Arvutitehnika bakalaureusetööd - Bachelor's theses

Permanent URI for this collectionhttps://hdl.handle.net/10062/42115

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Browsing Arvutitehnika bakalaureusetööd - Bachelor's theses by Author "Anbarjafari, Gholamreza, juhendaja"

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    Automated Data Extraction and Analysis for Arrayed Primer Extension Images
    (Tartu Ülikool, 2017) Haamer, Rain Eric; Anbarjafari, Gholamreza, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
    The Arrayed Primer Extension (APEX) method is used to detect Single-Nucleotide Polymorphism (SNP), deletion and insertion based diseases. The main method consists of washing different flourophores over oligonukleotites and then analysing which flourophore attached to identify the oligonukleotites. A crucial step in the APEX method is analysing the captured light from the flourophores when a laser excites them. The current method of analysing this data requires extensive manual review. This thesis describes a method of automating the data grid detection in the captured images which is currently a manual task. The second part describes the application of predictive methods for the data analysis of the four captured images and comparisons to the already existing clustering method.
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    Developing the behaviours for use in RoboCup 2015 based on rUNSWift architecture.
    (Tartu Ülikool, 2015) Keerdo, Rainer; Anbarjafari, Gholamreza, juhendaja; Tartu Ülikool. Loodus- ja tehnoloogiateaduskond; Tartu Ülikool. Tehnoloogiainstituut
    The RoboCup Standard Platform League has two teams, each consisting of five robots play football against each other in a semi-controlled setting. The robots used have the same hardware and modifications are not allowed. The purpose of this thesis was to find a method to improve the overall performance displayed during 2014 RoboCup and implement the method(s). During the course of the project, a new codebase, developed by team rUNSWift, was evaluated, tested and then adopted as it offered improvements compared to the Austin Villa codebase used in 2014. As the codebase offered only basic core functionality, a behaviour module needed to be implemented to offer both low- and high-level behaviours. The behaviours developed provide low-level functionality for movement, ball alignment and targeting and high-level functionality for basic soccer gameplay according to RoboCup 2015 rules. The individual strategy mimics the system used in 2014 with the main difference being the ability to recognize our teammates and then use that information to avoid collisions while trying to hit a ball that is in the common playing area of the two robots. The kick and walk performance appear more stable, as they are both dynamically generated using rUNSWift’s motion system. The walk is also offers greater configurability and needs careful calibration for tuning the input parameters.
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    Gesture Based Computer Controlling Using Kinect Camera
    (Tartu Ülikool, 2015) Demitševa, Sandra; Anbarjafari, Gholamreza, juhendaja; Tartu Ülikool. Loodus- ja tehnoloogiateaduskond; Tartu Ülikool. Tehnoloogiainstituut
    The main goal of the bachelor’s thesis was to develop an application that allows users to interact with a computer without using any intermediate devices that require physical contact. The resulting interface makes it possible to use the functionalities of a Windows desktop relying only on gestures, provided the computer meets the requirements of using a Kinect sensor and is equipped with one. Because the library used to track fingers is still in development, the functionalities are limited at this point. The possibilities for future development in human-computer interaction using vision based hand recognition are endless and the interaction will become more natural and effortless. As the equipment used to recognize hand poses is becoming more affordable and available, the possibility that mechanical devices which need physical contact will become obsolete becomes progressively more of a reality.