Refine
H-BRS Bibliography
- yes (102) (remove)
Departments, institutes and facilities
- Fachbereich Informatik (32)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (32)
- Fachbereich Wirtschaftswissenschaften (27)
- Fachbereich Ingenieurwissenschaften und Kommunikation (25)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (22)
- Institut für Verbraucherinformatik (IVI) (14)
- Institut für Cyber Security & Privacy (ICSP) (11)
- Sprachenzentrum (4)
- Institut für IT-Service (ITS) (2)
- Institute of Visual Computing (IVC) (2)
Document Type
- Conference Object (102) (remove)
Year of publication
Has Fulltext
- yes (102) (remove)
Keywords
- Risk-based Authentication (3)
- Sustainability (3)
- Usable Security (3)
- WiLD (3)
- document similarity (3)
- 802.11 (2)
- Augmented Reality (2)
- Big Data Analysis (2)
- Eco-Feedback (2)
- Hochschule Bonn-Rhein-Sieg (2)
Sustainable urban soil management is becoming increasingly crucial due to its vital role in climate and water regulation and its significant potential for storing soil organic carbon (SOC). This significance is emphasized considering the ongoing urbanization and climate change issues. Although SOC is influenced by many factors, such as soil type and climate fluctuations (temperature, precipitation patterns), on a regional scale, land use and management practices (e.g., fertilization, irrigation) can have a more significant impact on SOC storage and the balance of soil-atmosphere carbon fluxes. However, there is still a limited understanding of the amount of humus content in urban soils and the effects of urban development and management practices on soil health and carbon storage. We investigated how management practices in urban green spaces influence soil carbon storage as the primary indicator of soil health.
The present study was carried out in the Bonn-Rhein-Sieg area, as the region is vital in terms of sustainable urban and regional development with a high population density (Rhein-Sieg district: 338.4, Bonn: 520.9 inhabitants/km2) in Germany. A survey was conducted with owners and managers of urban private (e.g., allotment and backyard garden) and public green spaces on the practices for the most common vegetation types (e.g., lawn, vegetable, ornamental). In the autumn and winter of 2022, 248 soil samples (0–20 cm depth) were collected from 95 private and public green spaces in the study area and analyzed for physiochemical and biological properties. Multivariate Analysis of Variance (MANOVA) was performed to assess the effects of different management practices on soil properties.
Our results indicate that the average SOC stock in public green areas (94.67 Mg ha-1) is substantially higher than in private ones (house garden 67.72 Mg ha-1, allotment garden 73.15 Mg ha-1). Moreover, urban green spaces with vegetables (91.66 Mg ha-1) and ornamentals (85.05 mg ha-1) show greater SOC stock levels when comparing vegetation types (lawn 62.48 Mg ha-1). Significant differences in SOC are also found for various management practices. Specifically, the monthly fertilization schedule resulted in higher SOC levels (127.37 Mg ha⁻¹) compared to the yearly fertilization schedule (76.88 Mg ha⁻¹). Additionally, the use of organic fertilizers contributed to increased SOC levels (84.40 Mg ha⁻¹) in contrast to mineral fertilizer applications (65.31 Mg ha⁻¹). The average SOC stock in all the studied urban green spaces (85 mg ha-1) was higher than the average SOC stock in arable soils in Germany (47.30 Mg ha-1). The higher SOC in the region could be due to vegetation types and fertilization frequencies, which show statistically significant effects (p-value <0.001). Other management practices (e.g., irrigation type and frequency) did not show a significant effect. Our findings highlight the significance of soil management practices, particularly in selecting vegetation types and determining fertilization frequency, as essential factors influencing urban SOC.
The transport of carbon dioxide through pipelines is one of the important components of Carbon dioxide Capture and Storage (CCS) systems that are currently being developed. If high flow rates are desired a transportation in the liquid or supercritical phase is to be preferred. For technical reasons, the transport must stay in that phase, without transitioning to the gaseous state. In this paper, a numerical simulation of the stationary process of carbon dioxide transport with impurities and phase transitions is considered. We use the Homogeneous Equilibrium Model (HEM) and the GERG-2008 thermodynamic equation of state to describe the transport parameters. The algorithms used allow to solve scenarios of carbon dioxide transport in the liquid or supercritical phase, with the detection of approaching the phase transition region. Convergence of the solution algorithms is analyzed in connection with fast and abrupt changes of the equation of state and the enthalpy function in the region of phase transitions.
In intensively used agricultural landscapes, path margins are one of the few refuges and nurseries for wildlife. They provide e. g. food sources and overwintering opportunities for many insects, serve as migration corridors for animals, protect soil from erosion, increase its water-holding capacity, and increase soil organic carbon, contributing thus directly to biodiversity conservation and climate change mitigation. Path margins are often municipally owned but used and managed by agriculture. For a path margin to be functional, certain conditions must be fulfilled, such as the width, the botanical composition, and how it is managed through the seasons. Therefore, it must be managed under specific requirements. A multifunctional path margin can be achieved only through the commitment of all stakeholders (e.g., farmers, municipalities, conservationists, and civil society).
Accurate forecasting of solar irradiance is crucial for the integration of solar energy into the power grid, power system planning, and the operation of solar power plants. The Weather Research and Forecasting (WRF) model, with its solar radiation (WRF-Solar) extension, has been used to forecast solar irradiance in various regions worldwide. However, the application of the WRF-Solar model for global horizontal irradiance (GHI) forecasting in West Africa, specifically in Ghana, has not been studied. This study aims to evaluate the performance of the WRF-Solar model for GHI forecasting in Ghana, focusing on 3 health centers (Kologo, Kumasi and Akwatia) for the year 2021. We applied a two one-way nested domain (D1=15 km and D2=3 km) to investigate the ability of the WRF solar model to forecast GHI up to 72 hours in advance under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF operational forecasts. In addition, the optical aerosol depth (AOD) data at 550 nm from the Copernicus Atmosphere Monitoring Service (CAMS) were considered. The study uses statistical metrics such as mean bias error (MBE), root mean square error (RMSE), to evaluate the performance of the WRF-Solar model with the observational data obtained from automatic weather stations in the three health centers in Ghana. The results of this study will contribute to the understanding of the capabilities and limitations of the WRF-Solar model for forecasting GHI in West Africa, particularly in Ghana, and provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management of in the region.
The continuously increasing number of biomedical scholarly publications makes it challenging to construct document recommendation algorithms that can efficiently navigate through literature. Such algorithms would help researchers in finding similar, relevant, and related publications that align with their research interests. Natural Language Processing offers various alternatives to compare publications, ranging from entity recognition to document embeddings. In this paper, we present the results of a comparative analysis of vector-based approaches to assess document similarity in the RELISH corpus. We aim to determine the best approach that resembles relevance without the need for further training. Specifically, we employ five different techniques to generate vectors representing the text in the documents. These techniques employ a combination of various Natural Language Processing frameworks such as Word2Vec, Doc2Vec, dictionary-based Named Entity Recognition, and state-of-the-art models based on BERT. To evaluate the document similarity obtained by these approaches, we utilize different evaluation metrics that account for relevance judgment, relevance search, and re-ranking of the relevance search. Our results demonstrate that the most promising approach is an in-house version of document embeddings, starting with word embeddings and using centroids to aggregate them by document.
Question Answering (QA) has gained significant attention in recent years, with transformer-based models improving natural language processing. However, issues of explainability remain, as it is difficult to determine whether an answer is based on a true fact or a hallucination. Knowledge-based question answering (KBQA) methods can address this problem by retrieving answers from a knowledge graph. This paper proposes a hybrid approach to KBQA called FRED, which combines pattern-based entity retrieval with a transformer-based question encoder. The method uses an evolutionary approach to learn SPARQL patterns, which retrieve candidate entities from a knowledge base. The transformer-based regressor is then trained to estimate each pattern’s expected F1 score for answering the question, resulting in a ranking ofcandidate entities. Unlike other approaches, FRED can attribute results to learned SPARQL patterns, making them more interpretable. The method is evaluated on two datasets and yields MAP scores of up to 73 percent, with the transformer-based interpretation falling only 4 pp short of an oracle run. Additionally, the learned patterns successfully complement manually generated ones and generalize well to novel questions.
The continuous increase of biomedical scholarly publications makes it challenging to construct document recommendation algorithms to navigate through literature, an important feature for researchers to keep up with relevant publications. Understanding semantic relatedness and similarity between two documents could improve document recommendations. The objective of this study is performing a comparative analysis of vector-based approaches to assess document similarity in the RELISH corpus. Here we present our approach to compare five different techniques to generate vectors representing the text in the documents. These techniques employ a combination of various Natural Language Processing frameworks such as Word2Vec, Doc2Vec, dictionary-based Named Entity Recognition as well as state-of-the-art models based on BERT.
