The thesis deals on the theory of partial wetting of a wall, whereby a relation between the velocity of a droplet moving along an inclined plane and time is derived. There are explained basic definitions coherent to the theory of partial wetting. According to divergence of a normal vector of the droplet surface, there is developed a technique for mathematical evaluation of the component of dynamic adhesive force. Within the scope of diploma paper, there was an experimental measurement performed, whereat a velocities of droplets of various volumes and at different inclination angles on four analyzed surfaces were determined. By using non-linear regression, unknown parameters such as the adhesion coefficient, the component of a dynamic adhesive force, initial and terminal velocity of a droplet were evaluated from the experiment results. Within the thesis there was performed a simulation of droplet motion on an inclined plane in ANSYS Fluent. Conclusion includes an assessment and a comparison of results obtained, and new procedures that may be helpful at further research of descending droplet.

1 AbstraktEN The diploma thesis deals with linear mixed effects models. In the first chap- ter, we discuss parameter estimation and hypothesis testing in the linear mixed effects models. The second chapter is dedicated to graphical diagnostics. We look at the suitable diagnostic plots for residuals and random effects estimates. It is closely described, how the violations of assumptions affect the diagnostic plots. In the third chapter we have consequences of the violations of assumptions on the parameter estimates and results of hypothesis testing for fixed effects. 1

The goal of this diploma thesis is to design and develop a system for collecting, processing and storing data from large IoT networks. The developed system introduces a complex solution able to process data from various IoT networks using Apache Hadoop ecosystem. The data are real-time processed and stored in a NoSQL database, but the data are also stored  in the file system for a potential later processing. The system is optimized and tested using data from IQRF network. The data stored in the NoSQL database are visualized and the system periodically generates derived predictions. Users are connected to this system via an information system, which is able to automatically generate notifications when monitored values are out of range.