Global warming has increased significantly over the past decades and at its center, there are human factors which have the greatest impacts on productions of carbon dioxide which is considered as a primary greenhouse gas in development of global warming. Greenhouse gas emissions and, in particular, carbon dioxide emissions are growing significantly to the extent that if no initiatives are taken, it can have dramatic consequences for our future generations and in general for human’s life on Earth, therefore we need means by which we can control and maintain the levels of greenhouse gas emissions and in particular carbon dioxide emissions. One of the efficient solutions that can significantly decrease the levels of carbon dioxide emissions is the construction and development of smart cities. In this context (smart city), individuals can play an important role in reducing the CO2 emissions. By considering the new opportunities that can result from development of Smart Cities and the essential role of information and communication technology (ICT) in such cities, this thesis work tries to introduce the idea of a self-tracking Carbon Footprint mobile application which enables users to keep track of their individual’s carbon dioxide emissions occurred as a result of their daily activities such as eating, transportation, shopping, energy consumption, and etc. in real time. Being able to measure the generated carbon footprint with respect to each of the user’s activities, users will be able to monitor and control it. This monitoring and controlling of one’s carbon footprint can have significant influences in reducing those human factors which result in production of more carbon dioxide gases and consequently more global warming effects.

This Research-through-Design conducted as thesis project within Malmö University Interaction Design Master’s programme is an attempt to bridge the gap between the quantified self and the subjective & collective experiences of the self-tracking for less normative ways of meaning-making of data. In order to accomplish this, it offers a feminist critique of self-tracking and an exploration of new features for self-tracking apps using provotypes to inform the HCI community.

This thesis questions the idea that; quantified self technology can make us understand our bodies better and facilitate a healthy relationship with the body. Instead, it proposes that a healthy relationship to the body is developed through technology that facilitates a somatic practice, involving the bodily experience in the interpretations of the data. This is achieved by bringing in values inspired by the practice of mindfulness as an alternative to the existing design values promoted in technological solutions dealing with the body. I have designed a first prototype, Inner Mirror, which explores adolescents’ body relationship through screen-based visuals. Inner Mirror detects adolescents’ arousals to visualize their emotional changes in abstract representations that they are invited to connect to specific emotional experiences. The process of designing Inner Mirror will be described thoroughly in the paper. The process was a continuous negotiation between the ideas and values that I brought into the project and the adolescents’ worldview. This is described through a first-person perspective and a participatory design approach. Two school classes of 43 adolescents (between 13 to 14 years old) have participated in the project through three workshops. In the end, I test the prototype in two different settings: on myself, adopting the first-person perspective and together with the adolescents. Finally, three concepts that emerged in the design work are evaluated to suggest a direction for future work.

In quantified safety engineering, mathematical probability models are used to predict the risk of failure or hazardous events in systems. Markov processes have commonly been utilized to analyze the safety of systems modeled as discrete-state stochastic processes. In continuous time Markov models, transition time between states are exponentially distributed. Semi-Markov processes expand this modeling framework by allowing transition time between states to follow any distribution. This master thesis project seeks to extend the semi-Markov modeling framework even further by allowing hierarchical states, which further relaxes Markov-assumptions by allowing models to keep memory even in state transition. To achieve this, the master thesis proposes a method using the phase-type distribution to replace Markov-chains of states to a single state. For application purposes, it is shown how semi-Markov chains with phase-type distributed transitions can be evaluated by a method using the Laplace-Stieltjes transform. Furthermore, to replace semi-Markov chains, a method to approximate these by the phase-type distribution is presented. This is done by deriving the moments of the time to absorption in a semi-Markov process with a method using the Laplace-Stieltjes transform, and fitting a phase-type distribution with these moments. To evaluate the methods, some case studies are performed on appropriate models. Analytical results are compared with Monte-Carlo simulations and Laplace-transform inverse methods. The results are used to show how hierarchical semi-Markov models can be replaced in an exact manner, and how semi-Markov models can be replaced approximately with varying accuracy. An important conclusion is that by enabling hierarchical modeling, it is possible to predict the safety of systems which demand a more realistic model, as relaxing Markov assumptions allows for more complexity. / Matematiska sannolikhetsmodeller används inom kvantifierad säkerhetsteknik för att utvärdera risken för fel eller farliga olyckor i system. Ett vanligt sätt att analysera säkerheten i system som kan modelleras som stokastiska processer med diskreta tillstånd är att använda Markovprocesser. I tidskontinuerliga Markovprocesser är tidsövergången mellan tillstånd exponentialfördelade. Semi-Markov processer utökar denna modelleringsteknik ytterligare genom att tillåta tidsövergångar som är fördelade enligt alla möjliga fördelningar. Detta examensarbete har som mål att utöka modelleringsmöjligheterna med Semi-Markov processer genom att tillåta hierarkiska tillstånd, som därmed ytterligare utmanar antaganden inom Markov-modeller genom att bibehålla minne efter tillståndsövergång. För att uppnå detta föreslås i denna rapport en metod som använder phase-type-fördelningen för att byta ut Markovkedjor med ett enda tillstånd. För att tillämpa metoden visas hur semi-Markov kedjor kan utvärderas med hjälp av Laplace-Stieltjes-transformen. För att kunna ersätta semi-Markov kedjor med samma metod presenteras även en approximationsmetod för att åter igen använda phase-type-fördelningen. Detta görs genom att använda Laplace-Stieltjes-transformen för att generera momenten av tiden till absorption i semi-Markov processer, och anpassa dessa till momenten av en phase-type-fördelning. För att utvärdera metoderna presenteras en del exempel. Analytiska resultat jämförs med Monte-Carlo simulering och inverteringsmetoder för Laplace-transformen. Resultaten används för att visa hur hierarkiska Markov modeller kan ersättas exakt, och hur semi-Markov processer kan approximeras med varierande noggrannhet. En viktig slutsats är att genom att tillåta hierarkisk modellering är det möjligt att utvärdera säkerheten i system som kräver mer realistiska modeller, då detta öppnar upp för mer komplexitet.

Industrie 4.0 und aktuelle Entwicklungen in dem Bereich der produzierenden Unternehmen erfordern hohe Anpassungsleistungen von Menschen und von Maschinen gleichermaßen. In Smart Factories werden Produktionsmitarbeiter zu Wissensarbeitern. Dazu bedarf es neben neuen, intelligenten, technischen Lösungen auch neuer Ansätze für Arbeitsorganisation, Trainings- und Qualifizierungskonzepte, die mit adaptierbaren technischen Systemen flexibel zusammenarbeiten. Das durch die EU geförderte Projekt Factory2Fit entwickelt Lösungen für die Mensch-Technik-Interaktion in automatisierten Produktionssystemen, welche eine hohe Anpassungsfähigkeit an die Fähigkeiten, Kompetenzen und Präferenzen der individuellen Mitarbeiter bieten und damit gleichzeitig den Herausforderungen einer höchst kundenindividuellen Produktion gewachsen sind. Im vorliegenden Beitrag werden die grundlegenden Ziele und Ideen des Projektes vorgestellt sowie die Ansätze des Quantified-self im Arbeitskontext, die adaptive Automatisierung inklusive der verschiedenen Level der Automation sowie die spezifische Anwendung des partizipatorischen Designs näher beleuchtet. In den nächsten Arbeitsschritten innerhalb des Projektes gilt es nun, diese Konzepte um- und einzusetzen sowie zu validieren. Die interdisziplinäre Arbeitsweise sowie der enge Kontakt zwischen Wissenschafts-, Entwicklungs- und Anwendungspartnern sollten dazu beitragen, den Herausforderungen bei der Realisierung erfolgreich zu begegnen und zukunftsträchtige Smart Factory-Lösungen zu implementieren. Das Projekt Factory2Fit wird im Rahmen von Horizon 2020, dem EU Rahmenprogramm für Forschung und Innovation (H2020/2014-2020), mit dem Förderkennzeichen 723277 gefördert.

