This thesis describes a software tool used to study the biomechanics of elbow extension. The tool is an integrated computer program for data processing and graphing, and is used in the development of an EMG driven muscle model for dynamic ballistic muscle movement. The software is designed to manipulate data from a series of isometric and dynamic elbow extension experiments. Inputs include recordings from a torque sensor, load cell, and potentiometer as well as EMG from triceps and biceps muscles. Calculations are made to determine the effect of gravity, the Moment of Inertia, as well as the force-EMG, force-length and force-velocity relationships. Additionally, fatigue tests and postactivation potentials are analyzed. Modeling parameters are derived from isometric controls and verified by applying them to data from dynamic experiments. The principal design requirements for this software tool were adaptability, user control, and data processing protocol verification. The majority of data processing parameters can be controlled and adjusted by the user. Care was taken during software coding so that it would be easy to modify each step of the protocol and if necessary, add additional processing. Data is displayed on interactive graphs to provide control feedback to the user. / Thesis / Master of Engineering (MEngr)

This thesis covers the subject of information extraction from Web. The main objective is the design and implementation of an administration interface for an extraction system implemented as web application on Java platform. The application provides an editor for extraction tasks specification in the form of interactive graphs. It includes the possibility to upload and process an ontology from a file and generate graph according to selected ontology properties. The solution ensures integration with the FITLayout tool.

Nowadays, interactive visualizations have been one of the most used tools in Big Data fields for the purpose of searching for relationships and structured information in large datasets of unstructured information. In this project, these tools are applied to extract structured information from students following Self-Regulated Learning (SRL). By means of an interactive graph, we are able to study the paths that the students follow in the learning materials. Our visualization supports the investigation of patterns of behaviour of the students, which later could be used, for example, to adapt the study program to the student’s needs in a dynamic way or offer guidance if necessary.