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Water scarcity drives governments in arid and semi-arid regions to promote strategies for improving water use efficiency. Water-related research generally also plays an important role in the same countries and for the same reason. However, it remains unclear how to link the implementation of new government strategies and water-related research. This article’s principal objective is to present a novel approach that defines water-related research gaps from the point of view of a government strategy. The proposed methodology is based on an extensive literature review, followed by a systematic evaluation of the topics covered both in grey and peer-reviewed literature. Finally, we assess if and how the different literature sources contribute to the goals of the water strategy. The methodology was tested by investigating the impact of the water strategy of Jordan’s government (2008–2022) on the research conducted in the Azraq Basin, considering 99 grey and peer-reviewed documents. The results showed an increase in the number of water-related research documents from 37 published between 1985 and 2007 to 62 published between 2008 and 2018. This increase should not, however, be seen as a positive impact of increased research activity from the development of Jordan’s water strategy. In fact, the increase in water-related research activity matches the increasing trend in research production in Jordan generally. Moreover, the results showed that only about 80% of the documents align with the goals identified in the water strategy. In addition, the distribution of the documents among the different goals of the strategy is heterogeneous; hence, research gaps can be identified, i.e., goals of the water-strategy that are not addressed by any of the documents sourced. To foster innovative and demand-based research in the future, a matrix was developed that linked basin-specific research focus areas (RFAs) with the MWI strategy topics. In doing so, the goals that are not covered by a particular RFA are highlighted. This analysis can inspire researchers to develop and apply new topics in the Azraq Basin to address the research gaps and strengthen the connection between the RFAs and the strategy topics and goals. Moreover, the application of the proposed methodology can motivate future research to become demand-driven, innovative, and contribute to solving societal challenges.
An Analytical Investigation of Natural Convection of a Van Der Waals Gas over a Vertical Plate
(2021)
The study focused on a theoretical study of natural convection in a van der Waals gasnear a vertical plate. A novel simplified form of the van der Waals equation derived in the studyenabled analytical modeling of fluid flow and heat transfer. Analytical solutions were obtained forthe velocity and temperature profiles, as well as the Nusselt numbers. It was revealed that nonlineareffects considered by the van der Waals equation of state contribute to acceleration or decelerationof the flow. This caused respective enhancement or deterioration of heat transfer. Results for a vander Waals gas were compared with respective computations using an ideal gas model. Limits of theapplicability of the simplified van der Waals equations were pinpointed.
The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.
The increase in greenhouse gas emissions, mainly due to the burning of fossil fuels and land use change, has led to changes in the global climate. Agriculture is one of the economic sectors most vulnerable to the impacts generated by climate change. For this reason, the challenge facing humanity today is to develop innovative solutions to address the complexity of agricultural sustainability.
On the other hand, sugarcane is one of the crops that emits the most pollutants into the atmosphere, mainly due to the burning of sugarcane before and after harvesting. Most of these atmospheric pollutants are precursors of climate change and have an impact on the health and quality of life of communities. Moreover, this agricultural practice causes the gradual deterioration of the soil, directly affecting sugarcane production. Consequently, several sugarcane-producing countries have established regulations or dispositions to eliminate this agricultural practice, and one option to eliminate it is the mechanization of harvesting. However, its implementation implies social, environmental, and economic impacts that must be analyzed systemically to avoid potential failures during the technological transition process. It is for this reason that this research, through the MICMAC method, focused on identifying the variables associated with the reduction of sugarcane burning in Campos dos Goytacazes and Tamasopo, to subsequently analyze their direct and indirect interrelationship, and, thus, determine the opportunities and limitations of each locality for the reduction of sugarcane burning.
Through this analysis, it became evident that although the technological transition is an imminent step for the sustainability of sugarcane cultivation, certain factors such as legislation, technological innovation, and the perception of the stakeholders regarding the consequences of sugarcane burning, is what defines in the study sites the speed and subsequent success of this process of change towards green harvesting.
