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Die Verbindung der sozialen und der ökologischen Frage ist eine der zentralen Herausforderungen linker Politik und kritisch-engagierter Wissenschaft heute. Dafür, wie wenig das bisher gelingt, sind die öffentlichen 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 ökologischen Wohnungsfrage, die bisher stark fragmentiert behandelt werden, in einzelnen Beiträgen weiter auszuführen und auf ihren strukturellen Zusammenhang mit der sozialen Wohnungsfrage hin zu beleuchten.
Why Do Digital Native News Media Fail? An Investigation of Failure in the Early Start-Up Phase
(2020)
Digital native news media have great potential for improving journalism. Theoretically, they can be the sites where new products, novel revenue streams and alternative ways of organizing digital journalism are discovered, tested, and advanced. In practice, however, the situation appears to be more complicated. Besides the normal pressures facing new businesses, entrepreneurs in digital news are faced with specific challenges. Against the background of general and journalism specific entrepreneurship literature, and in light of a practice–theoretical approach, this qualitative case study research on 15 German digital native news media outlets empirically investigates what barriers curb their innovative capacity in the early start-up phase. In the new media organizations under study here, there are—among other problems—a high degree of homogeneity within founding teams, tensions between journalistic and economic practices, insufficient user orientation, as well as a tendency for organizations to be underfinanced. The patterns of failure investigated in this study can raise awareness, help news start-ups avoid common mistakes before actually entering the market, and help industry experts and investors to realistically estimate the potential of new ventures within the digital news industry.
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.
Neuartige Sanitärsysteme zielen auf eine ressourcenorientierte Verwertung von Abwasser ab. Erreicht werden soll dies durch die separate Erfassung von Abwasserteilströmen. In den Fachöffentlichkeiten der Wasserwirtschaft und Raumplanung werden neuartige Sanitärsysteme als ein geeigneter Ansatz für die zukünftige
Sicherung der Abwasserentsorgung in ländlichen Räumen betrachtet. Die Praxistauglichkeit dieser Systeme wurde zwar in Forschungsprojekten nachgewiesen, bisher erschweren jedoch für Abwasserentsorger vielfältige Risiken die Einführung einer ressourcenorientierten Abwasserbewirtschaftung. Ausgehend von einer Untersuchung der Kontexte bei der Umsetzung eines neuartigen Sanitärsystems im ländlichen Raum Thüringens wird in diesem Beitrag der Frage nachgegangen, wie auf Landesebene mit dem abwasserwirtschaftlichen Instrumentarium die Einführung von ressourcenorientierten Systemansätzen unterstützt werden kann. Zentrale Elemente des Beitrags sind die Darstellung der wesentlichen Transformationsrisiken in Bezug auf die Einführung innovativer Lösungsansätze, eine Erläuterung der spezifischen abwasserwirtschaftlichen Instrumente sowie die Darlegung von Steuerungsansätzen,mit denen die Einführung von neuartigen Sanitärsystemen gefördert werden kann. Im Ergebnis wird die Realisierbarkeit von neuartigen Sanitärsystemen 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.
The Marmara Region (NW Turkey) has experienced significant earthquakes (M > 7.0) to date. A destructive earthquake is also expected in the region. To determine the effect of the specific design spectrum, eleven provinces located in the region were chosen according to the Turkey Earthquake Building Code updated in 2019. Additionally, the differences between the previous and updated regulations of the country were investigated. Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) were obtained for each province by using earthquake ground motion levels with 2%, 10%, 50%, and 68% probability of exceedance in 50-year periods. The PGA values in the region range from 0.16 to 0.7 g for earthquakes with a return period of 475 years. For each province, a sample of a reinforced-concrete building having two different numbers of stories with the same ground and structural characteristics was chosen. Static adaptive pushover analyses were performed for the sample reinforced-concrete building using each province’s design spectrum. The variations in the earthquake and structural parameters were investigated according to different geographical locations. It was determined that the site-specific design spectrum significantly influences target displacements for performance-based assessments of buildings due to seismicity characteristics of the studied geographic location.
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.
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.
Städte ohne Wachstum - eine bislang kaum vorstellbare Vision. Doch Klimawandel, Ressourcenverschwendung, wachsende soziale Ungleichheiten und viele andere Zukunftsgefahren stellen das bisherige Allheilmittel Wachstum grundsätzlich infrage. Wie wollen wir heute und morgen zusammenleben? Wie gestalten wir ein gutes Leben für alle in der Stadt? Während in einzelnen Nischen diese Fragen bereits ansatzweise beantwortet werden, fehlt es noch immer an umfassenden Entwürfen und Transformationsansätzen, die eine fundamental andere, solidarische Stadt konturieren. Diesen Versuch wagt das Projekt Postwachstumsstadt.
