Filtern
Dokumenttyp
- Artikel (Wissenschaftlicher) (57)
- Dissertation (26)
- Teil eines Buches (Kapitel) (16)
- Masterarbeit (7)
- Buch (Monographie) (4)
- Preprint (3)
- Konferenzveröffentlichung (2)
- Habilitation (2)
- Bericht (2)
- Bachelorarbeit (1)
Institut
- Institut für Strukturmechanik (ISM) (42)
- Junior-Professur Bildtheorie (17)
- Professur Bauphysik (8)
- Professur Sozialwissenschaftliche Stadtforschung (7)
- Junior-Professur Organisation und vernetzte Medien (6)
- Institut für Europäische Urbanistik (5)
- Professur Bauchemie und Polymere Werkstoffe (3)
- Professur Denkmalpflege und Baugeschichte (3)
- Professur Modellierung und Simulation - Konstruktion (3)
- Bauhaus-Institut für zukunftsweisende Infrastruktursysteme (b.is) (2)
Schlagworte
- OA-Publikationsfonds2020 (27)
- Maschinelles Lernen (17)
- Machine learning (12)
- Künstlerische Forschung (10)
- Erdbeben (7)
- Deep learning (5)
- Theater (5)
- big data (5)
- Medien (4)
- Raumklima (4)
- machine learning (4)
- rapid visual screening (4)
- Aerodynamik (3)
- Architektur (3)
- Beton (3)
- Bridge (3)
- Brücke (3)
- Denkmalpflege (3)
- Intelligente Stadt (3)
- Journalismus (3)
- Pädagogik (3)
- Stadtplanung (3)
- Wohnen (3)
- Wohnungspolitik (3)
- computational fluid dynamics (3)
- earthquake (3)
- earthquake safety assessment (3)
- random forest (3)
- smart cities (3)
- Aktivismus (2)
- Antirassismus (2)
- Artificial neural network (2)
- Batterie (2)
- Behaglichkeit (2)
- Concrete (2)
- Deutschland (2)
- Dissipation (2)
- Europa (2)
- Fluid (2)
- Fotovoltaik (2)
- Fuzzy-Logik (2)
- Geopolymere (2)
- Heritage (2)
- Industriekomplexe (2)
- Ingenieurwissenschaften (2)
- Internet of things (2)
- Kunst (2)
- Mensch-Maschine-Kommunikation (2)
- Modellierung (2)
- Montage (2)
- Nachhaltigkeit (2)
- Nanostrukturiertes Material (2)
- Neuronales Netz (2)
- Performance (2)
- Performativität (2)
- Planung (2)
- Raumordnung (2)
- Schreiben (2)
- Simulation (2)
- Stadtbaugeschichte (2)
- Stadtentwicklung (2)
- Strömungsmechanik (2)
- Undercommons (2)
- Verbundwerkstoff (2)
- Vermittlung (2)
- Wohnungsfrage (2)
- Workshop (2)
- Zement (2)
- artificial intelligence (2)
- artificial neural networks (2)
- buildings (2)
- cement (2)
- cyclic load (2)
- damaged buildings (2)
- data science (2)
- ductless personalized ventilation (2)
- reinforcement learning (2)
- soft computing techniques (2)
- support vector machine (2)
- thermal comfort (2)
- urban morphology (2)
- vulnerability assessment (2)
- 2D/3D Adaptive Mesh Refinement (1)
- 3D Interaction Techniques (1)
- Abwasserwirtschaft (1)
- Aerodynamic derivatives (1)
- Aerodynamics (1)
- Aeroelasticity (1)
- Aeroelastizität (1)
- African Revolution (1)
- Ahnenkultur (1)
- Akkumulator (1)
- Akustische Laufzeit-Tomographie (1)
- Algorithmus (1)
- Allyship (1)
- Anthropozän (1)
- Antikolonialismus (1)
- Architecture (1)
- Arman (1)
- Artefakt (1)
- Artistic Research (1)
- Asynchronität (1)
- Audiovision (1)
- Augmented Audio Reality (1)
- Autogenous (1)
- Autokratie (1)
- Autonomous (1)
- BIM (1)
- Background-oriented schlieren (1)
- Balkan (1)
- Balkanroute (1)
- Battery (1)
- Battery development (1)
- Baudenkmal (1)
- Bauklimatik (1)
- Bauphysik (1)
- Bayes-Verfahren (1)
- Belüftung (1)
- Berlin (1)
- Beschädigung (1)
- Bestattung (1)
- Bildanalyse (1)
- Biodiversität (1)
- Biogas (1)
- Biogasproduktion (1)
- Biomechanics (1)
- Biomechanik (1)
- Bodentemperatur (1)
- Brasilien (1)
- Brazil (1)
- Brazilian Music (1)
- Bridge aerodynamics (1)
- Bridges (1)
- Bruchmechanik (1)
- Brustkorb (1)
- Brückenbau (1)
- Bubble column reactor (1)
- Building Information Modeling (1)
- Candomblé (1)
- Category Theory (1)
- Charles Sanders Peirce (1)
- Christo (1)
- City marketing (1)
- Club (1)
- Collage (1)
- Composite (1)
- Computational Fluid Dynamics (1)
- ContikiMAC (1)
- Convective indoor air flow (1)
- Counter-ethnography (1)
- Cross-correlation (1)
- Cultural tourism (1)
- Damage (1)
- Daseinsvorsorge (1)
- Datenmodell (1)
- Deal ii C++ code (1)
- Deutschland <Östliche Länder> (1)
- Dictatorship (1)
- Didaktik (1)
