Recent years have seen a rapid growth in movement research owing to new technologies contributing to the miniaturization and reduced costs of tracking devices. Similar trends have occurred in how environmental data are being collected (e.g., through satellites, unmanned aerial vehicles, and sensor networks). However, the development of analytical techniques for movement research has failed to keep pace with the data collection advances. There is a need for new methods capable of integrating increasingly detailed movement data with a myriad of contextual data - termed context aware movement analysis (CAMA). CAMA investigates more than movement geometry, by including biological and environmental conditions that may influence movement. However, there is a shortage of methods relating movement patterns to contextual factors, which is still limiting our ability to extract meaningful information from movement data. This thesis contributes to this methodological research gap by assessing the state-of-the art for CAMA within movement ecology and human mobility research, developing innovative methods to consider the spatio-temporal differences between movement data and contextual data and exploring computational methods that allow identification of patterns in contextualized movement data. We developed new methods and demonstrated how they facilitated and improved the integration between high frequency tracking data and temporally dynamic environmental variables. One of the methods, multi-channel sequence analysis, is then used to discover varying human behaviour relative to weather conditions in a large human GPS tracking dataset from Scotland. The second method is developed for combing multi-sensor satellite imagery (i.e., image fusion) of differing spatial and temporal resolutions. This method is applied to a GPS tracking data on maned wolves in Brazil to understand fine-scale movement behaviours related to vegetation changes across seasons. In summary, this thesis provides a significant development in terms of new ideas and techniques for performing CAMA for human and wildlife movement studies.

Weighted granular best matching algorithm is proposed for the operation of context matching in context-aware computing systems. New algorithm deals with the subjective, fuzzy and multidimensional characteristics of contextual information by using weights and a granular structure for contextual information. The proposal is applied on a case: CAPRA &ndash / Context-Aware Personal Reminder Agent tool to show the applicability of the new context matching algorithm. The obtained outputs showed that proposed algorithm produces the results which are more sensitive to the user&rsquo / s intention, more adaptive to the characteristics of the contextual information and applicable to a current Context-aware system.

Master of Science / Department of Mathematics / Andrew G. Bennett / In recent years motivation research has emerged as an area of interest within educational research. Increasing student achievement is not the only aspect of education being studied. Improving the quality of the learning experience and investigating how this improvement affects student achievement is an area of growing interest. Additional investigations also consider what aspects of instruction and teaching affect the quality of the learning experience. Many mathematical organizations have voiced a concern that post-secondary mathematics courses should adapt curriculum and instruction based on results of this research. The current study is an investigation into the effectiveness of suggestions made by these organizations, as well as the effect instructional adaptations have on student attitude and achievement.

Social entrepreneurship has grown in popularity since Muhammad Yunus and Grameen Bank was awarded the Nobel Peace Prize in the year 2006. Pollinate Energy is an Australian social business working to improve the lives of the urban poor in India. The purpose of this study is to investigate the portability of the organisation’s business model to other geographical locations, e.g what adjustments might be needed if transferring and implementing the concept in new cities and locations. A qualitative case study approach was conducted by gathering experiences from Bangalore through interviews and secondary sources and field observations from a field study conducted in Hyderabad, India. The results indicate that the local cultural context shapes the structure of the concept. It was found to be easier to establish relationships through products with immediate tangible benefits, which indicates that products are highly context dependent. Therefore, local trials of products are needed for the concept to be effective. Moreover, further investigations of the model would be required if the concept were to be transferred to other geographical locations. The model can generate spin-off effects contributing to development, and can thus be a catalyst for social change.

The Harry Potter novels written by J.K Rowling have been popular since the first book was released in 1997. Rowling has written seven books about Harry and the first four together with the Swedish National Agency for Education constitute the primary sources of this essay. The essay discusses how these supposed children’s’ novels can be used to construct a lesson for students in the Swedish upper secondary classroom. The lesson plan created is based on the analysis of the possible themes of the novels using Postcolonial and Marxist critical perspectives. The theories are used to show how discrimination and suppression can be seen in the Harry Potter novels. Previous research has shown that the occurrences in Harry Potter is similar to the occurrences happening in the real world and the lesson plan is created to compare these fictional happenings with the ones happening in our real society. The lesson plan constructed consequently focuses on how the Harry Potter novels can be used to discuss discrimination and suppression takes place in English speaking societies as required by the rules and guidelines provided by the Swedish National Agency for Education.

