Iskanje po katalogu digitalne knjižnice

Opis: Global foreign direct investment flows in terms of greenfield and brownfield investments have increased during the recent three decades resulting from the accelerating globalization. The considerable increases in the flows of foreign direct investment have many eventualities for the national economies. This study investigates the mutual effects among greenfield and brownfield (mergers and acquisitions) investments and economic growth in Central and Eastern European Union countries during the 2003–2015 period employing panel data analysis. The findings revealed that both greenfield and brownfield investments had positive influence on the economic growth, but the influence of greenfield investments was found to be relatively higher. Furthermore, one-way causality was discovered from both greenfield and brownfield investments to the economic growth.
Ključne besede: greenfield investments, brownfield investments, economic growth, panel data analysis, Central and Eastern European Union countries
Objavljeno v DKUM: 03.05.2018; Ogledov: 3222; Prenosov: 218
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Opis: Estonian Etymological Dictionary being compiled at the Institute of the Estonian Language. A limited number of dialect words will be included in the headword list of the dictionary. Dialect data may be vital for etymologization as well. In the case of genuine words and older loanwords, the archaic phonological traits that have survived in dialects are essential; in the case of more recent loanwords, the dialectal variants show different degrees of adaptation. Sometimes the areal distribution of a word may prove a valuable cue to its original background. Etymologization may also be based on the dialectal meaning of a word. A specific group consists of dialect words adopted into standard usage in a different sense as technical terms.
Ključne besede: Estonian, etymological dictionaries, computer data processing, dialectology, linguistic geography
Objavljeno v DKUM: 02.02.2018; Ogledov: 1252; Prenosov: 344
Celotno besedilo (313,02 KB)
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Opis: This master thesis deals with the effect of interoperability between architectural and structural BIM software in the case of a Mall project. The research and most of the work was performed on a BIM model of the Mall project that was modeled using Tekla BIM software. Since there is still a lack of investigations addressing interoperability issues in the structural engineering domain, this thesis pretends to show the collaboration between architectural and structural BIM software, taking into account a real and complex project. A general overview and research regarding building information modeling (BIM) and interoperability issues were done in this project. Various case studies were conducted, where the entire BIM model and partial models of the Mall project were transferred from BIM to FEM software using different data exchange methods. Structural analysis and design in the case of the relevant partial models of the Mall project were performed with the help of Dlubal-Structural Engineering Software for Analysis and Design. Such analyses were made in the structural analysis program RFEM, to investigate if those partial models are imported correctly. The general conclusion based on the used case studies is that data exchange between BIM and FEM software can be useful, but the ease of use depends on both the data exchange method and the way how the relevant model has been created in Tekla BIM software. Referring to these case studies, the most successful data exchange was achieved by using the direct link between BIM and FEM software.
Ključne besede: Building Information Modeling (BIM), Interoperability, Data, Direct link, IFC, DSTV (*.stp), Tekla, RFEM, Modeling, A&D, Mall Project.
Objavljeno v DKUM: 15.12.2017; Ogledov: 2813; Prenosov: 218
Celotno besedilo (20,15 MB)

Opis: Decision-making problems in the area of financial status evaluation are considered very important. Making incorrect decisions in firms is very likely to cause financial crises and distress. Predicting financial distress of factories and manufacturing companies is the desire of managers and investors, auditors, financial analysts, governmental officials, employees. Therefore, the current study aims to predict financial distress of Iranian Companies. The current study applies support vector data description (SVDD) to the financial distress prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use a grid-search technique using 3-fold cross-validation to find out the optimal parameter values of kernel function of SVDD. To evaluate the prediction accuracy of SVDD, we compare its performance with fuzzy c-means (FCM).The experiment results show that SVDD outperforms the other method in years before financial distress occurrence. The data used in this research were obtained from Iran Stock Market and Accounting Research Database. According to the data between 2000 and 2009, 70 pairs of companies listed in Tehran Stock Exchange are selected as initial data set.
Ključne besede: financial distress prediction, Support vector data description, Fuzzy c-mean
Objavljeno v DKUM: 30.11.2017; Ogledov: 959; Prenosov: 191
Celotno besedilo (1,10 MB)
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Opis: Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.
Ključne besede: Wikipedia, language, growth dynamics, data analysis, clustering
Objavljeno v DKUM: 13.11.2017; Ogledov: 1533; Prenosov: 395
Celotno besedilo (1004,06 KB)
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