This paper presents the results of the theoretical and practical analysis of selected features of the function of conditional average value of the absolute value of delayed signal (CAAV). The results obtained with the CAAV method have been compared with the results obtained by method of cross correlation (CCF), which is often used at the measurements of random signal time delay. The paper is divided into five sections. The first is devoted to a short introduction to the subject of the paper. The model of measured stochastic signals is described in Section 2. The fundamentals of time delay estimation using CCF and CAAV are presented in Section 3. The standard deviations of both functions in their extreme points are evaluated and compared. The results of experimental investigations are discussed in Section 4. Computer simulations were used to evaluate the performance of the CAAV and CCF methods. The signal and the noise were Gaussian random variables, produced by a pseudorandom noise generator. The experimental standard deviations of both functions for the chosen signal to noise ratio (SNR) were obtained and compared. All simulation results were averaged for 1000 independent runs. It should be noted that the experimental results were close to the theoretical values. The conclusions and final remarks were included in Section 5. The authors conclude that the CAAV method described in this paper has less standard deviation in the extreme point than CCF and can be applied to time delay measurement of random signals.

We discuss recent progress in hybrid atomistic-continuum methods with particular emphasis on developments in boundary condition imposition in molecular simulations, an essential ingredient of hybrid methods. Both Dirichlet (state variable) and flux boundary conditions are discussed. We also briefly review various coupling approaches and discuss the effects of compressibility and molecular fluctuations on the choice of coupling method. Common elements between hybrid methods and related multiscale simulation approaches are also briefly discussed.

In the structure of cities functional and spatial transformations are constant and are reflected in their contemporary landscape. The enormous scale of present cities creates difficulties in managing their heterogeneous landscape. This city landscape is composition of a number of different landscape units with distinct characteristics and values. Identification and delimitation of those landscape units based on field and study research could therefore be the key for urban landscape management. The current administrative city districts do not include landscape in as material for administration. In one administrational city district even few landscape units can be found. The delimitation of city landscapes as a part of Local Spatial Development Plan may be the basis for setting detailed guidelines for landscape administration. Landscape units therefore could become efficient management tool for urban landscaping.