@article{WolfLondong, author = {Wolf, Mario and Londong, J{\"o}rg}, title = {Transformation der Siedlungswasserwirtschaft - Steuerungsmechanismen im Diskurs ressourcenorientierter Systemans{\"a}tze am Beispiel von Th{\"u}ringen}, series = {Raumforschung und Raumordnung}, volume = {2020}, journal = {Raumforschung und Raumordnung}, number = {Band 78, Heft 4}, publisher = {Sciendo}, doi = {10.2478/rara-2020-0012}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20201022-42731}, pages = {397 -- 411}, abstract = {Neuartige Sanit{\"a}rsysteme zielen auf eine ressourcenorientierte Verwertung von Abwasser ab. Erreicht werden soll dies durch die separate Erfassung von Abwasserteilstr{\"o}men. In den Fach{\"o}ffentlichkeiten der Wasserwirtschaft und Raumplanung werden neuartige Sanit{\"a}rsysteme als ein geeigneter Ansatz f{\"u}r die zuk{\"u}nftige Sicherung der Abwasserentsorgung in l{\"a}ndlichen R{\"a}umen betrachtet. Die Praxistauglichkeit dieser Systeme wurde zwar in Forschungsprojekten nachgewiesen, bisher erschweren jedoch f{\"u}r Abwasserentsorger vielf{\"a}ltige Risiken die Einf{\"u}hrung einer ressourcenorientierten Abwasserbewirtschaftung. Ausgehend von einer Untersuchung der Kontexte bei der Umsetzung eines neuartigen Sanit{\"a}rsystems im l{\"a}ndlichen Raum Th{\"u}ringens wird in diesem Beitrag der Frage nachgegangen, wie auf Landesebene mit dem abwasserwirtschaftlichen Instrumentarium die Einf{\"u}hrung von ressourcenorientierten Systemans{\"a}tzen unterst{\"u}tzt werden kann. Zentrale Elemente des Beitrags sind die Darstellung der wesentlichen Transformationsrisiken in Bezug auf die Einf{\"u}hrung innovativer L{\"o}sungsans{\"a}tze, eine Erl{\"a}uterung der spezifischen abwasserwirtschaftlichen Instrumente sowie die Darlegung von Steuerungsans{\"a}tzen,mit denen die Einf{\"u}hrung von neuartigen Sanit{\"a}rsystemen gef{\"o}rdert werden kann. Im Ergebnis wird die Realisierbarkeit von neuartigen Sanit{\"a}rsystemen durch den strategischen Einsatz des Instrumentariums deutlich, gleichwohl die Wasserwirtschaft durch die Erweiterung der bisherigen Systemgrenzen auf die Kooperation mit anderen Bereichen der Daseinsvorsorge angewiesen ist.}, subject = {Raumordnung}, language = {de} } @misc{VollmerMichel, author = {Vollmer, Lisa and Michel, Boris}, title = {Wohnen in der Klimakrise. Die Wohnungsfrage als {\"o}kologische Frage: Aufruf zur Debatte}, series = {s u b \ u r b a n. zeitschrift f{\"u}r kritische stadtforschung}, volume = {2020}, journal = {s u b \ u r b a n. zeitschrift f{\"u}r kritische stadtforschung}, number = {Band 8, Heft 1/2}, publisher = {Sub\urban e.V.}, address = {Leipzig}, doi = {10.36900/suburban.v8i1/2.552}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210122-43327}, pages = {163 -- 166}, abstract = {Die Verbindung der sozialen und der {\"o}kologischen Frage ist eine der zentralen Herausforderungen linker Politik und kritisch-engagierter Wissenschaft heute. Daf{\"u}r, wie wenig das bisher gelingt, sind die {\"o}ffentlichen und wissenschaftlichen Diskussionen um die Wohnungsfrage gute Beispiele. Dieser Aufruf ist eine Einladung an den kollektiven Wissensschatz aus Wissenschaft und Aktivismus, die unterschiedlichen Aspekte der {\"o}kologischen Wohnungsfrage, die bisher stark fragmentiert behandelt werden, in einzelnen Beitr{\"a}gen weiter auszuf{\"u}hren und auf ihren strukturellen Zusammenhang mit der sozialen Wohnungsfrage hin zu beleuchten.}, subject = {Wohnen}, language = {de} } @article{StaubachMachacekSkowroneketal.2020, author = {Staubach, Patrick and Machacek, Jan and Skowronek, Josefine and Wichtmann, Torsten}, title = {Vibratory pile driving in water-saturated sand: Back-analysis of model tests using a hydro-mechanically coupled CEL method}, series = {Soils and Foundations}, volume = {2021}, journal = {Soils and Foundations}, number = {Volume 61, Issue 1}, publisher = {Elsevier, Science Direct}, address = {Amsterdam}, doi = {10.1016/j.sandf.2020.11.005}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210203-43571}, pages = {144 -- 159}, year = {2020}, abstract = {The development of a hydro-mechanically coupled Coupled-Eulerian-Lagrangian (CEL) method and its application to the back-analysisof vibratory pile driving model tests in water-saturated sand is presented. The predicted pile penetration using this