Faculty Profiles - TOKUNAGA Terumasa

Papers - TOKUNAGA Terumasa

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Global-Local Consistency for Cost-Effective Anomaly Localization with Point Annotations Reviewed International journal

Nakanishi Keiichi, Katafuchi Ryoya, Tokunaga Terumasa

2024 16th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI) 2024.10

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

Creating pixel-level ground-truth (GT) masks is quite costly for deep learning-based image segmentation. Specialists in areas such as anomaly detection and medical diagnostics face difficulties in producing many GT masks due to limited resources. To reduce this burden, we propose a cost-effective image segmentation framework with point annotations (CoSPA) that performs image segmentation with only point annotations. Point annotations refer to the partial and sparse labeled coordinates in an image. The key idea is to ensure consistency between the predictions for the same coordinates from the two different networks of CoSPA. This new consistency enables the CoSPA to improve segmentation performance and extend to semi-supervised learning. For the MVTec AD dataset, we verified the cost-effectiveness of CoSPA through an anomaly detection task. We demonstrated that the point annotating costs were reduced by 80% compared to creating GT masks. Subsequently, the CoSPA realized by 87% of the mean Intersection over Union (mIoU) achieved using the fully supervised method, DeepLabV3+. Moreover, the mIoU of CoSPA using only 30% of all point annotations defeated that of the unsupervised method, PaDiM. This study offers a new direction for economic anomaly localization.

CiNii Research

Other Link： https://kyutech.repo.nii.ac.jp/records/2000992

Bidirectional 2D Reservoir Computing for Image Anomaly Detection without any Training Reviewed International journal

Keiichi Nakanishi, Terumasa Tokunaga

Nonlinear Theory and Its Applications ( The Institute of Electronics, Information and Communication Engineers ) 15 ( 4 ) 838 - 850 2024.10

Mechanism of sensory perception unveiled by simultaneous measurement of membrane voltage and intracellular calcium Reviewed International journal

Terumasa Tokunaga, Noriko Sato, Mary Arai, Takumi Nakamura, Takeshi Ishihara

Communications Biology, ( Nature Portfolio (Springer Nature) ) 7 ( 1150 ) 2024.09

Authorship：Lead author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

Measuring neuronal activity is important for understanding neuronal function. Ca2+ imaging by genetically encoded calcium indicators (GECIs) is a powerful way to measure neuronal activity. Although it revealed important aspects of neuronal function, measuring the neuronal membrane voltage is important to understand neuronal function as it triggers neuronal activation. Recent progress of genetically encoded voltage indicators (GEVIs) enabled us fast and precise measurement of neuronal membrane voltage. To clarify the relation of the membrane voltage and intracellular Ca2+, we analyzed neuronal activities of olfactory neuron AWA in Caenorhabditis elegans by GCaMP6f (GECI) and paQuasAr3 (GEVI) responding to odorants. We found that the membrane voltage encodes the stimuli change by the timing and the duration by the weak semi-stable depolarization. However, the change of the intracellular Ca2+ encodes the strength of the stimuli. Furthermore, ODR- 3, a G-protein alpha subunit, was shown to be important for stabilizing the membrane voltage. These results suggest that the combination of calcium and voltage imaging provides a deeper understanding of the information in neural circuits.

DOI： 10.1038/s42003-024-06778-2

Scopus

Other Link： https://link.springer.com/article/10.1038/s42003-024-06778-2

Global-Local Consistency for Cost-Effective Anomaly Localization with Point Annotations Reviewed International journal

Keiichi Nakanishi, Ryoya Katafuchi, Terumasa Tokunaga

The proceedings of 16th IIAI International Congress on Advanced Applied Informatics ( IEEE Computer Society ) 53 - 57 2024.07

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

日本高松 2024.07.06 - 2024.07.12

DOI： 10.1109/IIAI-AAI63651.2024.00019

Kyutacar

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85208092849&origin=inward

Layer-wise External Attention by well-localized attention map for efficient deep anomaly detection Invited Reviewed International journal

