FlowEmu: An Open-Source Flow-Based Network Emulator

When analyzing the impact of a communication system on the Quality of Experience (QoE) of an interactive application, simulation and mathematical modeling typically require reimplementation or modeling of the application under test and only provide insights in terms of selected Key Performance Indicators (KPIs), which raises the need for network emulation. In this demo, we present FlowEmu, an open-source flow-based network emulator that allows the user to manipulate the underlying model and analyze various statistics in real-time via an easy-to-use Graphical User Interface (GUI), by using interactive game streaming as an example application

Genetic algorithms for automatic feature selection in a textureclassification system

This paper describes the use of genetic algorithms as feature selectors in a texture classification system. This is part of a system developed within a research project concerning the classification of genuine texture. An attempt is made to underline why an automatic feature selector is a useful part of the texture classification system. Furthermore a way of including the genetic algorithms into the system and the necessary feedback structure is explaine

Knowledge Transfer Quality Model Implementation - An Empirical Study in Product Engineering Contexts

Employee turnover, especially of experienced employees, is a constant challenge for companies as they are confronted with a loss of knowledge which they must compensate for. This leads to an accepted need to successfully transfer knowledge. Knowledge transfer has been reviewed in literature by multiple disciplines, whereas this paper focuses on a product engineering context. In this context, empirical research results show that knowledge transfer situations, e.g., communication of complex product specifications, can be improved regarding the speed of knowledge transfers by so-called interventions. Based on those findings, the quality of knowledge transfers is investigated further. Velocity-dependent, as well as quality-dependent interventions, are summarized in an intervention catalog. Whereas the effect of those velocity-dependent interventions has been investigated in empirical studies, the quality-dependent interventions have not yet been implemented in an industrial setting. This paper, therefore, describes the design and results of a workshop with experts from the area of knowledge management as well as from product development of universities and companies. The workshop was used to validate previously developed interventions and further add quality-dependent interventions. Further, the implementation of selected interventions in a product engineering context, using a Live-Lab as a research environment, is presented. The interventions intend to improve the quality of knowledge transfers in specific knowledge transfer situations. As this is validated by an empirical implementation study, the validity of this approach is justified

Time- and Frequency-Domain Dynamic Spectrum Access: Learning Cyclic Medium Access Patterns in Partially Observable Environments

Upcoming communication systems increasingly often tackle the spectrum scarcity problem through the coexistence with legacy systems in the same frequency band. Cognitive Radio presents popular methods for Dynamic Spectrum Access (DSA) that enable coexistence. Historically, DSA meant a separation solely in the frequency domain, while in recent years it has been extended through the dimension of time, by employing Machine Learning to learn semi-deterministic and cyclic medium access patterns of the legacy system that are observed through channel sensing. When this pattern is learnable, then a new system can utilize a neural network and predict future medium accesses, thus steering its own medium access. We investigate this novel and more fine-grained version of DSA, propose a predictor and show its capability of reliably predicting future medium accesses of a legacy system in an aeronautical coexistence scenario. We extend the predictor to the case of partial observability, where only a narrowband receiver is available, s.t. observations are limited to a single sensed channel per time slot. In particular, we propose a custom loss function that is tailored to partially observable environments. In the spirit of Open Science, all implementation files are released under an open license

Konzeption eines Software-Lifecycle-Managementsystems (SLM) zur Unterstützung und Beschleunigung von Softwareentwicklungsprozessen

In dieser Arbeit wird ein Konzept entwickelt und beispielhaft implementiert, welches den Lebenszyklus von Softwareprodukten abbildet. Dieses wird Software-Lifecycle-Management-System genannt (SLM-System). Es wird ein flexibel einsetzbares Werkzeug zur Verfügung gestellt, welches ein beliebiges, gewähltes Vorgehen bei der Softwareentwicklung unterstützt. Hierbei liegt ein besonderes Augenmerk auf dem gesamten Entwicklungsprozess, vom Auftragseingang bis hin zur Wartung der Software, bei der generell die meisten Kosten entstehen. Weiterhin wird die Softwareentwicklung in bisher nicht unterstützen Bereichen verbessert, durch die Möglichkeit der Einbindung geeigneter Entwicklungswerkzeuge. Die Unterstützung einer parallelen Softwareentwicklung in einem Entwicklungsteam ist durch das integrierte Workflow-Management und das flexible Lebenszyklusmodell gegeben. Durch die Verwendung der .NET-Architektur wird das SLM-System plattformunabhängig und der Einsatz von Webservices gestattet die Verwendung des SLM-Systems in heterogenen Netzwerken. Anhand des Einsatzes des SLM-Systems beim Redesign der Software ProfiPlus wird das Konzept des SLM-Systems in der Praxis erprobt und Tauglichkeit zur Unterstützung des Entwicklungsprozesses gezeigt. Insbesondere wird daran die Eignung des SLM-Systems zur Unterstützung des Softwareentwicklungsprozesses in Bereichen gezeigt, in denen es bis jetzt kaum oder gar keine Unterstützung gibt, und die Möglichkeit, als flexible Basis zur Integration von beliebigen Softwareentwicklungsumgebungen zu dienen

Knowledge Transfer Quality Improvement - The Quality Enhancement of Knowledge Transfers in Product Engineering

Developing a new product generation requires the transfer of knowledge among various knowledge carriers. Several factors influence knowledge transfer, e.g., the complexity of engineering tasks or the competence of employees, which can decrease the efficiency and effectiveness of knowledge transfers in product engineering. Hence, improving those knowledge transfers obtains great potential, especially against the backdrop of experienced employees leaving the company due to retirement, so far, research results show, that the knowledge transfer velocity can be raised by following the Knowledge Transfer Velocity Model and implementing so-called interventions in a product engineering context. In most cases, the implemented interventions have a positive effect on knowledge transfer speed improvement. In addition to that, initial theoretical findings describe factors influencing the quality of knowledge transfers and outline a setting to empirically investigate how the quality can be improved by introducing a general description of knowledge transfer reference situations and principles to measure the quality of knowledge artifacts. To assess the quality of knowledge transfers in a product engineering context, the Knowledge Transfer Quality Model (KTQM) is created, which serves as a basis to develop and implement quality-dependent interventions for different knowledge transfer situations. As a result, this paper introduces the specifications of eight situation-adequate interventions to improve the quality of knowledge transfers in product engineering following an intervention template. Those interventions are intended to be implemented in an industrial setting to measure the quality of knowledge transfers and validate their effect

The Market for Vanilla in Germany and the United States

This market research paper has been prepared under the supervision of Prof. Dr. Wolfgang Veit of Cologne University of Applied Sciences and Prof. Dr. Carol Scovotti of University of Wisconsin-Whitewater in the course of the inter-university cross-border collaboration student research project “Export Opportunity Surveys (EOS)”. This study explores vanilla export opportunities to the German and US markets

First pan-Arctic assessment of dissolved organic carbon in lakes of the permafrost region

Lakes in permafrost regions are dynamiclandscape components and play an important role for climatechange feedbacks. Lake processes such as mineralizationand flocculation of dissolved organic carbon (DOC), oneof the main carbon fractions in lakes, contribute to thegreenhouse effect and are part of the global carbon cycle.These processes are in the focus of climate research, butstudies so far are limited to specific study regions. Inour synthesis, we analyzed 2167 water samples from 1833lakes across the Arctic in permafrost regions of Alaska,Canada, Greenland, and Siberia to provide first pan-Arcticinsights for linkages between DOC concentrations andthe environment. Using published data and unpublisheddatasets from the author team, we report regional DOCdifferences linked to latitude, permafrost zones, ecoregions,geology, near-surface soil organic carbon contents, andground ice classification of each lake region. The lakeDOC concentrations in our dataset range from 0 to1130 mg L−1(10.8 mg L−1median DOC concentration).Regarding the permafrost regions of our synthesis, wefound median lake DOC concentrations of 12.4 mg L−1(Siberia), 12.3 mg L−1(Alaska), 10.3 mg L−1(Greenland),and 4.5 mg L−1(Canada). Our synthesis shows a significantrelationship between lake DOC concentration and lakeecoregion. We found higher lake DOC concentrationsat boreal permafrost sites compared to tundra sites. Wefound significantly higher DOC concentrations in lakesin regions with ice-rich syngenetic permafrost deposits(yedoma) compared to non-yedoma lakes and a weak butsignificant relationship between soil organic carbon contentand lake DOC concentration as well as between ground icecontent and lake DOC. Our pan-Arctic dataset shows that theDOC concentration of a lake depends on its environmentalproperties, especially on permafrost extent and ecoregion, aswell as vegetation, which is the most important driver of lakeDOC in this study. This new dataset will be fundamental toquantify a pan-Arctic lake DOC pool for estimations of theimpact of lake DOC on the global carbon cycle and climatechange

The Architecture of the Ara Platform for Mobile Agents

We describe a platform for the portable and secure execution of mobile agents writtenin various interpreted languages on top of a common run-time core. Agents may migrate at anypoint in their execution, fully preserving their state, and may exchange messages with otheragents. One system may contain many virtual places, each establishing a domain of logicallyrelated services under a common security policy governing all agents at this place. Agents areequipped with allowances limiting their resource accesses, both globally per agent lifetime andlocally per place. We discuss aspects of this architecture and report about ongoing work