In diesem Buch werden konzeptionelle und pragmatische Aspekte aus verschiedenen Bereichen der Stadtpolitik zusammengebracht, die neue Pfade aufzeigen und verknüpfen. Die Beiträge diskutieren städtische Wachstumskrisen, transformative Planung und Konflikte um Gestaltungsmacht. Nicht zuletzt wird dabei auch die Frage nach der Rolle von Stadtutopien neu gestellt. Dadurch soll eine längst fällige Debatte darüber angestoßen werden, wie sich notwendige städtische Wenden durch eine sozialökologische Neuorientierung vor Ort verwirklichen lassen.
This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES) based on a deep learning neural network (DLNN) model and an ensemble particle swarm optimization (PSO) algorithm with DLNN (PSO-DLNN), comparing these approaches with common artificial neural network (ANN) and support vector machine (SVM) models in Shirahan watershed, Iran. For this purpose, 13 independent variables affecting GES in the study area, namely, altitude, slope, aspect, plan curvature, profile curvature, drainage density, distance from a river, land use, soil, lithology, rainfall, stream power index (SPI), and topographic wetness index (TWI), were prepared. A total of 132 gully erosion locations were identified during field visits. To implement the proposed model, the dataset was divided into the two categories of training (70%) and testing (30%). The results indicate that the area under the curve (AUC) value from receiver operating characteristic (ROC) considering the testing datasets of PSO-DLNN is 0.89, which indicates superb accuracy. The rest of the models are associated with optimal accuracy and have similar results to the PSO-DLNN model; the AUC values from ROC of DLNN, SVM, and ANN for the testing datasets are 0.87, 0.85, and 0.84, respectively. The efficiency of the proposed model in terms of prediction of GES was increased. Therefore, it can be concluded that the DLNN model and its ensemble with the PSO algorithm can be used as a novel and practical method to predict gully erosion susceptibility, which can help planners and managers to manage and reduce the risk of this phenomenon.
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.
Der Beitrag verbindet die Diskussion um die postpolitische Stadt mit der zunehmenden wissenschaftlichen und aktivistischen Auseinandersetzung mit dem Anthropozän, ein Konzept, das die ökologischen und sozialpolitischen Implikationen menschlichen Handelns auf die Erdoberfläche beschreibt. Anhand von drei ausgewählten Fallstudien erkunden wir,
wie die spezifisch anthropogene, also menschengemachte, Krise urbaner Luftverschmutzung in künstlerischen Positionen problematisiert wird. Im Kontext des potenziellen Vormarschs von Postpolitik besprechen wir, wie der ambivalente Diskurs des Anthropozäns einerseits Depolitisierung begünstigt und andererseits neue Möglichkeiten für die Repolitisierung
globaler Umweltherausforderungen ermöglicht.
Rapid Visual Screening (RVS) is a procedure that estimates structural scores for buildings and prioritizes their retrofit and upgrade requirements. Despite the speed and simplicity of RVS, many of the collected parameters are non-commensurable and include subjectivity due to visual observations. This might cause uncertainties in the evaluation, which emphasizes the use of a fuzzy-based method. This study aims to propose a novel RVS methodology based on the interval type-2 fuzzy logic system (IT2FLS) to set the priority of vulnerable building to undergo detailed assessment while covering uncertainties and minimizing their effects during evaluation. The proposed method estimates the vulnerability of a building, in terms of Damage Index, considering the number of stories, age of building, plan irregularity, vertical irregularity, building quality, and peak ground velocity, as inputs with a single output variable. Applicability of the proposed method has been investigated using a post-earthquake damage database of reinforced concrete buildings from the Bingöl and Düzce earthquakes in Turkey.
Image Analysis Using Human Body Geometry and Size Proportion Science for Action Classification
(2020)
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.
For this paper, the problem of energy/voltage management in photovoltaic (PV)/battery systems was studied, and a new fractional-order control system on basis of type-3 (T3) fuzzy logic systems (FLSs) was developed. New fractional-order learning rules are derived for tuning of T3-FLSs such that the stability is ensured. In addition, using fractional-order calculus, the robustness was studied versus dynamic uncertainties, perturbation of irradiation, and temperature and abruptly faults in output loads, and, subsequently, new compensators were proposed. In several examinations under difficult operation conditions, such as random temperature, variable irradiation, and abrupt changes in output load, the capability of the schemed controller was verified. In addition, in comparison with other methods, such as proportional-derivative-integral (PID), sliding mode controller (SMC), passivity-based control systems (PBC), and linear quadratic regulator (LQR), the superiority of the suggested method was demonstrated.
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.
