The series “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing such as: computational intelligence, soft computing including neural networks, fuzzy systems, evolutionary computing and the fusion of these paradigms, social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, Web intelligence and multimedia. The publications within “Advances in Intelligent Systems and Computing” are primarily proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results.
This book contains a selection of papers accepted for the presentation and discussion at the 2018 International Conference on Digital Science (DSIC’18). This Conference had the support of the Institute of Certified Specialists, Russia, AISTI (Iberian Association for Information Systems and Technologies), and Springer. It will take place at Convention Centre, Budva, Montenegro, October 19–21, 2018. DSIC’18 is an international forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences, and concerns in the several perspectives of Digital Science. The main idea of this Conference is that the world of science is unified and united allowing all scientists/practitioners to be able to think, analyze, and generalize their thoughts. DSIC aims efficiently to disseminate original research results in natural, social, art, and humanities sciences. An important characteristic feature of the Conference should be the short publication time and worldwide distribution. This Conference enables fast dissemination, so conference participants can publish their papers in print and electronic format, which is then made available worldwide and accessible by numerous researchers. The Scientific Committee of DSIC’18 was composed of a multidisciplinary group of 26 experts. One hundred and seven invited reviewers who are intimately concerned with Digital Science have had the responsibility for evaluating, in a “double-blind review” process, the papers received for each of the main themes proposed for the Conference: Digital Art and Humanities; Digital Economics; Digital Education; Digital Engineering; Digital Environmental Sciences; Digital Finance, Business and Banking; Digital Media; Digital Medicine, Pharma and Public Health; Digital Public Administration; Digital Technology and Applied Sciences. DSIC’18 received 88 contributions from 16 countries around the world. The papers accepted for the presentation and discussion at the Conference are published by Springer (this book) and will be submitted for indexing by ISI, SCOPUS, among others.
The article deals with the problem of creating a temperature regulator, which does not require preliminary tuning for a specific production plant. Authors proposed to use a matrix approach of fuzzy logic for this purpose. It allows engineers to apply the linguistic rules formulated in the most general form for industrial processes control. It also allows building simple control algorithms for complex nonlinear systems. To verify the correctness of the algorithm, authors assembled installation with heaters of various types, powers and inertia. The full-scale experiment shown that the developed prototype of the device allows controlling the temperature in various settings without initial tuning.
This article proposes a method of constructing dynamic neural network mathematical models that allow not only to diagnose the disease at the current time, but also to simulate the appearance and development of diseases in future periods of time, as well as to control their appearance and development by selecting the optimal lifestyle and optimal intake of drugs. It is assumed that the use of dynamic neural network medical systems, instead of static, allow doctors, before prescribing courses of treatment to patients, to test the effect of drugs not on patients, but on their virtual mathematical models. The action of the system is demonstrated by examples.
The use of hedges has been an important topic in academic writing research. Much of this research has focused on L1 academic texts. This study investigates the use of the most frequent hedging devices in the corpus of 58 works written by Russian university students and compares it to the corpus of articles published in peer-reviewed journals in business and management. The analysis of learner corpus data and further comparison provided by the reference corpus have highlighted a number of problems which non-native learners experience when writing academic texts, e.g., phraseological infelicities and stylistic inappropriacies. Some teaching materials presented in the paper aim at helping teachers to deal with the problems identified. This study has important implications for creating EAP courses, research of second language acquisition, and writing pedagogy.
In this paper, we analyze a new approach for demand prediction in retail. One of the signicant gaps in demand prediction by machine learning methods is the unaccounted sales data censorship. Econometric approaches to modeling censored demand are used to obtain consistent and unbiased estimates of parameters. These approaches can also be transferred to different classes of machine learning models to reduce the prediction error of sales volume. In this study we build two ensemble models to predict demand with and without demand censorship, aggregating predictions for machine learning methods such as Linear regression, Ridge regression, LASSO and Random forest. Having estimated the predictive properties of both models, we test the best predictive power of the models with accounting for the censored nature of demand.
This article describes development experience of the neural network system for medical diagnostic of gastrointestinal diseases. There was used patient’s practical medical information for its creation. As input parameters were taken into consideration different factor groups, include demographic, patient’s complaints, life history, medical history and additional methods of research. Neural network model allowed making a significance assessment of factors, which have disease’s development influence. As a result, was designed neural network system of differential diagnosis, allowing diagnoses “gastritis”, “peptic ulcer”. In the future, developed diagnostic system can be used as a “provisional diagnosis of gastrointestinal diseases”.
