905 resultados para Legacy datasets
Resumo:
We present a multistage strategy to define the scale and geographic distribution of 'local' ceramic production at Lydian Sardis based on geochemical analysis (NAA) of a large diverse ceramic sample (n = 281). Within the sphere of local ceramic production, our results demonstrate an unusual pattern of reliance on a single resource relative to other contemporary Iron Age centers. When our NAA results are combined with legacy NAA provenience data for production centers in Western Anatolia, we can differentiate ceramic emulation from exchange, establish probable proveniences for the non-local component of the dataset, and define new non-local groups with as yet no known provenience. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
Changes in resource use over time can provide insight into technological choice and the extent of long-term stability in cultural practices. In this paper we re-evaluate the evidence for a marked demographic shift at the inception of the Early Iron Age at Troy by applying a robust macroscale analysis of changing ceramic resource use over the Late Bronze and Iron Age. We use a combination of new and legacy analytical datasets (NAA and XRF), from excavated ceramics, to evaluate the potential compositional range of local resources (based on comparisons with sediments from within a 10 km site radius). Results show a clear distinction between sediment-defined local and non-local ceramic compositional groups. Two discrete local ceramic resources have been previously identified and we confirm a third local resource for a major class of EIA handmade wares and cooking pots. This third source appears to derive from a residual resource on the Troy peninsula (rather than adjacent alluvial valleys). The presence of a group of large and heavy pithoi among the non-local groups raises questions about their regional or maritime origin. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
The study of supermassive black hole (SMBH) accretion during their phase of activity (hence becoming active galactic nuclei, AGN), and its relation to the host-galaxy growth, requires large datasets of AGN, including a significant fraction of obscured sources. X-ray data are strategic in AGN selection, because at X-ray energies the contamination from non-active galaxies is far less significant than in optical/infrared surveys, and the selection of obscured AGN, including also a fraction of heavily obscured AGN, is much more effective. In this thesis, I present the results of the Chandra COSMOS Legacy survey, a 4.6 Ms X-ray survey covering the equatorial COSMOS area. The COSMOS Legacy depth (flux limit f=2x10^(-16) erg/s/cm^(-2) in the 0.5-2 keV band) is significantly better than that of other X-ray surveys on similar area, and represents the path for surveys with future facilities, like Athena and X-ray Surveyor. The final Chandra COSMOS Legacy catalog contains 4016 point-like sources, 97% of which with redshift. 65% of the sources are optically obscured and potentially caught in the phase of main BH growth. We used the sample of 174 Chandra COSMOS Legacy at z>3 to place constraints on the BH formation scenario. We found a significant disagreement between our space density and the predictions of a physical model of AGN activation through major-merger. This suggests that in our luminosity range the BH triggering through secular accretion is likely preferred to a major-merger triggering scenario. Thanks to its large statistics, the Chandra COSMOS Legacy dataset, combined with the other multiwavelength COSMOS catalogs, will be used to answer questions related to a large number of astrophysical topics, with particular focus on the SMBH accretion in different luminosity and redshift regimes.
Resumo:
Book Synopsis: From Terra Nullius to Land of Opportunities and Last Frontier, the European dream has constructed and deconstructed Australia to feed its imagination of new societies. At the same time Australia has over the last two centuries forged and re-invented its own liaisons with Europe arguably to carve out its identity. From the arts to social sciences, to society itself, a complex dynamic has grown between the two continents in ways that invite study and discussion. A transnational research group has begun its collective investigation project of which this first volume is the outcome. The book is a substantial multidisciplinary collection of current research and offers critical perspectives on culture, literature and history around themes at the heart of the Imagined Australia project. The essays instigate reflection, discovery and discussion of how reciprocal imagining between Australia and Europe has articulated itself and ways and dimensions in which a relationship between communities, imagined and not, has unfolded.
