@article{BielikSchneiderKuligaetal., author = {Bielik, Martin and Schneider, Sven and Kuliga, Saskia and Griego, Danielle and Ojha, Varun and K{\"o}nig, Reinhard and Schmitt, Gerhard and Donath, Dirk}, title = {Examining Trade-Offs between Social, Psychological, and Energy Potential of Urban Form}, series = {ISPRS International Journal of Geo-Information}, volume = {2019}, journal = {ISPRS International Journal of Geo-Information}, editor = {Resch, Bernd and Szell, Michael}, doi = {10.3390/ijgi8020052}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190408-38695}, abstract = {Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal mehods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility. For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages.}, subject = {Planung}, language = {en} } @article{KavrakovLegatiukGuerlebecketal., author = {Kavrakov, Igor and Legatiuk, Dmitrii and G{\"u}rlebeck, Klaus and Morgenthal, Guido}, title = {A categorical perspective towards aerodynamic models for aeroelastic analyses of bridge decks}, series = {Royal Society Open Science}, journal = {Royal Society Open Science}, number = {Volume 6, Issue 3}, doi = {/10.1098/rsos.181848}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190314-38656}, pages = {20}, abstract = {Reliable modelling in structural engineering is crucial for the serviceability and safety of structures. A huge variety of aerodynamic models for aeroelastic analyses of bridges poses natural questions on their complexity and thus, quality. Moreover, a direct comparison of aerodynamic models is typically either not possible or senseless, as the models can be based on very different physical assumptions. Therefore, to address the question of principal comparability and complexity of models, a more abstract approach, accounting for the effect of basic physical assumptions, is necessary. This paper presents an application of a recently introduced category theory-based modelling approach to a diverse set of models from bridge aerodynamics. Initially, the categorical approach is extended to allow an adequate description of aerodynamic models. Complexity of the selected aerodynamic models is evaluated, based on which model comparability is established. Finally, the utility of the approach for model comparison and characterisation is demonstrated on an illustrative example from bridge aeroelasticity. The outcome of this study is intended to serve as an alternative framework for model comparison and impact future model assessment studies of mathematical models for engineering applications.}, subject = {Br{\"u}cke}, language = {en} } @article{MorgenthalEickRauetal., author = {Morgenthal, Guido and Eick, Jan Frederick and Rau, Sebastian and Taraben, Jakob}, title = {Wireless Sensor Networks Composed of Standard Microcomputers and Smartphones for Applications in Structural Health Monitoring}, series = {Sensors - Special Issue Selected Papers from 7th Asia-Pacific Workshop on Structural Health Monitoring}, volume = {2019}, journal = {Sensors - Special Issue Selected Papers from 7th Asia-Pacific Workshop on Structural Health Monitoring}, number = {Volume 19, Issue 9, 2070}, publisher = {MDPI}, doi = {10.3390/s19092070}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190514-39123}, pages = {22}, abstract = {Wireless sensor networks have attracted great attention for applications in structural health monitoring due to their ease of use, flexibility of deployment, and cost-effectiveness. This paper presents a software framework for WiFi-based wireless sensor networks composed of low-cost mass market single-board computers. A number of specific system-level software components were developed to enable robust data acquisition, data processing, sensor network communication, and timing with a focus on structural health monitoring (SHM) applications. The framework was validated on Raspberry Pi computers, and its performance was studied in detail. The paper presents several characteristics of the measurement quality such as sampling accuracy and time synchronization and discusses the specific limitations of the system. The implementation includes a complementary smartphone application that is utilized for data acquisition, visualization, and analysis. A prototypical implementation further demonstrates the feasibility of integrating smartphones as data acquisition nodes into the network, utilizing their internal sensors. The measurement system was employed in several monitoring campaigns, three of which are documented in detail. The suitability of the system is evaluated based on comparisons of target quantities with reference measurements. The results indicate that the presented system can robustly achieve a measurement performance commensurate with that required in many typical SHM tasks such as modal identification. As such, it represents a cost-effective alternative to more traditional monitoring solutions.