The annual rate of decomposition in five soil types of tundra situated in the Fugleberget drainage area (Hornsund Fjord, South Spitsbergen) was investigated by use of the method of standard cellulose samples. The rate of decomposition varied from 15% to over 65% a year and was closely connected with a contents of nitrogen in soil, amount of which varied from 0.33% to 3.44%. The results presently obtained are much higher than those obtained by the same method in other polar regions.
The main goal of the considered work is to adjust mathematical modeling for mass transfer, to specific conditions resulting from presence of chemical surface reactions in the flow of the mixture consisting of helium and methanol. The thermocatalytic devices used for decomposition of organic compounds incorporate microchannels coupled at the ends and heated to 500 ◦C at the walls regions. The experiment data were compared with computational fluid dynamics results to calibrate the constants of the model’s user defined functions. These extensions allow to transform the calculations mechanisms and algorithms of commercial codes adapting them for the microflows cases and increased chemical reactions rate on the interphase between fluid and solid, specific for catalytic reactions. Results obtained on the way of numerical calculations have been calibrated and compared with the experimental data to receive satisfactory compliance. The model has been verified and the performance of the thermocatalytic reactor with microchannels under hydrogen production regime has been investigated.
This paper focuses on the thermal behavior of the starch-based binder (Albertine F/1 by Hüttenes-Albertus) used in foundry technology of molding sand. The analysis of the course of decomposition of the starch material under controlled heating in the temperature range of 25-1100°C was conducted. Thermal analysis methods (TG-DTG-DSC), pyrolysis gas chromatography coupled with mass spectrometry (Py-GC/MS) and diffuse reflectance spectroscopy (DRIFT) were used. The application of various methods of thermal analysis and spectroscopic methods allows to verify the binder decomposition process in relation to conditions in the form in both inert and oxidizing atmosphere. It was confirmed that the binder decomposition is a complex multistage process. The identification of CO2 formation at set temperature range indicated the progressive process of decomposition. A qualitative evaluation of pyrolysis products was carried out and the course of structural changes occurring in the presence of oxygen was determined based on thermo-analytical investigations the temperature of the beginning of binder degradation in set condition was determined. It was noticed that, significant intensification of Albertine F/1 sample decomposition with formation of more degradation products took place at temperatures above 550ºC. Aromatic hydrocarbons were identified at 1100ºC.
The paper presents modification of the method dedicated to a complex area decomposition of a set of logic functions whereas the altered method is dedicated to implement the considered logic circuits within FPGA structures. The authors attempted to reach solutions where the number of configurable logic blocks and the number of structural layer would be reasonably balanced on the basis of the minimization principle. The main advantage of the procedure when the decomposition is carried out directly on the BDD diagram is the opportunity of immediate checking whether the decomposed areas of the diagram do not exceed the resources of logic blocks incorporated into the integrated circuits that are used for implementation of the logic functions involved.
The most challenging in speech enhancement technique is tracking non-stationary noises for long speech segments and low Signal-to-Noise Ratio (SNR). Different speech enhancement techniques have been proposed but, those techniques were inaccurate in tracking highly non-stationary noises. As a result, Empirical Mode Decomposition and Hurst-based (EMDH) approach is proposed to enhance the signals corrupted by non-stationary acoustic noises. Hurst exponent statistics was adopted for identifying and selecting the set of Intrinsic Mode Functions (IMF) that are most affected by the noise components. Moreover, the speech signal was reconstructed by considering the least corrupted IMF. Though it increases SNR, the time and resource consumption were high. Also, it requires a significant improvement under nonstationary noise scenario. Hence, in this article, EMDH approach is enhanced by using Sliding Window (SW) technique. In this SWEMDH approach, the computation of EMD is performed based on the small and sliding window along with the time axis. The sliding window depends on the signal frequency band. The possible discontinuities in IMF between windows are prevented by the total number of modes and the number of sifting iterations that should be set a priori. For each module, the number of sifting iterations is determined by decomposition of many signal windows by standard algorithm and calculating the average number of sifting steps for each module. Based on this approach, the time complexity is reduced significantly with suitable quality of decomposition. Finally, the experimental results show the considerable improvements in speech enhancement under non-stationary noise environments.