Resumo:
Association rule mining has made many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we firstly propose a definition for redundancy; then we propose a concise representation called Reliable basis for representing non-redundant association rules for both exact rules and approximate rules. An important contribution of this paper is that we propose to use the certainty factor as the criteria to measure the strength of the discovered association rules. With the criteria, we can determine the boundary between redundancy and non-redundancy to ensure eliminating as many redundant rules as possible without reducing the inference capacity of and the belief to the remaining extracted non-redundant rules. We prove that the redundancy elimination based on the proposed Reliable basis does not reduce the belief to the extracted rules. We also prove that all association rules can be deduced from the Reliable basis. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules.
Resumo:
Art continues to bemuse and confuse many people today. Yet, its critical analyses are saturated with daunting analyses of contemporary art's exhaustion, its predictability or its absorption into global commercial culture. In this book, the author seeks to clarify this apprehensive perception of art. He argues it is a consequence not only of confounding art-works, but also of the paradoxical impetus of a culture of modernity. By positively reassessing the perplexing or apprehensive features of cultural modernity as well as of aesthetic inquiry, this book redefines the ambitions of art in the wake of this legacy. In the process, it challenges many familiar approaches to art inquiry in order to offer a new understanding of the aesthetic, social and cultural aspirations of art in our time.
Resumo:
This article considers what drives donors to leave charitable bequests. Building on theories of charitable bequest giving, we consider two types of motivations for leaving a bequest: attitudinal and structural motivations. Using unique Australian data, we show that a strong belief in the efficacy of charitable organisations has a significant positive effect on the likelihood of leaving a bequest, as does past giving behaviour and having no children. As bequests constitute an important income stream for charitable organisations, this research can help fundraisers better target their marketing strategies towards those most likely to plan their estates and motivate these people to make bequests.
Resumo:
This paper presents an overview of technical solutions for regional area precise GNSS positioning services such as in Queensland. The research focuses on the technical and business issues that currently constrain GPS-based local area Real Time Kinematic (RTK) precise positioning services so as to operate in future across larger regional areas, and therefore support services in agriculture, mining, utilities, surveying, construction, and others. The paper first outlines an overall technical framework that has been proposed to transition the current RTK services to future larger scale coverage. The framework enables mixed use of different reference GNSS receiver types, dual- or triple-frequency, single or multiple systems, to provide RTK correction services to users equipped with any type of GNSS receivers. Next, data processing algorithms appropriate for triple-frequency GNSS signals are reviewed and some key performance benefits of using triple carrier signals for reliable RTK positioning over long distances are demonstrated. A server-based RTK software platform is being developed to allow for user positioning computations at server nodes instead of on the user's device. An optimal deployment scheme for reference stations across a larger-scale network has been suggested, given restrictions such as inter-station distances, candidates for reference locations, and operational modes. For instance, inter-station distances between triple-frequency receivers can be extended to 150km, which doubles the distance between dual-frequency receivers in the existing RTK network designs.
Resumo:
EXPLORING the ways in which women fold themselves into familiar patterns to fit in, move forward and make a place for themselves, Paschal Daantos Berry's The Folding Wife is an intimate work that engages the audience through a distinctive, almost do-it-yourself aesthetic. The Folding Wife is described by Daantos Berry as a biographical work that resonates with his and his sister Valerie's relationship to their cultural heritage, without being a representation of their story.
Resumo:
Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.
Resumo:
In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.
Resumo:
By December 2010 total superannuation assets had reached $1.3 trillion, covering 94% of all Australians. This substantial growth was not a natural evolution. Rather it can be directly traced to three decades of bipartisan reform strategies based on a claimed public interest ideology. This article investigates the concerns raised by Superannuation Select Committees, consumer and union organisations, independent researchers and actuarial experts that, in contrast to the public interest rhetoric, the regulatory reforms have primarily achieved major private interest gains for powerful lobbyists. The findings of this analysis indicate that the democratic power of Australian governments to set economic policy agendas has been progressively eclipsed by the power of the financial services industry's producer groups. Rather than producing a best practice governance structure, fund members remain trapped in a post-reform cost paradox: no right of exit regardless of the deepening cost burden imposed. In an industry set to control a projected nominal figure of $6.7 trillion in superannuation assets by 2035, these findings suggest that the real change necessary to improve the deepening cost burden faced by fund members within a life-long, mandatory superannuation investment is now beyond any government's reach.
Resumo:
Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures.