研究者詳細 - 徳永　旭将

論文 - 徳永　旭将

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Extraction of groove feelings from drum data using non-negative matrix factorization 査読有り

Ohya Y., Nakamura K., Tokunaga T.

6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 125 - 130 2012年12月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In this paper, we propose the algorithm to extract the groove feeling from drum data. In the previous researches, extraction of the groove feeling requires pre-separated acoustic sources. We employed non-negative matrix factorization (NMF) to make separated information on hitting time from monaural wave data in which multiple acoustic sources are mixed. We applied our algorithm to a drum data and obtained a difference of time fluctuations among instruments, which relates to groove feeling and impression. The result implies that the proposed algorithm can extract some sensitive differences of nuance of drumming. © 2012 IEEE.

DOI： 10.1109/SCIS-ISIS.2012.6505312

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Separation of stationary and non-stationary sources with a generalized eigenvalue problem 査読有り

Hara S., Kawahara Y., Washio T., von Bünau P., Tokunaga T., Yumoto K.

Neural Networks 33 7 - 20 2012年09月

記述言語：英語掲載種別：研究論文（学術雑誌）

Non-stationary effects are ubiquitous in real world data. In many settings, the observed signals are a mixture of underlying station ary and non-stationary sources that cannot be measured directly. For example, in EEG analysis, electrodes on the scalp record the activity from several sources located inside the brain, which one could only measure invasively. Discerning stationary and non-stationary contributions is an important step towards uncovering the mechanisms of the data generating system. To that end, in Stationary Subspace Analysis (SSA), the observed signal is modeled as a linear superposition of stationary and non-stationary sources, where the aim is to separate the two groups in the mixture. In this paper, we propose the first SSA algorithm that has a closed form solution. The novel method, Analytic SSA (ASSA), is more than 100 times faster than the state-of-the-art, numerically stable, and guaranteed to be optimal when the covariance between stationary and non-stationary sources is time-constant. In numerical simulations on wide range of settings, we show that our method yields superior results, even for signals with time-varying group-wise covariance. In an application to geophysical data analysis, ASSA extracts meaningful components that shed new light on the Pi 2 pulsations of the geomagnetic field. © 2012 Elsevier Ltd.

DOI： 10.1016/j.neunet.2012.04.001

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Onset time determination of precursory events in time series data by an extension of Singular Spectrum Transformation 招待有り査読有り国際誌

Tokunaga T., Ikeda D., Nakamura K., Higuchi T., Yoshikawa A., Uozumi T., Fujimoto A., Morioka A., Yumoto K.

International Journal of Circuits, Systems and Signal Processing 5 ( 1 ) 46 - 60 2011年10月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

To predict an occurrence of extraordinary phenomena, such as earthquakes, failures of engineering systems and financial market crushes, it is important to identify precursory events in time series. However, existing methods are limited in their applicability for real world precursor detections. Recently, Ide and Inoue [1] have developed an SSA-based change-point detection method, called singular spectrum transformation (SST). SST is suitable for detecting various types of change-points, but real world precursor detections can be far more difficult than expected. In general, precursory events are observed as minute and less-visible fluctuations preceding an onset of massive fluctuations of extraordinary phenomena and therefore they are easily over-looked. To overcome this point, we extend the conventional SST to the multivariable SST. The originality of our strategy is in focusing on synchronism detections of precursory events in multiple sequences of univariate time series. We performed some experiments by using artificial data and showed the superiority of multivariable SST in detecting onset of precursory events. Furthermore, the superiority is also shown statistically in determining the onset of precursory events by using real world time series.

Scopus

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Identification of full-substorm onset from ground-magnetometer data by singular value transformation 査読有り

徳永旭将, 湯元清文, 魚住禎司, CPMNグループ

Memoirs of the Faculty of Science, Kyushu University. Series D, Earth and planetary sciences ( 九州大学大学院理学研究院 ) 32 ( 3 ) 63 - 73 2011年03月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（大学，研究機関等紀要）

Pi 2 magnetic pulsations observed on the ground are a good indicator of the auroral breakup. However, they have not only corresponding full-substorm onsets but also most pseudobreakups. Another well-known substorm related phenomenon observed on the ground is positive bays. In order to identify full-substorm onsets from ground-magnetometer data, we developed a new algorithm based on "Singular Spectrum Analysis(SSA)". The algorithm enables us to screen Pi 2 pulsations accompanied by the magnetic positive bay. We applied proposed algorithm to ground-magnetometer data and compared to the obtained results with Polar/UVI data. As a result, we succeeded in identifying 62% of the full-substorm onsets from ground-magnetometer data obtained in the nighttime sector between 21 and 03LT.

DOI： 10.5109/19197

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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査読有り国際誌

徳永旭将, 池田大輔, 中村和幸

情報処理学会研究報告 ( 東京 : 情報処理学会 ) 2010年度 ( 5 ) 1 - 6 2011年02月

AKR modulation and global Pi2 oscillation 査読有り国際誌

Uozumi T., Yumoto K., Tokunaga T., Solovyev S., Shevtsov B., Marshall R., Liou K., Ohtani S., Abe S., Ikeda A., Kitamura K., Yoshikawa A., Kawano H., Itonaga M.

Journal of Geophysical Research: Space Physics 116 ( 6 ) 2011年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this report we present a temporal relationship between ground Pi2 and auroral kilometric radiation (AKR). We analyzed six isolated substorm events, which were observed by the MAGDAS/CPMN ground magnetometer network and the plasma wave instrument onboard the Polar satellite. We found that the time derivative of the height-integrated AKR power and the ground Pi2 D component had the same periodicity and that the two were synchronized with each other. When the D component fluctuated with the same (opposite) polarity as the magnetic bay variation, the AKR power tended to increase (decrease) during the corresponding interval. An isolated substorm event (AE ∼ 40 nT), which occurred around 10:19 UT on 24 January1997, was selected for a detailed study. The behavior of the Pi2 event can be interpreted by the substorm current wedge (SCW) and Pi2 propagation models. It is confirmed that the midlatitude and high-latitude D component oscillations can be treated as a proxy of the SCW oscillations, whereas the H component oscillations exhibited some phase shifts by the propagation delay of the Pi2 waves. That is, the temporal relation between the time derivative of the AKR power and the ground Pi2 suggests that the height-integrated AKR power was modulated coherently with the SCW oscillations. Copyright 2011 by the American Geophysical Union.

DOI： 10.1029/2010JA016042

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Identification of full-substorm onset from ground-magnetometer data by singular value transformation 査読有り

徳永旭将

Memoirs of the Faculty of Sciences, Kyushu University, Series D, Earth and Planetary Sciences 32 63 - 73 2011年01月

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査読有り

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, CpmnGroup

研究報告バイオ情報学（BIO） 2010 ( 14 ) 1 - 6 2010年12月

担当区分：筆頭著者,　責任著者記述言語：日本語掲載種別：研究論文（国際会議プロシーディングス）

一般に，前兆現象は突発現象にそのものに比べて非常に目立ちにくく，その開始時刻は曖昧である．従来よく用いられてきた変化点検出法を適用した場合，このような微小で緩慢な変化は見逃されやすい．Tokunaga et al.1) では，Ide and Inoue2) の提案した特異スペクトル分析を応用した変化点検出法 (SST) を，多次元データを用いたアルゴリズム (MSST) へと拡張することで，鋭敏に前兆現象の開始時刻を推定出来ることを示した．MSST は，緩慢な変化も検出できる鋭敏な手法であるが，実データへの適用では誤検出が問題になる．本稿では，突発現象の大まかな開始時刻を予め検出し，さらに検出された時刻の前後で前兆現象の開始時刻と終了時刻を個別に探索することで，誤検出を劇的に減少させることができることを示す．

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CiNii Research

Detecting precursory events in time series data by an extension of singular spectrum transformation 査読有り国際誌

Tokunaga T., Ikeda D., Nakamura K., Higuchi T., Yoshikawa A., Uozumi T., Fujimoto A., Morioka A., Yumoto K.

International Conference on Applied Computer Science - Proceedings 366 - 374 2010年12月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

To predict an occurrence of extraordinary phenomena, such as earthquakes, failures of engineering system and financial market crushes, it is important to identify precursory events in time series. However, existing methods are limited in their applicability for real world precursor detections. Recently, Ide and Inoue [1] have developed an SSA-based change-point detection method, called singular spectrum transformation (SST). In this paper, we extend the SST so that it is applicable for real world precursor detections, focusing on the wide applicability of the conventional SST. Although the SST is suitable for detecting various types of change-points, detecting precursors can be far more difficult than expected because, in general, real world time series contains measurement noise and non-stationary trends. Furthermore, precursory events are usually observed as minute and less-visible fluctuations preceding an onset of massive fluctuations of extraordinary phenomena and therefore they are easily over-looked. To overcome this, we extend the conventional SST to the multivariable SST, focusing on the synchronism detection of precursory events in multiple sequences of univariate time series. First, we would like to define the problem setting of real world precursory detections and consider its difficulties. Second, the multivariable SST is introduced. Third, we apply SST to geomagnetic time series data and show the multivariable SST is more suitable than the conventional SST for real world precursor detections. Finally, we show further experimental results using artificial data to evaluate the reliability of SST-based precursor detections.