- Digital image correlation (1)
- Digitaler Journalismus (1)
- Digitalisierung (1)
- Digitaljournalismus (1)
- Ding (1)
- Dingdiskurs (1)
- Dirac-Operator (1)
- Display (1)
- Drohne (1)
- Earthquake (1)
- Electrochemical properties (1)
- Elektrochemische Eigenschaft (1)
- Elektrode (1)
- Elektrodenmaterial (1)
- Energieeffizienz (1)
- Energiespeichersystem (1)
- Entrepreneurship (1)
- Erbe (1)
- Erdbebensicherheit (1)
- Ermüdung (1)
- Erneuerbare Energien (1)
- Erweiterte Realität <Informatik> (1)
- Ethnologie (1)
- European city-making process (1)
- Europäische Union (1)
- Experimente (1)
- FEM (1)
- Femimismus (1)
- Fernerkung (1)
- Film (1)
- Filmessay (1)
- Finite-Elemente-Methode (1)
- Flight path planning (1)
- Flow visualization (1)
- Flussgebiet (1)
- Flächengerechtigkeit (1)
- Flächenverbrauch (1)
- Flüchtlingspolitik (1)
- Format (1)
- Forschungsbericht (1)
- Fotografie (1)
- Fotografie als Handlung (1)
- Funktionentheorie (1)
- Fuzzy Logic (1)
- Fuzzy-Regelung (1)
- Gabe (1)
- Gaussian process regression (1)
- Gebäude (1)
- Geoinformatik (1)
- Geometric Modeling (1)
- Geometrie (1)
- Gerechtigkeit (1)
- Geschichte (1)
- Geschichtsbewusstsein (1)
- Geschichtswissenschaft (1)
- Geschäftsmodell (1)
- Gesundheit (1)
- Gesundheitsinformationssystem (1)
- Gesundheitswesen (1)
- Gewebeverbundwerkstoff (1)
- Gleichwertigkeit der Lebensverhältnisse (1)
- Goal-oriented A Posteriori Error Estimation (1)
- Graffiti (1)
- Graffito (1)
- Grundwasser (1)
- Größenverhältnis (1)
- Hans Ruin (1)
- Hausarzt (1)
- Healing (1)
- Heritage management (1)
- Hochschullehre (1)
- Housing (1)
- Housing Policy (1)
- Human thermal plume (1)
- Human-Computer Interaction (1)
- Hydrological drought (1)
- IAQ (1)
- IFC (1)
- IOT (1)
- Incompressibility (1)
- Industrie 4.0 (1)
- Infrastructures (1)
- Innovation (1)
- Innovationsforschung (1)
- Innovationsfähigkeit (1)
- Inspektion (1)
- Instrument (1)
- Inszenierte Fotografie (1)
- Internet (1)
- Internet der Dinge (1)
- Internet der dinge (1)
- Interoperabilität (1)
- Intersektionalität (1)
- Iran (1)
- Isogeometric Analysis (1)
- Isogeometrische Analyse (1)
- K-nearest neighbors (1)
- KNN (1)
- Klimapolitik (1)
- Kontamination (1)
- Konzeptkunst (1)
- Kulturwissenschaft (1)
- Kunsthochschule (1)
- Kybernetik (1)
- Körper (1)
- Kühlkörper (1)
- Künste (1)
- Künstlerischer Aktivismus (1)
- Künstliche Intelligenz (1)
- Land surface temperature (1)
- Lassen (1)
- Leistungsverhalten (1)
- Literaturrecherche (1)
- Localised Sound (1)
- Luftqualität (1)
- Ländlicher Raum (1)
- Lüftung (1)
- M5 model tree (1)
- Machine Learning (1)
- Macht (1)
- Mahlaggregat (1)
- Mahlung (1)
- Makroalgen (1)
- Mangement (1)
- Marmara Region (1)
- Mathematik (1)
- Mechanical properties (1)
- Mechanische Eigenschaft (1)
- Medienphilosophie (1)
- Medienphilosophie des Formats (1)
- Medientechnik (1)
- Medientheorie (1)
- Medienwirtschaft (1)
- Medienwissenschaft (1)
- Medienökonomie (1)
- Mensch (1)
- Mensch-Maschine-Interaktion (1)
- Mesh Refinement (1)
- Meso-Scale (1)
- Metakaolin (1)
- Metamodell (1)
- Methodologie (1)
- Mieten (1)
- Modernisierung (1)
- Modernization (1)
- Mongolei (1)
- Monitoring (1)
- Morphologie (1)
- Motion-induced forces (1)
- Multi-User Virtual Reality (1)
- Multi-criteria decision making (1)
- Multi-scale modeling (1)
- Muscle model (1)
- Museology (1)
- Museumskunde (1)
- Music (1)
- Musicology (1)
- Musik (1)
- Muskel (1)
- NURBS (1)
- Nanofluid (1)
- Nanomaterial (1)
- Nanomaterials (1)
- Nasskühlung (1)
- Nation-building (1)
- Naturkatastrophe (1)
- Navigation (1)
- Netzwerk (1)
- Neuartige Sanitärsysteme (1)
- Neue Medien (1)
- Neurodiversität (1)
- Nichtlineare Finite-Elemente-Methode (1)
- Nitratbelastung (1)
- North Korea (1)
- Nouveau Realisme (1)
- Näherungsverfahren (1)
- OA-Publikationsfonds2019 (1)
- OWL <Informatik> (1)
- Oberflächentemperatur (1)
- Oldenburg (1)
- Ontologie (1)
- Operante Konditionierung (1)
- Ostdeutschland (1)
- Pahlavi (1)
- Paid Content (1)
- Pan-Africanism (1)
- Performative Fotografie (1)
- Performative Strategien (1)
- Peripherisierungsforschung (1)
- Philosophie (1)
- Photobioreaktor (1)
- Photobioreaktorsystem (1)
- Plattformmodell (1)
- Polymere (1)
- Pop-Art (1)
- Post-colonial studies (1)
- Postkommunismus (1)
- Postpolitik (1)
- Postsozialismus (1)
- Postwachstumsstadt (1)
- Postwachstumsökonomie (1)
- Projektmanagement (1)
- Protestbewegung (1)
- Public-Private Partnerships (1)
- Pyongyang (1)
- RSSI (1)
- Radikales Lernen (1)
- Randwertproblem (1)
- Rapid Visual Screening (1)
- Raum (1)
- Raumklang (1)
- Raumluftströmungen (1)
- Raumplanung (1)
- Rauschenberg (1)
- Renewable energy (1)
- Resilience (1)
- Responsibilisierung (1)
- Rezension (1)
- Rumänien (1)
- Sakralbau (1)
- Saz (1)
- Schaden (1)
- Schadensanalyse (1)
- Schlierenspiegel (1)
- Schreiblabor (1)
- Segregation (1)
- Selbstbildnis (1)
- Selbstgenutztes Wohneigentum (1)
- Selbstheilung (1)
- Selbstportrait (1)
- Seminar (1)
- Siedlungswasserwirtschaft (1)
- Sinne (1)
- Sinnlichkeit (1)
- Smarter Together (1)
- Smog (1)
- Social Housing (1)
- Social movement (1)
- Solar (1)
- Soziale Bewegung (1)
- Soziale Mobilität (1)
- Soziale Sicherheit (1)
- Sozialer Muskel (1)
- Sozialer Wohnungsbau (1)
- Sozialismus (1)
- Speed Dating (1)
- Spekulative Didaktik (1)
- Spoerri (1)
- Stadt (1)
- Stadtbild (1)
- Stadtgeschichte <Fach> (1)
- Stadtmarketing (1)
- Stereofonie (1)
- Stereophonie (1)
- Steuerungsansätze (1)
- Strukturanalyse (1)
- Strukturmechanik (1)
- Strömung (1)
- Städtebau (1)
- Städtischer Wohnungsmarkt (1)
- Super Healing (1)
- Superplasticizer (1)
- Sustainability (1)
- Synchronisation (1)
- Synchronisierung (1)
- Technik (1)
- Technisches Denkmal (1)
- Tehran (1)
- Temperatur (1)
- Theatermaschine (1)
- Thermal conductivity (1)
- Thermoelasticity (1)
- Thermoelastizität (1)
- Thorax (1)
- Thüringen (1)
- Tod (1)
- Ton <Geologie> (1)
- Tonfilm (1)
- Tracht (1)
- Transdisziplinarität (1)
- Transformation (1)
- Transformation risks (1)
- Transformationsrisiken (1)
- UAS (1)
- Umweltbelastung (1)
- Umweltgerechtigkeit (1)
- Umweltveränderung (1)
- Universität (1)
- Urban Planning (1)
- Urban identity (1)
- Urbanität (1)
- Vertical roller mill (1)
- Vilém Flusser (1)
- Virtuelle Realität (1)
- Volkstracht (1)
- Vulnerability (1)
- Vulnerability assessment (1)
- Wasserreserve (1)
- Wasserressourcenmanagement (1)
- Wastewater manegement (1)
- Welfare State (1)
- Wettbewerb (1)
- Wohnfläche (1)
- Wohnraum (1)
- Wohnungsbau (1)
- Wohnungseigentum (1)
- Wärmeleitfähigkeit (1)
- Wärmeübergang (1)
- Wärmeübergangskoeffizient (1)
- Wärmeübergangskoeffizient an Zylinder (1)
- Zahlungsbereitschaft (1)
- Zementbeton (1)
- Zementmahlung (1)
- Zyklische Beanspruchung (1)
- action recognition (1)
- adaptive neuro-fuzzy inference system (ANFIS) (1)
- adaptive pushover (1)
- alumosilicate (1)
- ant colony optimization algorithm (ACO) (1)
- anti-colonialist (1)
- anti-racist (1)
- artificial neural network (1)
- artistic research (1)
- back-pressure (1)
- battery (1)
- berlinite (1)
- bridge inspection (1)
- capitalist city (1)
- cellulose (1)
- classification (1)
- classifier (1)
- clear channel assessments (1)
- cluster density (1)
- cluster shape (1)
- clustering (1)
- colonialcity (1)
- competition (1)
- computation (1)
- computational fluid dynamics (CFD) (1)
- congestion control (1)
- coronary artery disease (1)
- cross-contamination (1)
- damage information model (1)
- decolonisation (1)
- deep learning neural network (1)
- depletion method (1)
- desk fan (1)
- digital native news media (1)
- digital-born news media (1)
- digitale Kultur (1)
- digitization (1)
- dimensionality reduction (1)
- discrete Dirac operator (1)
- discrete boundary value problems (1)
- discrete monogenic functions (1)
- duty-cycles (1)
- earthquake damage (1)
- earthquake vulnerability assessment (1)
- energy consumption (1)
- energy efficiency (1)
- ensemble model (1)
- entrepreneurial journalism (1)
- experimental validation (1)
- extreme events (1)
- extreme pressure (1)
- fatigue (1)
- feministische Gesundheitsrecherche (1)
- firefly optimization algorithm (1)
- fisher-information matrix (1)
