Analýza inovačních indikátorů v Evropské unii s pomocí strojového učení

Evropská komise každoročně vydává Evropský srovnávací přehled inovací, který je nástrojem k měření inovační výkonnosti členských států Evropské unie (EU). Tato práce rozšiřuje analýzy publikované v Evropském srovnávacím přehledu inovací 2018 ve dvou směrech. První část zkoumá, pomocí shlukové analýzy, rozdělení členských států EU do skupin podle inovační výkonnosti. V této práci přicházíme s unikátním schématem řešení tohoto rozdělení za použití hierarchického shlukování. Při porovnání našeho schématu se schématem stávajícím se ukazuje, že hlavní vzory v obou schématech jsou velmi podobné. Jedinou výjimkou je odlišnost Velké Británie, Irska a Lucemburska od ostatních nadprůměrně výkonných států. Námi navrhované schéma navíc přináší informace o podobnosti států uvnitř jednotlivých výkonnostních skupin, například uvádí podobnost mezi Finskem, Švédskem a Dánskem a jejich relativní odlišnost od Francie, přestože jsou v jedné skupině. V druhé části se pomocí regresní analýzy pokoušíme zkoumat efekt inovací na reálnou lidskou produktivitu. Na rozdíl od existující literatury nenacházíme statisticky významný vztah mezi produktivitou a indikátory Evropského srovnávacího přehledu inovací. Proto následně rozšiřujeme analýzu o penalizační metodu, označovanou jako lasso metoda, která provádí výběr proměnných z...The European Commission annually publishes a European Innovation Scoreboard (EIS) as a tool to measure the innovation performance of the EU Member States. This thesis extends the analysis published in the EIS 2018 in two different manners. The first part, a clustering analysis, examines the partition of the EU Member States to innovation performance groups. The thesis comes with a unique scheme of partition created by using hierarchical clustering. A comparison with the existing scheme shows that the general trends are similar in both schemes. The only main exception is the differentiation of the British Isles and Luxembourg apart from the other high performing countries. The proposed scheme provides insight about the within-cluster similarities, such as the similarity of Finland, Sweden and Denmark and their relative distinction from France, although they belong to one cluster. The second part, a regression analysis, attempts to examine the impact of innovations on real labour productivity. Contrary to existing literature, we do not find a statistically significant relationship between productivity and the components of the EIS. Additionally, the analysis is extended by the lasso estimation that provides a variable selection. The latter approach improves our findings and identifies four EIS...Institut ekonomických studiíInstitute of Economic StudiesFaculty of Social SciencesFakulta sociálních vě

Dynamic Network Risk across main U.S. sectors

We study the effects of financial networks formed by the connectedness of stock return volatilities within sectors of the S&P 500 Index. We test whether the risk arising from dynamic volatility connections is priced in the cross-section of stock returns. Separately, for each sector, we estimate the dynamic network formed by firm-level realized volatilities from 2006 to 2018. We study how connectedness differs across sectors. Comparing the sector results, we conclude that there is a homogeneous pattern that describes the development of volatility connectedness. The pattern holds across all sectors throughout the studied period and is shaped by major financial events. We create risk factors that attempt to assess the risk arising from dynamic volatility connections. For each sector, we create a factor model that we test using the Fama-Macbeth regression. The results provide evidence that the created risk factors are priced in four out of ten sectors, that is, significant results are found in the Energy, Financials, Industrials, and Consumer Discretionary sectors

Innovation Indicator Analysis in the European Union: A Machine Learning Approach

The European Commission annually publishes a European Innovation Scoreboard (EIS) as a tool to measure the innovation performance of the EU Member States. This thesis extends the analysis published in the EIS 2018 in two different manners. The first part, a clustering analysis, examines the partition of the EU Member States to innovation performance groups. The thesis comes with a unique scheme of partition created by using hierarchical clustering. A comparison with the existing scheme shows that the general trends are similar in both schemes. The only main exception is the differentiation of the British Isles and Luxembourg apart from the other high performing countries. The proposed scheme provides insight about the within-cluster similarities, such as the similarity of Finland, Sweden and Denmark and their relative distinction from France, although they belong to one cluster. The second part, a regression analysis, attempts to examine the impact of innovations on real labour productivity. Contrary to existing literature, we do not find a statistically significant relationship between productivity and the components of the EIS. Additionally, the analysis is extended by the lasso estimation that provides a variable selection. The latter approach improves our findings and identifies four EIS..