approachis in good agreement with the results of the model tests as well as with fully Lagrangian simulations. In terms of pore water pressure, however, the results of the CEL simulation show a slightly worse accordance with the model tests compared to the Lagrangian simulation. Some shortcomings of the hydro-mechanically coupled CEL method in case of frictional contact problems and pore fluids with high bulk modulus are discussed. Lastly, the CEL method is applied to the simulation of vibratory driving of open-profile piles under partially drained conditions to study installation-induced changes in the soil state. It is concluded that the proposed method is capable of realistically reproducing the most important mechanisms in the soil during the driving process despite its addressed shortcomings.}, subject = {Plastische Deformation}, language = {en} } @article{ShamshirbandBabanezhadMosavietal., author = {Shamshirband, Shahaboddin and Babanezhad, Meisam and Mosavi, Amir and Nabipour, Narjes and Hajnal, Eva and Nadai, Laszlo and Chau, Kwok-Wing}, title = {Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants}, series = {Engineering Applications of Computational Fluid Mechanics}, volume = {2020}, journal = {Engineering Applications of Computational Fluid Mechanics}, number = {volume 14, issue 1}, publisher = {Taylor \& Francis}, doi = {10.1080/19942060.2020.1715842}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200227-41013}, pages = {367 -- 378}, abstract = {A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.}, subject = {Maschinelles Lernen}, language = {en} } @article{Schoenig, author = {Sch{\"o}nig, Barbara}, title = {Ererbte Transformation. Kommentar zu Matthias Bernt und Andrej Holm „Die Ostdeutschlandforschung muss das Wohnen in den Blick nehmen"}, series = {s u b \ u r b a n. zeitschrift f{\"u}r kritische stadtforschung}, volume = {2020}, journal = {s u b \ u r b a n. zeitschrift f{\"u}r kritische stadtforschung}, number = {Band 8, Heft 3}, publisher = {Sub\urban e.V.}, address = {Leipzig}, doi = {10.36900/suburban.v8i3.620}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210122-43296}, pages = {115 -- 122}, abstract = {Matthias Bernt und Andrej Holm weisen zu Recht darauf hin, dass es einer Forschung zu ostdeutschen St{\"a}dten als konzeptionell eigenst{\"a}ndigem Feld bedarf, die die spezifische Verr{\"a}umlichung des tiefgreifenden gesellschaftlichen Transformationsprozesses nach 1990 ins Zentrum stellt. Dabei betrachten sie insbesondere das Feld des Wohnens als produktiv, um Kenntnis {\"u}ber die Struktur und Wirkung dieses Prozesses zu erlangen. Allerdings bleiben sie vage dabei, wie eine solche spezifisch auf Ostdeutschland gerichtete Wohnungsforschung zu konzipieren w{\"a}re und in welcher Weise die Besonderheiten und Parallelit{\"a}ten ostdeutscher Entwicklungen zu den Transformationen von Wohnungs- und Stadtentwicklungspolitik in Westdeutschland, aber auch international, in Bezug zu setzen w{\"a}ren.}, subject = {Deutschland <{\"O}stliche L{\"a}nder>}, language = {de} } @article{SaqlaiGhaniKhanetal., author = {Saqlai, Syed Muhammad and Ghani, Anwar and Khan, Imran and Ahmed Khan Ghayyur, Shahbaz and Shamshirband, Shahaboddin and Nabipour, Narjes and Shokri, Manouchehr}, title = {Image Analysis Using Human Body Geometry and Size Proportion Science for Action Classification}, series = {Applied Sciences}, volume = {2020}, journal = {Applied Sciences}, number = {volume 10, issue 16, article 5453}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/app10165453}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200904-42322}, pages = {24}, abstract = {Gestures are one of the basic modes of human communication and are usually used to represent different actions. Automatic recognition of these actions forms the basis for solving more complex problems like human behavior analysis, video surveillance, event detection, and sign language recognition, etc. Action recognition from images is a challenging task as the key information like temporal data, object trajectory, and optical flow are not available in still images. While measuring the size of different regions of the human body i.e., step size, arms span, length of the arm, forearm, and hand, etc., provides valuable clues for identification of the human actions. In