Decentralized learning with budgeted network load using Gaussian copulas and classifier ensembles

We examine a network of learners which address the same classification task but must learn from different data sets. The learners cannot share data but instead share their models. Models are shared only one time so as to preserve the network load. We introduce DELCO (standing for Decentralized Ensemble Learning with COpulas), a new approach allowing to aggregate the predictions of the classifiers trained by each learner. The proposed method aggregates the base classifiers using a probabilistic model relying on Gaussian copulas. Experiments on logistic regressor ensembles demonstrate competing accuracy and increased robustness in case of dependent classifiers. A companion python implementation can be downloaded at https://github.com/john-klein/DELC

Techniques for Complex Analysis of Contemporary Data

Contemporary data objects are typically complex, semi-structured, or unstructured at all. Besides, objects are also related to form a network. In such a situation, data analysis requires not only the traditional attribute-based access but also access based on similarity as well as data mining operations. Though tools for such operations do exist, they usually specialise in operation and are available for specialized data structures supported by specific computer system environments. In contrary, advance analyses are obtained by application of several elementary access operations which in turn requires expert knowledge in multiple areas. In this paper, we propose a unification platform for various data analytical operators specified as a general-purpose analytical system ADAMiSS. An extensible data-mining and similarity-based set of operators over a common versatile data structure allow the recursive application of heterogeneous operations, thus allowing the definition of complex analytical processes, necessary to solve the contemporary analytical tasks. As a proof-of-concept, we present results that were obtained by our prototype implementation on two real-world data collections: the Twitter Higg's boson and the Kosarak datasets

Experiences of refugees and asylum seekers in general practice: a qualitative study

Background: There has been much debate regarding the refugee health situation in the UK. However most of the existing literature fails to take account of the opinions of refugees themselves. This study was established to determine the views of asylum seekers and refugees on their overall experiences in primary care and to suggest improvements to their care. Methods: Qualitative study of adult asylum seekers and refugees who had entered the UK in the last 10 years. The study was set in Barnet Refugee Walk in Service, London. 11 Semi structured interviews were conducted and analysed using framework analysis. Results: Access to GPs may be more difficult for failed asylum seekers and those without support from refugee agencies or family. There may be concerns amongst some in the refugee community regarding the access to and confidentiality of professional interpreters. Most participants stated their preference for GPs who offered advice rather than prescriptions. The stigma associated with refugee status in the UK may have led to some refugees altering their help seeking behaviour. Conclusion: The problem of poor access for those with inadequate support may be improved by better education and support for GPs in how to provide for refugees. Primary Care Trusts could also supply information to newly arrived refugees on how to access services. GPs should be aware that, in some situations, professional interpreters may not always be desired and that instead, it may be advisable to reach a consensus as to who should be used as an interpreter. A better doctor-patient experience resulting from improvements in access and communication may help to reduce the stigma associated with refugee status and lead to more appropriate help seeking behaviour. Given the small nature of our investigation, larger studies need to be conducted to confirm and to quantify these results

Measurements of π±\pi^\pm, K±K^\pm, KS0K^0_S, Λ\Lambda and proton production in proton-carbon interactions at 31 GeV/cc with the NA61/SHINE spectrometer at the CERN SPS

Measurements of hadron production in p+C interactions at 31 GeV/c are performed using the NA61/ SHINE spectrometer at the CERN SPS. The analysis is based on the full set of data collected in 2009 using a graphite target with a thickness of 4% of a nuclear interaction length. Inelastic and production cross sections as well as spectra of $\pi^\pm$, $K^\pm$, p, $K^0_S$ and $\Lambda$ are measured with high precision. These measurements are essential for improved calculations of the initial neutrino fluxes in the T2K long-baseline neutrino oscillation experiment in Japan. A comparison of the NA61/SHINE measurements with predictions of several hadroproduction models is presented.Comment: v1 corresponds to the preprint CERN-PH-EP-2015-278; v2 matches the final published versio

A Long Baseline Neutrino Oscillation Experiment Using J-PARC Neutrino Beam and Hyper-Kamiokande

Document submitted to 18th J-PARC PAC meeting in May 2014. 50 pages, 41 figuresDocument submitted to 18th J-PARC PAC meeting in May 2014. 50 pages, 41 figuresDocument submitted to 18th J-PARC PAC meeting in May 2014. 50 pages, 41 figuresHyper-Kamiokande will be a next generation underground water Cherenkov detector with a total (fiducial) mass of 0.99 (0.56) million metric tons, approximately 20 (25) times larger than that of Super-Kamiokande. One of the main goals of Hyper-Kamiokande is the study of $CP$ asymmetry in the lepton sector using accelerator neutrino and anti-neutrino beams. In this document, the physics potential of a long baseline neutrino experiment using the Hyper-Kamiokande detector and a neutrino beam from the J-PARC proton synchrotron is presented. The analysis has been updated from the previous Letter of Intent [K. Abe et al., arXiv:1109.3262 [hep-ex]], based on the experience gained from the ongoing T2K experiment. With a total exposure of 7.5 MW $\times$ 10$^7$ sec integrated proton beam power (corresponding to $1.56\times10^{22}$ protons on target with a 30 GeV proton beam) to a $2.5$-degree off-axis neutrino beam produced by the J-PARC proton synchrotron, it is expected that the $CP$ phase $\delta_{CP}$ can be determined to better than 19 degrees for all possible values of $\delta_{CP}$, and $CP$ violation can be established with a statistical significance of more than $3\,\sigma$ ($5\,\sigma$) for $76$ ($58$) of the $\delta_{CP}$ parameter space

