Informatica

The general concept of probabilistic argumentation systems PAS is restricted to the two types of variables: assumptions, which model the uncertain part of the knowledge, and propositions, which model the rest of the information. Here, we introduce a third kind into PAS: so-called decision variables. This new kind allows to describe the decisions a user can make to react on some state of the system. Such a decision allows then possibly to reach a certain goal state of the system. Further, we present an algorithm, which exploits the special structure of PAS with decision variables.

The design complexity of systems on a chip drives the need to reuse legacy or intellectual property cores, whose gate-level implementation details are unavailable. In this paper we consider the realization-independent testing and the impact of circuit realization on the fault coverage. We investigated two fault models (input-output pin pair fault and input-input-output pin triplet fault) that are used by test generation for circuits described at system description level. The test generation on the system-level model is preferable if the efforts and the duration of the test supplement activities are less than the efforts and the duration of the test generation on gate-level model. The test set for the black-box model is larger as compared to the test set for the particular realization of the circuit. However, large test sets for the black-box model can be compacted by analysis not only according to the stuck-at faults, but also according to various defects for the particular realization.

In 1995, Wu proposed a remote login authentication scheme based on geometric approach. However, Chien, Jan and Tseng presented a cryptanalysis of Wu’s scheme to show that it is not secure. Moreover, they proposed a modified version of Wu’s scheme. This paper presents there is a serious weakness in this modified remote login authentication scheme. We show that an illegal user can easily forge a valid login request in the modified version proposed previously.

In this paper we establish equivalence between a theory of fuzzy functional dependences and a fragment of fuzzy logic. We give away to interpret fuzzy functional dependences as formulas in fuzzy logic. This goal is realized in four steps. Truth assignment of attributes is defined in terms of closeness between two tuples in a fuzzy relation. A corresponding fuzzy formula is associated to a fuzzy functional dependence. It is proved that if a relation satisfies a fuzzy functional dependence, then the corresponding fuzzy formula is satisfied and vice verse. Finally, equivalence of a fuzzy formulas and a set fuzzy functional dependence is demonstrated. Thus we are in position to apply the rule of resolution from fuzzy logic, while calculating fuzzy functional dependences.

This paper discusses a soft sample clustering problem for multivariate independent random data satisfying the mixture model of the Gaussian distribution. The theory recommends to estimate the parameters of model by the maximum likelihood method and to use “plug-in” approach for data clustering. Unfortunately, the calculation problem of the maximum likelihood estimate is not completely solved in multivariate case. This work proposes a new constructive a few stage procedure to solve this task. This procedure includes statistical distribution analysis of a large number of the univariate projections of observations, geometric clustering of a multivariate sample and application of EM algorithm. The results of the accuracy analysis of the proposed methods is made by means of Monte-Carlo simulation.

The paper describes methods for generating image watermark for asymmetric key based watermark embedding and detection scheme in wavelet domain. The proposed method combines DWT-based watermarking and the ability to verify watermark using reliable methods of asymmetric coding. The watermark scheme is developed to be directly incorporated into JPEG2000 image coding standard, while it can be used in existing image coding standards. In presented watermarking method the application of public key infrastructure is emphasized. We use PGP (Pretty Good Privacy) public key management scheme as the element for verification of sender’s identity and also place of storing and retrieval of watermark detection keys. The most public key watermarking schemes use new, independent and cryptologically unverified keys. The reuse existing key verification and exchange infrastructure provides us cryptologically strong and verified keys.

Portfolio optimization is to find the stock portfolio minimizing the risk for a required return or maximizing the return for a given risk level. The seminal work in this field is the m ean-variance model formulated as a quadratic programming problem. Since it is not computationally practical to solve the original model directly, a number of alternative models have been proposed.

When handling engineering problems associated with optimal alternative selection a researcher often deals with not sufficiently accurate data. The alternatives are usually assessed by applying several different criteria. A method takes advantage of the relationship between fuzzy sets and matrix game theories can be offered for multicriteria decision-making. Practical investigations have already been discussed for selecting the variants water supply systems.

Verifiable encryption is a primitive that can be used to build extremely efficient fair exchange protocols where the items exchanged represent digital signatures. Such protocols may be used to digitally sign contracts on the Internet. This paper presents an efficient protocol for verifiable encryption of digital signatures that improves the security and efficiency of the verifiable encryption scheme of Ateniese. Our protocol can be applied to group signatures, key escrow and publicly verifiable secret and signature sharing to prove the fairness.

The aim of the given paper is the development of an approach for parametric identification of Wiener systems with piecewise linear nonlinearities, i.e., when the linear part with unknown parameters is followed by a saturation-like function with unknown slopes. It is shown here that by a simple data reordering and by a following data partition the problem of identification of a nonlinear Wiener system could be reduced to a linear parametric estimation problem. Afterwards, estimates of the unknown parameters of linear regression models are calculated by processing respective particles of input-output data. A technique based on ordinary least squares (LS) is proposed here for the estimation of parameters of linear and nonlinear parts of the Wiener system, including the unknown threshold of piecewise nonlinearity, too. The results of numerical simulation and identification obtained by processing observations of input-output signals of a discrete-time Wiener system with a piecewise nonlinearity by computer are given.