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Titlebook: Combinatorics; Room Squares, Sum-Fr W. D. Wallis,Jennifer Seberry Wallis,Anne Penfold Book 1972 Springer-Verlag Berlin Heidelberg 1972 Com

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书目名称Combinatorics
副标题Room Squares, Sum-Fr
编辑W. D. Wallis,Jennifer Seberry Wallis,Anne Penfold
视频video
丛书名称Lecture Notes in Mathematics
图书封面Titlebook: Combinatorics; Room Squares, Sum-Fr W. D. Wallis,Jennifer Seberry Wallis,Anne Penfold  Book 1972 Springer-Verlag Berlin Heidelberg 1972 Com
出版日期Book 1972
关键词Combinatorics; Hadamard; Matrices; Sets
版次1
doihttps://doi.org/10.1007/BFb0069907
isbn_softcover978-3-540-06035-2
isbn_ebook978-3-540-37994-2Series ISSN 0075-8434 Series E-ISSN 1617-9692
issn_series 0075-8434
copyrightSpringer-Verlag Berlin Heidelberg 1972
The information of publication is updating

书目名称Combinatorics影响因子(影响力)




书目名称Combinatorics影响因子(影响力)学科排名




书目名称Combinatorics网络公开度




书目名称Combinatorics网络公开度学科排名




书目名称Combinatorics被引频次




书目名称Combinatorics被引频次学科排名




书目名称Combinatorics年度引用




书目名称Combinatorics年度引用学科排名




书目名称Combinatorics读者反馈




书目名称Combinatorics读者反馈学科排名




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978-3-540-06035-2Springer-Verlag Berlin Heidelberg 1972
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Combinatorics978-3-540-37994-2Series ISSN 0075-8434 Series E-ISSN 1617-9692
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0075-8434 Overview: 978-3-540-06035-2978-3-540-37994-2Series ISSN 0075-8434 Series E-ISSN 1617-9692
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Uwe Diehr,Enrico Klingbeil,Michael Knipper,Thomas Mestwerdt,Hermann Rothfuchs,René Teichmann of people to which you probably belong-individuals who seek grants. In my years as Director of the New York library of The Foundation Center, * each and every day I encountered numbers of individuals look­ ing for grant money. Although I tried to be as supportive as possible, in the face of the par
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How do Small Firms Innovate in British Columbia?f new technologies. The measurement of innovation consequently concentrated on R&D personnel and outlays, on patent data, and on the rate by which new technologies, especially information technologies, were adopted and used.
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Multi-scale Multi-target Domain Adaptation for Angle Closure Classificationon of AS-OCT images. Based on these domain-invariant features at different scales, the deep model trained on the source domain is able to classify angle closure on multiple target domains even without any annotations in these domains. Extensive experiments on a real-world AS-OCT dataset demonstrate the effectiveness of the proposed method.
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