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Analysis of retinal nerve fiber layer for diagnosis of glaucoma
Vodáková, Martina ; Malínský, Miloš (referee) ; Odstrčilík, Jan (advisor)
The master thesis is focused on creating a methodology for quantification of the nerve fiber layer on photographs of the retina. The introductory part of the text presents a medical motivation of the thesis and mentions several studies dealing with this issue. Furthermore, the work describes available textural features and compares their ability to quantify the thickness of the nerve fiber layer. Based on the described knowledge, the methodology to make different regression models enabling prediction of the retinal nerve fiber layer thickness was developed. Then, the methodology was tested on the available image dataset. The results showed, that the outputs of regression models achieve a high correlation between the predicted output and the retinal nerve fiber layer thickness measured by optical coherence tomography. The conclusion discusses an usability of the applied solution.
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Data-driven sensors and their applications
Pakr, Jiří ; Dobrovský, Ladislav (referee) ; Škrabánek, Pavel (advisor)
Soft sensors are a gradually expanding technique in the field of industrial measurement. These sensors are computer programs that provide additional data using previously acquired data in a similar way to conventional hardware sensors. The additional data is obtained using predictive models based on machine learning methods such as neural networks or support vector machines. This work mainly includes a research on the function, structure and creation of soft sensors. It also describes machine learning, the distribution of its algorithms and introduces the methods commonly used in the field of virtual sensors. Towards the end, the author describes possible future development of soft sensors and the direction of further applications.
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Modelling and Analysis of Logistics Processes by Applying Process and Data Mining Techniques
Rudnitckaia, Julia ; Wang, Hao (referee) ; Zendulka, Jaroslav (referee) ; Hruška, Tomáš (advisor)
In this thesis, we propose an approach for modelling hidden and unknown processes and subprocesses in the example of a seaport logistics area. Having the underlying process model makes it possible to exploit more advanced algorithms since deviations and main paths are becoming visible and better controlled. The obtained model is the foundation for the core research of this work and will be enriched with key performing indicators and their forecast by applying advanced process mining, statistics, and machine learning techniques. The main difference of the approach is that we take as a target variable not any specific value, but the object - a process variant or a process type with a set of parameters. Bottleneck analysis, from one side, and predictive analysis, on the other hand, are enforced with context-aware information, especially with these additional objective process attributes. Furthermore, the support of the descriptive ("As is") current process model with certain notation and the integration with relevant bottleneck and predictive methods compromise the advantages of the approach. The work primarily focuses on the design of algorithms and methods for supporting logistics data analysis. However, it can be adjusted and applied to other areas accordingly, which makes the approach flexible and versatile. The result of the work is the framework for unstructured process modelling and the key process parameters predictive method. This analysis of processes with their attributes might be used for decision-making systems and process maps in future.
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The financial analysis of DEVELOP MOST s.r.o.
Nyklová, Anna ; Sieber, Martina (advisor) ; Loužek, Marek (referee)
The bachelor thesis will deal with the financial analysis of the company DEVELOP MOST s.r.o. The thesis is divided into a theoretical and a practical part. In the theoretical part, there is an explanation of the basic concept and the methods and ratios used in the financial analysis. In the practical part, individual ratios will be applied to the selected company. The aim was to reveal the strengths and weaknesses of the company. In addition, the thesis will contain a segmentation analysis of the market in which the company operates as well as an evaluation and comparison of the main competitors.
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The early literacy development and its variability in children at risk of dyslexia: The prediction models of literacy deficits.
Medřická, Tereza ; Kucharská, Anna (advisor) ; Špačková, Klára (referee) ; Bytešníková, Ilona (referee)
In the context of both projects Enhancing literacy development in European languages, work package 2 and The early literacy development and its variability in children at risk of specific learning disabilities, we monitored child development of literacy in preschool age and during the first years of school attendance in a four-stage process. The research group (n = 76) compound of typically developing children (BV = 37), children with the family risk of dyslexia (RR = 22) and children with specific language impairment (NVŘ = 17). We evaluated development of phonemic/phonological, lexical/semantic and morphological/syntactic skills, preliteracy skills and early literacy skills. The last fifth test stage included the assessment of literacy development in 3rd graders. First, a group of children with literacy deficits (n = 9) was identified via the latent profile analysis method. Subsequently, four predictive models of literacy deficits for each stage were created by means of lasso or L-1 penalized regression method. Predictive models follows the trend that until literacy skills are fully automatized (preschool age and the 1st grade), phonemic and phonological skills predominate, but later - after the formal learning to read and write proceeds - early literacy skills are becoming more and more...
