The article deals with the methodology and techniques of lexical typological studies. It focuses on the cross-linguistic analysis of semantic areas that are deeply involved in semantic derivation processes, i.e. they either make a wide use of words coming from other semantic domains (as is the case with pain predicates) or frequently give rise to extended meanings (as e.g. rotation verbs, sound verbs, aqua-motion verbs, adjectives of quality). Based on these data, we propose a general approach to a lexical-typological study – a frame-based approach. It is argued that semantic comparison should rely on a set of conceptual frames that underlie the domains under examination and that can be revealed through the analysis of word combinability in natural texts (corpora, spontaneous speech, etc.). The results obtained by this approach can be easily visualized as semantic maps, in which nodes are associated with frames. This technique is illustrated by several examples, which testify to its applicability not only to well-attested domains of semantic typology (like colors, body parts, cutting and breaking, etc.), but also to less observable and highly metaphorical domains. The typological analysis of these areas is appealing, as it allows not only to investigate their lexical organization, but also to compare, in a systematic way, the semantic shifts observed in different languages.
Increasing amount of scientific publications makes it difficult to conduct a comprehensive review and objectively compare results of previous researches. In some areas of research it is also difficult to extract regularities without computer aid due to complexity of experimental setup and results. Cancer treatment using dendritic cell vaccines is such an area. In this paper we describe a framework for semi-automatic information extraction and further analysis. We also present a case study in the field of dendritic cell vaccination and the corresponding experimental results, which include analysis of separability, classification and regression quality evaluation and cause relations mining.
A component model enabling to construct new software components from existing ones dynamically, at runtime, without their bytecodes generation is presented with supporting it software framework. The framework is implemented using JavaBeans component model, but is aimed to eliminate its drawback – the inability to create user-defined components without bytecodes generation. To construct user-defined component dynamically, a composed prototype object is built using predefined (hardcoded and/or composed) component instances; that prototype object can provide functionality required and can be transformed at runtime into a new component (instantiable type) whose instances are able to provide the same functionality, but more efficiently. The prototype object is composed using meta-components – the framework provided components to produce user-defined components dynamically.
Abstract – The paper presents methods of executable file signature creation based on frequency distributions of their informative features to be applied for program identification. Identification here should be understood as a process of file recognition by establishing its coincidence with a particular program. A new approach to creation of the archive of program signatures, both in terms of byte-frequency distribution of a program’s binary code, and in terms of frequency distribution of assembler commands in their disassembler codes, is presented. The new method of executable file identification is offered and the results of experiments on their identification using a statistical criterion of φ*-Fisher and analysis of the slope are provided. The proposed method can be used to audit data-storage medium.
A fridge plays an important role in the kitchen in comparison to other appliances because it helps to store food products at optimal conditions for a long period of time. The ordinary refrigerators perfectly allow preserving meals but they are not effective in case of food management. Providing a remote control for home appliances extends the everyday usage of these devices. In addition to the remote control device, some manufacturers use additional modules such as internal cameras and hands-free speaker for convenient control of an appliance. All these devices are able to communicate with each other to reach common goals. The home appliance producer Liebherr in cooperation with technology company Microsoft developed a solution for remote control of refrigeration with possibility of food recognition using Machine Learning algorithms. This option enables automatic compiling of the list of food stored in the fridge and food ordering in an online shop without manual actions. This opportunity enables not only a convenient usage of an appliance but also allows reduction of electricity consumption because user does not open fridge doors frequently as far as he knows a list of food in refrigerator. In this paper we describe SmartDevice technology from Liebherr that was developed for adding smart features to the brand products. In particular, we review main business processes of SmartDevice, discuss advantages and disadvantages of this solution for the end customers and identify future research for creating smart fridges.
Russia’s ambitions under Emperor Alexander I to establish a new political order in Europe in 1813–1815 have been widely discussed by historians. Assessments of this new order itself, as it was finally implemented in the wake of the Congress of Vienna, vary markedly, but it is generally believed that the post-war system was the fruit of interactions between several participants who represented Europe’s old regimes in an age of revolution. The Holy Alliance as a vision of international order is often presented to be diametrically opposed to the more radical, republican imagining of global order such as that associated with Immanuel Kant’s Perpetual Peace. This chapter shakes up this view by analysing the importance of Kant’s ideas in the intellectual formation of one of the most influential Russian imperial political thinkers of this period, Sergey Uvarov. The degree of indebtedness to Kant’s work in his vision of international order, though it ultimately conflicts with the spirit of Kant’s work, was strongest in the period of Franco–Russian conflict.
In Standard Average European (SAE), addressees of speech verbs are marked with dative or, in languages lacking cases, with dative-like prepositions. This merger is commonly explained through a metaphor: the information transferred in a speech act is said to be construed as the object being transferred, or Theme, and the addressee as its Recipient. This status of the addressee as a derived concept, a metaphor of the Recipient, and its dative marking in many languages rather than in SAE alone, is the reason why the addressee is usually not considered to be a separate semantic role. Based on data from East Caucasian languages that use different marking for Recipients and addressees of speech, I argue that speech addressees constitute a separate semantic role, also an animate Goal, but not a metaphor of the Recipient. Focusing on case marking assigned by the main speech verb, speech acts are shown to be construed in East Caucasian as spatial configurations: the crucial component is their directedness towards the addressee. In the conclusion, I come back to SAE and question the status of the dative addressees. Taking into account that the dative often develops from lative markers, it is suggested that, in the languages with dative addressees, one should also consider an alternative to the conventional explanation: merging the Recipient and the addressee in one marking may result not from a metaphorical extension but from formal under-specification of two different animate Goals.
This paper is aimed at applying and analyzing international active ageing indices in Russia, including the Active Ageing Index (AAI), developed by European Centre Vienna, and Global AgeWatch Index by HelpAge International, to provide the base for cross-national comparison and development of a comprehensive national policy on active ageing. Our research was motivated by the following questions (1) to what extent can the international approaches to measure active ageing be applied to the Russian context and data? (2) to what extent a country’s position in the ranking is sensitive to the index methodology and data used? (3) whether and under what conditions Russia can improve its positions in the active ageing indices? To answer these questions, we estimated the AAI for Russia based on eight data sources and recalculated some of the AgeWatch Index results based on reliable data. The methodology of both indices and the quality and adequacy of the data used are discussed in detail in the paper. The results show that ranking of Russia according to these indices varies considerably from the 65th place out of 96 countries by the Global AgeWatch Index to the 18th place among 29 countries (28 EU countries plus Russia) by the AAI. Nevertheless, both indices draw rather similar pictures of active ageing potential in Russia. We provide some recommendations on how the indicators can be modified to capture some peculiarities of the ageing context in Russia and other countries with similar demographic, economic and social context.
The debt-to-equity choice has always been one of the crucial decisions of the firm’s management. The capital structure is vital for the appropriate development of relationships among the company’s stakeholders. The conflicts of interests between management and shareholders and creditors as well as conflicts between other groups of stakeholders lead to the appearance of agency costs that decrease the corporate value. The role of agency costs is even higher in emerging markets due to higher information asymmetry, lower development of legal system, investors’ protection rights and corporate governance. Our paper contributes to the literature by analyzing the agency costs and capital structure choice on the data of emerging markets companies. Our sample consists of more than 150 companies from BRICS and Eastern Europe within 2000-2010. By conducting the empirical analysis based on both linear panel data regressions as well as simultaneous modeling of leverage choice and management shareholding we obtain the following results. The agency costs are relevant for debt-to-equity choice in Russia, India, China and Eastern Europe but the results are not so obvious in Brazil where financing policy could be explained by trade-off theory. We found out the non-linear relationship between financial leverage and management shareholding which is also in line with agency costs significance. Moreover we revealed that agency costs define long-term leverage, but cannot explain short-term debt in emerging markets. Further, we concluded that debt ratios based on market value of equity are not affected by agency costs opposite to capital structure variables based on book value of equity.
The main goal of the present paper is the development of general approach to network analysis of statistical data sets. First a general method of market network construction is proposed on the base of idea of measures of association. It is noted that many existing network models can be obtained as a particular case of this method. Next it is shown that statistical multiple decision theory is an appropriate theoretical basis for market network analysis of statistical data sets. Finally conditional risk for multiple decision statistical procedures is introduced as a natural measure of quality in market network analysis. Some illustrative examples are given.
Operational processes leave trails in the information systems supporting them. Such event data are the starting point for process mining – an emerging scientific discipline relating modeled and observed behavior. The relevance of process mining is increasing as more and more event data become available. The increasing volume of such data (“Big Data”) provides both opportunities and challenges for process mining. In this paper we focus on two particular types of process mining: process discovery (learning a process model from example behavior recorded in an event log) and conformance checking (diagnosing and quantifying discrepancies between observed behavior and modeled behavior). These tasks become challenging when there are hundreds or even thousands of different activities and millions of cases. Typically, process mining algorithms are linear in the number of cases and exponential in the number of different activities. This paper proposes a very general divide-and-conquer approach that decomposes the event log based on a partitioning of activities. Unlike existing approaches, this paper does not assume a particular process representation (e.g., Petri nets or BPMN) and allows for various decomposition strategies (e.g., SESE- or passage-based decomposition). Moreover, the generic divide-and-conquer approach reveals the core requirements for decomposing process discovery and conformance checking problems.
With the process of globalization the number of borrowings from English has rapidly increased in languages all over the world. In systems of automatic speech recognition, spell-checking, tagging and other tasks in the field of natural language processing the loan words frequently cause problems and should be treat separately. In this paper we present a corpora-based approach for the automatic detection of anglicisms in Russian social network texts. Proposed method is based on the idea of simultaneous scripting, phonetics and semantics similarity of the original Latin word and its Cyrillic analogue. We used a set of transliteration, phonetic transcription and morphological analysis methods to find possible hypotheses and distributional semantic models to filter them. Resulting list of borrowings, gathered from approximately 20 million LiveJournal texts shows good intersection with manually collected dictionary. Proposed method is fully automated and can be applied to any domain-specific area.
Nowadays a lot of various test generation tools are developed and applied to create tests for both software applications and hardware designs. Taking into account the size and complexity of modern projects, there is an urgent need for "smart" tools that would help maximize test coverage and keep the required effort and time to a minimum. Despite the fact that each project is unique in some sense, there is a set of common generation techniques that are applied in a wide range of projects (random tests, combinatorial tests, tests for corner cases, etc). In addition, projects belonging to specific domains tend to share similar test cases or use similar heuristics to generate them. A natural way to improve the quality of testing is to make the most of the experience gained working on different projects or performing testing at different stages of the same project. To achieve this goal, a knowledgebase holding information relevant to test generation would be of a great help. This would facilitate reuse of test cases and generation algorithms and would allow sharing knowledge of "interesting" situations that can occur in a system under test. The paper proposes a concept of a knowledgebase for test generation that can be used in a wide range of test generation tools. At ISPRAS, it is applied in test program generation tools that create test programs for microprocessors. The knowledgebase is designed to store information on widely used test generation techniques and test situations that can occur in a microprocessor design under verification.
The research concerns issues on simulation modeling of Russian Federation higher education system considering its interaction with macroeconomic and demographic factors. The proposed range of simulation models of higher education system is developed using agent-based modeling and system dynamics methods. The range of models allows strategic planning of development of Russian Federation higher education system.
The article deals with the set of simulation models of the pension system of the Russian Federation designed to support government decision-making in the pension field. The set of models is realized on the basis of the composite combination of methods of system dynamics and agent-based modeling and allows you to explore the dynamics of developmental processes in complex social and economic systems, including the cyclic transitions between individual and group behavior of economic and social agents at the micro-level and the basic processes of social and economic system at the macro-level. Stratification of socio-economic system is proposed as a tool of the ontological domain modeling. The stratified description of the pension system is formed as an example. Described agent-based models of social and economic behavior of insured persons with regard to the choice of the method of forming pension and individual pension policies allows you to explore self-organizing processes at the micro-level of the pension system.
Actual problems of modeling of ecologic-economic systems on the example of the Republic of Armenia (RA) are considered.
In the course of researching timetabling problems for complex distributed systems this article applies the multi-agent paradigm of computations and presents a correspondent mathematical model for university’s timetabling problem solution. The model takes into account dynamic nature of this problem and individual preferences of different remote users for time and location of classes. In the framework of that model authors propose an original problem-oriented algorithm of multi-agent communication. Developed algorithm is used as a foundation for the distributed software system AgentTime. Based on multi-agent JADE platform AgentTime provides friendly graphical interface for online design of time tables for universities.
This chapter surveys recent developments in agglomeration theory within a unifying framework. We highlight how locational fundamentals, agglomeration economies, the spatial sorting of heterogeneous agents, and selection effects affect the size, productivity, composition, and inequality of cities, as well as their size distribution in the urban system.