}, subject = {Structural Health Monitoring}, language = {en} } @article{MosaviShamshirbandEsmaeilbeikietal., author = {Mosavi, Amir and Shamshirband, Shahaboddin and Esmaeilbeiki, Fatemeh and Zarehaghi, Davoud and Neyshabouri, Mohammadreza and Samadianfard, Saeed and Ghorbani, Mohammad Ali and Nabipour, Narjes and Chau, Kwok-Wing}, title = {Comparative analysis of hybrid models of firefly optimization algorithm with support vector machines and multilayer perceptron for predicting soil temperature at different depths}, series = {Engineering Applications of Computational Fluid Mechanics}, volume = {2020}, journal = {Engineering Applications of Computational Fluid Mechanics}, number = {Volume 14, Issue 1}, doi = {10.1080/19942060.2020.1788644}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200911-42347}, pages = {939 -- 953}, abstract = {This research aims to model soil temperature (ST) using machine learning models of multilayer perceptron (MLP) algorithm and support vector machine (SVM) in hybrid form with the Firefly optimization algorithm, i.e. MLP-FFA and SVM-FFA. In the current study, measured ST and meteorological parameters of Tabriz and Ahar weather stations in a period of 2013-2015 are used for training and testing of the studied models with one and two days as a delay. To ascertain conclusive results for validation of the proposed hybrid models, the error metrics are benchmarked in an independent testing period. Moreover, Taylor diagrams utilized for that purpose. Obtained results showed that, in a case of one day delay, except in predicting ST at 5 cm below the soil surface (ST5cm) at Tabriz station, MLP-FFA produced superior results compared with MLP, SVM, and SVM-FFA models. However, for two days delay, MLP-FFA indicated increased accuracy in predicting ST5cm and ST 20cm of Tabriz station and ST10cm of Ahar station in comparison with SVM-FFA. Additionally, for all of the prescribed models, the performance of the MLP-FFA and SVM-FFA hybrid models in the testing phase was found to be meaningfully superior to the classical MLP and SVM models.}, subject = {Bodentemperatur}, language = {en} } @article{ShamshirbandJoloudariGhasemiGoletal., author = {Shamshirband, Shahaboddin and Joloudari, Javad Hassannataj and GhasemiGol, Mohammad and Saadatfar, Hamid and Mosavi, Amir and Nabipour, Narjes}, title = {FCS-MBFLEACH: Designing an Energy-Aware Fault Detection System for Mobile Wireless Sensor Networks}, series = {Mathematics}, volume = {2020}, journal = {Mathematics}, number = {Volume 8, Issue 1, article 28}, publisher = {MDPI}, doi = {10.3390/math8010028}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200107-40541}, pages = {24}, abstract = {Wireless sensor networks (WSNs) include large-scale sensor nodes that are densely distributed over a geographical region that is completely randomized for monitoring, identifying, and analyzing physical events. The crucial challenge in wireless sensor networks is the very high dependence of the sensor nodes on limited battery power to exchange information wirelessly as well as the non-rechargeable battery of the wireless sensor nodes, which makes the management and monitoring of these nodes in terms of abnormal changes very difficult. These anomalies appear under faults, including hardware, software, anomalies, and attacks by raiders, all of which affect the comprehensiveness of the data collected by wireless sensor networks. Hence, a crucial contraption should be taken to detect the early faults in the network, despite the limitations of the sensor nodes. Machine learning methods include solutions that can be used to detect the sensor node faults in the network. The purpose of this study is to use several classification methods to compute the fault detection accuracy with different densities under two scenarios in regions of interest such as MB-FLEACH, one-class support vector machine (SVM), fuzzy one-class, or a combination of SVM and FCS-MBFLEACH methods. It should be noted that in the study so far, no super cluster head (SCH) selection has been performed to detect node faults in the network. The simulation outcomes demonstrate that the FCS-MBFLEACH method has the best performance in terms of the accuracy of fault detection, false-positive rate (FPR), average remaining energy, and network lifetime compared to other classification methods.}, subject = {Vernetzung}, language = {en} } @article{Vollmer, author = {Vollmer, Lisa}, title = {Der Gentrifizierungsbegriff in wohnungspolitischen Protesten. Kommentar zu Neil Smiths „F{\"u}r eine Theorie der Gentrifizierung: ‚Zur{\"u}ck in die Stadt' als Bewegung des Kapitals, nicht der Menschen" (2019 [1979])}, series = {sub\urban. zeitschrift f{\"u}r kritische stadtforschung}, volume = {2019}, journal = {sub\urban. zeitschrift f{\"u}r kritische stadtforschung}, number = {Band 7, Heft 3}, doi = {10.36900/suburban.v7i3.493}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200122-40643}, pages = {113 -- 118}, abstract = {Seit 50 Jahren wird {\"u}ber Erkl{\"a}rungsans{\"a}tze f{\"u}r Gentrifizierung gestritten. Sehr viel l{\"a}nger schon wandert anlagesuchendes Kapital von einem Ort zum anderen und hinterl{\"a}sst dabei Investitionsruinen einerseits und Menschen, die durch Verdr{\"a}ngung ihr Zuhause verlieren, andererseits. Sehr viel k{\"u}rzer erst wird der Begriff Gentrifizierung hier und da von sozialen Bewegungen aufgegriffen, die sich mit letzterem Ph{\"a}nomen auseinandersetzen. In diesem Beitrag soll es nicht um die wissenschaftliche Debatte um Erkl{\"a}rungsans{\"a}tze f{\"u}r Gentrifizierung und auch nicht um die wissenschaftliche Relevanz des Begriffes gehen, sondern um seine Rolle und Funktion in sozialen Bewegungen.}, subject = {Soziale Bewegung}, language = {de} }