Updated on 2025/10/01

写真a

 
FUKUI,Kenichi
 
Organization
Faculty of Business Data Science Professor
Title
Professor
External link

Degree

  • 博士(情報科学) ( 2010.3   大阪大学 )

Research Interests

  • Data Science

  • Deep Learning

  • Data Mining

  • Machine Learning

  • Artificial Intelligence

Research Areas

  • Informatics / Intelligent informatics

  • Informatics / Soft computing

  • Informatics / Life, health and medical informatics

Education

  • Osaka University   Graduate School of Information Science and Technology   Department of Information and Physical Sciences

    2004.4 - 2005.6

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    Country: Japan

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  • Nagoya University

    2001.4 - 2003.3

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    Country: Japan

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  • Nagoya University   School of Informatics and Sciences   Department of Natural Science Informatics

    1998.4 - 2001.3

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    Country: Japan

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Research History

  • The University of Osaka

    2025.4

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    Country:Japan

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  • Kansai University   Faculty of Business Data Science   Professor

    2025.4

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    Country:Japan

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  • Osaka University

    2022.10 - 2025.3

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    Country:Japan

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  • Osaka University   SANKEN, Division of Information and Quantum Sciences   Associate Professor

    2015.7 - 2025.3

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    Country:Japan

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  • Osaka University   SANKEN, Division of Information and Quantum Sciences   Assistant Professor

    2010.4 - 2015.6

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    Country:Japan

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  • Osaka University

    2005.7 - 2010.3

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    Country:Japan

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Professional Memberships

Committee Memberships

  • 科学技術振興機構(JST)   経済安全保障重要技術育成プログラム 分科会委員  

    2024.7 - Present   

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    Committee type:Government

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  • 電子情報通信学会和文論文誌D「学生論文特集」   編集委員長  

    2023.1 - 2023.11   

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    Committee type:Academic society

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  • 人工知能学会   代議員  

    2021.6 - Present   

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  • 電子情報通信学会   和文論文誌D編集幹事  

    2020.6 - 2022.5   

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  • 人工知能学会   理事  

    2020.6 - 2022.5   

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  • New Generation Computing (人工知能学会英文論文誌)   Editorial Board Member  

    2018 - Present   

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  • 情報処理学会   論文誌:数理モデル化と応用(TOM) 編集委員  

    2015 - 2019   

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  • 人工知能学会   編集委員  

    2014 - 2018   

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  • 人工知能学会   合同研究会2025 実行委員(GeoSci研究会)  

    2025 - Present   

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    Committee type:Academic society

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  • 人工知能学会 地球惑星科学におけるAI研究会   幹事  

    2024.8 - Present   

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  • 人工知能学会   SIAI産学クロススクエア 実行委員  

    2023.10 - 2024.3   

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  • 電子情報通信学会和文論文誌D「学生論文特集」   編集幹事  

    2021.1 - 2021.11   

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  • 電子情報通信学会   和文論文誌D「学生論文特集」編集幹事  

    2020.1 - 2020.11   

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  • 電子情報通信学会和文論文誌D「ソフトウェアエージェントと応用特集」   編集幹事  

    2019.6 - 2020.6   

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  • 電子情報通信学会 人工知能と知識処理研究専門委員会   幹事  

    2019.6 - 2020.5   

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  • 電子情報通信学会 人工知能と知識処理研究専門委員会   専門委員  

    2017.6 - Present   

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  • 電子情報通信学会 和文論文誌D   編集委員  

    2017.6 - 2020.5   

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  • 電子情報通信学会和文論文誌D「ソフトウェアエージェントと応用特集」   編集幹事  

    2017.6 - 2018.6   

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  • 人工知能学会全国大会   プログラム委員会委員  

    2014 - 2017   

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  • 情報処理学会   会誌編集委員  

    2014 - 2015   

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  • 情報処理学会   論文誌ジャーナル/JIP編集委員会 編集委員  

