The functionals related to the quality of the system control are obtained
in the analytic form. The statement that the optimal strategy of controlling
the system is a deterministic strategy is proved. Analytic form representation
for the function the absolute extremum of which is determined as the optimal
control strategy is obtained also.
The present paper aims at investigating the productivity of the prefixoid samo- (‘self’) in Russian compounds from a diachronic perspective. In order to verify the hypothesis that the productivity of this prefixoid has grown over time, I consider the occurrences of samo-compounds in the Russian National Corpus, dividing the main corpus into four subcorpora, each one representing a particular time span: the 18th century, the 19th century, the 20th century and the period that lasts from the beginning of the 21st century to the present day. The approach chosen is quantitative in nature, and is based on the measure of “potential productivity” (Baayen & Lieber 1991; Baayen 1992, 1993), which is calculated by dividing the number of hapax legomena with a certain affix by the number of tokens with that affix. This measure, however, seems inadequate for the comparison of differently-sized corpora. To overcome this problem, I resort to parametric statistical models of frequency distribution known as LNRE (Large Number of Rare Events) models (Baayen 2001). These models, which allow extrapolating the expected values of types and hapax legomena with a given affix for arbitrary values of tokens, are implemented in the package zipfR (Baroni & Evert 2014), a tool for lexical statistics in R, which is used for this study.
Recent theories of cognitive control put large emphasis on theta oscillations in relation to action monitoring. Multiple EEG studies of cognitive control revealed increased power of theta oscillations restricted to midfrontal areas, while there is a substantial body of functional connectivity data demonstrating that theta oscillations may be a carrier of informational exchange over multiple cortical regions. fMRI studies revealed immense distributed networks involved in cognitive control. Paradoxically, MEG has been considered almost insensitive to theta oscillations in such an experimental context. It also remains debatable what is the functional role of such theta oscillations. An influential line of evidence links feedback-related theta oscillations to two types of prediction errors (unsigned and signed), but this distinction has not been tested during trial-end-error learning with theta activity measured beyond the midfrontal cortex.
We recorded MEG while participants were involved in trial-and-error learning within a novel multiple-choice behavioral task with complex stimulus-to-response mapping. Three conditions were analyzed: correct and erroneous trials during the initial stage of learning acquisition, as well as correct trials during stable performance. Sources of MEG activity were analyzed using minimum-norm estimation method within 4-6 Hz frequency range.
We revealed a number of bilateral cortical areas that displayed theta oscillations to the feedback signal: in addition to the "classical" medial frontal areas (the anterior part of the medial cingulate cortex and the pre-supplementary motor area), this network included the insula and the auditory cortex, the frontal operculum and posterior inferior frontal gyrus, the premotor cortex, the paracentral lobule, and the posterior part of the medial cingulate cortex. Granger causality analysis revealed overall communication directed from lateral to medial sites. During the initial stage of trial-and-error learning, we observed a strong non-differential response to feedback signal that reflected an unsigned component of the prediction error. The signed component of the prediction error was observed later – with greater theta activations after errors compared with correct responses.
Thus, using MEG, we were able to reveal a distributed network of brain areas in relation to feedback-related processing that included not only medial frontal, but also auditory areas, insula, lateral frontal, and medial parietal areas. The data obtained confirm the existence of two components of the prediction error, and this distinction was evident all over the network revealed.
The study was implemented in the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) in 2018.
An appendix to this paper, written by Alexander Magazinov, presents a 2-dimensional counterexample to a natural conjecture involving the geometric mean.
According to the embodied cognition theory, speech is largely based on the body motor and sensory experience. The question, which is crucial for our understanding of the origin of language, is how our brain transforms sensory-motor experience into word meaning. We have developed an auditory-motor experimental procedure that allowed investigating neural underpinning of word meaning acquisition by way of associative "trial-and-error" learning that mimics important aspects of natural word learning. Participants were presented with eight pseudowords; four of them were assigned to specific body part movements during the course of learning – through commencing actions by one of participant’s left or right extremities and receiving a feedback. The other pseudowords did not require actions, and were used as controls. Magnetoencephalogram was recorded during passive listening of the pseudowords before and after learning. The cortical sources of the magnetic evoked responses were reconstructed using distributed source modeling (MNE software). Neural responses to newly learnt words were significantly enhanced as compared to control pseudowords in a number of temporal and frontal cortical regions surrounding the Sylvan fissure of the left hemisphere. Learning-related cortical activation was inversely related to the number of trials needed to acquire the word meaning (this value varied between participants from 74 to 480 trials to the learning criterion). Our findings revealed a neural signature of associative learning of meaning of nonsense words and highlighted the role of sensory-motor transformation for association-grounded word semantics.
