An application framework for the systematic construction of multimedia-based Collaborative Complex Learning Resources

Aquest treball de tesi proposa aportar una infraestructura de programari per donar suport a nous tipus de metodologies i recursos d'aprenentatge col·laboratiu augmentats pedagògicament i a través d'una plataforma d'aplicació innovadora anomenada Plataforma de Virtualització de Sessions Col·laboratives (VCSF de l'angles Virtualized Collaborative Sessions Framework). El VCSF ajuda a satisfer els requisits pedagògics exigents de l'aprenentatge col·laboratiu en línia d’avui en dia, com ara augmentar la participació de l'estudiant i millorar el rendiment de l'aprenentatge durant la col·laboració. Al seu torn, l'aplicació sistemàtica de la plataforma VCSF, enriquida amb tecnologies semàntiques, permet als desenvolupadors d'e-learning aprofitar experiències d'aprenentatge col·laboratiu prèvies a través de la reutilització de programari, estalviant temps de desenvolupament i esforç. La plataforma ha sigut prototipada i provada amb èxit en entorns reals, el que demostra la capacitat de reutilització del programari i els beneficis pedagògics de l'enfocament VCSF.Este trabajo de tesis propone aportar una infraestructura de software para apoyar a nuevos tipos de metodologías y recursos de aprendizaje colaborativo aumentados pedagógicamente ya través de una plataforma de aplicación innovadora llamada Plataforma de Virtualización de Sesiones Colaborativa (VCSF del inglés Virtualized Collaborative Sessions Framework). El VCSF ayuda a satisfacer los requisitos pedagógicos exigentes del aprendizaje colaborativo en línea de hoy en día, tales como aumentar la participación del estudiante y mejorar el rendimiento del aprendizaje durante la colaboración. A su vez, la aplicación sistemática de la plataforma VCSF, enriquecida con tecnologías semánticas, permite a los desarrolladores de e-learning aprovechar experiencias de aprendizaje colaborativo previas a través de la reutilización de software, ahorrando tiempo de desarrollo y esfuerzo. La plataforma ha sido prototipada y probada con éxito en entornos reales, lo que demuestra la capacidad de reutilización del software y los beneficios pedagógicos del enfoque VCSF.This thesis project aims to provide a software infrastructure to support new types of pedagogically augmented collaborative learning methodologies and resources by means of an innovative application framework called Virtualized Collaborative Sessions Framework (VCSF). The VCSF helps meet challenging pedagogical requirements in online collaborative learning, such as increasing students' engagement and learning performance during the collaboration. In turn, the systematic application of the VCSF platform, enriched with semantic technologies, enables e-learning developers to leverage successful collaborative learning experiences through software reuse, saving in both development time and effort. The framework has been prototyped and successfully tested in real environments, thus showing the software reuse capability and the pedagogical benefits of the VCSF approach

Security Enhanced Applications for Information Systems

Every day, more users access services and electronically transmit information which is usually disseminated over insecure networks and processed by websites and databases, which lack proper security protection mechanisms and tools. This may have an impact on both the users’ trust as well as the reputation of the system’s stakeholders. Designing and implementing security enhanced systems is of vital importance. Therefore, this book aims to present a number of innovative security enhanced applications. It is titled “Security Enhanced Applications for Information Systems” and includes 11 chapters. This book is a quality guide for teaching purposes as well as for young researchers since it presents leading innovative contributions on security enhanced applications on various Information Systems. It involves cases based on the standalone, network and Cloud environments

Adaptive intelligent personalised learning (AIPL) environment

As individuals the ideal learning scenario would be a learning environment tailored just for how we like to learn, personalised to our requirements. This has previously been almost inconceivable given the complexities of learning, the constraints within the environments in which we teach, and the need for global repositories of knowledge to facilitate this process. Whilst it is still not necessarily achievable in its full sense this research project represents a path towards this ideal.In this thesis, findings from research into the development of a model (the Adaptive Intelligent Personalised Learning (AIPL)), the creation of a prototype implementation of a system designed around this model (the AIPL environment) and the construction of a suite of intelligent algorithms (Personalised Adaptive Filtering System (PAFS)) for personalised learning are presented and evaluated. A mixed methods approach is used in the evaluation of the AIPL environment. The AIPL model is built on the premise of an ideal system being one which does not just consider the individual but also considers groupings of likeminded individuals and their power to influence learner choice. The results show that: (1) There is a positive correlation for using group-learning-paradigms. (2) Using personalisation as a learning aid can help to facilitate individual learning and encourage learning on-line. (3) Using learning styles as a way of identifying and categorising the individuals can improve their on-line learning experience. (4) Using Adaptive Information Retrieval techniques linked to group-learning-paradigms can reduce and improve the problem of mis-matching. A number of approaches for further work to extend and expand upon the work presented are highlighted at the end of the Thesis

Collaborative Knowledge Visualisation for Cross-Community Knowledge Exchange

The notion of communities as informal social networks based on shared interests or common practices has been increasingly used as an important unit of analysis when considering the processes of cooperative creation and sharing of knowledge. While knowledge exchange within communities has been extensively researched, different studies observed the importance of cross-community knowledge exchange for the creation of new knowledge and innovation in knowledge-intensive organizations. Especially in knowledge management a critical problem has become the need to support the cooperation and exchange of knowledge between different communities with highly specialized expertise and activities. Though several studies discuss the importance and difficulties of knowledge sharing across community boundaries, the development of technological support incorporating these findings has been little addressed. This work presents an approach to supporting cross-community knowledge exchange based on using knowledge visualisation for facilitating information access in unfamiliar community domains. The theoretical grounding and practical relevance of the proposed approach are ensured by defining a requirements model that integrates theoretical frameworks for cross-community knowledge exchange with practical needs of typical knowledge management processes and sensemaking tasks in information access in unfamiliar domains. This synthesis suggests that visualising knowledge structures of communities and supporting the discovery of relationships between them during access to community spaces, could provide valuable support for cross-community discovery and sharing of knowledge. This is the main hypothesis investigated in this thesis. Accordingly, a novel method is developed for eliciting and visualising implicit knowledge structures of individuals and communities in form of dynamic knowledge maps that make the elicited knowledge usable for semantic exploration and navigation of community spaces. The method allows unobtrusive construction of personal and community knowledge maps based on user interaction with information and their use for dynamic classification of information from a specific point of view. The visualisation model combines Document Maps presenting main topics, document clusters and relationships between knowledge reflected in community spaces with Concept Maps visualising personal and shared conceptual structures of community members. The technical realization integrates Kohonen’s self-organizing maps with extraction of word categories from texts, collaborative indexing and personalised classification based on user-induced templates. This is accompanied by intuitive visualisation and interaction with complex information spaces based on multi-view navigation of document landscapes and concept networks. The developed method is prototypically implemented in form of an application framework, a concrete system and a visual information interface for multi-perspective access to community information spaces, the Knowledge Explorer. The application framework implements services for generating and using personal and community knowledge maps to support explicit and implicit knowledge exchange between members of different communities. The Knowledge Explorer allows simultaneous visualisation of different personal and community knowledge structures and enables their use for structuring, exploring and navigating community information spaces from different points of view. The empirical evaluation in a comparative laboratory study confirms the adequacy of the developed solutions with respect to specific requirements of the cross-community problem and demonstrates much better quality of knowledge access compared to a standard information seeking reference system. The developed evaluation framework and operative measures for quality of knowledge access in cross-community contexts also provide a theoretically grounded and practically feasible method for further developing and evaluating new solutions addressing this important but little investigated problem

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR