Diegesis and Spatiality are fundamental to visualization techniques in games. The impact of integrating user interfaces into the game world is a contentious issue between minimizing the heads-up display or maximizing functionality above realism. Previous studies have shown conflicting results determining what approach is better, but these studies have focused on conventional genres like the First Person Shooter. Strategy games, or more specifically, the grand strategy genre, is different in perspective and role of the player, as the genre places a heavier emphasis on panel elements than other genres. In this paper, we created two similar prototypes that differed in their focus on integration or superimposition. We then evaluated their impact on performance and the user experiences. The results showed that strictly spatial integration attributed to negative results, but diegetic integration was better received. Additionally, we identified several areas where implementing diegetic interfacing in grand strategy games is different from other genres of games. Finally, we gave recommendations to enhance the strengths and overcome the limitations of diegetic interfacing in grand strategy games. / Datorspel är levande världar som strävar efter att spelare ska ha kul. Olika spel har olika fokus på spelupplevelse, men också olika mängd gränssnitt som finns fastsatt på skärmen kontra inuti spelvärlden. Valet mellan fastsättning och integrering beror på genre och preferens, men mycket av nutida forskning fokuserar på mer vedertagna genrer såsom förstapersonskjutare. Strategispel, och mer specifikt, “grand strategy” spel följer inte samma konventioner, då perspektivet och rollen på spelaren är annorlunda. I detta examensarbete evaluerade vi hur en förändring i fokus mellan fastsättning och integrering av spelelement förändrade spelarprestandan och användarupplevelsen. Resultatet visar att strikt placering av panelelement i världen gav dålig användarupplevelse, men att diegetisk integration gynnade upplevelsen. Till sist analyserade vi hur utveckling av integrerade användargränssnitt inom genren var annorlunda gentemot andra genrer, och gav sedan rekommendationer på styrkor och svagheter som genrenhar.

A method for representing the design space of ortho-planar mechanisms has been developed. The method is based on the Theorem of Equality of Orientation Set Measures (TEOSM) which allows mechanisms to be represented by points in an abstract space. The method is first developed for single loop planar folded mechanisms with revolute joints, and later extended to mechanisms with prismatic joints and to spherical folded mechanisms. Functions which assign a value to each point in design space can be used to describe classes of mechanisms and evaluate their utility for MEMS design. Additionally, this work introduces the use of spherical mechanisms in MEMS design. Spherical mechanisms have characteristics that may be useful in MEMS, including the capability of spatial positioning of a link and the ability to convert rotation about an axis perpendicular to the substrate to rotation about an axis parallel to the substrate. Spherical kinematics has been used to develop three novel mechanisms, the Micro Helico-Kinematic Platform (MHKP), the Spherical Bistable Mechanism (SBM), and the Three-degree-of-freedom Platform (3DOFP). Mathematical models of these devices have been developed and MEMS prototypes have been designed and fabricated.

The use of parametric CAD models in engineering, analysis, and optimization has greatly enhanced the effectiveness and efficiency of the product development process. Parametric models provide an attractive avenue for expansive design exploration. There still exists, however, a great challenge for products requiring design input from multiple disciplines. The collaboration of engineering disciplines can be hampered by many factors including: competing design objectives, communication of design changes, the use of different design and analysis software, and different geometry definitions. These obstacles become compounded when developing products at the assembly level. The use of solid parametric assembly models is not readily employed for products developed by groups from differing engineering disciplines. This is due to the huge cooperative effort required to create, analyze, and iterate on the geometry of the assembly model. The objective of this thesis is to present a method for separate disciplines to be able to analyze multiple parameterizations of the same CAD assembly to help develop a master parametric assembly, and to define the design space to be explored during analysis and optimization. This is done through a custom application developed using the Application Programming Interface of Siemens' NX CAD software. The custom application allows the user to monitor the affects of manipulating the driving parameters of an assembly by observing user specified geometry, features, or parametric expressions. The application also allows switching from one set of parametric design rules controlling the assembly to another in a matter of seconds. Manipulating and observing key geometry from different parameterizations allows engineering teams to discover the impact of each discipline's driving equations and geometry on another discipline. This will have a profound impact on multidisciplinary design teams in developing a robust parametric assembly, while still taking consideration of the requirements of each discipline. The collaborative efforts in the development of parametric assembly models used by multidisciplinary design teams are vastly improved through the method and application developed herein. This research will also show both the enhancements that could be made to existing CAD software, as well as the benefits of custom design tool development within the CAD environment.

The Design of an experiment involves selection of levels of one or more factor in order to optimize one or more criteria such as prediction variance or parameter variance criteria. Good experimental designs will have several desirable properties. Typically, one can not achieve all the ideal properties in a single design. Therefore, there are frequently several good designs and choosing among them involves tradeoffs. This dissertation contains three different components centered around the area of optimal design: developing a new graphical evaluation technique, discussing designs for non-regular regions for first order models with interaction for the two- and three-factor case, and using the standard designs in the case of generalized linear models (GLM). The Fraction of Design Space (FDS) technique is proposed as a new graphical evaluation technique that addresses good prediction. The new technique is comprised of two tools that give the researcher more detailed information by quantifying the fraction of design space where the scaled predicted variance is less than or equal to any pre-specified value. The FDS technique complements Variance Dispersion Graphs (VDGs) to give the researcher more insight about the design prediction capability. Several standard designs are studied with both methods: VDG and FDS. Many Standard designs are constructed for a factor space that is either a p-dimensional hypercube or hypersphere and any point inside or on the boundary of the shape is a candidate design point. However, some economic, or practical constraints may occur that restrict factor settings and result in an irregular experimental region. For the two- and three-factor case with one corner of the cuboidal design space excluded, three sensible alternative designs are proposed and compared. Properties of these designs and relative tradeoffs are discussed. Optimum experimental designs for GLM depend on the values of the unknown parameters. Several solutions to the dependency of the parameters of the optimality function were suggested in the literature. However, they are often unrealistic in practice. The behavior of the factorial designs, the well-known standard designs of the linear case, is studied for the GLM case. Conditions under which these designs have high G-efficiency are formulated. / Ph. D.

CPU cache hierarchies are the central solution in bridging the memory wall. A proper understanding of how to trade-off their high cost against performance can lead to cost-savings without sacrificing performance.Due to the combinatorial nature of the problem, there exist a large number of configurations to investigate, making design space exploration slow and cumbersome. To improve this process, this Thesis develops and evaluates a model for optimally trading-off cost and performance of CPU cache hierarchies, named the Optimal Cache Problem (OCP), in the form of a Non-linear Integer Problem. A second goal of this work is the development of an efficient solver for the OCP, which was found to be a branch & bound algorithm and proven to function correctly. Experiments were conducted to empirically analyse and validate the model and to showcase possible use-cases. There, it was possible to ascribe the model outputs on measurable performance metrics. The model succeeded in formalising the inherent trade-off between cost and performance in a way that allows for an efficient and complete search of the configuration space of possible cache hierarchies. In future work, the model needs to be refined and extended to allow for the simultaneous analysis of multiple programs.

When designing an engineering part, better decisions are made by exploring the entire space of design variations. This design space exploration (DSE) may be accomplished manually or via optimization. In engineering, evaluating a design during DSE often consists of running expensive simulations, such as finite element analysis (FEA) in order to understand the structural response to design changes. The computational cost of these simulations can make thorough DSE infeasible, and only a relatively small subset of the designs are explored. Surrogate models have been used to make cheap predictions of certain simulation results. Commonly, these models only predict single values (SV) that are meant to represent an entire part's response, such as a maximum stress or average displacement. However, these single values cannot return a complete prediction of the detailed nodal results of these simulations. Recently, surrogate models have been developed that can predict the full field (FF) of nodal responses. These FF surrogate models have the potential to make thorough and detailed DSE much more feasible and introduce further design benefits. However, these FF surrogate models have not yet been applied to real engineering activities or been demonstrated in DSE contexts, nor have they been directly compared with SV surrogate models in terms of accuracy and benefits.This thesis seeks to build confidence in FF surrogate models for engineering work by applying FF surrogate models to real DSE and engineering activities and exploring their comparative benefits with SV surrogate models. A user experiment which explores the effects of FF surrogate models in simple DSE activities helps to validate previous claims that FF surrogate models can enable interactive DSE. FF surrogate models are used to create Goodman diagrams for fatigue analysis, and found to be more accurate than SV surrogate models in predicting fatigue risk. Mode shapes are predicted and the accuracy of mode comparison predictions are found to require a larger amount of training samples when the data is highly nonlinear than do SV surrogate models. Finally, FF surrogate models enable spatially-defined objectives and constraints in optimization routines that efficiently search a design space and improve designs.The studies in this work present many unique FF-enabled design benefits for real engineering work. These include predicting a complete (rather than a summary) response, enabling interactive DSE of complex simulations, new three-dimensional visualizations of analysis results, and increased accuracy.

More and more people are affected by stress in their work lives, and it is in society’s interest to decrease the levels of stress [15]. There are several approaches that can be used to reduce stress, such as bodily exercises, digital aids, psychological treatment programs, or relaxation exercises. A new psychological program called Mindfulness-Based Cognitive Therapy (MBCT), originally used to prevent relapses in depression, can also help to treat stress. However, not much research has been conducted on the effects of MBCT to treat stress, and even less on how to design for web solutions for this treatment. The aim of this study is to investigate and explore how web solutions for mindfulness-based cognitive therapy used to treat stress can be designed, with the research question Based on an informed understanding of Mindfulness-Based Cognitive Therapy, how might we, from a design perspective, design a novel web application for it? To investigate this, a research through design approach was used, and the method “future workshop” for the evaluation of the design prototype. The results of this study suggest that when designing websites for MBCT treatments, the most important features to include are visual representations of the patient’s progress and regulated home assignments. The visual representations should show the correlation between stressors and mood, and the regulation would provide assurance to the therapist that the patient does the home assignments. However, more research should be done to further explore the design space in web solutions for mindfulness-based cognitive therapy. / Fler och fler människor påverkas av stress på sina arbeten och det ligger i samhällets intresse att minska stressnivåerna [15]. Det finns flera tillvägagångssätt att minska stress, som exempelvis att göra kroppsliga övningar, använda digitala hjälpmedel, psykologiska behandlingsprogram eller avslappningsövningar. Ett nytt psykologiskt program kallat mindfulnessbaserad (medveten närvaro) kognitiv terapi (MBCT), ursprungligen använt för att förhindra återfall av depression, användas också för att behandla stress. Däremot har det inte gjorts mycket forskning om MBCT:s effekter för att behandla stress, och än mindre om hur man kan designa webblösningar för denna behandling. Målet för denna studie är att undersöka och utforska hur man kan designa webblösningar för mindfulnessbaserad kognitiv terapi som används för att behandla stress med frågeställningen Baserat på befintlig information om mindfulnessbaserad kognitiv terapi, hur kan man, från ett designperspektiv, designa en ny webbapplikation för den? För att undersöka det användes det iterativa tillvägagångssättet ”research through design” och metoden ”future workshop” för att utvärdera designprototypen. Denna studies resultat föreslår att de viktigaste funktionerna att inkludera i designandet av hemsidor för MCBCT-behandlingar är visuella representationer av patientens utveckling, samt reglerade hemuppgifter. De visuella representationerna borde visa korrelationen mellan stressorer och humör, och regleringen skulle garantera terapeuten att patienten gör hemuppgifterna. Däremot bör mer forskning göras för att ytterligare utforska designområdet inom webbaserade lösningar för mindfulnessbaserad kognitiv terapi.

