8,475 research outputs found

    Business process model customisation using domain-driven controlled variability management and rule generation

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    Business process models are abstract descriptions and as such should be applicable in different situations. In order for a single process model to be reused, we need support for configuration and customisation. Often, process objects and activities are domain-specific. We use this observation and allow domain models to drive the customisation. Process variability models, known from product line modelling and manufacturing, can control this customisation by taking into account the domain models. While activities and objects have already been studied, we investigate here the constraints that govern a process execution. In order to integrate these constraints into a process model, we use a rule-based constraints language for a workflow and process model. A modelling framework will be presented as a development approach for customised rules through a feature model. Our use case is content processing, represented by an abstract ontology-based domain model in the framework and implemented by a customisation engine. The key contribution is a conceptual definition of a domain-specific rule variability language

    Business process model customisation using domain-driven controlled variability management and rule generation

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    Business process models are abstract descriptions and as such should be applicable in different situations. In order for a single process model to be reused, we need support for configuration and customisation. Often, process objects and activities are domain-specific. We use this observation and allow domain models to drive the customisation. Process variability models, known from product line modelling and manufacturing, can control this customisation by taking into account the domain models. While activities and objects have already been studied, we investigate here the constraints that govern a process execution. In order to integrate these constraints into a process model, we use a rule-based constraints language for a workflow and process model. A modelling framework will be presented as a development approach for customised rules through a feature model. Our use case is content processing, represented by an abstract ontology-based domain model in the framework and implemented by a customisation engine. The key contribution is a conceptual definition of a domain-specific rule variability language

    Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

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    In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation and development of CNNs, several software frameworks have been released, primarily targeting power-hungry CPUs and GPUs. In this context, reconfigurable hardware in the form of FPGAs constitutes a potential alternative platform that can be integrated in the existing deep learning ecosystem to provide a tunable balance between performance, power consumption and programmability. In this paper, a survey of the existing CNN-to-FPGA toolflows is presented, comprising a comparative study of their key characteristics which include the supported applications, architectural choices, design space exploration methods and achieved performance. Moreover, major challenges and objectives introduced by the latest trends in CNN algorithmic research are identified and presented. Finally, a uniform evaluation methodology is proposed, aiming at the comprehensive, complete and in-depth evaluation of CNN-to-FPGA toolflows.Comment: Accepted for publication at the ACM Computing Surveys (CSUR) journal, 201

    Digital Repositories in Private Clouds

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    This study explores the use of digital repositories in private cloud environments. Private cloud computing is a cloud computing deployment model where compute and storage infrastructure are hosted on-premise by institutions. Digital repositories are used to manage institutions’ generated content. The advancement in cloud computing, the promise of elasticity, and the on-demand resource provisioning features of cloud systems are attractive characteristics that institutions can leverage on in delivering digital content to their audiences. In this study, a cloud computing operating system is deployed, and a means to install, monitor, manage and customise a repository system is developed. The repository system used is DSpace. Eucalyptus cloud software was used to setup a private cloud environment. A prototype application was developed to manage the installation and customisation of DSpace in the cloud environment. The prototype also included a feature to monitor the status of the running DSpace instances. To evaluate the efficiency, installation and customisation of DSpace in the cloud environment, two types of evaluations were carried out – a performance evaluation and a usability study. The performance evaluation was used to ascertain how long it takes to ingest and view items in DSpace. The experiments were carried out with varying numbers of running virtual machine instances in the cloud. The usability study evaluated the ease of installing and customising DSpace with the developed tool, called Lilu. A total of 22 participants took part in the usability study that was carried out within the premises of the University of Cape Town’s Computer Science Department. The participants belonged to 3 groups – experts, intermediate and beginners – based on their technical skill levels. The results show that private cloud environments can run institutional repositories with negligible performance degradation as the number of virtual machine instances in the cloud are increased. From the usability study, the tool developed was positively perceived. Participants in the study were able to install and customise DSpace. Institutional repositories can efficiently be installed and used in private cloud environments. Building tools that enable users to create single-click installations of the repositories, and creating user friendly interfaces to customise repositories would potentially increase the adoption and utilisation of private cloud environments by institutions