this article, a framework for classification of the human actions is presented where humans are detected and localized through faster region-convolutional neural networks followed by morphological image processing techniques. Furthermore, geometric features from human blob are extracted and incorporated into the classification rules for the six human actions i.e., standing, walking, single-hand side wave, single-hand top wave, both hands side wave, and both hands top wave. The performance of the proposed technique has been evaluated using precision, recall, omission error, and commission error. The proposed technique has been comparatively analyzed in terms of overall accuracy with existing approaches showing that it performs well in contrast to its counterparts.}, subject = {Bildanalyse}, language = {en} } @article{SaadatfarKhosraviHassannatajJoloudarietal., author = {Saadatfar, Hamid and Khosravi, Samiyeh and Hassannataj Joloudari, Javad and Mosavi, Amir and Shamshirband, Shahaboddin}, title = {A New K-Nearest Neighbors Classifier for Big Data Based on Efficient Data Pruning}, series = {Mathematics}, volume = {2020}, journal = {Mathematics}, number = {volume 8, issue 2, article 286}, publisher = {MDPI}, doi = {10.3390/math8020286}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200225-40996}, pages = {12}, abstract = {The K-nearest neighbors (KNN) machine learning algorithm is a well-known non-parametric classification method. However, like other traditional data mining methods, applying it on big data comes with computational challenges. Indeed, KNN determines the class of a new sample based on the class of its nearest neighbors; however, identifying the neighbors in a large amount of data imposes a large computational cost so that it is no longer applicable by a single computing machine. One of the proposed techniques to make classification methods applicable on large datasets is pruning. LC-KNN is an improved KNN method which first clusters the data into some smaller partitions using the K-means clustering method; and then applies the KNN for each new sample on the partition which its center is the nearest one. However, because the clusters have different shapes and densities, selection of the appropriate cluster is a challenge. In this paper, an approach has been proposed to improve the pruning phase of the LC-KNN method by taking into account these factors. The proposed approach helps to choose a more appropriate cluster of data for looking for the neighbors, thus, increasing the classification accuracy. The performance of the proposed approach is evaluated on different real datasets. The experimental results show the effectiveness of the proposed approach and its higher classification accuracy and lower time cost in comparison to other recent relevant methods.}, subject = {Maschinelles Lernen}, language = {en} } @article{PartschefeldWiegandBellmannetal., author = {Partschefeld, Stephan and Wiegand, Torben and Bellmann, Frank and Osburg, Andrea}, title = {Formation of Geopolymers Using Sodium Silicate Solution and Aluminum Orthophosphate}, series = {Materials}, volume = {2020}, journal = {Materials}, number = {Volume 13, issue 18, article 4202}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/ma13184202}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210122-43378}, pages = {1 -- 16}, abstract = {This paper reports the formation and structure of fast setting geopolymers activated by using three sodium silicate solutions with different modules (1.6, 2.0 and 2.4) and a berlinite-type aluminum orthophosphate. By varying the concentration of the aluminum orthophosphate, different Si/Al-ratios were established (6, 3 and 2). Reaction kinetics of binders were determined by isothermal calorimetric measurements at 20 °C. X-ray diffraction analysis as well as nuclear magnetic resonance (NMR) measurements were performed on binders to determine differences in structure by varying the alkalinity of the sodium silicate solutions and the Si/Al-ratio. The calorimetric results indicated that the higher the alkalinity of the sodium silicate solution, the higher the solubility and degree of conversion of the aluminum orthophosphate. The results of X-ray diffraction and Rietveldt analysis, as well as the NMR measurements, confirmed the assumption of the calorimetric experiments that first the aluminum orthophosphate was dissolved and then a polycondensation to an amorphous aluminosilicate network occurred. The different amounts of amorphous phases formed as a function of the alkalinity of the sodium silicate solution, indicate that tetrahydroxoaluminate species were formed during the dissolution of the aluminum orthophosphate, which reduce the pH value. This led to no further dissolution of the aluminum orthophosphate, which remained unreacted.