Many pervasive computing applications demand expressive situational awareness, which entails an entity in the pervasive computing environment learning detailed information about its immediate and surrounding context. Much work over the past decade focused on how to acquire and represent context information. However, this work is largely egocentric, focusing on individual entities in the pervasive computing environment sensing their own context. Distributed acquisition of surrounding context information is much more challenging, largely because of the expense of communication among these resource-constrained devices. This thesis presents Grapevine, a framework for efficiently sharing context information in a localized region of a pervasive computing network, using that information to dynamically form groups defined by their shared situations, and assessing the aggregate context of that group. Grapevine’s implementation details are presented and its performance benchmarked in both simulation and live pervasive computing network deployments. / text

The current paradigm shift in computing has placed mobile computation at the centre of focus. Users are now even more connected; demanding everything everywhere services. These services, such as social networking and media, benefit from the availability of context information seamlessly gathered and shared; providing customized and user-centric experiences. The distribution of context information no longer conforms to the paradigms of the existing Internet with regards to heterogeneity, connectivity and availability. This mandates new approaches towards its organization and provisioning in support of dependent applications and services. In response to these developments, the work summarized in this thesis addresses the fundamental problem of presenting context information in organized models as relevant subsets of global information. In approaching this problem, I introduced a distributed collection of context objects that can be arranged into simple relevant subsets called context schemata and presented to applications and services in supporting the realization of context based user experiences. Acknowledging the dynamic behaviour inherent of the real world interactions, I introduced an algorithm for measuring the proximities and similarities among these context objects, providing a metric through which to achieve organization. Additionally, I provided a means of ranking heterogeneous and distributed sensors in response to real time interaction between users and their digital ecosystem. Ranking provides an additional metric with which to achieve organization or identifying important and reputable information sources. The work I present here, additionally details my approach to realizing this complete behaviour an a distributed overlay, exploiting its properties for distribution, persistence and messaging. The overlay is also utilized for the provisioning of the supporting context information. Improvements in the ability to discover and attach new context information sources is fundamental to the ability to continually maintain expressions of context, derived from heterogeneous and disparate sources. By being able to create relevant subsets of organized data related to the requirements of applications and services in an end-point, infrastructures are realized for connecting and supporting the increasingly large numbers of users and their sources of information. Coupled with the distribution, these infrastructures realize improvements with regards to the effort required to achieve the same results. The culmination of the work presented in this thesis is an effort to enable seamless context-centric solutions on a future Internet of Things and thus constituting an adequate solution to the challenges raised above.

Context-aware computing requires software that can adapt to changes in context. When contextual circumstances trigger multiple adaptations, software must also understand the relationships between these adaptations and react according to the rules governing these relationships. Adaptable software needs a means to establish and interpret these rules in order to avoid any undesirable and potentially catastrophic conflicts. This dissertation designs and implements the Adaptation Rules Management API (ArmAPI). ArmAPI has been demonstrated to work with a Context-Oriented Programming variation for Java called ContextJ* to execute conflict-free adaptations in two software applications. ArmAPI allows programmers to define relationship types between adaptations, and transfers these definitions to Prolog facts and rules. The Prolog engine, encapsulated within ArmAPI, then works with imperative algorithms to determine the appropriate adaptations to execute based on the current set of facts, rules, and contextual circumstances. Context represents all of the conditions for all of the entities known to an observing device. In any environment, context represents a large amount of data that can influence a multitude of conflicting adaptations. This research provides an incremental step towards overcoming the problem of adaptation conflict by constructing an API that considers the relationship types of inclusion, exclusion, ordering, conditional dependency, and independence. The API has been validated via two prototypes that provide typical scenarios.

This dissertation is composed of research studies that contribute to three research areas including social context-aware computing, internal context-aware computing, and human behavioral data mining. In social context-aware computing, four studies are conducted. First, mobile phone user calling behavioral patterns are characterized in forms of randomness level where relationships among them are then identified. Next, a study is conducted to investigate the relationship between the calling behavior and organizational groups. Third, a method is presented to quantitatively define mobile social closeness and social groups, which are then used to identify social group sizes and scaling ratio. Last, based on the mobile social grouping framework, the significant role of social ties in communication patterns is revealed. In internal context-aware computing, two studies are conducted where the notions of internal context are intention and situation. For intentional context, the goal is to sense the intention of the user in placing calls. A model is thus presented for predicting future calls envisaged as a call predicted list (CPL), which makes use of call history to build a probabilistic model of calling behavior. As an incoming call predictor, CPL is a list of numbers/contacts that are the most likely to be the callers within the next hour(s), which is useful for scheduling and daily planning. As an outgoing call predictor, CPL is generated as a list of numbers/contacts that are the most likely to be dialed when the user attempts to make an outgoing call (e.g., by flipping open or unlocking the phone). This feature helps save time from having to search through a lengthy phone book. For situational context, a model is presented for sensing the user's situation (e.g., in a library, driving a car, etc.) based on embedded sensors. The sensed context is then used to switch the phone into a suitable alert mode accordingly (e.g., vibrate mode while in a library, handsfree mode while driving, etc.). Inferring (social and internal) context introduces a challenging research problem in human behavioral data mining. Context is determined by the current state of mind (internal), relationship (social), and surroundings (physical). Thus, the current state of context is important and can be derived from the recent behavior and pattern. In data mining research area, therefore, two frameworks are developed for detecting recent patterns, where one is a model-driven approach and the other is a data-driven approach.

The latest developments of mobile devices include a variety of hardware features that allow for more rich data collection and services. Numerous sensors, Internet connectivity, low energy Bluetooth connectivity to other devices (e.g., smart watches, activity tracker, health data monitoring devices) are just some examples of hardware that helps to provide additional information that can be beneficially used for many application domains. Among others, they could be utilized in mobile learning scenarios (for data collection in science education, field trips), in mobile health scenarios (for health data collection and monitoring the health state of patients, changes in health conditions and/or detection of emergency situations), and in personalized recommender systems. This information captures the current context situation of the user that could help to make mobile applications more personalized and deliver a better user experience. Moreover, the context related information collected by the mobile device and the different applications can be enriched by using additional external information sources (e.g., Web Service APIs), which help to describe the user’s context situation in more details. The main challenge in context modeling is the lack of generalization at the core of the model, as most of the existing context models depend on particular application domains or scenarios. We tackle this challenge by conceptualizing and designing a rich generic context model. In this thesis, we present the state of the art of recent approaches used for context modeling and introduce a rich context model as an approach for modeling context in a domain-independent way. Additionally, we investigate whether context information can enhance existing mobile applications by making them sensible to the user’s current situation. We demonstrate the reusability and flexibility of the rich context model in a several case studies. The main contributions of this thesis are: (1) an overview of recent, existing research in context modeling for different application domains; (2) a theoretical foundation of the proposed approach for modeling context in a domain-independent way; (3) several case studies in different mobile application domains.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.

Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.

The low literacy levels achieved by deaf children are of ongoing concern to educators and researchers alike. The present research considered emergent literacy as one aspect to consider in the acquisition of literacy skills in deaf children. The aim of this research was to describe the home-based literacy experiences of severely to profoundly deaf pre-schoolers as provided by their hearing parents. Parents of twenty-nine pre-school deaf children from schools for the deaf were selected to complete a questionnaire. The questionnaire was developed based on the four identified literacy contexts: the physical and functional context, the language context, the affective context and the educational context. The results obtained indicate that the deaf children in this survey are exposed to literacy-rich home environments where they are able to observe literate adult role models. Limitations in the quantity and quality of text-based interaction between the deaf pre-schoolers, their hearing parents and older siblings were identified. The results also indicated that the parents who participated in this research regarded the development of language and communication as more important than the early acquisition of literacy skills. The parents assigned the greatest responsibility in teaching literacy skills to teachers. This study highlights the sensitive nature of early literacy and language learning in young deaf children. Suggestions for further research are presented. / Dissertation (M(Augmentative and Alternative Communication))--University of Pretoria, 2005. / Centre for Augmentative and Alternative Communication (CAAC) / unrestricted

Purpose: The purpose of this study is to examine whether the context of ad pictures differs between Chinese ads and US ads and whether it can influence consumers' ad attitudes. Design/methodology/approach: An ad content analysis and a laboratory experiment were conducted to test the hypotheses. Findings: Findings suggest that contextualized ads appear more frequently in Chinese magazines because East Asians have a context-dependent mode of thinking while westerners have a context-independent mode of thinking. However, the effect of culture on advertising is moderated by product class (goods vs service), product category, and magazine category. Moreover, East Asians prefer contextualized ads to non-contextualized ones, while westerners prefer non-contextualized ads to contextualized ads. However, the effect of culture on ad attitudes may be moderated by ad involvement. Research limitations/implications: The limitations of this study stem from its being based on ad samples from China and its use of students to test ad attitudes. Practical implications: The findings allow managers to better determine whether and under what conditions to use contextualized or non-contextualized advertisements. Originality/value: The study's examination of the effect of culture on the context of ad format and effect of context on persuasion in this context constitutes a unique and valuable contribution to the literature. The paper also contributes much to the literature by checking cultural differences across 17 magazine categories, compared to the vast majority of studies analyzing ad content between eastern and western cultures, which have been based on ads from only a few sources.

Purpose: The purpose of this study is to examine whether the context of ad pictures differs between Chinese ads and US ads and whether it can influence consumers' ad attitudes. Design/methodology/approach: An ad content analysis and a laboratory experiment were conducted to test the hypotheses. Findings: Findings suggest that contextualized ads appear more frequently in Chinese magazines because East Asians have a context-dependent mode of thinking while westerners have a context-independent mode of thinking. However, the effect of culture on advertising is moderated by product class (goods vs service), product category, and magazine category. Moreover, East Asians prefer contextualized ads to non-contextualized ones, while westerners prefer non-contextualized ads to contextualized ads. However, the effect of culture on ad attitudes may be moderated by ad involvement. Research limitations/implications: The limitations of this study stem from its being based on ad samples from China and its use of students to test ad attitudes. Practical implications: The findings allow managers to better determine whether and under what conditions to use contextualized or non-contextualized advertisements. Originality/value: The study's examination of the effect of culture on the context of ad format and effect of context on persuasion in this context constitutes a unique and valuable contribution to the literature. The paper also contributes much to the literature by checking cultural differences across 17 magazine categories, compared to the vast majority of studies analyzing ad content between eastern and western cultures, which have been based on ads from only a few sources.