Keiichi Nakanishi, Ryo Shiroma, Tokihisa Hayakawa, Ryoya Katafuchi, Terumasa Tokunaga

SN Computer Science ( Springer Nature ) 592 ( 5 ) 2024.05

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

The external attention mechanism offers a promising approach to enhance image anomaly detection (Hayakawa et al., in: IMPROVE, pp. 100-–110, 2023). Nevertheless, the effectiveness of this method is contingent upon the judicious selection of an intermediate layer with external attention. In this study, we performed a comprehensive series of experiments to clarify the mechanisms through which external attention improves detection performance. We assessed the performance of the LEA-Net (Hayakawa et al., in: IMPROVE, pp. 100–110, 2023), which implements layer-wise external attention, using MVTec AD and Plant Village datasets. The detection performances of the LEA-Net were compared with that of the baseline model under different anomaly maps generated by three unsupervised approaches. In addition, we investigated the relationship between the detection performance of LEA-Net and the selection of an attention point, which means an intermediate layer where external attention is applied. The findings reveal that the synergy between the dataset and the generated anomaly map influenced the effectiveness of the LEA-Net. For poorly localized anomaly maps, the selection of the attention point becomes a pivotal factor in determining detection efficiency. At shallow attention points, a well-localized attention map successfully notably improves the detection performance. For deeper attention points, the overall intensity of the attention map is essential; this intensity can be substantially amplified by layer-wise external attention, even for a low-intensity anomaly map. Overall, the results suggest that for layer-wise external attention, the positional attributes of anomalies hold greater significance than the overall intensity or visual appearance of the anomaly map.

DOI： 10.1007/s42979-024-02912-3

Kyutacar

Other Link： https://www.scopus.com/record/display.uri?eid=2-s2.0-85194873765&origin=resultslist

Layer-Wise External Attention by Well-Localized Attention Map for Efficient Deep Anomaly Detection Invited Reviewed International journal

Nakanishi Keiichi, Shiroma Ryo, Hayakawa Tokihisa, Katafuchi Ryoya, Tokunaga Terumasa

SN Computer Science 5 ( 5 ) 592 2024.05

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

CiNii Research

Other Link： https://kyutech.repo.nii.ac.jp/records/2000766

Bidirectional 2D reservoir computing for image anomaly detection without any training Reviewed International journal

Nakanishi K., Tokunaga T.

Nonlinear Theory and its Applications, IEICE 15 ( 4 ) 838 - 850 2024.01

Layer-wise External Attention for Efficient Deep Anomaly Detection Reviewed

Tokihisa Hayakawa, Keiichi Nakanishi, Ryoya Katafuchi, Terumasa Tokunaga

Proceedings of the 3rd International Conference on Image Processing and Vision Engineering 100 - 110 2023.01

Behavioral forgetting of olfactory learning is mediated by interneuron-regulated network plasticity in Caenorhabditis elegans Reviewed International journal

Jamine Teo, Itsuki Kurokawa, Yuuki Onishi, Noriko Sato, Tomohiro Kitazono, Terumasa Tokunaga, Manabi Fujiwara, Takeshi Ishihara

eNeuro ( the Society for Neuroscience ) 9 ( 4 ) 2022.08

Language：English Publishing type：Research paper (scientific journal)

Forgetting is important for animals to manage acquired memories to enable adaptation to changing environments; however, the neural network in mechanisms of forgetting is not fully understood. To understand the mechanisms underlying forgetting, we examined olfactory adaptation, a form of associative learning, in Caenorhabditis elegans (C. elegans). The forgetting of diacetyl olfactory adaptation in C. elegans is regulated by secreted signals from AWC sensory neurons via the TIR-1/JNK-1 pathway. These signals cause a decline of the sensory memory trace in AWA neurons where diacetyl is mainly sensed. To further understand the neural network that regulates this forgetting, we investigated the function of interneurons downstream of AWA and AWC neurons. We found that a pair of interneurons, AIA, is indispensable for the proper regulation of behavioral forgetting of diacetyl olfactory adaptation. Loss of or inactivation of AIA caused the impairment of the chemotaxis recovery after adaptation without causing severe chemotaxis defects in naïve animal. AWA Ca2+ imaging analyses suggested that loss or inactivation of AIA interneurons did not affect the decline of the sensory memory trace after the recovery. Furthermore, AIA responses to diacetyl were observed in naïve and after the recovery, but not just after the conditioning, suggesting that AIA responses after the recovery are required for the chemotaxis to diacetyl. We propose that the functional neuronal circuit for attractive chemotaxis to diacetyl is changed temporally at the recovery phase so that AIA interneurons are required for chemotaxis, although AIAs are dispensable for attractive chemotaxis to diacetyl in naïve animals.

