Improving web search results with explanation-aware snippets: an experimental study

In this paper, we focus on a typical task on a web search, in which users want to discover the coherency between two concepts on the Web. In our point of view, this task can be seen as a retrieval process: starting with some source information, the goal is to find target information by following hyperlinks. Given two concepts, e.g. chemistry and gunpowder, are search engines able to find the coherency and explain it? In this paper, we introduce a novel way of linking two concepts by following paths of hyperlinks and collecting short text snippets. We implemented a proof-of-concept prototype, which extracts paths and snippets from Wikipedia articles. Our goal is to provide the user with an overview about the coherency, enriching the connection with a short but meaningful description. In our experimental study, we compare the results of our approach with the capability of web search engines. The results show that 72% of the participants find ours better than these of web search engines. (author's abstract

Surface Characteristics and Materials of Internal Combustion Engines Piston Liners

Tato bakalářská práce je odbornou rešerší a zabývá se problematikou pracovních povrchů válců spalovacích motorů. Uvádí technologie a koncepty, jež jsou uplatňovány v produkci pístových spalovacích motorů v současné době. Charakteristika každé z těchto technologií obsahuje popis výrobních procesů, dokončovacích operací a nejčastějších aplikací. Dále jsou uvedeny vlastnosti, struktury a dosahované drsnosti povrchů vytvořených těmito dostupnými technologiemi.This work is professional research and addresses the issues of working surfaces of cylinders of internal combustion engines. It describes the technologies and concepts that are applied in the production of internal combustion engines currently. The characteristics of each of these technologies provides a description of the production process, finishing and the most common applications. Furthermore, the properties, structure, and achieved surface roughness created by these technologies are available.

Microdata Information System MISSY: Benefits for Research with Official Microdata, DDI-Based Implementation, and Evaluation with Regard to FAIR Criteria

This paper presents the microdata information system (MISSY). MISSY is a service of the German Mi-crodata Lab (GML) for empirically working scientists conducting research using microdata from official statistics. MISSY provides detailed metadata on individual data sets from the German (Microcensus) and European official statistics (e.g. EU-SILC, EU-LFS) and aims to facilitate the use of the data through user-friendly and quickly accessible data documentation. We address the documentation requirements of official microdata, elaborate the benefits of structured metadata for researchers and describe the resulting objectives and contents of MISSY. Subsequently, we introduce the specific technical implementation: A general description of the technical infrastruc-ture as well as the basic data model (DDI-based) and the import/export interfaces of the database. Finally, we discuss MISSY with regard to the FAIR criteria and show how MISSY contributes to official microdata being "FAIR"

The Possibilities of Displacement Increase of 4C Zetor Engine

Diplomová práce se zabývá zpracováním počátečního návrhu konceptu motoru Zetor UŘ III se zvětšeným zdvihovým objemem a posléze provedením kontroly únosnosti hlavních a ojničních ložisek klikového hřídele pro tento koncept. K řešení konstrukční části práce je využito CAD software Creo 2, v němž jsou konstrukční změny na motoru zpracovány. Výpočetní část využívá multibody model klikového ústrojí se zahrnutým pružným MKP modelem klikového hřídele pro řešení dynamiky mechanismu a provedení analýzy kluzných ložisek pomocí simulací hydrodynamických výpočetních modelů v prostředí FEV Virtual Engine. Prezentované výsledky dokladují realizovatelnost návrhu a zároveň slouží jako podklady pro další nezbytné inženýrské kroky před samotnou realizací konceptu.Diploma thesis aims on mechanical design of new concept of Zetor UŘ III engine with displacement increase and solves calculations of main and pin hydrodynamic bearings of crankshaft. Creo 2 CAD software is used for preparing mechanical design of this new concept. For computation and analysis of hydrodynamic bearings multibody model of crankshaft mechanism is used with flexible FEM model of crankshaft for solving dynamics of mechanism and performing hydrodynamic analysis of bearings in FEV Virtual Engine. Results of this diploma thesis demonstrate the feasibility of new concept of engine and serve as a basis for next engineering tasks before realization of concept.

Charaterizing RDF graphs through graph-based measures - Framework and assessment

The topological structure of RDF graphs inherently differs from other types of graphs, like social graphs, due to the pervasive existence of hierarchical relations (TBox), which complement transversal relations (ABox). Graph measures capture such particularities through descriptive statistics. Besides the classical set of measures established in the field of network analysis, such as size and volume of the graph or the type of degree distribution of its vertices, there has been some effort to define measures that capture some of the aforementioned particularities RDF graphs adhere to. However, some of them are redundant, computationally expensive, and not meaningful enough to describe RDF graphs. In particular, it is not clear which of them are efficient metrics to capture specific distinguishing characteristics of datasets in different knowledge domains (e.g., Cross Domain vs. Linguistics). In this work, we address the problem of identifying a minimal set of measures that is efficient, essential (non-redundant), and meaningful. Based on 54 measures and a sample of 280 graphs of nine knowledge domains from the Linked Open Data Cloud, we identify an essential set of 13 measures, having the capacity to describe graphs concisely. These measures have the capacity to present the topological structures and differences of datasets in established knowledge domains

Cultural Tourism as a Driver of Rural Development.Case Study: Southern Moravia

The main aim of the study was to find out whether cultural tourism could be a driver of rural development in the selected area and in general. In case yes, to what extent and under what conditions. Three districts in the South-Moravian Region, Znojmo, Břeclav, and Hodonín, situated in the rural borderland with Austria and Slovakia represented the study area. Both geographical and sociological methods were used to gather evidence for cultural tourism in that study. Firstly, attractiveness analysis of the area defined for cultural tourism took place. Next, factors influencing the potential for cultural tourism affecting rural development in South Moravia were evaluated. Finally, synergistic relations were discussed. In the territory, many forms of tourism intersect. Based on the results, it can be stated that cultural tourism can hardly be the main driver of rural development after the decline of agriculture because the region's economy has branched out in several directions. However, it can be an important complementary activity that yields both economic and non-economic benefits.O

TweetsCOV19 -- A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic

Publicly available social media archives facilitate research in the social sciences and provide corpora for training and testing a wide range of machine learning and natural language processing methods. With respect to the recent outbreak of the Coronavirus disease 2019 (COVID-19), online discourse on Twitter reflects public opinion and perception related to the pandemic itself as well as mitigating measures and their societal impact. Understanding such discourse, its evolution, and interdependencies with real-world events or (mis)information can foster valuable insights. On the other hand, such corpora are crucial facilitators for computational methods addressing tasks such as sentiment analysis, event detection, or entity recognition. However, obtaining, archiving, and semantically annotating large amounts of tweets is costly. In this paper, we describe TweetsCOV19, a publicly available knowledge base of currently more than 8 million tweets, spanning October 2019 - April 2020. Metadata about the tweets as well as extracted entities, hashtags, user mentions, sentiments, and URLs are exposed using established RDF/S vocabularies, providing an unprecedented knowledge base for a range of knowledge discovery tasks. Next to a description of the dataset and its extraction and annotation process, we present an initial analysis and use cases of the corpus