Here we present a doc-2-doc relevance assessment performed on a subset of the TREC Genomics Track 2005 collection. Our approach includes an experimental set up to manually assess doc-2-doc relevance and the corresponding analysis done on the results obtained from this experiment. The experiment takes one document as a reference and assesses a second document regarding its relevance to the reference one. The consistency of the assessments done by 4 domain experts was evaluated. The lack of agreement between annotators may be due to: i) The abstract lacks key information and/or ii) Lack of experience of the annotators in the evaluation of some topics.
Während sich die unternehmerische Arbeitswelt immer mehr in Richtung Agilität verschiebt, verharrt das IT-Controlling noch in alten, klassischen Strukturen. Diese Arbeit untersucht die Fragestellung, ob und inwieweit agile Ansätze im IT-Controlling eingesetzt werden können. Dieser Beitrag ist eine modifizierte Version des in der Zeitschrift „HMD Praxis der Wirtschaftsinformatik“ (https://link.springer.com/article/10.1365/s40702-022-00837-0) erschienenen Artikels „Agiles IT-Controlling“.
Heutzutage werden alternative Mobilitätslösungen immer wichtiger. Dabei haben eBikes ihr Potential längst unter Beweis gestellt. Der zugehörige Markt ist über die letzten 10 Jahre enorm gewachsen und gleichermaßen auch die Erwartungen an das Produkt, wie bspw. eine Fahrt ohne störende Vibrationen und Geräusche zu haben. Der Motorfreilauf leistet dabei einen maßgeblichen Einfluss auf das dynamische Verhalten. In diesem Beitrag soll daher eine methodische Vorgehensweise vorgestellt werden, um mittels Versuch und Simulation den Einfluss des Motorfeilaufs auf das dynamische Verhalten der eBike Antriebseinheit zu bestimmen.
In the project EILD.nrw, Open Educational Resources (OER) have been developed for teaching databases. Lecturers can use the tools and courses in a variety of learning scenarios. Students of computer science and application subjects can learn the complete life cycle of databases. For this purpose, quizzes, interactive tools, instructional videos, and courses for learning management systems are developed and published under a Creative Commons license. We give an overview of the developed OERs according to subject, description, teaching form, and format. Following, we describe how licencing, sustainability, accessibility, contextualization, content description, and technical adaptability are implemented. The feedback of students in ongoing classes are evaluated.
Hydrogen as a versatile, greenhouse gas-free energy carrier will play an important role in our future economy. Yet sustainable, competitive production and distribution of hydrogen remains a challenge. Highly integrated solar water splitting systems aim to combine solar energy harvesting and electrolysis in a single device, similar to a photovoltaic module.[1] Such a system can produce hydrogen locally without the requirement to be connected to the electricity grid. Unlike large electrolysis that draws power from the grid, the power density of such a device is reduced so far that it does not require active cooling, but its operating temperature will closely follow outdoor conditions.
Here, we present our work on high-efficiency integrated solar water splitting devices based on multi-junction solar absorbers. The light-absorbing component is sensitive to the shape of the solar spectrum and generally becomes more efficient at lower temperatures. Catalysis, on the other hand, benefits from higher temperatures. These conflicting trends wih respect to the temperature impact the design of the solar hydrogen production system. We analyse how the local climate affects production efficiency[2] and show in a lab study that adequate system design allows efficient operation at temperatures as low as -20°C.[3] These insights can help to design small-scale distributed solar hydrogen production for both temperate regions, but also more extreme climatic conditions.
Risk-Based Authentication for OpenStack: A Fully Functional Implementation and Guiding Example
(2023)
Online services have difficulties to replace passwords with more secure user authentication mechanisms, such as Two-Factor Authentication (2FA). This is partly due to the fact that users tend to reject such mechanisms in use cases outside of online banking. Relying on password authentication alone, however, is not an option in light of recent attack patterns such as credential stuffing.
Risk-Based Authentication (RBA) can serve as an interim solution to increase password-based account security until better methods are in place. Unfortunately, RBA is currently used by only a few major online services, even though it is recommended by various standards and has been shown to be effective in scientific studies. This paper contributes to the hypothesis that the low adoption of RBA in practice can be due to the complexity of implementing it. We provide an RBA implementation for the open source cloud management software OpenStack, which is the first fully functional open source RBA implementation based on the Freeman et al. algorithm, along with initial reference tests that can serve as a guiding example and blueprint for developers.
Trojanized software packages used in software supply chain attacks constitute an emerging threat. Unfortunately, there is still a lack of scalable approaches that allow automated and timely detection of malicious software packages and thus most detections are based on manual labor and expertise. However, it has been observed that most attack campaigns comprise multiple packages that share the same or similar malicious code. We leverage that fact to automatically reproduce manually identified clusters of known malicious packages that have been used in real world attacks, thus, reducing the need for expert knowledge and manual inspection. Our approach, AST Clustering using MCL to mimic Expertise (ACME), yields promising results with a 𝐹1 score of 0.99. Signatures are automatically generated based on characteristic code fragments from clusters and are subsequently used to scan the whole npm registry for unreported malicious packages. We are able to identify and report six malicious packages that have been removed from npm consequentially. Therefore, our approach can support the detection by reducing manual labor and hence may be employed by maintainers of package repositories to detect possible software supply chain attacks through trojanized software packages.
Digital ecosystems are driving the digital transformation of business models. Meanwhile, the associated processing of personal data within these complex systems poses challenges to the protection of individual privacy. In this paper, we explore these challenges from the perspective of digital ecosystems' platform providers. To this end, we present the results of an interview study with seven data protection officers representing a total of 12 digital ecosystems in Germany. We identified current and future challenges for the implementation of data protection requirements, covering issues on legal obligations and data subject rights. Our results support stakeholders involved in the implementation of privacy protection measures in digital ecosystems, and form the foundation for future privacy-related studies tailored to the specifics of digital ecosystems.
Computers can help us to trigger our intuition about how to solve a problem. But how does a computer take into account what a user wants and update these triggers? User preferences are hard to model as they are by nature vague, depend on the user’s background and are not always deterministic, changing depending on the context and process under which they were established. We pose that the process of preference discovery should be the object of interest in computer aided design or ideation. The process should be transparent, informative, interactive and intuitive. We formulate Hyper-Pref, a cyclic co-creative process between human and computer, which triggers the user’s intuition about what is possible and is updated according to what the user wants based on their decisions. We combine quality diversity algorithms, a divergent optimization method that can produce many, diverse solutions, with variational autoencoders to both model that diversity as well as the user’s preferences, discovering the preference hypervolume within large search spaces.
We describe a systematic approach for rendering time-varying simulation data produced by exa-scale simulations, using GPU workstations. The data sets we focus on use adaptive mesh refinement (AMR) to overcome memory bandwidth limitations by representing interesting regions in space with high detail. Particularly, our focus is on data sets where the AMR hierarchy is fixed and does not change over time. Our study is motivated by the NASA Exajet, a large computational fluid dynamics simulation of a civilian cargo aircraft that consists of 423 simulation time steps, each storing 2.5 GB of data per scalar field, amounting to a total of 4 TB. We present strategies for rendering this time series data set with smooth animation and at interactive rates using current generation GPUs. We start with an unoptimized baseline and step by step extend that to support fast streaming updates. Our approach demonstrates how to push current visualization workstations and modern visualization APIs to their limits to achieve interactive visualization of exa-scale time series data sets.
The electricity grid of the future will be built on renewable energy sources, which are highly variable and dependent on atmospheric conditions. In power grids with an increasingly high penetration of solar photovoltaics (PV), an accurate knowledge of the incoming solar irradiance is indispensable for grid operation and planning, and reliable irradiance forecasts are thus invaluable for energy system operators. In order to better characterise shortwave solar radiation in time and space, data from PV systems themselves can be used, since the measured power provides information about both irradiance and the optical properties of the atmosphere, in particular the cloud optical depth (COD). Indeed, in the European context with highly variable cloud cover, the cloud fraction and COD are important parameters in determining the irradiance, whereas aerosol effects are only of secondary importance.
Intention: Within the research project EnerSHelF (Energy-Self-Sufficiency for Health Facilities in Ghana), i. a. energy-meteorological and load-related measurement data are collected, for which an overview of the availability is to be presented on a poster.
Context: In Ghana, the total electricity consumed has almost doubled between 2008 and 2018 according to the Energy Commission of Ghana. This goes along with an unstable power grid, resulting in power outages whenever electricity consumption peaks. The blackouts called "dumsor" in Ghana, pose a severe burden to the healthcare sector. Innovative solutions are needed to reduce greenhouse gas emissions and improve energy and health access.
