Utemöbler i dagens offentliga miljö ger möjligheter till en stunds andrum, men är det allt vi kräver idag för att trivas med vår omgivning? Samhället såväl som individen förlitar sig på telefoner och personlig elektronik för både funktioner och rekreation. Teknologi är alltid närvarande och då framtidens Smarta städer ska forma sig efter hur invånaren lever bör också utemiljön spegla hur vi lever idag med framtidssyn. Soliotech är ett företag som säljer smarta utebänkar och söker inspiration till expansionsmöjligheter inom deras sortement. Syftet med rapporten är att i undersöka trivsel i den offentliga utemiljön med fokus på solceller och smarta utemöbler, och samtidigt finna en rekommenderad väg för Soliotech att expandera sitt sortiment. Examensarbetet omfattar en klassisk designprocess indelad i sektioner: Planering, Utforska kontext, idégenerering samt prototypande. Processen förklaras linjärt för enkelhetens skull trots att den är högst iterativ. Först planeras projektet grovt innan relevanta aspekter utforskas i syfte att skapa en förståelse för intressenter, teknologi och utemiljö. Idéer genereras och utvärderas efter kriterier som byggs under utforskningen innan ett utvalt koncept tas vidare till prototypande fasen. Där experimenteras med funktion, ergonomi och gestaltning innan ett slutkoncept presenteras: Noah, en samlingsplats i utemiljö med smarta funktioner.

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This work introduces diagnostic methods for land surface model (LSM) evaluation that enable developers to identify structural shortcomings in model parameterizations by evaluating model 'signatures' (characteristic temporal and spatial patterns of behavior) in feature, cost-function, and parameter spaces. The ensemble-based methods allow researchers to draw conclusions about hypotheses and model realism that are independent of parameter choice. I compare the performance and physical realism of three versions of Noah LSM (a benchmark standard version [STD], a dynamic-vegetation enhanced version [DV], and a groundwater-enabled one [GW]) in simulating high-frequency near-surface states and land-to-atmosphere fluxes in-situ and over a catchment at high-resolution in the U.S. Southern Great Plains, a transition zone between humid and arid climates. Only at more humid sites do the more conceptually realistic, hydrologically enhanced LSMs (DV and GW) ameliorate biases in the estimation of root-zone moisture change and evaporative fraction. Although the improved simulations support the hypothesis that groundwater and vegetation processes shape fluxes in transition zones, further assessment of the timing and partitioning of the energy and water cycles indicates improvements to the movement of water within the soil column are needed. Distributed STD and GW underestimate the contribution of baseflow and simulate too-flashy streamflow. This work challenges common practices and assumptions in LSM development and offers researchers more stringent model evaluation methods. I show that, because of equifinality, ad-hoc evaluation using single parameter sets provides insufficient information for choosing among competing parameterizations, for addressing hypotheses under uncertainty, or for guiding model development. Posterior distributions of physically meaningful parameters differ between models and sites, and relationships between parameters themselves change. 'Plug and play' of modules and partial calibration likely introduce error and should be re-examined. Even though LSMs are 'physically based,' model parameters are effective and scale-, site- and model-dependent. Parameters are not functions of soil or vegetation type alone: they likely depend in part on climate and cannot be assumed to be transferable between sites with similar physical characteristics. By helping bridge the gap between the model identification and model development, this research contributes to the continued improvement of our understanding and modeling of environmental processes. / text

Responsible design practice should include environmental advocacy and a focus on community — subjects often lacking in design education. My creative project is the result of investigations into how designers integrate nature into their design process. By increasing their awareness for communal and environmental advocacy at the undergraduate level, students can develop responsible design practices at the beginning of their career. The result is the student's accumulation of integrity.

Anhand eines der erfolgreichsten Theaterstücke der Saison 2007/2008 untersucht der Beitrag die Repräsentation und Rolle von Schrift und Schreiben in Ulrich Hubs für Kinder verfassten "An der Arche um acht".

Anhand eines der erfolgreichsten Theaterstücke der Saison 2007/2008 untersucht der Beitrag die Repräsentation und Rolle von Schrift und Schreiben in Ulrich Hubs für Kinder verfassten "An der Arche um acht".

This master's thesis deals with the implications of metaphorical language, which comedy news programs used to portray Donald Trump as a candidate during the 2016 US presidential election. First, the author outlines the most important moments of Donald Trump's presidential campaign, then introduces the comedy news genre as well as three comedy news programs - The Daily Show, Last Week Tonight and Real Time - which are included in the analytical part of the thesis. The thesis continues with the theoretical and methodological chapters, in which conceptual metaphor analysis based on the works of Lakoff, Johnson and Yanow is presented. The metaphor analysis itself, performed on 73 comedy news episodes, reveals that mostly the same metaphors were used across all three programs and they overwhelmingly portray Donald Trump as non-human. As the election kept approaching, Donald Trump was increasingly portrayed as "a natural disaster," "the apocalypse" or "the Devil." The author suggests that the overall tacit objective of the metaphors used in the three comedy news programs was to dehumanize Donald Trump. Finally, the limitations of the analysis are discussed and suggestions for further research on the implications of metaphorical language are made.

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Land surfaces have changed as a result of human and natural processes, such asdeforestation, urbanization, desertification and natural disasters like wildfires. Land use and landcover change impacts local and regional climates through various bio geophysical processes acrossmany time scales. More realistic representation of land surface parameters within the land surfacemodels are essential to for climate models to accurately simulate the effects of past, current andfuture land surface processes. In this study, we evaluated the sensitivity and accuracy of theWeather Research and Forecasting (WRF) model though the default MODIS land cover data andannually updated land cover data over southeast of United States. Findings of this study indicatedthat the land surface fluxes, and moisture simulations are more sensitive to the surfacecharacteristics over the southeast US. Consequently, we evaluated the WRF temperature andprecipitation simulations with more accurate observations of land surface parameters over thestudy area. We evaluate the model performance for the default and updated land cover simulationsagainst observational datasets. Results of the study showed that updating land cover resulted insubstantial variations in surface heat fluxes and moisture balances. Despite updated land use andland cover data provided more representative land surface characteristics, the WRF simulated 2- m temperature and precipitation did not improved due to use of updated land cover data. Further,we conducted machine learning experiments to post-process the Noah-MP land surface modelsimulations to determine if post processing the model outputs can improve the land surfaceparameters. The results indicate that the Noah-MP simulations using machine learning remarkablyimproved simulation accuracy and gradient boosting, and random forest model had smaller meanerror bias values and larger coefficient of determination over the majority of stations. Moreover,the findings of the current study showed that the accuracy of surface heat flux simulations byNoah-MP are influenced by land cover and vegetation type.