Dynamické síťové riziko na amerických akciových trzích

We study the effects of financial networks formed by the connectedness of stock return volatilities within sectors of the S&P 500 Index. We test whether the risk arising from dynamic volatility connections is priced in the cross-section of stock returns. Separately, for each sector, we estimate the dynamic network formed by firm-level realized volatilities from 2006 to 2018. We study how connectedness differs across sectors. Comparing the sector results, we conclude that there is a homogeneous pattern that describes the development of volatility connectedness. The pattern holds across all sectors throughout the studied period and is shaped by major financial events. We create risk factors that attempt to assess the risk arising from dynamic volatility connections. For each sector, we create a factor model that we test using the Fama-Macbeth regression. The results provide evidence that the created risk factors are priced in four out of ten sectors, that is, significant results are found in the Energy, Financials, Industrials, and Consumer Discretionary sectors.Tato práce zkoumá propojenost volatility akcií v rámci jednotlivých sektorů ak- ciového indexu S&P 500. Zabýváme se zejména tím, zda riziko, které vzniká z finanční propojenosti, je naceněno v akciových výnosech. Pro každý z deseti sektorů odhadujeme dynamickou síť, která je vytvořena z realizovaných volatilit akcií v letech 2006 až 2018. Zkoumáme, jak se finanční propojenost liší napříč sektory. Z porovnání výsledků vyvozujeme, že finanční propojenost se vyvíjí podobně napříč všemi sektory po celé zkoumané období. Úroveň propojenosti je určována významnými událostmi, které ovlivňují celé finanční trhy. Ze sek- torových sítí poté vytváříme rizikový faktor, který se snaží znázornit riziko vyplývající z finanční propojenosti, která je směrově orientovaná a dynamická. Pro každý sektor vytváříme faktorový model, který odhadujeme pomocí Fama- MacBethovy metody. Empirické analýza prokazuje nacenění faktoru v případě čtyř sektorů, nacházíme statisticky významné výsledky u rizikových faktorů v sektoru energetickém, finančním, průmyslovém a v sektoru spotřebního zboží.Institute of Economic StudiesInstitut ekonomických studiíFakulta sociálních vědFaculty of Social Science

Fixation with Rtm6 Makes Preforming for Dry Fiber Placement more Economical and Avoids Influence of Additional External Material

Infusion process begins with preforming, where multiple CF layers are formed into three-dimensional shape and are fixed between fibre and mould or in-between the different fibre layers. Manual fixing process with magnet is time-consuming non-reproducible step, which requires additional carrier material and higher manufacturing tolerances. For automated fixing [1],[2] the most time-consuming and cost-ineffective process is binder application onto CF. The influence of the binder's compatibility with the resin to be infiltrated and the effect of added amount of binder on mechanical properties of cured component must also be taken into account [3]. Clear evidence of not completely dissolved binder could be observed in cured component [4]. This paper introduces a new automated fixing method, which applies the adhesive force of RTM6 resin. Due to subsequent infiltration with the same resin no indication of previously applied matrix and mechanical influences could be determined [5]. First, parameter study has been conducted for identification of holding force and quantity of resin according to layer number and position. Approximately 0,094 g/m² resin is required for first layer to hold 8 subsequently applied layers. Thereafter, robot based end-effector is developed to distribute the resin and investigated theoretically and practically on 4m diameter Pressure-Bulkhead

Low Temperature Co-fired Ceramics Plasma Generator for Atmospheric Pressure Gas Spectroscopy

AbstractAccurate and reliable measurements of gas composition are very important in science and industry applications. One way to accomplish this task is to measure spectrum of plasma gas discharge. In our work we propose integrated microcell for optical measurements of gas discharge at atmospheric pressure. This device is fabricated using Low Temperature Co-fired Ceramics (LTCC) technology. Investigated gas is excited in buried air-cavity, placed between two electrodes. Discharge is created using high alternating voltage (30kV). Optical signal is then transmitted through an integrated optical fiber to the miniature spectrometer. Because different gases have different emission lines, plot of light intensity vs. wavelength provides information about molecular composition of the investigated gas sample. In this work, design, fabrication and performance of the LTCC- based gas discharge chamber is presented. Spectral measurements are performed for air, argon and nitrogen. Moreover, influence of gas flow rate on obtained emission spectrum is discussed

Microfluidical Microwave Reactor for Synthesis of Gold Nanoparticles

Microwave treatment can reduce the time of selected syntheses, for instance of gold nanoparticles (AuNPs), from several hours to a few minutes. We propose a microfluidic structure for enhancing the rate of chemical reactions using microwave energy. This reactor is designed to control microwave energy with much higher accuracy than in standard devices. Thanks to this, the influence of microwave irradiation on the rate of chemical reactions can be investigated. The reactor consists of a transmission line surrounded by ground metallization. In order to deliver microwave energy to the fluid under test efficiently, matching networks are used and optimized by means of numerical methods. The monolithic device is fabricated in the low temperature co-fired ceramics (LTCC) technology. This material exhibits excellent microwave performance and is resistant to many chemical substances as well as high temperatures. Fabrication of the devices is described in detail. Measurements of microwave parameters are performed and differences between simulation and experiment results are discussed. Finally, the usefulness of the proposed device is proved in exemplary synthesis