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Abstract. In this paper we present a method for creating scheduling heuristics for parallel proportional machine scheduling environment and arbitrary performance criteria. Genetic programming is used to synthesize the priority function which, coupled with an appropriate metaalgorithm for a given environment, forms the priority scheduling heuristic. We show that the procedures derived in this way can perform similarly or better than existing algorithms. Additionally, this approach may be particularly useful for those combinations of scheduling environment and criteria for which there are no adequate scheduling algorithms.

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This paper deals with surface reconstruction and the gradient reconstruction in the volume rendering. In the volume rendering procedure, reconstruction according to the discrete set of samples is required. Due to the reconstruction procedure alias artifacts, in the final image, could not be neglected. In this paper we focus our attention on the gradient reconstruction based on the surface reconstruction. For the surface reconstruction we use the cubic B-splines and for the gradient reconstruction corresponding derivative.If the noise is present in the input data the approximation I)-spline is used, and the interpolation B-spline is used for the input signal without the noise. The shading procedure requires normal estimation. Two approaches are used for normal estimation. The classic approach for normal estimation is central difference calculation, and we propose derivative calculation of the reconstruction B-spline function. We show that calculation of the normal vector has important influence on the alias artifacts in the result.

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