- fixed effects regression (1)
- flow pattern (1)
- fog computing (1)
- food informatics (1)
- fractional-order control (1)
- fuzzy decision making (1)
- fuzzy set qualitative comparative analysis (1)
- geoinformatics (1)
- geopolymer (1)
- ground water contamination (1)
- gully erosion susceptibility (1)
- health (1)
- health informatics (1)
- heart disease diagnosis (1)
- heat sink (1)
- heat transfer coefficient for cylinders (1)
- human blob (1)
- human body proportions (1)
- human thermal plume (1)
- hybrid machine learning (1)
- hybrid machine learning model (1)
- hydraulic jump (1)
- hydrological model (1)
- hydrology (1)
- ideological space (1)
- image processing (1)
- indoor air quality (1)
- industry 4.0 (1)
- journalism (1)
- journalism theories (1)
- künstlerischer Aktivismus (1)
- least square support vector machine (LSSVM) (1)
- longitudinal dispersion coefficient (1)
- mass spectrometry (1)
- mathematical modeling (1)
- mean-squared error (1)
- media performance (1)
- memoy (1)
- mitigation (1)
- mobility points (1)
- mobility stations (1)
- monolithic (1)
- museum (1)
- nachhaltige Regionalentwicklung (1)
- nachhaltige Stadtentwicklung (1)
- nachhaltige Verkehrspolitik (1)
- nachhaltige Wirtschaft (1)
- nanofluid (1)
- natural hazard (1)
- neural networks (NNs) (1)
- news start-ups (1)
- papercrete (1)
- partical swarm optimization (1)
- personalisierte Lüftung (1)
- personalized ventilation (1)
- photovoltaic (1)
- photovoltaic-thermal (PV/T) (1)
- physical activities (1)
- polymer adsorption (1)
- practice theories (1)
- practice theory (1)
- precipitation (1)
- predictive model (1)
- principal component analysis (1)
- public health (1)
- public service media (1)
- public space (1)
- received signal strength indicator (1)
- recovery-based and residual-based error estimators (1)
- remote sensing (1)
- residential buildings (1)
- rice (1)
- rivers (1)
- rule based classification (1)
- schlieren imaging (1)
- schlieren velocimetry (1)
- seasonal precipitation (1)
- seismic assessment (1)
- seismic control (1)
- seismic hazard analysis (1)
- seismic risk estimation (1)
- seismic vulnerability (1)
- signal processing (1)
- site-specific spectrum (1)
- smart mobility (1)
- smart sensors (1)
- socialist city (1)
- sodium silicate solution (1)
- soil temperature (1)
- space of ideology (1)
- space of terror (1)
- spatial analysis (1)
- spatial transition (1)
- spatiotemporal database (1)
- spearman correlation coefficient (1)
- square root cubature calman filter (1)
- stacking system (1)
- standard deviation of pressure fluctuations (1)
- statistical analysis (1)
- statistical coeffcient of the probability distribution (1)
- stilling basin (1)
- structural analysis (1)
- structural control (1)
- studies in 1:1 scale (1)
- support vector regression (1)
- sustainability (1)
- tech company (1)
- technische Bilder (1)
- theory development (1)
- thermisches Empfinden (1)
- totalitarian city (1)
- tower-like structures (1)
- tracer gas (1)
- tuned mass damper (1)
- type-3 fuzzy systems (1)
- urban development (1)
- urban health (1)
- urban history (1)
- urban planning (1)
- urban regeneration (1)
- urban space (1)
- urban sustainability (1)
- urbanism (1)
- vestimentäre Moderne (1)
- visible spectrophotometry (1)
- visual arts (1)
- water quality (1)
- wavelet transform (1)
- wireless sensor network (1)
- wireless sensor networks (1)
- woven composites (1)
- zyklische Beanspruchung (1)
- Ästhetik (1)
- Öffentlich-private Partnerschaft (1)
- Öffentlich-rechtlicher Rundfunk (1)
- äquivalente Temperatur (1)
Erscheinungsjahr
- 2020 (123) (entfernen)
