Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale

Implementation of a data virtualization layer applied to insurance data

This work focuses on the introduction of a data virtualization layer to read and consolidate data from heterogeneous sources (Hadoop system, a data mart and a data warehouse) and provide a single point of data access to all data consumers

A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS

In service-oriented environments, services are put together in the form of a workflow with the aim of distributed problem solving. Capturing the execution details of the services' transformations is a significant advantage of using workflows. These execution details, referred to as provenance information, are usually traced automatically and stored in provenance stores. Provenance data contains the data recorded by a workflow engine during a workflow execution. It identifies what data is passed between services, which services are involved, and how results are eventually generated for particular sets of input values. Provenance information is of great importance and has found its way through areas in computer science such as: Bioinformatics, database, social, sensor networks, etc. Current exploitation and application of provenance data is very limited as provenance systems started being developed for specific applications. Thus, applying learning and knowledge discovery methods to provenance data can provide rich and useful information on workflows and services. Therefore, in this work, the challenges with workflows and services are studied to discover the possibilities and benefits of providing solutions by using provenance data. A multifunctional architecture is presented which addresses the workflow and service issues by exploiting provenance data. These challenges include workflow composition, abstract workflow selection, refinement, evaluation, and graph model extraction. The specific contribution of the proposed architecture is its novelty in providing a basis for taking advantage of the previous execution details of services and workflows along with artificial intelligence and knowledge management techniques to resolve the major challenges regarding workflows. The presented architecture is application-independent and could be deployed in any area. The requirements for such an architecture along with its building components are discussed. Furthermore, the responsibility of the components, related works and the implementation details of the architecture along with each component are presented

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

Narrative Threads: supporting young people in developing writing skills through narrative-based game creation

This thesis examines how narrative-based game creation can be used as an activity to improve writing skills for young people aged 11-15, and how additional representational support in a game creation tool can increase the benefits of the activity. Creating narrative-based games can involve traditional writing skills as well as requiring the 21st century skills of multimodal and interactive writing. Toolsets make it possible for young people to create 3D role-playing games with a commercial look and feel, but they do not provide support for the complex task of interactive and multimodal narrative creation. To investigate the desirable features of a tool that would support this task and the associated learning, an extensive learner-centred design process was conducted. This involved teachers and young people, and also incorporated relevant theory synthesised into a design model. A suite of tools, Narrative Threads, was designed and developed through an iterative process to provide the support highlighted as important. Two evaluative studies were conducted in different learning contexts; a secondary school and a vacation workshop. A mixed-methods approach was used to examine the overall potential for the activity to support writing skills development and the impact made by additional representational support. Comparative studies between groups showed some evidence that writing skills were improved for those taking part in game creation, and there were further benefits for groups using Narrative Threads in the workshop setting, but not in the school setting. Additionally, a multimodal analysis of the games created showed that many participants demonstrated a developing proficiency in using 3D graphical elements, text and sound to convey an interactive narrative. The findings indicate promise for the approach, although additional curricular and pedagogical support would be crucial if the potential is to be actualised in a classroom context

Requirement validation with enactable descriptions of use cases.

The validation of stakeholder requirements for a software system is a pivotal activity for any nontrivial software development project. Often, differences in knowledge regarding development issues, and knowledge regarding the problem domain, impede the elaboration of requirements amongst developers and stakeholders. A description technique that provides a user perspective of the system behaviour is likely to enhance shared understanding between the developers and stakeholders. The Unified Modelling Language (UML) use case is such a notation. Use cases describe the behaviour of a system (using natural language) in terms of interactions between the external users and the system. Since the standardisation of the UML by the Object Management Group in 1997, much research has been devoted to use cases. Some researchers have focussed on the provision of writing guidelines for use case specifications whereas others have focussed on the application of formal techniques. This thesis investigates the adequacy of the use case description for the specification and validation of software behaviour. In particular, the thesis argues that whereas the user-system interaction scheme underpins the essence of the use case notation, the UML specification of the use case does not provide a mechanism by which use cases can describe dependencies amongst constituent interaction steps. Clarifying these issues is crucial for validating the adequacy of the specification against stakeholder expectations. This thesis proposes a state-based approach (the Educator approach) to use case specification where constituent events are augmented with pre and post states to express both intra-use case and inter-use case dependencies. Use case events are enacted to visualise implied behaviour, thereby enhancing shared understanding among users and developers. Moreover, enaction provides an early "feel" of the behaviour that would result from the implementation of the specification. The Educator approach and the enaction of descriptions are supported by a prototype environment, the EducatorTool, developed to demonstrate the efficacy and novelty of the approach. To validate the work presented in this thesis an industrial study, involving the specification of realtime control software, is reported. The study involves the analysis of use case specifications of the subsystems prior to the application of the proposed approach, and the analysis of the specification where the approach and tool support are applied. This way, it is possible to determine the efficacy of the Educator approach within an industrial setting

Augmented Language Models: a Survey

This survey reviews works in which language models (LMs) are augmented with reasoning skills and the ability to use tools. The former is defined as decomposing a potentially complex task into simpler subtasks while the latter consists in calling external modules such as a code interpreter. LMs can leverage these augmentations separately or in combination via heuristics, or learn to do so from demonstrations. While adhering to a standard missing tokens prediction objective, such augmented LMs can use various, possibly non-parametric external modules to expand their context processing ability, thus departing from the pure language modeling paradigm. We therefore refer to them as Augmented Language Models (ALMs). The missing token objective allows ALMs to learn to reason, use tools, and even act, while still performing standard natural language tasks and even outperforming most regular LMs on several benchmarks. In this work, after reviewing current advance in ALMs, we conclude that this new research direction has the potential to address common limitations of traditional LMs such as interpretability, consistency, and scalability issues

Semi-Automation in Video Editing

Semi-automasjon i video redigering Hvordan kan vi bruke kunstig intelligens (KI) og maskin læring til å gjøre videoredigering like enkelt som å redigere tekst? I denne avhandlingen vil jeg adressere problemet med å bruke KI i videoredigering fra et Menneskelig-KI interaksjons perspektiv, med fokus på å bruke KI til å støtte brukerne. Video er et audiovisuelt medium. Redigere videoer krever synkronisering av både det visuelle og det auditive med presise operasjoner helt ned på millisekund nivå. Å gjøre dette like enkelt som å redigere tekst er kanskje ikke mulig i dag. Men hvordan skal vi da støtte brukerne med KI og hva er utfordringene med å gjøre det? Det er fem hovedspørsmål som har drevet forskningen i denne avhandlingen. Hva er dagens "state-of-the-art" i KI støttet videoredigering? Hva er behovene og forventningene av fagfolkene om KI? Hva er påvirkningen KI har på effektiviteten og nøyaktigheten når det blir brukt på teksting? Hva er endringene i brukeropplevelsen når det blir brukt KI støttet teksting? Hvordan kan flere KI metoder bli brukt for å støtte beskjærings- og panoreringsoppgaver? Den første artikkelen av denne avhandlingen ga en syntese og kritisk gjennomgang av eksisterende arbeid med KI-baserte verktøy for videoredigering. Artikkelen ga også noen svar på hvordan og hva KI kan bli brukt til for å støtte brukere ved en undersøkelse utført av 14 fagfolk. Den andre studien presenterte en prototype av KI-støttet videoredigerings verktøy bygget på et eksisterende videoproduksjons program. I tillegg kom det en evaluasjon av både ytelse og brukeropplevelse på en KI-støttet teksting fra 24 nybegynnere. Den tredje studien beskrev et idiom-basert verktøy for å konvertere bredskjermsvideoer lagd for TV til smalere størrelsesforhold for mobil og sosiale medieplattformer. Den tredje studien utforsker også nye metoder for å utøve beskjæring og panorering ved å bruke fem forskjellige KI-modeller. Det ble også presentert en evaluering fra fem brukere. I denne avhandlingen brukte vi en brukeropplevelse og oppgave basert framgangsmåte, for å adressere det semi-automatiske i videoredigering.How can we use artificial intelligence (AI) and machine learning (ML) to make video editing as easy as "editing text''? In this thesis, this problem of using AI to support video editing is explored from the human--AI interaction perspective, with the emphasis on using AI to support users. Video is a dual-track medium with audio and visual tracks. Editing videos requires synchronization of these two tracks and precise operations at milliseconds. Making it as easy as editing text might not be currently possible. Then how should we support the users with AI, and what are the current challenges in doing so? There are five key questions that drove the research in this thesis. What is the start of the art in using AI to support video editing? What are the needs and expectations of video professionals from AI? What are the impacts on efficiency and accuracy of subtitles when AI is used to support subtitling? What are the changes in user experience brought on by AI-assisted subtitling? How can multiple AI methods be used to support cropping and panning task? In this thesis, we employed a user experience focused and task-based approach to address the semi-automation in video editing. The first paper of this thesis provided a synthesis and critical review of the existing work on AI-based tools for videos editing and provided some answers to how should and what more AI can be used in supporting users by a survey of 14 video professional. The second paper presented a prototype of AI-assisted subtitling built on a production grade video editing software. It is the first comparative evaluation of both performance and user experience of AI-assisted subtitling with 24 novice users. The third work described an idiom-based tool for converting wide screen videos made for television to narrower aspect ratios for mobile social media platforms. It explores a new method to perform cropping and panning using five AI models, and an evaluation with 5 users and a review with a professional video editor were presented.Doktorgradsavhandlin