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IEC-104 and MODBUS protocol conversion
Syskov, Mykyta ; Grenar, David (referee) ; Slavíček, Karel (advisor)
IEC 104 and ModbusRTU communication protocols are used for control, measurement and data collection in remote terminal units (RTUs) primarily in industrial automation, especially in the power industry. This bachelor’s thesis deals with methods of data conversion between these protocols. The theoretical part contains introductions to these protocols, followed by a description of proposed methods for mutual mapping of the items of individual protocols. The result of the work are scripts that are written in the Python language. These scripts implement the described designs. The operation algorithms are documented in detail in the practical part. Finally, using the UniPi G110 device and the xS51 extension from UniPi Technology, a demonstration of the functionality of this software solution is presented.
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Adaptive scanning based on lower resolution images
Dymáček, Michal ; Klapetek, Petr (referee) ; Pavera, Michal (advisor)
Tato diplomová práce se zabývá vývojem metody adaptivního skenování založené na obrázcích s nižším rozlišením, která má za cíl zkrátit dobu měření a otevřít tak nové možnosti metod SPM, konkrétně mikroskopie atomárních sil (AFM), pro aplikace např. v biologii a polovodičovém průmyslu. V prvním kroku navrhovaného přístupu je pořízen obrázek s nižším rozlišením, který je uměle zvětšen s využitím interpolace a dále zpracován pro tvorbu rychlostní mapy, která určuje rychlost skenování pro jednotlivé řádky druhého měření. Řádky protínající vyvýšené struktury jsou skenovány pomalu, čímž je zachována nutná přesnost, ale celková doba měření je snížena, jelikož jsou řádky obsahující pouze povrch substrátu skenovány zvýšenou rychlostí. Na základě rešeršní studie a provedených experimentů byl navržen přístup adaptivního skenování využívající skriptovací modul SPM mikroskopu LiteScope založený na programovacím jazyce Python. S využitím tohoto přístupu bylo dosaženo redukce doby měření o 30 % pro kalibrační mřížku TGQ1.
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Web platform for online marketing
Křivánek, Tomáš ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
The work focuses on the entire process of developing web application to facilitate the connection between creators of user-generated content and online marketing managers of companies. This marketing industry is relatively new in the Czech Republic, and there are currently no platforms that simplify the interaction between these mentioned participants. The development process begins with a careful collection and analysis of the requirements of potential users of this new system. Based on the gathered requirements, the system architecture is then designed using modern technologies. For the system development, a backend in the form of a REST API is chosen, programmed using the Python FastAPI framework. Additionally, the Vue framework will be utilized on the client side. Data storage will involve MySQL and MongoDB databases, along with a cloud storage solution. After the selection of specific technologies, the implementation of the system is described, as well as how the testing of the whole application was carried out.
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A Reduced Neural Network for Classifying the Presence of People in an Image
Stanček, Rastislav ; Rydlo, Štěpán (referee) ; Goldmann, Tomáš (advisor)
Táto práca sa zameriava na tému počítačového videnia, presnejšie, na binárnu klasifikáciu prítomnosti ľudí v obrazových dátach. Cieľom tejto práce je vytvoriť redukovanú neurónovú sieť s využitím metódy knowledge distillation. Klasifikácia a detekcia objektov je výpočtovo náročná operácia. Študentský model vytvorený pomocou knowledge distillation vykazuje ekvivalentnú presnosť, pričom je menší a má vyššiu inferenčnú rýchlosť v porovnaní s učiteľským modelom. Takýto model môže byť interdisciplinárne všestranný a to predovšetkým na koncových zariadeniach, ktoré majú relatívne slabé výpočtové schopnosti.
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Using of neural network for detection of heart rhythm disturbances from ECG data and accelerometer signal
Aleksandrenko, Borys ; Ředina, Richard (referee) ; Bulková, Veronika (advisor)
This bachelor's thesis addresses the issue of detecting heart rhythm disorders from EKG and accelerometer signals using machine learning. First, an analysis of the possibilities for detecting heart rhythm disorders from these signals was conducted through a theoretical review. In the next part, a methodology was proposed for detecting two rhythm disorders: inappropriate sinus tachycardia and chronotropic incompetence. The methodology was further supplemented with adaptive filtering of EKG signals using signals from the accelerometer. In the third part of the thesis, a database of samples was created for training machine learning models proposed in the methodology. The next section included the description and implementation of the models. In the fifth part of the thesis, an application for detecting heart rhythm disorders using the proposed methodology was developed in the Python programming language. Finally, a discussion and evaluation of the results were conducted.
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Application of Python programming language in image analysis and modeling of physical processes of graphene
Stehlíček, Kamil ; Képeš, Erik (referee) ; Bartošík, Miroslav (advisor)
In this thesis, we focus on evaluating experimental data using the Python programming language across three different physics problems dealing with graphene. The goals of the thesis are based on practical experiments that use gallium or gallium nitride to alter the electro-optical properties of graphene or experiments that require the simulation of charge propagation in graphene nanoelectronics. These tasks successively use image analysis and numerical simulations. The theoretical part of the thesis serves as a research and as an introduction to basic image processing algorithms and numerical simulation techniques. The practical part of the thesis then focuses on the evaluation of the success of each program, its implementation in practical evaluation and explanation of experimental results.
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Detection of Diseases Caused by Diabetes in Retinal Images
Zapletal, Michal ; Semerád, Lukáš (referee) ; Kavetskyi, Andrii (advisor)
The goal of this thesis is to design and implement an algorithm for detecting exudates and microaneurysms in colored retinal images. These diseases are the first signs of diabetic retinopathy and early detection is crucial. The proposed algorithm begins with preprocessing, where excess background is removed, contrast is enhanced using CLAHE and histogram stretching, and noise filtering is applied. Optic disc localization is based on iterative background removal and row and column variances. Exudates detection is performed based on gamma correction, thresholding and optic disc removal. Microaneurysm detection is based on morphological operations, hit-or-miss transformation and principal component analysis (PCA). The algorithm was tested on 4 datasets with accuracy 73,1 % for exudates and 73,3 % for microaneurysms. The resulting program could assist in automatic disease detection, which could potentially save time for doctors.
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Detekce typu a bodového ohodnocení kartiček ve hře Hobiti
Hlinský, Martin ; Kohút, Jan (referee) ; Vaško, Marek (advisor)
This thesis aims to create a card detector that can train a model that can detect the score of a card and its type using the synthetic generation of the dataset. The YOLOv8 model is used for training. The first step is to take pictures of the cards, which then go through a pre-processing stage so they do not contain background and are aligned. These pre-processed card images are combined with photos from other datasets in a generator that randomly translates, rotates, and otherwise simulates photos of possible card placements. This generator’s output is roughly 50 000 annotated images in the case of the Hobiti game, but different dataset sizes and pre-trained weights are compared in the experiments. The latest generation of trained detectors was validated on a real dataset for unbiased testing, and the most accurate model trained on purely synthetic datasets achieved precision up to 81.5 % according to the 50 metric. It is then possible to implement, for example, a point counter on the final detector, a prototype of which is also described in this paper.
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