When it comes to monitoring of huge structures, main issues are limited time, high costs and how to deal with the big amount of data. In order to reduce and manage them, respectively, methods from the field of optimal design of experiments are useful and supportive. Having optimal experimental designs at hand before conducting any measurements is leading to a highly informative measurement concept, where the sensor positions are optimized according to minimal errors in the structures’ models. For the reduction of computational time a combined approach using Fisher Information Matrix and mean-squared error in a two-step procedure is proposed under the consideration of different error types. The error descriptions contain random/aleatoric and systematic/epistemic portions. Applying this combined approach on a finite element model using artificial acceleration time measurement data with artificially added errors leads to the optimized sensor positions. These findings are compared to results from laboratory experiments on the modeled structure, which is a tower-like structure represented by a hollow pipe as the cantilever beam. Conclusively, the combined approach is leading to a sound experimental design that leads to a good estimate of the structure’s behavior and model parameters without the need of preliminary measurements for model updating.
Die im Jahr 2020 in Deutschland praktizierte Siedlungs- und Wohnungspolitik erhält in Anbetracht ihrer Auswirkungen auf die soziale und ökologische Lage einen bitteren Beigeschmack. Arm und Reich triften weiter auseinander und einer zielgerichteten ökologischen Transformation der Art und Weise, wie Stadtentwicklung und Wohnungspolitik gestaltet werden,stehen noch immer historisch und systemisch bedingte Pfadabhängigkeiten im Weg. Diese werden nur durch eine integrierte Betrachtung sozialer und ökonomischer Aspekte sichtbar und deuten auf eine der ursprünglichen Fragen linker Gesellschaftsforschung hin: Die Auseinandersetzung mit dem Verhältnis von Eigentum und Gerechtigkeit.
Im Ergebnis stehen drei wesentliche Befunde: Der Diskurs zum Schutz des Klimas und der Biodiversität berührt direkt die Parameter Dichte, Nutzungsmischung und Flächeninanspruchnahme; zweitens steigt letztere relativ mit erhöhtem, individuell verfügbaren Kapital und insbesondere im selbstgenutztem Eigentum gegenüber Mietwohnungen; und drittens wächst der Eigentumsanteil mit fortschreitender Finanzialisierung des Wohnungsmarktes, sodass das Risiko sozialer und ökologischer Krisen sich verschärft.
Prediction of the groundwater nitrate concentration is of utmost importance for pollution control and water resource management. This research aims to model the spatial groundwater nitrate concentration in the Marvdasht watershed, Iran, based on several artificial intelligence methods of support vector machine (SVM), Cubist, random forest (RF), and Bayesian artificial neural network (Baysia-ANN) machine learning models. For this purpose, 11 independent variables affecting groundwater nitrate changes include elevation, slope, plan curvature, profile curvature, rainfall, piezometric depth, distance from the river, distance from residential, Sodium (Na), Potassium (K), and topographic wetness index (TWI) in the study area were prepared. Nitrate levels were also measured in 67 wells and used as a dependent variable for modeling. Data were divided into two categories of training (70%) and testing (30%) for modeling. The evaluation criteria coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and Nash–Sutcliffe efficiency (NSE) were used to evaluate the performance of the models used. The results of modeling the susceptibility of groundwater nitrate concentration showed that the RF (R2 = 0.89, RMSE = 4.24, NSE = 0.87) model is better than the other Cubist (R2 = 0.87, RMSE = 5.18, NSE = 0.81), SVM (R2 = 0.74, RMSE = 6.07, NSE = 0.74), Bayesian-ANN (R2 = 0.79, RMSE = 5.91, NSE = 0.75) models. The results of groundwater nitrate concentration zoning in the study area showed that the northern parts of the case study have the highest amount of nitrate, which is higher in these agricultural areas than in other areas. The most important cause of nitrate pollution in these areas is agriculture activities and the use of groundwater to irrigate these crops and the wells close to agricultural areas, which has led to the indiscriminate use of chemical fertilizers by irrigation or rainwater of these fertilizers is washed and penetrates groundwater and pollutes the aquifer.