    2011 - 2014   

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  • 人工知能学会全国大会   プログラム委員会委員  

    2011 - 2012   

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  • 情報処理学会 数理モデル化と問題解決研究会   運営委員  

    2007 - 2010   

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Papers

  • Bayesian Model Selection for Variable-coefficient Partial Differential Equation Discovery Reviewed

    Pongpisit Thanasutives, Yoshinobu Kawahara, Ken-ichi Fukui

    Results in Engineering   106930 - 106930   2025.9

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

    DOI: 10.1016/j.rineng.2025.106930

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  • Adaptive Uncertainty-Penalized Model Selection for Data-Driven PDE Discovery. Reviewed

    Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui

    IEEE Access   12   13165 - 13182   2024

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

    DOI: 10.1109/ACCESS.2024.3354819

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  • Gated Variable Selection Neural Network for Multimodal Sleep Quality Assessment Reviewed

    Yue Chen, Takashi Morita, Tsukasa Kimura, Takafumi Kato, Masayuki Numao, Ken-ichi Fukui

    Artificial Neural Networks and Machine Learning – ICANN 2023   288 - 299   2023.9

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    Authorship:Last author   Language:English   Publishing type:Part of collection (book)   Publisher:Springer Nature Switzerland  

    DOI: 10.1007/978-3-031-44192-9_23

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  • Sound-based sleep assessment with controllable subject-dependent embedding using Variational Domain Adversarial Neural Network Reviewed

    Ken-ichi Fukui, Shunya Ishimaru, Takafumi Kato, Masayuki Numao

    International Journal of Data Science and Analytics   2023.7

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    Abstract

    Sleep quality assessment as an indicator of daily health care plays an important role in our physiological and mental activity. Sound during sleep contains rich information on biological activities, such as body movement, snoring, and sleep bruxism. However, sound features differ depending on individual and environmental differences. In order to develop a wide-rage applicable daily sleep assessment, this paper utilizes deep learning to ease individual and environmental differences of sound features. Firstly, by Variational Domain Adversarial Neural Network (VDANN) encodes sound events into latent representation, simultaneously eliminates subject-dependent features. Then, sleep pattern in the obtained latent space is trained by Long Short-Term Memory (LSTM) with associated sleep assessment of one night. We performed age group estimation from normal sleep as an objective indicator of sleep comparing to their age group. The experiment with more than 100 subjects showed that VDANN is able to extract subject independent features, and the proposed method outperforms the conventional method for age group estimation from sleep sound even for new subjects. In addition, our model is able to personalize by controlling subject-dependent embedding when after data accumulation of the subject.

    DOI: 10.1007/s41060-023-00407-7

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    Other Link: https://link.springer.com/article/10.1007/s41060-023-00407-7/fulltext.html

  • Granger causality-based cluster sequence mining for spatio-temporal causal relation mining Reviewed

    Nat Pavasant, Takashi Morita, Masayuki Numao, Ken-ichi Fukui

    International Journal of Data Science and Analytics   2023.7

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    Authorship:Last author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    Abstract

    We proposed a method to extract causal relations of spatial clusters from multi-dimensional event sequence data, also known as a spatio-temporal point process. The proposed Granger cluster sequence mining algorithm identifies the pairs of spatial data clusters that have causality over time with each other. It extended the cluster sequence mining algorithm, which utilized a statistical inference technique to identify the occurrence relation, with a causality inference based on the Granger causality. In addition, the proposed method utilizes a false discovery rate procedure to control the significance of the causality. Based on experiments on both synthetic and semi-real data, we confirmed that the algorithm is able to extract the synthetic causal relations from multiple different sets of data, even when disturbed with high level of spatial noise. False discovery rate procedure also helps to increase the accuracy even more under such case and also make the algorithm less-sensitive to the hyperparameters.

