Informatica

As a significant segment of the Information Industries, classified advertising can be a prime example of how conventional businesses, rather than being simply transplanted to the New (digital) Media, may indeed be transformed for future growth. To be successful, such transformations must be able to take full advantage of the defining features of the emerging information infrastructure for innovative creation of economic value. Focused Broadcasting, a class of service for matching classified and want ads using the World Wide Web, is an approach that balances the push-pull dynamics of information over the Internet. Applying the concept of product introduction with complementary network externalities, a dynamic model is formulated to simulate the potential growth of such business in cyberspace. Robustness of the model is demonstrated.

A new method for a creation of the information system for sequential identification of states of technological processes or other dynamic systems for their supervision and control is considered. The states of dynamic system can be unknown and can change themselves abruptly or slowly. The method is based on a sequential nonlinear mapping of many-dimensional vectors of parameters (collection of which describes the present state of dynamic systems) into two-dimensional vectors in order to reflect the states and their changes on the PC screen and to observe the situation by means of computer. The mapping error function is chosen and expressions for sequential nonlinear mapping are obtained. The mapping preserves the inner structure of distances among the vectors. Examples are given.

In the previous paper (Pupeikis, 1998), the problem of recursive estimation of the state of linear dynamic systems, described by an autoregressive model (AR), in the presence of time-varying outliers in observations to be processed has been considered. An approach to the robust recursive state estimation has been obtained and proved by estimating the real chemical process (Box and Jenkins, 1970). The aim of the given paper is the development of the abovementioned approach for the robust recursive state estimation of an autoregressive-moving average (ARMA) process in a case of additive noises with patchy outliers. The results of numerical simulation and the state estimation of the AR model (Figs. 1–4) and the real chemical process, described by the ARMA model, which is chosen from the same book of Box and Jenkins (Figs. 5–8) are given.

This paper deals with the study of the optimal control problem for the objective F(x,u,v)=∫^T0f(x(t),x(t−h),ζ(t),u(t),v(t),t)dt, with x∈X,u∈U,v∈V;X,U and V being vector spaces, and ζ(t)=∫^h0R(t,τ)x(t−τ)dτ subject to the differential equation $\frac{d}{dt}x(t)=m(x(t),x(t-h),\zeta(t),u(t),v(t),t)(0\leq t\leq T)$, and the constraints g1(u(t),t)∈S1,g2(v(t),t)∈S2;n1(x(t),t)∈V1,n2(x(t−h),t)∈V2;n3(ζ(t),t)∈V3(0≤t≤T), where x(t)∈Rⁿ;ζ(t)∈Rⁿ;u(t)∈R^k;f,m,gi(i=1,2),ni(1≤i≤3) and the entries to r(t,τ):R+×R+→L(X,X) are continuously differentiable functions. It is assumed that boundary conditions x(0)=x(T)=0 are imposed. Si(i=1;2) and Vi(1≤i≤3) are convex cones. The existence of a time-optimal control in analytic linear systems is also investigated via an extension of the bang-bang principle.

A general model for pair formation in age, sex, and sociologically structured interacting human communities is presented. More precisely, the religion factor is taken into account. The model describes dynamics of interacting religions which tolerate both uniconfessional pairs and those with different religions. Two particular models are analyzed. One of them describes the uniconfessional pairs dynamics and allows the religion change only for the sake of marriage. The other one demonstrates the evolution of communities forbidding any confession change. In the case of constant vital rates solutions of these two models are constructed and the longtime behavior of the total numbers of single adults and pairs of each community is demonstrated.