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.
Wind effects can be critical for the design of lifelines such as long-span bridges. The existence of a significant number of aerodynamic force models, used to assess the performance of bridges, poses an important question regarding their comparison and validation. This study utilizes a unified set of metrics for a quantitative comparison of time-histories in bridge aerodynamics with a host of characteristics. Accordingly, nine comparison metrics are included to quantify the discrepancies in local and global signal features such as phase, time-varying frequency and magnitude content, probability density, nonstationarity and nonlinearity. Among these, seven metrics available in the literature are introduced after recasting them for time-histories associated with bridge aerodynamics. Two additional metrics are established to overcome the shortcomings of the existing metrics. The performance of the comparison metrics is first assessed using generic signals with prescribed signal features. Subsequently, the metrics are applied to a practical example from bridge aerodynamics to quantify the discrepancies in the aerodynamic forces and response based on numerical and semi-analytical aerodynamic models. In this context, it is demonstrated how a discussion based on the set of comparison metrics presented here can aid a model evaluation by offering deeper insight. The outcome of the study is intended to provide a framework for quantitative comparison and validation of aerodynamic models based on the underlying physics of fluid-structure interaction. Immediate further applications are expected for the comparison of time-histories that are simulated by data-driven approaches.
Despite digitization and platformization, mass media and established media companies still play a crucial role in the provision of journalistic content in democratic societies. Competition is one key driver of (media) company behavior and is considered to have an impact on the media’s performance. However, theory and empirical research are ambiguous about the relationship. The objective of this article is to empirically analyze the effect of competition on media performance in a cross-national context. We assessed media performance of media companies as the importance of journalistic goals within their stated corporate goal system. We conducted a content analysis of letters to the shareholders in annual reports of more than 50 media companies from 2000 to 2014 to operationalize journalistic goal importance. When employing a fixed effects regression analysis, as well as a fuzzy set qualitative comparative analysis, results suggest that competition has a positive effect on the importance of journalistic goals, while the existence of a strong public service media sector appears to have the effect of “crowding out” commercial media companies.
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.
The effect of urban form on energy consumption has been the subject of various studies around the world. Having examined the effect of buildings on energy consumption, these studies indicate that the physical form of a city has a notable impact on the amount of energy consumed in its spaces. The present study identified the variables that affected energy consumption in residential buildings and analyzed their effects on energy consumption in four neighborhoods in Tehran: Apadana, Bimeh, Ekbatan-phase I, and Ekbatan-phase II. After extracting the variables, their effects are estimated with statistical methods, and the results are compared with the land surface temperature (LST) remote sensing data derived from Landsat 8 satellite images taken in the winter of 2019. The results showed that physical variables, such as the size of buildings, population density, vegetation cover, texture concentration, and surface color, have the greatest impacts on energy usage. For the Apadana neighborhood, the factors with the most potent effect on energy consumption were found to be the size of buildings and the population density. However, for other neighborhoods, in addition to these two factors, a third factor was also recognized to have a significant effect on energy consumption. This third factor for the Bimeh, Ekbatan-I, and Ekbatan-II neighborhoods was the type of buildings, texture concentration, and orientation of buildings, respectively.
Cooling Performance of a Novel Circulatory Flow Concentric Multi-Channel Heat Sink with Nanofluids
(2020)
Heat rejection from electronic devices such as processors necessitates a high heat removal rate. The present study focuses on liquid-cooled novel heat sink geometry made from four channels (width 4 mm and depth 3.5 mm) configured in a concentric shape with alternate flow passages (slot of 3 mm gap). In this study, the cooling performance of the heat sink was tested under simulated controlled conditions.The lower bottom surface of the heat sink was heated at a constant heat flux condition based on dissipated power of 50 W and 70 W. The computations were carried out for different volume fractions of nanoparticles, namely 0.5% to 5%, and water as base fluid at a flow rate of 30 to 180 mL/min. The results showed a higher rate of heat rejection from the nanofluid cooled heat sink compared with water. The enhancement in performance was analyzed with the help of a temperature difference of nanofluid outlet temperature and water outlet temperature under similar operating conditions. The enhancement was ~2% for 0.5% volume fraction nanofluids and ~17% for a 5% volume fraction.
