Проблематика целевой ориентации деятельности организации
The problem of recognition of a sequence of objects (e.g., video-based image recognition, phoneme recognition) is explored. The generalization of the fuzzy phonetic decoding method is proposed by assuming the distribution of the classified object to be of exponential type. Its preliminary phase includes association of each model object with the fuzzy set of model classes with grades of membership defined as the confusion probabilities estimated with the Kullback-Leibler divergence between model distributions. At first, each object (e.g., frame) in a classified sequence is put in correspondence with the fuzzy set which grades are defined as the posterior probabilities. Next, this fuzzy set is intersected with the fuzzy set corresponding to the nearest neighbor. Finally, the arithmetic mean of these fuzzy intersections is assigned to the decision for the whole sequence. In this paper we propose not to limit the method's usage with the Kullback-Leibler discrimination and to estimate the grades of membership of models and query objects based on an arbitrary distance with appropriate scale factor. The experimental results in the problem of isolated Russian vowel phonemes and words recognition for state-of-the-art measures of similarity are presented. It is shown that the correct choice of the scale parameter can significantly increase the recognition accuracy.
Over the past decade Russia has experienced stable economic growth with Gross Domestic Product (GDP) growing by 7 percent per year from 1998 to 2007. While the nation still enjoys a relatively healthy growth rate, analysis shows that the sources for the future growth are limited and to boost growth Russia should rely on increasing labor productivity. Improving productivity will impose new demands on Russia's workforce requiring better skills to satisfy the needs of economy growth. The international business environment survey reports that Russia's private sector considers the lack of skills and education of workers to be the most severe constraint on its expansion and growth. Despite the very high level of formal education attained by Russian workers the problem behind this may be explained by the current quality and content of education, which does not develop the necessary skills and competences demanded by the labor market. This report examines the reasons and the consequences of this skills deficit, which constrain productivity and limits innovation ultimately stifling accelerated economic growth in Russia. The objectives of the report are: 1) to deepen the understanding of the structure and composition of this skills deficit by analyzing in detail the demand for and supply of particular cognitive and non-cognitive skills; 2) to review the capacity and problems of the current systems for skills provision in Russia both through the public and private provision thereby identifying some of the underlying reasons for this skills gap; and 3) to support the development of evidence-based policy making in professional education and training, which will lead to a system better responding to the challenges of the economy and labor market.
In this paper, we consider the following problem - what affects the amount of investment in knowledge when one of the network firms enters another innovation network. The solution of this problem will allow us to understand exactly how innovative companies will behave when deciding whether to enter the innovation network of another country or region, what conditions affect it and how the level of future investments in knowledge can be predicted.