In modern software development, the gap between software requirements and implementation is not always conciliated. Typically, for Web services-based context-aware systems, reconciling this gap is even harder. The aim of this research is to explore how software reengineering can facilitate the reconciliation between requirements and implementation for the said systems. The underlying research in this thesis comprises the following three components. Firstly, the requirements recovery framework underpins the requirements elicitation approach on the proposed reengineering framework. This approach consists of three stages: 1) Hypothesis generation, where a list of hypothesis source code information is generated; 2) Segmentation, where the hypothesis list is grouped into segments; 3) Concept binding, where the segments turn into a list of concept bindings linking regions of source code. Secondly, the derived viewpoints-based context-aware service requirements model is proposed to fully discover constraints, and the requirements evolution model is developed to maintain and specify the requirements evolution process for supporting context-aware services evolution. Finally, inspired by context-oriented programming concepts and approaches, ContXFS is implemented as a COP-inspired conceptual library in F#, which enables developers to facilitate dynamic context adaption. This library along with context-aware requirements analyses mitigate the development of the said systems to a great extent, which in turn, achieves reconciliation between requirements and implementation.

Information protection is a key issue for the acceptance and adoption of pervasive computing systems where various portable devices such as smart phones, Personal Digital Assistants (PDAs) and laptop computers are being used to share information and to access digital resources via wireless connection to the Internet. Because these are resources constrained devices and highly mobile, changes in the environmental context or device context can affect the security of the system a great deal. A proper security mechanism must be put in place which is able to cope with changing environmental and system context. Usage CONtrol (UCON) model is the latest major enhancement of the traditional access control models which enables mutability of subject and object attributes, and continuity of control on usage of resources. In UCON, access permission decision is based on three factors: authorisations, obligations and conditions. While authorisations and obligations are requirements that must be fulfilled by the subject and the object, conditions are subject and object independent requirements that must be satisfied by the environment. As a consequence, access permission may be revoked (and the access stopped) as a result of changes in the environment regardless of whether the authorisations and obligations requirements are met. This constitutes a major shortcoming of the UCON model in pervasive computing systems which constantly strive to adapt to environmental changes so as to minimise disruptions to the user. We propose a Context-Aware and Adaptive Usage Control (CA-UCON) model which extends the traditional UCON model to enable adaptation to environmental changes in the aim of preserving continuity of access. Indeed, when the authorisation and obligations requirements are fulfilled by the subject and object, and the conditions requirements fail due to changes in the environmental or the system context, our proposed model CA-UCON triggers specific actions in order to adapt to the new situation, so as to ensure continuity of usage. We then propose an architecture of CA-UCON model, presenting its various components. In this model, we integrated the adaptation decision with usage decision architecture, the comprehensive definition of each components and reveals the functions performed by each components in the architecture are presented. We also propose a novel computational model of our CA-UCON architecture. This model is formally specified as a finite state machine. It demonstrates how the access request of the subject is handled in CA-UCON model, including detail with regards to revoking of access and actions undertaken due to context changes. The extension of the original UCON architecture can be understood from this model. The formal specification of the CA-UCON is presented utilising the Calculus of Context-aware Ambients (CCA). This mathematical notation is considered suitable for modelling mobile and context-aware systems and has been preferred over alternatives for the following reasons: (i) Mobility and Context awareness are primitive constructs in CCA; (ii) A system's properties can be formally analysed; (iii) Most importantly, CCA specifications are executable allowing early validation of system properties and accelerated development of prototypes. For evaluation of CA-UCON model, a real-world case study of a ubiquitous learning (u-learning) system is selected. We propose a CA-UCON model for the u-learning system. This model is then formalised in CCA and the resultant specification is executed and analysed using an execution environment of CCA. Finally, we investigate the enforcement approaches for CA-UCON model. We present the CA-UCON reference monitor architecture with its components. We then proceed to demonstrate three types of enforcement architectures of the CA-UCON model: centralised architecture, distributed architecture and hybrid architecture. These are discussed in detail, including the analysis of their merits and drawbacks.