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Data-driven sensors and their applications
Pakr, Jiří ; Dobrovský, Ladislav (referee) ; Škrabánek, Pavel (advisor)
Soft sensors are a gradually expanding technique in the field of industrial measurement. These sensors are computer programs that provide additional data using previously acquired data in a similar way to conventional hardware sensors. The additional data is obtained using predictive models based on machine learning methods such as neural networks or support vector machines. This work mainly includes a research on the function, structure and creation of soft sensors. It also describes machine learning, the distribution of its algorithms and introduces the methods commonly used in the field of virtual sensors. Towards the end, the author describes possible future development of soft sensors and the direction of further applications.
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The early literacy development and its variability in children at risk of dyslexia: The prediction models of literacy deficits.
Medřická, Tereza ; Kucharská, Anna (advisor) ; Špačková, Klára (referee) ; Bytešníková, Ilona (referee)
In the context of both projects Enhancing literacy development in European languages, work package 2 and The early literacy development and its variability in children at risk of specific learning disabilities, we monitored child development of literacy in preschool age and during the first years of school attendance in a four-stage process. The research group (n = 76) compound of typically developing children (BV = 37), children with the family risk of dyslexia (RR = 22) and children with specific language impairment (NVŘ = 17). We evaluated development of phonemic/phonological, lexical/semantic and morphological/syntactic skills, preliteracy skills and early literacy skills. The last fifth test stage included the assessment of literacy development in 3rd graders. First, a group of children with literacy deficits (n = 9) was identified via the latent profile analysis method. Subsequently, four predictive models of literacy deficits for each stage were created by means of lasso or L-1 penalized regression method. Predictive models follows the trend that until literacy skills are fully automatized (preschool age and the 1st grade), phonemic and phonological skills predominate, but later - after the formal learning to read and write proceeds - early literacy skills are becoming more and more...
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Financial analysis of the company
HOUŽVIČKOVÁ, Lucie
The aim of the thesis is to evaluate the financial situation of the selected company, to identify sources of inefficiencies and create proposals to improve the current situation. The first part presents the theoretical background of financial analysis as a basis to frame out the methodology and to perform the following practical analysis. For the evaluation of the financial situation, the company financial statements and the financial statements of a group of companies from the same field for the period 2012 to 2016 are used. Both fundamental and technical analysis are applied. In the technical part, the techniques of horizontal and vertical analysis, net working capital analysis, analysis of financial ratios, DuPont analysis, Grünwald solvency index and index IN05 are used. All the company results are compared with the results of the group of companies from the same industrial sector. The outcome of the analysis is that the company went through a crisis during the given period, however, over the last two years it has been in a situation of a strong financial health. It has excellent liquidity, low debt ratio and positive profitability. The company should focus mainly on attracting new qualified workers and on investments of redundant financial means.
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The financial analysis of DEVELOP MOST s.r.o.
Nyklová, Anna ; Sieber, Martina (advisor) ; Loužek, Marek (referee)
The bachelor thesis will deal with the financial analysis of the company DEVELOP MOST s.r.o. The thesis is divided into a theoretical and a practical part. In the theoretical part, there is an explanation of the basic concept and the methods and ratios used in the financial analysis. In the practical part, individual ratios will be applied to the selected company. The aim was to reveal the strengths and weaknesses of the company. In addition, the thesis will contain a segmentation analysis of the market in which the company operates as well as an evaluation and comparison of the main competitors.
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Usability of modern evaluation methods for the financial situation in the company (indicators EVA, MVA and the cost of capital)
MINARČÍKOVÁ, Jana
The aim of this diploma paper is to evaluate the applicability and usability of modern evaluation methods for the financial situation in the company, focused on indicators EVA, MVA, and the cost of capital. Firstly, there are some basic terms defined in the theoretical part. The methodological part describes single the steps of calculations that were done in order to find out the answers for these hypothetical assumptions: 1.Evaluate whether it is possible to substitute difficult to detect characteristics of modern EVA and MVA indicators by different, easier indicator which will have at least the same explanatory power. 2.EVA indicator is able to predict the future development of a business as well as traditional predication models. These hypotheses were tested on a sample of 100 Czech firms in the construction industry. The data source was the database Albertina, which was purchased through a grant GAJU 053/2016/S. In the practical part are introduced results and its interpretations. The thesis conclusion is focused on the evaluation of particular hypotheses. The analysis proved: irreplaceability of indicators EVA and MVA in the success evaluation of company in certain year and inability of indicators EVA, MVA and predicting models as well to predict the future evolution
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