Human civilization has a great history of managing Water, Sanitation, and Hygiene (WaSH) services. But such services in rural areas have been neglected throughout our history. Numerous multimillion dollars WaSH interventions have been implemented in rural areas to eradicate open defecation, but most of them failed to create a demand for sanitation. Lack of equity and fair participation in approaches to change behavior and mindset, rather than habits, has made it hard for governments to achieve their WaSH related targets. Participatory rural sanitation approaches that focus on behavior change and ownership building among the community members have helped in the transition to open defecation free (ODF) societies. A justice-focused sanitation approach shows potential in fast-tracking this transition. Just transition is a concept that has not been endured in the sanitation discussion yet but shows the potential of sustainable WaSH solutions. This social empirical research has explored the feasibility of a justice-based sanitation approach guiding a transition towards societies with universal access to sanitation services. A just sanitation transition framework was adapted from the considered theoretical foundations and was used to map the capability and justice dimensions of two rural sanitation approaches being implemented in schools in the Mukuyu community in Trans-Nzoia county, Kenya. The adapted framework has been able to compute both sanitation approaches on a scoring tool, quantitatively assessing the productivity and justice dimensions of both approaches. This research has helped in establishing the viability of a just sanitation transition framework to produce an informed understanding of the potential of rural sanitation approaches to produce desired results while being just. Study findings help in filling research gaps and laying the foundation to the just transition debate in the sanitation sector and opens a window to further researches on the same, in the future.
Assessment of the BaFin Guidance Notice on Dealing with Sustainability Risks in Risk Management
(2021)
The elaboration of research addressed the sustainability risks identified in the BaFin Guidance Notice with regard to risk management. Sustainability risks (ESG risks) must be
divided into the three areas: ‘Environment’, ‘Social’ and ‘Governance’. ‘Environment’, which is potentially the largest area of the three, is divided again into physical risks
and transition risks. Physical risks describe the possible impacts of extreme weather events, and transition risks are those that can arise as a result of the transition to a
low-carbon economy (through political decisions or technological developments, for example). According to the BaFin, the Guidance Notice is a ‘compendium of non-binding procedures’ and the measures to be taken by the companies should be based on the type, magnitude and complexity of the risks involved (principle of proportionality).
To compensate the shortage of cyber risk data and offer some indication of the status quo on the data available on cyber risks, the researchers prepared a systematic overview to offer cyber risk stakeholders a database of publicly accessible data on cyber risks and cybersecurity. The study focussed on the data sets used in the academic literature.
Bridging Gaps in Minimum Humanitarian Standards and Shelter Planning by Critical Infrastructures
(2021)
Current agendas such as the Sendai Framework for Disaster Risk Reduction or the Sustain-able Development Goals are demanding more integration of disaster risk management into otherthematic fields and relevant sectors. However, certain thematic fields such as shelter planning andcritical infrastructure have not been integrated yet. This article provides an analysis of minimumhumanitarian standards contained in the well-known Sphere handbook. Gaps are identified forseveral critical infrastructure services. Moreover, guidance on how to derive infrastructure or lifelineneeds has been found missing. This article analyses the missing service supply and infrastructureidentification items and procedures. The main innovation is a more integrative perspective on infras-tructure that can improve existing minimum humanitarian standards. It can guide the provision ofinfrastructure services to various types for different hazard scenarios, hence make humanitarian aidand shelter planning more sustainable in terms of avoiding infrastructure or lifeline shortages.
The paper structure of historical prints is sort of a unique fingerprint. Paper with the same origin shows similar chain line distances. As the manual measurement of chain line distances is time consuming, the automatic detection of chain lines is beneficial. We propose an end-to-end trainable deep learning method for segmentation and parameterization of chain lines in transmitted light images of German prints from the 16th Century. We trained a conditional generative adversarial network with a multitask loss for line segmentation and line parameterization. We formulated a fully differentiable pipeline for line coordinates’ estimation that consists of line segmentation, horizontal line alignment, and 2D Fourier filtering of line segments, line region proposals, and differentiable line fitting. We created a dataset of high-resolution transmitted light images of historical prints with manual line coordinate annotations. Our method shows superior qualitative and quantitative chain line detection results with high accuracy and reliability on our historical dataset in comparison to competing methods. Further, we demonstrated that our method achieves a low error of less than 0.7 mm in comparison to manually measured chain line distances.
The main scope of this work is to develop nano-carbon-based mixed matrix celluloseacetate membranes (MMMs) for the potential use in both gas and liquid separation processes. Forthis purpose, a variety of mixed matrix membranes, consisting of cellulose acetate (CA) polymerand carbon nanotubes as additive material were prepared, characterized, and tested. Multi-walledcarbon nanotubes (MWCNTs) were used as filler material and diacetone alcohol (DAA) as solvent.The first main objective towards highly efficient composite membranes was the proper preparationof agglomerate-free MWCNTs dispersions. Rotor-stator system (RS) and ultrasonic sonotrode (USS)were used to achieve the nanofillers’ dispersion. In addition, the first results of the application of thethree-roll mill (TRM) technology in the filler dispersion achieved were promising. The filler material,MWCNTs, was characterized by scanning electron microscopy (SEM) and liquid nitrogen (LN2)adsorption-desorption isotherms at 77 K. The derivatives CA-based mixed matrix membranes werecharacterized by tensile strength and water contact angle measurements, impedance spectroscopy,gas permeability/selectivity measurements, and water permeability tests. The studied membranesprovide remarkable water permeation properties, 12–109 L/m2/h/bar, and also good separationfactors of carbon dioxide and helium separations. Specifically, a separation factor of 87 for 10%He/N2feed concentration and a selectivity value of 55.4 for 10% CO2/CH4feed concentrationwere achieved.
This paper presents the cognitive module of the Cognitive Architecture for Artificial Intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipeline orchestration and configuration. A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance for further evaluation through the cognitive module. Thus, the cognitive module is able to select feasible and robust configurations for process pipelines in varying use cases. Furthermore, it automatically adapts the models and algorithms based on model quality and resource consumption. The cognitive module also instantiates additional pipelines to evaluate algorithms from different classes on test functions. CAAI relies on well-defined interfaces to enable the integration of additional modules and reduce implementation effort. Finally, an implementation based on Docker, Kubernetes, and Kafka for the virtualization and orchestration of the individual modules and as messaging technology for module communication is used to evaluate a real-world use case.
The paper focuses on a study of turbulence decay in flow with streamwise gradient. For the first time, an analytical solution of this problem was obtained based on the k‐ε model of turbulence in one‐dimensional (1D) approximation, as well as on the symmetry properties of the system of differential equations. Lie group technique enabled reducing the problem to a linear differential equation. The analytical solution enabled parametric studies, which are computationally cheap in comparison to CFD based simulations. The lattice Boltzmann method (LBM) in two‐dimensional approximation (2D) was used to validate the analytical results. Large eddy simulation (LES) Smagorinsky approach was used to close the LBM model. Computations revealed that the rate of turbulence decay is significantly different for the cases of positive and negative streamwise pressure gradient. The further comparisons showed that the analytical solution underpredicts the predictions by the numerical methodology, which can be attributed to the simplified problem statement used to derive the closed‐form analytical solution. Comparisons of calculations with experiments revealed that the theoretical models used in the study underpredict the measurements for flows with a positive pressure gradient. Hence it can be concluded that the LBM technique combined with the LES Smagorinsky model requires the further modification.
Abstract
The paper represents an analysis of convective instability in a vertical cylindrical porous microchannel performed using the Galerkin method. The dependence of the critical Rayleigh number on the Darcy, Knudsen, and Prandtl numbers, as well as on the ratio of the thermal conductivities of the fluid and the wall, was obtained. It was shown that a decrease in permeability of the porous medium (in other words, increase in its porosity) causes an increase in flow stability. This effect is substantially nonlinear. Under the condition Da > 0.1, the effect of the porosity on the critical Rayleigh number practically vanishes. Strengthening of the slippage effects leads to an increase in the instability of the entire system. The slippage effect on the critical Rayleigh number is nonlinear. The level of nonlinearity depends on the Prandtl number. With an increase in the Prandtl number, the effect of slippage on the onset of convection weakens. With an increase in the ratio of the thermal conductivities of the fluid and the wall, the influence of the Prandtl number decreases. At high values of the Prandtl numbers (Pr > 10), its influence practically vanishes.
This presentation briefly introduces my research project: The Covid-19 impact on the Chinese insurance and reinsurance industry. In the following, I will give you some background information, an overview of the macro implications and some details on the impact on each line of business. Finally, I will end with an outlook for the industry following COVID-19.
Remote sensing applications of change detection are increasingly in demand for many areas of land use and urbanization, and disaster risk reduction. The Sendai Framework for Disaster Risk Reduction and the New Urban Agenda by the United Nations call for risk monitoring. This study maps and assesses the urban area changes of 23 Mexican-USA border cities with a remote sensing-based approach. A literature study on existing studies on hazard mapping and social vulnerability in those cities reveals a need for further studies on urban growth. Using a multi-modal combination of aerial, declassified (CORONA, GAMBIT, HEXAGON programs), and recent (Sentinel-2) satellite imagery, this study expands existing land cover change assessments by capturing urban growth back to the 1940s. A Geographic Information System and census data assessment results reveal that massive urban growth has occurred on both sides of the national border. On the Mexican side, population and area growth exceeds the US cities in many cases. In addition, flood hazard exposure has grown along with growing city sizes, despite structural river training. These findings indicate a need for more risk monitoring that includes remote sensing data. It has socio-economic implications, too, as the social vulnerability on Mexican and US sides differ. This study calls for the maintenance and expansion of open data repositories to enable such transboundary risk comparisons. Common vulnerability variable sets could be helpful to enable better comparisons as well as comparable flood zonation mapping techniques. To enable risk monitoring, basic data such as urban boundaries should be mapped per decade and provided on open data platforms in GIS formats and not just in map viewers.