    DOI: 10.1007/s41060-023-00411-x

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    Other Link: https://link.springer.com/article/10.1007/s41060-023-00411-x/fulltext.html

  • Noise-aware physics-informed machine learning for robust PDE discovery. Reviewed

    Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui

    Machine Learning: Science and Technology   4 ( 1 )   15009 - 15009   2023.3

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    DOI: 10.1088/2632-2153/acb1f0

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  • Soft Periodic Convolutional Recurrent Network for Spatiotemporal Climate Forecast Reviewed

    Ekasit Phermphoonphiphat, Tomohiko Tomita, Takashi Morita, Masayuki Numao, Ken-Ichi Fukui

    Applied Sciences   11 ( 20 )   9728 - 9728   2021.10

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

    Many machine-learning applications and methods are emerging to solve problems associated with spatiotemporal climate forecasting; however, a prediction algorithm that considers only short-range sequential information may not be adequate to deal with periodic patterns such as seasonality. In this paper, we adopt a Periodic Convolutional Recurrent Network (Periodic-CRN) model to employ the periodicity component in our proposals of the periodic representation dictionary (PRD). Phase shifts and non-stationarity of periodicity are the key components in the model to support. Specifically, we propose a Soft Periodic-CRN (SP-CRN) with three proposals of utilizing periodicity components: nearby-time (PRD-1), periodic-depth (PRD-2), and periodic-depth differencing (PRD-3) representation to improve climate forecasting accuracy. We experimented on geopotential height at 300 hPa (ZH300) and sea surface temperature (SST) datasets of ERA-Interim. The results showed the superiority of PRD-1 plus or minus one month of a prior cycle to capture the phase shift. In addition, PRD-3 considered only the depth of one differencing periodic cycle (i.e., the previous year) can significantly improve the prediction accuracy of ZH300 and SST. The mixed method of PRD-1, and PRD-3 (SP-CRN-1+3) showed a competitive or slight improvement over their base models. By adding the metadata component to indicate the month with one-hot encoding to SP-CRN-1+3, the prediction result was a drastic improvement. The results showed that the proposed method could learn four years of periodicity from the data, which may relate to the El Niño–Southern Oscillation (ENSO) cycle.

    DOI: 10.3390/app11209728

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  • A Framework for Predicting Remaining Useful Life Curve of Rolling Bearings Under Defect Progression Based on Neural Network and Bayesian Method Reviewed

    Masashi Kitai, Takuji Kobayashi, Hiroki Fujiwara, Ryoji Tani, Masayuki Numao, Ken-ichi Fukui

    IEEE Access   9   62642 - 62652   2021.4

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    DOI: 10.1109/ACCESS.2021.3073945

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  • Kernelized evolutionary distance metric learning for semi-supervised clustering Reviewed

    Wasin Kalintha, Satoshi Ono, Masayuki Numao, Ken-ichi Fukui

    Intelligent Data Analysis   23 ( 6 )   1271 - 1297   2019.11

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:IOS Press  

    DOI: 10.3233/ida-184283

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  • Cluster sequence mining from event sequence data and its application to damage correlation analysis Reviewed

    Ken-ichi Fukui, Yoshiyuki Okada, Kazuki Satoh, Masayuki Numao

    Knowledge-Based Systems   179   136 - 144   2019.9

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.knosys.2019.05.012

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  • Defect Detection Method for Rolling Bearing Including Micro Defect by Feature Selection and Two Step Outlier Detection Method Reviewed

    M. Kitai, Y. Akamatsu, K. Fukui

    Information Processing Society of Japan. Transactions on mathematical modeling and its applications   12 ( 1 )   32 - 42   2019.3

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

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  • Reinforcement Learning for Evolutionary Distance Metric Learning Systems Improvement Reviewed

    Bassel Ali, Wasin Kalintha, Koichi Moriyama, Masayuki Numao, Ken-ichi Fukui

    Proceedings of Genetic and Evolutionary Computation Conference (GECCO) Companion   155 - 156   2018.7

