Informatica

The model of the HIV/AIDS infection spread is proposed and investigated. The paper deals with some specific features of the disease spread at the initial stage, i.e., when the infection extent is small enough. We propose a model characterizing any risk group by three differential equations. These equations describe the dynamics of active susceptible, active infected, and passive infected individuals. The evaluation of parameters from demographical and medical data is discussed. The package for the investigation of infection is presented, and possibilities to control the infection are shown. Two general directions of control may be distinguished: the HIV/AIDS blood tests and the publicity and availability of protective means. The investigations showed under what conditions the HIV/AIDS infection may be stopped.

The binary logic functions “excitation and/or noninhibition” and “excitation and noninhibition” are realized by the model of a nonlinear stationary dendritic branch. The neuron with such dendrites is a complex logic system performing a great member of elementary logic operations.

In this paper, we discuss computational aspects of an interior-point algorithm [1] for indefinite quadratic programming problems with box constraints. The algorithm finds a local minimizer by successively solving indefinite quadratic problems with an ellipsoid constraint. In addition, we present a sufficient condition for a local minimizer to be global, and we use this result to generate test problems with a known global solution. The proposed algorithm has been implemented on an IBM 3090 computer and tested on a variety of dense test problems, including problems with a known global optimizer.

It is well known that many practical optimization problems with random elements lead from the mathematical point of view to deterministic optimization problems depending on the random elements through probability laws only. Further, it is also well known that these probability laws are known very seldom. Consequently, statistical estimates of the unknown probability measure, if they exist, must be employed to obtain some estimates of the optimal value and the optimal solution, at least.

In this paper, we present a new local search algorithm for solving the Quadratic Assignment Problem based on the Kernighan-Lin heuristic for the Graph Partitioning Problem. We also prove that finding a local optimum for the Quadratic Assignment Problem, with the neighborhood structure defined in the algorithm, is PLS-complete. The greatest advantages of the algorithm are its simplicity and speed in generating high quality solutions. The algorithm has been implemented and tested on an IBM 3090 computer with a variety of test problems of dimensions up to 100, including many test problems available in the literature and a new set of test problems with known optimal permutations.

The main approach to improve the computer performance by enhancing the operating speed of transistors, used in modern computer technology, are reviewed. The qualitative enhance of the transistor operating speed could be realized by using semiconductor materials with the higher than in silicon electron mobility (such as GaAs, InGaAs) and by decreasing the size of transistors until nanometric dimensions. That opens the way to design computers with the operating speed larger than 10 billion operations per second.

In the previous papers (Pupeikis, 1990; 1991; 1992) the problems of model oder determination and recursive estimation of dynamic systems parameters in the presence of outliers in observations have been considered. The aim of the given paper is the development, in such a case, of classical off-line algorithms for systems of unknown parameters estimation using batch processing of the stored data. An approach, based on a substitution of the corresponding values of the sample covariance and cross-covariance functions by their robust analogues in respective matrices and on a further application of the least square (LS) parameter estimation algorithm, is worked out. The results of numerical simulation by IBM PC/AT (Table 1, 2) are given.

The basic properties and methods of developing max-min and max-Δ transitive approximations of resemblance matrices of observed objects are reviewed. A new algorithm of constructing max-Δ transitive closure of such matrices is presented. The conditions of applications of the max-min and max-Δ transitive measures of similarity are considered.