This paper introduces a constructive approach to online social networks analysis. We suggest a conceptual model of a social network, formulate major problems of analysis and control in social networks, describe methods and algorithms for activity analysis in social networks, as well as technologies for social networks monitoring and analysis.

The problem of selection the most informative features is reduced to an optimization problem for the average risk functional whose maximization is equivalent to maximization of informational distance between distributions of features in two classes. We consider a maximization procedure for the average risk functional via empirical risk, estimating the divergence between them, with Rademacher complexity. The proposed method has been applied efficiently to problems of selection parameters important to separate the states of technological processes. We show an experimental comparison of the developed approach with other widely known feature selection techniques.

Обобщаются результаты недавних публикаций о предсказании неизвестного максимума процесса на случай экспоненциального семимартингала, логарифм которого представим в виде суммы локальных мартингалов и положительного сноса. Полученные в статье результаты охватывают широкий круг моделей, включая многофакторные. Результаты могут быть применены к задачам редуцирования рисков.

Аналитически решена задача удара цепочки связанных материальных точек, обладающей вязко-упругими свойствами о неподвижное препятствие. Найдены условия окончания фазы удара, получен аналитический вид нагрузки на препятствие со стороны цепочки, осуществлен предельный переход к вязко-упругому стержню.

Consideration was given to the classical NP-hard problem 1|r_j |Lmax of the scheduling theory. An algorithm to determine the optimal schedule of processing n jobs where the job parameters satisfy a system of linear constraints was presented. The polynomially solvable area of the problem 1|r_j |Lmax was expanded. An algorithm was described to construct a Pareto-optimal set of schedules by the criteria Lmax and Cmax for complexity of O(n^3 log n) operations.