The paper deals with the problem of bias randomization in evaluation of the measuring instrument capability. The bias plays a significant role in assessment of the measuring instrument quality. Because the measurement uncertainty is a comfortable parameter for evaluation in metrology, the bias may be treated as a component of the uncertainty associated with the measuring instrument. The basic method for calculation of the uncertainty in modern metrology is propagation of distributions. Any component of the uncertainty budget should be expressed as a distribution. Usually, in the case of a systematic effect being a bias, the rectangular distribution is assumed. In the paper an alternative randomization method using the Flatten-Gaussian distribution is proposed.
The paper concerns the problem of treatment of the systematic effect as a part of the coverage interval associated with the measurement result. In this case the known systematic effect is not corrected for but instead is treated as an uncertainty component. This effect is characterized by two components: systematic and random. The systematic component is estimated by the bias and the random component is estimated by the uncertainty associated with the bias. Taking into consideration these two components, a random variable can be created with zero expectation and standard deviation calculated by randomizing the systematic effect. The method of randomization of the systematic effect is based on a flatten-Gaussian distribution. The standard uncertainty, being the basic parameter of the systematic effect, may be calculated with a simple mathematical formula. The presented evaluation of uncertainty is more rational than those with the use of other methods. It is useful in practical metrological applications.
Transverse effective thermal conductivity of the random unidirectional fibre-reinforced composite was studied. The geometry was circular with random patterns formed using random sequential addition method. Composite geometries for different volume fraction and fibre radii were generated and their effective thermal conductivities (ETC) were calculated. Influence of fibre-matrix conductivity ratio on composite ETC was investigated for high and low values. Patterns were described by a set of coordination numbers (CN) and correlations between ETC and CN were constructed. The correlations were compared with available formulae presented in literature. Additionally, symmetry of the conductivity tensor for the studied geometries of fibres was analysed.
A spinal code is the type of rateless code, which has been proved to be capacity- achieving over both a binary symmetric channel (BSC) and an additive white Gaussian noise (AWGN) channel. Rateless spinal codes employ a hash function as a coding kernel to generate infinite pseudo-random symbols. A good hash function can improve the perfor- mance of spinal codes. In this paper, a lightweight hash function based on sponge structure is designed. A permutation function of registers is a nonlinear function. Feedback shift registers are used to improve randomness and reduce bit error rate (BER). At the same time, a pseudo-random number generator adopts a layered and piecewise combination mode, which further encrypts signals via the layered structure, reduces the correlation between input and output values, and generates the piecewise random numbers to compensate the shortcoming of the mixed linear congruence output with fixed length. Simulation results show that the designed spinal code with the lightweight hash function outperforms the original spinal code in aspects of the BER, encoding time and randomness.