発表文献

論文(査読あり)

  1. H. Koyama, A. M. Ito, H. Okumura, T. Otani, K. Nakamura and T. Fujimori, "Cell position-based evaluation of mechanical features of cells in multicellular systems," Journal of Theoretical Biology, Vol. 604, 7 May 2025, 112070, 2025.
  2. Y. Han and K. Nakamura, "The Application of Zig-Zag Sampler in Sequential Markov Chain Monte Carlo," Journal of Information Processing, 32, pp.231-244, 2025.
  3. 西澤勇祐,三浦弘慈,デヴィン グナワン,五十嵐乃愛,曽我部直樹,岩前伸幸,玉野慶吾,中村和幸,「データ同化技術を用いた橋梁の非線形地震応答解析モデルの精緻化」AI・データサイエンス論文集,5 巻,3 号, pp. 42-52,2024.
  4. H. Yokoyama, T. Yamashita, Y. Kojima and K. Nakamura, "Deep learning-based flocculation sensor for automatic control of flocculant dose in sludge dewatering processes during wastewater treatmeent," Water Research, 260, 121890, 2024.
  5. T. Ishizone, Y. Matsunaga, S. Fuchigami, and K. Nakamura, "Representation of Protein Dynamics Disentangled by Time-structure-based Prior", Journal of Chemical Theory and Computation, 20, 1, 436–450, 2024.
  6. M. Nakashima, M. Miyasaka, N. Satomi, Y. Kobayashi, S. Hirose, M. Saigan, Y. Enta, T. Ishizone, K. Nakamura, M. Hata and N. Tada, "Implications of the En Face View of Transcatheter Heart Valves for Coronary Access Post-TAVR," JACC: Cardiovascular Interventions, 16 (24), pp. 3049–3051, 2023.
  7. T. Ishizone, T. Higuchi and K. Nakamura, "Ensemble kalman variational objective: a variational inference framework for sequential variational auto-encoders," Nonlinear Theory and Its Applications, 14, 4, pp.691-717, 2023.
  8. H. Koyama, H. Okumura, A. M Ito, K. Nakamura, T. Otani, K. Kato and T. Fujimori, "Effective mechanical potential of cell-cell interaction explains three-dimensional morphologies during early embryogenesis," PLoS computational biology, 19(8), e1011306, 2023.
  9. 石曽根毅,樋口知之,中村和幸,「生産ラインにおける異常検知・非定常サイクル同定のオンラインシステム」 計測自動制御学会論文集,Vol. 59, No.7, 2023.
  10. T. Ishizone and K. Nakamura, "Real-time Linear Operator Construction and State Estimation with the Kalman Filter," Journal of Information Processing, Vol. 30, pp. 888-897, 2022.
  11. T. Amemiya, K. Shibata, J. Takahashi, M. Watanabe, S. Nakata, K. Nakamura and T. Yamaguchi, "Glycolytic oscillations in HeLa cervical cancer cell spheroids," The FEBS journal, online, doi:10.1111/febs.16454, 2022.
  12. S. Kubo, S. Kato, K. Nakamura, N. Kodera, S. Takada, "Resolving the data asynchronicity in high-speed atomic force microscopy measurement via the Kalman Smoother," Scientific reports, 10, 18393, 2020.
  13. 保利武志,中村和幸,嵯峨山茂樹,「楽譜情報を用いた高時間分解能 Audio-to-MIDI 変換」,情報処理学会論文誌, Vol.60, No.11, pp. 1–14, 2019.
  14. 中村要介, 小池俊雄, 阿部紫織, 中村和幸, 佐山敬洋, 池内幸司,「粒子フィルタを適用したRRIモデルによる河川水位予測技術の開発」, 土木学会論文集B1(水工学),Vol. 74, No. 5, I_1381-I_1386, 2018.
  15. 勝山翔生,谷口健司,中村和幸,「逐次型データ同化手法の応用によるアンサンブル降雨予測情報の改善」, 土木学会論文集B1(水工学),Vol. 74, No. 5, I_253-I_258, 2018.
  16. N. Sviridova, T. Zhao, K. Aihara, K. Nakamura and A. Nakano, "Photoplethysmogram at green light: Where does chaos arise from?, Chaos, Solitons & Fractals, Vol. 116, pp. 157-165, 2018.
  17. 奥野拓也,中村和幸,「状態空間モデルによる購買間隔の規則性の推定」, オペレーションズ・リサーチ, Vol. 63, No. 2, pp. 83-90, 2018.
  18. 奥野拓也,中村和幸,「個人別セールスプロモーション効果の推定」,情報処理学会論文誌数理モデル化と応用(TOM), Vol. 9, No. 3, pp. 61-74 (2016年12月14日) , 2016.
  19. N. Sviridova and K. Nakamura, "Local noise sensitivity: Insight into the noise effect on chaotic dynamics," Chaos, Vol. 26, 123102, DOI: 10.1063/1.4970322, 2016.
  20. A. Kimura, A. Celani, H. Nagao, T. Stasevich and K. Nakamura, "Estimating cellular parameters through optimization procedures: elementary principles and applications," Frontiers in Physiology, 03 March 2015 (online), DOI: 10.3389/fphys.2015.00060, 2015.