DOI： https://doi.org/10.1523/ENEURO.0084-22.2022

Other Link： https://www.eneuro.org/content/early/2022/08/17/ENEURO.0084-22.2022

半教師あり二値分類のためのクラス事前確率を用いたコスト関数の提案 Reviewed

中西慶一, 徳永旭将

第25回画像の認識・理解シンポジウム ( 情報処理学会コンピュータビジョンとイメージメディア(CVIM)研究会 ) 2022.07

Authorship：Last author,　Corresponding author Language：Japanese Publishing type：Research paper (conference, symposium, etc.)

日本姫路 2022.07.25 - 2022.07.28

本稿は半教師あり二値分類のための新しいコスト関数を提案する. 提案するコスト関数は, Focal Loss を半教師あり分類のために拡張した損失関数とクラス事前確率罰則項から構成される. クラス事前確率罰則項を導入することで, ラベルなしデータにおける正例の割合がわかる場合, その事前情報を直接的に推論に活用することが可能である. 提案するコスト関数の有用性を評価するため, CIFAR-10 を用いた画像二値分類試験を行った. その結果, 少量のラベルありデータセットや不均衡なデータセットにおいて, 提案するコスト関数は既存のコスト関数と比べて優れた性能を示すことを確認した.

Other Link： https://sites.google.com/view/miru2022/program#h.44rbhnwbmvlj

Behavioral Forgetting of Olfactory Learning Is Mediated by Interneuron-Regulated Network Plasticity in Caenorhabditis elegans Reviewed

Teo J.H.M., Kurokawa I., Onishi Y., Sato N., Kitazono T., Tokunaga T., Fujiwara M., Ishihara T.

eNeuro 9 ( 4 ) 2022.07

Signal and Noise Separation from Satellite Magnetic Field Data through Independent Component Analysis: Prospect of Magnetic Measurements without Boom and Noise Source Information Reviewed International journal

Shun Imajo, Masahito Nosé, Mari Aida, Haruhisa Matsumoto, Nana Higashio, Terumasa Tokunaga , Ayako Matsuoka

Journal of Geophysical Research: Space Physics ( American Geophysical Union ) 126 ( 5 ) 2021.04

Language：English Publishing type：Research paper (scientific journal)

We propose an application of the independent component analysis (ICA) to separate satellite-induced time-varying stray fields from magnetic field data obtained using onboard multiple magnetometers. The ICA is a method for estimating source signals at multiple sites so that the estimated source signals can become statistically independent of each other. Since stray field variations are statistically independent of external natural field variations, the ICA method is expected to separate the natural variations from stray fields. Thus, we applied the ICA to magnetic field data from the first Quasi-Zenith Satellite, which has two triaxial fluxgate magnetometers, without using an extendable boom. First, we removed the long-period trend from the original data to create detrended data. Then, we applied the FastICA algorithm to the detrended data and obtained six independent components (ICs). The stray fields were successfully separated into three ICs (noise ICs), and the natural signals were represented by the other three ICs (signal ICs). Finally, we restored the observed signals from the signal ICs, and confirmed that the natural phenomena variations were not altered by the processing step. We also proposed a selection method of the noise ICs using the C coefficient, which is the coefficient of the variance of the mixing vectors. There was a large difference in C between the ICs whose C coefficients are the largest 3rd and 4th ones. Overall, these results demonstrate the possibility that the ICA method can support for boom-less magnetic observations in future satellite missions.

DOI： 10.1029/2020JA028790

Scopus

Other Link： https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020JA028790

Image-based Plant Disease Diagnosis with Unsupervised Anomaly Detection based on Reconstructability of Colors Reviewed International journal

Katafuchi, R. and Tokunaga, T.

In Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE ( SciTePress ) 112 - 120 2021.04

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

Virtual Virtual 2021.04.28 - 2021.04.30

This paper proposes an unsupervised anomaly detection technique for image-based plant disease diagnosis. The construction of large and publicly available datasets containing labeled images of healthy and diseased crop plants led to growing interest in computer vision techniques for automatic plant disease diagnosis. Although supervised image classifiers based on deep learning can be a powerful tool for plant disease diagnosis, they require a huge amount of labeled data. The data mining technique of anomaly detection includes unsupervised approaches that do not require rare samples for training classifiers. We propose an unsupervised anomaly detection technique for image-based plant disease diagnosis that is based on the reconstructability of colors; a deep encoder-decoder network trained to reconstruct the colors of healthy plant images should fail to reconstruct colors of symptomatic regions. Our proposed method includes a new image-based framework for plant disease detection that u tilizes a conditional adversarial network called pix2pix and a new anomaly score based on CIEDE2000 color difference. Experiments with PlantVillage dataset demonstrated the superiority of our proposed method compared to an existing anomaly detector at identifying diseased crop images in terms of accuracy, interpretability and computational efficiency.

DOI： 10.5220/0010463201120120

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85115692116&origin=inward

Cohesive and anisotropic vascular endothelial cell motility driving angiogenic morphogenesis Reviewed International journal

Takubo Naoko, Yura Fumitaka, Naemura Kazuaki, Yoshida Ryo, Tokunaga Terumasa, Tokihiro Tetsuji, Kurihara Hiroki

Scientific Reports 9 ( 1 ) 9304-1 - 9304-9 2019.12

Language：English Publishing type：Research paper (scientific journal)

Vascular endothelial cells (ECs) in angiogenesis exhibit inhomogeneous collective migration called “cell mixing”, in which cells change their relative positions by overtaking each other. However, how such complex EC dynamics lead to the formation of highly ordered branching structures remains largely unknown. To uncover hidden laws of integration driving angiogenic morphogenesis, we analyzed EC behaviors in an in vitro angiogenic sprouting assay using mouse aortic explants in combination with mathematical modeling. Time-lapse imaging of sprouts extended from EC sheets around tissue explants showed directional cohesive EC movements with frequent U-turns, which often coupled with tip cell overtaking. Imaging of isolated branches deprived of basal cell sheets revealed a requirement of a constant supply of immigrating cells for ECs to branch forward. Anisotropic attractive forces between neighboring cells passing each other were likely to underlie these EC motility patterns, as evidenced by an experimentally validated mathematical model. These results suggest that cohesive movements with anisotropic cell-to-cell interactions characterize the EC motility, which may drive branch elongation depending on a constant cell supply. The present findings provide novel insights into a cell motility-based understanding of angiogenic morphogenesis.

DOI： 10.1038/s41598-019-45666-2

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85068037379&origin=inward

SPF-CellTracker: Tracking Multiple Cells with Strongly-Correlated Moves Using a Spatial Particle Filter Reviewed International journal

Hirose O., Kawaguchi S., Tokunaga T., Toyoshima Y., Teramoto T., Kuge S., Ishihara T., Iino Y., Yoshida R.

IEEE/ACM Transactions on Computational Biology and Bioinformatics ( Institute of Electrical and Electronics Engineers Inc. ) 15 ( 6 ) 1822 - 1831 2018.11

Phase analysis of whole-brain activity data in C. elegans

Iwasaki Y., Teramoto T., Oe S., Tokunaga T., Hirose O., Wu S., Toyoshima Y., Jang M. S., Yoshida R., Iino Y., Ishihara T.

