Page 249 – University of Klagenfurt

The best of all universes? Science takes a look at Star Trek

Scientists representing a variety of specialist fields have come together at Alpen-Adria-Universität to explore the Star Trek phenomenon through the lens of their respective discipline. The results included a lecture series with lecture theatres consistently filled to capacity. The edited volume with the title “Set Phasers to Teach! Star Trek in Research and Teaching” was recently published, offering insights into the wealth of perspectives and delivering opportunities for thought-provoking impulses, even for die-hard Trekkies. We joined the co-editors Martin Gabriel (Department of History) and Wilfried Elmenreich (Department of Networked and Embedded System) for an interview. Former AAU staff members Stefan Rabitsch and John NA Brown were subsequently invited to add their statements.

Topic for a Master Thesis in Information Management

The following topic is offered at the Department of Applied Informatics:

“Analysis and design of an information and communication platform based on Confluence”

Web-based tools for information collection, information exchange and communication are nowadays common in many organisations. Typical examples are knowledge management systems, corporate wikis, discussion forums or file exchange systems.

Smaller companies are, however, often confronted with the problem that commercial solutions offer too much functionality for the planned use; at the same time, these system can only be adapted to the organisational requirements with some effort.

In the context of the master thesis the software system “Confluence” by the company Atlassian will be examined regarding its usability and applicability for a start-up company in the area of political and economic strategy development and communication. The expected result of the master thesis is a study of possible applications, limitations and alternatives to the mentioned software solution.

The topic is suitable for students of Information Management. Alternatively, the topic can also be worked on in the frame of a “Praxis” (Section 6.1 of the curriculum).

For further information, please contact Prof. Dietmar Jannach, Research Group Information Systems.

Master Thesis Detection of alpine activities using Smartphones

Student: Christoph Lagger

Supervisor: Peter Schartner

Unfortunately accidents in alpine environments happen on a daily basis, often during mountain hikes in summer or ski tours in winter. Besides standardized security beacons (e.g. avalanche beep) everybody carries a smartphone with multiple sensors (such as Accelerometers and Gyroscopes among others) with them. In emergency situations, time is crucial and an accurate and robust recognition system in form of a mobile application could trigger the chain of survival automatically and support rescue missions. In this thesis machine learning is used to determine current movement patterns or activities based on sensor data such as walking up/down, skiing down, pause, or in the worst case an emergency situation. We recorded a large dataset of actual movement patterns (7 days, 19 hours, 21 minutes and 22 seconds) from all available smartphone sensors during actual alpine activities. Movement data was analyzed and a comprehensive training dataset was created for further usage. The goal was to determine the best combination of sensors, algorithms, features and window size parameters to accurately detect said movement patterns. A framework was implemented to perform a series of experiments using 10-fold cross validation, evaluate its outcome and visualize movement data as well as simulate results. Evaluation results as well as simulation results showed that the Random Forest algorithm using data from the Gyroscope and Magnetometer sensor in combination with a 4-second sliding window and an overlap of 20%, utilizing the Root Mean Square, Mean, Signal Vector Magnitude, Energy, Variance, and Standard Deviation as features, achieved a promising F-Measure of 0.975.

Figure 1: Key activities and corresponding result of a simulation run using the most promising combination of algorithm, sensors, features and sliding window parameters.