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

    DOI: 10.1145/3205651.3205675

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  • Statistical Sleep Pattern Modelling for Sleep Quality Assessment based on Sound Events Reviewed

    H. Wu, T. Kato, M. Numao, K. Fukui

    5 ( 11 )   2017.10

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

    DOI: 10.1007/s13755-017-0031-z

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  • Personal sleep pattern visualization using sequence-based kernel self-organizing map on sound data Reviewed

    Hongle Wu, Takafumi Kato, Tomomi Yamada, Masayuki Numao, Ken-ichi Fukui

    ARTIFICIAL INTELLIGENCE IN MEDICINE   80   1 - 10   2017.7

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

    DOI: 10.1016/j.artmed.2017.06.012

    Web of Science

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  • Error Detection of Oceanic Observation Data Using Sequential Labeling Reviewed

    29   1 - 4   2015.10

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    CiNii Books

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  • Evolutionary multi-objective distance metric learning for multi-label clustering Reviewed

    Taishi Megano, Ken-ichi Fukui, Masayuki Numao, Satoshi Ono

    2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings   2945 - 2952   2015.9

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Institute of Electrical and Electronics Engineers Inc.  

    DOI: 10.1109/CEC.2015.7257255

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  • Cluster sequence mining: Causal inference with time and space proximity under uncertainty Reviewed

    Yoshiyuki Okada, Ken-ichi Fukui, Koichi Moriyama, Masayuki Numao

    Proc. The 19th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD2015)   293 - 304   2015.5

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Verlag  

    DOI: 10.1007/978-3-319-18032-8_23

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  • AERO-Net: AutoEncoder-Driven Residual Optimization Network for Latent Bias Correction of WRF-ROMS Reviewed

    Passin Pornvorapha, Kanoksri Sarinnapakorn, Ken-ichi Fukui, Peerapon Vateekul

    Expert Systems with Applications   129607 - 129607   2025.9

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.eswa.2025.129607

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  • Multi-modal Data Transfer by Knowledge Distillation for Enhancing Precipitation Nowcasting Reviewed

    Qihang Wang, Tomohiko Tomita, Ken-ichi Fukui

    Proc. International Conference on Artificial Intelligence Applications and Innovations (AIAI2025)   283 - 296   2025.6

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

    DOI: 10.1007/978-3-031-96228-8_21

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  • Enhancing Sound-Based Sleep Quality Assessment by Multi-modal Knowledge Distillation Reviewed

    112 - 125   2025.6

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    Authorship:Last author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Nature Switzerland  

    DOI: 10.1007/978-3-031-96235-6_9

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  • Uncertainty-Penalized Bayesian Information Criterion for Parametric Partial Differential Equation Discovery Reviewed

    Pongpisit Thanasutives, Ken-ichi Fukui

    NeurIPS 2024 Workshop: Machine Learning and the Physical Sciences   2024.12

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  • Local density estimation procedure for autoregressive modeling of point process data Reviewed

    Nat PAVASANT, Takashi MORITA, Masayuki NUMAO, Ken-ichi FUKUI

    IEICE Transactions on Information and Systems   2024.7

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    Authorship:Last author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electronics, Information and Communications Engineers (IEICE)  

    DOI: 10.1587/transinf.2023edl8084

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  • Automated parameter estimation for geothermal reservoir modeling using machine learning Reviewed

    Anna Suzuki, Shuokun Shi, Taro Sakai, Ken-ichi Fukui, Shinya Onodera, Junichi Ishizaki, Toshiyuki Hashida

    Renewable Energy   224   120243 - 120243   2024.4

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.renene.2024.120243

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  • On uncertainty-penalized Bayesian information criterion.