Measurements of neutrino oscillation in appearance and disappearance channels by the T2K experiment with 6.6 x 10(20) protons on target

111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee commentsWe thank the J-PARC staff for superb accelerator performance and the CERN NA61/SHINE Collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC, and CFI, Canada; CEA and CNRS/IN2P3, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; RSF, RFBR and MES, Russia; MINECO and ERDF funds, Spain; SNSF and SER, Switzerland; STFC, UK; and the U. S. Deparment of Energy, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK, and the Emerald High Performance Computing facility in the Centre for Innovation, UK. In addition, participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; and DOE Early Career program, USA

Measurement of the electron neutrino charged-current interaction rate on water with the T2K ND280 pi(0) detector

10 pages, 6 figures, Submitted to PRDhttp://journals.aps.org/prd/abstract/10.1103/PhysRevD.91.112010© 2015 American Physical Society11 pages, 6 figures, as accepted to PRD11 pages, 6 figures, as accepted to PRD11 pages, 6 figures, as accepted to PR

Measurement of νˉμ\bar{\nu}_{\mu} and νμ\nu_{\mu} charged current inclusive cross sections and their ratio with the T2K off-axis near detector

We report a measurement of cross section $\sigma(\nu_{\mu}+{\rm nucleus}\rightarrow\mu^{-}+X)$ and the first measurements of the cross section $\sigma(\bar{\nu}_{\mu}+{\rm nucleus}\rightarrow\mu^{+}+X)$ and their ratio $R(\frac{\sigma(\bar \nu)}{\sigma(\nu)})$ at (anti-)neutrino energies below 1.5 GeV. We determine the single momentum bin cross section measurements, averaged over the T2K $\bar{\nu}/\nu$-flux, for the detector target material (mainly Carbon, Oxygen, Hydrogen and Copper) with phase space restricted laboratory frame kinematics of $\theta_{\mu}$500 MeV/c. The results are $\sigma(\bar{\nu})=\left( 0.900\pm0.029{\rm (stat.)}\pm0.088{\rm (syst.)}\right)\times10^{-39}$ and $\sigma(\nu)=\left( 2.41\ \pm0.022{\rm{(stat.)}}\pm0.231{\rm (syst.)}\ \right)\times10^{-39}$in units of cm$^{2}$/nucleon and$R\left(\frac{\sigma(\bar{\nu})}{\sigma(\nu)}\right)= 0.373\pm0.012{\rm (stat.)}\pm0.015{\rm (syst.)}$.Comment: 18 pages, 8 figure

Fire detection from social media images by means of instance-based learning

Social media can provide valuable information to support decision making in crisis management, such as in accidents, explosions, and fires. However, much of the data from social media are images, which are uploaded at a rate that makes it impossible for human beings to analyze them. To cope with that problem, we design and implement a database-driven architecture for fast and accurate fire detection named FFireDt. The design of FFireDt uses the instance-based learning through indexed similarity queries expressed as an extension of the relational Structured Query Language. Our contributions are: (i) the design of the Fast-Fire Detection (FFireDt), which achieves efficiency and efficacy rates that rival to the state-of-the-art techniques; (ii) the sound evaluation of 36 image descriptors, for the task of image classification in social media; (iii) the evaluation of content-based indexing with respect to the construction of instance-based classification systems; and (iv) the curation of a ground-truth annotated dataset of fire images from social media. Using real data from Flickr, the experiments showed that system FFireDt was able to achieve a precision for fire detection comparable to that of human annotators. Our results are promising for the engineering of systems to monitor images uploaded to social media services.FAPESPCNPqCAPESSTIC-AmSudRESCUER project, funded by the European Commission (Grant: 614154) and by the CNPq/MCTI (Grant: 490084/2013-3)International Conference on Enterprise Information Systems - ICEIS (17. 2015 Barcelona

Search for short baseline nu(e) disappearance with the T2K near detector

8 pages, 6 figures, submitted to PRD rapid communication8 pages, 6 figures, submitted to PRD rapid communicationWe thank the J-PARC staff for superb accelerator performance and the CERN NA61 collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC and CFI, Canada; Commissariat `a l’Energie Atomique and Centre National de la Recherche Scientifique–Institut National de Physique Nucle´aire et de Physique des Particules, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; Russian Science Foundation, RFBR and Ministry of Education and Science, Russia; MINECO and European Regional Development Fund, Spain; Swiss National Science Foundation and State Secretariat for Education, Research and Innovation, Switzerland; STFC, UK; and DOE, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK. In addition participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; DOE Early Career program, USA