Title Autors Web Description
Possibilities of Using Modern Technologies and Creation of the CurrentProject Documentation Leading to the Optimal Management of theBuilding for Sustainable Development Kristýna Prušková, Martin Dědič, Jiří Kaiser . The paper describes the creation of a 3D model of a building using 3D scanning. There are scanning, joining scans and data cleansing procedures described. The process is described in its variants. The description of the process is based on diagrams according to the BPMN standard.
Implementation of BIM Technology into the design process using the scheme of BIM Execution Plan Kristýna Prušková, Jiří Kaiser . The paper provides description of the design process of building according to the czech legislative. The focus is on identifiction of redundant activities and information flows that can be possibly eliminated by using building information modeling (BIM) principles. The case study of apartment building design process is provided including the process map according to Business Process Model and Notation (BPMN) standard.
Usage of the Bag Of Words Model for URL Roman Hujer Main idea of the paper is to use the Bag of words method on URL as strings. As an input will be taken a list with a large quantity of URLs. These URLs will be used to create one bag of words along with quantities (frequencies) of these words. It is assumed that words with high frequencies might be patterns in URL or might suggest some possibilities of classification.
TIMODAZ Michal Višňovský, Pavel Strnad The article focuses on the analysis of data from the project TIMODAZ that examines the effect of temperature on the concrete lining of the storage of nuclear waste. The article primarily presents the results of the methods used in removing outliers in the data acquired and the manner in which the missing values in the data added. Finally, the arcticle evaluates results and recommendations added.
Algorithm for Missing Values Imputation in Categorical Data with Use of Association Rules Jiří Kaiser The paper presents new algorithm for missing values imputation in categorical data. The algorithm is based on using association rules and is presented in three variants. Experiments shows better accuracy of missing values imputation using new algorithm than using most common attribute value.
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