Global climate change entails both threats and new opportunities for social and economic development of the Altai-Sayan Ecoregion. Taking into account the scale of climate change forecasted for the ASE, the importance of Altai-Sayan as one of the world’s biodiversity hotspots as well as an important role assigned to the region in strategic plans of Russia’s economic development, the need to develop regional measures of adaptation to both negative and positive impacts of climate change raises no doubts. In particular, climate change is referred to as a new determinant of development and a security challenge to Russia and its regions in such strategic documents as: the RF Environmental Doctrine (2002), the RF Long-Term Social and Economic Development Concept for the period to 2020 (2008), the RF Forest Complex Development Strategy for the period to 2020 (2008), the RF National Security Strategy for the period to 2020 (2009), the RF Climate Doctrine (2009), the Energy Strategy of Russia for the period to 2030 (2009), the RF Food Safety Doctrine (2010) and the Strategy of Social and Economic Development of Siberia for the period to 2020 (2010).
The paper presents the result of the research of the inuence of text font size on attention indicators. On the basis of the experimental data, the multiple linear regression of the dependence of the optimum of the font size on the criterion of maximizing the value of mental efficiency indicator from the indicators of attention and memory of the subject was constructed. An algorithm for adapting the font size of text for optimal perception is presented.
The article is about adaptation of immigrant children, adolescents, and their families
According to UN estimates for 2015, the Russian Federation is the world’s third-leading country in terms of the number of immigrants, after the US and Germany. Central Asian countries account for most of the inflow of migration. The purpose is to investigate the relationships between the strategies of acculturation, ethnic, religious, country of origin, Russian national identities and the sociocultural and psychological adaptation of migrants from Central Asia in Moscow region. Representatives of two ethnic groups - 105 Uzbeks and 96 Tajiks (N = 201) - participated in the research. The methods of the study include the scales of acculturation strategies, social identities, life satisfaction, self-esteem, and sociocultural adaptation from the MIRIPS (Mutual Intercultural Relations in Plural Societies) project questionnaire. The results of path analysis conducted in AMOS program showed that integration and assimilation are the best strategies for migrants from Central Asia: integration predicts self-esteem; assimilation predicts their life satisfaction. The preference for integration strategy is positively associated with ethnic and Russian national identities, the preference for assimilation strategy is positively associated with Russian national and religious identities and negatively associated with ethnic identity. Separation and marginalization do not contribute to self-esteem of the migrants. Marginalization is positively related to religious identity; separation is positively related to ethnic, religious, country of origin identities, and negatively related to Russian national identity. Also we found that social identities had a mediational role in the influence of acculturation strategies on the adaptation of migrants from Central Asia in the Moscow region.
The article was devoted the analysis adaptation strategies of the Roman Catholic and Russian Orthodox Churches to the new social and political conditions in the last decades. The author comes to the conclusion that Russian Orthodox Church chooses strategy of conservation to the new social and political conditions and Roman Catholic Church makes decision to follow democratic adaptation strategies.
In this article a combination of two modern aspects of games development is considered: (i) the impact of high quality graphics and virtual reality (VR) user adaptation to believe in realness of in-game events by user’s own eyes; (ii) modeling an enemy’s behavior under automatic computer control, called BOT, which reacts similarly to human players. We consider a First-Person Shooter (FPS) game genre, which simulates an experience of combat actions. We describe some tricks to overcome simulator sicknesses in a shooter with respect to Oculus Rift and HTC Vive headsets. We created a BOT model that strongly reduces the conflict and uncertainty in matching human expectations. BOT passes VR game Alan Turing test with 80% threshold of believable human-like behavior.
We consider a problem of adaptive design of experiments for Gaussian process regression. We introduce a Bayesian framework, which provides theoretical justification for some well-know heuristic criteria from the literature and also gives an opportunity to derive some new criteria. We also perform testing of methods in question on a big set of multidimensional functions.
This article is devoted to the issue of developing adaptive learning systems for vocational education and training (VET). Firstly, it justifies the urgency of developing and using personalized adaptive learning in vocational educational organizations. Specific features of the Russian VET system and its students are described, demonstrating a number of arguments for the importance of a search for new digital educational solutions. Secondly, the paper elaborates on the theoretical framework of personalization of vocational education and training, which takes into account the necessity for both skills and knowledge. Finally, the authors present a prototype of an adaptive educational system, which is based on ontologically-controlled management of learning trajectories. The developed software is aimed at improving the effectiveness of the VET material science curriculum.