In this study, machine learning methods of artificial neural networks (ANNs), least squares support vector machines (LSSVM), and neuro-fuzzy are used for advancing prediction models for thermal performance of a photovoltaic-thermal solar collector (PV/T). In the proposed models, the inlet temperature, flow rate, heat, solar radiation, and the sun heat have been considered as the input variables. Data set has been extracted through experimental measurements from a novel solar collector system. Different analyses are performed to examine the credibility of the introduced models and evaluate their performances. The proposed LSSVM model outperformed the ANFIS and ANNs models. LSSVM model is reported suitable when the laboratory measurements are costly and time-consuming, or achieving such values requires sophisticated interpretations.
Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that were divided into training (70%) and validation (30%) for modeling. The area under curve (AUC) was used to assess the effeciency of the RF, SVM, and Bayesian GLM. Piping erosion susceptibility results indicated that all three RF, SVM, and Bayesian GLM models had high efficiency in the testing step, such as the AUC shown with values of 0.9 for RF, 0.88 for SVM, and 0.87 for Bayesian GLM. Altitude, pH, and bulk density were the variables that had the greatest influence on the piping erosion susceptibility in the Zarandieh watershed. This result indicates that geo-environmental and soil chemical variables are accountable for the expansion of piping erosion in the Zarandieh watershed.
Matthias Bernt und Andrej Holm weisen zu Recht darauf hin, dass es einer Forschung zu ostdeutschen Städten als konzeptionell eigenständigem Feld bedarf, die die spezifische Verräumlichung des tiefgreifenden gesellschaftlichen Transformationsprozesses nach 1990 ins Zentrum stellt. Dabei betrachten sie insbesondere das Feld des Wohnens als produktiv, um Kenntnis über die Struktur und Wirkung dieses Prozesses zu erlangen. Allerdings bleiben sie vage dabei, wie eine solche spezifisch auf Ostdeutschland gerichtete Wohnungsforschung zu konzipieren wäre und in welcher Weise die Besonderheiten und Parallelitäten ostdeutscher Entwicklungen zu den Transformationen von Wohnungs- und Stadtentwicklungspolitik in Westdeutschland, aber auch international, in Bezug zu setzen wären.
Energy‐Efficient Method for Wireless Sensor Networks Low‐Power Radio Operation in Internet of Things
(2020)
The radio operation in wireless sensor networks (WSN) in Internet of Things (IoT)applications is the most common source for power consumption. Consequently, recognizing and controlling the factors affecting radio operation can be valuable for managing the node power consumption. Among essential factors affecting radio operation, the time spent for checking the radio is of utmost importance for monitoring power consumption. It can lead to false WakeUp or idle listening in radio duty cycles and ContikiMAC. ContikiMAC is a low‐power radio duty‐cycle protocol in Contiki OS used in WakeUp mode, as a clear channel assessment (CCA) for checking radio status periodically. This paper presents a detailed analysis of radio WakeUp time factors of ContikiMAC. Furthermore, we propose a lightweight CCA (LW‐CCA) as an extension to ContikiMAC to reduce the Radio Duty‐Cycles in false WakeUps and idle listening though using dynamic received signal strength indicator (RSSI) status check time. The simulation results in the Cooja simulator show that LW‐CCA reduces about 8% energy consumption in nodes while maintaining up to 99% of the packet delivery rate (PDR).
Die derzeitige Wohnungskrise hat eine sozial-ökologische Kernproblematik. Dabei ist die sozial ungerechte und ökologisch problematische Verteilung von Wohnfläche meist unsichtbar und wird weder in wissenschaftlichen noch in aktivistischen Kontexten ausreichend als Frage der Flächengerechtigkeit problematisiert. Denn Wohnraum und Fläche in einer Stadt sind keine endlos verfügbaren Güter: Wenn einige Menschen auf viel Raum leben, bleibt für andere Menschen weniger Fläche übrig. Und die Menschen, die am wenigstens für eine Verknappung von Wohnraum verantwortlich sind, leiden am meisten darunter. Dieser Artikel arbeitet zunächst den Begriff der Wohnflächengerechtigkeit heraus, wobei auf die Ungleichverteilung von Wohnfläche und deren gesellschaftliche Implikationen unter derzeitigen Wohnungsverteilungsmechanismen Bezug genommen wird. Anschließend wird der Verbrauch von (Wohn-)Fläche aus ökologischer Perspektive problematisiert. Der Artikel diskutiert scheinbare und transformationsorientierte Lösungs- und Handlungsansätze. Abschließend fordert er in der kritischen Stadtforschung und in aktivistischen Kontexten eine stärkere Debatte um eine Wohnflächengerechtigkeit, deren Verwirklichung gleichermaßen eine soziale wie ökologische Dimension hat.