Today, IT infrastructure represents the central nervous system of every company. Many of the activities of our daily lives are handled via the Internet. There is a lack of an adequately sustainable awareness of the cyber risks to which companies are exposed due to advanced digital networking. This is partly due to the fact that the danger of so-called ‘cyber attacks’ is only partially palpable to many, with attacks going unnoticed in some cases. As a result of major incidents, such as WannaCry and Petya in 2017, or Emotet in 2019, awareness of these risks should be keen, and yet vulnerability remains high due to the often insufficient protections against cyber crime.
Educational institutions have increasing needs for professional digital communication. When selecting suitable communication tools, there is a need for appropriate information as a basis for decision-making. Messenger communication in particular is strongly integrated into people's private everyday lives. While needs for extensive data-secure communication in educational contexts are increasing, there is a lack of concepts for data-protected and privacy-preserving support of educational processes through software (Karaboga et al 2014; Digitalcourage e.V. n.d.) , as well as for mandatory training for professionals (Zorn, Tillmann, and Kaminski 2014; Imort and Niesyto 2014), and reliable information for viable software alternatives. This paper outlines the specific requirements of educational institutions when selecting suitable software, using messenger communication as an example. From these requirements, criteria for needed information are presented as a basis for software selection decisions in three categories: data protection/privacy, accessibility/low-barrier, practicability. Since no criteria and good practice suggestions were available so far, a study was conducted to elicit the characteristics of potentially suitable messenger software. To this end, the necessary criteria for the three categories mentioned were first defined and then German and well-known international messengers were tested for data protection criteria. Based on the results for conformity with the EU's General Data Protection Regulation (GDPR) as an inclusion criterion, the messengers in question were subjected to a practical test. In the process, additional practicality criteria were developed, in part iteratively.
In addition to institution-internal messengers, six services were identified among the freely available provider-dependent messengers that can be used in a GDPR-compliant manner, at least for users over the age of 16. At the time of publication, this leaves only five: Threema, Wire, SID, Ginlo, Chiffry. Furthermore, provider-independent messenger systems that adhere to the international standard protocol for the exchange of chat messages (XMPP) appear to be a viable option for educational institutions. In-house or commissioned server hosting would then be possible and a corresponding agreement for commissioned data processing can be concluded with an IT service provider.
The decisions to use "Wire" and "Threema Work" in the IDiT project context are explained and justified. The context was vocational training for prospective office management clerks at vocational schools and vocational training centers. Although the underlying considerations are tailored to the project context (application in the Berufsförderungswerk Köln), they can be generalized.
Ghana suffers from frequent power outages, which can be compensated by off-grid energysolutions. Photovoltaic-hybrid systems become more and more important for rural electrificationdue to their potential to offer a clean and cost-effective energy supply. However, uncertainties relatedto the prediction of electrical loads and solar irradiance result in inefficient system control and canlead to an unstable electricity supply, which is vital for the high reliability required for applicationswithin the health sector. Model predictive control (MPC) algorithms present a viable option to tacklethose uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts.This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA)algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM)model, and (d) a customized statistical approach for electrical load forecasting on real load data of aGhanaian health facility, considering initially limited knowledge of load and pattern changes throughthe implementation of incremental learning. The correlation of the electrical load with exogenousvariables was determined to map out possible enhancements within the algorithms. Results showthat all algorithms show high accuracies with a median normalized root mean square error (nRMSE)<0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMAalgorithm and the linear regression model show extreme error outliers of nRMSE >1, methods viathe LSTM model and the customized statistical approaches perform better with a median nRMSE of0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study isa favoring towards the LSTM model and the statistical approach, with regard to MPC applicationswithin photovoltaic-hybrid system solutions in the Ghanaian health sector.
This bachelor thesis deals with framework-agnostic design systems in the environment of micro frontends. The properties of micro frontends and design systems are developed individually, to finally get combined. Important disciplines of this research are in particular cybernetics and system thinking, whereby further properties in the relationships between the stakeholders and the design system are highlighted and defined. In addition, based on the highlighted properties, a practically oriented evaluation is prepared, which demonstratively verifies how framework-agnostic design systems can be realized using Svelte and Tailwind CSS. The insights gained from this work can be used for further considerations in other works within the domain, or similar domains. In particular the cybernetic view of systematic design offers potential for further investigations.