National Repository of Grey Literature 263 records found  previous11 - 20nextend  jump to record: Search took 0.00 seconds. 
Portraits of Vilém and Petr Vok of Rosenberg as compensatory aids for visually disabled
SMRŽ, Pavel
This bachelor thesis consists of a theoretical part and a practical part. The theoretical part is divided into four chapters. The first chapter focuses on the basic characteristics of portraiture in the history of art. The chapture describes selected artistic directions and their characteristic properties associated with portraiture. The next chapture focuses on the life of the last lords of Rosenberg - William and Petr Vok. The third chapture deals with Kratochvíle chateau, its appearance and history from the beginning of construction to the present. The last chapture deals with the topic of visually impaired people. This chapture outlines the issue of using compensatory aids - such as haptic models for these individuals. The aim of practical part of this bachelor thesis was to create haptic models for the blind and visually impaired by portraits William and Petr Vok from Rosenberg. Both models will be part of the exhibitions at Kratochvíle chateau.
System for Verifying the Minimum Resources Required to Run an Application
Žák, Jiří ; Doležal, Jan (referee) ; Smrž, Pavel (advisor)
The main goal of this bachelor thesis is to create a system for the verifying minimum resources required to run an application. The theoretical part deals with the topic of computer performance evaluation metrics and the principle of operation of the Linux operating system. The practical part describes how the design and implementation of the entire system, which uses BPF (Berkeley Packet Filter) technology, was created. The end of the work is completed by testing and evaluation of the whole work. The system was successfully deployed in the partner company BringAuto. It turned out, that the operating system is powerful enough to run applications.
Energy Harvesting for Industry 4.0 Applications
Gajdošík, Róbert ; Šimek, Václav (referee) ; Smrž, Pavel (advisor)
Cieľom tejto práce je demoštrácia možností využitia energy harvestingu v priemysle 4.0, so zameraním na prototyp samonapájacieho vibračného senzoru. Vrámci práce bol vykonaný výskum techník pre zhromažďovanie a spracovanie dát ako aj výskum ohľadom senzorového vybavenie budúceho prototypu.   V ďalšom kroku bol vykonaný výskum a získaný prehľad ohľadom energy harvesterov, metód presunu a manipulácie vyťaženej elektrickej energie, a spôsobu jej uchovania. Ďalej bol vybraný vhodný mikroprocesor s vhodnou výbavou ohľadom vstupu a výstupu napájania, energie a konektivity. Nakoniec implementácie boli vyriešené rozhrania medzi jednotlivými komponentami prototypu.   Po vyhodnotení ďalšieho postupu bolo rozhodnuté vyvinúť software pre plánované rozhrania medzi senzorom a procesorom, ako aj spracovávanie dát za použitia vzorkovania a rekonštrukcie analógového signálu za použitia analógovo-digitálneho meniča. Ďalej bola vyvinutá jednoduchá časť software pre detekciu anomálií v očakávaných frekvenčných pásmach daného objektu, a otestovaný jednoduchý kód pre využite subsystému BLE. Nakoniec tejto časti projektu boli preskúmané možnosti vylepšenia účinnosti využitia energie použitej pre napájanie mikroprocesora.   V poslednom kroku práce boli otestované všetky komponenty navrhnutého prototypu. V prvej časti bola otestovaná funkcionalita komponentov bez integrácie s ostatnými časťami systému. Bola testovaná presnosť vibračného senzoru, funkcionalita harvesteru, a otestované jednotlivé subsystémy mikroprocesoru. V druhej časti testovania boli testované interakcie jednotlivých komponentov, napríklad rozhranie medzi mikroprocesorom a vibračným senzorom, a testovanie korektnosti softvérových metód pre vypočítanie frekvencie monitorovaného objektu. V poslednom kroku testovania boli otestované množstvá enegie vyťažené piezoelektrickým efektom a porovnané s experimentálne overeným odberom energie kompletného obvodu. Následne boli tieto informácie využité k aproximácií ceny prototypu a jeho realizovateľnosti v praktickom priemyselnom prostredí. Výsledkom práce je funčný prototyp obvodu samonapájacieho vibračného senzoru a teoretický návrh efektívnejšej verzie založenej na experimentálnych metódach prenosu energie medzi harvesterom a úložistom energie, ako aj aproximácia jednotkovej ceny obvodu a vyhodnotenia jeho použiteľnosti v modernom priemysle.
