As mobile computing applications have become commonplace, it is increasingly important for them to address end-users' privacy requirements. Mobile privacy requirements depend on a number of contextual socio-cultural factors to which mobility adds another level of contextual variation. However, traditional requirements elicitation methods do not sufficiently account for contextual factors and therefore cannot be used effectively to represent and analyse the privacy requirements of mobile end users. On the other hand, methods that investigate contextual factors tend to produce data which can be difficult to use for requirements modelling. To address this problem, we have developed a Distillation approach that employs a problem analysis model to extract and refine privacy requirements for mobile applications from raw data gathered through empirical studies involving real users. Our aim was to enable the extraction of mobile privacy requirements that account for relevant contextual factors while contributing to the software design and implementation process. A key feature of the distillation approach is a problem structuring framework called privacy facets (PriF). The facets in the PriF framework support the identification of privacy requirements from different contextual perspectives namely - actors, information, information-flows and places. The PriF framework also aids in uncovering privacy determinants and threats that a system must take into account in order to support the end-user's privacy. In this work, we first show the working of distillation using qualitative data taken from an empirical study which involved social-networking practices of mobile users. As a means of validating distillation, another distinctly separate qualitative dataset from a location-tracking study is used, in both cases, the empirical studies relate to privacy issues faced by real users observed in their mobile environment.

With the introduction and rapid rise of mobile computing, the multi tasking phenomenon has impinged mobile environments. Currently, mobile devices enable and induce multitasking on the move by taking tasks into mobile environments and encouraging interaction through prompts. But they are al so inhibitors because they fail to support effective, efficient, and enjoyable multitasking. This failure can be traced back to challenges arising from being mobile and to challenges arising from mobile devices. Mobile device users encounter constantly changing mobile contexts, which results in interruptions and unpredicted incidents, distractions, and fluctuations. These lead to increasingly fragmented interaction s. Moreover, these challenges are not addressed by current mobile technologies, which are plagued by issues of " miniaturisation" of mobile devices and their persisting reliance on Graphic User Interface (GUI) metaphors. This thesis aims to develop novel mobile interfaces that support, rather than inhibit, multitasking behaviour on the move. Indeed, it argues that a new direction is required to support mobile interactions by minimising the demands placed upon the human cognitive system caused by interaction tasks and adapting interactions to the context the user is currently in . To achieve this, two approaches from the field of Human-Computer Interaction (HCI), Minimal Attention User Interfaces and context-awareness. A Minimal Attention User Interface (MAUI), taking the form of a multimodal interface, allows for natmal and flexible interaction and reduces the attention taken away from mobility tasks by using complementary modalities rather than disruptive modalities for interaction tasks. To exploit the natural capabilities for human multitasking, cognitive resource theories from the field of Human factors play a central role in the design of such a multimodal interface. The promise of context-aware systems me also harnessed by enabling context-sensitive selection of communication modalities through the recognition of typical mobility tasks.

Context provides information about the present status of people, places, things, network and devices in the environment. Context-awareness refers to the use of context information for an application to adapt its functionality to the current context of use. Development of context-aware applications is inherently complex. Previous researches on mobile computing emphasize on programmable interfaces for development of context-aware systems. There are limited researches that emphasize on the modelling aspects of adaptive applications. This research aims at developing a complete infrastructure for development of context-aware applications. The infrastructure consists of a middleware for context-aware application development that is supported by a set of context information modelling and reasoning facilities. It aims at extending the capabilities of context-aware middleware infrastructures by incorporating novel approaches to model context and situations under uncertainty. This thesis addresses the key challenges in context-aware computing by a complete infrastructure that aims at achieving the following: (1) support for fuzzy composition of high level context abstraction from low level detector context, and fuzzy-based inference mechanisms, (2) support for mobile services that can be dynamically composed and migrated with reference to adaptation requirements for different context situations, (3) support for modelling of adaptation components and entities.

