Sammanfattning Denna studie avser att undersöka hur socialsekreterare, boendepersonal och ensamkommande barn talar om integration samt vilka skillnader och likheter som konstrueras mellan grupperna. Syftet är även att studera vilka problem som uppstår i och med att integrationen konstrueras på olika sätt. Detta görs genom kvalitativa intervjuer med tre ensamkommande ungdomar, tre socialsekreterare och fyra boendepersonal. Materialet bearbetas utifrån ett diskursanalytiskt perspektiv och belyser konstruktioner som vi ansett haft en betydelse för våra frågeställningar: Diskursanalyshar även varit vår teoretiska utgångspunkt tillsammans med José Alberto Diazactor context model. Studien visar att det inte finns en enhetlig konstruktion av integration, vilket gör att arbetet och förväntningarna kring integration ser olika ut. Genom respondenternas konstruktioner belyser vi olika aspekter som de menar har betydelse för integrationsprocessen. Deras konstruktioner ger även en bild på förväntningar och behov som respondenterna menar måste tillgodoses för ett gynnsammare arbete med ensamkommande barn och dess integration.

Effective methods for information access are of the greatest importance for our modern lives – particularly with respect to handheld devices. Personalisation is one such method which models a user’s characteristics to deliver content more focused to the user’s needs. The emerging area of sophisticated mobile computing devices has started to inspire new forms of personalised systems that include aspects of the person’s contextual environment. This thesis seeks to understand the role of personalisation and context, to evaluate the effectiveness of context for content personalisation and to investigate the event and map content domain for mobile usage. The work presented in this thesis has three parts: The first part is a user experiment on context that investigated the contextual attributes of time, location and interest, with respect to participants’ perception of their usefulness. Results show highly dynamic and interconnected effects of context on participants’ usefulness ratings. In the second part, these results were applied to create a predictive model of context that was related to attribution theory and then combined with an information retrieval score to create a weighted personalisation model. In the third part of this work, the personalisation model was applied in a mobile experiment. Participants solved situational search tasks using a (i) non-personalized and a (ii) personalized mobile information system, and rating entertainment events based on usefulness. Results showed that the personalised system delivered about 20% more useful content to the mobile user than the non-personalised system, with some indication for reduced search effort in terms of time and the amount of queries per task. The work presented provides evidence for the promising potential of context to facilitate personalised information delivery to users of mobile devices. Overall, it serves as an example of an investigation into the effectiveness of context from multiple angles and provides a potential link to some of the aspects of psychology as a potential source for a deeper understanding of contextual processes in humans.

This thesis presents two novel coding schemes and applications to both two- and three-dimensional image compression. Image compression can be viewed as methods of functional approximation under a constraint on the amount of information allowable in specifying the approximation. Two methods of approximating functions are discussed: Iterated function systems (IFS) and wavelet-based approximations. IFS methods approximate a function by the fixed point of an iterated operator, using consequences of the Banach contraction mapping principle. Natural images under a wavelet basis have characteristic coefficient magnitude decays which may be used to aid approximation. The relationship between quantization, modelling, and encoding in a compression scheme is examined. Context based adaptive arithmetic coding is described. This encoding method is used in the coding schemes developed. A coder with explicit separation of the modelling and encoding roles is presented: an embedded wavelet bitplane coder based on hierarchical context in the wavelet coefficient trees. Fractal (spatial IFSM) and fractal-wavelet (coefficient tree), or IFSW, coders are discussed. A second coder is proposed, merging the IFSW approaches with the embedded bitplane coder. Performance of the coders, and applications to two- and three-dimensional images are discussed. Applications include two-dimensional still images in greyscale and colour, and three-dimensional streams (video).

This thesis presents two novel coding schemes and applications to both two- and three-dimensional image compression. Image compression can be viewed as methods of functional approximation under a constraint on the amount of information allowable in specifying the approximation. Two methods of approximating functions are discussed: Iterated function systems (IFS) and wavelet-based approximations. IFS methods approximate a function by the fixed point of an iterated operator, using consequences of the Banach contraction mapping principle. Natural images under a wavelet basis have characteristic coefficient magnitude decays which may be used to aid approximation. The relationship between quantization, modelling, and encoding in a compression scheme is examined. Context based adaptive arithmetic coding is described. This encoding method is used in the coding schemes developed. A coder with explicit separation of the modelling and encoding roles is presented: an embedded wavelet bitplane coder based on hierarchical context in the wavelet coefficient trees. Fractal (spatial IFSM) and fractal-wavelet (coefficient tree), or IFSW, coders are discussed. A second coder is proposed, merging the IFSW approaches with the embedded bitplane coder. Performance of the coders, and applications to two- and three-dimensional images are discussed. Applications include two-dimensional still images in greyscale and colour, and three-dimensional streams (video).

This paper's main objective is to consolidate the knowledge on context in the realm of intelligent systems, systems that are aware of their context and can adapt their behavior accordingly. We provide an overview and analysis of 36 context models that are heterogeneous and scattered throughout multiple fields of research. In our analysis, we identify five shared context categories: social context, location, time, physical context, and user context. In addition, we compare the context models with the context elements considered in the discourse on intelligent systems and find that the models do not properly represent the identified set of 3,741 unique context elements. As a result, we propose a consolidation of the findings from the 36 context models and the 3,741 unique context elements. The analysis reveals that there is a long tail of context categories that are considered only sporadically in context models. However, particularly these context elements in the long tail may be necessary for improving intelligent systems' context awareness.