Using Word-Association Games for Language Teaching
Babača, Martin ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This thesis explores the use of the word associative game Codenames in language learning, especially learning English as the second language. In order to achieve the goal, it addresses the problem of explaining semantic relations among words. The explanations take advantage of word sketches, provided by the Sketch Engine tool, and of word descriptions available in specialized English dictionaries. The implemented extension of the previously created engine for playing Codenames enables explaining the automatically suggested relations among the hint words and intended words in each game, motivating users for further exploration of the studied language.
Supporting Board Game Nemesis on Android Mobile Phone
Štěpánek, Miroslav ; Švec, Tomáš (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to create a mobile application for the board game Nemesis designed for the Android system, which will allow the user to find out information about the game components during the game. The solution consists of two main parts the first is a model created with the help of the Tensorflow library, which is responsible for the detection of these components. The second is the application itself, which receives results from the model and displays the resulting information to the user. This makes the game easier for the user and helps to speed it up. The resulting system can be modified so that the application can be used for other games.
Plot Analysis from Book Summaries and User Reviews
Rúček, Peter ; Dočekal, Martin (referee) ; Smrž, Pavel (advisor)
The aim of this work is to create a system for analysis and classification of plot keywords from summarized storylines and user reviews in English. The chosen problem is solved using a transformer-based machine learning technique. The created solution also implements data downloading and a dataset of user reviews and information about books was created, exceeding 23 million reviews and 900 thousand information about books. The system can predict what plot keywords the data contains. 
Named Entity Disambiguation in Slovak
Križan, Samuel ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
Thesis deals with the topic of named entity recognition and disambiguation. A basic system was created which includes all prequisitions necessary for named entity disambiguation in Slovak language. Part of the system is building of a knowledge base out of an export from Slovak Wikipedia. This was subsequently compared to knowledge base obtained from Wikidata, which revealed that the main contribution of Wikipedia knowledge base for Slovak language is greater coverage of entities with link to Slovak Wikipedia and better determination of entity classes. Apart from that, morfological dictionary of KNOT@FIT research group was updated, which yielded an improvement by 33-39 %. This work presumes possible utilization in relation to system extention by a disambiguation modul and enhancement of alternative names coverage.
Recognizing and Classification of Traffic Situations
Zbořil, Jiří ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to identify and classify dangerous situations from surveillance cameras, monitoring traffic. An example of such situations is dangerous standing near by the road and car crash, on which this work focuses. The created system uses object detector, analyzing average images in given interval, K nearest neighbor and K Means algorithm and re-detection of enlarged local area in a frame to select anomaly candidates. Detected objects, that do not belong on the road are eliminated by attaching created road mask. At the very last phase, the interval, together with the classification is determined. Calculated F1 score is 0.645, S4 score 0.535 and precision of classification 80 %.
Neural Networks for Autonomous Car Driving
Dopita, Marek ; Hradiš, Michal (referee) ; Smrž, Pavel (advisor)
In this work, the principles of neural networks are introduced with a focus on autonomous vehicles. Based on this information, a proposal for the implementation of a system is created, which allows to drive a car without a driver. It builds on tools that allow easy creation and testing of autonomous vehicles. It is CARLA simulator and ranking.The proposal divides vehicle routes into three different situations. Each situation requires the use of different sensors, so a specific autonomous agent is created that is able to recognize the situation and switch between different neural network designs. Each such network is specific in its inputs and is taught in a specific situation.Programs are created that are able to easily collect a data set using the CARLA Leaderboard. Then, a way is introduced to how the collected data can be divided into categories so that each category can be used to learn its neural network. 
Predicting Trajectories of Vehicles and Pedestrians for Driving Assistent Systems
Mudroň, Marek ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
This bachelor thesis deals with representation of a traffic scene by processing monocular video sequence. I try to predict a trajectory of detected vehicles in a short time horizon, based on created representation. Current approaches use multiple expensive sensors to gather instant information of environment. In the thesis I introduce technique, which is able to extract data from an environment by image processing techniques without the need of expensive sensors.  The result of this work is a system creating opportunity to reduce the sensor costs of a system for scene representation and  trajectory prediction of vehicles in the scene. In addition, comparison of models trained on differently processed data is provided, as well as data about how my system approximates the most reliable prediction models.

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