Embodied cognition theory implies that speech is largely based on the body motor and sensory experience. The question, which is crucial for understanding the origin of language, is how our brain transforms sensory-motor experience and gets access to word semantic representation. We developed an auditory-motor experimental procedure that allowed investigating neural underpinning of word meaning acquisition by way of associative "trial-and-error" learning paradigm that mimics basic aspects of natural language learning. Participants were presented with eight pseudowords; four of them were assigned to specific body part movements during learning blocks – through commencing actions by one of participant’s left or right extremities and receiving a feedback. The other pseudowords did not require actions and were used as controls. Magnetoencephalogram was recorded during passive listening of the pseudowords before and after learning blocks. The cortical sources of the magnetic evoked responses were reconstructed using distributed source modeling. Learning of novel word meaning through word-action association selectively increased neural specificity for these words in the auditory parabelt areas responsible for spectrotemporal analysis, as well as in articulatory areas, both located in the left hemisphere. The extent of neural changes was linked to the degree of language learning, specifically implicating the physiological contribution of the left perisylvian cortex in the speech learning success.
Credit risk management is of considerable importance for banks, and the most common credit risk models are based on combining client’s private information with credit terms. However, if credit terms are an integral part of initial calculations, then results have to be recalculated for every alteration of credit terms. Thus, banks obtain ‘one-shot’ results from decision support systems that are built with application of these models. In the given paper a credit risk model is proposed. This model is based on a separate analysis of client’s private information and credit terms in order to construct a contour subspace for credit terms that correspond to an equal credit risk value. Application of a proposed model will add advanced options for decision support systems in loan granting, i.e. to visualize a contour subspace of credit terms for a client according to an individual creditworthiness estimation, provide options to choose credit terms from this contour subspace, and manage credit terms on-line according to the dynamics in a creditworthiness estimation.
User system trust is critical to the uptake of recommendations, and several factors of trust have been identified and compared. In this paper we present a cross-cultural, crowdsourced study examining user perceptions of nine factors of trust and link the observed differences to trust development processes and cultural dimensions. While some factors consistently instil trust, others are preferred only in certain countries. Our findings and the discovered links are important for design of trusted recommender systems
The poetic texts pose a challenge to full morphological tagging and lemmatization since the authors seek to extend the vocabulary, employ morphologically and semantically deficient forms, go beyond standard syntactic templates, use non-projective constructions and non-standard word order, among other techniques of the creative language game. In this paper we evaluate a number of probabilistic taggers based on decision trees, CRF and neural network algorithms as well as a state-of-the-art dictionary-based tagger. The taggers were trained on prosaic texts and tested on three poetic samples of different complexity. Firstly, we suggest a method to compile the gold standard datasets for the Russian poetry. Secondly, we focus on the taggers’ performance in the identification of the part of speech tags and lemmas. We reveal what kind of POS classes, paradigm classes and syntactic patterns mostly affect the quality of processing.
Who joins voluntary associations? Based on previous research, we hypothesize that full- or part-time employment makes it more likely that respondents will join voluntary associations. This article examines how employment, supervisory status, and other occupational characteristics (creativity, autonomy or intellectual nature of work) influence membership rates in voluntary associations in cross-national comparison. This research combines individual-level data from the World Values Survey Wave 5 and 6, and country-level Freedom House data, in multilevel regression modeling. This research demonstrates that respondents in the labor force are more likely to report membership in a range of voluntary organizations, controlling for a range of individual and country-level characteristics. Similarly, employed respondents who are work supervisors are also more likely to report membership in most countries, while creativity at work increases the likelihood of membership in some settings.
Stronger beta (15-30 Hz) suppression in higher-order areas of motor cortex accompanies more difficult search in semantic memory during verb generation task.
