The paper is concerned with issues of the estimation of random variable distribution parameters by the Monte Carlo method. Such quantities can correspond to statistical parameters computed based on the data obtained in typical measurement situations. The subject of the research is the mean, the mean square and the variance of random variables with uniform, Gaussian, Student, Simpson, trapezoidal, exponential, gamma and arcsine distributions.

Speech enhancement objective is to improve the noisy speech signals for human perception. The intention of speech enhancement algorithm is to improve the performance of the communication, when the signal is occluded by noise. The quality and intelligibility of speech is reduced because of the presence of background noise. There are various adaptive filtering algorithms for speech enhancement. The existing least mean square and normalised least mean square algorithms have the problem of choosing the step size that guarantees the stability of the algorithm. To overcome this problem, we focus on speech enhancement by amended adaptive filtering. The proposed algorithm follows blind source separation strategy using adaptive filtering. Comparison of existing adaptive filtering algorithms with proposed algorithm justifies the amendment incorporated in this paper. Taking the objective criteria into account the algorithms has been tested for segmental signal to noise ratio (SegSNR), segmental mean square error (SegMSE), signal to noise ratio and mean square error. The proposed algorithm can be used for hand-free cell phone, hearing aids and teleconferencing systems.

In the study we introduce an extension to a stochastic volatility in mean model (SV-M), allowing for discrete regime switches in the risk premium parameter. The logic behind the idea is that neglecting a possibly regimechanging nature of the relation between the current volatility (conditional standard deviation) and asset return within an ordinary SV-M specication may lead to spurious insignicance of the risk premium parameter (as being ‛averaged out’ over the regimes). Therefore, we allow the volatility-in-mean eect to switch over dierent regimes according to a discrete homogeneous two-state Markov chain. We treat the new specication within the Bayesian framework, which allows to fully account for the uncertainty of model parameters, latent conditional variances and hidden Markov chain state variables. Standard Markov Chain Monte Carlo methods, including the Gibbs sampler and the Metropolis-Hastings algorithm, are adapted to estimate the model and to obtain predictive densities of selected quantities. Presented methodology is applied to analyse series of the Warsaw Stock Exchange index (WIG) and its sectoral subindices. Although rare, once spotted the switching in-mean eect substantially enhances the model t to the data, as measured by the value of the marginal data density.

Numerical methods are mostly used to predict the acoustic pressure inside duct systems. In this paper, the development of a numerical method based on the convected Helmholtz equation to compute the acoustic pressure inside an axisymmetric duct is presented. A validation of the proposed method was done by a comparison with the analytical formulation for simple cases of hard wall and lined ducts. The effect of the flow on the acoustic pressure inside these ducts was then evaluated by computing this field with different Mach numbers.

One of the important parameters describing pneumatic liquid atomisation is the air to liquid mass ratio (ALR). Along with the atomiser design and properties of the liquid it has extremely important influence on parameters of atomised liquid such as: mean droplet diameter, jet range and angle. Knowledge about real characteristics of an atomiser in this respect is necessary to correctly choose its operating parameters in industrial applications.

The paper presents results of experimental research of two-fluid atomisers with internal mixing built according to custom design. Investigated atomizers were designed for spraying a urea aqueous solution inside the power boiler combustion chamber. They are an important element of SNCR (selective non-catalytic reduction) installation which is used to reduce nitrogen oxides in a flue gas boiler. Obtained results were used by authors in further research, among others to determine the boundary conditions in the SNCR installation modeling.

The research included determining mean droplet diameter as a function of ALR. It has been based on the immersion liquid method and on the use of specialised instrumentation for determining distribution of droplet diameters in a spray – Spraytec by Malvern. Results obtained with both methods were later compared. The measurements were performed at a laboratory stand located at the Institute of Heat Engineering, Warsaw University of Technology. The stand enables extensive investigation of the water atomisation process.

For many years, learning the competences to teach mathematics in early education at university has been associated with the ability to reproductively apply methodological guidelines. Currently, however, the need to not only understand the mathematical meanings given by teachers, but also students of the specialty, are seen to be important. This article attempts to engage in an interpretive line of thinking with regard to mathematics education, coming from the perspective of students learning to be early education teachers. Their understanding of the contexts for learning mathematical concepts, as well as their sensitivity to the processes of constructing mathematical knowledge by very young pupils, being a way of predicting what educational activities will be undertaken in the classroom in the future. This text is the result of qualitative analyses of written essays of early education students, where respondents had to make conceptualizations of their beliefs by justifying the selection of particular declarative statements. Students’ mathematical meanings were also uncovered in their strategies for solving mathematical problems for very young pupils. Moreover, the results of this analyses provides a context for reading the students’ understanding of mathematics learning processes.