Context-aware systems use context information to decide what adaptation actions to perform in response to changes in their environment. Depending on applications, context information includes physical context (e.g. temperature and location), user context (e.g. user preferences and user activity), and ICT context (e.g. device capabilities and battery power). Sensors are the main mean of capturing context. Unfortunately, sensed context data are commonly prone to imperfection due to the technical limitations of sensors, their availability, dysfunction, and the highly dynamic nature of environment. Consequently, sensed context data might be imprecise, erroneous, conflicting, or simply missing. To limit the impact of context imperfection on the behavior of a context-aware system, a notion of Quality of Context (QoC) is used to measure quality of any information that is used as context information. Adaptation is performed only if the context data used in the decision-making has an appropriate quality level. This thesis conducts a novel framework for QoC in context-aware systems, which is called MCFQoC (Multilayered-Context Framework for Quality of Context). The main innovative features of our framework, MCFQoC, include: (1) a new definition that generalizes the notion of QoC to encompass sensed context as well as user profiled context; (2) a novel multilayer context model, that distinguishes between three context abstractions: context situation, context object, and context element in descending order. A context element represents a single value and many context elements can be compound into a context object. Many context objects in turn form a context situation; (3) a novel model of QoC parameters which extends the existing parameters with new quality parameter and explicitly distributes the quality parameters across the three layers of context abstraction; (4) a novel algorithm, RCCAR (Resolving Context Conflicts Using Association Rules), which has been developed to resolve conflicts in context data using the Association Rules (AR) technique; (5) a novel mechanism to define QoC policy by assigning weights to QoC parameters using a multi-criteria decision-making technique called Analytical Hierarchy Process (AHP); (6) and finally, a novel quality control algorithm called IPQP (Integrating Prediction with Quality of context Parameters for Context Quality Control) for handling context conflicts, context missing values, and context erroneous values. IPQP is extension of RCCAR. Our framework, MCFQoC, has been implemented in MatLab and evaluated using a case study of a flood forecast system. Results show that the framework is expressive and modular, thanks to the multilayer context model and also to the notion QoC policy which enables us to assign weights for QoC’s parameters depending on quality requirements of each specific application. This flexibility makes it easy to apply our approach to a wider type of context-aware applications. As a part of MCFQoC framework, IPQP algorithm has been successfully tested and evaluated for QoC control using a variety of scenarios. The algorithm RCCAR has been tested and evaluated either individually and as a part of MCFQoC framework with a significant performance concerning resolving context conflicts. In addition, RCCAR has achieved a good success comparing to traditional prediction methods such as moving average (MA), weighted moving average, exponential smoothing, doubled exponential smoothing, and autoregressive moving average (ARMA).

The study takes servant-leadership and attempts to find if there is an equivalent concept in management. Leadership and management have been extensively compared and contrasted in research and theory and while there are divergent views of exactly what each entails, others hold the view that they might be equal and complementary. The research design follows a positivist philosophy. An instrument that measures distinct leader, manager and professional role preferences is used to check the discrete operation of three contexts among a sample of members of the accountancy profession. The instrument is derived from contextualising pre-developed and pre-tested servant-leadership measuring instruments. Items from the role preference map instrument are added together with demographic details to come up with a meta-instrument adapted for the study. After validating it through pilot-testing, the instrument is applied in real-world research. The research was conducted among a sample of professional accountants working in 28 countries across four continents in organisations with over 82,000 employees. Statistical analysis, employing; analysis of variance, correlations, frequencies, significances, means, variances and tests of scale reliability was performed on both the data and the instruments. The research found clear and reliable servant-leadership-type behaviours exhibited across the three discreet roles and contexts of leader, manager and professional. Some professional accountancy courses are delivered across many countries in the world. The Association of Chartered Certified Accountants (ACCA) is one such professional accountancy body that offers qualifications on a global scale. However, as accountants originate from, and practice in diverse cultures and economies around the world they are trained by institutes like ACCA from a common syllabus that has elements of management as a subject. Servant-leadership is a type of leadership that is theorised to be humanistic and spiritual rather than rational and mechanistic. Management practice on the other hand needs rationality and contains some mechanistic elements in typical management functions like coordinating and controlling. The implication is whether servant-leadership attributes can be exhibited if professional accountants contextualise themselves as leaders, managers or professionals. The study focuses on the profession of accountants and tests the operation of servant-leadership behaviours from the manager, leader and professional contexts using pre-tested servant-leadership scales and applying them in specific leader and manager contexts. This approach is new in its treatment of servant-leadership in this fashion. A further original approach is the use of the accountancy profession. This treatment of instruments from other fields like psychology and sociology is new.

This presentation was given at the 2011 Open Access Week program, “The Future of Data: Open Access and Reproducibility” on October 25, 2011. Open Access Week is a world-wide event where academic institutions explore Open Access – the ideal of free, full-text, immediate, online access to peer-reviewed scholarship and research results so new ideas and information can be obtained rapidly and freely by everyone. Open Data is the idea that data should be freely available to anyone to use and reuse without access restrictions, licenses, copyright, patents and charges for use.