Wavelet transform becomes a more and more common method of processing 3D signals. It is widely used to analyze data in various branches of science and technology (medicine, seismology, engineering, etc.). In the field of mechanical engineering wavelet transform is usually used to investigate surface micro- and nanotopography. Wavelet transform is commonly regarded as a very good tool to analyze non-stationary signals. However, to analyze periodical signals, most researchers prefer to use well-known methods such as Fourier analysis. In this paper authors make an attempt to prove that wavelet transform can be a useful method to analyze 3D signals that are approximately periodical. As an example of such signal, measurement data of cylindrical workpieces are investigated. The calculations were performed in the MATLAB environment using the Wavelet Toolbox.
The stability of positive linear continuous-time and discrete-time systems is analyzed by the use of the decomposition of the state matrices into symmetrical and antisymmetrical parts. It is shown that: 1) The state Metzler matrix of positive continuous-time linear system is Hurwitz if and only if its symmetrical part is Hurwitz; 2) The state matrix of positive linear discrete-time system is Schur if and only if its symmetrical part is Hurwitz. These results are extended to inverse matrices of the state matrices of the positive linear systems.
Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.
Over the last decades the method of proper orthogonal decomposition (POD) has been successfully employed for reduced order modelling (ROM) in many applications, including distributed parameter models of chemical reactors. Nevertheless, there are still a number of issues that need further investigation. Among them, the policy of the collection of representative ensemble of experimental or simulation data, being a starting and perhaps most crucial point of the POD-based model reduction procedure. This paper summarises the theoretical background of the POD method and briefly discusses the sampling issue. Next, the reduction procedure is applied to an idealised model of circulating fluidised bed combustor (CFBC). Results obtained confirm that a proper choice of the sampling strategy is essential for the modes convergence however, even low number of observations can be sufficient for the determination of the faithful dynamical ROM.
Ludwigite is the main available boron-bearing resource in China. In order to enrich the theory system and optimize its utilization processes, this paper study the mechanism and kinetics on non-isothermal decomposition of ludwigite in inert atmosphere by means of thermal analysis. Results show that, the decomposition of serpentine and szajbelyite is the main cause of mass loss in the process. At the end of decomposition, hortonolite and ludwigite are the two main phases in the sample. The average E value of structural water decomposition is 277.97 kJ/mol based on FWO method (277.17 kJ/mol based on KAS method). The results is proved to be accurate and reliable. The mechanism model function of structural water decomposition is confirmed by Satava method and Popescu method. The form of the most probable model function is G(α) = (1 – α)–1 – 1 (integral form) and f (α) = (1 – α)2 (differential form), and its mechanism is chemical reaction. This is verified by the criterion based on activation energy of model-free kinetics analysis.
We estimated a structural vector autoregressive (SVAR) model describing the links between a banking sector and a real economy. We proposed a new method to verify robustness of impulse-response functions to the ordering of variables in an SVAR model. This method applies permutations of orderings of variables and uses the Cholesky decomposition of the error covariance matrix to identify parameters. Impulse response functions are computed and combined for all permutations. We explored the method in practice by analyzing the macro-financial linkages in the Polish economy. Our results indicate that the combined impulse response functions are more uncertain than those from a single model specification with a given ordering of variables, but some findings remain robust. It is evident that macroeconomic aggregate shocks and interest rate shocks have a significant impact on banking variables.
The paper presents the results of analyzes of gases emitted during exposure to high temperature foundry molding sands, where binders are organic resins. As a research tool has been used special gas chromatograph designed to identify odorous compounds including the group of alkanes.
Poland is expected to enter the Exchange Rate Mechanism II (ERM II). The European Central Bank recommends that the ERM II central rate should reflect the best possible assessment of the equilibrium exchange rate. Since the equilibrium rate is changing in time, it is important to identify the pushing and pulling forces of the exchange rate. This knowledge will let the authorities to defend only the exchange rate that is in equilibrium and to assess outcomes of their actions. We use the VEC approach of Johansen to estimate the behavioral equilibrium exchange rate and to identify the pushing forces of the Polish zloty/euro rate. We apply the Gonzalo-Granger decomposition to calculate the permanent equilibrium exchange rate and to identify the pulling forces of the zloty exchange rate. We demonstrate that this approach may be useful for Polish authorities while entering the ERM II as well as within that mechanism.