Récemment, le diagnostic des machines tournantes devient un des sujets de recherche les plus importants. Plusieurs axes sont développés dans ce domaine : traitement de signal, reconnaissance des formes et autres. En plus, les systèmes industriels peuvent être surveillés à distance en temps réel grâce à la disponibilité de l’internet. Cette surveillance se trouve exigeante au niveau de l’acquisition et le stockage des données. En 2004, le Compressive Sensing est introduit dans le but d’acquérir les données a une basse fréquence afin d’économiser l’énergie dans les réseaux de capteurs sans fils. Des résultats similaires peuvent être achevés par l’Echantillonnage Aléatoire qui procure une acquisition à basse fréquence grâce à sa propriété d’anti-repliement. Comme cette technique d’échantillonnage est jusqu’à l’instant de la rédaction de cette thèse n’est pas encore disponible au marché, le travail sur ce sujet se trouve promettant afin de présenter une implémentation pratique validée. D’où, la contribution de cette thèse est de présenter les différentes propriétés de l’échantillonnage aléatoire à travers une étude théorique détaillée dans le domaine temporel et fréquentiel suivie d’une simulation et d’une application pratique sur des signaux synthétisés simples puis sur des signaux de vibration extraits des principaux composants des machines : roulements et engrenages. Les résultats obtenus au niveau de la simulation et la pratique sont satisfaisants grâce à la diminution de la fréquence d’échantillonnage et la quantité de données à sauvegarder ce qui peut être considéré comme une résolution de la problématique de la surveillance à temps réel / Nowadays, machine monitoring and supervision became one of the most important domains of research. Many axes of exploration are involved in this domain: signal processing, machine learning and several others. Besides, industrial systems can now be remotely monitored because of the internet availability. In fact, as many other systems, machines can now be connected to any network by a specified address due to the Internet of Things (IOT) concept. However, this combination is challenging in data acquisition and storage. In 2004, the compressive sensing was introduced to provide data with low rate in order to save energy consumption within wireless sensor networks. This aspect can also be achieved using random sampling (RS). This approach is found to be advantageous in acquiring data randomly with low frequency (much lower than Nyquist rate) while guaranteeing an aliasing-free spectrum. However, this method of sampling is still not available by hardware means in markets. Thus, a comprehensive review on its concept, its impact on sampled signal and its implementation in hardware is conducted. In this thesis, a study of RS and its different modes is presented with their conditions and limitations in time domain. A detailed examination of the RS’s spectral analysis is then explained. From there, the RS features are concluded. Also, recommendations regarding the choice of the adequate mode with the convenient parameters are proposed. In addition, some spectral analysis techniques are proposed for RS signals in order to provide an enhanced spectral representation. In order to validate the properties of such sampling, simulations and practical studies are shown. The research is then concluded with an application on vibration signals acquired from bearing and gear. The obtained results are satisfying, which proves that RS is quite promising and can be taken as a solution for reducing sampling frequencies and decreasing the amount of stored data. As a conclusion, the RS is an advantageous sampling process due to its anti-aliasing property. Further studies can be done in the scope of reducing its added noise that was proven to be cyclostationary of order 1 or 2 according to the chosen parameters

Quantified Boolean formulas (QBFs) play an important role in theoretical computer science. QBF extends propositional logic in such a way that many advanced forms of reasoning can be easily formulated and evaluated. In this dissertation we present our ZQSAT, which is an algorithm for evaluating quantified Boolean formulas. ZQSAT is based on ZBDD: Zero-Suppressed Binary Decision Diagram / which is a variant of BDD, and an adopted version of the DPLL algorithm. It has been implemented in C using the CUDD: Colorado University Decision Diagram package. <br><br> The capability of ZBDDs in storing sets of subsets efficiently enabled us to store the clauses of a QBF very compactly and let us to embed the notion of memoization to the DPLL algorithm. These points led us to implement the search algorithm in such a way that we could store and reuse the results of all previously solved subformulas with a little overheads. ZQSAT can solve some sets of standard QBF benchmark problems (known to be hard for DPLL based algorithms) faster than the best existing solvers. In addition to prenex-CNF, ZQSAT accepts prenex-NNF formulas. We show and prove how this capability can be exponentially beneficial. <br><br> / In der Dissertation stellen wir einen neuen Algorithmus vor, welcher Formeln der quantifizierten Aussagenlogik (engl. Quantified Boolean formula, kurz QBF) löst. QBFs sind eine Erweiterung der klassischen Aussagenlogik um die Quantifizierung über aussagenlogische Variablen. Die quantifizierte Aussagenlogik ist dabei eine konservative Erweiterung der Aussagenlogik, d.h. es können nicht mehr Theoreme nachgewiesen werden als in der gewöhnlichen Aussagenlogik. Der Vorteil der Verwendung von QBFs ergibt sich durch die Möglichkeit, Sachverhalte kompakter zu repräsentieren. <br><br> SAT (die Frage nach der Erfüllbarkeit einer Formel der Aussagenlogik) und QSAT (die Frage nach der Erfüllbarkeit einer QBF) sind zentrale Probleme in der Informatik mit einer Fülle von Anwendungen, wie zum Beispiel in der Graphentheorie, bei Planungsproblemen, nichtmonotonen Logiken oder bei der Verifikation. Insbesondere die Verifikation von Hard- und Software ist ein sehr aktuelles und wichtiges Forschungsgebiet in der Informatik. <br><br> Unser Algorithmus zur Lösung von QBFs basiert auf sogenannten ZBDDs (engl. Zero-suppressed Binary decision Diagrams), welche eine Variante der BDDs (engl. Binary decision Diagrams) sind. BDDs sind eine kompakte Repräsentation von Formeln der Aussagenlogik. Der Algorithmus kombiniert nun bekannte Techniken zum Lösen von QBFs mit der ZBDD-Darstellung unter Verwendung geeigneter Heuristiken und Memoization. Memoization ermöglicht dabei das einfache Wiederverwenden bereits gelöster Teilprobleme. <br><br> Der Algorithmus wurde unter Verwendung des CUDD-Paketes (Colorado University Decision Diagram) implementiert und unter dem Namen ZQSAT veröffentlicht. In Tests konnten wir nachweisen, dass ZQSAT konkurrenzfähig zu existierenden QBF-Beweisern ist, in einigen Fällen sogar bessere Resultate liefern kann.

Characterization and Source Apportionment of Ambient PM2.5 in Atlanta, Georgia: On-Road Emission, Biomass Burning and SOA Impact Bo Yan 260 Pages Directed by Drs. Armistead G. Russell and Mei Zheng Various airborne PM2.5 samples were collected in the metropolitan Atlanta and surrounding areas, which are directly impacted or dominated by on-road mobile and other typical urban emissions, regional transport sources, prescribed burning plumes, wildfire plumes, as well as secondary sources with anthropogenic and biogenic nature in origin. Detailed PM2.5 chemical speciation was conducted including over one hundred of GC/MS-quantified organic compounds, organic carbon (OC), water-soluble organic carbon (WSOC), elemental carbon (EC), ionic species, and tens of trace metals. Day-night, seasonal and spatial variations of PM2.5 characterization were also studied. Contributions of PM2.5 major sources were identified quantitatively through the receptor source apportionment models. These modeling results, especially on-road mobile source contributions and secondary organic carbon (SOC) were assessed by multiple approaches. Furthermore, new season- and location-specific source profiles were developed in this research to reflect real-world and representative local emission characterizations of on-road mobile sources, aged prescribed burning plumes, and wildfire plumes. Secondary organic aerosol (SOA), a major component of PM2.5 in the summer, was also explored for sources and contributions.

