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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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Tracking of Moving Objects in Video
Folenta, Ján ; Bartl, Vojtěch (referee) ; Herout, Adam (advisor)
This bachelor thesis deals with the issue of detection, tracking and counting vehicles in different directions in video. To deal with this problem, modern techniques of object detection and tracking using convolutional neural networks are used. The goal of this work is to achieve highest possible accuracy of vehicle counting while maintaining the processing of video recordings in real-time. The problems of the implemented method for detection and tracking are solved by analyzing and working with the trajectories of vehicles. With accuracy of 90,94% and total score of 0,8829, this work participated in AI City Challenge 2020, where it placed 6th.
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Knowledge Discovery in Object Relational Databases
Chytka, Karel ; Vrážel, Dušan (referee) ; Chmelař, Petr (advisor)
The goal of this master's thesis is to acquaint with a problem of a knowledge discovery and objectrelational data classification. It summarizes problems which are connected with mining spatiotemporal data. There is described data mining kernel algorithm SVM. The second part solves classification method implementation. This method solves data mining in a Caretaker trajectory database. This thesis contains application's implementation for spatio-temporal data preprocessing, their organization in database and presentation too.
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Individual, social and cultural factors shaping the use of amphetamine-type stimulants in Europe
Martens, Marcus-Sebastian ; Mravčík, Viktor (advisor) ; Radimecký, Josef (referee) ; Kachlík, Petr (referee)
Background: Amphetamine-type stimulants (ATS) encompass a varied assortment of substances that possess comparable pharmacological effects and stimulant characteristics. ATS display diversity in patterns of use among different substances and users' sociodemographic characteristics. The utilization of ATS is associated with both favorable and unfavourable outcomes. The biopsychosocial model of substance use provides a comprehensive framework for understanding ATS use. Aims: The primary objective of this study is to cultivate a thorough comprehension of the motivating factors driving individuals to initiate, cease, escalate, and/or curtail their ATS use. Material and methods: In a mixed methods approach, qualitative interviews were conducted to explore distinct groups of ATS users and one group of non-ATS users. These qualitative interviews then informed standardized quantitative computer-assisted personal interviews that utilized a range of (standard) instruments. The interviews were carried out in five European Union member states, and a minimum of five years had to elapse between the first usage of or exposure to ATS and the conducted interview. In the qualitative study arm, a total of 279 individuals were interviewed. Among them, 17% were identified as currently dependent on ATS, 20% were formerly...
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Tracking of Moving Objects in Video
Folenta, Ján ; Bartl, Vojtěch (referee) ; Herout, Adam (advisor)
This bachelor thesis deals with the issue of detection, tracking and counting vehicles in different directions in video. To deal with this problem, modern techniques of object detection and tracking using convolutional neural networks are used. The goal of this work is to achieve highest possible accuracy of vehicle counting while maintaining the processing of video recordings in real-time. The problems of the implemented method for detection and tracking are solved by analyzing and working with the trajectories of vehicles. With accuracy of 90,94% and total score of 0,8829, this work participated in AI City Challenge 2020, where it placed 6th.
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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.
|
|
|
Knowledge Discovery in Object Relational Databases
Chytka, Karel ; Vrážel, Dušan (referee) ; Chmelař, Petr (advisor)
The goal of this master's thesis is to acquaint with a problem of a knowledge discovery and objectrelational data classification. It summarizes problems which are connected with mining spatiotemporal data. There is described data mining kernel algorithm SVM. The second part solves classification method implementation. This method solves data mining in a Caretaker trajectory database. This thesis contains application's implementation for spatio-temporal data preprocessing, their organization in database and presentation too.
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