15 resultados para web-scale discovery system

em Aston University Research Archive


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When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

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The Electronic Product Code Information Service (EPCIS) is an EPCglobal standard, that aims to bridge the gap between the physical world of RFID1 tagged artifacts, and information systems that enable their tracking and tracing via the Electronic Product Code (EPC). Central to the EPCIS data model are "events" that describe specific occurrences in the supply chain. EPCIS events, recorded and registered against EPC tagged artifacts, encapsulate the "what", "when", "where" and "why" of these artifacts as they flow through the supply chain. In this paper we propose an ontological model for representing EPCIS events on the Web of data. Our model provides a scalable approach for the representation, integration and sharing of EPCIS events as linked data via RESTful interfaces, thereby facilitating interoperability, collaboration and exchange of EPC related data across enterprises on a Web scale.

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Monitoring is essential for conservation of sites, but capacity to undertake it in the field is often limited. Data collected by remote sensing has been identified as a partial solution to this problem, and is becoming a feasible option, since increasing quantities of satellite data in particular are becoming available to conservationists. When suitably classified, satellite imagery can be used to delineate land cover types such as forest, and to identify any changes over time. However, the conservation community lacks (a) a simple tool appropriate to the needs for monitoring change in all types of land cover (e.g. not just forest), and (b) an easily accessible information system which allows for simple land cover change analysis and data sharing to reduce duplication of effort. To meet these needs, we developed a web-based information system which allows users to assess land cover dynamics in and around protected areas (or other sites of conservation importance) from multi-temporal medium resolution satellite imagery. The system is based around an open access toolbox that pre-processes and classifies Landsat-type imagery, and then allows users to interactively verify the classification. These data are then open for others to utilize through the online information system. We first explain imagery processing and data accessibility features, and then demonstrate the toolbox and the value of user verification using a case study on Nakuru National Park, Kenya. Monitoring and detection of disturbances can support implementation of effective protection, assist the work of park managers and conservation scientists, and thus contribute to conservation planning, priority assessment and potentially to meeting monitoring needs for Aichi target 11.

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The objective of this study was to design, construct, commission and operate a laboratory scale gasifier system that could be used to investigate the parameters that influence the gasification process. The gasifier is of the open-core variety and is fabricated from 7.5 cm bore quartz glass tubing. Gas cleaning is by a centrifugal contacting scrubber, with the product gas being flared. The system employs an on-line dedicated gas analysis system, monitoring the levels of H2, CO, CO2 and CH4 in the product gas. The gas composition data, as well as the gas flowrate, temperatures throughout the system and pressure data is recorded using a BBC microcomputer based data-logging system. Ten runs have been performed using the system of which six were predominantly commissioning runs. The main emphasis in the commissioning runs was placed on the gas clean-up, the product gas cleaning and the reactor bed temperature measurement. The reaction was observed to occur in a narrow band, of about 3 to 5 particle diameters thick. Initially the fuel was pyrolysed, with the volatiles produced being combusted and providing the energy to drive the process, and then the char product was gasified by reaction with the pyrolysis gases. Normally, the gasifier is operated with reaction zone supported on a bed of char, although it has been operated for short periods without a char bed. At steady state the depth of char remains constant, but by adjusting the air inlet rate it has been shown that the depth of char can be increased or decreased. It has been shown that increasing the depth of the char bed effects some improvement in the product gas quality.

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A method of accurately controlling the position of a mobile robot using an external large volume metrology (LVM) instrument is presented in this article. By utilising an LVM instrument such as a laser tracker or indoor GPS (iGPS) in mobile robot navigation, many of the most difficult problems in mobile robot navigation can be simplified or avoided. Using the real-time position information from the laser tracker, a very simple navigation algorithm, and a low cost robot, 5mm repeatability was achieved over a volume of 30m radius. A surface digitisation scan of a wind turbine blade section was also demonstrated, illustrating possible applications of the method for manufacturing processes. Further, iGPS guidance of a small KUKA omni-directional robot has been demonstrated, and a full scale prototype system is being developed in cooperation with KUKA Robotics, UK. © 2011 Taylor & Francis.

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Purpose - To develop a systems strategy for supply chain management in aerospace maintenance, repair and overhaul (MRO). Design/methodology/approach - A standard systems development methodology has been followed to produce a process model (i.e. the AMSCR model); an information model (i.e. business rules) and a computerised information management capability (i.e. automated optimisation). Findings - The proof of concept for this web-based MRO supply chain system has been established through collaboration with a sample of the different types of supply chain members. The proven benefits comprise new potential to minimise the stock holding costs of the whole supply chain whilst also minimising non-flying time of the aircraft that the supply chain supports. Research limitations/implications - The scale of change needed to successfully model and automate the supply chain is vast. This research is a limited-scale experiment intended to show the power of process analysis and automation, coupled with strategic use of management science techniques, to derive tangible business benefit. Practical implications - This type of system is now vital in an industry that has continuously decreasing profit margins; which in turn means pressure to reduce servicing times and increase the mean time between them. Originality/value - Original work has been conducted at several levels: process, information and automation. The proof-of-concept system has been applied to an aircraft MRO supply chain. This is an area of research that has been neglected, and as a result is not well served by current systems solutions. © Emerald Group Publishing Limited.