  21. Y. Yura, H. Takayasu, K. Nakamura, and M. Takayasu, "Rapid detection of the switching point in a financial market structure using the particle filter," Journal of Statistical Computation and Simulation, Vol.84, No.10, DOI: 10.1080/00949655.2013.781603, 2014.
  22. Y. Ohya and K. Nakamura, "A New Setting Method of Friction Parameter for Real-Time Tsunami Run-Up Simulations Based on Inundation Observation," Theoretical and Applied Mechanics Japan, Vol. 62, pp. 167-178, 2014.
  23. 大家義登,中村和幸,「津波減災のための浸水シミュレーションと観測データの活用」,応用数理,Vol.23, No.3, pp.16-27, 2013.
  24. A. Murakami, T. Shuku, S. Nishimura, K. Fujisawa, and K. Nakamura, "Data assimilation using the particle filter for identifying the elasto-plastic material properties of geomaterials," International Journal for Numerical and Analytical Methods in Geomechanics, Vol.37, No.11, Doi: 10.1002/nag.2125, 2013.
  25. T. Shuku, A. Murakami, S. Nishimura, K. Fujisawa, and K. Nakamura, "Parameter identification for Cam-clay model in partially loading tests using the particle filter," Soils and Foundations, Vol.52, No.2, pp.279-298, 2012.
  26. H. Koyama, T. Umeda, K Nakamura, T. Higuchi and A. Kimura, "A high-resolution shape fitting and simulation demonstrated equatorial cell surface softening during cytokinesis and its promotive role in cytokinesis," PLoS ONE 7(2), e31607, 2012.
  27. 徳永旭将,池田大輔,中村和幸,樋口知之,吉川顕正,魚住禎司,藤本晶子,森岡昭,湯元清文, 「変化点検出を応用した時系列データからの突発現象の前兆検出アルゴリズム」,情報処理学会論文誌数理モデル化と応用(TOM),Vol. 4,No. 3,pp. 14-34, 2011.
  28. T. Tokunaga, D. Ikeda, K. Nakamura, T. Higuchi, A. Yoshikawa, T. Uozumi, A. Fujimoto, A. Morioka, K. Yumoto and CPMN group, "Onset Time Determination of Precursory Events of Singular Spectrum Transformation," International Journal of Circuits, Systems and Signal processing, vol.5, pp. 46-60, 2011.
  29. 珠玖隆行,村上章,西村伸一,藤沢和謙,中村和幸,「粒子フィルタによる神戸空港島沈下挙動のデータ同化」,応用力学論文集,第13巻,土木学会,pp. 67-77, 2010.
  30. N. Mitsui, T. Hori, S. Miyazaki, and K. Nakamura, "Constraining interplate frictional parameters by using limited terms of synthetic observation data for afterslip: a preliminary test of data assimilation," Theoretical and Applied Mechanics Japan, Vol. 58, pp. 113-120, 2010.
  31. D. Inazu, T. Higuchi, and K. Nakamura, "Optimization of boundary condition and physical parameter in an ocean tide model using an evolutionary algorithm," Theoretical and Applied Mechanics Japan, Vol. 58, pp. 101-112, 2010.
  32. 村上章,西村伸一,藤澤和謙,中村和幸,樋口知之, 「粒子フィルタによる地盤解析のデータ同化」,応用力学論文集,第12巻,土木学会,2009.
  33. D. Inazu, T. Sato, S. Miura, Y. Ohta, K. Nakamura, H, Fujimoto, C. F. Larsen, and T. Higuchi, "Accurate ocean tide modeling in southeast Alaska and large tidal dissipation around Glacier Bay," Journal of Oceanography, Vol. 65, No. 3, pp. 335-347, 2009.
  34. K. Nakamura, N. Hirose, B.H. Choi, and T. Higuchi, "Particle filtering in data assimilation and its application to estimation of boundary condition of tsunami simulation model," Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, edited by S. K. Park and L. Xu, pp. 353-366, Springer, 2009.
  35. 中野慎也,上野玄太,中村和幸,樋口知之, 「Merging particle filter とその特性」統計数理,Vol.56, No. 2, pp. 225—234, 2008.
  36. K. Nakamura and T. Tsuchiya, "A Recursive Recomputation Approach for Smoothing in Nonlinear State-Space Modeling: An Attempt for Reducing Space Complexity," IEEE Transactions on Signal Processing, Vol. 55, No. 11, pp. 5167-5178, 2007.
  37. 中村和幸,上野玄太,樋口知之,「データ同化:その概念と計算アルゴリズム」 統計数理[研究詳解],53巻2号,pp. 211-229, 2005.

Proceedings(査読あり)

  1. T. Ishizone, T. Higuchi, K. Okusa and K. Nakamura, "An Online System of Detecting Anomalies and Estimating Cycle Times for Production Lines," IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, 2022.
  2. H. Oshima, T. Ishizone, K. Nakamura and T. Higuchi, "Occupancy Detection for General Households by Bidirectional LSTM with Attention," IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, 2022.
  3. Y. Han and K. Nakamura, "The Influence of Velocity Refresh in Sequential MCMC with the Invertible Particle Flow and Discrete Bouncy Particle Sampler," Proceedings of the 53rd ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 18-23, 2022.
  4. T. Ishizone and K. Nakamura, "LSLOCK: A method to estimate state space model by spatiotemporal continuity," CONTROLO 2020: Proceedings of the 14th APCA International Conference on Automatic Control and Soft Computing, pp. 342-351, 2020.
  5. H. Kawata, T. Hori and K. Nakamura, "Evaluation System for Groove Feelings Evoked by Drum Sounds," Proceedings of the 50th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 142-146, 2019.
  6. T. Kimura and K. Nakamura, "Bayesian Estimation of Deer Population DynamicsUsing Hamiltonian Monte Carlo Algorithm," Proceedings of the 50th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 19-24, 2019.
  7. T. Hori, K. Nakamura and S. Sagayama, "Multiresolutional Hierarchical Bayesian NMF for Detailed Audio Analysis of Music Performances," Proceedings of APSIPA Annual Summit and Conference (ASC), 2018.
  8. Y. Shimazaki, K. Nakamura and Y. Tanokura, "Analysis of Exchange Rates and Gold Price Using Relative Noise Contribution," Proceedings of the 49th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 142-146, 2018.
  9. T. Hori, K. Nakamura and S. Sagayama, "Music Chord Recognition From Audio Data Using Bidirectional Encoder-decoder LSTMs," Proceedings of APSIPA Annual Summit and Conference (ASC), 2017.
  10. T. Hori, K. Nakamura and S. Sagayama, "Jazz Piano Trio Synthesizing System Based on HMM and DNN," Proceedings of 14th Sound and Music Computing Conference, pp. 153-158, 2017.
  11. Y. Kono and K. Nakamura, "Prediction System of Subway Traffic Flow and Appropriate Parameters Shifting," Proceedings of the 48th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 168-173, 2017.
  12. T. Hori, K. Nakamura and S. Sagayama, "Automatic selection and concatenation system for jazz piano trio using case data," Proceedings of the 48th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 98-104, 2017.
  13. K. Nakamura and Y. Kono, "Fast and stable estimation of macroscopic parameters in particle systems by data assimilation," Proceedings of the 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, pp. 132-136, 2016.
  14. Y. Ohya, K. Nakamura, and T. Tokunaga, "Extraction of Groove Feelings from Drum Data using Non-Negative Matrix Factorization," Proceedings of SCIS-ISIS 2012, pp. 125-130, 2012.
  15. Y. Yura, H. Takayasu, K. Nakamura, and M. Takayasu, "Instability Caused by the Cubic Potential in the Foreign Exchange Marcket observed at the Intervention by the Bank of Japan", Proceedings of 15th International Conference on Information Fusion, pp. 2147-2153, 2012.
  16. K. Nakamura, S. Yamamoto, and M. Honda, "Sequential Data Assimilation in Geotechnical Engineering and Its Application to Seepage Analysis," Proceedings of 14th International Conference on Information Fusion, pp. 544-549, 2011.
  17. T. Tokunaga, D. Ikeda, K. Nakamura, T. Higuchi, A. Yoshikawa, T. Uozumi, A. Fujimoto, A. Morioka, K. Yumoto, and CPMN group, "Detecting Precursory Events in Time Series Data by an Extension of Singular Spectrum Transformation," Proceedings of the 10th WSEAS International Conference on Applied Computer Science, pp. 366-374, 2011.
  18. K. Nakamura, R. Yoshida, M. Nagasaki, S. Miyano, and T. Higuchi, "Parameter estimation of in silico biological pathways with particle filtering towards a petascale computing," The Proceedings of 14th Pacific Symposium on Biocomputing, pp. 227-238, 2009.
  19. K. Nakamura, T. Higuchi, and N. Hirose, "Application of Particle Filter to Identification of Tsunami Simulation Model," Proceedings of Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems, 2006.

Book chapter(査読あり)

  1. T. Amemiya, K. Shibata, M. Watanabe, S. Nakata, K. Nakamura and T. Yamaguchi, "Glycolytic Oscillations in Cancer Cells," In Understanding Complex Systems, pp. 245-259, Springer Science and Business Media Deutschland GmbH, 2021.

論文(査読なし)・解説記事等

  1. 藤岡徳穂,中村和幸,「ベイズ推定を用いた地理的プロファイリング」 シミュレーション, Vol. 38, No. 3, 2019.
  2. 中村和幸,「データ同化のこれまでとこれから」 シミュレーション,Vol. 38, No. 1, pp. 21-27, 2019.
  3. 中村和幸,「データ同化による不確かさを持つ現象の理解と予測ならびにモデリングへの展開」 数理解析研究所講究録,No. 2057,pp. 59-66, 2017.
  4. 中村和幸,「統計的時系列解析4:グラフィカルモデルとデータ同化」 応用数理,Vol. 24, No. 4, pp. 29-35, 2014.
  5. 中村和幸,「統計的時系列解析3:非線形・非ガウス状態空間モデル」 応用数理,Vol. 24, No. 3, pp. 33-38, 2014.
  6. 中村和幸,「統計的時系列解析2:状態空間モデル」 応用数理,Vol. 24, No. 2, pp. 26-31, 2014.
  7. 中村和幸,「統計的時系列解析1:定常性とARモデル」 応用数理,Vol. 24, No. 1, pp. 23-28, 2014.
  8. 樋口知之,中村和幸,「データ同化によるオンラインセンシングの高度化」 計測自動制御学会誌, Vol. 51, No. 9, 2012.
  9. 中村和幸,「状態推定」オペレーションズリサーチ, Vol. 55, No. 7, pp. 433-434, 2010.
  10. 中村和幸,樋口知之,「最近のベイズ理論の進展と応用[II] ─逐次ベイズとデータ同化─」 電子情報通信学会誌,Vol. 92, No.12. pp. 1062-1067, 2009.
  11. K. Nakamura, T. Higuchi, and N. Hirose, "Sequential Data Assimilation: Information Fusion of a Numerical Simulation and Large Scale Observation Data," Journal of Universal Computer Science, Vol. 12, pp. 608—626, 2006.

研究報告(主要なもののみ記載)

  1. 下村真生,中村和幸,「Black Average Drop: 医用画像に対する可視化選択指標」 研究報告コンピュータビジョンとイメージメディア(CVIM),2019-CVIM-218(16), 1-6, 2019.
  2. 河田洋人,保利武志,中村和幸,「位相情報を考慮したRNNによるドラム自動採譜」 研究報告音楽情報科学(MUS), 2019-MUS-122(27), 1-4, 2019.
  3. 保利武志,中村和幸,嵯峨山茂樹,「多重解像度NMFに基づく音響信号演奏詳細解析」 研究報告音楽情報科学(MUS), 2018-MUS-120(16), 1-6, 2019.
  4. 河田洋人,保利武志,中村和幸,「同時録音ドラム演奏音源に対するグルーヴ感の評価」 研究報告音楽情報科学(MUS), 2018-MUS-120(15), 1-5, 2018.
  5. 保利武志,中村和幸,嵯峨山茂樹,「特徴量軌跡の機械学習に基づくジャズセッションの自動生成」 研究報告音楽情報科学(MUS), 2017-MUS-116(12), 1-6, 2017.
  6. 保利武志,中村和幸,嵯峨山茂樹,「Encoder-decoderモデルとStacked bidirectional LSTMに基づく和声解析の検討」 研究報告音楽情報科学(MUS), 2017-MUS-115(33), 1-5, 2017.
  7. 保利武志,中村和幸,嵯峨山茂樹,「統計的に学習可能な自動ジャズセッションシステムのための数理モデル・演奏特徴量・事例活用の検討」 研究報告音楽情報科学(MUS), 2016-MUS-112(18), 1-6, 2016.
  8. 稲津大祐,樋口知之,中村和幸,「進化アルゴリズムを用いた海底地形データセットの最適化」 研究報告数理モデル化と問題解決(MPS), 2009(19(2009-MPS-73)), 29-32, 2009.

著書

  1. 基幹講座 数学 統計学,東京図書,2017.
  2. 現象数理学の冒険(三村昌泰編著),「地球科学の数理」(pp. 95-123)分担執筆,明治大学出版会,2015.
  3. 新版 信頼性ハンドブック(日本信頼性学会編),「2.7.1 データ同化とは」(pp. 458-462)担当,日科技連,2014.
  4. データ同化入門―次世代のシミュレーション技術―(樋口知之編著),5章ならびに9章分担執筆,朝倉書店,2011.

AltStyle によって変換されたページ (->オリジナル) /