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This study permits a reliability analysis to solve the mechanical behaviour issues existing in the current structural design of fabric structures. Purely predictive material models are highly desirable to facilitate an optimized design scheme and to significantly reduce time and cost at the design stage, such as experimental characterization.
The present study examined the role of three major tasks; a) single-objective optimization, b) sensitivity analyses and c) multi-objective optimization on proposed weave structures for woven fabric composites. For single-objective optimization task, the first goal is to optimize the elastic properties of proposed complex weave structure under unit cells basis based on periodic boundary conditions.
We predict the geometric characteristics towards skewness of woven fabric composites via Evolutionary Algorithm (EA) and a parametric study. We also demonstrate the effect of complex weave structures on the fray tendency in woven fabric composites via tightness evaluation. We utilize a procedure which does not require a numerical averaging process for evaluating the elastic properties of woven fabric composites. The fray tendency and skewness of woven fabrics depends upon the behaviour of the floats which is related to the factor of weave. Results of this study may suggest a broader view for further research into the effects of complex weave structures or may provide an alternative to the fray and skewness problems of current weave structure in woven fabric composites.
A comprehensive study is developed on the complex weave structure model which adopts the dry woven fabric of the most potential pattern in singleobjective optimization incorporating the uncertainties parameters of woven fabric composites. The comprehensive study covers the regression-based and variance-based sensitivity analyses. The second task goal is to introduce the fabric uncertainties parameters and elaborate how they can be incorporated into finite element models on macroscopic material parameters such as elastic modulus and shear modulus of dry woven fabric subjected to uni-axial and biaxial deformations. Significant correlations in the study, would indicate the need for a thorough investigation of woven fabric composites under uncertainties parameters. The study describes here could serve as an alternative to identify effective material properties without prolonged time consumption and expensive experimental tests.
The last part focuses on a hierarchical stochastic multi-scale optimization approach (fine-scale and coarse-scale optimizations) under geometrical uncertainties parameters for hybrid composites considering complex weave structure. The fine-scale optimization is to determine the best lamina pattern that maximizes its macroscopic elastic properties, conducted by EA under the following uncertain mesoscopic parameters: yarn spacing, yarn height, yarn width and misalignment of yarn angle. The coarse-scale optimization has been carried out to optimize the stacking sequences of symmetric hybrid laminated composite plate with uncertain mesoscopic parameters by employing the Ant Colony Algorithm (ACO). The objective functions of the coarse-scale optimization are to minimize the cost (C) and weight (W) of the hybrid laminated composite plate considering the fundamental frequency and the buckling load factor as the design constraints.
Based on the uncertainty criteria of the design parameters, the appropriate variation required for the structural design standards can be evaluated using the reliability tool, and then an optimized design decision in consideration of cost can be subsequently determined.
Space is a social product and a social producer. The main aim of this thesis is to reveal ‘the process of totalitarian city making in Pyongyang’, especially in the light of the interaction between the power and urban space.
The totalitarian city of Pyongyang was born out of modernization in the process of masses formation. During the growth of colonial capitalism and Christian liberal ideas, Pyongyang was modernized and displayed the characteristics of a modern city with industrialization and urbanization. During the introduction of Japanese colonial capitalism, peasants, women, and slaves became the first masses and urban poor, and they later transformed into the mob; their violence was finally demonstrated during the Anti-Chinese Riot.
After the 1945 independence, Kim’s regime formed the one-party state with a cry for revolution. They produced an atmosphere of imminent war to instill fear and hatred into the psyche of Pyongyang citizens. The regime eliminated all political opponents in 1967 and finally declared the totalitarian ideology in 1974. During this process, Pyongyang demonstrated two main characteristics of a totalitarian city: the space of terror and of ideology. The space of terror produces the fear of death and the space of ideology controls the thought and life of citizens.
After entry to the market, to keep Kim’s controlling power, the regime used the strategy of location exchange. The camp, market, and Foreign Currency Shop were effective tools to prepare for executives’ gifts. However, the market also produces the desire not only for consumption but also for freedom and truth; it is tearing down the foundation of the totalitarian city of Pyongyang.