Meeting Abstracts of the Physical Society of Japan ( The Physical Society of Japan ) 72.1 ( 0 ) 2817 - 2817 2017.01

Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space Reviewed International journal

Toyoshima Y., Tokunaga T., Hirose O., Kanamori M., Teramoto T., Jang M.S., Kuge S., Ishihara T., Yoshida R., Iino Y.

PLoS Computational Biology ( Public Library of Science ) 12 ( 6 ) 2016.06

Automated detection and tracking of many cells by using 4D live-cell imaging data Reviewed

Tokunaga T., Hirose O., Kawaguchi S., Toyoshima Y., Teramoto T., Ikebata H., Kuge S., Ishihara T., Iino Y., Yoshida R.

Bioinformatics ( Oxford University Press ) 30 ( 12 ) 2014.06

3次元動画像内の非常に多数の細胞領域を自動追跡するための粒子フィルタ手法の開発

広瀬修, 川口翔太郎, 徳永旭将, 豊島有, 寺本孝行, 佐藤賢二, 池端久貴, 佐藤博文, 久下小百合, 石原健, 飯野雄一, 吉田亮

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 ) JSAI2014 ( 0 ) 2C32in - 2C32in 2014.01

Language：Japanese Publishing type：Research paper (conference, symposium, etc.)

<p>細胞動画像の典型的な特徴として多数の追跡対象物が密に存在し視覚的に類似していることが挙げられる．このような動画像に対し標準的な粒子フィルタを利用した場合，本来の追跡対象を別の対象物と誤認し追跡に容易に失敗する．この問題に対し多数の細胞の共変動性に着目し追跡のための補助情報としてこれを利用することで追跡精度の向上を目指す．</p>

DOI： 10.11517/pjsai.jsai2014.0_2c32in

CiNii Article

CiNii Research

Data Assimilation for Reconstructing a Whole Neuronal System of C. Elegans : The Current State and Issue(<Special Feature>Big Data and Data Assimilation) Invited Reviewed

32 ( 4 ) 287 - 294 2013.12

Extraction of groove feelings from drum data using non-negative matrix factorization Reviewed

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 2012.12

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

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

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84877794120&origin=inward

Separation of stationary and non-stationary sources with a generalized eigenvalue problem Reviewed

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

Neural Networks 33 7 - 20 2012.09

Language：English Publishing type：Research paper (scientific journal)

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

Scopus

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Onset time determination of precursory events in time series data by an extension of Singular Spectrum Transformation Invited Reviewed International journal

International Journal of Circuits, Systems and Signal Processing 5 ( 1 ) 46 - 60 2011.10

Authorship：Lead author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80053970902&origin=inward

Identification of full-substorm onset from ground-magnetometer data by singular value transformation Reviewed

Tokunaga Terumasa, Yumoto Kiyohumi, Uozumi Teiji, CPMN Group

Memoirs of the Faculty of Science, Kyushu University. Series D, Earth and planetary sciences ( Faculty of Science, Kyushu University ) 32 ( 3 ) 63 - 73 2011.03

Authorship：Lead author,　Corresponding author Language：English Publishing type：Research paper (bulletin of university, research institution)

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

CiNii Article

CiNii Research

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 Reviewed International journal

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 2011.02

AKR modulation and global Pi2 oscillation Reviewed International journal

Uozumi T., Yumoto K., Tokunaga T., Solovyev S.I., Shevtsov B.M., 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 ) 2011.01

Identification of full-substorm onset from ground-magnetometer data by singular value transformation Reviewed

徳永旭将

Memoirs of the Faculty of Sciences, Kyushu University, Series D, Earth and Planetary Sciences 32 63 - 73 2011.01

AKR modulation and Global Pi 2 oscillation : Jan.24, 1997 event Reviewed International journal

徳永旭将

Journal of Geophysical Research 印刷中 2011.01

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 Reviewed

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 2010.12

Authorship：Lead author,　Corresponding author Language：Japanese Publishing type：Research paper (international conference proceedings)

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．

CiNii Article

CiNii Research

Detecting precursory events in time series data by an extension of singular spectrum transformation Reviewed International journal

366 - 374 2010.12

Detecting Precursory Events in Time Series Data by an Extension of Singular Spectrum Transformation Reviewed International journal

徳永旭将

Proceedings of the 10th WSEAS International Conference on Applied Computer Science 366 - 374 2010.01

Onset Time Determination of Precursory Events of Singular Spectrum Transformation Invited Reviewed International journal

徳永旭将

International Journal of Circuits, Systems and Signal processing 5 46 - 60 2010.01

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

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 ) 2009.11

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=72149099064&origin=inward

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

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 2008.01

Global features of Pi 2 pulsations obtained by independent component analysis Reviewed International journal

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

Geophysical Research Letters ( American Geophysical Union ) 34 ( 14 ) 2007.07

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 ) 2022.08

Identifying Snowfall Clouds at Syowa Station, Antarctica via a Convolutional Neural Network Reviewed International journal

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 2021.07

Language：English Publishing type：Research paper (scientific journal)

Japan オンライン

This study evaluated the impact of Atmospheric River (AR) clouds on snowfall amounts based on limited observation data to estimate the surface mass balance (SMB) of Antarctica. To accomplish this, we attempted to identify the snowfall cloud at Syowa Station, Antarctica. We constructed a new convolutional neural network (CNN) architecture with multinomial and binary classifications for National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) images over five years. The CNN was based on VGG16, and concatenate layers were added as the inception module. We replaced all the convolution layers with global average pooling to reduce the number of parameters. Based on the positive CNN sample re- sult, the multinomial classification emphasized the entire cloud structure, while the binary classification focused on cloud continuity. The results indicated accuracies of 71.00% and 65.37% for binary and multinomial classifications, respectively.

DOI： 10.1007/978-3-030-73113-7_7

Other Link： https://link.springer.com/chapter/10.1007/978-3-030-73113-7_7

Identifying the Snowfall Cloud at Syowa Station, Antarctica via a Convolutional Neural Network

SUZUKI Kazue, SHIMOMURA Masaki, NAKAMURA Kazuyuki, HIRASAWA Naohiko, YABUKI Hironori, YAMANOUCHI Takashi, TOKUNAGA Terumasa

Proceedings of the Annual Conference of JSAI ( The Japanese Society for Artificial Intelligence ) 2020 ( 0 ) 3F1ES205 - 3F1ES205 2020.01

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

<p>This study evaluated snowfall values based on limited observation data to estimate the surface mass balance (SMB) of Antarctica. To accomplish this, we attempted to identify the snowfall cloud at Syowa Station, Antarctica. We constructed a new convolutional neural network (CNN) architecture with multinomial and binary classifications and added National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) images over five years. The CNN was based on VGG16, and concatenate layers were added as the inception module. We replaced all the convolution layers with global average pooling to reduce the number of parameters. Based on the positive CNN sample result, the multinomial classification emphasized the entire cloud structure, while the binary classification focused on cloud continuity. The results indicated accuracies of 71.00% for binary and 65.37% for multinomial classifications.</p>

DOI： 10.11517/pjsai.JSAI2020.0_3F1ES205

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130007857079

An Inspirational Collaboration between Measurements, Mathematical Modeling and Data Science for Image Analysis Invited Reviewed

TOKUNAGA Terumasa

Journal of The Society of Instrument and Control Engineers ( The Society of Instrument and Control Engineers ) 58 ( 3 ) 166 - 170 2019.03

The cloud patterns in the snowfall conditions around Syowa Station, Antarctica detected by Convolutional Neural Network

Suzuki Kazue, Tokunaga Terumasa, Fukuchi Misaki, Hirasawa Naohiko, Yamanouchi Takashi

Summaries of JSSI and JSSE Joint Conference on Snow and Ice Research ( The Japanese Society of Snow and Ice / Japan Society for Snow Engineering ) 2019 ( 0 ) 119 2019.01

Causality analysis of the whole-brain activity data in C. elegans II

Iwasaki Y., Sato H., Oe S., Kuge S., Teramoto T., Tokunaga T., Hirose O., Wu S., Toyoshima Y., Jang M. S., Yoshida R., Iino Y., Ishihara T.

