12 resultados para Hexagonal 3-web
em Aston University Research Archive
Resumo:
The main argument of this paper is that Natural Language Processing (NLP) does, and will continue to, underlie the Semantic Web (SW), including its initial construction from unstructured sources like the World Wide Web (WWW), whether its advocates realise this or not. Chiefly, we argue, such NLP activity is the only way up to a defensible notion of meaning at conceptual levels (in the original SW diagram) based on lower level empirical computations over usage. Our aim is definitely not to claim logic-bad, NLP-good in any simple-minded way, but to argue that the SW will be a fascinating interaction of these two methodologies, again like the WWW (which has been basically a field for statistical NLP research) but with deeper content. Only NLP technologies (and chiefly information extraction) will be able to provide the requisite RDF knowledge stores for the SW from existing unstructured text databases in the WWW, and in the vast quantities needed. There is no alternative at this point, since a wholly or mostly hand-crafted SW is also unthinkable, as is a SW built from scratch and without reference to the WWW. We also assume that, whatever the limitations on current SW representational power we have drawn attention to here, the SW will continue to grow in a distributed manner so as to serve the needs of scientists, even if it is not perfect. The WWW has already shown how an imperfect artefact can become indispensable.
Resumo:
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.
Resumo:
INTAMAP is a Web Processing Service for the automatic spatial interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the Open Geospatial Consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an integrated, open source solution. The system couples an open-source Web Processing Service (developed by 52°North), accepting data in the form of standardised XML documents (conforming to the OGC Observations and Measurements standard) with a computing back-end realised in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a markup language designed to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropy, extreme values, and data with known error distributions. Besides a fully automatic mode, the system can be used with different levels of user control over the interpolation process.
Resumo:
Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.
Resumo:
Calibration of consumer knowledge of the web refers to the correspondence between accuracy and confidence in knowledge of the web. Being well-calibrated means that a person is realistic in his or her assessment of the level of knowledge that he or she possesses. This study finds that involvement leads to better calibration and that calibration is higher for procedural knowledge and common knowledge, as compared to declarative knowledge and specialized knowledge. Neither usage, nor experience, has any effect on calibration of knowledge of the web. No difference in calibration is observed between genders. But, in agreement with previous findings, this study also finds that males are more confident in their knowledge of the web. The results point out that calibration could be more a function of knowledge-specific factors and less that of individual-specific factors. The study also identifies flow and frustration with the web as consequences of calibration of knowledge of the web and draws the attention of future researchers to examine these aspects.
Resumo:
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.
Resumo:
Increasingly, people's digital identities are attached to, and expressed through, their mobile devices. At the same time digital sensors pervade smart environments in which people are immersed. This paper explores different perspectives in which users' modelling features can be expressed through the information obtained by their attached personal sensors. We introduce the PreSense Ontology, which is designed to assign meaning to sensors' observations in terms of user modelling features. We believe that the Sensing Presence ( PreSense ) Ontology is a first step toward the integration of user modelling and "smart environments". In order to motivate our work we present a scenario and demonstrate how the ontology could be applied in order to enable context-sensitive services. © 2012 Springer-Verlag.
Resumo:
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.
Resumo:
Copper(II) acetylacetonate was anchored onto a hexagonal mesoporous silica (HMS) material using a two-step procedure: (i) functionalisation of the surface hydroxy groups with (3-aminopropyl)triethoxysilane (AMPTSi) and then (ii) anchoring of the copper(II) complex through Schiff condensation with free amine groups, using two different metal complex loadings. Upon the first step, nitrogen elemental analysis, XPS and DRIFT showed the presence of amine groups on the surface of the HMS material, and porosimetry indicated that the structure of the mesoporous material remained unchanged, although a slight decrease in surface area was observed. Atomic absorption, XPS and DRIFT showed that copper(II) acetylacetonate was anchored onto the amine-functionalised HMS by Schiff condensation between the free amine groups and the carbonyl groups of the copper(II) complex; using EPR an NO3 coordination sphere was proposed for the anchored copper(II) complex. The new [Cu(acac)2]-AMPTSi/HMS materials were tested in the aziridination of styrene at room temperature, using PhI=NTs as nitrogen source and acetonitrile as solvent. The styrene conversion and total TON of the heterogeneous phase reaction are higher than those of the same reaction catalysed in homogeneous phase by [Cu(acac)2]; nevertheless, the initial activity decreases and the reaction time increases due to substrate and product diffusion limitations. The heterogeneous catalyst showed a successive slight decrease in catalytic activity when reused for two more times. © Wiley-VCH Verlag GmbH & Co. KGaA, 2006.
Resumo:
Two modified Jacobsen-type catalysts were anchored onto an amine functionalised hexagonal mesoporous silica (HMS) using two distinct anchoring procedures: (i) one was anchored directly through the carboxylic acid functionalised diimine bridge fragment of the complex (CAT1) and (ii) the other through the hydroxyl group on the aldehyde fragment of the complex (CAT2), mediated by cyanuric chloride. The new heterogeneous catalyst, as well as the precedent materials, were characterised by elemental analyses, DRIFT, UV-vis, porosimetry and XPS which showed that the complexes were successfully anchored onto the hexagonal mesoporous silica. These materials acted as active heterogeneous catalysts in the epoxidation of styrene, using m-CPBA as oxidant, and α-methylstyrene, using NaOCl as oxidant. Under the latter conditions they acted also as enantioselective heterogeneous catalysts. Furthermore, when compared to the reaction run in homogeneous phase under similar experimental conditions, an increase in asymmetric induction was observed for the heterogenised CAT1, while the opposite effect was observed for the heterogenised CAT2, despite of CAT2 being more enantioselective than CAT1 in homogeneous phase. These results indicate that the covalent attachment of the Jacobsen catalyst through the diimine bridge leads to improved enantiomeric excess (%ee), whereas covalent attachment through one of the aldehyde fragments results in a negative effect in the %ee. Using α-methylstyrene and NaOCl as oxidant, heterogeneous catalyst reuse led to no significant loss of catalytic activity and enantioselectivity. © 2005 Elsevier Inc. All rights reserved.
Resumo:
As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.
Resumo:
The manufacturing industry faces many challenges such as reducing time-to-market and cutting costs. In order to meet these increasing demands, effective methods are need to support the early product development stages by bridging the gap of communicating early design ideas and the evaluation of manufacturing performance. This paper introduces methods of linking design and manufacturing domains using disparate technologies. The combined technologies include knowledge management supporting for product lifecycle management systems, Enterprise Resource Planning (ERP) systems, aggregate process planning systems, workflow management and data exchange formats. A case study has been used to demonstrate the use of these technologies, illustrated by adding manufacturing knowledge to generate alternative early process plan which are in turn used by an ERP system to obtain and optimise a rough-cut capacity plan. Copyright © 2010 Inderscience Enterprises Ltd.