This research focuses primarily on the interaction between political power and urban space. In the process of making a totalitarian city, the power produced urban space and it influenced the psyche of Pyongyang citizens. Even though this spatial transition has created the totalitarian city and helped maintain political power, it also led and produced intended or unintended social variation in Pyongyang society.
In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Text
The performance of ductless personalized ventilation (DPV) was compared to the performance of a typical desk fan since they are both stand-alone systems that allow the users to personalize their indoor environment. The two systems were evaluated using a validated computational fluid dynamics (CFD) model of an office room occupied by two users. To investigate the impact of DPV and the fan on the inhaled air quality, two types of contamination sources were modelled in the domain: an active source and a passive source. Additionally, the influence of the compared systems on thermal comfort was assessed using the coupling of CFD with the comfort model developed by the University of California, Berkeley (UCB model). Results indicated that DPV performed generally better than the desk fan. It provided better thermal comfort and showed a superior performance in removing the exhaled contaminants. However, the desk fan performed better in removing the contaminants emitted from a passive source near the floor level. This indicates that the performance of DPV and desk fans depends highly on the location of the contamination source. Moreover, the simulations showed that both systems increased the spread of exhaled contamination when used by the source occupant.
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.
Rechargeable lithium ion batteries (LIBs) play a very significant role in power supply and storage. In recent decades, LIBs have caught tremendous attention in mobile communication, portable electronics, and electric vehicles. Furthermore, global warming has become a worldwide issue due to the ongoing production of greenhouse gases. It motivates solutions such as renewable sources of energy. Solar and wind energies are the most important ones in renewable energy sources. By technology progress, they will definitely require batteries to store the produced power to make a balance between power generation and consumption. Nowadays,rechargeable batteries such as LIBs are considered as one of the best solutions. They provide high specific energy and high rate performance while their rate of self-discharge is low.
Performance of LIBs can be improved through the modification of battery characteristics. The size of solid particles in electrodes can impact the specific energy and the cyclability of batteries. It can improve the amount of lithium content in the electrode which is a vital parameter in capacity and capability of a battery. There exist diferent sources of heat generation in LIBs such as heat produced during electrochemical reactions, internal resistance in battery. The size of electrode's electroactive particles can directly affect the produced heat in battery. It will be shown that the smaller size of solid particle enhance the thermal characteristics of LIBs.
Thermal issues such as overheating, temperature maldistribution in the battery, and thermal runaway have confined applications of LIBs. Such thermal challenges reduce the Life cycle of LIBs. As well, they may lead to dangerous conditions such as fire or even explosion in batteries. However, recent advances in fabrication of advanced materials such as graphene and carbon nanotubes with extraordinary thermal conductivity and electrical properties propose new opportunities to enhance their performance. Since experimental works are expensive, our objective is to use computational methods to investigate the thermal issues in LIBS. Dissipation of the heat produced in the battery can improve the cyclability and specific capacity of LIBs. In real applications, packs of LIB consist several battery cells that are used as the power source. Therefore, it is worth to investigate thermal characteristic of battery packs under their cycles of charging/discharging operations at different applied current rates. To remove the produced heat in batteries, they can be surrounded by materials with high thermal conductivity. Parafin wax absorbs high energy since it has a high latent heat. Absorption high amounts of energy occurs at constant temperature without phase change. As well, thermal conductivity of parafin can be magnified with nano-materials such as graphene, CNT, and fullerene to form a nano-composite medium. Improving the thermal conductivity of LIBs increase the heat dissipation from batteries which is a vital issue in systems of battery thermal management. The application of two-dimensional (2D) materials has been on the rise since exfoliation the graphene from bulk graphite. 2D materials are single-layered in an order of nanosizes which show superior thermal, mechanical, and optoelectronic properties. They are potential candidates for energy storage and supply, particularly in lithium ion batteries as electrode material. The high thermal conductivity of graphene and graphene-like materials can play a significant role in thermal management of batteries. However, defects always exist in nano-materials since there is no ideal fabrication process. One of the most important defects in materials are nano-crack which can dramatically weaken the mechanical properties of the materials. Newly synthesized crystalline carbon nitride with the stoichiometry of C3N have attracted many attentions due to its extraordinary mechanical and thermal properties. The other nano-material is phagraphene which shows anisotropic mechanical characteristics which is ideal in production of nanocomposite.