West Africa has great potential for the use of solar energy systems, as it has both a high solar radiation rate and a lack of energy production. West Africa is a very aerosol-rich region, whose effects on photovoltaic (PV) use are due to both atmospheric conditions and existing solar technology. This study reports the variability of aerosol optical properties in the city of Koforidua, Ghana over the period 2016 to 2020, and their impact on the radiation intensity and efficiency of a PV cell. The study used AERONET ground (Giles et al., 2019) and satellite data produced by CAMS (Gschwind, et al., 2019), which both provide aerosol optical depth (AOD) and metrological parameters used for radiative transfer calculations with libRadtran (Emde, et al., 2016). A spectrally resolved PV model (Herman-Czezuch et al., 2022) is then used to calculate the PV yield of two PV technologies: polycrystalline and amorphous silicon. It is observed that for both data sets, the aerosol is mainly composed of dust and organic matter, with a very increased AOD load during the harmattan period (December-February), also due to the fires observed during this period.
The aim of this paper is to assess the objectives of farmers’ challenges in enhancing biodiversity. The so-called “trilemma” (WBGU 2021) of land use stems from the multiple demands made on land for the benefit of mitigating climate change, securing food and maintaining biodiversity. The agricultural sector is accused of maladministration: it is blamed for causing soil contamination, animal cruelty, bee mortality and climate change. That is why farmers are seen as key actors at all levels. They are, however, also key players when it comes to overcoming the problems of the future. Their supportive role is urgently needed, but farmers find themselves caught between a “rock” and a ”hard place”. Consumers are calling for sustainable, environmentally friendly production and inexpensive food products that do not contain pesticide residues, demanding enough food for all. Farmers are restricted by the wants and needs of consumers who are influenced by interest groups and are exposed to direct and indirect influencing factors and their interdependencies. They are also tasked with balancing the scrutiny of the critical public on the one hand, and the control exercised by eager authorities on the other.
As part of the DINA (Diversity of Insects in Nature protected Areas) project, a trans- and interdisciplinary research study, we collected and surveyed the data of farmers who are farming within or close to the 21 selected nature protected areas included in the DINA project. Data was collected as part of a mixed method approach using a semi-structured questionnaire. The methodological and strategic approach and interdependencies of issues demonstrate the complexity of today’s problems. To investigate this, we first used the data collection method using questionnaires with closed and open questions. The conflicts and obstacles farmers face were evaluated, and the results show farmers’ willingness and the importance of appreciation shown to farmers for implementation of biodiversity measures. The paper proposes some follow-up activities (quantitative study) to verify the objectives. The results will later lead to recommendations for policymakers and farmers in all German nature protected areas.
The accurate forecasting of solar radiation plays an important role for predictive control applications for energy systems with a high share of photovoltaic (PV) energy. Especially off-grid microgrid applications using predictive control applications can benefit from forecasts with a high temporal resolution to address sudden fluctuations of PV-power. However, cloud formation processes and movements are subject to ongoing research. For now-casting applications, all-sky-imagers (ASI) are used to offer an appropriate forecasting for aforementioned application. Recent research aims to achieve these forecasts via deep learning approaches, either as an image segmentation task to generate a DNI forecast through a cloud vectoring approach to translate the DNI to a GHI with ground-based measurement (Fabel et al., 2022; Nouri et al., 2021), or as an end-to-end regression task to generate a GHI forecast directly from the images (Paletta et al., 2021; Yang et al., 2021). While end-to-end regression might be the more attractive approach for off-grid scenarios, literature reports increased performance compared to smart-persistence but do not show satisfactory forecasting patterns (Paletta et al., 2021). This work takes a step back and investigates the possibility to translate ASI-images to current GHI to deploy the neural network as a feature extractor. An ImageNet pre-trained deep learning model is used to achieve such translation on an openly available dataset by the University of California San Diego (Pedro et al., 2019). The images and measurements were collected in Folsom, California. Results show that the neural network can successfully translate ASI-images to GHI for a variety of cloud situations without the need of any external variables. Extending the neural network to a forecasting task also shows promising forecasting patterns, which shows that the neural network extracts both temporal and momentarily features within the images to generate GHI forecasts.
ProtSTonKGs: A Sophisticated Transformer Trained on Protein Sequences, Text, and Knowledge Graphs
(2022)
While most approaches individually exploit unstructured data from the biomedical literature or structured data from biomedical knowledge graphs, their union can better exploit the advantages of such approaches, ultimately improving representations of biology. Using multimodal transformers for such purposes can improve performance on context dependent classication tasks, as demonstrated by our previous model, the Sophisticated Transformer Trained on Biomedical Text and Knowledge Graphs (STonKGs). In this work, we introduce ProtSTonKGs, a transformer aimed at learning all-encompassing representations of protein-protein interactions. ProtSTonKGs presents an extension to our previous work by adding textual protein descriptions and amino acid sequences (i.e., structural information) to the text- and knowledge graph-based input sequence used in STonKGs. We benchmark ProtSTonKGs against STonKGs, resulting in improved F1 scores by up to 0.066 (i.e., from 0.204 to 0.270) in several tasks such as predicting protein interactions in several contexts. Our work demonstrates how multimodal transformers can be used to integrate heterogeneous sources of information, paving the foundation for future approaches that use multiple modalities for biomedical applications.
Hydrogen is a versatile energy carrier. When produced with renewable energy by water splitting, it is a carbon neutral alternative to fossil fuels. The industrialization process of this technology is currently dominated by electrolyzers powered by solar or wind energy. For small scale applications, however, more integrated device designs for water splitting using solar energy might optimize hydrogen production due to lower balance of system costs and a smarter thermal management. Such devices offer the opportunity to thermally couple the solar cell and the electrochemical compartment. In this way, heat losses in the absorber can be turned into an efficiency boost for the device via simultaneously enhancing the catalytic performance of the water splitting reactions, cooling the absorber, and decreasing the ohmic losses.[1,2] However,integrated devices (sometimes also referred to as “artificial leaves”), currently suffer from a lower technology readiness level (TRL) than the completely decoupled approach.
For research in audiovisual interview archives often it is not only of interest what is said but also how. Sentiment analysis and emotion recognition can help capture, categorize and make these different facets searchable. In particular, for oral history archives, such indexing technologies can be of great interest. These technologies can help understand the role of emotions in historical remembering. However, humans often perceive sentiments and emotions ambiguously and subjectively. Moreover, oral history interviews have multi-layered levels of complex, sometimes contradictory, sometimes very subtle facets of emotions. Therefore, the question arises of the chance machines and humans have capturing and assigning these into predefined categories. This paper investigates the ambiguity in human perception of emotions and sentiment in German oral history interviews and the impact on machine learning systems. Our experiments reveal substantial differences in human perception for different emotions. Furthermore, we report from ongoing machine learning experiments with different modalities. We show that the human perceptual ambiguity and other challenges, such as class imbalance and lack of training data, currently limit the opportunities of these technologies for oral history archives. Nonetheless, our work uncovers promising observations and possibilities for further research.
We benchmark the robustness of maximum likelihood based uncertainty estimation methods to outliers in training data for regression tasks. Outliers or noisy labels in training data results in degraded performances as well as incorrect estimation of uncertainty. We propose the use of a heavy-tailed distribution (Laplace distribution) to improve the robustness to outliers. This property is evaluated using standard regression benchmarks and on a high-dimensional regression task of monocular depth estimation, both containing outliers. In particular, heavy-tailed distribution based maximum likelihood provides better uncertainty estimates, better separation in uncertainty for out-of-distribution data, as well as better detection of adversarial attacks in the presence of outliers.
Current research in augmented, virtual, and mixed reality (XR) reveals a lack of tool support for designing and, in particular, prototyping XR applications. While recent tools research is often motivated by studying the requirements of non-technical designers and end-user developers, the perspective of industry practitioners is less well understood. In an interview study with 17 practitioners from different industry sectors working on professional XR projects, we establish the design practices in industry, from early project stages to the final product. To better understand XR design challenges, we characterize the different methods and tools used for prototyping and describe the role and use of key prototypes in the different projects. We extract common elements of XR prototyping, elaborating on the tools and materials used for prototyping and establishing different views on the notion of fidelity. Finally, we highlight key issues for future XR tools research.
The rapid increase in solar photovoltaic (PV) installations worldwide has resulted in the electricity grid becoming increasingly dependent on atmospheric conditions, thus requiring more accurate forecasts of incoming solar irradiance. In this context, measured data from PV systems are a valuable source of information about the optical properties of the atmosphere, in particular the cloud optical depth (COD). This work reports first results from an inversion algorithm developed to infer global, direct and diffuse irradiance as well as atmospheric optical properties from PV power measurements, with the goal of assimilating this information into numerical weather prediction (NWP) models.