In this paper, we propose an adaptive model of data storage in a heterogeneous distributed cloud environment. Our system utilizes the methods of secret sharing schemes and error correction codes based on Redundant Residue Number System (RRNS). We consider data uploading, storing and downloading. To minimize data access, we use data transfer mechanism between cloud providers. We provide theoretical analysis and experimental evaluation of our scheme with six real data storage providers. We show how dynamic adaptive strategies not only increase security, reliability, and reduction of data redundancy but allow processing encrypted data. We also discuss potentials of this approach, and address methods for mitigating the risks of confidentiality, integrity, and availability associated with the loss of information, denial of access for a long time, and information leakage.
Experimental approach to communicative language techniques has proved to be effective within the frame of instructional cycle. Communicative techniques would naturally include the broad concept of individualization. Finding effective techniques for large classes appears to to a major concern in order to examine the popular belief that general outline of learning a second language is nominal and the interactive approach is to rely on percetive percularities within the sequence approach.
The paper presents algorithms for automatic detection of non-stationary periods of cardiac rhythm during professional activity. While working and subsequent rest operator passes through the phases of mobilization, stabilization, work, recovery and the rest. The amplitude and frequency of non-stationary periods of cardiac rhythm indicates the human resistance to stressful conditions. We introduce and analyze a number of algorithms for non-stationary phase extraction: the different approaches to phase preliminary detection, thresholds extraction and final phases extraction are studied experimentally.
Due to very significant differences between streams obtained from different persons and relatively small amount of data common machine learning techniques do not work well with our data. Thus, we had to develop adaptive algorithms based on domain-specific high-level properties of data and adjust parameters based on the preliminary analysis of the stream, making the algorithms adaptive and thus able to capture individual features of a person.
These algorithms are based on local extremum computation and analysis of linear regression coefficient histograms. The algorithms do not need any labeled datasets for training and could be applied to any person individually. The suggested algorithms were experimentally compared and evaluated by human experts.
By an additive action on a hypersurface H in a projective space we mean an effective action of a commutative unipotent group on the projective space which leaves H invariant and acts on H with an open orbit. Brendan Hassett and Yuri Tschinkel have shown that actions of commutative unipotent groups on projective spaces can be described in terms of local algebras with some additional data. We prove that additive actions on projective hypersurfaces correspond to invariant multilinear symmetric forms on local algebras. It allows us to obtain explicit classification results for non-degenerate quadrics and quadrics of corank one.
We introduce a new compression scheme for high-dimensional vectors that approximates the vectors using sums of M codewords coming from M different codebooks. We show that the proposed scheme permits efficient distance and scalar product computations between compressed and uncompressed vectors. We further suggest vector encoding and codebook learning algorithms that can minimize the coding error within the proposed scheme. In the experiments, we demonstrate that the proposed compression can be used instead of or together with product quantization. Compared to product quantization and its optimized versions, the proposed compression approach leads to lower coding approximation errors, higher accuracy of approximate nearest neighbor search in the datasets of visual descriptors, and lower image classification error, whenever the classifiers are learned on or applied to compressed vectors.
The article describes the features of an enterprise’s business process management that concerns ad-hoc processes. The analysis of the possible implementation problems in ECM system is shown and ways of overcoming.
The article describes the features of business process management that concerns ad-hoc processes in enterprises as expert communities. The analysis of the possible implementation in corresponding Enterprise Content Management (ECM) system is shown. These results were obtained in the fourth stage of the complex project, which is carried in the frame of Government Grant with participation of NRU HSE and “IT” Corporation (Russia).
This chapter addresses the interaction between the authorities and non-state actors in HIV prevention among drug users. Based on case studies in Samara and St. Petersburg, it looks into the mix of vertical structures of governance (dominated by health authorities, including the regional AIDS centers, and drug control authorities) and aspects of network governance where both state and non-state actors collaborate on policy-making and implementation. The chapter concludes that the issue is largely left in a void outside the direct responsibility and attention of state agencies and governance networks. It is approached mainly by actors within the non-governmental sector which, for their part, do not have the resources or necessary authority to make the required policy impact.