Use of continuous solid-phase synthesis to obtain phosphors based on strontium aluminate

The effect of conditions of continuous solid-phase synthesis on particle size distribution of nanostructured powders of strontium aluminate was studied. It was shown that continuous solid-phase synthesis allows for: synthesis of strontium aluminate in the form of nanostructured powders with controlled particle size distribution directly during its synthesis; in the presence of a liquid phase strontium aluminate is synthesized with a high level of monophasity. It was shown that in order to optimize the illuminating parameters of phosphors based on strontium aluminate, it is advisable to use continuous solid-phase synthesis

On the Complexity of Query Result Diversification

Query result diversification is a bi-criteria optimization problem for ranking query results. Given a database D, a query Q and a positive integer k, it is to find a set of k tuples from Q(D) such that the tuples are as relevant as possible to the query, and at the same time, as diverse as possible to each other. Subsets of Q(D) are ranked by an objective function defined in terms of relevance and diversity. Query result diversification has found a variety of applications in databases, information retrieval and operations research. This paper studies the complexity of result diversification for relational queries. We identify three problems in connection with query result diversification, to determine whether there exists a set of k tuples that is ranked above a bound with respect to relevance and diversity, to assess the rank of a given k-element set, and to count how many k-element sets are ranked above a given bound. We study these problems for a variety of query languages and for three objective functions. We establish the upper and lower bounds of these problems, all matching, for both combined complexity and data complexity. We also investigate several special settings of these problems, identifying tractable cases. 1

Conceptual basis for developing of trainig models in complex system software assembling generator

This paper presents conceptual basis for developing of training models of interactive assembling system for automatic building of application software systems, obtained during practical works over "Design and architecture of software systems" and "Object-oriented analysis and design" courses. The system is intended for practical demonstration of basic stages and operations in development of complex and critical software. This also includes a consideration of solutions for some substantial problems of complex systems software generation, such as: program module compatibility, formalization of computer interaction and choosing of formal model for human machine interface. In addition, several training model implementations are provided.Keywords: software generator, training models, interactive system

Analysis of process flexibility designs under disruptions

Most previous studies concerning process flexibility designs have focused on expected sales and demand uncertainty. In this paper, we examine the worst-case performance of flexibility designs in the case of demand and supply uncertainties, where the latter can be in the form of either plant or arc disruptions. We define the Plant Cover Index under Disruptions (PCID) as the minimum required plants’ capacity to supply a fixed number of products after the disruptions. By exploiting PCID, we establish that under symmetric uncertainty sets the worst-case performance can be expressed in terms of PCID, supply and demand uncertainties. Additionally, PCID enables us to make meaningful comparisons of different designs. In particular, we demonstrate that under disruptions the 2-long chain design is superior to a broad class of designs. Moreover, we identify a condition wherein both Q-short and Q-long chain designs have the same worst-case performance. We also discuss the notion of fragility that quantifies the impact of disruptions in the worst case and compare fragilities of Q-short and Q-long chain designs under different types of disruptions. Finally, by employing PCID, we develop an algorithm to generate designs that perform well under supply and demand uncertainties in both the worst case and in expectation

An Assessment of the Economic Performance of the EU Baltic Region States

The paper explores how the common economic space, a product of the EU, influenced the economies of the Baltic Sea Region states in 1995-2015. The authors investigate changes in the economic performance of the developed (Germany, Denmark, Finland, and Sweden) and Eastern European countries (Poland, Latvia, Lithuania, Estonia) during the integration of the latter states into the EU. Performance dynamics is analyzed for eight EU Baltic Sea Region countries. Three Russian Baltic regions constitute a control group. The authors conduct a production-function-based comparative analysis of development dynamics in individual countries to identify distinctive features for each group. Despite a rapid growth of Eastern European economies, the difference between the region’s eastern and western countries remains substantial. Economic convergence between eastern and western EU countries in terms of investment does not lead to convergence in labour efficiency. The capital-labour ratio and the growth rate of labour efficiency in the Russian Baltic are close to the Eastern European average

Control of Symetry by Lyapunov Exponents

In this paper we describe control systems with local and global symmetry. Recent results in control theory have demonstrated that control can lead to symmetry breaking in chaotic systems with a simple type of symmetry. In our work we analyze controllability of Lyapunov exponents using continuous control functions. We show that, by controlling Lyapunov exponents, a chaotic attractor lying in some invariant subspace can be made unstable with respect to perturbations transverse to the invariant subspace. Furthermore, a symmetry-increasing bifurcation can occur, after which the attractor possesses the system symmetry. We demonstrate control of local Lyapunov exponents for the control of symmetry in nonlinear dynamical systems. We also study the effect of noise in the system. It is shown that the small-amplitude noise can restore the symmetry in the attractor after the bifurcation and that the average time for trajectories to switch between the symmetry-broken components of the attractor scales algebraically with the noise amplitude. We demonstrate the relation between Lyapunov exponents, order parameters (Haken, 1983, 1988) and symmetry using a simple physical system and discuss the applicability of our approach to the study of state transitions in the epileptic brain.Дослідження останніх років у галузі систем керування показують, що зовнішні збурення можуть призводити до порушення симетрії в системах з хаотичною динамікою з певним типом симетрії. В роботі проаналізовано можливість керування показниками Ліяпунова за допомогою неперервного зовнішнього впливу. Показано, що хаотичний атрактор може стати нестабільним по відношенню до трансверсальних до інваріантного підпростору збурень. При цьому можуть виникати біфуркації, після яких утворюється нова симетрія атрактора. Ми також: показуємо існування співвідношення між: показниками Ляпунова, параметрами порядку (Хакен, 1983, 1988) та симетрією на прикладі простої фізичної системи. Обговорюється можливість використання нашого підходу до вивчення перехідних режимів в епілептичному головному мозку

Genetic algorithm of network graph multi-objective optimization as an instrument of project monitoring

© 2015 Canadian Center of Science and Education. All rights reserved. Proper tracking of progress remains a vital part of modern project management, defining prospects of successful implementation of planned tasks. There are several popular concepts of project monitoring, such as logical framework approach (LFA), earned value management (EVM), etc., and each of them depends on properly optimized network graph that represents dependences between project tasks. Article describes the features and problems of multi-objective optimization in project management with reference to network graphs. The significant role of network graph optimization for project monitoring systems is proved and the model of multi-objective optimization of the network graph on criterion functions of duration and project cost based on NSGA-II genetic algorithm is proposed as the main purpose of research. Model takes into account the reserves of time on a critical way of the network graph, possibility of decreasing the load of available resources at the expense of time reserves on non-critical ways of the network graph, variety of used resources and options of delegation. One of its main advantages is quite low laboriousness of implementation, that depends on number of nodes on the network graph of the project and on number of possible options of delegation for the project tasks with several alternatives of delegation. Model has been tested on sample project with real data and results have been analyzed

Solving a class of feature selection problems via fractional 0–1 programming

Feature selection is a fundamental preprocessing step for many machine learning and pattern recognition systems. Notably, some mutual-information-based and correlation-based feature selection problems can be formulated as fractional programs with a single ratio of polynomial 0–1 functions. In this paper, we study approaches that ensure globally optimal solutions for these feature selection problems. We conduct computational experiments with several real datasets and report encouraging results. The considered solution methods perform well for medium- and reasonably large-sized datasets, where the existing mixed-integer linear programs from the literature fail

Fractional 0–1 programming and submodularity

In this note we study multiple-ratio fractional 0–1 programs, a broad class of NP-hard combinatorial optimization problems. In particular, under some relatively mild assumptions we provide a complete characterization of the conditions, which ensure that a single-ratio function is submodular. Then we illustrate our theoretical results with the assortment optimization and facility location problems, and discuss practical situations that guarantee submodularity in the considered application settings. In such cases, near-optimal solutions for multiple-ratio fractional 0–1 programs can be found via simple greedy algorithms