Design Space Exploration (DSE) is the exploration of a space of possible designs with the goal of finding some optimal design according to some constraints and criteria. Within embedded systems design, automated DSE in particular can allow the system designer to efficiently find good solutions in highly complex design spaces. One particular tool for performing automated DSE is IDeSyDe which uses Constraint Programming (CP) and constraint optimization for modelling and optimization. The constraint models of DSE often include some real-valued parameters, but optimized CP-solvers typically require integer arguments. This makes it necessary to discretize the problem in order to make the approach useful in practice, effectively limiting the size of the search space significantly. The effects of this discretization procedure on the quality of the solutions have not previously been well studied. An investigation into how this kind of discretization affects the approximate solutions could make the approach more rigorous, and possibly also uncover exploitable details that could facilitate the development of even more efficient algorithms. This project presents a convergence proof based in CP and Multiresolutional analysis (MRA), including a practically useful error bound for solutions obtained with different discretizations. In particular, the mapping and scheduling of Syncronous Data Flow (SDF) models for streaming applications onto tile-based multiple processor system-on-chip platforms with a common time-division multiplexing bus interconnect is studied. The theoretical results are also verified using IDeSyDe for a few different configurations of applications and platforms. It can be seen that the experiments behave as predicted, with first order convergence in total error and adherence to the bound. / Designrymdsutforskning är benämningen för en systematisk utforskning av en rymd av möjliga designer i syfte att hitta bra eller optimala lösningar som optimerar något mål och som uppfyller krav och begränsningar. Automatiserad designrymdsutforskning har i synnerhet sett utveckling för tillämpningar inom design av inbyggda system, där den ständigt ökande komplexiteten hos moderna plattformar motiverat utvecklingen av nya metoder. Två stora delar är nödvändiga för att kunna tillämpa designrymdsutforskning för design av inbyggda system: en modell av systemet och en optimiseringsprocess. Beroende på situation kan systemmodeller variera från detaljerade simuleringar på transistornivå till övergripande analytiska modeller på applikationsnivå eller högre. Detaljerade simuleringar gör det möjligt att utvärdera en viss lösning mycket noggrant, men till en hög beräkningskostnad. Med analytiska modeller är det istället billigt att utvärdera enskilda lösningar, men på bekostnad av noggrannhet. På samma sätt kan olika optimeringsprocesser också användas: snabbare approximativa algoritmer kan användas för att hitta lösningar relativt snabbt men utan garantier för optimalitet, medans mer uttömmande algoritmer typiskt kräver mycket beräkningskraft. Ett verktyg för automatiserad designrymdsutforskning är IDeSyDe. IDeSyDe använder villkorsbaserade modeller och uttömmande sökning genom Branch and Bound. Optimerade algoritmiska lösare för villkorsprogrammeringsproblem kräver ofta heltalsparametrar. Modeller för designrymdsutforskning innehåller å andra sidan ofta kontinuerliga parametrar. På grund av detta är det ofta nödvändigt att disktretisera problemet för att effektivt kunna hitta lösningar. Eftersom en diskretisering begränsar mängden lösningar i sökrymden riskerar en sådan omformulering att ta bort även optimala lösningar. En designrymdsutforskningsalgoritm som utnyttjar diskretisering av designrymden måste på grund av detta generellt ses som en approximativ algoritm. Hur en sådan diskretisering påverkar lösningarna -- dvs. hur nära de approximativa lösningarna kan förväntas komma den optimala lösningen utan diskretisering -- har dock inte studerats i närmare detalj. En bättre förståelse för hur diskreta, approximativa problem och lösningar relaterar till sina exakta motsvarigheter kan ge metoden mer rigör. En undersökning av den underliggande matematiken har också potential att belysa andra samband och strukturer som potentiellt skulle kunna användas för att utveckla bättre eller mer effektiva algoritmer. I den här rapporten presenteras ett konvergensbevis baserat på villkorsprogrammering och multiupplösningsanalys med ett begränsat felintervall i termer av probleminstansspecifika parametrar och en diskretiseringsparameter. Beviset är framtaget för tillämpning med IDeSyDe och är därför begränsat till en kombination av modeller som verktyget för närvarande stödjer, nämligen strömmande-dataflödesapplikationer beskrivna som synkrona dataflödesmodeller (Synchronous Data Flow, SDF) samt en ''tile''-baserad modell för system med flera processorer på ett chip (MPSoC) med en gemensam tidspartitionerad multiplexor-bus för kommunikation mellan processor-''tiles''. De teoretiska resultaten är verifierade och tillämpade på ett flertal exempelfall beräknade med IDeSyDe, där konvergensen studerats experimentellt.

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Polymer nanofibers are gaining importance due to their wide applicability in diverse fields, such as tissue engineering, fuel cells, photonics and sensors. For these applications, manufacturing aligned polymer nanofibers with precisely controlled morphology and well characterized mechanical properties in a bottom up configuration is essential. In this work, we developed an isodiametric design space for fabrication of aligned polystyrene nanofibers (diameter 60-800nm) using non-electrospinning Spinneret based Tunable Engineered Parameter (STEP) technique. By adjusting the processing parameters such as relative humidity, solvent volatility and polarity, porous polymer tubes are demonstrated having large specific surface areas. Combining STEP with sol-gel process, aligned inorganic nanofibers, such as Titanium Oxide (TiO2) with varied morphologies can be conveniently obtained. Mechanical properties of aligned polymer nanofibers (diameter from 50nm to several hundred nanometers) with fixed-fixed boundary conditions were estimated using a lateral force microscope (LFM). We find that the tension in the fiber caused during fabrication process scales with fiber diameter and it dominates fiber stiffness. Our studies demonstrate isotropic arrangement of polymer chains in the fibers and anisotropic arrangement in the necking region for fibers undergone deformation. Finally, this study demonstrates development of force sensors capable of measuring single cell forces, which scale with the fiber structural stiffness. The ability to measure cell forces during cell division, migration and apoptosis provides new insights in cell mechanobiology. / Ph. D.