    Pongpisit Thanasutives, Ken-ichi Fukui

    CoRR   abs/2404.16881   2024

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    Language:English   Publishing type:Research paper (other academic)  

    DOI: 10.48550/arXiv.2404.16881

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  • Clustering and Data Augmentation to Improve Accuracy of Sleep Assessment and Sleep Individuality Analysis.

    Shintaro Tamai, Masayuki Numao, Ken-ichi Fukui

    CoRR   abs/2404.10299   2024

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    DOI: 10.48550/arXiv.2404.10299

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  • Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Superresolution Convolutional Neural Networks Reviewed

    Tsuyoshi Thomas Sekiyama, Syugo Hayashi, Ryo Kaneko, Ken-ichi Fukui

    Artificial Intelligence for the Earth Systems   2 ( 3 )   2023.7

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:American Meteorological Society  

    Abstract

    Surrogate modeling is one of the most promising applications of deep learning techniques in meteorology. The purpose of this study was to downscale surface wind fields in a gridded format at a much lower computational load. We employed a superresolution convolutional neural network (SRCNN) as a surrogate model and created a 20-member ensemble by training the same SRCNN model with different random seeds. The downscaling accuracy of the ensemble mean remained stable throughout a year and was consistently better than that of the input wind fields. It was confirmed that 1) the ensemble spread was efficiently created and that 2) the ensemble mean was superior to individual ensemble members and 3) robust to the presence of outlier members. Training, validation, and test data for 10 years were computed via our nested mesoscale weather forecast models not derived from public analysis datasets or real observations. The predictands were 1-km gridded surface zonal and meridional winds, of which the domain was defined as a 180 km × 180 km area around Tokyo, Japan. The predictors included 5-km gridded surface zonal and meridional winds, temperature, humidity, vertical gradient of the potential temperature, elevation, and land-to-water ratio as well as 1-km gridded elevation and land-to-water ratio. Although a perfect surrogate of the weather forecast model could not be achieved, the SRCNN downscaling accuracy could likely enable us to apply this approach in high-resolution advection simulations, considering its overwhelmingly high prediction speed.

    DOI: 10.1175/aies-d-23-0007.1

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  • Visualizing internal micro-damage distribution in solid oxide fuel cells Reviewed

    Kazuhisa Sato, Yoshie Yabuta, Keigo Kumada, Ken-ichi Fukui, Masayuki Numao, Tatsuya Kawada

    Journal of Power Sources   570   23359   2023.6

  • Update of global maps of Alisov’s climate classification Reviewed

    Ryu Shimabukuro, Tomohiko Tomita, Ken-ichi Fukui

    Progress in Earth and Planetary Science   10 ( 19 )   2023.4

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  • Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE Discovery.

    Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui

    CoRR   abs/2308.10283   2023

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    Language:English   Publishing type:Research paper (other academic)  

    DOI: 10.48550/arXiv.2308.10283

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  • Multi-Kernel Temporal and Spatial Convolution for EEG-Based Emotion Classification Reviewed International journal

    Taweesak Emsawas, Takashi Morita, Tsukasa Kimura, Ken-ichi Fukui, Masayuki Numao

    Sensors   22 ( 21 )   8250   2022.10

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    Deep learning using an end-to-end convolutional neural network (ConvNet) has been applied to several electroencephalography (EEG)-based brain–computer interface tasks to extract feature maps and classify the target output. However, the EEG analysis remains challenging since it requires consideration of various architectural design components that influence the representational ability of extracted features. This study proposes an EEG-based emotion classification model called the multi-kernel temporal and spatial convolution network (MultiT-S ConvNet). The multi-scale kernel is used in the model to learn various time resolutions, and separable convolutions are applied to find related spatial patterns. In addition, we enhanced both the temporal and spatial filters with a lightweight gating mechanism. To validate the performance and classification accuracy of MultiT-S ConvNet, we conduct subject-dependent and subject-independent experiments on EEG-based emotion datasets: DEAP and SEED. Compared with existing methods, MultiT-S ConvNet outperforms with higher accuracy results and a few trainable parameters. Moreover, the proposed multi-scale module in temporal filtering enables extracting a wide range of EEG representations, covering short- to long-wavelength components. This module could be further implemented in any model of EEG-based convolution networks, and its ability potentially improves the model’s learning capacity.