In den Atmosphärenwissenschaften spielt die Strahlungsbilanz der Erde eine wichtige Rolle für unser Verständnis des Klimasystems. Hier liefern ausgereifte Satellitenprodukte dekadische Klimazeitreihen mit einer so hohen Genauigkeit, dass z.B. Änderungen im Zusammenhang mit dem Klimawandel detektiert werden können. Dies gilt insbesondere auch für die solaren Strahlungsflüsse an der Erdoberfläche. Beim Vergleich dieser Satellitenprodukte mit instantanen Beobachtungen der Strahlung am Erdboden sind jedoch oft erhebliche Abweichungen feststellbar, die hauptsächlich durch kleinskalige Variabilität in der räumlichen Struktur von Wolken und ihrer Strahlungswirkung verursacht werden. Hier ist auch zu bedenken, dass Bodenbeobachtungen fast einer Punktmessung entsprechen, während Satellitenpixel eine Fläche in der Größenordnung von Quadratkilometern abtasten.
West Africa has a great potential for the application of solar energy systems, as it combines high levels of solar irradiance with a lack of energy production. Southern West Africa is a region with a very high aerosol load. Urbanization, uncontrolled fires, traffic as well as power plants and oil rigs lead to increasing anthropogenic emissions. The naturally circulating north winds bring mineral dust from the Sahel and Sahara and monsoons - sea salt and other oceanic compounds from the south. The EU-funded Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project (2014–2018), dlivered the most complete dataset of the atmosphere over the region to date. In our study, we use in-situ measured optical properties of aerosols from the airborne campaign over the Gulf of Guinea and inland, and from ground measurements in coastal cities.
An der Hochschule Bonn-Rhein-Sieg fand am Donnerstag, den 23.9.21 das erste Verbraucherforum für Verbraucherinformatik statt. Im Rahmen der Online-Tagesveranstaltung diskutierten mehr als 30 Teilnehmer:innen über Themen und Ideen rund um den Bereich Verbraucherdatenschutz. Dabei kamen sowohl Beiträge aus der Informatik, den Verbraucher- und Sozialwissenschaften sowie auch der regulatorischen Perspektive zur Sprache. Der folgende Beitrag stellt den Hintergrund der Veranstaltung dar und berichtet über Inhalte der Vorträge sowie Anknüpfungspunkte für die weitere Konstituierung der Verbraucherinformatik. Veranstalter waren das Institut für Verbraucherinformatik an der H-BRS in Zusammenarbeit mit dem Lehrstuhl IT-Sicherheit der Universität Siegen sowie dem Kompetenzzentrum Verbraucherforschung NRW der Verbraucherzentrale NRW e. V. mit Förderung des Bundesministeriums der Justiz und für Verbraucherschutz.
Die Blockchain-Technologie ist einer der großen Innovationstreiber der letzten Jahre. Mit einer zugrundeliegenden Blockchain-Technologie ist auch der Betrieb von verteilten Anwendungen, sogenannter Decentralized Applications (DApps), bereits technisch umsetzbar. Dieser Beitrag verfolgt das Ziel, Gestaltungsmöglichkeiten der digitalen Verbraucherteilhabe an Blockchain-Anwendungen zu untersuchen. Hierzu enthält der Beitrag eine Einführung in die digitale Verbraucherteilhabe und die technischen Grundlagen und Eigenschaften der Blockchain-Technologie, einschließlich darauf basierender DApps. Abschließend werden technische, ethisch-organisatorische, rechtliche und sonstige Anforderungsbereiche für die Umsetzung von digitaler Verbraucherteilhabe in Blockchain-Anwendungen adressiert.
Frequently the main purpose of domestic artifacts equipped with smart sensors is to hide technology, like previous examples of a Smart Mirror show. However, current Smart Homes often fail to provide meaningful IoT applications for all residents’ needs. To design beyond efficiency and productivity, we propose to realize the potential of the traditional artifact for calm and engaging experiences. Therefore, we followed a design case study approach with 22 participants in total. After an initial focus group, we conducted a diary study to examine home routines and developed a conceptual design. The evaluation of our mid-fidelity prototype shows, that we need to study carefully the practices of the residents to leverage the physical material of the artifact to fit the routines. Our Smart Mirror, enhanced by digital qualities, supports meaningful activities and makes the bathroom more appealing. Thereby, we discuss domestic technology design beyond automation.
With the debates on climate change and sustainability, a reduction of the share of cars in the modal split has become increasingly prevalent in both public and academic discourse. Besides some motivational approaches, there is a lack of ICT artifacts that successfully raise the ability of consumers to adopt sustainable mobility patterns. To further understand the requirements and the design of these artifacts within everyday mobility adopted a practice-lens. This lens is helpful to get a broader perspective on the use of ICT artifacts along consumers’ transformational journey towards sustainable mobility practices. Based on 12 retrospective interviews with car-free mobility consumers, we argue that artifacts should not be viewed as ’magic-bullet’ solutions but should accompany the complex transformation of practices in multifaceted ways. Moreover, we highlight in particular the difficulties of appropriating shared infrastructures and aligning own practices with them. This opens up a design space to provide more support for these kinds of material-interactions, to provide access to consumption infrastructures and make them usable, rather than leaving consumers alone with increased motivation.
Recent publications propose concepts of systems that integrate the various services and data sources of everyday food practices. However, this research does not go beyond the conceptualization of such systems. Therefore, there is a deficit in understanding how to combine different services and data sources and which design challenges arise from building integrated Household Information Systems. In this paper, we probed the design of an Integrated Household Information System with 13 participants. The results point towards more personalization, automatization of storage administration and enabling flexible artifact ecologies. Our paper contributes to understanding the design and usage of Integrated Household Information Systems, as a new class of information systems for HCI research.
Die digitale Transformation verändert die internationale Kooperation der Hochschulen massiv. Über die Möglichkeiten der virtuellen Mobilität hinaus entstehen neue Themenfelder, die internationale Lern- und Lehrerlebnisse mit digitaler Unterstützung verändern, ergänzen oder neu ermöglichen. Dazu sind im Bereich der Förderung der Internationalisierung (DAAD, Erasmus+, BMBF u.a.) Projekte und Förderformate entstanden, die Digitalisierung und Internationalisierung kombinieren und die neuen Themenstellungen adressieren, z.B. didaktische Formate, administrative Prozesse (auch im Kontext OZG und DSGVO), virtuelle und hybride Mobilität, internationale Projekt- und Teamformate sowie schlussendlich auch Inhalte, die internationale, interkulturelle und interdisziplinäre Kompetenzen mit digitalen Kompetenzen verbinden. Der vorgeschlagene Workshop soll entsprechende Projekte zusammenbringen und die Themen strukturieren, um einen Überblick der Entwicklungen zu schaffen und somit einen Beitrag zur Definition des Themenfelds „Digitalisierung & Internationalisierung“ zu leisten.
Risk-based authentication (RBA) aims to strengthen password-based authentication rather than replacing it. RBA does this by monitoring and recording additional features during the login process. If feature values at login time differ significantly from those observed before, RBA requests an additional proof of identification. Although RBA is recommended in the NIST digital identity guidelines, it has so far been used almost exclusively by major online services. This is partly due to a lack of open knowledge and implementations that would allow any service provider to roll out RBA protection to its users. To close this gap, we provide a first in-depth analysis of RBA characteristics in a practical deployment. We observed N=780 users with 247 unique features on a real-world online service for over 1.8 years. Based on our collected data set, we provide (i) a behavior analysis of two RBA implementations that were apparently used by major online services in the wild, (ii) a benchmark of the features to extract a subset that is most suitable for RBA use, (iii) a new feature that has not been used in RBA before, and (iv) factors which have a significant effect on RBA performance. Our results show that RBA needs to be carefully tailored to each online service, as even small configuration adjustments can greatly impact RBA's security and usability properties. We provide insights on the selection of features, their weightings, and the risk classification in order to benefit from RBA after a minimum number of login attempts.
Over the last decades, different kinds of design guides have been created to maintain consistency and usability in interactive system development. However, in the case of spatial applications, practitioners from research and industry either have difficulty finding them or perceive such guides as lacking relevance, practicability, and applicability. This paper presents the current state of scientific research and industry practice by investigating currently used design recommendations for mixed reality (MR) system development. We analyzed and compared 875 design recommendations for MR applications elicited from 89 scientific papers and documentation from six industry practitioners in a literature review. In doing so, we identified differences regarding four key topics: Focus on unique MR design challenges, abstraction regarding devices and ecosystems, level of detail and abstraction of content, and covered topics. Based on that,we contribute to the MR design research by providing three factors for perceived irrelevance and six main implications for design recommendations that are applicable in scientific and industry practice.