Evidence suggests that when memories are reactivated they become labile and can be updated or even erased. Reactivation induces plasticity in memory representations, rendering them fragile, much as they were after initial acquisition. When a memory has been reactivated it must be re-stabilized, which requires reconsolidation. A recent set of studies established the phenomenon of memory reconsolidation for episodic memory (Hupbach et al., 2007, 2008, 2011). That reconsolidation effects apply to explicit memory, which requires conscious recollection, has far reaching implications. In the Hupbach et al. studies the ability of subtle reminders to trigger reconsolidation was investigated; these reminders consisted of the same spatial context, the same experimenter and a reminder question. Given we live in a predictable world, episodes are not random occurrences of events in time and space, but instead consist of statistical and semantic regularities. This leaves open the question of whether semantic relations and statistical regularities between episodes can trigger a reactivation of episodic memory. If so, how would this affect the status of the reactivated memory? This dissertation explored the role of semantic relatedness between the elements of different episodes in memory reactivation and subsequent updating. We focused particularly on categorical and contextual aspects of semantic relations. A series of experiments considered different kinds of semantic relations between elements of episodes, providing evidence of memory reactivation and updating as a consequence of basic level category relations between items in two separate episodes. We also tested the predictions of the Temporal Context Model (TCM) (Sederberg et al., 2011) for our experimental paradigm and show that the current TCM model is not able to account for all the effects of semantic relatedness in the reconsolidation paradigm. Finally, we explore an alternative approach that seeks to explain memory reconsolidation as Bayesian Inference. Our results provide support for this Bayesian framework, showing the potential of it for exploring different aspects of memory organization.

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Technology evolution throughout history has initiated many changes in different aspects of human activities. Learning, as one of the most representative human activities has also been subject to these changes. Nowadays, the use of information and communication technologies has considerably changed the way people learn and collaborate. These changes have been accompanied by new approaches to support learning using a wide range of mobile devices, software applications and different communication platforms. In these technology rich landscapes, the notion of context emerges as a crucial component to be considered for the design and technical implementation of technology-enhanced learning environments. The main research question investigated in this thesis relates to the use of different context instantiations for the design and development of innovative technology-enhanced learning environments.This thesis is a collection of eight papers that describe the results of the research efforts conducted in four different experimental cases during a period of four years. These experiments have been designed and developed as part of two research projects. The theoretical foundations that guided this research were based on the view of context and interaction from a learning theory, human-computer-interaction perspective, as well as dimensional data modelling techniques. Different methodological approaches, (such as action-oriented, design-based research and case study) have been used while investigating the main research question. The main contribution that this thesis offers to the research community is a conceptual context model accompanied by a dimensional data model that can be used as a design tool for embedding learning activities in context. In the four trials that encompass my empirical work, the conceptual model proposed in the thesis guided the design and technical development of the different novel technology-enhanced learning activities. The outcomes of these efforts provided various insights regarding the use of different context instantiations that have implications for the design and development of these environments. This thesis advocates that computational context attributes should be used as metadata descriptors that would potentially promote personalization and interoperability of digital learning content. Content personalization offers opportunities for personalized learning that increases learners’ engagement and eventually could lead to better learning results. Furthermore, the research and industrial community could use the context model developed in this thesis as a guiding tool to promote the creation of new ways to personalize services and technologies.

Context-aware systems can dynamically adapt to user situations to provide smarter services. In general, context refers to the information that can be used to characterize these situations, and context models are deployed to specify contextual information described in context-aware systems. However, even though user context is highly dynamic, existing context models either focus on modeling static views of context or lack appropriate design abstractions to deal with dynamic aspects and interactions involving contextual elements such location, time, user roles, social relationships, and changing preferences. Moreover, virtual environments have not been modelled by most of the existing context models even though online interaction is very common and popular. This thesis presents a dynamic user-centric context model that can be used to model the aspects of context-aware systems that are subject to frequent change. Four case studies are proposed to illustrate the applicability of the approach taken by this thesis, and they are in the domains of mobile e-healthcare, mobile commerce, mobile tourism, and mobile augmented reality gaming. Benefits of the proposed model include avoiding the development of context-aware systems from scratch, enabling future use of model-driven approaches, and reducing implementation effort.

This study deals with immigrants’ political participation in Sweden and the Netherlands. Scholars have recognized low level of political participation of immigrants in Sweden compared to the Netherlands. The main goal of this study is to analyze the institutional influence, mainly from political parties over immigrants’ motivation for active electoral participation. The modified actor-context model uses here as the main theoretical framework. In addition, social capital theory employs to analyze immigrants’ voluntary organizational membership. This study confirms that, Swedish immigrants have the lower participation rate in the political sphere, at lest to a certain extent, than its counterparts the Dutch immigrants. This study also confirms the argument that contextual factors can influence actor’s motivations in integration-oriented action, and similarly it validates the necessity of enlargement of the actor-context model.