Suggested Reading: Advances in News Recommendation

Major news sites like Google News or Yahoo! News as well as social media sites like Facebook or Twitter provide their users with personalized recommendations. These recommendations are tailored to the users’ individual reading preferences and are based on advanced machine learning techniques. Researchers at AAU Klagenfurt, TU Dortmund, and the University of Antwerp have recently published a survey on intelligent techniques and open-sourced a software framework for benchmarking such algorithms in a realistic setting.

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. 

Master Thesis scan.net – Interactive Learning Platform for IT Security

Student: Andreas Schorn

Supervisor: Peter Schartner

 

Cyber security training is about training IT security experts and end users in the field of information security. Traditional teaching and learning methods, such as lectures and literature research, however, have been proven inadequate in the field of cyber security. Implementing basic security concepts in real-world environments is difficult for many people as they usually lack knowledge about the specific procedures. With the help of interactive exercises, an attempt is made in a practical way to implement these basic concepts in a realistic environment, and therefore facilitate better understanding of information security.

In this thesis an overview of different variants of cyber security training and cyber security exercises is given. Structure as well as implementation of such exercises, consisting of a secure exercise environment and hacking instructions, is explained in detail. The thesis contains approaches on how cyber security trainings can be implemented in higher education organisations and describes the development and evaluation of a cyber security training platform (scan.net) for lectures at the Alpen-Adria-Universität Klagenfurt.

 

 

 

 

 

 

 

Study in Italy

Master Studies: Applied Informatics, Information Management, Information & Communications Engineering

DOUBLE DEGREE – UNIVERSITÁ DEGLI STUDI DI UDINE

“One study – two degrees”
After completion of the Double Degree program, you will be awarded with one academic degree, which has the legal effect of Austria as well as the partner country; only one academic title shall be used.

Focuses:
Informatics, Information Management, Information and Communications Engineering & Electronic Engineering, Information and Communications Engineering & Multimedia Systems

University Stay

ERASMUS+ – UNIVERSITÁ DEGLI STUDI DI MILANO BICOCCA

Focus:
Date Science

Benefits:

  • Waving of tuition at the host and home university
  • Grants to cover the increased costs of living abroad
  • Good contacts and local support

More Information: