Refine
Year of publication
- 2021 (39) (remove)
Document Type
- Article (39) (remove)
Has Fulltext
- yes (39)
Keywords
- Katastrophenmanagement (2)
- Risikomanagement (2)
- Wärmeübertragung (2)
- 11M41 (1)
- 11S80 (1)
- AGMD (1)
- Activity Recognition (1)
- Adaptation (1)
- Aerial Image (1)
- Affordability (1)
Faculty
- Fakultät 12 / Institut für Technologie und Ressourcenmanagement in den Tropen und Subtropen (7)
- Angewandte Naturwissenschaften (F11) (5)
- Fakultät 10 / Institut Allgemeiner Maschinenbau (5)
- Fakultät 07 / Institut für Nachrichtentechnik (4)
- Fakultät 09 / Institut für Rettungsingenieurwesen und Gefahrenabwehr (4)
- Fakultät 09 / Institut Anlagen und Verfahrenstechnik (3)
- Fakultät 01 / Institut für Geschlechterstudien (2)
- Fakultät 04 / Schmalenbach Institut für Wirtschaftswissenschaften (2)
- Fakultät 01 / Institut für Medienforschung und Medienpädagogik (1)
- Fakultät 02 / Cologne Game Lab (1)
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.
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.
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.
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.
We study p-adic L-functions Lp(s, 휒) for Dirichlet characters 휒. We show that Lp(s, 휒) has a Dirichlet series expansion for each regularization parameter c that is prime to p and the conductor of 휒. The expansion is proved by transforming a known formula for p-adic L-functions and by controlling the limiting behavior. A fnite number of Euler factors can be factored of in a natural manner from the p-adic Dirichlet series. We also provide an alternative proof of the expansion using p-adic measures and give an explicit formula for the values of the regularized Bernoulli distribution. The result is particularly simple for c = 2, where we obtain a Dirichlet series expansion that is similar to the complex case.
In the literature, many studies outline the advantages of agrivoltaic (APV) systems from different viewpoints: optimized land use, productivity gain in both the energy and water sector, economic benefits, etc. A holistic analysis of an APV system is needed to understand its full advantages. For this purpose, a case study farm size of 0.15 ha has been chosen as a reference farm at a village in Niger, West Africa. Altogether four farming cases are considered. They are traditional rain-fed, irrigated with diesel-powered pumps, irrigated with solar pumps, and the APV system. The APV system is further analyzed under two scenarios: benefits to investors and combined benefits to investors and farmers. An economic feasibility analysis model is developed. Different economic indicators are used to present the results: gross margin, farm profit, benefit-cost ratio, and net present value (NPV). All the economic indicators obtained for the solar-powered irrigation system were positive, whereas all those for the diesel-powered system were negative. Additionally, the diesel system will emit annually about 4005 kg CO2 to irrigate the chosen reference farm. The land equivalent ratio (LER) was obtained at 1.33 and 1.13 for two cases of shading-induced yield loss excluded and included, respectively.
High-quality rendering of spatial sound fields in real-time is becoming increasingly important with the steadily growing interest in virtual and augmented reality technologies. Typically, a spherical microphone array (SMA) is used to capture a spatial sound field. The captured sound field can be reproduced over headphones in real-time using binaural rendering, virtually placing a single listener in the sound field. Common methods for binaural rendering first spatially encode the sound field by transforming it to the spherical harmonics domain and then decode the sound field binaurally by combining it with head-related transfer functions (HRTFs). However, these rendering methods are computationally demanding, especially for high-order SMAs, and require implementing quite sophisticated real-time signal processing. This paper presents a computationally more efficient method for real-time binaural rendering of SMA signals by linear filtering. The proposed method allows representing any common rendering chain as a set of precomputed finite impulse response filters, which are then applied to the SMA signals in real-time using fast convolution to produce the binaural signals. Results of the technical evaluation show that the presented approach is equivalent to conventional rendering methods while being computationally less demanding and easier to implement using any real-time convolution system. However, the lower computational complexity goes along with lower flexibility. On the one hand, encoding and decoding are no longer decoupled, and on the other hand, sound field transformations in the SH domain can no longer be performed. Consequently, in the proposed method, a filter set must be precomputed and stored for each possible head orientation of the listener, leading to higher memory requirements than the conventional methods. As such, the approach is particularly well suited for efficient real-time binaural rendering of SMA signals in a fixed setup where usually a limited range of head orientations is sufficient, such as live concert streaming or VR teleconferencing.