The article ask the question whether Plutarch' s narration on Cimon is trustworthy
This paper focuses on referential coherence which is seen as a crucial attribute of effective academic writing. I report findings from a corpus study of Russian students' use of anaphoric expressions in their research proposals which is compared to a reference corpus comprising research articles published in peer-reviewed journals. I hypothesise that learners use anaphora less frequently than professional writers. The results of the analysis confirmed the hypothesis and allowed me to identify particular problems connected with the students' use of anaphoric expressions. It is hoped that the reported findings will challenge EAP teachers and textbook writers to consider paying closer attention to the markers of referential coherence in a course of academic writing for L2 students.
This article is devoted to the method of creating an intelligent neural network system. Unlike existing similar systems, the proposed system does not require frequent updates, because it is able to adapt itself to the constantly changing state of the economy and to the peculiarities of a particular region. Besides, the proposed system allows performing scenario forecasting of regional real estate markets depending on virtually changing economic parameters such as the dollar rate, the market price of oil, gross domestic product and gross regional product, the volume of housing construction in the region, the parameters of the state’s credit policy, etc.
The study is a quantitative analysis of the use of syntactic markers of academic discourse in two kinds of corpora: expert corpora which comprise articles published in peer-reviewed journals in management and economics and learner corpora of students’ research papers in the same disciplines. The syntactic constructions selected for the analysis are taken from various guidebooks and textbooks in academic writing. They are it-clefts; pseudo-clefts; th-wh constructions; attitudinal clauses; various types of adverbial clauses; relative clauses and non-finite clauses. The paper aims at identifying the differences between student and professional writing as well as ‘hard’ and ‘soft’ disciplines in order to facilitate EAP teachers to design their courses in academic writing in the conditions of limited classroom time making them more discipline specific and relevant to learners’ needs.
The article addresses the stage of web-application realization for uploading, storing, and processing academic texts in English. The architecture and functions of the application are described, realization methods of software solution are suggested with the specifics of the subject domain. The choice of software tool are described.
This article discusses the attitude of consumers to food without synthetic additives. The practical part of the study is devoted to the assessment of the willingness to pay for mayonnaise, which does not contain synthetic preservatives, by Perm consumers. The paper uses the contingent valuation method to determine the willingness to pay for the product. The results of the analysis suggest that the average consumer of mayonnaise in Perm is ready to buy mayonnaise, which does not contain a synthetic preservative, with a 23,55 % premium to the price of mayonnaise with a synthetic preservative. Previously, there were no studies of the willingness to pay by Russian consumers for a product without synthetic preservatives and this work fills this gap. The results of the study will help companies and government to assess the attitude of consumers to synthetic preservatives.
The article aims to produce an analysis, typology and understanding of the specifics brought about into the English XX-century novel by memory as a technology to narrate the past which has complicated the already existing system of narrative modes and formed a poetics of its own.
The research is based on eleven first-person retrospective English novels: The Good Soldier; Coming Up for Air; Brideshead Revisited; A Dance to the Music of Time; Free Fall; The Sea, the Sea; Waterland; Last Orders; The Remains of the Day; Experiment in Love; Love, etc.
Using historical-literary approach, comparative analysis and narratological methods, the article produces a typological description of such poetological categories as the narrator’s image, the chronotope, the narratee and the system of narrative modes (memory, document and tale).
Developing Bakhtin’s definition of the novel as a “genre of formation” we describe our novels as those of reformation. The narrator is placed in a liminal situation (death, existential crisis, loss of job or divorce) which urges him/her to restore the past. The narrator typically belongs to intellectual background (artist, writer, theatre director, school teacher) and is prone to self-reflection.
The temporal transfer into the past correlates with the physical movement, namely with the chronotope of the road. The past is restored as a result of a return trip (accidental in Waugh or conscious in Orwell and in “Last Orders”) or may unfold in the process of prospective journey as in Ishiguro.
In Waugh and Powell memory is autocommunicative: the narrators restore the past inside their minds, without addressing anyone. Here the implied reader steps to the forefront: by noticing repetitions, omissions and contradictions it makes the narrated world one whole. This reader is not limited to a private story but, through a system of cultural, historical and literary allusions, also shares the cultural past with the characters of Powell and Swift.
Memory also enters symbiotic relations with oral and written modes which makes the novels more dialogic. Via written mode in Murdoch and Golding the novel attempts to bridge the gap between fiction and reality and obtain the status of a real object (the book, the text) through the narrator’s metaliterary commentary and reflection. In the second case (Orwell, Mantel and Barnes) memory is verbalized as a system of voices that address each other and/or the reader. The reader, thus, is involved into the fictional world as a participant.
