Context information available in wearable devices is believed to be useful in many ways. It allows for hiding much of the complexity from the user, thus enabling simpler user interfaces and less user interaction when carrying out tasks on behalf of a user, as well as enabling network operators to provide a better interface to thirdparty service providers who will provide and deliver wireless services. Using the available context information from the wearable device, optimization of service delivery in wireless networks, such as setting up optimal delivery paths between two wearable devices, may be possible without using a third party to do negotiations. In order to fully enable context-awareness, a clear model for how to sense, manage, derive, store, and exchange context information must be defined. This will then provide the platform needed to enable development of context-aware applications that can exploit the possibilities of context-aware computing. The model must take into consideration parameters such as memory usage and power and bandwidth consumption, in order to be efficient on all types of platforms and in all types of networks. It must also be modular enough to survive replacing and upgrading of internal parts. Today little research is available about sensing context information, sensor management, APIs towards other applications, and how and how often to present context information to applications. Since context aware computing relies heavily on the ability to obtain and represent context information, sensing strategies greatly affect efficiency and performance. It is therefore of great interest to develop and evaluate models for carrying out these tasks in order to exploit the results of context awareness research. This thesis will identify and design several components of such a model, as well as test and evaluate the design, in order to be able to make conclusions to whether is lives up to the expectations stated. In order to make the proper design decisions, a full understanding of the context-awareness research area and the goals and purposes of context-aware computing are required. To understand the entire picture is crucial to find a suitable solution. Therefore, determining an efficient sensor input and management strategy, along with a powerful and flexible API for applications, which are the goals of this thesis, fully qualifies as a significant master thesis assignment. / Information om bärbara enheters omgivning som kan göras tillgänglig i enheten, tros kunna vara användbart på många sätt. Det kan möjliggöra gömmande av komplexitet från användaren, vilket ger enklare användargränssnitt och mindre användarinteraktivitet, när utförandet av uppdrag från användaren sker, eller underlätta för en nätverksoperatör som tillhandahåller ett bättre gränssnitt gentemot en tredje part, som tillhandahåller och levererar trådlösa tjänster. Genom att utnyttja tillgänglig information om omgivningen från en bärbar enhet, kan man optimera leverans av tjänster i trådlösa nätverk, så som att hitta en optimal kommunikationsväg mellan två bärbara enheter, utan att använda sig av förhandlingar med en tredje part. För att till fullo möjliggöra ett sådant omgivningsmedvetande, krävs en tydlig modell för att uppfatta, förfina, lagra och utbyta det data som beskriver omgivningen. Denna modell kan då utgöra en plattform som möjliggör utveckling av omgivningsmedvetande applikationer, som kan utnyttja och reagera på de data som beskriver omgivningen. Modellen måste ta hänsyn till parametrar så som minneskonsumtion och batteri- och bandbreddsförbrukning, för att vara effektiv på alla typer av plattformar och i alla typer av nätverk. Den måste också bestå av tillräckligt väl separerade moduler för att klara av byten och uppgraderingar av dess beståndsdelar. Idag finns endast lite tillgänglig forskning om insamlandet av omgivningsdata, hanteringen av sensorer, gränssnitt gentemot mot applikationer och hur och hur ofta omgivningsdata skall presenteras för applikationer. Eftersom omgivningsmedvetenhet beror av möjligheten att införskaffa och representera omgivningsdata, påverkar strategier för att uppfatta omgivningen både effektivitet och prestanda. Det finns därför ett stort intresse i att utveckla och utvärdera modeller för utförandet av dessa uppdrag och för att utforska forskningsresultat om omgivningsmedvetande. Denna rapport identifierar och konstruerar flera komponenter till en sådan modell, samt testar och utvärderar denna för att kunna dra slutsatser om huruvida den lever upp till de förväntningar som finns. För att kunna göra en fullgod konstruktion, krävs en ingående förståelse i forskningsområdet omgivningsmedvetande och syften och mål med densamma. Att förstå den övergripande bilden är nyckeln till en passande lösning. Konstruktion av effektiva strategier för att uppfatta omgivningen, tillsammans med ett kraftfullt och flexibelt API gentemot applikationer, vilket är målen med denna rapport, kvalificerar sig därför som ett examensarbete.

This research dissertation explores how memory can be used as a design tool when dealing with sites or places that have undergone political oppression in the past. It aims to explore the ways in which memory can inform and invigorate identity and meaning to regain the spirit of the place. The study area is in Marabastad, Pretoria, South Africa, which underwent political oppression including forced relocation, racial separation and destruction of its urban fabric. The future development plans for Marabastad propose that previous residents have the opportunity to return to their land. The use of memories in the future design and development plans becomes important for people who know Marabastad past and for those who don’t because it creates a reference to the past that can be identified with. Marabastad’s meaning lies within its memories and it is important to have this connection to the past in order to build a meaningful future. / Dissertation (MArch(Prof))--University of Pretoria, 2010. / Architecture / unrestricted

Highlighting is an annotation method frequently used to indicate importance. This document introduces context highlighting of web documents and demonstrates that passive readers may benefit from summaries produced by context/keyword highlighting. HighBrow, a prototype browser developed to enable active readers to create context/keyword summaries from web documents, is introduced. This document provides the results of an experiment using three groups of passive readers: the first group reading an entire document; the second group reading a context/keyword summary provided by HighBrow; and the third group reading a keyword only summary (provided by a modified version of HighBrow). The experiment was developed to measure quiz performance, preparation time, and efficiency (quiz score divided by time).

