205,590 research outputs found

    Weight enumerators of Reed-Muller codes from cubic curves and their duals

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    Let Fq\mathbb{F}_q be a finite field of characteristic not equal to 22 or 33. We compute the weight enumerators of some projective and affine Reed-Muller codes of order 33 over Fq\mathbb{F}_q. These weight enumerators answer enumerative questions about plane cubic curves. We apply the MacWilliams theorem to give formulas for coefficients of the weight enumerator of the duals of these codes. We see how traces of Hecke operators acting on spaces of cusp forms for SL2(Z)\operatorname{SL}_2(\mathbb{Z}) play a role in these formulas.Comment: 19 pages. To appear in "Arithmetic, Geometry, Cryptography, and Coding Theory" (Y. Aubry, E. W. Howe, C. Ritzenthaler, eds.), Contemp. Math., 201

    CORI: Balancing Individual Rights and Public Access: Challenges of the Criminal Offender Record Information System and Opportunities for Reform

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    Reviews the creation and evolution of the Criminal Offender Record Information (CORI) system in Massachusetts, some of its key challenges, and ideas for reform

    RWU Professor Writes Book on Personal Branding

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    What is your personal brand

    The 2009 H1N1 Swine Flu Pandemic: Reconciling Goals of Patents and Public Health Initiatives

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    Teaching Stats for Data Science

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    “Data science” is a useful catchword for methods and concepts original to the field of statistics, but typically being applied to large, multivariate, observational records. Such datasets call for techniques not often part of an introduction to statistics: modeling, consideration of covariates, sophisticated visualization, and causal reasoning. This article re-imagines introductory statistics as an introduction to data science and proposes a sequence of 10 blocks that together compose a suitable course for extracting information from contemporary data. Recent extensions to the mosaic packages for R together with tools from the “tidyverse” provide a concise and readable notation for wrangling, visualization, model-building, and model interpretation: the fundamental computational tasks of data science
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