This chapter explores the nature of the 2008 crisis and the channels through which it affected the performance of Russian firms. Based on the findings of manufacturing industry survey, the evidence suggests that all manufacturing firms were affected by the crisis and there is no single and dominant transmission channel. Crisis reactions were significantly related to participation in international markets, although participation in trade, external borrowing or FDI can not explain recession by themselves. The reversal of growth was mainly caused by demand shock, and following that, by financial constraints. Thus hypothesis that blames overheating of internal demand in the years prior to the crisis seems to receive statistical backing. Globalised companies, thogh hit by external shocks, were better prepared to pay the cost and balance the consequences of the crisis.
Development of Russian electric power industry in recent years is characterized by a multitude of problems and a decrease in a number of performance indicators. It dissatisfies consumers and encourages them to implement various measures to reduce risks and costs of energy supply. This creates preconditions for the emergence of «active» consumers in the domestic electric power industry. Given this trend it would be appropriate to switch from Supply Side Management to Demand Side Management. This will require the implementation of a wide range of measures, including strategic issues of industry development, legal framework and transition to a customer-centric market model.
We introduce the active XML database architecture to build very large, scalable, loosely structured distributed data storage. Traditionally data is regarded as passive records operated by DBMS software. Our idea is that every data unit is active, capable of communication with other data units and database clients. Combined with the special overlay structure incrementally formed by data units (Metrized Small World Graph) this provides for effective distribution of data units among database servers and unbounded scalability of the resulting storage ensuring logarithmic search and append complexity. Each active data unit is represented as an XML document addressable by a unique URL having a locally stored extendable set of XLink links to other data units, and a software module driving the communication with other data units and clients. Search in this structure is performed by sequential and/or parallel crawling following the links in the list obtained on each step. The active data units communicate by sending XML messages over a transport protocol such as HTTP. The communication includes the retrieval of XML content and link lists, addition of new links, calculating query relevance and work delegation (so that every unit can actively propagate the process initiated or mediated by another unit). Since there are no central controlling nodes in the structure, multiple processes of adding new data units and searching for existing data can be performed independently and simultaneously, and begin with any existing data unit. Moreover, because the data units are active, these processes may propagate on they own without being fully dictated by originator. This allows the distribution of data processing along with the distribution of data itself. We have built a prototype implementation of the architecture. The analysis of the small world overlay structure properties confirmed the possibility of building efficient XML data storages which contain hundreds of petabytes of data.
The analysis of typical ways to build tools of control of the security perimeter and intrusion into the protected area. The method of compensation of the effect of ambient light, the block diagram and measuring information processing algorithm of active infrared sensor of reflecting type, allowing to use it to register movement, is reviewed. The results of experimental studies of the device to control the intrusion into the protected area on the basis of active infrared sensor of reflecting type are considered.
In automated health services based on text and voice interfaces, there is a need to be able to understand what the user is talking about, and what is the attitude of the user towards a subject. Typical machine learning methods for text analysis require a lot of annotated data for the training. This is often a problem in addressing specific and possibly very personal health care needs. In this paper, we propose an active learning algorithm for the training of a text classifier for a conversational therapy application in the area of health behavior change. A new active learning algorithm, Query by Embedded Committee (QBEC), is proposed in the paper. The methods are particularly suitable for the text classification task in a dynamic environment and give a good performance with realistic test data.
The aim of this paper is to systematize the variety of rationality in reasoning. What is gained, then, is a goal-rationality framework for the logical modelling of ‘belief biases’ in reasoning.
The legal strategy of the future is reached in daily law-enforcement practice of China. The analysis within comparative jurisprudence is in many respects predetermined by its functions which are setting target orientation and vectors of studying, comparison, an assessment. Problems of legal distinctions of Russia and China from the point of view of opportunities of their overcoming are obvious. In this context it is possible to speak about distinctions, and not only about temporary and long-term, but also about the ineradicable.
Certainly, the emphasis on comparison only laws leaves other phenomena of legal life in a shadow: sources of law, state institutes, legal establishments, application of law, legal education and science. Obviously, it is necessary to carry that is a question not of an one-stage look, and of difficult informative process of its intensive development to the positive moments of the carried-out analysis of the current legislation of China.
Тhe objects of the tax control in Russia and China are the same. But the instruments used by these countries are different.
At first In China the tax control is more extensive. Secondly the responsibility in China is more strict than in Russia.
At the same time notions and theory of tax control seems to be more developed in Russia. Russian legislation is codified. However it’s much less effective even if in Russia there are much more instruments of tax control.
As the result in the perspective of BRICS on the first steps of its creation we can adopt the strongest features of the other BRICS countries to improve the law systems.