Body Area Networks (BAN) are unique in that the large-scale mobility of users alongside the complexity of body movements allows the network itself to travel across a diverse range of operating domains or even to enter new and unknown environments. These body movements along with the diversity of these unknown environments can create unique transmission channels. This network mobility is unlike node mobility in that sensed changes in inter-network interference level may be used to identify opportunities for intelligent inter-networking, for example, by merging or splitting from other networks, thus providing an extra degree of freedom. As the BAN network travels it will cause and be subject to inter-network interference but it also has the opportunity to sense and interact with a range of other networks. Using a series of carefully controlled measurements of the mesh interconnectivity both within and between ambulatory BANs as well as a stationary desk-based network, this thesis presents an investigation of context aware body area network (CABAN) interference detection at the physical layer. This thesis, also gives consideration to the co-existence of multiple co-located BAN users and the complex interaction of body-shadowing, user movement as well as the multi:"path environment itself and its impact on channel conditions. The final aspect of the thesis investigates the interaction between physical layer characteristics and packet error rate (PER) at the data link layer as two independent BANs operating in CSMA networks as they could merge and split

One of the main reasons why smartphone users do not adopt authentication mechanisms is due to the inefficiency of entering a PIN/Pattern/Password each time they use their phone. On the other hand. users who do use these locking mechanisms find them annoying (40- 47%) (Egelman et al.. 2014; Harbach et al., 2014; Jakobsson et al., 2009). Previous research (Gupta et al. 2012; Hayashi et al., 2013) has studied the potential of using sensor data to detect the location of the phone for the purpose of implicit authentication. However. little consideration has been given to applying the rich set of environment-related sensor data such as noise. light and magnetic field ("ambient factors") to authentication. Therefore, this research used ambient sensors with the purpose of detecting changes in environmental surroundings so that the phone asks for explicit authentication only when a change is detected in these conditions. The main aim is to improve the efficiency and user satisfaction of smartphone authentication mechanisms, to increase use (adoption) among traditional nonadopters (users who do not lock their phone). and reduce the level of annoyance to current adopters, all while maintaining a reasonable level of security. An empirical study was first conducted to investigate the use of ambient sensors and to determine if ambient profiles that confirm the consistency of sensor readings for a user would improve the efficiency of smartphone authentication. Subsequently, two further empirical studies were conducted to investigate the strengths and weaknesses of this mechanism from a security and battery consumption perspective. Since all these empirical studies confirmed the premise of this work. a three phase user study was conducted to evaluate this novel context-sensitive authentication mechanism from a usability and adoption perspective. The security and battery consumption studies showed that the use of ambient sensors during context-sensitive authentication adds an extra layer of security over location only solutions because this authentication mechanism can reasonably detect most of the insider attacks and still achieve an acceptable number of false positives (where there is a failure to identify the legitimate user). The usability and adoption study showed that both current adopters and traditional non-adopters felt that the evaluated mechanism had all the necessary qualities for being adopted because it satisfied their divergent security needs. Unlocking their phone only when necessary was considered to be more efficient. did not annoy them and offered a reasonable level of security. Another contribution of this thesis is that participants responded positively to the option of choosing when a PIN/Pattern is required in different contexts. Therefore, this research recommends that designers of smartphone locking mechanisms should consider ceding a reasonable level of control over security settings (e.g. choosing the locations in which explicit authentication is required) to users to increase adoption and convenience, while keeping smartphones reasonably secure.

This study investigates the state of the art of the concept and practice of Mobile Learning (ML) and the integration of Mobile Device Technologies (MDTs) in educational processes. Using a combination of techniques from Requirement Engineering (RE) and Agent Oriented Software Engineering (AOSE), the domain is explored and analysed for ongoing effectiveness and sustainability. Impressive advances in MDTs have made them pervasive and entrenched in many cultures, systems and in everyday living. In the last decade, the emergent of mobile / handheld devices, and subsequently, wireless technology standards have given rise to the concept of ML. Although MDT was seen by many early on as part of the solutions for learning transformation, quantifying benefits and placement in teaching and learning, either to achieve learning objectives or enhance the process remain problematic. In spite of efforts in the last decade by researchers and educators, expected potentials for learning mobility and adaptability resulting from their use are largely unfulfilled. Rapid changes in development and manufacture also continue to present additional challenges. Most research studies typically employ the approach of evidencing benefits through usage implementations and experimentation. In the review of this thesis, application of techniques provided in domain neutral RE and AOSE disciplines for specifying goals and requirements for complex systems is proposed. Alignment with teaching and learning strategies as well as institutional goals and strategies is considered essential for successful integration in any learning institution. Consequently, this review advocate strategies for alignment through elicitation and modelling techniques of RE and AOSE disciplines. Requirement elicitation is carried out using a mixed methods of inquiry comprising of four phases in sequential & parallel investigations. Phase I involves literature / citation report analysis / systematic review and quantitative survey. Secondary quantitative data is also sought during this phase. Phase II includes further in-depth quantitative and qualitative study. Questions used during this phase are designed from issues arising in Phase I. Phase III comprises of targeted studies among stakeholders in Higher Educational Institutions (HEIs), allowing for comparison of underpinning policies, cultures and practices; gaining an understanding of the concept and influential factors. Data gathering techniques include surveys, observations, interviews and focus group sessions. Using both sequential and parallel mixed method of enquiry afford opportunities to establish a frame of reference and analyse opinions within the domain among relevant stakeholders: students, academics / educators, those in the role of learning support and governance and IT support personnel. The survey is analysed using descriptive statistical analysis techniques, also involving comparison of responses from all participating groups. Qualitative data is analysed using thematic methods The review of this thesis contributes to the body of knowledge on ML as a concept and practice, evaluating definitions, frameworks and practices as relating to HEIs for the most part. Approaches to integration by selected HEIs are explored and analysed for effectiveness. A series of models is created illustrating the use of RE and AOSE techniques to align ML system requirements with organisational goals and strategies. Outcomes from the review will make it possible to advance research and knowledge forward for the practice of ML and integration of MDTs in educational processes.

The knowledge of the facing direction of a human can provide imp0l1ant behavioural cues that can be exploited for a diverse set of pervasive computing applications, ranging from improved human computer interactions and real world gaming to navigation and social signal processing. However, providing a machine understanding of the facing direction of humans continuously in different daily life situations remains a significant technical challenge, despite the increasing pervasiveness of computing technologies and advances in mobile computing. This thesis aims to close this gap by providing a solution for opportunistic estimation of the facing direction of smartphone users. While achieving this objective, it addresses a number of challenges faced by mobile phone centric sensing systems including the volatile orientation and wearing position of the device in daily life situations and on-the-fly calibration of the sensors measurements against environmental impacts such as magnetic perturbation. Estimation of the facing direction of users is based on a novel technique, which exploits the acceleration pattern that can be measured by a smartphone as the user is walking. This approach is independent of the initial orientation of the device and is adaptable to various wearing positions on a user's body, which gives the user a larger degree of freedom. The information about the wearing position is provided by an intelligent wearing position recognition technique, which constitutes our second contribution. Utilising a novel pre-processing approach alongside with It set of carefully selected features classifiers the proposed technique provides timely estimations of the wearing position of the device with almost perfect accuracy. Also a novel iterative algorithm is developed for fast and accurate calibration of the magnetometer readouts. The provided algorithm estimates and compensates the magnetic interference parameters with a minimum number of magnetic field samples while imposing a very low computation cost. Detailed evaluations of each individual technique against the existing state of the 31t techniques arc provided. Throughout the evaluation procedures, prototypes of the techniques are developed on a smartphone when required and several field experiments are conducted. In order to prove the applicability of the provided approach for real world applications, two mobile phone application examples have been developed and evaluated in practice, which include a dead reckoning and a face-to- face interaction detection application. Our work provides an initial proof that conventional off-the-shelve smal1 phones can serve as a suitable platform for pervasive user direction estimation, provided that adequate algorithms are deployed on it.

