The diploma thesis shows the status of the automotive industry in the Czech Republic. It shows the trends in the Czech automotive industry in short theoretical presentation. There is a trend of the future competition from developing countries, other problems are growing raw material prices or government's limits in CO2 production. The companies connected to the automotive industry are reacting. The relevant information about the status and reactions of the Czech automotive industry companies, especially at the time of the crisis, was gained. The work answers the main question: How will the situation look like in the Czech automotive industry after the end of the crisis.

Streaming analytics deploy Kleene pattern queries to detect and aggregate event trends against high-rate data streams. Despite increasing workloads, most state-of-the-art systems process each query independently, thus missing cost-saving sharing opportunities. Sharing complex event trend aggregation poses several technical challenges. First, the execution of nested and diverse Kleene patterns is difficult to share. Second, we must share aggregate computation without the exponential costs of constructing the event trends. Third, not all sharing opportunities are beneficial because sharing aggregation introduces overhead. We propose a novel framework, Muse (Multi-query Snapshot Execution), that shares aggregation queries with Kleene patterns while avoiding expensive trend construction. It adopts an online sharing strategy that eliminates re-computations for shared sub-patterns. To determine the beneficial sharing plan, we introduce a cost model to estimate the sharing benefit and design the Muse refinement algorithm to efficiently select robust sharing candidates from the search space. Finally, we explore optimization decisions to further improve performance. Our experiments over a wide range of scenarios demonstrate that Muse increases throughput by 4 orders of magnitude compared to state-of-the-art approaches with negligible memory requirements.

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This master’s thesis determines qualities of the application used as a supporting tool in decision-making processes and which is useful for automatization of time series analysis. The thesis describes solution created by following the formulated criteria. It shows examples of use of the created application in praxis and interprets the outputs.

This thesis deals with the implementation of the software for automated stock trading based on trend indicators and oscillators. It describes the various signals that are provided by formations in charts and technical indicators, but also the possibility of using advanced artificial intelligence methods. This document describes entire development process of the software from individual parts to the folding of these parts into one system. It focuses on the optimization processes of individual parts, as well as a complete system. This thesis also deals with the testing of the system on historical data and its application on the latest data. It introduces the future plans, deployment options to the real market and its further improvement in order to develop ideal business system capable of autonomous thinking and trading.

The diploma thesis focuses on assessment of given financial indicators of chosen company. It is predicted the future development of chosen financial indicators using appropriate statistical methods. It contains assessment of financial situation of analysed company and solutions of its present situation.

Studien syftar till att undersöka vad fem identifierade trender på applikationen TikTok förmedlar samt vilken respons som trenderna bemöts med. Vidare syftar studien till att förstå och förklara det gemensamma flödet på TikTok. Studien undersöker även hur barn och ungdomar mellan 12-18 år upplever social interaktion genom TikTok, hur de beskriver användningen av applikationen samt eventuella risker och möjligheter. Studien tillämpar en kvalitativ metod genom en textanalys och intervjuer. Resultatet visar att trenderna består av innehåll som relaterar till verkligheten och även innehåll som användare återskapar. Responsen på trenderna är kommentarer om det som händer i mikrovideornas innehåll. Det framkommer även att TikToks gemensamma flöde och funktioner möjliggör stor spridning av innehåll och digitala beteenden. De unga respondenterna använder TikTok som underhållning, ett tidsfördriv och som ett socialt verktyg i vänskapsrelationer. Jargongen på TikTok ska vara ironisk enligt de unga respondenterna men samtidigt förekommer det hat och kränkningar. Slutligen kan innehåll på TikTok spridas viralt vilket utgör både möjligheter och risker. Opassande innehåll kan även vara en risk men samtidigt uppfattas TikTok som en arena för social interaktion.

In an attempt to preserve research integrity, the aim of this study is to examine how often statistical results are being misrepresented in empirical studies by using terms such as “marginally significant,” “approached significance,” or “trend toward significance” when interpreting findings. The use of these terms gives ambiguous significance to results that are in fact nonsignificant, which threatens future research by contributing to issues such as the replication crisis. For this study, data were coded from 437 empirical articles published online in The Journal of Personality and Social Psychology (JPSP) over a 4-year period between 2017 and 2020. According to our findings, although misrepresentation of statistical results are prevalent within JPSP articles, rates decreased significantly over the four-year time period examined. Additionally, as the number of studies published in JPSP increased each year during the four-year period examined, there may be a potential rise in representatively sound studies and decrease of misrepresentation within this discipline.

The aim is to study the trends of cigarette smoking from 2001 to 2012 using a California representative sample in the US. Data was taken from the California Health Interview Survey (CHIS) from 2001 to 2012, which is a population-based, biennial, random digit-dial telephone survey of the non-institutionalized population. The CHIS is the largest telephone survey in California and the largest state health survey in the US. 282,931 adults (n = 184,454 with age 18–60 and n = 98,477 with age >60) were included in the analysis. Data were weighted to be representative and adjusted for potential covariance and non-response biases. During 2001–2012, the prevalence of current smoking decreased from 18.86 to 15.4 % among adults age 18–60 (β = −0.8, p = 0.0041). As for adults age >60, the prevalence of current smoking trend decreased with variations, started from 9.66 % in 2001, slightly increased to 9.74 % in 2003, but then gradually decreased, falling to 8.18 % in 2012. In 2012, there was a 14 % reduction of daily smoking adults age 18–60 (OR 0.84, 95 % CI 0.76–0.93, p = 0.0006) compared to 2001, while no significant reduction of daily smoking was observed for those age >60. The reductions of smoking prevalence for adults younger than 60 are encouraging. However, there is a concern for smoking cessation rates among those older than 60 years of age, particularly for African Americans.

Today, digital development is happening at such a high rate that security is not as prioritized as it should be. When security is prioritized away, there is a high risk that vulnerabilities arise that malicious actors would like to exploit. It can be for accessing sensitive information, financial gain or simply bringing harm. In order for IT-security personnel to be able to more easily prevent and focus efforts on the vulnerabilities that are current today, this study aims to answer the following question: What is the trend of the most prevalent vulnerabilities? What is the trend of product owners with the most vulnerabilities? What is the trend based on the severity linked to the vulnerabilities? What is the trend of the impact on confidentiality, integrity, and accessibility? To answer the questions, a quantitative data analysis was done on the database from the National Vulnerability Database (NVD) together with the dataset from the Common Weakness Enumeration (CWE). The data set from CWE has been used to name and classify the vulnerabilities in NVD. Trends that have been identified in the analysis are as follows: injection, insufficient data authentication and uncontrolled resource consumption are vulnerabilities that have increased percentage every year since 2016. The impact of availability on the reported vulnerabilities declines as a percentage over the years. Vulnerabilities with a high impact on integrity, accessibility and confidentiality has decreased as a percentage.