Kompetenzen auf dem Gebiet der Datenbanken gehören zum Pflichtbereich der Informatik. Das Angebot an Lehrbüchern, Vorlesungsformaten und Tools lässt sich jedoch für Lehrende oft nur eingeschränkt in die eigene Lehre integrieren. In diesem Aufsatz schildern wir unsere Erfahrungen in der Nutzung (frei) verfügbarer und der Entwicklung eigener digitaler Inhalte für grundlegende Datenbankveranstaltungen. Die Präferenzen der Studierenden werden mittels Nutzungsanalysen und Befragungen ermittelt. Wir stellen die Anforderungen auf, wie die nicht selten aufwendig herzustellenden digitalen Materialien von Lehrenden in ihre Lehr- und Lernumgebungen integriert werden können. Als konstruktive Antwort auf diese Herausforderung wird das Konzept EILD zur Entwicklung von Inhalten für die Lehre im Fach Datenbanken vorgestellt. Die Inhalte sollen in vielfältigen Lernszenarien eingesetzt werden können und mit einer Creative Commons (CC) Lizenzierung als OER (open educational resources) frei zur Verfügung stehen.
In child–robot interaction (cHRI) research, many studies pursue the goal to develop interactive systems that can be applied in everyday settings. For early education, increasingly, the setting of a kindergarten is targeted. However, when cHRI and research are brought into a kindergarten, a range of ethical and related procedural aspects have to be considered and dealt with. While ethical models elaborated within other human–robot interaction settings, e.g., assisted living contexts, can provide some important indicators for relevant issues, we argue that it is important to start developing a systematic approach to identify and tackle those ethical issues which rise with cHRI in kindergarten settings on a more global level and address the impact of the technology from a macroperspective beyond the effects on the individual. Based on our experience in conducting studies with children in general and pedagogical considerations on the role of the institution of kindergarten in specific, in this paper, we enfold some relevant aspects that have barely been addressed in an explicit way in current cHRI research. Four areas are analyzed and key ethical issues are identified in each area: (1) the institutional setting of a kindergarten, (2) children as a vulnerable group, (3) the caregivers’ role, and (4) pedagogical concepts. With our considerations, we aim at (i) broadening the methodology of the current studies within the area of cHRI, (ii) revalidate it based on our comprehensive empirical experience with research in kindergarten settings, both laboratory and real-world contexts, and (iii) provide a framework for the development of a more systematic approach to address the ethical issues in cHRI research within kindergarten settings.
The paper focused on an analytical analysis of the main features of heat transfer in incompressible steady-state flow in a microconfusor with account for the second-order slip boundary conditions. The second-order boundary conditions serve as a closure of a system of the continuity, transport, and energy differential equations. As a result, novel solutions were obtained for the velocity and temperature profiles, as well as for the friction coefficient and the Nusselt number. These solutions demonstrated that an increase in the Knudsen number leads to a decrease in the Nusselt number. It was shown that the account for the second-order terms in the boundary conditions noticeably affects the fluid flow characteristics and does not influence on the heat transfer characteristics. It was also revealed that flow slippage effects on heat transfer weaken with an increase in the Prandtl number.
Floods are a known natural hazard in Germany, but the amount of precipitation and ensuing high death toll and damages after the events especially from 14 to 15 July 2021 came as a surprise. Almost immediately questions about failure in the early warning chains and the effectiveness of the German response emerged, also internationally. This article presents lessons to learn and argues against a blame culture. The findings are based on comparisons with findings from previous research projects carried out in the Rhein-Erft Kreis and the city of Cologne, as well as on discussions with operational relief forces after the 2021 events. The main disaster aspects of the 2021 flood are related to issuing and understanding warnings, a lack of information and data exchange, unfolding upon a situation of an ongoing pandemic and aggravated further by critical infrastructure failure. Increasing frequencies of flash floods and other extremes due to climate change are just one side of the transformation and challenge, Germany and neighbouring countries are facing. The vulnerability paradox also heavily contributes to it; German society became increasingly vulnerable to failure due to an increased dependency on its infrastructure and emergency system, and the ensuing expectations of the public for a perfect system.