As the demand for feature-rich portable devices continues to increase, new techniques are needed to minimise power consumption. This thesis is concerned with the development and validation of new systematic architectural methods of determining pipeline stage insertion in data-dominated designs with the aim of reducing dynamic power consumption. The methods place special emphasis on the number of latches used in pipeline stages and voltage scaling. The first part of the thesis addresses power:minimisation through systematic analysis of the number of latches in pipeline stages. A new pipeline stage insertion (PSI) method operating at the architectural level is developed which takes into account system clock period and FEs outputs and delays. A PSI algorithm based on analytical heuristic equations is formulated to ensure the successful application of this method to any given data-dominated design. The input to the algorithm 'is designer clock period and naively inserted pipeline stages. The output from the algorithm is a pipelined design fulfilling the timing constraint with the least dynamic power consumption. To support efficient power-performance trade-offs exploration, the algorithm was fully automated. The second part of the thesis focuses on the validation of the PSI method using two real-life case studies: triple data path floating-point adder· and MPEG-I motion compensation module. These designs are common in many portable devices and have numerous implementation challe·nges including large number of FEs and significant power consumption. Extensive experimental results show that for the motion compensation module, the PSI is able to reduce dynamic power consumption by up to 30% compared with other reported approaches. The final part of the thesis concentrates on voltage scaling (VS) and its impact on pipeline stages. The timing slack available in each stage is investigated, with the aim of further reducing power consumption by lowering the supply voltage. The PSI method is modified to support voltage scaling, and as a result, a new pipeline stage insertion with voltage scaling (PSI-VS) method is proposed. Experimental results show that the PSI-VS can lead to significant power saving compared with PSI without VS. For the MPEG-I motion compensation case study, a power saving of 68% is observed. All the developed methods have linear time complexity as the number of pipeline stages increases, facilitating their application to large designs without incurring run time penalty. The results for the case studies were based on a synthesisable RTL implementation using 90nrn technology together with accurate power analysis using commercial tools.

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The use of technology across a number of domains and facets is widespread. It is predicted by Forrester that almost half (42%) of the entire world’s population, by the end of 2015, will own a smart phone. Furthermore, during the last ten years, there has been much development in the communication arena as a direct result of smart mobile technologies, including within the work setting, thus facilitating a greater degree of communication and information-sharing capacity in work communities. Nonetheless, it remains that not all the features and tools offered by this technology are utilised, which predominantly is owing to the lack of insight and understanding of users. Accordingly, we argue that people sharing knowledge in the workplace are sharing all the knowledge they are aware of in the most effective way, because it is shared in the situation where they naturally experience problems -at the workplace. Owing to the universal nature inherent in this technology, it is considered pivotal that smart phone technology goes hand-in-hand with intrinsic support. Importantly, however, if not altogether lacking, this is very often inadequate. However, adopting mobile technology within the workplace setting can give rise to challenges that impact user behaviour and performance. Four studies were conducted with the aim of examining how employees address and manage problems on a smart mobile device (SMD) and accordingly aim at overcoming the issue. The first three studies considered provides valuable input for the researcher that was recognised as required in the fourth research. The third study was carried out amongst 90 participants located in two countries, using internet connectivity, as a case study. Confidence and frustration have previously been connected with technology competence, but this was not applied to a workplace scenario during problem-solving, when users are assigned an unfamiliar smart mobile device. This research focuses on identifying the link between workplace users’ levels of confidence and frustration when seeking to independently solve problems whilst completing familiar tasks on new smart mobile devices. A detailed video analysis of users’ attitudes and behaviour during problem- solving was conducted, highlighting a correlation between attitudes and behaviour towards completing a task. When reviewing and considering the findings from the first researches, the criteria for a universal crowdsourcing solution were identified. In the final of the studies, users across different levels of technology experiences and from varying job roles in different departments in a firm were brought together to form a collaborative community referred to as YourSpace designed and implemented for this thesis. To this end, the subjects were grouped across three progressive levels of a knowledge management framework devised for this specific study, namely Pedagogy (engagement), Andragogy (cultivation) and Heutagogy (realisation) levels. The employees of Malta International Airport were permitted to utilise YourSpace for a one- week period, during which time there was an assessment of its adoption within the work setting. Methodology validation in this thesis was carried out through the considered design of a tablet-based research instrument that encompassed a characteristic facilitating knowledge-capture. This was achieved through taking YourSpace and accordingly utilising its peer-to-peer support communities. An innovative method is introduced through improving modern-day global technology in a number of ways: firstly, by further expanding works carried out in the social media domain, specifically by capturing Just in Time knowledge when seeking to overcome obstacles in the work environment; secondly, by providing a crowdsourcing instrument with the capacity to capture Just in Time knowledge in an organic work setting through gaining insight into individuals’ characteristics and their within-community interactions throughout the process; and thirdly, by examining the behaviours and perspectives of users when seeking to overcome common issues experienced when utilising an unfamiliar device. The results highlighted provide a crowdsourced Just in Time support solution, which could prove pivotal in overcoming problems through the provision of a collaborative framework that supports the gathering of knowledge that is not dependent on technology experience.