Stress is now recognized as one of the major causes of physical and psychological illness. It is known as a reaction to surrounding environmental threats and the best way to manage it is to understand its triggers. Although people continuously react to their surrounding environments, they sometimes are not aware that certain elements in their environment are considered to be stressors. Based on this fact, researchers have recently proposed context-aware stress management systems. Most of the proposed systems use context data to provide real time stress monitoring and visualization, along with intervention techniques. However, these interventions are limited to the second and tertiary stages and very little attention has been given to the primary stage. In this thesis, we introduce a system called CASP. The system’s objective is to provide stress status predictions based on a user’s current contextual data. Therefore, a detection method is developed using heart rate variability (HRV) as a stress indicator to deliver personalized context-aware stress reports. Based on the predicted status, the system provides users with stress interventions at an early stage in order to help avoid and/or eliminate the occurrence of stress. Our evaluation results show that the CASP system is able to predict the stress status of a user with an averaged accuracy of 78.23% through our limited activity, when compare to a stress status measured using physiological signals. Moreover, it provides prediction models that adapt to the changing nature of both the user’s stress status and the surrounding environment.

In this study I aim to use my body as a tool to derive themes for use in performance making and to underpin this in theory. I focus on aspects of Tadashi Suzuki (1986) actor training (referred to as Suzuki training), free writing and the body. I use black feminism, cognitive neuroscience and body theory to account for my lived body, which I then use in performance. Practice and theory informed each other in a cyclical manner in accordance with Practice as Research as a methodology. Therefore, elements that emerged from my practice determined the theory included in the study, as practice was considered a way of knowing. I work to establish a relationship between race, subjugation and some of the multiple implications thereof on the body in the urban context: I draw on limited notions of culture and the body to interrogate how these can materialise in performance. The study also addresses aspects of the performing body to support why I derive value in Suzuki (1986) training as one psychophysical actor training tool. I theoretically discuss this technique as developing expressive abilities in young performers. The primary purpose of this research is to create work that is rooted in the tradition of devising. My research moves between the physical body and the body in performance in a South African context as I worked to conceptually account for the body in both instances. Although limited, this research includes theories that account for the performing body engaged in somatic foot-based practices where these interact with my practice. I further discuss the devising process I undertook with a cast, as a performance maker, my findings and reflection on this process.

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Increased life expectancy has led to a 15% growth in the population of seniors (aged 65 and above) in Canada, in the last 5 years and this trend is expected to grow. However, the provision of personalized care is bottlenecked, due a severe shortage of formal caregivers in the healthcare industry. Technological solutions are proposed to supplement or replace human care, but have not been widely accepted due to their inability of dynamically adapting to user needs and context of respective situations. Affective data (i.e., emotions and moods of individuals), can be utilized to induce context-awareness and artificial emotional intelligence in such technological solutions, and thereby provide personalized support. Moreover, the capacity of brain to process affective phenomenon can serve as an indicator of onsetting neuro-degenerative diseases. This research thoroughly investigated what affect is, and how it can be used in computing in real-life scenarios. Particularly, evidence was obtained on which biological signals collected using a wearable sensor device were capable of capturing the arousal dimension of affective states (emotions and moods) of individuals. Furthermore, a qualitative study was conducted with older adults using semi-structured interviews, to determine the feasibility and acceptability of different self-report measures of mood, which are crucial to capture the valence dimension of affect. As the hypothesis that older adults would prefer a pictorial measure to self-report their mood failed, we proposed an adjective-based mood reporting instrument prototype, and laid down implications for future research.

<p> Numerous studies have shown retrieval practice to be an effective strategy for improving memory. One account proposed to explain this benefit is the episodic context account (Karpicke et al., 2014). This account proposes that contextual information is reinstated and updated when an item is retrieved. This updated context is then used to aid in retrieval. Examining memory for contextual information, in addition to item memory, may provide additional insight into retrieval practice and what contextual cues are relevant in retrieval. The current study examined memory for temporal-contextual information at 2 different grain sizes: (a) memory for which list a word occurred in, and (b) memory for when an item occurred within a list. Previous research has shown that retrieval practice enhances memory for list temporal contextual information, as assessed by a list discrimination task (Brewer et al., 2010; Chan & McDermott, 2007). In contrast, Karpicke and Zaromb (2010) found worse memory following retrieval practice (relative to restudy) for within-list temporal-contextual information, as assessed by an order reconstruction task. In both experiments of the current study, participants studied multiple lists of words and either engaged in a word stem completion cued recall task, or restudied the words. Our results were partially consistent with previous research. We found no difference in performance between the retrieval practice and restudy groups when assessed on a list discrimination test. However, performance was worse for the retrieval practice group relative to restudy when assessed on an order reconstruction task. Finally, in both experiments, there was no difference in recognition accuracy. Overall, our results suggest that certain retrieval practice tasks may differentially affect memory for various grain sizes of temporal-contextual information. </p>

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