Meeting Abstracts of the Physical Society of Japan ( The Physical Society of Japan ) 73.2 ( 0 ) 2315 - 2315 2018.01

Causality analysis of the whole-brain activity data in C. elegans

Iwasaki Y., Sato H., Oe S., Teramoto T., Tokunaga T., Hirose O., Wu S., Toyoshima Y., Jang M. S., Yoshida R., Iino Y., Ishihara T.

Meeting Abstracts of the Physical Society of Japan ( The Physical Society of Japan ) 73.1 ( 0 ) 2853 - 2853 2018.01

線虫の全脳活動データに対する位相解析

岩崎唯史, 寺本孝行, 大江紗, 徳永旭将, 広瀬修, S. Wu, 豊島有, ジャンムンソン, 吉田亮, 飯野雄一, 石原健

2017年度日本物理学会第72回年次大会講演集 ( 一般社団法人日本物理学会 ) 2017.03

空間粒子フィルタによる多数の細胞の同時追跡

広瀬修, 川口翔太朗, 徳永旭将

電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 ( 東京 : 電子情報通信学会 ) 115 ( 112 ) 137 - 141 2015.06

Data Assimilation for Reconstructing a Whole Neuronal System of C. Elegans : The Current State and Issue Invited Reviewed

Terumasa Tokunaga, Ryo Yoshida, Yuishi Iwasaki

Journal of The Japan Society for Simulation Technology ( Japan Society for Simulation Technology ) 32 ( 4 ) 287 - 294 2013.12

Annual and semi-annual Sq variations at 96° MM MAGDAS I and II stations in Africa Reviewed International journal

El Hawary R., Yumoto K., Yamazaki Y., Mahrous A., Ghamry E., Meloni A., Badi K., Kianji G., Uiso C.B.S., Mwiinga N., Joao L., Affluo T., Sutcliffe P.R., Mengistu G., Baki P., Abe S., Ikeda A., Fujimoto A., Tokunaga T.

Earth, Planets and Space 64 ( 6 ) 425 - 432 2012.01

Pi 2 waves simultaneously observed by Cluster and CPMN ground-based magnetometers near the plasmapause Reviewed International journal

Kawano H., Ohtani S., Uozumi T., Tokunaga T., Yoshikawa A., Yumoto K., Lucek E.A., André M.

Annales Geophysicae 29 ( 9 ) 1663 - 1672 2011.10

Pi 2 waves simultaneously observed by Cluster and CPMN ground-based magnetometers near the plasmapause Reviewed International journal

Hideaki Kawano, Shin-ichi Ohtani, Teiji Uozumi, Terumasa Tokunaga, Akimasa Yoshikawa, Kiyohum Yumoto, E. A. Lucek, M. Andre, the CPMN group

Annales Geophysicae ( European Geophysical Union ) 29 ( 9 ) 1663 - 1672 2011.09

STPデータからの異常検出法の開発: Substorm precursor検出への応用

徳永旭将, 中村和幸, 樋口知之, 吉川顕正, 魚住禎司, 池田大輔, 藤本晶子, 森岡昭, 湯元清文, Tokunaga Terumasa, Nakamura Kazuyuki, Higuchi Tomoyuki, Yoshikawa Akimasa, Uozumi Teiji, Ikeda Daisuke, Fujimoto Akiko, Morioka Akira, Yumoto Kiyofumi

宇宙航空研究開発機構特別資料: 第6回「宇宙環境シンポジウム」講演論文集 = JAXA Special Publication: Proceedings of the 6th Spacecraft Enivironment Symposium ( 宇宙航空研究開発機構 ) JAXA-SP-09-006 260 - 265 2010.02

STPデータからの異常検出法の開発～オーロラサブストームへの応用

徳永旭将

Proceedings of the 6^<th> Space Environment Symposium. 260 - 265 2010.01

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