Coronary Artery Disease Diagnosis: Ranking the Significant Features Using a Random Trees Model
(2020)
Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate. The most popular tool for diagnosing CAD is the use of medical imaging, e.g., angiography. However, angiography is known for being costly and also associated with a number of side effects. Hence, the purpose of this study is to increase the accuracy of coronary heart disease diagnosis through selecting significant predictive features in order of their ranking. In this study, we propose an integrated method using machine learning. The machine learning methods of random trees (RTs), decision tree of C5.0, support vector machine (SVM), and decision tree of Chi-squared automatic interaction detection (CHAID) are used in this study. The proposed method shows promising results and the study confirms that the RTs model outperforms other models.
This study investigates the performance of two systems: personalized ventilation (PV) and ductless personalized ventilation (DPV). Even though the literature indicates a compelling performance of PV, it is not often used in practice due to its impracticality. Therefore, the present study assesses the possibility of replacing the inflexible PV with DPV in office rooms equipped with displacement ventilation (DV) in the summer season. Numerical simulations were utilized to evaluate the inhaled concentration of pollutants when PV and DPV are used. The systems were compared in a simulated office with two occupants: a susceptible occupant and a source occupant. Three types of pollution were simulated: exhaled infectious air, dermally emitted contamination, and room contamination from a passive source. Results indicated that PV improved the inhaled air quality regardless of the location of the pollution source; a higher PV supply flow rate positively impacted the inhaled air quality. Contrarily, the performance of DPV was highly sensitive to the source location and the personalized flow rate. A higher DPV flow rate tends to decrease the inhaled air quality due to increased mixing of pollutants in the room. Moreover, both systems achieved better results when the personalized system of the source occupant was switched off.
This thesis explores how cultural heritage plays a role in the development of urban identity by engaging both actively and passively with memory, i.e. remembering and forgetting. I argue that architectural heritage is a medium where specific cultural and social decisions form its way of presentation, and it reflects the values and interests of the period. By the process of remembering and forgetting, the meanings between inhabitant and object in urban environment are practiced, and the meanings are created.
To enable the research in narrative observation, cultural tourism management is chosen as the main research object, which reflects the alteration of interaction between the architectural heritage and urban identity. Identifying the role of heritage management, the definition of social resilience and the prospects of cultural heritage as a means of social resilience are addressed. Case region of the research is East Ger- many, thereby, the study examines the distinct approaches and objectives regarding heritage management under the different political systems along the German reunification process.
The framework is based on various theoretical paradigms to investigate the broad research questions: 1) What is the role of historic urban quarters in the revitalisation of East German towns? 2) How was the transition processed by cultural heritage management? 3) How did policy affect residents’ lives?
The case study is applied to macro level (city level: Gotha and Eisenach) and micro level study (object level: specific heritage sites), to analyse the performance of selective remembering and making tourist destination through giving significance to specific heritage. By means of site observations, archival research, qualitative inter- views, photographs, and discourse analysis on printed tourism materials, the study demonstrates that certain sites and characteristics of the city enable creating and focusing messages, which aids the social resilience.
Combining theory and empirical studies this thesis attempts to widen the academic discussion regarding the practice of remembering and forgetting driven by cultural heritage. The thesis argues for cultural heritage tourism as an element of social resilience and one that embraces the historic and cultural identity of the inhabitants.
Personalisierte Lüftung (PL) kann die thermische Behaglichkeit sowie die Qualität der eingeatmeten Atemluft verbessern, in dem jedem Arbeitsplatz Frischluft separat zugeführt wird. In diesem Beitrag wird die Wirkung der PL auf die thermische Behaglichkeit der Nutzer unter sommerlichen Randbedingungen untersucht. Hierfür wurden zwei Ansätze zur Bewertung des Kühlungseffekts der PL untersucht: basierend auf (1) der äquivalenten Temperatur und (2) dem thermischen Empfinden. Grundlage der Auswertung sind in einer Klimakammer gemessene sowie numerisch simulierte Daten. Vor der Durchführung der Simulationen wurde das numerische Modell zunächst anhand der gemessenen Daten validiert. Die Ergebnisse zeigen, dass der Ansatz basierend auf dem thermischen Empfinden zur Evaluierung des Kühlungseffekts der PL sinnvoller sein kann, da bei diesem die komplexen physiologischen Faktoren besser berücksichtigt werden.
Der perfekte Bankraub
(2020)
Finanzielle Unabhängigkeit, überleben können, Superheld*in oder Pop-Star sein, Adrenalin-Kick, lebenslange Kompliz*innenschaft und ewige romanti- sche Verbundenheit, Verschwörung, siegreiches Über- listen, Täuschungstechniken – die Fantasien, die sich um die Idee des Bankraubs ranken, sind so verschieden wie die Menschen, die sie haben. Ein Banküberfall ist wahrscheinlich der Traum Vieler, angesichts der zuneh- menden Prekarisierung persönlicher Ökonomien und
– gleichzeitig oder gerade deswegen – ein spektakulari- siertes, fast popkulturelles Ereignis, das in den Medien gut dokumentiert und in unzähligen Filmen illustriert und weitergesponnen wird.