Risk-based authentication (RBA) extends authentication mechanisms to make them more robust against account takeover attacks, such as those using stolen passwords. RBA is recommended by NIST and NCSC to strengthen password-based authentication, and is already used by major online services. Also, users consider RBA to be more usable than two-factor authentication and just as secure. However, users currently obtain RBA's high security and usability benefits at the cost of exposing potentially sensitive personal data (e.g., IP address or browser information). This conflicts with user privacy and requires to consider user rights regarding the processing of personal data. We outline potential privacy challenges regarding different attacker models and propose improvements to balance privacy in RBA systems. To estimate the properties of the privacy-preserving RBA enhancements in practical environments, we evaluated a subset of them with long-term data from 780 users of a real-world online service. Our results show the potential to increase privacy in RBA solutions. However, it is limited to certain parameters that should guide RBA design to protect privacy. We outline research directions that need to be considered to achieve a widespread adoption of privacy preserving RBA with high user acceptance.
In contrast to the German power supply, the energy supply in many West African countries is very unstable. Frequent power outages are not uncommon. Especially for critical infrastructures, such as hospitals, a stable power supply is vital. To compensate for the power outages, diesel generators are often used. In the future, these systems will increasingly be supplemented by PV systems and storage, so that the generator will have to be used less or not at all when needed. For the design and operation of such systems, it is necessary to better understand the atmospheric variability of PV power generation. For example, there are large variations between rainy and dry seasons, between days with high and low dust levels - caused by sandstorms (harmattan) or urban air pollution.
In view of the rapid growth of solar power installations worldwide, accurate forecasts of photovoltaic (PV) power generation are becoming increasingly indispensable for the overall stability of the electricity grid. In the context of household energy storage systems, PV power forecasts contribute towards intelligent energy management and control of PV-battery systems, in particular so that self-sufficiency and battery lifetime are maximised. Typical battery control algorithms require day-ahead forecasts of PV power generation, and in most cases a combination of statistical methods and numerical weather prediction (NWP) models are employed. The latter are however often inaccurate, both due to deficiencies in model physics as well as an insufficient description of irradiance variability.
New communication technologies are changing the way we work and communicate with people around the world. Given this reality, students in Higher Education (HE) worldwide need to develop knowledge in their area of study as well as attitudes and values that will enable them to be responsible and ethical global citizens in the workforce they will soon enter, regardless of the degree. Different institutional and country-specific requirements are important factors when developing an international Virtual Exchange (VE) program. Digital learning environments such as ProGlobe – Promoting the Global Exchange of Ideas on Sustainable Goals, Practices, and Cultural Diversity – offer a platform for collaborating with diverse students around the world to share and reflect on ideas on sustainable practices. Students work together virtually on a joint interdisciplinary project that aims to create knowledge and foster cultural diversity. This project was successfully integrated into each country’s course syllabus through a common global theme; sustainability. The focus of this paper is to present multi-disciplinary perspectives on the opportunities and challenges in implementing a VE project in HE. Furthermore, it will present the challenges that country coordinators dealt with when planning and implementing their project. Given the disparity found in each course syllabus, project coordinators uniquely handled the project goal, approach, and assessment for their specific course and program. Not only did the students and faculty gain valuable insight into different aspects of collaboration when working in interdisciplinary HE projects, they also reflected on their own impact on the environment and learned to listen to how people in different countries deal with environmental issues. This approach provided students with meaningful intercultural experiences that helped them link ideas and concepts about a global issue through the lens of their own discipline as well as other disciplines worldwide.
Target meaning representations for semantic parsing tasks are often based on programming or query languages, such as SQL, and can be formalized by a context-free grammar. Assuming a priori knowledge of the target domain, such grammars can be exploited to enforce syntactical constraints when predicting logical forms. To that end, we assess how syntactical parsers can be integrated into modern encoder-decoder frameworks. Specifically, we implement an attentional SEQ2SEQ model that uses an LR parser to maintain syntactically valid sequences throughout the decoding procedure. Compared to other approaches to grammar-guided decoding that modify the underlying neural network architecture or attempt to derive full parse trees, our approach is conceptually simpler, adds less computational overhead during inference and integrates seamlessly with current SEQ2SEQ frameworks. We present preliminary evaluation results against a recurrent SEQ2SEQ baseline on GEOQUERY and ATIS and demonstrate improved performance while enforcing grammatical constraints.
Since stationary self-checkout is widely introduced and well understood, previous research barely examined newer generations of smartphone-based Scan&Go. Especially from a design perspective, we know little about the factors contributing to the adoption of Scan&Go solutions and how design enables consumers to take full advantage of this development rather than being burdened with using complex and unenjoyable systems. To understand the influencing factors and the design from a consumer perspective, we conducted a mixed-methods study where we triangulated data of an online survey with 103 participants and a qualitative study with 20 participants. Based on the results, our study presents a refined and nuanced understanding of technology as well as infrastructure-related factors that influence adoption. Moreover, we present several implications for designing and implementing of Scan&Go in retail environments.
An der H-BRS, einer Hochschule für Angewandte Wissenschaften mit ca. 9.000 Studierenden, wurde die OER-Kultur bewusst als Teil der Strategie zur Digitalisierung der Lehre in drei Schritten etabliert: (1) Gemeinsame Strategiebildung als Teil eines partizipativ erarbeiteten Hochschulentwicklungsplans: Verankerung von OER in der Digitalisierungsstrategie. (2) Basierend auf der Vernetzung der Expertinnen und Experten erfolgreiche Einwerbung von OER-Projekten, die exemplarisch vorgestellt werden. (3) Dauerhafte strategische Verankerung, basierend auf kontinuierlicher interner und externer Netzwerkarbeit, Etablierung von digitalen Austauschplattformen für die Lehrenden, Transfer des OER-Gedankens (Kooperation, Austausch, Mehrfachnutzen) auf die Hochschuldidaktik sowie regelmäßige Ausschreibungen von Fördermaßnahmen.
Less is Often More: Header Whitelisting as Semantic Gap Mitigation in HTTP-Based Software Systems
(2021)
The web is the most wide-spread digital system in the world and is used for many crucial applications. This makes web application security extremely important and, although there are already many security measures, new vulnerabilities are constantly being discovered. One reason for some of the recent discoveries lies in the presence of intermediate systems—e.g. caches, message routers, and load balancers—on the way between a client and a web application server. The implementations of such intermediaries may interpret HTTP messages differently, which leads to a semantically different understanding of the same message. This so-called semantic gap can cause weaknesses in the entire HTTP message processing chain.
In this paper we introduce the header whitelisting (HWL) approach to address the semantic gap in HTTP message processing pipelines. The basic idea is to normalize and reduce an HTTP request header to the minimum required fields using a whitelist before processing it in an intermediary or on the server, and then restore the original request for the next hop. Our results show that HWL can avoid misinterpretations of HTTP messages in the different components and thus prevent many attacks rooted in a semantic gap including request smuggling, cache poisoning, and authentication bypass.
XML Signature Wrapping (XSW) has been a relevant threat to web services for 15 years until today. Using the Personal Health Record (PHR), which is currently under development in Germany, we investigate a current SOAP-based web services system as a case study. In doing so, we highlight several deficiencies in defending against XSW. Using this real-world contemporary example as motivation, we introduce a guideline for more secure XML signature processing that provides practitioners with easier access to the effective countermeasures identified in the current state of research.
Threats to passwords are still very relevant due to attacks like phishing or credential stuffing. One way to solve this problem is to remove passwords completely. User studies on passwordless FIDO2 authentication using security tokens demonstrated the potential to replace passwords. However, widespread acceptance of FIDO2 depends, among other things, on how user accounts can be recovered when the security token becomes permanently unavailable. For this reason, we provide a heuristic evaluation of 12 account recovery mechanisms regarding their properties for FIDO2 passwordless authentication. Our results show that the currently used methods have many drawbacks. Some even rely on passwords, taking passwordless authentication ad absurdum. Still, our evaluation identifies promising account recovery solutions and provides recommendations for further studies.
Atomic oxygen in the mesosphere and lower thermosphere measured by terahertz heterodyne spectroscopy
(2021)
Atomic oxygen is a main component of the mesosphere and lower thermosphere (MLT). The photochemistry and the energy balance of the MLT are governed by atomic oxygen. In addition, it is a tracer for dynamical motions in the MLT. It is difficult to measure with remote sensing techniques. Concentrations can be inferred indirectly from the oxygen air glow or from observations of OH, which is involved in photochemical processes related to atomic oxygen. Such measurements have been performed with several satellite instruments such as SCIAMACHY, SABER, WINDII and OSIRIS. However, the methods are indirect and rely on photochemical models and assumptions such as quenching rates, radiative lifetimes, and reaction coefficients. The results are not always in agreement, particularly when obtained with different instruments.
Photovoltaic (PV) power data are a valuable but as yet under-utilised resource that could be used to characterise global irradiance with unprecedented spatio-temporal resolution. The resulting knowledge of atmospheric conditions can then be fed back into weather models and will ultimately serve to improve forecasts of PV power itself. This provides a data-driven alternative to statistical methods that use post-processing to overcome inconsistencies between ground-based irradiance measurements and the corresponding predictions of regional weather models (see for instance Frank et al., 2018). This work reports first results from an algorithm developed to infer global horizontal irradiance as well as atmospheric optical properties such as aerosol or cloud optical depth from PV power measurements.
Data emerged as a central success factor for companies to benefit from digitization. However, the skills in successfully creating value from data – especially at the management level – are not always profound. To address this problem, several canvas models have already been designed. Canvas models are usually created to write down an idea in a structured way to promote transparency and traceability. However, some existing data science canvas models mainly address developers and are thus unsuitable for decision-makers and communication within interdisciplinary teams. Based on a literature review, we identified influencing factors that are essential for the success of data science projects. With the information gained, the Data Science Canvas was developed in an expert workshop and finally evaluated by practitioners to find out whether such an instrument could support data-driven value creation.
Augmented/Virtual Reality (AR/VR) is still a fragmented space to design for due to the rapidly evolving hardware, the interdisciplinarity of teams, and a lack of standards and best practices. We interviewed 26 professional AR/VR designers and developers to shed light on their tasks, approaches, tools, and challenges. Based on their work and the artifacts they generated, we found that AR/VR application creators fulfill four roles: concept developers, interaction designers, content authors, and technical developers. One person often incorporates multiple roles and faces a variety of challenges during the design process from the initial contextual analysis to the deployment. From analysis of their tool sets, methods, and artifacts, we describe critical key challenges. Finally, we discuss the importance of prototyping for the communication in AR/VR development teams and highlight design implications for future tools to create a more usable AR/VR tool chain.
Risk-based Authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional features during login, and when observed feature values differ significantly from previously seen ones, users have to provide additional authentication factors such as a verification code. RBA has the potential to offer more usable authentication, but the usability and the security perceptions of RBA are not studied well.
We present the results of a between-group lab study (n=65) to evaluate usability and security perceptions of two RBA variants, one 2FA variant, and password-only authentication. Our study shows with significant results that RBA is considered to be more usable than the studied 2FA variants, while it is perceived as more secure than password-only authentication in general and comparably secure to 2FA in a variety of application types. We also observed RBA usability problems and provide recommendations for mitigation. Our contribution provides a first deeper understanding of the users' perception of RBA and helps to improve RBA implementations for a broader user acceptance.
Long-term variability of solar irradiance and its implications for photovoltaic power in West Africa
(2020)
West Africa is one of the least developed regions in the world regarding the energy availability and energy security. Located close to the equator West Africa receives high amounts of global horizontal irradiance (GHI). Thus, solar power and especially photovoltaic (PV) systems seem to be a promising solution to provide electricity with low environmental impact. To plan and to dimension a PV power system climatological data for global horizontal irradiance (GHI) and its variability need to be taken into account. However, ground based measurements of irradiances are not available continuously and cover only a few discrete locations.
Incoming solar radiation is an important driver of our climate and weather. Several studies (see for instance Frank et al. 2018) have revealed discrepancies between ground-based irradiance measurements and the predictions of regional weather models. In the realm of electricity generation, accurate forecasts of solar photovoltaic (PV)energy yield are becoming indispensable for cost-effective grid operation: in Germany there are 1.6 million PVsystems installed, with a nominal power of 46 GW (Bundesverband Solarwirtschaft 2019). The proliferation of PV systems provides a unique opportunity to characterise global irradiance with unprecedented spatiotemporalresolution, which in turn will allow for highly resolved PV power forecasts.
Renewable energies play an increasingly important role for energy production in Europe. Unlike coal or gas powerplants, solar energy production is highly variable in space and time. This is due to the strong variability of cloudsand their influence on the surface solar irradiance. Especially in regions with large contribution from photovoltaicpower production, the intermittent energy feed-in to the power grid can be a risk for grid stability. Therefore goodforecasts of temporal and spatial variability of surface irradiance are necessary to be able to properly regulate thepower supply.
Due to the policy goals for sustainable energy production, renewable energy plants such as photovoltaics are increasingly in use. The energy production from solar radiation depends strongly on atmospheric conditions. As the weather mostly changes, electrical power generation fluctuates, making technical planning and control of power grids to a complex problem.
Risk-based Authentication (RBA) is an adaptive security measure that improves the security of password-based authentication by protecting against credential stuffing, password guessing, or phishing attacks. RBA monitors extra features during login and requests for an additional authentication step if the observed feature values deviate from the usual ones in the login history. In state-of-the-art RBA re-authentication deployments, users receive an email with a numerical code in its body, which must be entered on the online service. Although this procedure has a major impact on RBA's time exposure and usability, these aspects were not studied so far.
We introduce two RBA re-authentication variants supplementing the de facto standard with a link-based and another code-based approach. Then, we present the results of a between-group study (N=592) to evaluate these three approaches. Our observations show with significant results that there is potential to speed up the RBA re-authentication process without reducing neither its security properties nor its security perception. The link-based re-authentication via "magic links", however, makes users significantly more anxious than the code-based approaches when perceived for the first time. Our evaluations underline the fact that RBA re-authentication is not a uniform procedure. We summarize our findings and provide recommendations.
More and more devices will be connected to the internet [3]. Many devicesare part of the so-called Internet of Things (IoT) which contains many low-powerdevices often powered by a battery. These devices mainly communicate with the manufacturers back-end and deliver personal data and secrets like passwords.
The Learning Culture Survey (LCS) is a questionnaire-based research, investigating students’ perceptions of and expectations towards Higher Education (HE). The aim of this survey is to improve our understanding about the sources of cultural conflicts in educational scenarios. This understanding, shell help us to predict potential conflict situations and develop supportive measures.
After three years of development, the LCS was initialized in 2010 in South Korea and Germany. During the following years, the investigations were extended to further countries. The results, on the one hand, provided insights about the cultural context of HE in general and on the other hand, about specific (national / regional) characteristics of learners in HE. Most issues targeted with the questionnaire were directly linked to value systems. Thus, we expected from the beginning that the collected data would keep valid over longer periods of time. However, we had no evidence regarding the actual persistence of learning culture. For a study, designed to being implemented on a global scope and providing input for further applications, persistence is a basic condition to justify related investigations.
To answer the question on persistence, we repeated the LCS in our university every four years, between 2010 to 2018/19. Besides a small number of slight changes, explainable out of their situational context, the overall results kept consistent over the investigated years. In this paper, after an introduction of the LCS’ concept, setting and its general results from the past years, we present the insights from our most recently finalized longitudinal study on learning culture.
Digital transformation in Higher Education and Science is a mission-critical demand to prepare educational institutions for their future competition on the international market. In many cases, the digitization goes along with the search for and acquisition of new software. For easily exchangeable software, wrong product decisions, in the worst case, lead to calculable financial losses. However, if a planned software requires a lot of technological adjustments and is to be applied as central component of a business- and/or security-critical environment, wrong decisions during the software acquisition process might lead to hardly calculable damage. Questions arising are how to decide for a product and how many resources should be invested for the acquisition process.
We planned to apply a commercial Business Support System, which should replace the currently used in-house developed software. Our goals were the increase of our university’s level of data security, to ease the interaction between stakeholders, to eliminate media discontinuities, to improve the process management and transparency, and to reduce the execution time of automated processes. Alongside with the introduction of the electronic case file, our agenda stipulates the digitization (and automation) of administrative university processes, especially, but not limited to, the student self-service and the administrative student life cycle. Usual tools and practices, commonly applied to (simple) software acquisition, failed in our scenario.
With the case study introduced in this paper, we address all persons, involved within software acquisition processes: From our experiences, we strongly recommend to place greater value on an exhaustively completed acquisition process, than on short-termed economic advantages.
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.
Verschiedene intelligente Heimautomatisierungsgeräte wie Lampen, Schlösser und Thermostate verbreiten sich rasant im privaten Umfeld. Ein typisches Kommunikationsprotokoll für diese Geräteklasse ist Bluetooth Low Energy (BLE). In dieser Arbeit wird eine strukturierte Sicherheitsanalyse für BLE vorgestellt. Die beschriebene Vorgehensweise kategorisiert bekannte Angriffsvektoren und beschreibt einen möglichen Aufbau für eine Analyse. Im Zuge dieser Arbeit wurden einige sicherheitsrelevante Probleme aufgedeckt, die es Angreifern ermöglichen die Geräte vollständig zu übernehmen. Es zeigte sich, dass im Standard vorgesehene Sicherheitsfunktionen wie Verschlüsselung und Integritätsprüfungen häufig gar nicht oder fehlerhaft implementiert sind.