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Component-based development (CBD) has become an important emerging topic in the software engineering field. It promises long-sought-after benefits such as increased software reuse, reduced development time to market and, hence, reduced software production cost. Despite the huge potential, the lack of reasoning support and development environment of component modeling and verification may hinder its development. Methods and tools that can support component model analysis are highly appreciated by industry. Such a tool support should be fully automated as well as efficient. At the same time, the reasoning tool should scale up well as it may need to handle hundreds or even thousands of components that a modern software system may have. Furthermore, a distributed environment that can effectively manage and compose components is also desirable. In this paper, we present an approach to the modeling and verification of a newly proposed component model using Semantic Web languages and their reasoning tools. We use the Web Ontology Language and the Semantic Web Rule Language to precisely capture the inter-relationships and constraints among the entities in a component model. Semantic Web reasoning tools are deployed to perform automated analysis support of the component models. Moreover, we also proposed a service-oriented architecture (SOA)-based semantic web environment for CBD. The adoption of Semantic Web services and SOA make our component environment more reusable, scalable, dynamic and adaptive.

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Forests play a pivotal role in timber production, maintenance and development of biodiversity and in carbon sequestration and storage in the context of the Kyoto Protocol. Policy makers and forest experts therefore require reliable information on forest extent, type and change for management, planning and modeling purposes. It is becoming increasingly clear that such forest information is frequently inconsistent and unharmonised between countries and continents. This research paper presents a forest information portal that has been developed in line with the GEOSS and INSPIRE frameworks. The web portal provides access to forest resources data at a variety of spatial scales, from global through to regional and local, as well as providing analytical capabilities for monitoring and validating forest change. The system also allows for the utilisation of forest data and processing services within other thematic areas. The web portal has been developed using open standards to facilitate accessibility, interoperability and data transfer.

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The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.

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Monitoring land-cover changes on sites of conservation importance allows environmental problems to be detected, solutions to be developed and the effectiveness of actions to be assessed. However, the remoteness of many sites or a lack of resources means these data are frequently not available. Remote sensing may provide a solution, but large-scale mapping and change detection may not be appropriate, necessitating site-level assessments. These need to be easy to undertake, rapid and cheap. We present an example of a Web-based solution based on free and open-source software and standards (including PostGIS, OpenLayers, Web Map Services, Web Feature Services and GeoServer) to support assessments of land-cover change (and validation of global land-cover maps). Authorised users are provided with means to assess land-cover visually and may optionally provide uncertainty information at various levels: from a general rating of their confidence in an assessment to a quantification of the proportions of land-cover types within a reference area. Versions of this tool have been developed for the TREES-3 initiative (Simonetti, Beuchle and Eva, 2011). This monitors tropical land-cover change through ground-truthing at latitude / longitude degree confluence points, and for monitoring of change within and around Important Bird Areas (IBAs) by Birdlife International and the Royal Society for the Protection of Birds (RSPB). In this paper we present results from the second of these applications. We also present further details on the potential use of the land-cover change assessment tool on sites of recognised conservation importance, in combination with NDVI and other time series data from the eStation (a system for receiving, processing and disseminating environmental data). We show how the tool can be used to increase the usability of earth observation data by local stakeholders and experts, and assist in evaluating the impact of protection regimes on land-cover change.

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While semantic search technologies have been proven to work well in specific domains, they still have to confront two main challenges to scale up to the Web in its entirety. In this work we address this issue with a novel semantic search system that a) provides the user with the capability to query Semantic Web information using natural language, by means of an ontology-based Question Answering (QA) system [14] and b) complements the specific answers retrieved during the QA process with a ranked list of documents from the Web [3]. Our results show that ontology-based semantic search capabilities can be used to complement and enhance keyword search technologies.

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In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. We present a novel unsupervised machine learning method called CORDER (COmmunity Relation Discovery by named Entity Recognition) to turn these unstructured data into structured information for knowledge management in these organizations. CORDER exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments in an expert evaluation, a quantitative benchmarking, and an application of CORDER in a social networking tool called BuddyFinder.

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The Semantic Web (SW) offers an opportunity to develop novel, sophisticated forms of question answering (QA). Specifically, the availability of distributed semantic markup on a large scale opens the way to QA systems which can make use of such semantic information to provide precise, formally derived answers to questions. At the same time the distributed, heterogeneous, large-scale nature of the semantic information introduces significant challenges. In this paper we describe the design of a QA system, PowerAqua, designed to exploit semantic markup on the web to provide answers to questions posed in natural language. PowerAqua does not assume that the user has any prior information about the semantic resources. The system takes as input a natural language query, translates it into a set of logical queries, which are then answered by consulting and aggregating information derived from multiple heterogeneous semantic sources.

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The semantic web (SW) vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language (NL) and an ontology as input, and returns answers drawn from one or more knowledge bases (KB). AquaLog presents an elegant solution in which different strategies are combined together in a novel way. AquaLog novel ontology-based relation similarity service makes sense of user queries.

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Objectives: To develop a decision support system (DSS), myGRaCE, that integrates service user (SU) and practitioner expertise about mental health and associated risks of suicide, self-harm, harm to others, self-neglect, and vulnerability. The intention is to help SUs assess and manage their own mental health collaboratively with practitioners. Methods: An iterative process involving interviews, focus groups, and agile software development with 115 SUs, to elicit and implement myGRaCE requirements. Results: Findings highlight shared understanding of mental health risk between SUs and practitioners that can be integrated within a single model. However, important differences were revealed in SUs' preferred process of assessing risks and safety, which are reflected in the distinctive interface, navigation, tool functionality and language developed for myGRaCE. A challenge was how to provide flexible access without overwhelming and confusing users. Conclusion: The methods show that practitioner expertise can be reformulated in a format that simultaneously captures SU expertise, to provide a tool highly valued by SUs. A stepped process adds necessary structure to the assessment, each step with its own feedback and guidance. Practice Implications: The GRiST web-based DSS (www.egrist.org) links and integrates myGRaCE self-assessments with GRiST practitioner assessments for supporting collaborative and self-managed healthcare.