It shows ductile fracture behavior when subjected under uniaxial loadings. It is worth to investigate their thermo-mechanical properties in its pristine and defective states. We hope that the findings of our work not only be useful for both experimental and theoretical researches but also help to design advanced electrodes for LIBs.
Vor dem Hintergrund einer stetig wachsenden Nachfrage an Beton wie auch ambitionierter Reduktionsziele beim in der Zementproduktion anfallenden CO2 gelten calcinierte Tone als derzeit aussichtsreichste technische Neuerung im Bereich nachhaltiger Bindemittelkonzepte. Unter Ausnutzung ihrer Puzzolanität soll ein erheblicher Teil der Klinkerkomponente im Zement ersetzt werden, wobei der zu ihrer Aktivierung notwendige Energiebedarf vergleichsweise niedrig ist. Wesentliche Vorteile der Tone sind ihre weltweit nahezu unbegrenzte Verfügbarkeit sowie der äußerst geringe rohstoffbedingte CO2-Ausstoß während der Calcinierung. Schwierigkeiten auf dem Weg der Umsetzung bestehen allerdings in der Vielseitigkeit des Systems, welches durch eine hohe Varietät der Rohtone und des daraus folgenden thermischen Verhaltens gekennzeichnet ist. Entsprechend schwierig ist die Übertragbarkeit von Erfahrungen mit bereits etablierten calcinierten Tonen wie dem Metakaolin, der sich durch hohe Reinheit, einen aufwendigen Aufbereitungsprozess und eine entsprechend hohe Reaktivität auszeichnet. Ziel der Arbeit ist es daher, den bereits erlangten Kenntnisstand auf andere, wirtschaftlich relevante Tone zu erweitern und deren Eignung für die Anwendung im Beton herauszuarbeiten.
In einem mehrstufigen Arbeitsprogramm wurde untersucht, inwieweit großtechnisch nutzbare Tone aktivierbar sind und welche Eigenschaften sich daraus für Zement und Beton ergeben. Die dabei festgestellte Reihenfolge Kaolinit > Montmorillonit > Illit beschreibt sowohl die Reaktivität der Brennprodukte als auch umgekehrt die Höhe der optimalen Calciniertemperatur. Auch wandelt sich der Charakter der entstandenen Metaphasen in dieser Abfolge von röntgenamorph und hochreaktiv zu glasig und reaktionsträge. Trotz dieser Einordnung konnte selbst mit dem Illit eine mit Steinkohlenflugasche vergleichbare Puzzolanität festgestellt werden. Dies bestätigte sich anschließend in Parameterversuchen, bei denen die Einflüsse von Rohstoffqualität, Calcinierung, Aufbereitung und Zement hinsichtlich der Reaktivitätsausbeute bewertet wurden. Die Bandbreite der erzielbaren Qualitäten ist dabei immens und gipfelt nicht zuletzt in stark unterschiedlichen Wirkungen auf die Festbetoneigenschaften. Hier machte sich vor allem die für Puzzolane typische Porenverfeinerung bemerkbar, sodass viele von Transportvorgängen abhängige Schadmechanismen unterdrückt wurden. Andere Schadex-positionen wie der Frostangriff ließen sich durch Zusatzmaßnahmen wie dem Eintrag von Luftporen beherrschen. Zu bemängeln sind vor allem die schlechte Verarbeitbarkeit kaolinitischer Metatone wie auch die für Puzzolane stark ausgeprägte Carbonatisierungsneigung.
