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Multi-Dimensional Data Vizualization
Jambor, Marek ; Přibyl, Jaroslav (referee) ; Vyskočil, Michal (advisor)
This work deals with the problems connected to the visualization n-Dimensional data, where n>3, includes the retrieval of elementary methods, incl.field possibilities of an application. Further this work deals with problems connected to the projection and implementation of the module of visualization of n-dimensional data. Implementation was applied in programming environment Java with upgrade Java 3D.
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NoSQL: Support of Multidimensional Data Storage
Hrivnák, Jan ; Zendulka, Jaroslav (referee) ; Volf, Tomáš (advisor)
This bachelor's thesis deals with posibilities of storing multidimensional data in NoSQL databases. It compares suitability of several different databases for storing trajectories of moving 2D objects. Experiments with MongoDB were carried out to find the best way to store trajectories and create indexes over them. This thesis also provides a simple demonstration program in Python which works with MongoDB API.
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Interactive clustering approaches in single-cell cytometry
Urban, Nicole Aemilia ; Šmelko, Adam (advisor) ; Stuchlý, Jan (referee)
Flow cytometry allows inexpensive monitoring of large and diverse cell populations using fluorescent markers, providing immense applications in studying biological properties of blood and tissues as well as diagnostics in the clinical setting. Recent methodological advances highlight automatic clustering as a tool of choice for data analysis, and many clustering algo- rithms were developed for various use cases. However, the applicability of such algorithms in biology and medicine remains challenging unless the tools expose user-friendly, interactive interfaces that are accessible to domain ex- perts. The goal of the thesis is to review the available methods that allow such interaction and supervision of the clustering process by the user, specif- ically focusing on interfaces desirable in clinical setting that does not require the user to interact with programming environments. As the main practi- cal result, the thesis should design a new tool that builds upon previously developed methodology (iDendro, gMHCA), allowing the application of the researched methodology on real datasets. By using proper data visualization techniques, the end user should be able to interact with the dataset in a way that is both intuitive and useful for producing biologically relevant results.
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The impact of grandchildren on retirement timing: evidence from SHARE data
Srna, Jan ; Pertold-Gebicka, Barbara (advisor) ; Votápková, Jana (referee)
This thesis examines the role of grandchildren's existence in the retirement timing decision- making process of grandparents. Previous literature has focused mostly on other aspects of retirement and potential causes that can affect its timing. Using the Two-Stage least squares estimation on the SHARE dataset, representing 17 European countries and Israel, we estimate the desired effect with respect to various data limitations (age groups, gender, child existence). Residential proximity is used as the instrument for estimation. Having at least one grandchild yields a statistically significant result that increases on average the likelihood of retirement by 19% when compared to a non-grandparent while holding other factors constant. As a secondary outcome, the estimated effect of an additional child on retirement likelihood is negative. JEL Classification C36, C51, J26 Keywords grandchild, retirement, Instrumental variable, SHARE, IV, wide-ranging data, 2SLS Title The impact of grandchildren on retirement timing: evidence from SHARE data
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Depth of two-dimensional data
Dočekalová, Denisa ; Šír, Zbyněk (advisor) ; Hlubinka, Daniel (referee)
In this paper we summarize the basic information about halfplane depth function. It consists of two parts. In the first part we deal with the halfplane depth based on the distribution function, we describe its basic properties and define the concepts of depth contours, central regions and the halfplane median. We also deal with these concepts in the rest of the paper with the main focus on the halfplane median. In the second part of this work we deal with the halfplane depth based on the random choice with the main focus on data visualization. The used methods for visualization are the display of depth contours and the bagplot. This work includes pictures of depth contours for specific distributions which were gained by implementation of an algorithm in the software Mathematica. 1
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NoSQL: Support of Multidimensional Data Storage
Hrivnák, Jan ; Zendulka, Jaroslav (referee) ; Volf, Tomáš (advisor)
This bachelor's thesis deals with posibilities of storing multidimensional data in NoSQL databases. It compares suitability of several different databases for storing trajectories of moving 2D objects. Experiments with MongoDB were carried out to find the best way to store trajectories and create indexes over them. This thesis also provides a simple demonstration program in Python which works with MongoDB API.
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Multi-Dimensional Data Vizualization
Jambor, Marek ; Přibyl, Jaroslav (referee) ; Vyskočil, Michal (advisor)
This work deals with the problems connected to the visualization n-Dimensional data, where n>3, includes the retrieval of elementary methods, incl.field possibilities of an application. Further this work deals with problems connected to the projection and implementation of the module of visualization of n-dimensional data. Implementation was applied in programming environment Java with upgrade Java 3D.
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