Användningen av självkvantifieringsapplikationer är utbredd, men dess utförande långt från fulländat. Den användning som förekommer är nästintill uteslutande koncentrerad till självförbättring. I denna undersökning appliceras denna trend av självförbättring på en global hållbarhetskontext med syfte att minska klimatpåverkan kopplat till livsmedelskonsumtion. Här avses undersöka hur återkoppling i en självkvantifieringsapplikation kan utformas för att förändra en specifik vana, köttkonsumtion. Undersökningen som utfördes bestod i en kvantifieringsstudie där deltagare på egen hand kartlade sin livsmedelskonsumtion utifrån huruvida den var vegetarisk eller ej. Deltagarna i studien fick ta del av olika typer av återkoppling på sin konsumtion. För hälften av deltagarna sattes den personliga konsumtionen i förhållande till den genomsnittliga konsumtionen. Den andra hälften tog istället del av vetenskapligt grundade påståenden om hur konsumtionen måste se ut för en hållbar framtidsutveckling. Ingen av grupperna visade på någon definitiv beteendeförändring av köttkonsumtionen. Deltagarna efterfrågade olika återkoppling beroende på deras mål och viljor samt förkunskaper. Självkvantifering i detta syfte togs väl emot och deltagarna var positiva till användningen, men önskade ytterligare återkoppling. / The use of Quantified Self (QS) applications is widely spread, however, its design and potential is far from fulfilled. Today, its main focus is on self-improvement. This essay aims to investigate how self-improvement can be put in a global sustainable context and how the feedback in a QS-application can be designed to change one specific habit, meat consumption. The survey consisted of a logging phase where participants logged their food consumption in terms of whether each meal was vegetarian or not. The participants in the study were divided into two groups that got two different types of feedback on their consumption. The first group’s feedback consisted of a relation between each participants individual meat consumption related to the mean score of the rest of the group, while the other group got information about scientifically established facts about future sustainable meat consumption. Neither of the groups showed any definite behaviour change in their meat consumption. Results show that the participants had needs for individually designed feedback depending on their motivation, ability and attitudes to the issue. The concept of self quantization got positive feedback in the post-study survey participants were asked to answer, although many of participants requested more interactivity and differently designed feedback content.

Det har idag blivit alltmer populärt att spåra sin aktivitet i syfte att förbättra och förenkla sin vardag och sitt liv. Genom att använda olika verktyg kan människor idag ge produkter och tjänster tillgång till deras data för att spåra deras aktivitet. Ett sådant verktyg är aktivitetsarmbandet och smartklockan. Med dessa kan användare bland annat mäta puls, antal steg och få sms- och samtalsnotifikationer. Armbanden och klockorna samlar därmed in data kring användarnas hälsa och aktivitet och på så sätt kan de visa statistik för användarna för att ge dem information om hur mycket - eller hur lite - de till exempel rör sig under en dag. Denna studie har fokuserat på hur användare upplever användningen av dessa armband och klockor och hur dessa verktyg påverkar deras motivation. Tillvägagångssättet för studien har varit en dagboksstudie kombinerat med kompletterande intervjuer. Genom denna metod har olika teman kunnat identifieras utifrån svaren som dagböckerna och intervjuerna har gett. Dessa teman är: aktivitetsspårning, funktionalitet, personlig utveckling, feedback och uppkoppling. Resultatet har visat att deltagarna i studien upplever i stort sett en motivation av att använda armbanden och klockorna, på så sätt att de uppmuntras att ta fler steg när de ser svart på vitt hur många steg de hittills har tagit. Resultatet pekar även på ett större engagemang hos deltagarna att hålla en koll på deras motion och hälsa, vilket armbanden och klockorna möjliggör. / It has become popular today to track one’s activity in order to improve and simplify one’s everyday life and well being. By using different tools you can today give products and services access to your data for them to track your activity, be it your movement or your phone activity logs. By giving them access to such you can in turn get information for example about how much - or how little - you exercise during a day. This study has focused on how users experience wearables and smart watches and how these tools influence their motivation. Through a diary study and interviews we have identified five themes: activity tracking, functionality, personal development, feedback and connection. The result of this study has shown that most of the participants of the study experience motivation to use the wearables and watches, partly because they can clearly see how many steps they have taken and how many steps they have left to reach their goal. The result also shows a higher commitment among the participants to track their activity and their health, which the wearables and smart watches enable them to do.