Wesentliches Ergebnis der Arbeit ist, dass auch Tone, die bisher als geringwertig bezüglich des Aktivierungspotentials galten, nutzbare puzzolanische Eigenschaften entwickeln können. So kann selbst ein stark verunreinigter Illit-Ton die Qualität von Flugasche erreichen. Mit stei-gendem Tonmineralgehalt sowie bei Präsens thermisch instabilerer Tonminerale wie Mont-morillonit und Kaolinit erweitert sich das Spektrum nutzbarer Puzzolanitäten bis hin zur hochreaktiven Metakaolin-Qualität. Damit lassen sich gute bis sehr gute Betoneigenschaften erzielen, sodass die Leistungsfähigkeit etablierter Kompositmaterialien erreicht wird. Somit sind die Voraussetzungen für eine umfangreiche Nutzung der erheblichen Tonmengen im Zement und Beton gegeben. Entsprechend können Tone einen effektiven Beitrag zu einer gesteigerten Nachhaltigkeit in der Baustoffproduktion weltweit leisten.
Synergistic Framework for Analysis and Model Assessment in Bridge Aerodynamics and Aeroelasticity
(2020)
Wind-induced vibrations often represent a major design criterion for long-span bridges. This work deals with the assessment and development of models for aerodynamic and aeroelastic analyses of long-span bridges.
Computational Fluid Dynamics (CFD) and semi-analytical aerodynamic models are employed to compute the bridge response due to both turbulent and laminar free-stream. For the assessment of these models, a comparative methodology is developed that consists of two steps, a qualitative and a quantitative one. The first, qualitative, step involves an extension
of an existing approach based on Category Theory and its application to the field of bridge aerodynamics. Initially, the approach is extended to consider model comparability and completeness. Then, the complexity of the CFD and twelve semi-analytical models are evaluated based on their mathematical constructions, yielding a diagrammatic representation of model quality.
In the second, quantitative, step of the comparative methodology, the discrepancy of a system response quantity for time-dependent aerodynamic models is quantified using comparison metrics for time-histories. Nine metrics are established on a uniform basis to quantify the discrepancies in local and global signal features that are of interest in bridge aerodynamics. These signal features involve quantities such as phase, time-varying frequency and magnitude content, probability density, non-stationarity, and nonlinearity.
The two-dimensional (2D) Vortex Particle Method is used for the discretization of the Navier-Stokes equations including a Pseudo-three dimensional (Pseudo-3D) extension within an existing CFD solver. The Pseudo-3D Vortex Method considers the 3D structural behavior for aeroelastic analyses by positioning 2D fluid strips along a line-like structure. A novel turbulent Pseudo-3D Vortex Method is developed by combining the laminar Pseudo-3D VPM and a previously developed 2D method for the generation of free-stream turbulence. Using analytical derivations, it is shown that the fluid velocity correlation is maintained between the CFD strips.
Furthermore, a new method is presented for the determination of the complex aerodynamic admittance under deterministic sinusoidal gusts using the Vortex Particle Method. The sinusoidal gusts are simulated by modeling the wakes of flapping airfoils in the CFD domain with inflow vortex particles. Positioning a section downstream yields sinusoidal forces that are used for determining all six components of the complex aerodynamic admittance. A closed-form analytical relation is derived, based on an existing analytical model. With this relation, the inflow particles’ strength can be related with the target gust amplitudes a priori.
The developed methodologies are combined in a synergistic framework, which is applied to both fundamental examples and practical case studies. Where possible, the results are verified and validated. The outcome of this work is intended to shed some light on the complex wind–bridge interaction and suggest appropriate modeling strategies for an enhanced design.
Diese Dissertation beschäftigt sich mit Kunstwerken, die das alltägliche Ding in den Blick nehmen. Nährboden dieser Kunstform sind die soziokulturellen Entwicklungen des 20. Jahrhunderts, mit denen wesentliche Veränderungen hinsichtlich des Verhältnisses von Mensch und Ding einhergingen.
Daraus resultierte eine allgemeine künstlerische Zuwendung zu den Dingen und eine einzigartige Kulmination aus verschiedenartigen Auseinandersetzungen mit ihnen als kunstfähige Gegenstände, über die sich die neue Dingwelt erschlossen wurde und deren Kunstwerke einen Spiegel dieser Entwicklungen darstellen.