This paper studies the long-run relationship between consumption, labour income and asset wealth in Poland. Within cointegrated VAR model dynamic responses of the variables in the system to shocks are studied. In addition, series are decomposed into permanent and transitory components on the basis of the cointegrating relation found in the system. Main conclusion of this paper is that deviations of the three variables from their estimated long-run relationship are better explained with uctuations of labour income than assets. A tentative explanation of this nding is presented. Additionally, the magnitude of the asset wealth eect in Poland is calculated and compared with other studies for European countries and for the U.S.
The paper discusses Bayesian productivity analysis of 27 EU Member States, USA, Japan and Switzerland. Bayesian Stochastic Frontier Analysis and a two-stage structural decomposition of output growth are used to trace sources of output growth. This allows us to separate the impacts of capital accumulation, labour growth, technical progress and technical efficiency change on economic development. Since estimates of the growth components are conditioned upon model parameterisation and the underlying assumptions, a number of possible specifications are considered. The best model for decomposing output growth is chosen based on the highest marginal data density, which is calculated using adjusted harmonic mean estimator.
Organic binders applied in foundry plants based on synthetic resins, from the one side influence obtaining the required technological properties by the moulding sand and – in consequence – obtaining good quality castings, and on the other side are the source of volatile organic compounds (VOC). Together with synthetic resins their hardeners, which although added in very small amounts emit during their thermal decomposition substances negatively influencing the natural environment, are also used. Both, resins and hardeners only at the influence of high temperatures accompanying moulds pouring with liquid metal generate harmful volatile organic compounds including compounds from the BTEX group. Investigations of the temperature influence on the kind and amount of organic compounds formed during the thermal decomposition of selected binders and hardeners and their mixtures allow to determine temperature ranges the most favourable for emitting harmful substances as well as to compare their emission from the selected materials. The aim of this study was the determination the temperature influence on formation substances from the BTEX group, during thermal decomposition of the selected binder, its hardener and their mixture. The BTEX group emission constitutes one of the basic criteria in assessing the harmfulness of materials applied for moulding and core sands and it can undergo changes in dependence of the applied system resin-hardener. Investigations were carried out on the specially developed system for the thermal decomposition of organic substances in the temperature range: 5000 C – 13000 C, at the laboratory scale. The investigations subject was the furan resin, its hardener and hardened furan resin. The assessment of the emission degree of the BTEX group in dependence of the system subjected to the temperature influence was performed, within the studies. The temperature range, in which maximal amounts of benzene, toluene, ethylbenzene and xylenes were emitted from tested materials – was defined. The qualitative and quantitative analysis of the BTEX group were carried out with using the gas chromatography technique coupled with the mass spectrometry (GC/MS).
The paper presents Gupta's relational decomposition technique expanded on linguistic level. It allows to reduce the hardware cost of the fuzzy system or the computing time of the final result, especially when referring to First Aggregation Then Inference (FATI) relational systems or First Inference Then Aggregation (FITA) rule systems. The inference result of the hierarchical system using decomposition technique is more fuzzy than of the classical system. The paper describes a linguistic decomposition technique based on partitioning the knowledge base of the fuzzy inference system. It allows to decrease or even totally remove a redundant fuzziness of the inference result.
The minimum energy control problem for the positive descriptor discrete-time linear systems with bounded inputs by the use of Weierstrass-Kronecker decomposition is formulated and solved. Necessary and sufficient conditions for the positivity and reachability of descriptor discrete-time linear systems are given. Conditions for the existence of solution and procedure for computation of optimal input and the minimal value of the performance index is proposed and illustrated by a numerical example.
The relationship between internal response-based reliability and conditionality is investigated for Gauss-Markov (GM) models with uncorrelated observations. The models with design matrices of full rank and of incomplete rank are taken into consideration. The formulas based on the Singular Value Decomposition (SVD) of the design matrix are derived which clearly indicate that the investigated concepts are independent of each other. The methods are presented of constructing for a given design matrix the matrices equivalent with respect to internal response-based reliability as well as the matrices equivalent with respect to conditionality. To analyze conditionality of GM models, in general being inconsistent systems, a substitute for condition number commonly used in numerical linear algebra is developed, called a pseudo-condition^number. Also on the basis of the SVD a formula for external reliability is proposed, being the 2-norm of a vector of parameter distortions induced by minimal detectable error in a particular observation. For systems with equal nonzero singular values of the design matrix, the formula can be expressed in terms of the index of internal response-based reliability and the pseudo-condition^number. With these measures appearing in explicit form, the formula shows, although only for the above specific systems, the character of the impact of internal response-based reliability and conditionality of the model upon its external reliability. Proofs for complementary properties concerning the pseudo-condition^number and the 2-norm of parameter distortions in systems with minimal constraints are given in the Appendices. Numerical examples are provided to illustrate the theory.