Das vorliegende Gutachten befasst sich mit der Innovationslandschaft des deutschen Journalismus. Innovation wird als eine essenzielle Voraussetzung verstanden, um tragfähige Lösungsansätze für die gegenwärtigen Probleme des Journa-lismus zu entwickeln. Im Mittelpunkt des Gutachtens steht die Frage, wie Innovationspolitik im Journalismus – d. h. die Unterstützung von Innovation durch die öffentliche Hand – funktionstüchtig ausgestaltet werden kann. Dabei wird dem Innovationssysteme-Ansatz gefolgt, welcher Probleme, Barrieren und Hemmnisse identifiziert, die der Innovationsfähigkeit des Journalismus in Deutschland grundlegend im Wege stehen.
In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful tool for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-wavelet-ANN models are compared with those obtained from wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicator in rivers.
Discrete function theory in higher-dimensional setting has been in active development since many years. However, available results focus on studying discrete setting for such canonical domains as half-space, while the case of bounded domains generally remained unconsidered. Therefore, this paper presents the extension of the higher-dimensional function theory to the case of arbitrary bounded domains in Rn. On this way, discrete Stokes’ formula, discrete Borel–Pompeiu formula, as well as discrete Hardy spaces for general bounded domains are constructed. Finally, several discrete Hilbert problems are considered.
The latest earthquakes have proven that several existing buildings, particularly in developing countries, are not secured from damages of earthquake. A variety of statistical and machine-learning approaches have been proposed to identify vulnerable buildings for the prioritization of retrofitting. The present work aims to investigate earthquake susceptibility through the combination of six building performance variables that can be used to obtain an optimal prediction of the damage state of reinforced concrete buildings using artificial neural network (ANN). In this regard, a multi-layer perceptron network is trained and optimized using a database of 484 damaged buildings from the Düzce earthquake in Turkey. The results demonstrate the feasibility and effectiveness of the selected ANN approach to classify concrete structural damage that can be used as a preliminary assessment technique to identify vulnerable buildings in disaster risk-management programs.
Earthquake is among the most devastating natural disasters causing severe economical, environmental, and social destruction. Earthquake safety assessment and building hazard monitoring can highly contribute to urban sustainability through identification and insight into optimum materials and structures. While the vulnerability of structures mainly depends on the structural resistance, the safety assessment of buildings can be highly challenging. In this paper, we consider the Rapid Visual Screening (RVS) method, which is a qualitative procedure for estimating structural scores for buildings suitable for medium- to high-seismic cases. This paper presents an overview of the common RVS methods, i.e., FEMA P-154, IITK-GGSDMA, and EMPI. To examine the accuracy and validation, a practical comparison is performed between their assessment and observed damage of reinforced concrete buildings from a street survey in the Bingöl region, Turkey, after the 1 May 2003 earthquake. The results demonstrate that the application of RVS methods for preliminary damage estimation is a vital tool. Furthermore, the comparative analysis showed that FEMA P-154 creates an assessment that overestimates damage states and is not economically viable, while EMPI and IITK-GGSDMA provide more accurate and practical estimation, respectively.
Conventional superplasticizers based on polycarboxylate ether (PCE) show an intolerance to clay minerals due to intercalation of their polyethylene glycol (PEG) side chains into the interlayers of the clay mineral. An intolerance to very basic media is also known. This makes PCE an unsuitable choice as a superplasticizer for geopolymers. Bio-based superplasticizers derived from starch showed comparable effects to PCE in a cementitious system. The aim of the present study was to determine if starch superplasticizers (SSPs) could be a suitable additive for geopolymers by carrying out basic investigations with respect to slump, hardening, compressive and flexural strength, shrinkage, and porosity. Four SSPs were synthesized, differing in charge polarity and specific charge density. Two conventional PCE superplasticizers, differing in terms of molecular structure, were also included in this study. The results revealed that SSPs improved the slump of a metakaolin-based geopolymer (MK-geopolymer) mortar while the PCE investigated showed no improvement. The impact of superplasticizers on early hardening (up to 72 h) was negligible. Less linear shrinkage over the course of 56 days was seen for all samples in comparison with the reference. Compressive strengths of SSP specimens tested after 7 and 28 days of curing were comparable to the reference, while PCE led to a decline. The SSPs had a small impact on porosity with a shift to the formation of more gel pores while PCE caused an increase in porosity. Throughout this research, SSPs were identified as promising superplasticizers for MK-geopolymer mortar and concrete.