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In this contribution, we describe the activities and promotion programs installed at the Bonn-Rhein-Sieg University as an institution and at the Department of Computer Science respectively for increasing the total number of computer science students and in particular the female rate. We report about our experiences in addressing gender aspects in education and try to evaluate the outcome of our programs with respect to our equal rights for women strategy. We propose a closer look at mental self-theories enabled by E-portfolios to address also gender issues in Computer Science. Moreover, reasons are identified and discussed which may be responsible for the reduced interest in particular of female young adults to choose a computer science study program.
Quantifying Interference in WiLD Networks using Topography Data and Realistic Antenna Patterns
(2019)
Avoiding possible interference is a key aspect to maximize the performance in Wi-Fi based Long Distance networks. In this paper we quantify self-induced interference based on data derived from our testbed and match the findings against simulations. By enhancing current simulation models with two key elements we significantly reduce the deviation between testbed and simulation: the usage of detailed antenna patterns compared to the cone model and propagation modeling enhanced by license-free topography data. Based on the gathered data we discuss several possible optimization approaches such as physical separation of local radios, tuning the sensitivity of the transmitter and using centralized compared to distributed channel assignment algorithms. While our testbed is based on 5 GHz Wi-Fi, we briefly discuss the possible impact of our results to other frequency bands.