Die Dissertation stellt ebenfalls die Dinge selbst in den Fokus. Vier Aspekte von Dingen (Materialität, Funktionalität, Repräsentationalität und Relationalität) werden gesondert ins Auge gefasst und in den theoretischen Diskurs des 20. Jahrhunderts eingeordnet, um sie als Teil der gelebten Realität besser zu verstehen, von der sich der ästhetische Blick nicht trennen lässt. Anhand der künstlerischen Positionen von Robert Rauschenberg, Christo und Jeanne-Claude, Daniel Spoerri und Arman sowie Claes Oldenburg werden die verschiedenen Aspekte der Dinge näher betrachtet und analysiert, wie diese speziell in den Kunstwerken thematisiert werden und welche Relevanz sie für deren Rezeptionserfahrung haben.
Die Korrelation dieser beiden Ebenen - die Dinge als konstitutiver Bestandteil im sozialen Raum und die Dinge als Elemente in Kunstwerken -, die im Fokus der vorliegenden Untersuchung steht, ermöglicht es, die künstlerische Zuwendung zu den Dingen in den 1960er-Jahren neu einzuordnen. Darüber hinaus wird dadurch ein differenziertes Bild von der Kunst dieser Zeit sowie den Dingen in der Kunst im Allgemeinen gezeichnet.
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.
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.
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.
Recently, the demand for residence and usage of urban infrastructure has been increased, thereby resulting in the elevation of risk levels of human lives over natural calamities. The occupancy demand has rapidly increased the construction rate, whereas the inadequate design of structures prone to more vulnerability. Buildings constructed before the development of seismic codes have an additional susceptibility to earthquake vibrations. The structural collapse causes an economic loss as well as setbacks for human lives. An application of different theoretical methods to analyze the structural behavior is expensive and time-consuming. Therefore, introducing a rapid vulnerability assessment method to check structural performances is necessary for future developments. The process, as mentioned earlier, is known as Rapid Visual Screening (RVS). This technique has been generated to identify, inventory, and screen structures that are potentially hazardous. Sometimes, poor construction quality does not provide some of the required parameters; in this case, the RVS process turns into a tedious scenario. Hence, to tackle such a situation, multiple-criteria decision-making (MCDM) methods for the seismic vulnerability assessment opens a new gateway. The different parameters required by RVS can be taken in MCDM. MCDM evaluates multiple conflicting criteria in decision making in several fields. This paper has aimed to bridge the gap between RVS and MCDM. Furthermore, to define the correlation between these techniques, implementation of the methodologies from Indian, Turkish, and Federal Emergency Management Agency (FEMA) codes has been done. The effects of seismic vulnerability of structures have been observed and compared.
Experimente lernen, Techniken tauschen. Ein spekulatives Handbuch
Das spekulative Handbuch bietet vielfältige Techniken für ein radikales Lernen und Vermitteln. Es umfasst konkrete Anleitungen, Erfahrungen und theoretische Überlegungen. Die Texte beteiligen sich an der Konzeption einer Vermittlung, die das gemeinsame Experimentieren (wieder) einführt.
Im Seminarraum, in Workshops, auf Festivals, in Fluren, Parks und der Stadt finden Lernen und Verlernen statt. Texte und Anleitungen u. a. zu: Filmessays, Collagen, Banküberfällen, der Universität der Toten, wildem Schreiben, konzeptuellem speed Dating, neurodiversem Lernen, Format-Denken, dem Theater der Sorge, dem Schreiblabor, dem Körperstreik.
Experimente lernen, Techniken tauschen
Ein spekulatives Handbuch
Das spekulative Handbuch bietet vielfältige Techniken für ein radikales Lernen und Vermitteln. Es umfasst konkrete Anleitungen, Erfahrungen und theoretische Überlegungen. Die Texte beteiligen sich an der Konzeption einer Vermittlung, die das gemeinsame Experimentieren (wieder) einführt.
Im Seminarraum, in Workshops, auf Festivals, in Fluren, Parks und der Stadt finden Lernen und Verlernen statt. Texte und Anleitungen u. a. zu: Filmessays, Collagen, Banküberfällen, der Universität der Toten, wildem Schreiben, konzeptuellem speed Dating, neurodiversem Lernen, Format-Denken, dem Theater der Sorge, dem Schreiblabor, dem Körperstreik.