Among the big corpus of the commentaries over the Qur’an, one of the special developments was a genre of gloss (hāšiya). The study addresses main Ottoman glosses written to the Qur’anic commentaries, contextualizing it within the internal dimensions of the content transformations. It is argued that since the glosses were used as the textbooks in the Ottoman medrese, they could be considered as the “mainstream” Ottoman reading of the Qur’an. This reading was not merely one of the practices for approaching the Qur’an, but the kind of tradition with the related authorities and meaningful developments. The research covers these patterns of interpretations applied to the case of Āl ‘Imrān, 3: 7, showing the way of how the philology and theology interacted in the Ottoman tafsīr glosses.

The recently proposed q-rung orthopair fuzzy set (q-ROFS) characterized by a membership degree and a non-membership degree is powerful tool for handling uncertainty and vagueness. This paper proposes the concept of q-rung orthopair linguistic set (q-ROLS) by combining the linguistic term sets with q-ROFSs. Thereafter, we investigate multi-attribute group decision making (MAGDM) with q-rung orthopair linguistic information. To aggregate q-rung orthopair linguistic numbers ( q-ROLNs), we extend the Heronian mean (HM) to q-ROLSs and propose a family of q-rung orthopair linguistic Heronian mean operators, such as the q-rung orthopair linguistic Heronian mean (q-ROLHM) operator, the q-rung orthopair linguistic weighted Heronian mean (q-ROLWHM) operator, the q-rung orthopair linguistic geometric Heronian mean (q-ROLGHM) operator and the q-rung orthopair linguistic weighted geometric Heronian mean (q-ROLWGHM) operator. Some desirable properties and special cases of the proposed operators are discussed. Further, we develop a novel approach to MAGDM within q-rung orthopair linguistic context based on the proposed operators. A numerical instance is provided to demonstrate the effectiveness and superiorities of the proposed method.

The study aims at a statistical verification of breaks in the risk-return relationship for shares of individual companies quoted at the Warsaw Stock Exchange. To this end a stochastic volatility model incorporating Markov switching in-mean effect (SV-MS-M) is employed. We argue that neglecting possible regime changes in the relation between expected return and volatility within an ordinary SV-M specification may lead to spurious insignificance of the risk premium parameter (as being ’averaged out’ over the regimes).Therefore, we allow the volatility-in-mean effect to switch over different regimes according to a discrete homogeneous two- or
three-state Markov chain. The model is handled within Bayesian framework, which allows to fully account for the uncertainty of
model parameters, latent conditional variances and state variables. MCMC methods, including the Gibbs sampler, Metropolis-Hastings algorithm and the forward-filtering-backward-sampling scheme are suitably adopted to obtain posterior densities of interest as well
as marginal data density. The latter allows for a formal model comparison in terms of the in-sample fit and, thereby, inference on the
’adequate’ number of the risk premium regime

The aim of the article is to construct an asymptotically consistent test, based on a subsampling approach, to verify hypothesis about existence of the individual or common deterministic cycle in coordinates of multivariate macroeconomic time series. By the deterministic cycle we mean the periodic or almost periodic fluctuations in the mean function in cyclical fluctuations. To construct test we formulate a multivariate non-parametric model containing the business cycle component in the unconditional mean function. The construction relies on the Fourier representation of the unconditional expectation of the multivariate Almost Periodically Correlated time series and is related to fixed deterministic cycle presented in the literature. The analysis of the existence of common deterministic business cycles for selected European countries is presented based on monthly industrial production indexes. Our main findings from the empirical part is that the deterministic cycle can be strongly supported by the data and therefore should not be automatically neglected during analysis without justification.

In the areas of acoustic research or applications that deal with not-precisely-known or variable conditions, a method of adaptation to the uncertainness or changes is usually necessary. When searching for an adaptation algorithm, it is hard to overlook the least mean squares (LMS) algorithm. Its simplicity, speed of computation, and robustness has won it a wide area of applications: from telecommunication, through acoustics and vibration, to seismology. The algorithm, however, still lacks a full theoretical analysis. This is probabely the cause of its main drawback: the need of a careful choice of the step size - which is the reason why so many variable step size flavors of the LMS algorithm has been developed.

This paper contributes to both the above mentioned characteristics of the LMS algorithm. First, it shows a derivation of a new necessary condition for the LMS algorithm convergence. The condition, although weak, proved useful in developing a new variable step size LMS algorithm which appeared to be quite different from the algorithms known from the literature. Moreover, the algorithm proved to be effective in both simulations and laboratory experiments, covering two possible applications: adaptive line enhancement and active noise control.

The velocity field around the standard Rushton turbine was investigated by the Laser Doppler Anemometry (LDA) and Particle Image Velocimetry (PIV) measurements. The mean ensembleaveraged velocity profiles and root mean square values of fluctuations were evaluated at two different regions. The first one was in the discharge stream in the radial direction from the impeller where the radial flow is dominant and it is commonly modelled as a swirling turbulent jet. The validity range of the turbulent jet model was studied. The second evaluated region is under the impeller where flow seems to be at first sight rather rigorous but obtained results show nonnegligible values of fluctuation velocity.

This paper presents a numerical analysis of an agitated fully baffled cylindrical vessel with a down pumping four blade worn or unworn pitched blade impeller (α = 45° and 30°) under a turbulent flow regime. CFD simulations predict the pumping capacity of the system equipped by worn and unworn pitched blade impeller. Experimental data were taken from the authors’ previous work and compared with results of numerical computations. A good agreement with experimental data was obtained. The ensemble-average mean velocity field with worn and unworn impellers was computed. It follows from the simulation results that the wear rate of the impeller blade has a significantly negative effect on the velocity distribution in an agitated liquid. The greater the destruction of the worn blade, the higher is the deformation of the velocity field around the rotating impeller, with a simultaneous decrease in impeller pumping capacity.

The correlation of data contained in a series of signal sample values makes the estimation of the statistical characteristics describing such a random sample difficult. The positive correlation of data increases the arithmetic mean variance in relation to the series of uncorrelated results. If the normalized autocorrelation function of the positively correlated observations and their variance are known, then the effect of the correlation can be taken into consideration in the estimation process computationally. A significant hindrance to the assessment of the estimation process appears when the autocorrelation function is unknown. This study describes an application of the conditional averaging of the positively correlated data with the Gaussian distribution for the assessment of the correlation of an observation series, and the determination of the standard uncertainty of the arithmetic mean. The method presented here can be particularly useful for high values of correlation (when the value of the normalized autocorrelation function is higher than 0.5), and for the number of data higher than 50. In the paper the results of theoretical research are presented, as well as those of the selected experiments of the processing and analysis of physical signals.

Cooling is indispensable for maintaining the desired performance and reliability over a very huge variety of products like electronic devices, computer, automobiles, high power laser system etc. Apart from the heat load amplification and heat fluxes caused by many industrial products, cooling is one of the major technical challenges encountered by the industries like manufacturing sectors, transportation, microelectronics, etc. Normally water, ethylene glycol and oil are being used as the fluid to carry away the heat in these devices. The development of nanofluid generally shows a better heat transfer characteristics than the water. This research work summarizes the experimental study of the forced convective heat transfer and flow characteristics of a nanofluid consisting of water and 1% Al₂O₃(volume concentration) nanoparticle flowing in a parallel flow, counter flow and shell and tube heat exchanger under laminar flow conditions. The Al₂O₃ nanoparticles of about 50 nm diameter are used in this work. Three different mass flow rates have been selected and the experiments have been conducted and their results are reported. This result portrays that the overall heat transfer coefficient and dimensionless Nusselt number of nanofluid is slightly higher than that of the base liquid at same mass flow rate at same inlet temperature. From the experimental result it is clear that the overall heat transfer coefficient of the nanofluid increases with an increase in the mass flow rate. It shows that whenever mass flow rate increases, the overall heat transfer coefficient along with Nusselt number eventually increases irrespective of flow direction. It was also found that during the increase in mass flow rate LMTD value ultimately decreases irrespective of flow direction. However, shell and tube heat exchanger provides better heat transfer characteristics than parallel and counter flow heat exchanger due to multi pass flow of nanofluid. The overall heat transfer coefficient, Nusselt number and logarithmic mean temperature difference of the water and Al₂O₃/water nanofluid are also studied and the results are plotted graphically.

Although currently pole dancing is growing in popularity due to its sport dimension, it seems that such a form of expression is still commonly associated with strip clubs and connotes above all the erotic performance of a woman in front of a male audience. And yet, as one can find by frequenting dance studios that teach pole dancing, it is practiced not only by women, but also by men and children. Thus keeping in mind the ambiguity that arises at the intersection of competing optics in decoding the pole dance—with regard to “perpetuate interpretation logic” and the everyday experience of people undertaking the activity—the aim of this paper is to reflect on the issue of constructing and interpreting the meanings of actions and processes within the context of pole dancing. These processes can be seen as a reflection of the everyday life in which they occur.