224,356 research outputs found

    Consistency analysis in multi-language knowledge sharing system

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    Unprecedented growth in knowledge sharing among multi-language communities, both common and distinct languages, has raised the possibility of sharing inconsistent content. Though popular with traditional system, the approach to explicitly state consistency rules to avoid inconsistency is practically not suited for multi-language knowledge sharing system because of sheer complexity. Alternatively this chapter focuses on potential cause of inconsistency, cases such as content omitted, content updates not propagated and content conflicts. Ignoring such cases in knowledge sharing has undesirable consequences: community bias, global and local inconsistency and regional discrepancies. Consistency constraints from opposing knowledge sharing goals among communities is another issue. Due to which consistency policy ranges from rigid ‘one to one consistency’ to non-rigid ‘consistency where needed’. This chapter contributes with (a) process-based approach for multilingual content synchronization to leverage knowledge equally and (b) propagation-based approach to analyze community preferences when sharing specific content categories/geographic regions, to customize knowledge sharing; a value add-on to designing language services adhering to knowledge sharing goals. © 2018, Springer Nature Singapore Pte Ltd

    A Semantic Collaboration Method Based on Uniform Knowledge Graph

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    The Semantic Internet of Things is the extension of the Internet of Things and the Semantic Web, which aims to build an interoperable collaborative system to solve the heterogeneous problems in the Internet of Things. However, the Semantic Internet of Things has the characteristics of both the Internet of Things and the Semantic Web environment, and the corresponding semantic data presents many new data features. In this study, we analyze the characteristics of semantic data and propose the concept of a uniform knowledge graph, allowing us to be applied to the environment of the Semantic Internet of Things better. Here, we design a semantic collaboration method based on a uniform knowledge graph. It can take the uniform knowledge graph as the form of knowledge organization and representation, and provide a useful data basis for semantic collaboration by constructing semantic links to complete semantic relation between different data sets, to achieve the semantic collaboration in the Semantic Internet of Things. Our experiments show that the proposed method can analyze and understand the semantics of user requirements better and provide more satisfactory outcomes

    Special educational needs and disability : Understanding local variation in prevalence, service provision and support

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    There is a growing recognition of the variation between local authorities in the proportions of children with SEN, the apparent composition of these groups, and the nature and quality of services provided to support them. Local area data collected on children with SEN, particularly the termly School Census and the annual SEN2 return by local authorities, show differences in the number of children with SEN, the nature of their recorded conditions and the Code of Practice level of support they are receiving. This variation was highlighted by the House of Commons Education and Skills Select Committee which commented on a ‘postcode lottery’ or a ‘lottery of provision’, and reports by the Audit Commission and Ofsted which also highlighted variation in provision and standards

    Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

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    Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

    A Concurrent Language with a Uniform Treatment of Regions and Locks

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    A challenge for programming language research is to design and implement multi-threaded low-level languages providing static guarantees for memory safety and freedom from data races. Towards this goal, we present a concurrent language employing safe region-based memory management and hierarchical locking of regions. Both regions and locks are treated uniformly, and the language supports ownership transfer, early deallocation of regions and early release of locks in a safe manner

    A collaborative platform for integrating and optimising Computational Fluid Dynamics analysis requests

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    A Virtual Integration Platform (VIP) is described which provides support for the integration of Computer-Aided Design (CAD) and Computational Fluid Dynamics (CFD) analysis tools into an environment that supports the use of these tools in a distributed collaborative manner. The VIP has evolved through previous EU research conducted within the VRShips-ROPAX 2000 (VRShips) project and the current version discussed here was developed predominantly within the VIRTUE project but also within the SAFEDOR project. The VIP is described with respect to the support it provides to designers and analysts in coordinating and optimising CFD analysis requests. Two case studies are provided that illustrate the application of the VIP within HSVA: the use of a panel code for the evaluation of geometry variations in order to improve propeller efficiency; and, the use of a dedicated maritime RANS code (FreSCo) to improve the wake distribution for the VIRTUE tanker. A discussion is included detailing the background, application and results from the use of the VIP within these two case studies as well as how the platform was of benefit during the development and a consideration of how it can benefit HSVA in the future

    Ontology of core data mining entities

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    In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend
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