Неопределенность и риски инвестиционных проектов
The Asia-Pacific region is of growing importance for both the United States and Russia, each of which seeks to “pivot” or “rebalance” its global commitments toward Asia. Yet the focus of U.S.-Russia relations remains on Europe and the former Soviet Union, and neither country has paid sufficient attention to the implications of their respective Asian pivots for the bilateral relationship. Since U.S.-Russia relations in Asia and the Pacific remain underdeveloped, the region holds the potential to act as a sort of laboratory for trying out new mechanisms for bilateral and multilateral cooperation.
Both countries are turning to Asia primarily to benefit from Asia’s economic dynamism. At the same time, they recognize that Asia’s growth is imperiled by a range of traditional and nontraditional security threats, from the nuclear-tipped standoff on the Korean Peninsula to territorial disputes in the East China Sea and South China Sea to terrorism, climate change, migration, and other transnational challenges. Among the most important drivers of change in Asia is the continued rise of China, which is in different ways a critical partner for both Washington and Moscow.
Because Asia’s economic and security landscape remains in flux and the legacies of mistrust hanging over U.S.-Russia relations in Europe are less pronounced, Moscow and Washington have an opportunity to build more effective forms of cooperation from the ground up. This will require efforts from both sides. The United States must reconcile cooperation with Russia with its existing commitments, including long-standing alliance relationships and growing security cooperation with several states in the region. Russia’s challenge lies mainly in convincing states and regional institutions that it is an important player in the region—which in turn requires it to more fully integrate Siberia and the Russian Far East into Asia’s regional economy—and more than a regional satellite of China.
Supply chain management is rather new scientific field that reflects the concept of integrated business planning. This concept should be experts and practitioners in logistics and strategic management. Today, integrated planning to become a reality thanks to the development of information technology and computer technology. At the same time to achieve a competitive advantage is not enough high-speed, low-cost data transfer process. In order to effectively apply information technology tools necessary to develop a quantitative analysis of the effectiveness of supply chain management. The mam element of this tool are optimization models that reveal the complex interactions, the wave and the synergies that arise in supply chain management. In this article we consider one of the classes of such models - the so-called dynamic models of conveyor systems, processing of applications.
Uncertainty is a concept associated with data acquisition and analysis, usually appearing in the form of noise or measure error, often due to some technological constraint. In supervised learning, uncertainty affects classification accuracy and yields low quality solutions. For this reason, it is essential to develop machine learning algorithms able to handle efficiently data with imprecision. In this paper we study this problem from a robust optimization perspective. We consider a supervised learning algorithm based on generalized eigenvalues and we provide a robust counterpart formulation and solution in case of ellipsoidal uncertainty sets. We demonstrate the performance of the proposed robust scheme on artificial and benchmark datasets from University of California Irvine (UCI) machine learning repository and we compare results against a robust implementation of Support Vector Machines.
The report is devoted to comprehensive research in the field of strategic planning, logistics infrastructure in to ensure the implementation of export-import and transit potential of Russia in the global system of international transport corridors (ITC). Particularly attention spares to the place and the role of the Russian Transportations Ministry and the Russian Rail-way joint stock company in the investment projects realization, also to the problems of the logistics infrastructure development in sea ports and multimodal transport junctions for example North-East and Moscow regions.
Flexible goal-directed behavior in cognitive tasks relies on multiple task-specific processes, as well as on functioning of the monitoring system. In multiple-choice tasks, the task-specific processes include sensory evidence integration and action selection that partially occur in the lateral intraparietal area (LIP). The performance monitoring system is located in the medial frontal regions of the cortex. Activation of this system is associated with increased frontal midline theta (FMT) power, and increased theta coherence between midfrontal areas and the task-specific areas. One of the situations that require the increase of cognitive control is receiving a negative feedback after an erroneous response. There are two possible types of errors. One of them originates from failures in task-specific processes and is associated with increased response times with high outcome uncertainty; the other is related to failures of non-specific motor inhibition and is characterized by decreased response times with low levels of outcome uncertainty. In the present study, we aimed to investigate whether post-feedback activity of the performance monitoring system depends on the type of committed errors. We recorded EEG while subjects performed an auditory version of the two-choice condensation task, in which both types of errors described above could occur. In the time window between the stimulus and the response, we observed significant decrease of alpha power in the left central-parietal sites (compared to the baseline), which presumably reflects the task-specific activation of the LIP area. Higher frontal midline theta (FMT) power and theta-band coherence with left parietal electrodes were observed after negative feedback, compared to positive one, reflecting error detection by medial frontal structures and their interaction with the LIP aimed to prevent future errors, respectively. Furthermore, the difference in theta coherence and the mean response time ratio between erroneous and correct responses were positively correlated, i.e. subjects that tended to commit slow errors demonstrated stronger increase of theta coherence after negative feedback. These findings support the idea that slow errors are associated with high outcome uncertainty, and the feedback information in this case is used to a greater degree in the processes aimed at performing post-error adaptations.
Into the Red explores the emergence of a credit card market in post-Soviet Russia during the formative period from 1988 to 2007. In her analysis, Alya Guseva locates the dynamics of market building in the social structure, specifically the creative use of social networks. Until now, network scholars have overlooked the role that networks play in facilitating exchange in mass markets because they have exclusively focused on firm-to-firm or person-to-person ties. Into the Reddemonstrates how networks that combine individuals and organizations help to build markets for mass consumption. The book is situated on the cutting edge of emerging interdisciplinary research, linking multiple layers of analysis with institutional evolution. Using an intricate framework, Guseva chronicles both the creation of a credit card market and the making of a mass consumer. These processes are placed in the context of the ongoing restructuring in postcommunist Russia and the expansion of Western markets and ideologies through the rest of the world.