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Growing up in dysfunctional family
KOSTELECKÁ, Adéla
The diploma's thesis focuses on the topic of growing up in dysfunctional families with a focus on aggressive and auto-aggressive behavior. The thesis' aim is to describe the dysfunctional family and problem behavior based on professional sources and then to find out the impact of growing up in a dysfunctional family on an individual's life (especially in the area of problem behavior) with the help of research. The thesis introduces the basic concepts related to the family and the dysfunctional family, mentions the functions and types of the family, the importance of the development of the attachment and further defines problem behavior. The practical part focuses on the description of growing up in a dysfunctional family by individual respondents. In the practical part, qualitative research is used. A semi-structured interview is used for data collection. The data is processed using the thematic coding method.
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Awareness of Child Abuse and Neglect Syndrome in the context of the campaigne MeToo
KOSTELECKÁ, Adéla
Bachelor's thesis deals with the problematic of the abused and neglected child syndrome. The thesis' aim is to determine grammar school students' awareness of this problematic. Thesis introduces the main concepts concerning the CAN syndrome, mentions prevention options, different CAN syndrome forms and their consequences. Furthermore, selected institutions dealing with said syndrome are listed. The practical part is focused on the determination of grammar school students' awareness of the CAN syndrome and the #MeToo Campaign. Quantitative research is used in the practital part. In the final part, information determined via the survey is summarized.
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Content-Based Image Retrieval: from Primitive to Advanced Techniques
Kostelecká, Adéla ; Novozámský, Adam (advisor) ; Kleber, Florian (referee)
The Wienbibliothek im Rathaus, Vienna City Library, collected over 300 thousand posters scanned in high quality from the last 100 years. Browsing and searching in such a large dataset is beyond human power. Therefore, a project was set up in cooperation with the Technical University of Vienna to test the possibilities of automatic data annotation on a selected sample. One of the requirements was Content-based Image Retrieval - retrieving images based on their visual content. This thesis reviews these techniques that emerged over the last decades. We focus on simple techniques based on colour, texture, and shape, as well as more advanced algorithms using convolutional neural networks. We implement these methods and compare their retrieval effectiveness on par- ticular image datasets. Finally, we describe the functionality of a developed web application. 1
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Construction of G^1 continuous surfaces.
Kostelecká, Adéla ; Šír, Zbyněk (advisor) ; Bizzarri, Michal (referee)
This thesis introduces an algorithm that connects two Bézier patches indis- tinguishtably. The algorithm modifies patches to have a common tangent plane. We use the Chiyokura Kimura method to a tensor product Bézier surfaces and Bé- zier triangles. We ensure this type of continuity for multiple patches by replacing the control points with rational functions. These are called the Gregory patches. We prove that both of the methods connect two patches with G1 continuity. Fi- nally, we present the results of the algorithm on asymmetric icosahedron and on real geometric objects such as Standford Bunny. 1
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