4,006 research outputs found
Ontology-Based Quality Evaluation of Value Generalization Hierarchies for Data Anonymization
In privacy-preserving data publishing, approaches using Value Generalization
Hierarchies (VGHs) form an important class of anonymization algorithms. VGHs
play a key role in the utility of published datasets as they dictate how the
anonymization of the data occurs. For categorical attributes, it is imperative
to preserve the semantics of the original data in order to achieve a higher
utility. Despite this, semantics have not being formally considered in the
specification of VGHs. Moreover, there are no methods that allow the users to
assess the quality of their VGH. In this paper, we propose a measurement
scheme, based on ontologies, to quantitatively evaluate the quality of VGHs, in
terms of semantic consistency and taxonomic organization, with the aim of
producing higher-quality anonymizations. We demonstrate, through a case study,
how our evaluation scheme can be used to compare the quality of multiple VGHs
and can help to identify faulty VGHs.Comment: 18 pages, 7 figures, presented in the Privacy in Statistical
Databases Conference 2014 (Ibiza, Spain
Distribution anisotropy: the influence of magnetic interactions on the anisotropy of magnetic remanence
The anisotropy of magnetic remanence (AMR) is often used as a tool for examining magnetic anisotropy of rocks. However, the influence of magnetostatic interactions on AMR has not been previously rigorously addressed either theoretically or experimentally, though it is widely thought to be highly significant. Using a three-dimensional micromagnetic algorithm, we have conducted a systematic numerical study of the role of magnetostatic interactions on AMR. We have considered both lineation and foliation, by modelling assemblages of ideal single domain grains and magnetically non-uniform magnetite-like cubic grains. We show that magnetostatic interactions strongly affect the measured AMR signal. It is found that depending on the orientation of the single-grain anisotropy and grain spacing it is possible for the AMR signal from a chain or grid of grains to be either oblate or prolate. For non-uniform grains, the degree of anisotropy generally increases with increasing interactions. In the modelling of AMR anisotropy, saturation isothermal remanence was chosen for numerical tractability. The influence of interactions on other types of more commonly measured AMR, are considered in light of the results in this paper. © The Geological Society of London 2004.Accepted versio
Recommended from our members
α-Lactosylceramide Protects Against iNKT-Mediated Murine Airway Hyperreactivity and Liver Injury Through Competitive Inhibition of Cd1d Binding.
Invariant natural killer T (iNKT) cells, which are activated by T cell receptor (TCR)-dependent recognition of lipid-based antigens presented by the CD1d molecule, have been shown to participate in the pathogenesis of many diseases, including asthma and liver injury. Previous studies have shown the inhibition of iNKT cell activation using lipid antagonists can attenuate iNKT cell-induced disease pathogenesis. Hence, the development of iNKT cell-targeted glycolipids can facilitate the discovery of new therapeutics. In this study, we synthesized and evaluated α-lactosylceramide (α-LacCer), an α-galactosylceramide (α-GalCer) analog with lactose substitution for the galactose head and a shortened acyl chain in the ceramide tail, toward iNKT cell activation. We demonstrated that α-LacCer was a weak inducer for both mouse and human iNKT cell activation and cytokine production, and the iNKT induction by α-LacCer was CD1d-dependent. However, when co-administered with α-GalCer, α-LacCer inhibited α-GalCer-induced IL-4 and IFN-γ production from iNKT cells. Consequently, α-LacCer also ameliorated both α-GalCer and GSL-1-induced airway hyperreactivity and α-GalCer-induced neutrophilia when co-administered in vivo. Furthermore, we were able to inhibit the increases of ConA-induced AST, ALT and IFN-γ serum levels through α-LacCer pre-treatment, suggesting α-LacCer could protect against ConA-induced liver injury. Mechanistically, we discerned that α-LacCer suppressed α-GalCer-stimulated cytokine production through competing for CD1d binding. Since iNKT cells play a critical role in the development of AHR and liver injury, the inhibition of iNKT cell activation by α-LacCer present a possible new approach in treating iNKT cell-mediated diseases
Global science literacy : definition, needs assessment and concerns for Cyprus
Global Science Literacy has as its goals to stimulate an interest in
science, represent modern technological goals of science, develop international
understanding, relate science to social needs, and develop thinking and
problem-solving skills for the 21st Century. Such an approach is proposed as
viable on an international basis for conceptual strength in integrated science
courses. Assessment of GSL’s potential in Cyprus serves as an example of
preparations needed and concerns to be addressed if GSL is to become the basis
of the science curriculum. Toward this end, a survey of teachers throughout
Cyprus identified teachers’ priorities for environmental issues and system
science concepts their students should know, the teachers’ knowledge of those
concepts and issues, and their current levels of teaching them. This paper will
discuss the teachers’ relative perceptions of local and global understandings,
Earth systems science, and teacher education issues involved in fostering
Global Science Literacy.peer-reviewe
Explorations of the viability of ARM and Xeon Phi for physics processing
We report on our investigations into the viability of the ARM processor and
the Intel Xeon Phi co-processor for scientific computing. We describe our
experience porting software to these processors and running benchmarks using
real physics applications to explore the potential of these processors for
production physics processing.Comment: Submitted to proceedings of the 20th International Conference on
Computing in High Energy and Nuclear Physics (CHEP13), Amsterda
Let's Make Block Coordinate Descent Go Fast: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
Block coordinate descent (BCD) methods are widely-used for large-scale
numerical optimization because of their cheap iteration costs, low memory
requirements, amenability to parallelization, and ability to exploit problem
structure. Three main algorithmic choices influence the performance of BCD
methods: the block partitioning strategy, the block selection rule, and the
block update rule. In this paper we explore all three of these building blocks
and propose variations for each that can lead to significantly faster BCD
methods. We (i) propose new greedy block-selection strategies that guarantee
more progress per iteration than the Gauss-Southwell rule; (ii) explore
practical issues like how to implement the new rules when using "variable"
blocks; (iii) explore the use of message-passing to compute matrix or Newton
updates efficiently on huge blocks for problems with a sparse dependency
between variables; and (iv) consider optimal active manifold identification,
which leads to bounds on the "active set complexity" of BCD methods and leads
to superlinear convergence for certain problems with sparse solutions (and in
some cases finite termination at an optimal solution). We support all of our
findings with numerical results for the classic machine learning problems of
least squares, logistic regression, multi-class logistic regression, label
propagation, and L1-regularization
- …