}, subject = {Geopolymere}, language = {en} } @article{OuaerHosseiniAmaretal., author = {Ouaer, Hocine and Hosseini, Amir Hossein and Amar, Menad Nait and Ben Seghier, Mohamed El Amine and Ghriga, Mohammed Abdelfetah and Nabipour, Narjes and Andersen, P{\aa}l {\O}steb{\o} and Mosavi, Amir and Shamshirband, Shahaboddin}, title = {Rigorous Connectionist Models to Predict Carbon Dioxide Solubility in Various Ionic Liquids}, series = {Applied Sciences}, volume = {2020}, journal = {Applied Sciences}, number = {Volume 10, Issue 1, 304}, publisher = {MDPI}, doi = {https://doi.org/10.3390/app10010304}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200107-40558}, pages = {18}, abstract = {Estimating the solubility of carbon dioxide in ionic liquids, using reliable models, is of paramount importance from both environmental and economic points of view. In this regard, the current research aims at evaluating the performance of two data-driven techniques, namely multilayer perceptron (MLP) and gene expression programming (GEP), for predicting the solubility of carbon dioxide (CO2) in ionic liquids (ILs) as the function of pressure, temperature, and four thermodynamical parameters of the ionic liquid. To develop the above techniques, 744 experimental data points derived from the literature including 13 ILs were used (80\% of the points for training and 20\% for validation). Two backpropagation-based methods, namely Levenberg-Marquardt (LM) and Bayesian Regularization (BR), were applied to optimize the MLP algorithm. Various statistical and graphical assessments were applied to check the credibility of the developed techniques. The results were then compared with those calculated using Peng-Robinson (PR) or Soave-Redlich-Kwong (SRK) equations of state (EoS). The highest coefficient of determination (R2 = 0.9965) and the lowest root mean square error (RMSE = 0.0116) were recorded for the MLP-LMA model on the full dataset (with a negligible difference to the MLP-BR model). The comparison of results from this model with the vastly applied thermodynamic equation of state models revealed slightly better performance, but the EoS approaches also performed well with R2 from 0.984 up to 0.996. Lastly, the newly established correlation based on the GEP model exhibited very satisfactory results with overall values of R2 = 0.9896 and RMSE = 0.0201.}, subject = {Maschinelles Lernen}, language = {en} } @article{MosaviShokriMansoretal., author = {Mosavi, Amir Hosein and Shokri, Manouchehr and Mansor, Zulkefli and Qasem, Sultan Noman and Band, Shahab S. and Mohammadzadeh, Ardashir}, title = {Machine Learning for Modeling the Singular Multi-Pantograph Equations}, series = {Entropy}, volume = {2020}, journal = {Entropy}, number = {volume 22, issue 9, article 1041}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/e22091041}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210122-43436}, pages = {1 -- 18}, abstract = {In this study, a new approach to basis of intelligent systems and machine learning algorithms is introduced for solving singular multi-pantograph differential equations (SMDEs). For the first time, a type-2 fuzzy logic based approach is formulated to find an approximated solution. The rules of the suggested type-2 fuzzy logic system (T2-FLS) are optimized by the square root cubature Kalman filter (SCKF) such that the proposed fineness function to be minimized. Furthermore, the stability and boundedness of the estimation error is proved by novel approach on basis of Lyapunov theorem. The accuracy and robustness of the suggested algorithm is verified by several statistical examinations. It is shown that the suggested method results in an accurate solution with rapid convergence and a lower computational cost.}, subject = {Fuzzy-Regelung}, language = {en} }