Международно-правовые аспекты развития экономического сотрудничества государств - членов Содружества Независимых Государств

The Article contemplates CIS countries economic cooperation development dynamics since foundation till present. The analysis is carried out and the characteristic is given to the basic international legal bills enacted in economic area by the Commonwealth of Independent States.В статье рассматривается динамика развития экономического сотрудничества государств - членов СНГ начиная с момента образования Содружества и по настоящее время. Проводится анализ и дается характеристика основным международно-правовым документам, принятым в экономической области странами СНГ

A transdisciplinary and community-driven database to unravel subduction zone initiation

Subduction zones are pivotal for the recycling of Earth’s outer layer into its interior. However, the conditions under which new subduction zones initiate are enigmatic. Here, we constructed a transdisciplinary database featuring detailed analysis of more than a dozen documented subduction zone initiation events from the last hundred million years. Our initial findings reveal that horizontally forced subduction zone initiation is dominant over the last 100 Ma, and that most initiation events are proximal to pre-existing subduction zones. The SZI Database is expandable to facilitate access to the most current understanding of subduction zone initiation as research progresses, providing a community platform that establishes a common language to sharpen discussion across the Earth Science community

Strategic analysis of Mlékárna Kunín a.s.

Cílem bakalářské práce je provést strategickou analýzu společnosti Mlékárna Kunín a.s. a na jejím základě vypracovat strategická doporučení pro společnost za účelem dosažení cílů. Práce se dělí na dvě části – teoretickou a praktickou. Teoretická část slouží jako podklad pro provedení strategické analýzy. Praktická část se již zabývá samotným provedením analýzy. Strategická analýza se dělí na externí a interní analýzu. Externí analýza se zabývá makrookolím a mikrookolím a využívá následující metody: PEST analýza, mapa konkurenčních skupin a Porterův model 5 sil. Interní analýza hodnotí vnitřní zdroje podniku a využívá VRIO analýzu, finanční analýzu a analýzu portfolia. Na základě výstupů uvedených analýz se vypracovává SWOT analýza, která je pak podkladem pro návrh strategických doporučení společnosti.The aim of the bachelor's thesis is to execute a strategic analysis for the company Mlékárna Kunín a.s. and to develop on its basis strategic recommendations for the company, enabling it to achieve its goal. The work is divided into two parts - theoretical and practical. The theoretical part is a basis for strategic analysis accomplishing. The practical part deals with its actual implementation. Strategic analysis is divided into external and internal analysis. External analysis deals with macro-environments and micro-environments and uses the following methods: PEST analysis, map of competing groups and Porter's 5 forces model. Internal analysis evaluates the company's internal resources and uses VRIO analysis, financial analysis, and portfolio analysis. The SWOT analysis is done on the base of the outputs of the above-mentioned analyses and is used as a basis for creating strategic recommendations for the company

Commonwealth of Independent States countries economic cooperation development international legal aspects

The Article contemplates CIS countries economic cooperation development dynamics since foundation till present. The analysis is carried out and the characteristic is given to the basic international legal bills enacted in economic area by the Commonwealth of Independent States

Big data analysis for studying spatiotemporal trends in the sustainable development of large cities

The article covers the analysis of big data in urban planning. The purpose of this work is to study modern problems of processing big data containing information about real estate objects and prospects for solving these problems, as well as the possibility of practical implementation of the methodology for processing such data sets by designing and filling a special graphic abstraction “metahouse” using a practical example. The relevance of the study lies in identifying a number of advantages in the presentation of data in graphical form. The mathematical basis of the technique is the use of multidimensional spaces, where measurements are the characteristics of individual objects. In the course of the work, the specifics of big data sets, consisting of information about real estate in a large city, were described. methods of effective solution of the set practical problem of processing and searching for patterns in a large data array were proposed: abstraction “metahouse”, data aggregator. In the course of the study, it was revealed that the presentation of groups of the obtained data in a graphical form has a number of advantages over the tabular presentation of data. The obtained results can be used both for the primary study of big data processing technologies, and as a basis for the development of real applications in the following areas: analysis of changes in the area of houses over time, analysis of changes in the number of storeys in urban development, etc

