Minimal forbidden subwords

Motivated by a study of similar problems stated for factors of words, we study forbidden subwords of a language or a word. A procedure for obtaining the set of all words avoiding a given set of subwords is presented. On the other hand, an algorithm for computing the set of minimal forbidden subwords for a word is given. The case of a two-letter alphabet appears to be particularly interesting and it is considered separately.     

Adaptive output-feedback stabilization of non-local hyperbolic PDEs

We address the problem of adaptive output-feedback stabilization of general first-order hyperbolic partial integro-differential equations (PIDE). Such systems are also referred to as PDEs with non-local (in space) terms. We apply control at one boundary, take measurements on the other boundary, and allow the system’s functional coefficients to be unknown. To deal with the absence of both full-state measurement and parameter knowledge, we introduce a pre-transformation (which happens to be based on backstepping) of the system into an observer canonical form. In that form, the problem of adaptive observer design becomes tractable. Both the parameter estimator and the control law employ only the input and output signals (and their histories over one unit of time). Prior to presenting the adaptive design, we present the non-adaptive/baseline controller, which is novel in its own right and facilitates the understanding of the more complex, adaptive system. The parameter estimator is of the gradient type, based on a parametric model in the form of an integral equation relating delayed values of the input and output. For the closed-loop system we establish boundedness of all signals, pointwise in space and time, and convergence of the PDE state to zero pointwise in space. We illustrate our result with a simulation.     

Unscented Kalman filter with advanced adaptation of scaling parameter

The paper deals with state estimation of the nonlinear stochastic systems by means of the unscented Kalman filter with a focus on specification of the σ$\sigma$-points. Their position is influenced by two design parameters—the scaling parameter determining the spread of the σ$\sigma$-points and a covariance matrix decomposition determining rotation of the σ$\sigma$-points. In this paper, a choice of the scaling parameter is analyzed. It is shown that considering other values than the standard choice may lead to increased quality of the estimate, especially if the scaling parameter is adapted. Several different criteria for the adaptation are proposed and techniques to reduce computational costs of the adaptation are developed. The proposed algorithm of the unscented Kalman filter with advanced adaptation of the scaling parameter is illustrated in a numerical example.     

Water soluble acrylamide polymers, 2. Aging and viscous flow of aqueous solutions of polyacrylamide and hydrolyzed polyacrylamide

The aging of aqueous solutions of polyacrylamide which appears experimentally as a decrease of solution viscosity and which is probably caused by microorganisms may be prevented by the addition of a small amount (0.02 wt.-%) of an antimicrobial agent such as sodium azide. Aluminium chloride causes a very strong decrease of the viscosity during a prolongated storing time. The addition of aluminium ions to the polymer solution leads to a complexing of amidic groups with aluminium cations and probably also to decrease of the dimensions of individual polymer coils. The viscous flow of aqueous solutions of polyacrylamide and hydrolyzed polyacrylamides was studied as a dependence of the shear gradient D on the shear stress τ and was described by the relation D = k · τⁿ, where k and n denote constants. Both constants depend on the polymer concentration, the degree of polymerization and the content of carboxylic groups in the polymer. The greatest deviations from the Newtonian behaviour were found in the range of molecular weights over 2 · 10⁶ g/mol and practically no deviations were observed for polyacrylamide with molecular weights below 1 · 10⁶ g/mol. The dependence of the viscosity on the shearing time at different shear rates (300, 600 and 1200 s^?1) which was observed in solutions of polyacrylamide, hydrolyzed polyacrylamide and poly-(N,N-dimethyl)-acrylamide was explained by an entanglement model.     

Influence of anionic form on thermooxidation of TMAHP–cellulose

With the help of DTA, DTG elementary analysis of carbonized residues and ESR spectroscopy the influence of anionic form on thermooxidation of trimethylammoniumhydroxyprophyl (TMAHP)–cellulose was studied. At 300°C the percentage of carbon in carbonized residue thermolyzed in oxidative atmosphere is higher than for the sample degraded in inert atmosphere. The percentage of hydrogen decreases simultaneously. The concentration of free radicals in thermolyzed residue also increases due to the presence of oxygen. We propose that oxygen is abstracting the hydrogen atoms from polysaccharide and unpaired electrons on carbon atoms are produced. At 400°C the percentage of carbon in residues prepared at inert atmosphere is higher than for residue formed at oxidative atmosphere. Also the concentration of free radicals in thermolyzed residues obtained in inert atmosphere is greater than for those from oxidative ones. That is why suppose that at this temperature oxygen is bonded to polysaccharide residue and free radicals are terminated. From the semiquantitative DTA we can make the following sequence of samples according to their increasing thermooxidative effect: unmodified cellulose < A–HSO < A–Br^? < A–I^? < A–NO < A–H₂PO < A–CH₃COO^? < A–HCO < A–F^? < A–Cl^?1 < A–OH^p?.     

Predicting Missing Items in Shopping Carts

Existing research in association mining has focused mainly on how to expedite the search for frequently co-occurring groups of items in “shopping cart” type of transactions; less attention has been paid to methods that exploit these “frequent itemsets” for prediction purposes. This paper contributes to the latter task by proposing a technique that uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy. Using the recently proposed data structure of itemset trees (IT-trees), we obtain, in a computationally efficient manner, all rules whose antecedents contain at least one item from the incomplete shopping cart. Then, we combine these rules by uncertainty processing techniques, including the classical Bayesian decision theory and a new algorithm based on the Dempster-Shafer (DS) theory of evidence combination.     

Stochastic source seeking for nonholonomic unicycle

We apply the recently introduced method of stochastic extremum seeking to navigate a nonholonomic unicycle towards the maximum of an unknown, spatially distributed signal field, using only the measurement of the signal at the vehicle’s location but without the measurement of the vehicle’s position. Keeping the forward velocity constant and controlling only the angular velocity, we design a stochastic source seeking control law which employs excitation based on filtered white noise, rather than sinusoidal perturbations used in the existing work. We study stability with the help of stochastic averaging theorems that we recently developed for general nonlinear continuous-time systems with stochastic perturbations. We prove local exponential convergence, both almost surely and in probability, to a small neighborhood near the source. We characterize the convergence speed explicitly and provide design guidelines for maximizing it, as well as for minimizing the residual set near the source. We present a detailed simulation study, including a study of the effect of saturation on the steering input.     

Virtual Mechatronic/Robotic laboratory – A step further in distance learning

The implementation of the distance learning and e-learning in technical disciplines (like Mechanical and Electrical Engineering) is still far behind the grown practice in narrative disciplines (like Economy, management, etc.). This comes out from the fact that education in technical disciplines inevitably involves laboratory exercises and this fact drastically increases the complexity of a potential e-learning system. New approach and new specific knowledge are needed to develop such a system. We expect to meet the requirements of distance learning by developing the software-based laboratory exercises, i.e., a virtual laboratory. To fully substitute a physical system like laboratory equipment, one must emulate its full dynamics. The mathematical model in the form of differential equations will be applied to calculate dynamics and provide the data that would otherwise be measured on a physical system – this means simulation.     

Active fault detection and control: Unified formulation and optimal design

A new unified formulation of the active fault detection and control problem for discrete-time stochastic systems and its optimal solution are proposed. The problem formulation stems from the optimal stochastic control problem and includes important special cases: an active detector and controller, an active detector and input signal generator, and an active detector with a given input signal generator. The optimal solution is derived using the so-called closed loop information processing strategy. This strategy respects the influence of the current decision and/or input on the future behavior of the observed system, allows penalizing future wrong decisions, and improves the quality of fault detection. The proposed formulation and obtained solution also provide better understanding of the active fault detection and its relation to the optimal stochastic control. The results are illustrated in numerical examples.     

Library of sophisticated functions for analysis of nuclear spectra

In the paper we present compact library for analysis of nuclear spectra. The library consists of sophisticated functions for background elimination, smoothing, peak searching, deconvolution, and peak fitting. The functions can process one- and two-dimensional spectra. The software described in the paper comprises a number of conventional as well as newly developed methods needed to analyze experimental data.

Program summary

Program title: SpecAnalysLib 1.1Catalogue identifier: AEDZ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDZ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 42 154No. of bytes in distributed program, including test data, etc.: 2 379 437Distribution format: tar.gzProgramming language: C++Computer: Pentium 3 PC 2.4 GHz or higher, Borland C++ Builder v. 6. A precompiled Windows version is included in the distribution packageOperating system: Windows 32 bit versionsRAM: 10 MBWord size: 32 bitsClassification: 17.6Nature of problem: The demand for advanced highly effective experimental data analysis functions is enormous. The library package represents one approach to give the physicists the possibility to use the advanced routines simply by calling them from their own programs. SpecAnalysLib is a collection of functions for analysis of one- and two-parameter γ-ray spectra, but they can be used for other types of data as well. The library consists of sophisticated functions for background elimination, smoothing, peak searching, deconvolution, and peak fitting.Solution method: The algorithms of background estimation are based on Sensitive Non-linear Iterative Peak (SNIP) clipping algorithm. The smoothing algorithms are based on the convolution of the original data with several types of filters and algorithms based on discrete Markov chains. The peak searching algorithms use the smoothed second differences and they can search for peaks of general form. The deconvolution (decomposition - unfolding) functions use the Gold iterative algorithm, its improved high resolution version and Richardson-Lucy algorithm. In the algorithms of peak fitting we have implemented two approaches. The first one is based on the algorithm without matrix inversion - AWMI algorithm. It allows it to fit large blocks of data and large number of parameters. The other one is based on the calculation of the system of linear equations using Stiefel-Hestens method. It converges faster than the AWMI, however it is not suitable for fitting large number of parameters.Restrictions: Dimensionality of the analyzed data is limited to two.Unusual features: Dynamically loadable library (DLL) of processing functions users can call from their own programs.Running time: Most processing routines execute interactively or in a few seconds. Computationally intensive routines (deconvolution, fitting) execute longer, depending on the number of iterations specified and volume of the processed data.