This paper proposes an analytical model to describe the interaction of a bounded ultrasonic beam with an immersed plate. This model, based on the Gaussian beams decomposition, takes into account multiple reflections into the plate. It allows predicting three-dimensional spatial distributions of both transmitted and reflected fields. Thereby, it makes it easy to calculate the average pressure over the receiver’s area taking into account diffraction losses. So the acoustical parameters of the plate can be determined more accurately. A Green’s function for the interaction of an ultrasonic beam with the plate is derived. The obtained results are compared to those given by the angular spectrum approach. A good agreement is seen showing the validity of the proposed model.
Quantitative ultrasound has been widely used for tissue characterization. In this paper we propose a new approach for tissue compression assessment. The proposed method employs the relation between the tissue scatterers’ local spatial distribution and the resulting frequency power spectrum of the backscattered ultrasonic signal. We show that due to spatial distribution of the scatterers, the power spectrum exhibits characteristic variations. These variations can be extracted using the empirical mode decomposition and analyzed. Validation of our approach is performed by simulations and in-vitro experiments using a tissue sample under compression. The scatterers in the compressed tissue sample approach each other and consequently, the power spectrum of the backscattered signal is modified. We present how to assess this phenomenon with our method. The proposed in this paper approach is general and may provide useful information on tissue scattering properties.
The vapour pressure of most explosives is very low. Therefore, the explosive trace detection is very difficult. To overcome the problem, concentration units can be applied. At the Institute of Optoelectronics MUT, an explosive vapour concentration and decomposition unit to operate with an optoelectronic sensor of nitrogen dioxide has been developed. This unit provides an adsorption of explosive vapours from the analysed air and then their thermal decomposition. The thermal decomposition is mainly a chemical reaction, which consists in breaking up compounds into two or more simple compounds or elements. During the heating process most explosive particles, based on nitro aromatics and alkyl nitrate, release NO2 molecules and other products of pyrolysis. In this paper, the most common methods for the NO2 detection were presented. Also, an application of the concentration and decomposition unit in the NO2 optoelectronic sensor has been discussed.
Spectrophotometry is an analytical technique of increasing importance for the food industry, applied i.a. in the quantitative assessment of the composition of mixtures. Since the absorbance data acquired by means of a spectrophotometer are highly correlated, the problem of calibration of a spectrophotometric analyzer is, as a rule, numerically ill-conditioned, and advanced data-processing methods must be frequently applied to attain an acceptable level of measurement uncertainty. This paper contains a description of four algorithms for calibration of spectrophotometric analyzers, based on the singular value decomposition (SVD) of matrices, as well as the results of their comparison - in terms of measurement uncertainty and computational complexity - with a reference algorithm based on the estimator of ordinary least squares. The comparison is carried out using an extensive collection of semi-synthetic data representative of trinary mixtures of edible oils. The results of that comparison show the superiority of an algorithm of calibration based on the truncated SVD combined with a signal-to-noise ratio used as a criterion for the selection of regularisation parameters - with respect to other SVD-based algorithms of calibration.
Analysis of power consumption presents a very important issue for power distribution system operators. Some power system processes such as planning, demand forecasting, development, etc.., require a complete understanding of behaviour of power consumption for observed area, which requires appropriate techniques for analysis of available data. In this paper, two different time-frequency techniques are applied for analysis of hourly values of active and reactive power consumption from one real power distribution transformer substation in urban part of Sarajevo city. Using the continuous wavelet transform (CWT) with wavelet power spectrum and global wavelet spectrum some properties of analysed time series are determined. Then, empirical mode decomposition (EMD) and Hilbert-Huang Transform (HHT) are applied for the analyses of the same time series and the results showed that both applied approaches can provide very useful information about the behaviour of power consumption for observed time interval and different period (frequency) bands. Also it can be noticed that the results obtained by global wavelet spectrum and marginal Hilbert spectrum are very similar, thus confirming that both approaches could be used for identification of main properties of active and reactive power consumption time series.