    Personalised Learning: Developing a Vygotskian Framework for E-learning

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    Personalisation has emerged as a central feature of recent educational strategies in the UK and abroad. At the heart of this is a vision to empower learners to take more ownership of their learning and develop autonomy. While the introduction of digital technologies is not enough to effect this change, embedding the affordances of new technologies is expected to offer new routes for creating personalised learning environments. The approach is not unique to education, with consumer technologies offering a 'personalised' relationship which is both engaging and dynamic, however the challenge remains for learning providers to capture and transpose this to educational contexts. As learners begin to utilise a range of tools to pursue communicative and collaborative actions, the first part of this paper will use analysis of activity logs to uncover interesting trends for maturing e-learning platforms across over 100 UK learning providers. While personalisation appeals to marketing theories this paper will argue that if learning is to become personalised one must ask what the optimal instruction for any particular learner is? For Vygotsky this is based in the zone of proximal development, a way of understanding the causal-dynamics of development that allow appropriate pedagogical interventions. The second part of this paper will interpret personalised learning as the organising principle for a sense-making framework for e-learning. In this approach personalised learning provides the context for assessing the capabilities of e-learning using Vygotsky’s zone of proximal development as the framework for assessing learner potential and development

    Learning objects and learning designs: an integrated system for reusable, adaptive and shareable learning content

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    This paper proposes a system, the Smart Learning Design Framework, designed to support the development of pedagogically sound learning material within an integrated, platform-independent data structure. The system supports sharing, reuse and adaptation of learning material via a metadata-driven philosophy that enables the technicalities of the system to be imperceptible to the author and consumer. The system proposes the use of pedagogically focused metadata to support and guide the author and to adapt and deliver the content to the targeted consumer. A prototype of the proposed system, which provides proof of concept for the novel processes involved, has been developed. The paper describes the Smart Learning Design Framework and places it within the context of alternative learning object models and frameworks to highlight similarities, differences and advantages of the proposed system

    Empirical modelling principles to support learning in a cultural context

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    Much research on pedagogy stresses the need for a broad perspective on learning. Such a perspective might take account (for instance) of the experience that informs knowledge and understanding [Tur91], the situation in which the learning activity takes place [Lav88], and the influence of multiple intelligences [Gar83]. Educational technology appears to hold great promise in this connection. Computer-related technologies such as new media, the internet, virtual reality and brain-mediated communication afford access to a range of learning resources that grows ever wider in its scope and supports ever more sophisticated interactions. Whether educational technology is fulfilling its potential in broadening the horizons for learning activity is more controversial. Though some see the successful development of radically new educational resources as merely a matter of time, investment and engineering, there are also many critics of the trends in computer-based learning who see little evidence of the greater degree of human engagement to which new technologies aspire [Tal95]. This paper reviews the potential application to educational technology of principles and tools for computer-based modelling that have been developed under the auspices of the Empirical Modelling (EM) project at Warwick [EMweb]. This theme was first addressed at length in a previous paper [Bey97], and is here revisited in the light of new practical developments in EM both in respect of tools and of model-building that has been targetted at education at various levels. Our central thesis is that the problems of educational technology stem from the limitations of current conceptual frameworks and tool support for the essential cognitive model building activity, and that tackling these problems requires a radical shift in philosophical perspective on the nature and role of empirical knowledge that has significant practical implications. The paper is in two main sections. The first discusses the limitations of the classical computer science perspective where educational technology to support situated learning is concerned, and relates the learning activities that are most closely associated with a cultural context to the empiricist perspective on learning introduced in [Bey97]. The second outlines the principles of EM and describes and illustrates features of its practical application that are particularly well-suited to learning in a cultural setting

    Strategic Roadmaps and Implementation Actions for ICT in Construction

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