The recorded music industry experienced declining revenue from 1998 to 2014, but it saw a return to growth in 2015. This thesis uses a sample of 17 countries to explore the determinants behind this revenue expansion, and to assess whether this sales growth can be sustained. I examine the impact of eight factors on the overall, physical, digital, and streaming music revenue and revenue per capita, as well as the digital and streaming revenue share. The eight independent variables include the GNI per capita, the total population, the percentage of the young people, the percentage of the young females, the gross enrollment rate in secondary education, the percentage of Internet users, the percentage of mobile cellular subscriptions, and the percentage of fixed broadband subscriptions. Based on my study, the fixed broadband subscription rate has an impact that is both statistically significant and economically important on the streaming revenue share, which makes it the most important indicator for the industry’s potential sustainable development. The percentage of the young population also shows statistical significance and economic importance for explaining the overall and physical revenue per capita, but it has no effect on the digital and streaming revenue share. Also, although the Internet penetration rate and the mobile cellular subscription rate are statistically insignificant for the digital or streaming revenue share, point estimates suggest that these factors have important economic impacts.

Web services have made many kinds of data and computing services available. However, to use web services often requires significant programming efforts and thus limits the people who can take advantage of them to only a small group of skilled programmers. In this dissertation, I will present a tool called Gneiss that extends the spreadsheet model to support four challenging aspects of using web services: programming two-way data communications with web services, creating interactive GUI applications that use web data sources, using hierarchical data, and using live streaming data. Gneiss contributes innovations in spreadsheet languages, spreadsheet user interfaces and interaction techniques to allow programming tasks that currently require writing complex, lengthy code to instead be done using familiar spreadsheet mechanisms. Spreadsheets are arguably the most successful and popular data tools among people of all programming levels. This work advances the use of spreadsheets to new domains and could benefit a wide range of users from professional programmers to end-user programmers.

A series of experimental studies was performed to investigate two separate fluid impingement flow systems intended for removal of particles from a surface or deposition of particles onto a surface. One of these flow systems is generated using a nozzle that incorporates both tilted jets and suction to create what we call a "bounded vortex flow", consisting of an annular swirling jet and a wall-normal vortex with axial upflow into a suction outlet. The other flow system is generated by a combination of acoustic streaming and substrate heating from an ultrasonic source. The primary methods used in the study for flow field measurements included laser-induced fluorescence (LIF) and particle-image velocimetry (PIV). Thermocouples are utilized for gathering temperature information from the ultrasonic induced flow. For the bounded vortex flow, different jet/suction flow rates and different nozzle-substrate separation distances were examined. In the acoustic-generated flow system, different acoustic intensities and transducer-substrate separation distances and different choices of substrate material were examined. Both flow systems achieve high levels of shear stress on the impingement surface via a combination of flow oriented toward and/or away from the surface and via formation of vortex structures near the impingement surface. In the bounded flow configuration, the vortex flow is oriented with axis normal to the impingement surface, whereas in the acoustic-generated flow a series of vortex rings form with axes parallel to the impingement surface. For both flow fields, conditions are observed with high impingement surface shear stress that are well suited to particle removal from the impingement surface. However, as the variables controlling the flows are varied, other conditions are observed in which the flow fields become unstable, leading to oscillatory flows that generally have much smaller shear stress values on the impingement surface. The rate of fluid mixing, as characterized by upward and downward flows normal to the impingement surface, is also generally decreased after these flow transitions have occurred, implying that the unstable flows will be less suited for both particle deposition on and particle removal from the impingement surface.

This work deals with the development of a new label-free detection technique called Pulsed Streaming Potential (PSP). Its novelty relies on the adaptation of a classical electrokinetic phenomenon (streaming potential) into a tool which can evaluate molecular interplay in label-free fashion. Implementation of PSP to microfluidic platforms allowed the label-free sensing of binding events to plastic (modified and unmodified) surfaces. It was demonstrated the use of real time PSP in plastic microfluidic platforms for determination of kinetic parameters of the interaction of proteins and plastic surfaces. Moreover, initial change of PSP after adsorption of proteins showed to be proportional to the bulk concentration of proteins and it was used for quantification of Lysozyme in the nanomolar range. Several approaches were studied to manipulate the surface of microfluidic channels in order to improve selectivity of PSP through reduction of non-specific adsorption. These approaches included the fabrication of composite surface of polyacrilic acid (PAA) and polyethylene glycol acrylate (PEGA) on cyclic olefin copolymer microchannels, as well as adsorption of nanospheres on COC-PEGA channels.

