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Home Smart Wiring with Independent Sources
Doktor, Viktor ; Uher, Václav (referee) ; Kadlec, Radim (advisor)
The output of our work is complete proposal of the building wiring, the photovoltaic power plant proposal and technical report. In the first part we find the theoretical information concerning the proposal of the house wiring, explanations of basic terms and principles of technical documentation. We can find also an overview of known intelligent systems and a brief description. In the second part we describe itself proposal of concrete building, step by step. We can find a description of a created program to control building. The third part is focused on theoretical information about photovoltaics. Here we explain the basic principle, the limits of technology, materials and the panel structure. In the fourth part we proceeded to the actual plant proposal. Here we find the principle and a block diagram of system and description of the components of the plant, evaluation of production and energy consumption. Drawings of the technical documentation wiring as a photovoltaic power plant, distributor scheme and its layout can be found in the technical report, in Attachment.
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Optical character recognition from image data
Marinič, Michal ; Uher, Václav (referee) ; Burget, Radim (advisor)
The thesis is concerned with optical character recognition from image data with different methods used for character classification. In the first theoretical part it focuses on explanation of all important parts of system for optical character recognition. The latter practical part of the thesis describes an example of image segmentation, the implementation of artificial neural networks for image recognition and create simple training set of data for the evaluation of the network. It also describes the process of training Tesseract tool and its implementation in a simple application EasyTessOCR for character recognition.
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Computational tasks for solving parallel data processing
Rexa, Denis ; Uher, Václav (referee) ; Mašek, Jan (advisor)
The goal of this diploma thesis was to create four laboratory exercises for the subject "Parallel Data Processing", where students will try on the options and capabilities of Apache Spark as a parallel computing platform. The work also includes basic setup and use of Apache Kafka technology and NoSQL Apache Cassandra database. The other two lab assignments focus on working with a Travelling Salesman Problem. The first lab was designed to demonstrate the difficulty of a task where the student will face an exponential increase in complexity. The second task consists of an optimization algorithm to solve the problem in cluster. This algorithm is subjected to performance measurements in clusters. The conclusion of the thesis contains recommendations for optimization as well as comparison of running with different number of computing devices.
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Segmentation of microscopic brain structures
Láska, Samuel ; Uher, Václav (referee) ; Burget, Radim (advisor)
This thesis is involved in image processing of medical data and its implementation using Java programming language. The main contribution of this thesis is creation of algorithms for feature extraction from 3D data and subsequent verification of the results for the issue of imagining 3D brain data, and creation of image filters and their implementation in the program RapidMiner. Consequently, the segmentation process is created at the 2D and 3D level, and output of 3D level segmentation are segmented brain structures. Furthermore, segmentation algorithms were compared on the basis of the final form of segmented structures and this approach was compared with other works.
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PLC simulation using TwinCat tool
Krátký, Martin ; Uher, Václav (referee) ; Mašek, Jan (advisor)
Bachelor project is about options in TwinCat 2 for programming the programmable logic controller (PLC). As part of the work will be described the principle of the PLC and PLC uses nowadays. The principe of developing tool TwinCAT will be described and an overview of the programming languages that standard IEC / EN 61131-3. The main contribution of this work is to create a program description in TwinCAT development tool in version 2. The main result will be a simulation of robotic arm created in TwinCAT version 3 and for this simulation will also be created graphical interface in Visual Studio in language C#.
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A tool for generating a random configuration of a cyber arena
Matisko, Maroš ; Kolařík, Martin (referee) ; Uher, Václav (advisor)
The master's thesis is focused on the design and implementation of a tool for generating configuration named Ansible. The result of using this tool is generated configuration, which contains random values chosen according to specified parameters and it was deployed on a virtual testing infrastructure. The theoretical part describes approaches of network automation in the process of deploying and configuration of network devices called Infrastructure as code. It also describes programme Ansible, which will be using the output of the implemented tool. The practical part of the thesis is focused on designing the functionality and internal structure of the tool, implementation of the tool and testing implemented tool as well as generated configuration.
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Musical genre classification
Káčerová, Erika ; Říha, Kamil (referee) ; Uher, Václav (advisor)
The aim of this bachelor thesis is creating a system for automatic music genre recognition. The thesis deals with two main issues, which are feature extraction of a genre and machine learning process. For the purpose of feature extraction a source code is written in JAVA programming language based on jAudio library. Six machine learning models are created in RapidMiner Studio software. The most appropriate one of them, Neural Networks method is then improved and tested on different parts of songs from database.These database contains 250 training songs and 25 test songs from five music genres: classical music, disco, drum and bass, hip hop and rock.
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Image similarity measurement using points of interest
Jelínek, Ondřej ; Uher, Václav (referee) ; Burget, Radim (advisor)
This paper presents a new object detection method. The method is based on keypoints analysis and their parameters. Computed parameters are used for building a decision model using machine learning methods. The model is able to detect object in the picture based on input data and compares its similarity to the chosen example. The new method is described in detail, its accuracy is evaluated and this accuracy is compared to other existing detectors. The new method’s detection ability is by more than 40% better than detection ability of detectors like SURF. In order to understand the object detection this paper describes the process step by step including popular algorithms designed for specific roles in each step.
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Multiple sclerosis detection
Kopuletý, Michal ; Mangová, Marie (referee) ; Uher, Václav (advisor)
This thesis is focused on detecting multiple sclerosis lesions from magnetic resonance images. Correctly retrieved lesions are very important for medical diagnosis. Detection of lesions using machine learning techniques is quite challenging because of large variability in size, shape and position of lesions in the brain. In the practical part is designed base software, which after completion will classify pixels, so that is possible to find lesions of multiple sclerosis. For classification will be used Support vector machine. Theoretical part describes multiple sclerosis, basic operations performed with biomedical images and data classification.
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