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- Adloff, C, et al.
(author)
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Energy flow and rapidity gaps between jets in photoproduction at HERA
- 2002
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044. ; 24:4, s. 517-527
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Journal article (peer-reviewed)abstract
- Dijet events in photon-proton collisions in which there is a large pseudorapidity separation, Deltaeta > 2.5 between the two highest E-T jets are studied with the H1 detector at HERA. The inclusive dijet cross sections are measured as functions of the longitudinal momentum fractions of the proton and photon which participate in the production of the jets, x(p)(jets) and x(gamma)(jets) respectively, Deltaeta, the pseudorapidity P separation between the two highest E-T jets, and E-T(gap), the total summed transverse energy between the jets. Rapidity gap events are defined as events in which E-T(gap) is less than E-T(cut), for E-T(cut) varied between jets 0.5 and 2.0 GeV. The fraction of dijet events with a rapidity gap is measured differentially in Deltaeta, x(p)(jets) and x(gamma)(jets). An excess of events with rapidity gaps at low values of E-T(cut) is observed above the expectation from standard photoproduction processes. This excess can be explained by the exchange of a strongly interacting colour singlet object between the jets.
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- Adloff, C, et al.
(author)
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Measurement of dijet electroproduction at small jet separation
- 2002
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044. ; 24:1, s. 33-41
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Journal article (peer-reviewed)abstract
- Deep-inelastic scattering data in the range 150 < Q(2) < 35000 GeV2 are used to investigate the minimum jet separation necessary to allow accurate description of the rate of dijet production using next-to-leading order perturbative QCD calculations. The required jet separation is found to be small, allowing about 1/3 of DIS data to be classified as dijet, as opposed to approximately 1/10 with more typical jet analyses. A number of precision measurements made using this dijet sample are well described by the calculations. The data are also described by the combination of leading order matrix elements and parton showers, as implemented in the QCD based Monte Carlo model RAPGAP.
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- Adloff, C, et al.
(author)
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Measurement of D*(+/-) meson production and F-2(c) in deep-inelastic scattering at HERA
- 2002
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In: Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. - 0370-2693. ; 528:3-4, s. 199-214
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Journal article (peer-reviewed)abstract
- The inclusive production of D*+/-(2010) mesons in deep-inelastic scattering is studied with the HI detector at HERA. In the kinematic region 1 < Q(2) < 100 GeV2 and 0.05 < y < 0.7 an e(+) p cross section for inclusive D*+/- meson production of 8.50 +/- 0.42(stat.)(-100)(+1.21)(syst.) nb is measured in the visible range p(tD*) > 1.5 GeV and eta(D*) < 1.5. Single and double differential inclusive D*+/- meson cross sections are compared to perturbative QCD calculations in two different evolution schemes, The charm contribution to the proton structure, F-c(2)(x, Q(2)), is determined by extrapolating the visible charm cross section to the full phase space. This contribution is found to rise from about 10% at Q(2) = 1.5 GeV2 to more than 25% at Q(2) = 60 GeV2 corresponding to x values ranging from 5 x 10(-5) to 3 x 10(-3). (C) 2002 Elsevier Science B.V. All rights reserved.
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- Adloff, C, et al.
(author)
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Search for excited neutrinos at HERA
- 2002
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In: Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. - 0370-2693. ; 525:1-2, s. 9-16
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Journal article (peer-reviewed)abstract
- We present a search for excited neutrinos using e(-) p data taken by the H1 experiment at HERA at a center-of-mass energy of 318 GeV with an integrated luminosity of 15 pb(-1). No evidence for excited neutrino production is found. Mass dependent exclusion limits are determined for the ratio of the coupling to the compositeness scale, f/Lambda, independently of the relative couplings to the SU(2) and U(1) gauge bosons. These limits extend the excluded region to higher masses than has been possible in previous searches at other colliders.
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- Bate, Iain, et al.
(author)
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Searching for the minimum failures that can cause a hazard in a wireless sensor network
- 2013
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In: GECCO - Proceedings of the 2013 Genetic and Evolutionary Computation Conference. - New York, NY, USA : ACM. - 9781450319638 ; , s. 1213-1220
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Conference paper (peer-reviewed)abstract
- Wireless Sensor Networks (WSN) are now being used in a range of applications, many of which are critical systems, e.g. monitoring assisted living facilities or for fire detection systems which is the example used in this paper. For critical systems it is important to be able to determine the minimum number of failures that can cause a hazard to occur. This is normally a manual, human intensive, task. This paper presents a novel application of search to both the WSN and safety domains; searching for combinations of failures that can cause a hazard and then reducing these to the minimum possible using a combination of automated search and manual refinement. Due to the size and complexity of the search problem, a parallel search algorithm is designed that runs on available compute resources with the results being processed using R. Copyright © 2013 ACM.
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- Orre, R., et al.
(author)
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Bayesian neural networks with confidence estimations applied to data mining
- 2000
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In: Computational Statistics & Data Analysis. - 0167-9473 .- 1872-7352. ; 34:4, s. 473-493
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Journal article (peer-reviewed)abstract
- An international database of case reports, each one describing a possible case of adverse drug reactions (ADRs), is maintained by the Uppsala Monitoring Centre (UMC), for the WHO international program on drug safety monitoring. Each report can be seen as a row in a data matrix and consists of a number of variables, like drugs used, ADRs, and other patient data. The problem is to examine the database and find significant dependencies which might be signals of potentially important ADRs, to be investigated by clinical experts. We propose a method by which estimated frequencies of combinations of variables are compared with the frequencies that would be predicted assuming there were no dependencies. The estimates of significance are obtained with a Bayesian approach via the variance of posterior probability distributions. The posterior is obtained by fusing a prior distribution (Dirichlet of dimension 2(n-1)) with a batch of data, which is also the prior used when the next batch of data arrives. To decide whether the joint probabilities of events are different fi-om what would follow from the independence assumption, the information component log(P-ij/(PiPj)) plays a crucial role, and one main technical contribution reported here is an efficient method to estimate this measure, as well as the variance of its posterior distribution, for large data matrices. The method we present is fundamentally an artificial neural network denoted Bayesian confidence propagation neural network (BCPNN). We also demonstrate an efficient way of finding complex dependencies. The method is now (autumn 1998) being routinely used to produce warning signals on new unexpected ADR associations.
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