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Solar energy plants are one of the key options to serve the rising global energy need with low environmental impact. Aerosols reduce global solar radiation due to absorption and scattering and therewith solar energy yields. Depending on the aerosol composition and size distribution they reduce the direct component of the solar radiation and modify the direction of the diffuse component compared to standard atmospheric conditions without aerosols.
This work discusses how to use OSM for robotic applications and aims at starting a discussion between the OSM and the robotics community. OSM contains much topological and semantic information that can be directly used in robotics and offers various advantages: 1) Standardized format with existing tooling. 2) The graph structure allows to compose the OSM models with domain-specific semantics by adding custom nodes, relations, and key-value pairs. 3) Information about many places is already available and can be used by robots since it is driven by a community effort.
This paper introduces a random number generator (RNG) based on the avalanche noise of two diodes. A true random number generator (TRNG) generates true random numbers with the use of the electronic noise produced by two avalanche diodes. The amplified outputs of the diodes are sampled and digitized. The difference between the two concurrently sampled and digitized outputs is calculated and used to select a seed and to drive a pseudo-random number generator (PRNG). The PRNG is an xorshift generator that generates 1024 bits in each cycle. Every sequence of 1024 bits is moderately modified and output. The TRNG delivers the next seed and the next cycle begins. The statistical behavior of the generator is analyzed and presented.
In the context of the Franco-German research project Re(h)strain, this work focuses on a global system analysis integrating both safety and security analysis of international and/or urban railway stations. The Re(h)strain project focuses on terrorist attacks on high speed train systems and investigates prevention and mitigation measures to reduce the overall vulnerability and strengthen the system resilience. One main criterion regarding public transport issues is the number of passengers. For example, the railway station of Paris “Gare du Nord” deals with a bigger number of passengers than the biggest airport in the world (SNCF open Data 2014), the Atlanta airport, but in terms of passengers, it is only around the 23rd rank railway station in the world. Due to the enormous mass of people, this leads to the system approach of breaking out the station into several classes of zones, e.g. entrance, main hall, quays, trains, etc. All classes are analysed considering state-of-the-art parameters, like targets attractiveness, feasibility of attack, possible damage, possible mitigation and defences. Then, safety incidence of security defence is discussed in order to refine security requirement with regard to the considered zone. Finally, global requirements of security defence correlated to the corresponding class of zones are proposed.
Urban food systems consist of many stakeholders with different perspectives, different interests and different governance tools. This study aimed at developing potential future scenarios for the food system of Cologne by analysing the system with a Delphi approach. In our research-design, the suitability of the Delphi-method was evaluated not only as a tool for future modelling and scenario design, but also as a communication tool among the group of participants on a multi-stakeholder-platform. As a case study, the Food Policy Council of Cologne, Germany was used. Cologne can be seen as a forerunner among German cities in the development of a new urban food policy. Some of the successful steps to re-envisioning food as an urban system include joining the Milan Urban Food Policy Pact, the decision of the City Council to become an edible city and the establishment of a Food Policy Council. For the study it was important to capture participants’ visions of a common goal regarding the governance of the urban food system and also to identify mental ‘silos’. It was obvious that the municipality of Cologne together with the Food Policy Council made great efforts towards participatory processes to build a vision for a sustainable and regional food supply. However, many stakeholder-groups in the process still work exclusively among themselves and do not actively practice the confrontation with the viewpoints of other relevant groups. This supports the maintenance of ‘silos’ and leaves little room for face-to-face discussions. Therefore, the primary aim of this study is to explore key components of food provisioning in the future for Cologne while confronting all stakeholders (municipal administration and politicians, farmers and food activists) with the perspectives of all group members. We used a multi-stakeholder Delphi approach with 19 panellists to find out essential components of the municipal regional food provisioning system in Cologne. Unique in this Delphi study is the bringing together of municipal administration, regional urban farmers and food activists. The research is still on-going, but preliminary results show that more communication among all relevant actors, especially horizontally among different city departments, in the urban food system is needed.
The Life Cycle Assessment (LCA) approach is the most important tool in the evaluation of environmental (sustainability) impacts of products and processes. We used the method to conduct an impact analysis with regard to raw material inputs (pulp) for the German paper production industry. In our analysis, we compare the environmental effects of primary sulphate pulp, scrap paper pulp and grass-based pulp and estimate their impacts in the impact categories "greenhouse gas emissions", "eutrophication" as well as "energy and water consumption". Furthermore, we discuss the opportunities of the methodical approach and some general problems and limits of the application of a LCA. In conclusion, we found environmental advantages for the use of grass as an alternative resource in the German paper production industry, especially in the fields of transport and water consumption.
Seit 2012 wird an der Hochschule Bonn-Rhein-Sieg die Studieneingangsphase im Qualitätspakt Lehre gefördert. Ein wesentliches Anliegen im Projekt „Pro-MINT-us“ ist die Einbeziehung der gesamten Hochschule, um keine isolierten Maßnahmen anzubieten, sondern die im Projekt entwickelten Lehrideen nachhaltig zu verankern.
Quantifying the spectrum occupancy in an outdoor 5 GHz WiFi network with directional antennas
(2018)
WiFi-based Long Distance networks are seen as a promising alternative for bringing broadband connectivity to rural areas. A key factor for the profitability of these networks is using license free bands. This work quantifies the current spectrum occupancy in our testbed, which covers rural and urban areas alike. The data mining is conducted on the same WiFi card and in parallel with an operational network. The presented evaluations reveal tendencies for various aspects: occupancy compared to population density, occupancy fluctuations, (joint)-vacant channels, the mean channel vacant duration, different approaches to model/forecast occupancy, and correlations among related interfaces.
More and more low-power wide-area networks (LPWANs) are being deployed and planning the gateway locations plays a significant role for the network range, performance and profitability. We choose LoRa as one LPWAN technology and evaluated the accuracy of the Received Signal Strength Indication (RSSI) of different chipsets in a laboratory environment. The results show the chipsets report significantly different RSSI. To estimate the range of a LPWAN beforehand, path loss models have been proposed. Compared to previous work, we evaluated the Longley-Rice Irregular Terrain Model which makes use of real-world elevation data to predict the path loss. To verify the results of that prediction, an extensive measurements campaign in a semi-urban area in Germany has been conducted. The results show that terrain data can increase the prediction accuracy.