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The diploma thesis is dealing with the analysis of the use of social networks by two canadian political parties and their leaders during the Canadian federal election 2015. The thesis refers to the theory of political communication, election campaigns and political marketing as the theoretical basis. It approaches the concept of Web 2.0 and identifies two major social media functions in political communication, dissemination of information and engagement. Use of social media and the representation of the these features is further analyzed by quantitative content analysis on social networks Facebook, Twitter and Youtube. The thesis builds on the past and present social networking research and can serve as a basis for further research into the use of social networks in political communication.

Diplomová práca sa zaoberá súčasnými prístupmi a praktikami Internetového marketingu. Cieľom práce je voľba a následná aplikácia nástrojov online marketingovej komunikácie, ktorými by sa zvýšilo povedomie o značke vybranej spoločnosti. Preskúmaním jednotlivých nástrojov internetového marketingu, práca navrhuje online komunikačný mix firmy s využitím sociálnych médií a online reklamy.

The diploma thesis deals with the assessment of the effectiveness of on-line communication with the application for DOX Centre for Contemporary Art in Prague. It focuses on clarifying the theoretical framework of principles of social networks, mapping new trends and approaches in on-line communication and marketing. Part of the work is given to the identification of the percentage of the visitors of DOX who only search for information about exhibitions and other related program via the Internet. The emphasis is on research of the share of real customer of DOX to fan base on the Facebook social network. To make on-line communication more effective the priorities are set for various on-line channels with the tool for monitoring of mentions on the internet related to DOX. According to the fact that Facebook is an important interactive channel for DOX, there is created detailed analysis of the publications of contributions and the resulting recommendations for implementation. In conclusion, DOX expresses the contribution of the diploma thesis.

This thesis focuses on the development of strategy for universal application of social networking in a school of pre-primary and primary education level and its subsequent application in a real school. It describes potential benefits of such application and discusses other ways of use of social networks in primary schools. In addition, in theoretical part it defines actors of school environment and information flows between them. Subsequently discusses about communication needs of these actors given the current communication tools and generational differences. The practical part is based on applying a specific strategy of social networks in a school in Slovakia along with the information and summarized results of this application.

The aim of the Masterâs thesis was to create a computational model for integration of the cogeneration unit into the smart thermal network. For the better use of waste heat from the selected cogeneration unit MOTORGAS MGM250 during the summer period, the absorption circuit was dimensioned and the appropriate trigeneration computational model was formed. In the theoretical part, the function, operation and heat performance of the cogeneration unit as well as the suitability of the connection of the cogeneration unit with the absorption chiller during the summer period were described. In the practical part, the operational data of the Faculty of Mechanical Engineering of the Brno University of Technology and the theoretical performance data from created cogeneration and trigeneration computational models were compared. Based on this comparison, the conclusion about the suitability of use of both computational models was made.

This master's thesis is focused on algorithmic trading on the forex market using artificial neural networks. In the introduction, there are generally described terms concerning the trading. Subsequently, in the following chapters, the thesis describes the theory of neural networks and their possible use. The practical part contains designed business strategies with neural networks. Inputs used in the network are indicators of technical analysis or directly price level. Business strategies have been implemented and tested. In the conclusion, there are summarized findings of individual business models.

This diploma thesis deals with the application of deep neural networks with focus on image segmentation. The theoretical part contains a description of deep neural networks and a summary of widely used convolutional architectures for segmentation of objects from the image. Practical part of the work was devoted to testing of an existing network architectures. For this purpose, an open-source software library Tensorflow, implemented in Python programming language, was used. A frequent problem incorporating the use of convolutional neural networks is the requirement on large amount of input data. In order to overcome this obstacle a new data set, consisting of a combination of five freely available databases was created. The selected U-net network architecture was tested by first modification of the newly created data set. Based on the test results, the chosen network architecture has been modified. By these means a new network has been created achieving better performance in comparison to the original network. The modified architecture is then trained on a newly created data set, that contains images of different types taken with various fundus cameras. As a result, the trained network is more robust and allows segmentation of retina blood vessels from images with different parameters. The modified architecture was tested on the STARE, CHASE, and HRF databases. Results were compared with published segmentation methods from literature, which are based on convolutional neural networks, as well as classical segmentation methods. The created network shows a high success rate of retina blood vessels segmentation comparable to state-of-the-art methods.

It is necessary to monitor networks namely for diagnostics, troubleshooting, detection of anomalies and suspicious header encapsulations. This thesis aims to design and implement a system for monitoring protocol structure on 10 Gb networks, which will be able to capture packets based on the sequence of encapsulated protocols. To achieve requested throughput some tasks like packet parsing and packet filtering were accelerated in FPGA. Flexibility is achieved by using a tool that maps P4 programs, which define packet parsing process, to VHDL language. Based on the information gained from packet parsing, flow records are created and stored via IPFIX protocol. This information is displayed through a graphical user interface in the form of protocol tree, whose nodes are associated with flow records.

This diploma thesis focuses on a face recognition from a video, specifically how to aggregate feature vectors into a single discriminatory vector also called a template. It examines the issue of the extremely angled faces with respect to the accuracy of the verification. Also compares the relationship between templates made from vectors extracted from video frames and vectors from photos. Suggested hypothesis is tested by two deep convolutional neural networks, namely the well-known VGG-16 network model and a model called Fingera provided by company Innovatrics. Several experiments were carried out in the course of the work and the results of which confirm the success of proposed technique. As an accuracy metric was chosen the ROC curve. For work with neural networks was used framework Caffe.