1,307 research outputs found

    Specifying and Verifying Meta-Security by Means of Semantic Web Methods

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    In order to achieve a systematic treatment of security protocols, organizations release a number of technical briefings for describing how security incidents have to be managed. These documents can suffer semantic deficiencies, mainly due to ambiguity or different granularity levels of description and analysis. Ontological Engineering (OE) is a powerful instrument that can be applied for both, cleaning methods and knowledge in incident protocols, and specifying (meta)security requirements on protocols for solving security incidents. We also show how the ontology built from security reports can be used as the knowledge core for semantic systems in order to work with resolution incidents in a safe way. The method has been illustrated with a case studyJunta de AndalucĂ­a TIC-606

    Spatial antibunching of photons with parametric down-conversion

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    The theoretical framework behind a recent experiment by Nogueira et. al. [Phys. Rev. Lett. 86}, 4009 (2001)] of spatial antibunching in a two-photon state generated by collinear type II parametric down-conversion and a birefringent double-slit is presented. The fourth-order quantum correlation function is evaluated and shown to violate the classical Schwarz-type inequality, ensuring that the field does not have a classical analog. We expect these results to be useful in the rapidly growing fields of quantum imaging and quantum information.Comment: 5 pages, 3 figures. Minor changes made, accepted for publication in PR

    Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

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    Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

    Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

    Get PDF
    Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

    A Green's function approach to transmission of massless Dirac fermions in graphene through an array of random scatterers

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    We consider the transmission of massless Dirac fermions through an array of short range scatterers which are modeled as randomly positioned ÎŽ\delta- function like potentials along the x-axis. We particularly discuss the interplay between disorder-induced localization that is the hallmark of a non-relativistic system and two important properties of such massless Dirac fermions, namely, complete transmission at normal incidence and periodic dependence of transmission coefficient on the strength of the barrier that leads to a periodic resonant transmission. This leads to two different types of conductance behavior as a function of the system size at the resonant and the off-resonance strengths of the delta function potential. We explain this behavior of the conductance in terms of the transmission through a pair of such barriers using a Green's function based approach. The method helps to understand such disordered transport in terms of well known optical phenomena such as Fabry Perot resonances.Comment: 22 double spaced single column pages. 15 .eps figure

    Measurement of the Bs0→J/ψKS0B_s^0\to J/\psi K_S^0 branching fraction

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    The Bs0→J/ψKS0B_s^0\to J/\psi K_S^0 branching fraction is measured in a data sample corresponding to 0.41fb−1fb^{-1} of integrated luminosity collected with the LHCb detector at the LHC. This channel is sensitive to the penguin contributions affecting the sin2ÎČ\beta measurement from B0→J/ψKS0B^0\to J/\psi K_S^0 The time-integrated branching fraction is measured to be BF(Bs0→J/ψKS0)=(1.83±0.28)×10−5BF(B_s^0\to J/\psi K_S^0)=(1.83\pm0.28)\times10^{-5}. This is the most precise measurement to date

    Measurement of the CP-violating phase \phi s in Bs->J/\psi\pi+\pi- decays

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    Measurement of the mixing-induced CP-violating phase phi_s in Bs decays is of prime importance in probing new physics. Here 7421 +/- 105 signal events from the dominantly CP-odd final state J/\psi pi+ pi- are selected in 1/fb of pp collision data collected at sqrt{s} = 7 TeV with the LHCb detector. A time-dependent fit to the data yields a value of phi_s=-0.019^{+0.173+0.004}_{-0.174-0.003} rad, consistent with the Standard Model expectation. No evidence of direct CP violation is found.Comment: 15 pages, 10 figures; minor revisions on May 23, 201

    Search for a W' boson decaying to a bottom quark and a top quark in pp collisions at sqrt(s) = 7 TeV

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    Results are presented from a search for a W' boson using a dataset corresponding to 5.0 inverse femtobarns of integrated luminosity collected during 2011 by the CMS experiment at the LHC in pp collisions at sqrt(s)=7 TeV. The W' boson is modeled as a heavy W boson, but different scenarios for the couplings to fermions are considered, involving both left-handed and right-handed chiral projections of the fermions, as well as an arbitrary mixture of the two. The search is performed in the decay channel W' to t b, leading to a final state signature with a single lepton (e, mu), missing transverse energy, and jets, at least one of which is tagged as a b-jet. A W' boson that couples to fermions with the same coupling constant as the W, but to the right-handed rather than left-handed chiral projections, is excluded for masses below 1.85 TeV at the 95% confidence level. For the first time using LHC data, constraints on the W' gauge coupling for a set of left- and right-handed coupling combinations have been placed. These results represent a significant improvement over previously published limits.Comment: Submitted to Physics Letters B. Replaced with version publishe

    Measurement of the ratio of branching fractions BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma) and the direct CP asymmetry in B0 -> K*0 gamma

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    The ratio of branching fractions of the radiative B decays B0 -> K*0 gamma and Bs0 phi gamma has been measured using an integrated luminosity of 1.0 fb-1 of pp collision data collected by the LHCb experiment at a centre-of-mass energy of sqrt(s)=7 TeV. The value obtained is BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma) = 1.23 +/- 0.06(stat.) +/- 0.04(syst.) +/- 0.10(fs/fd), where the first uncertainty is statistical, the second is the experimental systematic uncertainty and the third is associated with the ratio of fragmentation fractions fs/fd. Using the world average value for BR(B0 -> K*0 gamma), the branching fraction BR(Bs0 -> phi gamma) is measured to be (3.5 +/- 0.4) x 10^{-5}. The direct CP asymmetry in B0 -> K*0 gamma decays has also been measured with the same data and found to be A(CP)(B0 -> K*0 gamma) = (0.8 +/- 1.7(stat.) +/- 0.9(syst.))%. Both measurements are the most precise to date and are in agreement with the previous experimental results and theoretical expectations.Comment: 21 pages, 3 figues, 4 table
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