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.
Solar energy is one option to serve the rising global energy demand with low environmental impact. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic (PV) systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data.
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.
“Building Bridges Across Continents” (BBAC) is an intercultural and student-centered project that seeks to promote international communication and helps students develop competencies in entrepreneurship, international trade and global cultural awareness. The project, which is in its fourth phase of implementation, connects students from the United States, Germany, Ghana and Kenya with the help of Information Communication Technologies (ICT) in order to work on a common research assignment for a period of ten calendar weeks. The main ICTs used in the project are Skype, Facebook, wiki, email and WhatsApp. This paper describes and analyzes the background, structure, and results of the project.
Higher Education Institutions (HEIs) should, on the one hand, provide theoretical and practical knowledge to students and, on the other hand, make valuable contributions to theoretical knowledge and provide new insights by means of research. However, HEIs have to face changing and increasing demands with respect to what they are expected to achieve. Education and research issues are no longer enough, what matters today is the so called “third mission”. A specific example for implementing a third mission is the cooperation between HEIs and business incubators. With this in mind, a local consortium consisting of regional HEIs, e.g. Bonn-Rhein-Sieg University of Applied Sciences, as well as public and private institutions and partners initiated and established an incubator hub for the region Bonn/Rhein-Sieg in 2016, called “Digital Hub Region Bonn”. This conference contribution reports on our experience with regards to this cooperation approach resulting from the above- mentioned case. Furthermore the pros and cons as well as some issues of this kind of cooperation will be discussed. Last but not least this paper initiates the opportunity to share and compare the experiences of other university business incubators in Africa as well as in Germany. As we will describe, the financial investment of HEIs in a joint-incubator with other public as well as private partners offers substantial benefits, such as mutual know-how transfer from HEIs to the economy and vice versa. This strengthens entrepreneurial mindsets and activities and contributes to the development and growth of the local economy. Consequently, this cooperation sometimes creates challenges at various levels, for example due to differing interests between HEIs and business partners. This conference contribution offers approaches to solve these issues and to support private public partnership in business incubation.
Real-World Performance of current Mesh Protocols in a small-scale Dual-Radio Multi-Link Environment
(2017)
Two key questions motivated the work in this paper: What is the impact of different usage schemes for multiple channels in a dual-radio Wireless Mesh Network (WMN), and what is the impact of some popular WMN routing protocols on its performance. These two questions were evaluated in a small and simple real-world scenario. A major concern was reproducibility of the results. We show that it is beneficial to use both radios on different frequencies in a fully meshed environment with four routers. The routing protocols Babel, B.A.T.M.A.N. V, BMX7 and OLSRv2 recognize a saturated channel and prefer the other one. We show that in our scenario all of the protocols perform equally well since the protocol overhead is comparably low not influencing the overall performance of the network.
In diesem Paper wird das abbildende Millimeterwellen-Radarsystem SAMMI® (Stand Alone MilliMeter wave Imager) des Fraunhofer-Institutes für Hochfrequenzphysik und Radartechnik FHR vorgestellt. SAMMI ist ein CW System welches bei einer Messfrequenz von 78 GHz die Proben in Transmission vermisst. Durch ein Endlosband wird ein kontinuierlicher Materialstrom sichergestellt, wobei ein DIN A4 Blatt innerhalb von 20 s durchleuchtet wird. SAMMI besitzt die Größe eines durchschnittlichen Laserdruckers wodurch es leicht zu transportieren und in wenigen Minuten einsatzbereit ist. Die mittels SAMMI erfassten Messdaten, können bereits während der Datenerfassung mit verschiedenen bereits vorinstallierten Verfahren aufbereitet und analysiert werden. Zu den integrierten Algorithmen in SAMMI® gehören unter anderen Verfahren zum 2D-Phase Unwrapping-, Cluster- und Rekonstruktions-Algorithmen zur Berechnung der Materialparameter. Die offene Softwareschnittstelle erlaubt auch die Implementierung eigener Verfahren auf der mitgelieferten Computer-Hardware. Mit den integrierten Algorithmen bietet SAMMI® eine Vielzahl an Möglichkeiten um z.B. Verunreinigungen in Materialien zu detektieren oder Schwankungen im Fertigungsprozess frühzeitig zu identifizieren. Desweiteren ist SAMMI® eine optimale Ausbildungsplattform in den Bereichen der industriellen Bildverarbeitung mittels Hochfrequenzsensoren. Insbesondere können Verfahren für unterschiedliche Anwendungen getestet bzw. für Anwendungen weiterentwickelt werden. Es werden konkrete Beispiele aus dem Bereich der Qualitätssicherung erläutert und Möglichkeiten des Gerätes und der Millimeterwellen-Technologie für die zerstörungsfreie Prüfung in Detail beschrieben.
In January 2015, German trade and industry announced to support the national animal welfare initiative "Initiative Tierwohl" (ITW) which stands for a more sustainable and animal-friendly meat production. A web content analysis shows that the ITW initiative has been widely picked up and discussed by online media and that user comments are quite heterogeneous. The current study identifies different types of consumers through factor and cluster analysis and is based on an online survey as well as face-to-face interviews. According to our results, the identified consumer groups demonstrate a rather passive comment behaviour on the internet. In fact, the internet was hardly mentioned as an information source for meat production; consumers more frequently referred to brochures, leaflets and personal contacts with sales personnel.
Argentina substantially contributes to the global organic agriculture and food sector due to its large areas of organically managed agricultural land. However, most of the organic production is foreseen for export. Overall, food supply for the domestic organic market is hardly tapped. This study investigates the current importance of organic agriculture and food production as well as its consumption within the country. The novelty of the study also lies in the observation, documentation and analysis of latest stakeholder-driven developments towards organic agriculture and food. The publication allows to make the Argentinian organic market significantly more visible for the international audience.
Food losses occur for many reasons at all stages of supply chains for fruits, vegetables and potatoes. They cause immense economic, environmental and social costs – not only in developing countries but also in developed countries. According to the European Commission, about 90 million tonnes of food are wasted annually in Europe alone. However, particularly for the early stages of supply chains for fruits, vegetables and potatoes there is still a lack of reliable data. Thus, one objective of this study is to contribute to the quantification of food losses between field and retail, where the main focus is set on potatoes, apples, carrots, strawberries and asparagus. Furthermore, neither reasons why products are removed from the supply chains nor their alternative uses are fully examined yet. This is why, the study takes a look on those issues, too. Results are based on data from an online survey among producers of fruits, vegetables and potatoes in North-Rhine Westphalia, Germany and on interviews with producers and other supply chain experts. Findings suggest that the products’ size and form, their storage capabilities and food safety issues have big impacts on food losses. Despite a small sample size, these findings are in line with recent studies.
WiFi-based Long Distance (WiLD) networks have emerged as a promising alternative approach for Internet in rural areas. The main hardware components of these networks are commercial off-the-shelf WiFi radios and directional antennas. During our experiences with real-world WiLD networks, we encountered that interference among long-distance links is a major issue even with high gain directional antennas. In this work, we are providing an in-depth analysis of these interference effects by conducting simulations in ns-3. To closely match the real-world interference effects, we implemented a module to load radiation pattern of commonly used antennas. We analyze two different interference scenarios typically present as a part of larger networks. The results show that side-lobes of directional antennas significantly influence the throughput of long-distance WiFi links depending on the orientation. This work emphasizes that the usage of simple directional antenna models needs to be considered carefully.
Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.
Tierexperimentell konnte nachgewiesen werden, dass spezifische Ionenkanäle (vor allem TRPA1) des nozizeptiven Systems nachhaltig durch die Exposition mit blauem Licht moduliert werden können. Durch Nachweis der Wirksamkeit von nicht-visuellen Effekten einer Lichtexposition auf Somatosensorik und Nozizeption beim Menschen könnte der Einsatz einer Lichttherapie bei Patienten mit Erkrankungen des somatosensorischen Systems, insbesondere neuropathischen Schmerzen, von großer Bedeutung sein.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data. Hence the generation of robust reviewed global irradiance data is an essential contribution for the energy transition.
Agricultural activities within the city boundaries have a long history in both developed and developing countries. Especially in developing countries these activities contribute to food security and the mitigation of malnutrition (food grown for home consumption). They generate additional income and contribute to recreation, environmental health as well as social interaction. In this paper, a broad approach of Urban AgriCulture is used, which includes the production of crops in urban and peri-urban areas and ranges in developed countries from allotment gardens (Schrebergarten) over community gardens (Urban Gardening) to semi-entrepreneurial self-harvest farms and fully commercialized agriculture (Urban Farming). Citizens seek to make a shift from traditional to new (sustainable) forms of food supply. From this evolves a demand for urban spaces that can be used agriculturally. The way how these citizens’ initiatives can be supported and their contribution to a resilient and sustainable urban food system increasingly attracts attention. This paper presents an empirical case study on Urban AgriCulture initiatives in the Bonn-Rhein-Sieg region (Germany). Urban AgriCulture is still a niche movement with the potential to contribute more significantly to urban development and constitute a pillar of urban quality of life.
This paper examines how students learn to collaborate in English by participating in an intercultural project that focuses on teaching students to work together on a digital writing project using various online tools, and participated in this digital collaboration project. Mixed groups of students, two French and two German, used several synchronous and asynchronous tools to communicate with their counterparts (Facebook, WordPress blog, WIMS e-learning platform, email, videoconferencing). Students had to produce an article together, comparing French and German attitudes about a topic they negotiated freely in their groups. Before publishing their post, students were expected to peer-review the article written by their group. Once published, the stage consisted of voting for the best posts on the e-learning platform, WIMS. A videoconference was also organized to create cohesion between the participants. The result of the student evaluations, together with the administrative, technical vastly differing university setups is presented.
WiFi-based Long Distance (WiLD) networks have emerged as a promising alternative approach for Internet in rural areas. However, the MAC layer, which is based on the IEEE802.11 standard, comprises contiguous stations in a cell and is spatially restricted to a few hundred meters at most. In this work, we summarize efforts by different researchers to use IEEE802.11 over long-distances. In addition, we introduce WiLDToken, our solution to optimizing the throughput and fairness and reducing the delay on WiLD links. Compared to previous alternative MAC layers protocols for WiLD, our focus is on optimizing a single link in a multi-radio multi-channel mesh. We implement our protocol in the ns-3 network simulator and show thatWiLDToken is superior to an adapted version of the Distributed Coordination Function (DCF) for different link distances. We find that the throughput on a single link is close to the physical data-rate without a major decrease over longer distances.
WiFi-based Long Distance (WiLD) networks have emerged as a promising alternative technology approach for providing Internet in rural areas. An important factor in network planning of these wireless networks is estimating the path loss. In this work, we present various propagation models we found suitable for point-to-point (P2P) operation in the WiFi frequency bands. We conducted outdoor experiments with commercial offthe- shelf (COTS) hardware in our testbed made of 7 different long-distance links ranging from 450 m to 10.3 km and a mobile measurement station. We found that for short links with omni-directional antennas ground-reflection is a measurable phenomenon. For longer links, we show that either FSPL or the Longley-Rice model provides accurate results for certain links. We conclude that a good site survey is needed to exclude influences not included in the propagation models.
Softwareentwickelnde kleine und mittlere Unternehmen (KMU) erkennen zunehmend, dass die nutzerzentrierte Gestaltung ein wichtiges, oft entscheidendes Kriterium für die Benutzerfreundlichkeit und damit den Erfolg ihrer Produkte ist. Stolpersteine auf dem Weg zum erfolgreichen Usability- und User Experience-Engineering sind dabei allerdings häufig die Unkenntnis der passenden Methoden bzw. die Befürchtung zu hohen Aufwands an Ressourcen und von Verzögerungen in der Produktentwicklung (vgl. Stade et al., 2013; Reckin & Brandenburg, 2013; Woywode et al., 2011).
Die Vorteile, Nutzer aktiv, früh und langfristig in ntwicklungsprozesse zu integrieren, um Fehlentwicklungen zu vermeiden und Nutzerbedürfnisse zu adressieren, sind nicht nur in der akademischen Forschung bekannt. Prozesse und Strukturen in Unternehmen der IKT-Branche sind bereits häufig agil implementiert. Dennoch schaffen es kleine und mittlere Unternehmen (KMU) oftmals nicht, die Potentiale einer Nutzerintegration konsequent auszuschöpfen. In Fallstudien wurden drei unterschiedliche KMU analysiert, wie sie die Stimme des Nutzers im Entwicklungsprozess berücksichtigen. Unterschiedliche Strategien der Nutzerintegration, die sich in Rollen und Werkzeugen, in Anforderungen und Problemen an das Nutzersample, Methoden und Datenaufbereitung widerspiegeln, werden beleuchtet. Unser Beitrag soll helfen, Herausforderungen und Probleme von KMU auf der Suche nach angemessenen und passgenauen Wegen der Nutzerintegration zu verstehen und Lösungen zu gestalten.
Das Konzept des Living Lab ist eine in der Wissenschaft anerkannte Innovations- und Forschungsmethodik. Im betrieblichen Kontext - insbesondere in kleinen und mittleren Unternehmen (KMU) – wird sie bislang jedoch kaum genutzt. Um die Nutzung im kommerziellen Kontext von Smart Home zu erforschen, wird im Forschungsprojekt SmartLive aktuell ein Living Lab zum Thema aufgebaut, bei dem Unternehmen, Forscher sowie ca. 30 teilnehmenden Haushalte die alltägliche Nutzung von kommerziellen, sowie experimentell entwickelten Lösungen untersuchen und neue Interaktionskonzepte gemeinsam erarbeiten. Ferner wurden mit den teilnehmenden Unternehmen Interviews zu deren Entwicklungsprozessen, deren Einstellung zu Usability und User Experience (UUX), sowie den Potenzialen und Möglichkeiten eines Living Labs für KMU geführt. Ziel der Interviews ist es, darauf aufbauend UUX-Dienstleistungen zu identifizieren, die rund um ein kommerziell betriebenes Living Lab angeboten werden können. Hierbei wurde zunächst das Kompetenz-Netzwerk als ein wichtiges Asset eines Living Lab hervorgehoben, da es eine projektförmige Kooperation fördert. Zudem wurde der Bedarf nach flexiblen Dienstleistungen ähnlich einem Baukastensystem deutlich, mit dessen Hilfe relativ kurzfristig als auch nachhaltige innovative Konzepte erprobt, Marketingstrategien entwickelt sowie prototypische Entwicklungen hinsichtlich UUX und technischer Qualität evaluiert werden können.
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Although much effort is made to prevent risks arising from food, food-borne diseases are an ever present-threat to the consumers’ health. The consumption of fresh food that is contaminated with pathogens like fungi, viruses or bacteria can cause food poisoning that leads to severe health damages or even death. The outbreak of Shiga Toxin-producing enterohemorrhagic E. coli (EHEC) in Germany and neighbouring countries in 2011 has shown this dramatically. Nearly 4.000 people were reported of being affected and more than 50 people died during the so called EHEC-crisis. As a result the consumers’ trust in the safety of fruits and vegetables decreased sharply.
Sustainable development needs sustainable production and sustainable consumption. During the last decades the encouragement of sustainable production has been the focus of research and policy makers under the implicit assumption that the observable increasing ‘green’ values of consumers would also entail a growing sustainable consumption. However, it has been found that the actual purchasing behaviour often deviates from ‘green’ attitudes. This phenomenon is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications.
Solar energy is one option to serve the rising global energy demand with low environmental impact.1 Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections. Clouds are moving on a short term timescale and have a high influence on the available solar radiation, as they absorb, reflect and scatter parts of the incoming light.2 However, the impact of cloudiness on photovoltaic power yields (PV) and cloud induced deviations from average yields might vary depending on the technology, location and time scale under consideration.
Solar energy is one option to serve the rising global energy demand with low environmental Impact [1]. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections. Clouds are moving on a short term timescale and have a high influence on the available solar radiation, as they absorb, reflect and scatter parts of the incoming light [2]. However, modeling photovoltaic (PV) power yields with a spectral resolution and local cloud information gives new insights on the atmospheric impact on solar energy.
An Empirical Evaluation of the Received Signal Strength Indicator for fixed outdoor 802.11 links
(2015)
For the evaluation of the received signal strength indication (RSSI) a different methodology compared to previous publications is introduced in this paper by exploiting a spectral scan feature of recent Qualcomm Atheros WiFi NICs. This method is compared to driver reports and to an industrial grade spectrum analyzer. During the conducted outdoor experiments a decreased scattering of the RSSI compared to previous publications is observed. By applying well-known mathematical tests for normality it is possible to show that the RSSI does not follow a normal distribution in a line-of-sight outdoor environment. The evaluated spectral scan features offers additional possibilities to develop interference classifiers which is an important step for frequency allocation in long-distance 802.11 networks.