NAGASAKA Kosaku | ![]() |
Graduate School of Human Development and Environment / Department of Human Environmental Science | |
Associate Professor | |
Mathematics |
Jun. 2005 Japan Society for Symbolic and Algebraic Computation, Encouragement Prize, 多変数多項式の絶対既約半径の改善について
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We propose a better algorithm for approximate greatest common divisor (approximate GCD) of univariate polynomials in terms of robustness and distance, based on the NewtonSLRA algorithm that is a solver for the structured low rank approximation (SLRA) problem. Our algorithm mainly enlarges the tangent space in the NewtonSLRA algorithm and adapts it to a certain weighted Frobenius norm. Moreover, we propose some improvement in computing time.
Association for Computing Machinery (ACM), Sep. 2021, ACM Communications in Computer Algebra, 55 (3), 97 - 101, English[Refereed]
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Computing the greatest common divisor (GCD) of polynomials can be done by computing the Gröbner basis instead of the well-known Euclidean algorithm, studied by Gianni and Trager in 1985, and Sasaki and Suzuki in 1992. In this paper, we extend their theories to polynomials with parameters. That is the theory of parametric greatest common divisors by means of comprehensive Gröbner systems (CGS). Moreover, this can be considered as an indirect extension of known parametric GCD algorithms to those for several multivariate polynomials with parameters.
Association for Computing Machinery, 23 Jul. 2017, Proceedings of the International Symposium on Symbolic and Algebraic Computation, ISSAC, 129312, 341 - 348, English[Refereed]
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For computing the greatest common divisor of two univariate polynomials with a priori numerical errors on their coefficients, we use several approximate polynomial GCD algorithms: QRGCD, UVGCD, STLN-based, Fastgcd, GPGCD and so on. Among them, QRGCD is the most common algorithm since it has been distributed as a part of Maple and there are many papers including their comparisons of efficiency and effectiveness against QRGCD. In this paper, we give an improved QRGCD algorithm (ExQRGCD) which is unfortunately not faster than the original but more accurate and the resulting perturbation is able to satisfy the given tolerance.
SPRINGER-VERLAG BERLIN, 2013, COMPUTER ALGEBRA IN SCIENTIFIC COMPUTING, CASC 2013, 8136, 257 - 272, English[Refereed]
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Symbolic numeric algorithms for polynomials are very important, especially for practical computations since we have to operate with empirical polynomials having numerical errors on their coefficients. Recently, for those polynomials, a number of algorithms have been introduced, such as approximate univariate GCD and approximate multivariate factorization for example. However, for polynomials over integers having coefficients rounded from empirical data, changing their coefficients over reals does not remain them in the polynomial ring over integers; hence we need several approximate operations over integers. In this paper, we discuss computing a polynomial GCD of univariate or multivariate polynomials over integers approximately. Here, "approximately" means that we compute a polynomial GCD over integers by changing their coefficients slightly over integers so that the input polynomials still remain over integers. (C) 2011 Elsevier Ltd. All rights reserved.
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, Dec. 2011, JOURNAL OF SYMBOLIC COMPUTATION, 46 (12), 1306 - 1317, English[Refereed]
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We compute an approximate greatest common divisor (GCD) of co-prime polynomials over integers by changing their coefficients slightly over integers so that the input polynomials still remain over integers. In this paper, we give an improved algorithm with a new lattice construction process by which we can restrict the range of perturbations in some cases. Copyright © 2011 ACM.
2011, SNC'11 - Proceedings of the 2011 International Workshop on Symbolic-Numeric Computation, 63 - 64, English[Refereed]
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There are several preliminary definitions for a Grobner basis with inexact input since computing such a basis is one of the challenging problems in symbolic-numeric computations for several decades. A structured Grobner basis is such a basis defined from the data mining point of view: how to extract a meaningful result from the given inexact input when the amount of noise is not small or we do not have enough information about the input. However, the known algorithm needs a suitable (unknown) information on terms required for a variant of the Buchberger algorithm. In this paper, we introduce an improved version of the algorithm that does not need any extra information in advance.
ASSOC COMPUTING MACHINERY, 2011, ISSAC 2011: PROCEEDINGS OF THE 36TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND ALGEBRAIC COMPUTATION, 273--280, 273 - 280, English[Refereed]
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Grobner basis is one of the most important tools in recent symbolic algebraic computations. However, computing a Grobner basis for the given polynomial ideal is not easy and it is riot numerically stable if polynomials have inexact coefficients. In this paper, we study what we should get for computing a Grobner basis with inexact coefficients and introduce a naive method to compute a Grobner basis by reduced row echelon form, for the ideal generated by the given polynomial set having a priori errors on their coefficients.
SPRINGER-VERLAG BERLIN, 2009, COMPUTER ALGEBRA IN SCIENTIFIC COMPUTING, PROCEEDINGS, 5743, 247 - 258, English[Refereed]
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Ruppert and Sylvester matrices are very common for computing irreducible factors of bivariate polynomials and computing polynomial greatest common divisors, respectively. Since Ruppert matrix comes from Ruppert criterion for bivariate polynomial irreducibility testing and Sylvester matrix comes from the usual subresultant mapping, they are used for different purposes and their relations have not been focused yet. In this paper, we show some relations between Ruppert and Sylvester matrices as the usual subresultant mapping for computing (exact/approximate) polynomial GCDs, using Ruppert matrices.
SPRINGER-VERLAG BERLIN, 2007, Computer Algebra in Scientific Computing, Proceedings, 4770, 316 - 327, English[Refereed]
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「市民の科学に対する大学の支援に関する実践的研究」(略称「市民の科学」)プロジェクトの一環として、「サイエンスカフェ神戸」を創始した。このプロジェクトは、科学技術的課題に対する市民のエンパワーメント・システム構築をめざすもので、サイエンスカフェ開催はその第一段階として位置づけられる。2005年10月から2006年6月までに16回を開催し、科学コミュニケーションの新しいスタイルとして高い可能性を確認した。サイエンスカフェは現在各地に広がりつつあるが、「サイエンスカフェ神戸」では、文化としての科学を地域社会に根づかせることを大きな目的とし、運営に市民が主体的に参加し、様々な場で頻繁に開催されるようなあり方をゴールとして設定している点で特徴をもっている。「市民の科学」プロジェクトでは、次のステップとして、サイエンスカフェを通じて形成された緩やかなネットワークも利用しつつ、大学の支援のもとでの、環境などに関わる課題の市民による調査・研究の展開可能性を探ってゆく。
Japan Society of Science Education, Aug. 2006, 日本科学教育学会研究会研究報告, Vol. 21, No. 1, pp. 37-42 (1), 37 - 42, JapaneseScientific journal
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科学・技術が高度に発達した社会において、(a)環境問題等の解決手段として、(b)知的探求活動として、市民の科学・技術にかかわる問題の調査・研究能力を高めてゆくこと(エンパワーメント)が大きな意味を持つ。我々は、神戸大学大学院総合人間科学研究科に設置された発達支援インスティテュート/ヒューマン・コミュニティ創成研究センターの研究プロジェクトとして「市民科学に対する大学の支援に関する実践的研究」の取り組みを始めた。本プロジェクトは、神戸を主なフィールドとして、幅広い年齢や素養をもつ市民が、大学の支援のもとに、科学リテラシーを高めるとともに、自らが調査・研究能力を獲得してゆく持続可能なシステムとそれを担う組織、人材のあり方を実践的に探り、日本の社会に適したモデルを構築することを目指す。
Japan Society of Science Education, Sep. 2005, 科教研報, 20・2, 47-51 (2), 47 - 51, JapaneseScientific journal
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We study the problem of bounding a polynomial which is absolutely irreducible, away from polynomials which are not absolutely irreducible. These separation bounds are useful for testing whether an empirical polynomial is absolutely irreducible or not, for the given tolerance or error bound of its coefficients. In the former paper, we studied some improvements on Kaltofen and May's method which finds applicable separation bounds using an absolute irreducibility criterion due to Ruppert. In this paper, we study the similar improvements on the method using the criterion due to Gao and Rodrigues for sparse polynomials satisfying Newton polytope conditions, by which we are able to find more accurate separation bounds, for such bivariate polynomials. We also discuss a concept of separation bound continuations for both dense and sparse polynomials.
SPRINGER-VERLAG BERLIN, 2005, COMPUTER ALGEBRA IN SCIENFIFIC COMPUTING, PROCEEDINGS, 3718, 318 - 329, English[Refereed]
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This study analyzed the color space as human sensibility to develop the software converting the expression of graphics into more effective color. In existing researches, a lot of researches using the Munsell Color System were performed.As a result, the color space of three dimensions was assumed. However, it was difficult to plot the color in the space. Because the the favor of the color varied from person to person.Therefore, it experimented by both the sensibility words used by the past research and the sensibility words that newly suited L^*u^*v^* in this experiment. As a result, the main axis of dimension and a new color space as human sensibility by the color specification system of L^*u^*v^* of even color space CIELUV were extracted by this experiment.
Japanese Society for the Science of Design, 20 Jun. 2009, Proceedings of the Annual Conference of JSSD, (56), 18 - 19, JapaneseReport scientific journal
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Mathematics Education Society of Japan
Sep. 2022 - PresentACM
May 2022 - PresentACM SIGSAM
Jul. 2002 - PresentJapan Society for Symbolic and Algebraic Computation
Apr. 2002 - PresentInformation Processing Society of Japan
Apr. 2002 - Mar. 2023Japan Society for Industrial and Applied Mathematics
Apr. 2002 - Mar. 2023LMS上でのオンラインテストはこれまでSTACKを使って新規に実装を行ったり,既存コンテンツの解答形式の見直しを若干行ったりした.また, 大阪府立大学で運用されているMathematica を用いたMATH ON WEBの問題コンテンツの移植をいくつかの問題について行なった.これらの問題は数値の入力が必要であり,行列が多数出てくる線形代数においては,学生のスマートフォン活用に着目した本研究の視点からは利便性に相当の問題がある場合がある.この点を改善するために, これらの問題を,場合によっては視点を変えた形に変換した上で,多肢選択問題としての出題が可能かについての検討を行った.また,実際,そのいくつかについては, CAS(Mathematica)を用いて実装を開始し, 基本的な実装手順を確立した.同様に開発をしている分担者(長坂)とも協議し,開発における仕様の統一化や,他の一般教員が参加できるようにWebベースでの開発のインターフェイスができないかなど必要な検討課題について打ち合せを行い,今後 webMathematica の他,無償の言語もしくはCASを使った Webでの開発環境について討議することになった. また, 本研究のアイデアについて, 国際学会(ICMS-2018, EAMS-2018)および国内学会(JSiSE全国大会および研究会,CIEC北海道研究会)で発表し, 国内外の研究者と意見交換や情報収集を行った.その結果,STACKのPRT(Potential Response Tree)に代表される既存の問題におけるフィードバック手法と多肢選択問題の誤選択肢の生成は相補関係にあるという知見を確認することができた.
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