354 research outputs found

    An Integrated Semantic Web Service Discovery and Composition Framework

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    In this paper we present a theoretical analysis of graph-based service composition in terms of its dependency with service discovery. Driven by this analysis we define a composition framework by means of integration with fine-grained I/O service discovery that enables the generation of a graph-based composition which contains the set of services that are semantically relevant for an input-output request. The proposed framework also includes an optimal composition search algorithm to extract the best composition from the graph minimising the length and the number of services, and different graph optimisations to improve the scalability of the system. A practical implementation used for the empirical analysis is also provided. This analysis proves the scalability and flexibility of our proposal and provides insights on how integrated composition systems can be designed in order to achieve good performance in real scenarios for the Web.Comment: Accepted to appear in IEEE Transactions on Services Computing 201

    Temporal meta-model framework for Enterprise Information Systems (EIS) development

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    This thesis has developed a Temporal Meta-Model Framework for semi-automated Enterprise System Development, which can help drastically reduce the time and cost to develop, deploy and maintain Enterprise Information Systems throughout their lifecycle. It proposes that the analysis and requirements gathering can also perform the bulk of the design phase, stored and available in a suitable model which would then be capable of automated execution with the availability of a set of specific runtime components

    On supporting K-anonymisation and L-diversity of crime databases with genetic algorithms in a resource constrained environment

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    The social benefits derived from analysing crime data need to be weighed against issues relating to privacy loss. To facilitate such analysis of crime data Burke and Kayem [7] proposed a framework (MCRF) to enable mobile crime reporting in a developing country. Here crimes are reported via mobile phones and stored in a database owned by a law enforcement agency. The expertise required to perform analysis on the crime data is however unlikely to be available within the law enforcement agency. Burke and Kayem [7] proposed anonymising the data(using manual input parameters) at the law enforcement agency before sending it to a third party for analysis. Whilst analysis of the crime data requires expertise, adequate skill to appropriately anonymise the data is also required. What is lacking in the original MCRF is therefore an automated scheme for the law enforcement agency to adequately anonymise the data before sending it to the third party. This should, however, be done whilst maximising information utility of the anonymised data from the perspective of the third party. In this thesis we introduce a crime severity scale to facilitate the automation of data anonymisation within the MCRF. We consider a modified loss metric to capture information loss incurred during the anonymisation process. This modified loss metric also gives third party users the flexibility to specify attributes of the anonymised data when requesting data from the law enforcement agency. We employ a genetic algorithm(GA) approach called "Crime Genes"(CG) to optimise utility of the anonymised data based on our modified loss metric whilst adhering to notions of privacy denned by k-anonymity and l-diversity. Our CG implementation is modular and can therefore be easily integrated with the original MCRF. We also show how our CG approach is designed to be suitable for implementation in a developing country where particular resource constraints exist

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Evaluating FAIR Digital Object and Linked Data as distributed object systems

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    FAIR Digital Object (FDO) is an emerging concept that is highlighted by European Open Science Cloud (EOSC) as a potential candidate for building a ecosystem of machine-actionable research outputs. In this work we systematically evaluate FDO and its implementations as a global distributed object system, by using five different conceptual frameworks that cover interoperability, middleware, FAIR principles, EOSC requirements and FDO guidelines themself. We compare the FDO approach with established Linked Data practices and the existing Web architecture, and provide a brief history of the Semantic Web while discussing why these technologies may have been difficult to adopt for FDO purposes. We conclude with recommendations for both Linked Data and FDO communities to further their adaptation and alignment.Comment: 40 pages, submitted to PeerJ C

