There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Data Mining - Concepts and Techniques.

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

Context. The forecasting system fixing in cybersport is relevant at this point, it is connected to an active development cybersport. In this paper the ability to predict matches users is implemented. Objective. The purpose of this work is the system model design of collective predicting outcomes of games results in cyber sport using modern technology of the neuro forecasting. The task is a system development for common user forecasting results of matches cybersport and independent information processing and issuing its own forecast. The main tasks include: all past and future games accounting and analysis; all teams performance / results accounting and analysis; user capabilities to make personal prediction for every match; determining the team winning odds based on previous matches. Method. The problem by the survey of experts by means of analytical reports and using artificial neural network is solved. ANN is established in three layers. The first layer consists of 10 neurons-receptors, neurons of inputs data. The second layer of neurons is inside. The third layer is the source of neurons, it is only 2 neurons. The input data for the algorithm is the number of matches won the last 10; the number of won games before this meeting; team rating; stability of (time invariance of the team); the average of the losing team. The answer is 1 or 2 (the victory of a particular team). Results. To achieve the cops of the relevant literature with information about the main types of collective prediction is reviewed. A tree objectives, and conducted a systematic analysis of the future system is developed. In this paper the method of interviews with experts and implemented it in their system is altered. Online resources implemented with CMS Drupal. The basic methods of collective prediction are described. A systematic analysis of the research object and subject is developed; objectives tree is developed and the problem and constructed UML-diagrams are studied. The method of interviews with experts and the use of this method in the paper are described. The implementation of a web site with CMS Drupal and programming language PHP is showed. Conclusions. Based on the algorithm calculation example and training artificial neural network independent of the human factor in the process of predicting matches cyber sport is implemented. The presence of such system greatly simplifies the search for example cyber sports matches and give everyone the opportunity to take part in predicting matches. This system can give new impetus to the problem of predicting results not only in cyber-sport and sport in general.

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Matches prognostication features and perspectives in cybersport

Modeling of Operation of Information System for Critical Use in the Conditions of Influence of a Complex Certain Negative Factor

This article deals with the approach to automation of abstracting text documents based on the modification of the TF-IDF measure by ontology of the subject area to which the abstracted document belongs. A method of abstracting based on this approach has developed.

Abstracting Text Content Based on Weighing the TF-IDF Measure by the Subject Area Ontology

The object of this research is the Big Data (BD) analysis processes. One of the most problematic places is the lack of a clear classification of BD analysis methods, the presence of which will greatly facilitate the selection of an optimal and efficient algorithm for analyzing these data depending on their structure. In the course of the study, Data Mining methods, Technologies Tech Mining, MapReduce technology, data visualization, other technologies and analysis techniques were used. This allows to determine their main characteristics and features for constructing a formal analysis model for Big Data. The rules for analyzing Big Data in the form of an ontological knowledge base are developed with the aim of using it to process and analyze any data. A classifier for forming a set of Big Data analysis rules has been obtained. Each BD has a set of parameters and criteria that determine the methods and technologies of analysis. The very purpose of BD, its structure and content determine the techniques and technologies for further analysis. Thanks to the developed ontology of the knowledge base of BD analysis with Protege 3.4.7 and the set of RABD rules built in them, the process of selecting the methodologies and technologies for further analysis is shortened and the analysis of the selected BD is automated. This is due to the fact that the proposed approach to the analysis of Big Data has a number of features, in particular ontological knowledge base based on modern methods of artificial intelligence. Thanks to this, it is possible to obtain a complete set of Big Data analysis rules. This is possible only if the parameters and criteria of a specific Big Data are analyzed clearly.

Big Data analytics ontology

This article dwells upon research concerning human language processing techniques, namely emotion analysis, conducted to identify emotions of author quotations in English newspaper articles. The publication describes general information about human language processing, brief description of analogues based on machine learning and neural network to analyse emotions in text. The main goal is to develop intelligent system for sentiment analysis of English language quotations and keywords identification that influences public opinion. The article describes sequence of program actions and tools that have been used. Then, statistics of tasks performed by neural networks with various functions of activators have been described. In the publication, product demo version has been described, and primary usage scenario has been depicted. In the end, research results have been summarised.

Victoria Vysotska

Papers

Matches prognostication features and perspectives in cybersport

Modeling of Operation of Information System for Critical Use in the Conditions of Influence of a Complex Certain Negative Factor

Abstracting Text Content Based on Weighing the TF-IDF Measure by the Subject Area Ontology

Big Data analytics ontology

Sentiment Analysis Technology of English Newspapers Quotes Based on Neural Network as Public Opinion Influences Identification Tool