Scopus

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Detecting Precursory Events in Time Series Data by an Extension of Singular Spectrum Transformation 査読有り国際誌

徳永旭将

Proceedings of the 10th WSEAS International Conference on Applied Computer Science 366 - 374 2010年01月

Onset Time Determination of Precursory Events of Singular Spectrum Transformation 招待有り査読有り国際誌

徳永旭将

International Journal of Circuits, Systems and Signal processing 5 46 - 60 2010年01月

Propagation characteristics of Pi 2 pulsations observed at high- And low-latitude MAGDAS/CPMN stations: A statistical study 査読有り

Uozumi T., Abe S., Kitamura K., Tokunaga T., Yoshikawa A., Kawano H., Marshall R., Morris R.J., Shevtsov B.M., Solovyev S.I., McNamara D.J., Liou K., Ohtani S., Itonaga M., Yumoto K.

Journal of Geophysical Research: Space Physics 114 ( 11 ) 2009年11月

記述言語：英語掲載種別：研究論文（学術雑誌）

The objective of this study is to understand better the propagation of Pi 2 waves in the nighttime region. We examined Pi 2 oscillations that showed high correlation between high- and low-latitude Magnetic Data Acquisition System/Circum Pan-Pacific Magnetometer Network stations (correlation coefficient: |γ| ≥ 0.75). For each horizontal component (H and D) we examined the magnetic local time (MLT) dependence of the delay time of high-latitude Pi 2 oscillations that corresponds to the highest correlation with the low-latitude Pi 2 oscillation. We found the delay time of the high-latitude H showed remarkable MLT dependence, especially in the premidnight sector: we found that in the premidnight sector the high-latitude H oscillation tends to delay from the low-latitude oscillation (<100 s). On the other hand, the delay time of the high-latitude D oscillation was not significant (∼±10 s) in the entire nighttime sector. We propose a Pi 2 propagation model to explain the observed delay time of high-correlation highlatitude H. The model quantitatively explains the trend of the event distribution. We also examined the spatial distribution of high-correlation Pi 2 events relative to the center of auroral breakups. It was found that the high-correlation Pi 2 events tend to occur away from the center of auroral breakups by more than 1.5 MLT. The present result suggests that the high-correlation H component Pi 2 oscillations at high latitude are a manifestation of forced Alfvén waves excited by fast magnetosonic waves. Copyright 2009 by the American Geophysical Union.

DOI： 10.1029/2009JA014163

Scopus

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A new index to monitor temporal and long-term variations of the equatorial electrojet by MAGDAS/CPMN real-time data: EE-index 査読有り

Uozumi T., Yumoto K., Kitamura K., Abe S., Kakinami Y., Shinohara M., Yoshikawa A., Kawano H., Ueno T., Tokunaga T., McNamara D., Ishituka J.K., Dutra S.L.G., Damtie B., Doumbia V., Obrou O., Rabiu A.B., Adimula I.A., Othman M., Fairos M., Otadoy R.E.S.

Earth, Planets and Space 60 ( 7 ) 785 - 790 2008年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

A new index, EE-index (EDst, EU, and EL), is proposed to monitor temporal and long-term variations of the equatorial electrojet by using the MAGDAS/CPMN real-time data. The mean value of the H component magnetic variations observed at the nightside (LT = 18-06) MAGDAS/CPMN stations along the magnetic equatorial region is found to show variations similar to those of Dst; we defined this quantity as EDst. The EDst can be used as a proxy of Dst for the real-time and long-term geospace monitoring. By subtracting EDst from the H component data of each equatorial station, ir is possible to extract the Equatorial Electrojet and Counter Electrojetcomponents, which are defined as EU and EL, respectively. Copyright © The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS).

DOI： 10.1186/BF03352828

Scopus

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Global features of Pi 2 pulsations obtained by independent component analysis 査読有り国際誌

Tokunaga T., Kohta H., Yoshikawa A., Uozumi T., Yumoto K.

Geophysical Research Letters ( American Geophysical Union ) 34 ( 14 ) 2007年07月

担当区分：筆頭著者,　責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Ground Pi 2 pulsations are mixtures of several components reflecting (1) propagations of fast and shear Alfvén wave, (2) resonances of plasmaspheric/magnetospheric cavity and magnetic field lines, and (3) tansformations to ionospheric current systems. However, it has been unclear how they coupled with each other and how their signals are distributed at different latitudes. The present work is intended to pilot the future possibilities whether we can identify the global system of Pi 2 pulsations by Independent Component Analysis (ICA). We have successfully decomposed an isolated Pi 2 event on a quiet day observed at the CPMN stations into two components. One was the global oscillation that occurs from nightside high to equatorial latitudes with the common waveform and has an amplitude maximum at nightside high latitude. Another component was localized at nightside high latitudes. Its amplitudes were quite weak at low latitudes, but were enhanced near dayside dip equator. Copyright 2007 by the American Geophysical Union.

DOI： 10.1029/2007GL030174

Scopus

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High-top clouds play an efficient part in moisture transport to the Antarctic

Kazue Suzuki, Terumasa Tokunaga, Takashi Yamanouchi, Hideaki Motoyama

ESS Open Archive ( Wiley and Authorea ) 2022年08月

Identifying Snowfall Clouds at Syowa Station, Antarctica via a Convolutional Neural Network 査読有り国際誌

Kazue Suzuki, Masaki Shimomura, Kazuyuki Nakamura, Naohiko Hirasawa, Hironori Yabuki, Takashi Yamanouchi, Terumasa Tokunaga

Advances in Artificial Intelligence - Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2020) ( Springer International Publishing ) 1357 ( 1 ) 78 - 83 2021年07月

CNNを用いた南極・昭和基地に降雪をもたらす雲識別

鈴木香寿恵, 下村真生, 中村和幸, 平沢尚彦, 矢吹裕伯, 山内恭, 徳永旭将

人工知能学会全国大会論文集 ( 一般社団法人人工知能学会 ) 2020 ( 0 ) 3F1ES205 - 3F1ES205 2020年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

<p>近年の温暖化環境における南極氷床の涵養量の変動のふるまいは、地球全体の水収支に大きな影響を及ぼすことから関心が高まっているが，その厳しい環境や降雪量の観測自体が難しいという現状である。限定された観測データを組み合わせ降雪量推定モデルの開発を行ってきた。今回は南極・昭和基地において観測された降雪時の雲画像に対して、CNNを適用し，二値および三値の自動識別を試みた。「Atmospheric River」と呼ばれる高高度の連なる雲が降雪に寄与しているとし，その雲構造をもつ降雪時の画像を正例，その雲構造がない，もしくは画像視野が十分でない場合準正例とした。ネットワーク構造としてはVGG16にInception構造を加え，全結合層をGlobal Average Poolingに置き換えてパラメタ数を削減した。学習に対し正例138, 準正例477, 負例511のサンプルを用いた。二値問題には正例と準正例を正例として扱った。識別精度は，二値(三値)分類は71.00%(65.37%)であった。 Grad-CAMによる可視化結果は三値分類時に雲構造を捉えられている様子を示していた。</p>

DOI： 10.11517/pjsai.JSAI2020.0_3F1ES205

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CiNii Research

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計測，モデル，データ科学はどのように協調できるか？招待有り査読有り

徳永旭将

計測と制御 ( 公益社団法人計測自動制御学会 ) 58 ( 3 ) 166 - 170 2019年03月

ディープラーニングによる南極昭和基地周辺における降雪をもたらす雲の検出

鈴木香寿恵, 徳永旭将, 福地岬稀, 平沢尚彦, 山内恭

雪氷研究大会講演要旨集 ( 公益社団法人日本雪氷学会／日本雪工学会 ) 2019 ( 0 ) 119 2019年01月

線虫の全中枢神経細胞活動データに対する因果性解析II

岩崎唯史, 佐藤博文, 大江紗, 久下小百合, 寺本孝行, 徳永旭将, 広瀬修, 豊島有, ジャンムンソン, 吉田亮, 飯野雄一, 石原健

日本物理学会講演概要集 ( 一般社団法人日本物理学会 ) 73.2 ( 0 ) 2315 - 2315 2018年01月

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