherence of the objects in it; however, the tree structure locating the next node in the path of a ray is complex and time consuming. The cell structure, on the other hand, can be stored in a three-dimensional array, and each cell can be efficiently accessed by specifying three indices. However, such a uniform cell division does not take care of object coherence. The proposed data structure combines the positive features of the above data structures while minimising their disadvantages. The entire object space is implicitly assumed to be a three-dimensional grid of cells. Initially, the entire object space is a single voxel which later undergoes “adaptive cell division.” But, unlike in the octree structure, where each voxel is divided exactly at the middle of each dimension, in adaptive cell division, each voxel is divided at the nearest cell boundary. The result is that each voxel contains an integral number of cells along each axis. Corresponding to the implicit cell division we maintain a three-dimensional array, with each array element containing the voxel number which is used to index into the voxel array. The voxel array is used to store information about the structure of each voxel, in particular, the objects in each voxel. While a ray moves from one voxel to another we always keep track of the cell through which the ray is currently passing. Since only arrays are involved in accessing the next voxel in the path of the ray, the operation is very efficient.     

Finite-element grid improvement by minimization of stiffness matrix trace

A new and simple method of finite-element grid improvement is presented. The objective is to improve the accuracy of the analysis. The procedure is based on a minimization of the trace of the stiffness matrix. For a broad class of problems this minimization is seen to be equivalent to minimizing the potential energy. The method is illustrated with the classical tapered bar problem examined earlier by Prager and Masur. Identical results are obtained.     

Microscopical studies of water/flour systems

Summary Wheat flour particles sprinkled on a water surface form strands which are visible in the light microscope. These strands form aggregates by means of mechanical forces which show viscoelastic behaviour. Amino acid analysis of both the protein strands and the aggregates formed shows that they consist of gluten protein. The formation of the protein strands occurs at the air/water interface and results from the action of a protein film which spreads around the flour particles.

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Mikroskopische Untersuchungen von Mehl/Wasser-Systemen

Zusammenfassung Weizenmehlpartikel, die auf Wasser gestreut werden, bilden lichtmikroskopisch sichtbare Stränge aus. Durch mechanische Beanspruchung lassen sich these Stränge zu Aggregaten zusammenfassen, die visco-elastisches Verhalten zeigen. Die Aminosäureanalyse sowohl der Proteinstrange wie auch der daraus gebildeten Aggregate zeigt, daß es sich dabei um Kleberprotein handelt. Die Proteinfäden entstehen an der Wasser-Luft-Grenzflache als Folge eines spreitenden Proteinfilms, der sich um die Mehlpartikel herum ausbreitet.

     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Magnetic field dependence of shielding current density in Y-Ba-Cu-O rings at 77 K

A method for contactless measurement of the shielding critical current density and its dependence on the external magnetic field is described and analyzed. The obtained values are compared with those measured resistively on two different samples. It is shown that the shielding critical current densityJ _cs and the intergranular transport current densityJ _cr are identical if the measurement conditions are similar. A degradation ofJ _cs measured in the external field with AC ripple has been observed.     

Intelligent identification and control for autonomous guided vehicles using adaptive fuzzy-based algorithms

Fuzzy logic was first suggested as the mechanism by which humans drive cars. This paper addresses the use of fuzzy logic and algorithms towards the intelligent autonomous motion control of land vehicles. To cope with vehicle complexities, internal parametric changes, and with unpredictable environmental effects, the controllers that are presented, whilst heuristic in nature, are self-organizing or self-learning in that they generate automatically by observation an experiential rule base that models the vehicle, and via an appropriate performance index an optimal control rule base that is robust to large parametric changes. The methodology presented is applicable to any complex process which is too difficult to model or control using conventional methods, or which has relied on the experience of a human operator. An overview of fuzzy logic and static fuzzy logic control (akin to expert systems) is provided, together with illustrative examples.     

Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

心电图信号的频域分析

提出了一种简便有效的、由心电图（ECG）曲线提取QRS-T复合波的新方法，从而获得P波（当房颤未发生时）或f波（当房颤时）；利用功率谱、自相关、互相关等信号处理技术，对它进行了处理和分析，特别是，比较了未房颤时和发生房颤时的相关信息的显著差别。