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Predicting Future Location of a Moving Object
Kebísek, Ján ; Stríž, Rostislav (referee) ; Pešek, Martin (advisor)
This thesis deals with the design and the implementation of the application for predicting future location of a moving object. It describes a method for prediction based on the algorithm WhereNext. This algorithm obtains T-Patterns from a database of trajectories of objects, which represent frequent patterns of movement of objects, and those subsequently uses for prediction. The algorithm was implemented in programming language Java and its functionality was tested on a generated dataset of movement of cars.
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Hippocampal neuronal representation of a moving object in a novel spatial avoidance task
Ahuja, Nikhil ; Stuchlík, Aleš (advisor) ; Jiruška, Přemysl (referee) ; Telenský, Petr (referee)
In real world environments, animals need to organize their behavior relative to other moving animals or objects; when hunting a predator, when migrating in groups or during various social interactions. In all of these situations, the animal needs to orient relative to another moving animal/object. To understand the role of the hippocampus in this ability we adopted a two-step approach. We developed a task that would mimic important elements of this behavior in the laboratory. The task required the rats to assess not only their distance from the moving object but also their position relative to the object. We further studied how neurons in the hippocampal CA1 subfield encode the subject, the moving object and the environment in the behavioral paradigm and how do these representations interact among themselves. In rats, we aimed to characterize spatial behaviors relative to moving objects and to explore the cognitive mechanisms controlling these behaviors. Three groups of animals were trained to avoid a mild foot-shock delivered in one of three positions: either in front, on the left side, or the right side of a moving robot. Using different variations of the task, we also probed whether avoidance was simply due to increased noise level or size of the retinal image or appearance of the robot. As the...
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Predicting Future Location of a Moving Object
Kebísek, Ján ; Stríž, Rostislav (referee) ; Pešek, Martin (advisor)
This thesis deals with the design and the implementation of the application for predicting future location of a moving object. It describes a method for prediction based on the algorithm WhereNext. This algorithm obtains T-Patterns from a database of trajectories of objects, which represent frequent patterns of movement of objects, and those subsequently uses for prediction. The algorithm was implemented in programming language Java and its functionality was tested on a generated dataset of movement of cars.
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