Building an Associative Classification Data Model Based on the Apriori Method

The purpose of the work is to explore the current problems and prospects of mining solution, big web data in real time, as well as the possibility of practical implementation of Web Mining technology for big web data on a practical example. Materials and methods. The study included a review of bibliographic sources on big data mining. We used Web Mining technology for associative analysis of large web data, as well as computer modeling of the practical task of transaction analysis using a general-purpose scripting language (PHP). Results. During the work, the specifics of the Data Mining technology were described, and a modern approach to the analysis of large web data –Web Mining was analyzed. A brief classification of tasks solved using Web Mining technology is given. The problem of data mining of large web data in a general-purpose scripting language (PHP) has been solved: the lack of libraries for data mining, the difficult normalization of data to the form necessary for associative analysis, interaction with the database management system. Also, an example showing an approach to the mining of large web data was implemented. Based on the understanding of Web Mining technology and the described difficulties of analyzing web data in the PHP language, methods for effectively solving the practical problem of analyzing web data based on transactions committed in a dynamic web application have been proposed. A module for associative analysis of customer transactions in the programming language PHP was developed. The module includes an intelligent data processing class. The structural scheme of the module and system architecture were developed. The constructed module allows us to solve the main part of the problem of associative analysis of large web data using Web Mining technology in order to solve the problem of identifying patterns in a large array of web data. Associative analysis of web data is much faster because of the combination of a general-purpose scripting language and an object-oriented approach. Conclusion. According to the results of the study, it can be argued that the current state of the technology for the analysis of large web data allows efficiently process data objects, identify patterns, obtain hidden data and receive complete statistical data in real time. The results can be used both for the purpose of the initial research of technologies for analyzing large web data, and as an addition to the content management system for the intelligent analysis of web data. The usage of the technology of associative analysis and the created universal handler class makes the created module flexible, while the possibility of manual integration makes this module universal. With manual integration, the database management system is not important. Algorithm methods work with selected data. This factor greatly simplifies the further development of program code

The problem of analysis of big web data and the use of data mining technology for processing and searching patterns in big web data on a practical example

The purpose of the work is to study the current problems and prospects of the solution for processing big data received or stored in the Internet (web data), as well as the possibility of practical realization of Data Mining technology for big web data on practical example. Materials and methods. The study included a review of bibliographic sources on big data analysis problems.Data Mining technology was used to analyze large web data, as well as computer modeling of a practical problem using the C # programming language and creating a DDL database structure for accumulating web data.Results. In the course of the work, the specifics of big data were described, the main characteristics of big data were highlighted, and modern approaches to processing big data were analyzed. A brief description of the horizontal-scalable architecture and the BI-solution architecture for big data processing is given. The problems of processing large web data are formulated: limiting the speed of access to data, providing access via network protocols through general-purpose networks.An example showing the approach to processing large web data was also implemented. Based on the idea of big data, the described complexities of web data processing and the methods of Data Mining, techniques were proposed for effectively solving the practical problem of processing and searching patterns in a large data array.The following classes have been developed in the C # programming language:Class of receiving web data via the Internet; Data conversion class;Intelligent data processing class;Created DDL script that creates a structure for the accumulation of web data.A single UML class diagram has been developed.The constructed system of data and classes allows to solve the main part of the problems of processing large web data and perform intelligent processing using Data Mining technology in order to solve the problem posed of identifying certain records in a large array. The combination of object-oriented approach, neural networks and BI-analysis to filter data will speed up the process of data processing and obtaining the result of the studyConclusion. According to the results of the study, it can be argued that the current state of technology for analyzing large web data allows you to efficiently process data objects, identify patterns, get hidden data and get full-fledged statistical data.The obtained results can be used both for the purpose of the initial study of big data processing technologies, and as a basis for developing an already real application for analyzing web data. The use of neural networks and the created universal classes-handlers makes the created architecture flexible and self-learning, and the class declarations and the base DDL structure will greatly simplify the development of program code

Survival of LLSVPs for billions of years in a vigorously convecting mantle: Replenishment and destruction of chemical anomaly

We study segregation of the subducted oceanic crust (OC) at the core-mantle boundary and its ability to accumulate and form large thermochemical piles (such as the seismically observed Large Low Shear Velocity Provinces (LLSVPs)). Our high-resolution numerical simulations of thermochemical mantle convection suggest that the longevity of LLSVPs for up to three billion years, and possibly longer, can be ensured by a balance in the rate of segregation of high-density OC material to the core-mantle boundary (CMB) and the rate of its entrainment away from the CMB by mantle upwellings. For a range of parameters tested in this study, a large-scale compositional anomaly forms at the CMB, similar in shape and size to the LLSVPs. Neutrally buoyant thermochemical piles formed by mechanical stirring—where thermally induced negative density anomaly is balanced by the presence of a fraction of dense anomalous material—best resemble the geometry of LLSVPs. Such neutrally buoyant piles tend to emerge and survive for at least 3 Gyr in simulations with quite different parameters. We conclude that for a plausible range of values of density anomaly of OC material in the lower mantle—it is likely that it segregates to the CMB, gets mechanically mixed with the ambient material, and forms neutrally buoyant large-scale compositional anomalies similar in shape to the LLSVPs. This research was originally published in the Journal of Geophysical Research: Biogeosciences. © 2015 American Geophysical Unio