Im Workshop des Sinnlichen
(2020)
Folgende fiktive Situation soll ein Problem markieren, das in diesem Beitrag diskutiert wird und nach Ansicht seines Autors ein an Kunsthochschulen weit verbreitetes Phänomen darstellt. Im Rahmen eines Mentoring-Workshops stellt eine Gruppe Studierender Arbeitsmaterial ihres aktuellen Projekts vor, um es anschließend in der Gruppe zu besprechen. Ziel des Veranstaltungsformats ist es, die Studierenden während der Entwicklung ihrer künstlerischen Praktiken zu begleiten und diese nicht anhand handwerklicher Kriterien überzudeterminieren, sondern ihrer Eigenlogik zu folgen, den ihnen inhärenten ästhetischen Potentialen nachzugehen und ein Bewusstsein für die Kontexte und Diskurse zu schaffen, in denen sie verortet sind. Die Studierenden, die heute ihr Projekt vorstellen, haben ein Photoalbum mitgebracht, in das sie, der Anordnungslogik von Urlaubsaufnahmen folgend, eine Reihe analoger Photographien geklebt haben, die Dutzende Schnappschüsse einer entfernten Insel zeigen, die sich hinter der den Vordergrund des Bildes einnehmenden Meeresoberfläche abzeichnet.
Why isn't Google welcome in Kreuzberg? Social movement and the effects of Internet on urban space
(2020)
Advances in information and communication technologies such as the Internet have driven a great transformation in the interactions between individuals and the urban environment. As the use of the Internet in cities becomes more intense and diverse, there is also a restructuring of urban space, which is experienced by groups in society in various ways, according to the specificity of each context. Accordingly, large Internet companies have emerged as new players in the processes of urbanization, either through partnerships with the public administration or through various services offered directly to urban residents. Once these corporations are key actors in the digitalization of urban services, their operations can affect the patterns of urban inequality and generate a series of new struggles over the production of space. Interested in analyzing this phenomena from the perspective of civil society, the present Master Thesis examined a social movement that prevented Google to settle a new startup campus in the district of Kreuzberg, in Berlin. By asking why Google was not welcome in that context, this study also sought to understand how internet, as well as its main operators, has affected everyday life in the city. Thus, besides analyzing the movement, I investigated the particularities of the urban context where it arose and the elements that distinguish the mobilization’s opponent. In pursuit of an interdisciplinary approach, I analyzed and discussed the results of empirical research in dialogue with critical theories in the fields of urban studies and the Internet, with emphasis on Castells' definitions of urban social movements and network society (1983, 2009, 2015), Couldry's and Mejias' (2019) idea of data colonialism, Lefèbvre's (1991, 1996) concepts of abstract space and the right to the city, as well as Zuboff's (2019) theory of surveillance capitalism. The case at hand has exposed that Google plays a prominent role in the way the Internet has been developed and deployed in cities. From the perspective accessed, the current appropriation of Internet technologies has been detrimental to individual autonomy and has contributed to intensifying existing inequalities in the city. The alternative vision to this relies mainly on the promotion of decentralized solidarity networks.
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.
Wie können journalistische Angebote nachhaltig finanziert werden? Dies bleibt die Kernfrage für Medienhäuser und journalistische Neugründungen bei der Entwicklung und beim Aufbau tragfähiger digitaler Geschäftsmodelle.
Die Autoren des vorliegenden Bandes vermitteln einen breiten Überblick über den Wissensstand zum Thema Paid Content, Plattformen und Zahlungsbereitschaft im Journalismus und eröffnen innovative Blickwinkel auf neuartige Plattformmodelle ebenso wie auf Motive und Bedürfnisse der Nutzerinnen und Nutzer digitaljournalistischer Inhalte. Auf Grundlage empirischer Forschung werden Handlungsempfehlungen für die nutzerzentrierte Ausgestaltung von Paid-Content-Angeboten sowie neue Perspektiven auf Zahlungsbereitschaft im digitalen Journalismus erschlossen – relevant sowohl für die Wissenschaft wie auch für die Medienpraxis.