Ford, Swift and Ishiguro equivocally merge all three modes which, respectively, reflects Dowell’s attempt to escape self-judgement, correlates with the message on the universal connection between times, people and events, is a perfect technique to portray an unreliable narrator. Overall the permeability of modes exemplifies the XX-century tendency to relativize ontological, temporal and narrative borders.
The paper deals with problem of the Athenian Myth on aotochthony.
The article describes the development process of model for comparing scientific texts stylistic characteristics. The model has been created from several components, such as method of text information representation, method of these models comparison and way of text stylistic characteristics representation and also tested on a trial data set. Metrics for comparing texts stylistic characteristics can be used for quality control of works in education and also at linguistic researches.
The article addresses the issues expert system development which provides style analysis of a written academic text in English produced by a nonnative Russian speaker. Producing a high quality text written according to the rules of contemporary Academic discourse is a challenging task for any nonnative speaker, even more challenging for novice writers. Since publishing in well recommended academic journals and magazines is a primary task for researchers using special software which checks style against criteria set by publishes might save time and effort. The system which implements the task of assessment of L2 written academic text against the style criteria set by publishers of academic journals is developed in CLIPS environment. The article provides comparative analysis of existing software products. On the basis of the analysis and identifying weakness and limitations of existing systems the major goals of the expert system are formed. The main steps of system development in CLIPS environment are presented in the article. In conclusion practical and pedagogical implications of the system are presented
SummaryMaximus’ idea of appropriation of the divine will by deified humans, in any consistent interpretation, would mean their deprivation of their own freedom – exactly in the same manner as it could be in the case of servitude to sin. Maximus’ own logic, however, was paraconsistent when applied to the case of deification (whereas not to the opposite case of the servitude to sin). A recourse to a paraconsistent deontic logic was not a uniquely Maximian tool even in the Middle Ages and could serve as an inspiring example for logicians today.
It is well known that mobile ad hoc networks are widespread nowadays. Such networks are created in a short time and function during short time. The number of nodes and interconnections between these nodes change all the time. The algorithms for ad hoc networks management change too. Thus, the software tools and language of the simulation systems must correspond to the dynamically changing elements of the ad hoc system and dynamically changing structure. The paper gives an example of modeling the routing algorithms in ad hoc networks and presents simulation software for the investigation of routing algorithms functioning in ad hoc networks.
In this paper, we consider anti-smoking policy in Russia and the socioeconomic factors that influence an individual’s decision to smoke. Among various factors, we investigate the individual time preferences of Russians. To estimate individual time preferences, we use an experiment in which survey respondents are given hypothetical money prizes. We find that being middle-aged, being unmarried and having parents who smoke are positively correlated with both men and women’s likelihood of taking up smoking in Russia. We consider the possible endogeneity of an individual’s health status and find a positive relationship between smoking and the time preferences of Russians. Our findings confirm that decisionmakers should devote their efforts primarily to developing restrictive anti-smoking policy. The choice of policy measures should be guided by the individual characteristics of target population groups. Social advertising, public lectures and preventive care should be actively engaged in forming public attitudes towards smoking.
In this research we analyze the demand for performing arts. Since the observed demand is limited by the capacity of house, one needs to account for demand censorship. The presence of consumer segments with different purposes of going to the theatre and willingness-to-pay for performance and ticket characteristics compels to account for heterogeneity in theatre demand. In this paper we propose an estimator for prediction of demand that accounts for both demand censorship and preferences heterogeneity. The estimator is based on the idea of classification and regression trees and bagging prediction aggregation. We extend the algorithm for censored data prediction problem. Our algorithm predicts and combines predictions from both discrete and continuous parts of censored data. We show that the estimator is better in prediction accuracy compared with estimators which account for censorship or heterogeneity of preferences only.
The aim of this paper is to study the influence of chief executive officers' overconfidence on corporate research and development (R&D). We analyze a sample of 766 firms from the United Kingdom, France, Germany, Switzerland, Italy, Spain, and the Netherlands between 2008 and 2013. We use 3 measures of managerial overconfidence: the press coverage of chief executive officers, his/her age, and his/her experience in the industry. Our results show that the firms run by overconfident managers actually invest more in R&D expenditures, even after controlling for country, industry, and time factors. Overconfident managers not only spend more on R&D but also amplify the effect of financial determinants of R&D such as firm liquidity or profitability. Nevertheless, overconfident managers do not invest efficiently in R&D, and these expenditures can negatively affect the value of the firm.