The aim of the thesis 'Development of on-demand portals. Netflix and his original programming extension' is to map the production, marketing and distribution strategies of Netflix, the largst on- demand platform in the world, in context with the current state of linear television broadcasting. It can be pressumed, that both the on-line distribution and original content programming of on-demand platforms will contitnue to grow. The thesis examines the programming of Netflix, in regard to other international platforms and also compares the business and marketing strategies of Netflix's biggest rival - cable television HBO. The last chapter reveals current environment of on-demand distribution in the Czech Republic, in contect with Netflix's expansion on the Czech market in the newt two years and its possible operation on local market.

This thesis deals with the design and implementation of an optimizer and a transformer of relational queries. Firstly, the thesis describes the theory of the relational query compilers. Secondly, we present the data structures and algorithms used in the implemented tool. Finally, the important implementation details of the developed tool are discussed. Part of the thesis is the selection of used relational algebra operators and design of an appropriate input. Input of the implemented software is a query written in a XML file in the form of relational algebra. Query is optimized and transformed into physical plan which will be executed in the parallelization framework Bobox. Developed compiler outputs physical plan written in the Bobolang language, which serves as an input for the Bobox. Powered by TCPDF (www.tcpdf.org)

The main objective of this thesis is the description and characterization of media content generated within the community around the game League of Legends inside the phenomenon of e-sports. The central issue is the definition of metagame term and anchoring its functions in different types of media content rising in the community around the game League of Legends. The output of this work is analysis of different types of media content, in which the term metagame is designed, interpreted and transmitted to the audience.

The video streaming applications contribute to a major share of the Internet traffic. Consequently, monitoring and management of video streaming quality has gained a significant importance in the recent years. The disturbances in the video, such as, amount of buffering and bitrate adaptations affect user Quality of Experience (QoE). Network operators usually monitor such events from network traffic with the help of Deep Packet Inspection (DPI). However, it is becoming difficult to monitor such events due to the traffic encryption. To address this challenge, this thesis work makes two key contributions. First, it presents a test-bed, which performs automated video streaming tests under controlled time-varying network conditions and measures performance at network and application level. Second, it develops and evaluates machine learning models for the detection of video buffering and bitrate adaptation events, which rely on the information extracted from packets headers. The findings of this work suggest that buffering and bitrate adaptation events within 60 second intervals can be detected using Random Forest model with an accuracy of about 70%. Moreover, the results show that the features based on time-varying patterns of downlink throughput and packet inter-arrival times play a distinctive role in the detection of such events.

Off-highway vehicles are on the verge of switching from analog to digital video camera technology (VCT), which offers better video quality and new features but adds complexity to the system. This thesis project aims to implement the digital VCT to the display computer CCpilot VA intended for off-highway vehicles. In this project the differences between analog and digital VCTs were reviewed and then a demo displaying a live digital camera video feed on the embedded Linux based display computer CCpilot VA was implemented with Qt and QML. More specifically, different GStreamer pipelines were tested, as Qt uses GStreamer to play video, and camera settings were changed using the ISO 17215 standard.  The demo displayed a live digital camera video feed with high quality, low latency and high frame rate on the VA by using a GStreamer pipeline utilizing hardware decoding. The results have shown that digital video cameras perform better than analog cameras, primarily because digital cameras have better video quality. The attempts to simultaneously display a video feed and a Graphical User Interface created by Qt have been made. However, they were only successful with poor video performance. A zero-copy link between the GStreamer pipeline’s decoder and sink element must be used to obtain good video performance.

Adaptive streaming is a popular technique that allows quality adaption for videos based on the current playback conditions. The purpose of this thesis is to investigate how chunks in video files downloaded from YouTube correlate to each other. We investigate how the chunk size characteristics depend on the category and encoding of the video. The main focus is to analyze the chunk sizes of the video, focusing on distinctness between 360$^\circ$ and 2D videos. This is performed using the YouTube API. The videos are downloaded and analysed using youtube-dl and mkv-info. The results show that chunk sizes for adjacent qualities have higher correlation and that videos having a similarity between scenes have higher correlation. In addition, 360$^\circ$ videos differ primarily from regular 2D videos by the amount of qualities used and a generally higher correlation for all qualities.