839 research outputs found

    Magnetron deposition of metal-ceramic protective coatings on glasses of windows of space vehicles

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    Transparent refractory metal-ceramic nanocomposite coatings with a high coefficient of elasticrecovery and microhardness on the basis of Ni/Si-Al-N are formed on a glass substrate by the pulse magnetron deposition method. The structure-phase states were investigated by TEM, SEM. It was established that the first layer consists of Ni nanograins with a fcc crystalline lattice, the second layer is two-phase: 5-10 nm nanocrystallites of the AlN phase with the hcp crystalline lattice in amorphous matrix of the Si3N4 phase

    Magnetron deposition of metal-ceramic protective coatings on glasses of windows of space vehicles

    Get PDF
    Transparent refractory metal-ceramic nanocomposite coatings with a high coefficient of elasticrecovery and microhardness on the basis of Ni/Si-Al-N are formed on a glass substrate by the pulse magnetron deposition method. The structure-phase states were investigated by TEM, SEM. It was established that the first layer consists of Ni nanograins with a fcc crystalline lattice, the second layer is two-phase: 5-10 nm nanocrystallites of the AlN phase with the hcp crystalline lattice in amorphous matrix of the Si3N4 phase

    Using Big Data Technologies for HEP Analysis

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    The HEP community is approaching an era were the excellent performances of the particle accelerators in delivering collision at high rate will force the experiments to record a large amount of information. The growing size of the datasets could potentially become a limiting factor in the capability to produce scientific results timely and efficiently. Recently, new technologies and new approaches have been developed in industry to answer to the necessity to retrieve information as quickly as possible to analyze PB and EB datasets. Providing the scientists with these modern computing tools will lead to rethinking the principles of data analysis in HEP, making the overall scientific process faster and smoother. In this paper, we are presenting the latest developments and the most recent results on the usage of Apache Spark for HEP analysis. The study aims at evaluating the efficiency of the application of the new tools both quantitatively, by measuring the performances, and qualitatively, focusing on the user experience. The first goal is achieved by developing a data reduction facility: working together with CERN Openlab and Intel, CMS replicates a real physics search using Spark-based technologies, with the ambition of reducing 1 PB of public data in 5 hours, collected by the CMS experiment, to 1 TB of data in a format suitable for physics analysis. The second goal is achieved by implementing multiple physics use-cases in Apache Spark using as input preprocessed datasets derived from official CMS data and simulation. By performing different end-analyses up to the publication plots on different hardware, feasibility, usability and portability are compared to the ones of a traditional ROOT-based workflow

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks