Now in most CASE tools the information collected during the stage of IS cycle analysis is not used to generate the models of the designing stage. Improving CASE systems it is offered to enlarge them with an activity knowledge basis, what becomes an additional source of information to generate project model. Activity knowledge model created in the department of data systems has been specified and activity setting system has been designed and realized during the work. System design has been conducted using programming appliances: Rational Rose Enterprise Edition 2002, Microsoft Visio Professional 2002. Use Case model generating algorithms has been created on the grounds of the activity basis. UCM models storage and software needed for its functioning have been worked out. CASE activity knowledge basis ordering system has been created on the grounds of the activity meta-model worked out in the department of data systems. Realized activity knowledge ordering system is used to extend traditional CASE systems functional possibilities. Realized CASE activity knowledge basis ordering system (Visual FoxPro 7.0) lets:  To input and adjust activity knowledge – activity elements described on the grounds of work model sequences activity procedures, activity functions, information flow, material flow and users;  To relate activity processes, activity functions, simulate their hierarchy structure;  To make accounts about the content of knowledge basis;  To generate users case... [to full text]

During the last decade, many baseline estimation methods have been proposed, but many of these approaches are either only useful for specific kinds of analytical signals or require the adjustment of many parameters. This complicates the selection of an appropriate approach for each kind of chemical signal and the optimization of multiple parameters itself is not an easy task. In this work, an asymmetric least squares (ALS) approach is used with truncated and augmented Fourier basis functions to provide a universal basis space for baseline approximation for diverse analytical signals. The proposed method does not require extensive parameter adjustment or prior baseline information. The basis set used to model the baselines includes a Fourier series truncated to low frequency sines and cosines (consistent with the number of channels) which is then augmented with lower frequencies. The number of basis functions employed depends mainly on the frequency characteristics of the baseline, which is the only parameter adjustment required for baseline estimation. The weighting factor for the asymmetric least squares in this case is dependent mainly on the level of the noise. The adjustment of these two parameters can be easily performed by visual inspection of results. To estimate and eliminate the baseline from the analytical signals, a novel algorithm, called Truncated Fourier Asymmetric Least Squares (TFALS) was successfully developed and optimized. It does not require baseline representative signals or extensive parameter adjustments. The method is described only with parameters optimization using simulated signals. The results with simulated and experimental data sets having different baseline artefacts show that TFALS is a versatile, effective and easy-to-use baseline removal method.

Neuroniniai tinklai ypatingi tuo, kad juos galima apmokyti. Radialinių bazinių funkcijų neuroniniai tinklai naudojami kaip aproksimavimo funkcijos atpažįstant objektus ir apdorojant signalus. Norint gerai vizualizuoti daugiamačius duomenis radialinių bazinių funkcijų neuroniniais tinklais, daug kas priklauso nuo to, kokie metodai bus parenkami geram rezultatui gauti ir į kokius duomenis atsižvegiant bus vizualizuojami analizuojami įėjimo duomenys (pavyzdžiui, pagal svorius, ar pagal bazinių funkcijų reikšmes). Darbe yra detaliai ištirti radialinių bazinių funkcijų (RBF) neuroniniai tinklai bei šio metodo galimybės duotiems taškams vizualizuoti. Darbo uždavinys — sukurti radialinių bazinių funkcijų neuroninių tinklų algoritmą daugiamačiams duomenims vizualizuoti. Tinklo apmokymui buvo parinkti efektyvūs metodai bazinės funkcijos parametrams rasti. Kompiuteriniams eksperimentams atlikti naudotas MATLAB programinis paketas. Atlikta algoritmo lyginamoji analizė pagal šiuos aspektus:  svorius;  bazinių funkcijų gautas reikšmes;  vizualų duomenų projekcijų įvertinimą. Radialinių bazinių funkcijų neuroninių tinklų efektyvumas labai priklauso nuo bazinių funkcijų centrų parinkimo. Darbe atskleistos naujos galimybės greitam daugiamačių duomenų vizualizavimui plokštumoje ir erdvėje. Tai sudaro pagrindą tolesniems tyrimams šioje duomenų analizės srityje. / Neural networks are special, because they can “learn“. Radial Basic Function Type Neural Networks are used as functions for approximation in object recognition and signal processing. When trying to achieve good visualization of data by using RBFN, a lot depends on the methods used to achieve this result and the data, used to visualize and analyze input data (e.g. by weight or by basic function values). This thesis contains detailed analysis of Radial Basic Function (RBF) neural networks and the possibilities of this method to visualize the given points. The task of this thesis is to explore the possibility of RBF application in visualization of multidimensional data. For network "education", the effective methods for finding basic function parameters were chosen. Computer experiments where conducted with MATLAB software. A comparative analysis of the algorithm was performed according to the following aspects:  weights;  values, obtained by basic functions;  visual evaluation of data projections. Efficiency of RBFN depends greatly on selection of the centers of basic functions. The research showed, that RBNF can be successfully applied in multidimensional data visualization. Thesis gives new possibilities for displaying multidimensional data on a plane and in space. This serves as a background for future researches in this field of data analysis.

This research develops a memory model capable of performing in a human-like fashion on a maze traversal task. The model is based on and retains the underlying ideas of Minerva 2 but is executed with different mathematical operations and with some added parameters and procedures that enable more capabilities. When applied to the same maze traversal task as was used in a previous experiment with human subjects, the performance of a maze traversal agent with the developed model as its memory emulated the error rates of the human data remarkably well. As well, the maze traversal agent and memory model successfully emulated the human data when it was divided into two groups: fast maze learners and slow maze learners. It was able to account for individual differences in performance, specifically, individual differences in the learning rate. Because forgetting was not applied and therefore all experiences were flawlessly encoded in memory, the model additionally demonstrates that error can be due to interference between memories rather than forgetting. / Thesis (Master, Computing) -- Queen's University, 2008-06-04 13:39:38.179

This thesis details a method of enumerating bases of hyperplane arrangements up to symmetries. I consider here automorphisms, geometric symmetries which leave the set of all points contained in the arrangement setwise invariant. The algorithm for basis enumeration described in this thesis is a backtracking search over the adjacency graph implied on the bases by minimum-ratio simplex pivots, pruning at bases symmetric to those already seen. This work extends Bremner, Sikiri c, and Sch urmann's method for basis enumeration of polyhedra up to symmetries, including a new pivoting rule for nding adjacent bases in arrangements, a method of computing automorphisms of arrangements which extends the method of Bremner et al. for computing automorphisms of polyhedra, and some associated changes to optimizations used in the previous work. I include results of tests on ACEnet clusters showing an order of magnitude speedup from the use of C++ in my implementation, an up to 3x speedup with a 6-core parallel variant of the algorithm, and positive results from other optimizations.

No description available.

2-connected outerplanar graphs have a unique minimal cycle basis with length 2|E|-|V|. They are the only Hamiltonian graphs with a cycle basis of this length. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

Existence of basis in locally convex space has been an important problem in functional analysis for more than 40 years. In this thesis the conditions for the existence of basis are examined. These thesis consist of three parts. The first part is about the exterior interpolative conditions. The second part deals with the inner interpolative conditions on nuclear frechet space. These are sufficient conditions on existence of basis. In the last part, it is shown that for a regular nuclear K&ouml / the space the inner interpolative conditions are satisfied and moreover another type of inner interpolative conditions are introduced.

No description available.

Zugl.: Dortmund, Univ., Diss., 2006