    Quality of experience in affective pervasive environments

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    The confluence of miniaturised powerful devices, widespread communication networks and mass remote storage has caused a fundamental shift in the user interaction design paradigm. The distinction between system and user in pervasive environments is evolving into an increasingly integrated loop of interaction, raising a number of opportunities to provide enhanced and personalised experiences. We propose a platform, based on a smart architecture, to address the identified opportunities in pervasive computing. Smart systems aim at acting upon an environment for improving quality of experience: a subjective measure that has been defined as an emotional reaction to products or services. The inclusion of an emotional dimension allows us to measure individual user responses and deliver personalised services with the potential to influence experiences positively. The platform, Cloud2Bubble, leverages pervasive systems to aggregate user and environment data with the goal of addressing personal preferences and supra-functional requirements. This, combined with its societal implications, results in a set of design principles as a concrete fruition of design contractualism. In particular, this thesis describes: - a review of intelligent ubiquitous environments and relevant technologies, including a definition of user experience as a dynamic affective construct; - a specification of main components for personal data aggregation and service personalisation, without compromising privacy, security or usability; - the implementation of a software platform and a methodological procedure for its instantiation; - an evaluation of the developed platform and its benefits for urban mobility and public transport information systems; - a set of design principles for the design of ubiquitous systems, with an impact on individual experience and collective awareness. Cloud2Bubble contributes towards the development of affective intelligent ubiquitous systems with the potential to enhance user experience in pervasive environments. In addition, the platform aims at minimising the risk of user digital exposure while supporting collective action.Open Acces

    Hybrid Query Answering Over OWL Ontologies

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    Abstract. Query answering over OWL 2 DL ontologies is an important reasoning task for many modern applications. Unfortunately, due to its high computational complexity, OWL 2 DL systems are still not able to cope with datasets containing billions of data. Consequently, application developers often employ provably scalable systems which only support a fragment of OWL 2 DL and which are, hence, most likely incomplete for the given input. However, this notion of completeness is too coarse since it implies that there exists some query and some dataset for which these systems would miss answers. Nevertheless, there might still be a large number of user queries for which they can compute all the right answers even over OWL 2 DL ontologies. In the current paper, we investigate whether, given a query Q with only distinguished variables over an OWL 2 DL ontology T and a system ans, it is possible to identify in an efficient way if ans is complete for Q, T and every dataset. We give sufficient conditions for (in)completeness and present a hybrid query answering algorithm which uses ans when it is complete, otherwise it falls back to a fully-fledged OWL 2 DL reasoner. However, even in the latter case, our algorithm still exploits ans as much as possible in order to reduce the search space of the OWL 2 DL reasoner. Finally, we have implemented our approach using a concrete system ans and OWL 2 DL reasoner obtaining encouraging results.

    Virtual Reality Games for Motor Rehabilitation

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    This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

    A Peer-to-Peer Network Framework Utilising the Public Mobile Telephone Network

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    P2P (Peer-to-Peer) technologies are well established and have now become accepted as a mainstream networking approach. However, the explosion of participating users has not been replicated within the mobile networking domain. Until recently the lack of suitable hardware and wireless network infrastructure to support P2P activities was perceived as contributing to the problem. This has changed with ready availability of handsets having ample processing resources utilising an almost ubiquitous mobile telephone network. Coupled with this has been a proliferation of software applications written for the more capable `smartphone' handsets. P2P systems have not naturally integrated and evolved into the mobile telephone ecosystem in a way that `client-server' operating techniques have. However as the number of clients for a particular mobile application increase, providing the `server side' data storage infrastructure becomes more onerous. P2P systems offer mobile telephone applications a way to circumvent this data storage issue by dispersing it across a network of the participating users handsets. The main goal of this work was to produce a P2P Application Framework that supports developers in creating mobile telephone applications that use distributed storage. Effort was assigned to determining appropriate design requirements for a mobile handset based P2P system. Some of these requirements are related to the limitations of the host hardware, such as power consumption. Others relate to the network upon which the handsets operate, such as connectivity. The thesis reviews current P2P technologies to assess which was viable to form the technology foundations for the framework. The aim was not to re-invent a P2P system design, rather to adopt an existing one for mobile operation. Built upon the foundations of a prototype application, the P2P framework resulting from modifications and enhancements grants access via a simple API (Applications Programmer Interface) to a subset of Nokia `smartphone' devices. Unhindered operation across all mobile telephone networks is possible through a proprietary application implementing NAT (Network Address Translation) traversal techniques. Recognising that handsets operate with limited resources, further optimisation of the P2P framework was also investigated. Energy consumption was a parameter chosen for further examination because of its impact on handset participation time. This work has proven that operating applications in conjunction with a P2P data storage framework, connected via the mobile telephone network, is technically feasible. It also shows that opportunity remains for further research to realise the full potential of this data storage technique
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