    DOI: 10.3390/s22218250

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  • Development of dental inspection method: Nondestructive evaluation of an adhesive interface by ACTIVE acoustic emission Reviewed

    Ryoma Ezaki, Atsushi Mine, Kazuhisa Sato, Ken-ichi Fukui, Keigo Kumada, Masahiro Yumitate, Shintaro Ban, Azusa Yamanaka, Mariko Matsumoto, Bart Van Meerbeek, Hirokazu Moriya, Toshiyuki Hashida, Hirofumi Yatani

    Journal of Prosthodontic Research   65 ( 2 )   236 - 242   2022.4

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Japan Prosthodontic Society  

    DOI: 10.2186/jpr.jpr_d_20_00260

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  • Data-Driven Geothermal Reservoir Modeling: Estimating Permeability Distributions by Machine Learning Reviewed

    Anna Suzuki, Ken-ichi Fukui, Shinya Onodera, Junichi Ishizaki, Toshiyuki Hashida

    Geosciences   12 ( 3 )   130 - 130   2022.3

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    Numerical modeling for geothermal reservoir engineering is a crucial process to evaluate the performance of the reservoir and to develop strategies for the future development. The governing equations in the geothermal reservoir models consist of several constitutive parameters, and each parameter is given to a large number of simulation grids. Thus, the combinations of parameters we need to estimate are almost limitless. Although several inverse analysis algorithms have been developed, determining the constitutive parameters in the reservoir model is still a matter of trial-and-error estimation in actual practice, and is largely based on the experience of the analyst. There are several parameters which control the hydrothermal processes in the geothermal reservoir modeling. In this study, as an initial challenge, we focus on permeability, which is one of the most important parameters for the modeling. We propose a machine-learning-based method to estimate permeability distributions using measurable data. A large number of learning data were prepared by a geothermal reservoir simulator capable of calculating pressure and temperature distributions in the natural state with different permeability distributions. Several machine learning algorithms (i.e., linear regression, ridge regression, Lasso regression, support vector regression (SVR), multilayer perceptron (MLP), random forest, gradient boosting, and the k-nearest neighbor algorithm) were applied to learn the relationship between the permeability and the pressure and temperature distributions. By comparing the feature importance and the scores of estimations, random forest using pressure differences as feature variables provided the best estimation (the training score of 0.979 and the test score of 0.789). Since it was learned independently of the grids and locations, this model is expected to be generalized. It was also found that estimation is possible to some extent, even for different heat source conditions. This study is a successful demonstration of the first step in achieving the goal of new data-driven geothermal reservoir engineering, which will be developed and enhanced with the knowledge of information science.

    DOI: 10.3390/geosciences12030130

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  • Sleep stage-dependent changes in tonic masseter and cortical activities in young subjects with primary sleep bruxism. Reviewed International journal

    Risa Toyota, Ken-Ichi Fukui, Mayo Kamimura, Ayano Katagiri, Hajime Sato, Hiroki Toyoda, Pierre Rompré, Kazunori Ikebe, Takafumi Kato

    Sleep   2021.8

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    STUDY OBJECTIVES: The present study investigated the hypothesis that subjects with primary sleep bruxism (SB) exhibit masseter and cortical hyperactivities during quiet sleep periods that are associated with a high frequency of rhythmic masticatory muscle activity (RMMA). METHODS: Fifteen SB and ten control participants underwent polysomnographic recordings. The frequencies of oromotor events and arousals and the percentage of arousals with oromotor events were assessed. Masseter muscle tone during sleep was quantified using a cluster analysis. Electroencephalography power and heart rate variability were quantified and then compared between the two groups and among sleep stages. RESULTS: The frequency of RMMA and percentage of arousals with RMMA were significantly higher in SB subjects than in controls in all stages, while these variables for non-rhythmic oromotor events did not significantly differ between the groups. In SB subjects, the frequency of RMMA was the highest in stage N1 and the lowest in stages N3 and R, while the percentage of arousals with RMMA was higher in stage N3 than stages N1 and R. The cluster analysis classified masseter activity during sleep into two clusters for masseter tone and contractions. Masseter muscle tone showed typical stage-dependent changes in both groups, but did not significantly differ between the groups. Furthermore, no significant differences were observed in electroencephalography power or heart rate variability between the groups. CONCLUSION: Young SB subjects exhibited sleep stage-dependent increases in the responsiveness of RMMA to transient arousals, but did not show masseter or cortical hyperactivity during sleep.

    DOI: 10.1093/sleep/zsab207

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  • Adversarial Multi-task Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Reviewed

    Pongpisit Thanasutives, Masayuki Numao, Ken-ichi Fukui

    Proc. 2021 The International Joint Conference on Neural Networks (IJCNN2021)   1 - 9   2021.7

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    DOI: 10.1109/IJCNN52387.2021.9533606

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  • EEG emotion Enhancement using Task-specific Domain Adversarial Neural Network Reviewed

    Ding Ke-Ming, Tsukasa Kimura, Fukui Ken-ichi, Numao Masayuki

    Proc. 2021 The International Joint Conference on Neural Networks (IJCNN2021)   2021.7

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    DOI: 10.1109/ijcnn52387.2021.9533310

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  • Development of dental inspection method: nondestructive evaluation of a dentin–adhesive interface by acoustic emission Reviewed

    Ryoma Ezaki, Atsuhi Mine, Kazuhisa Sato, Ken-ichi Fukui, Keigo Kumada, Masahiro Yumitate, Shintaro Ban, Azusa Yamanaka, Mariko Matsumoto, Bart Van Meerbeek, Toshiyuki Hashida, Hirofumi Yatani

    Journal of Prosthodontic Research   65 ( 4 )   438 - 442   2021.5

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  • Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization Reviewed

    Juan Lorenzo Hagad, Tsukasa Kimura, Ken-ichi Fukui, Masayuki Numao

    Sensors   21 ( 5 )   1792 - 1792   2021.3

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    Two of the biggest challenges in building models for detecting emotions from electroencephalography (EEG) devices are the relatively small amount of labeled samples and the strong variability of signal feature distributions between different subjects. In this study, we propose a context-generalized model that tackles the data constraints and subject variability simultaneously using a deep neural network architecture optimized for normally distributed subject-independent feature embeddings. Variational autoencoders (VAEs) at the input level allow the lower feature layers of the model to be trained on both labeled and unlabeled samples, maximizing the use of the limited data resources. Meanwhile, variational regularization encourages the model to learn Gaussian-distributed feature embeddings, resulting in robustness to small dataset imbalances. Subject-adversarial regularization applied to the bi-lateral features further enforces subject-independence on the final feature embedding used for emotion classification. The results from subject-independent performance experiments on the SEED and DEAP EEG-emotion datasets show that our model generalizes better across subjects than other state-of-the-art feature embeddings when paired with deep learning classifiers. Furthermore, qualitative analysis of the embedding space reveals that our proposed subject-invariant bi-lateral variational domain adversarial neural network (BiVDANN) architecture may improve the subject-independent performance by discovering normally distributed features.

    DOI: 10.3390/s21051792

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  • Cross-Phase Emotion Recognition using Multiple Source Domain Adaptation Reviewed

    Ding Keming, Tsukasa Kimura, Ken-ichi Fukui, Masayuki Numao

    Proc. 14th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2021)   2021.2

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    DOI: 10.5220/0010200701500157

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  • Encoder-Decoder Based Convolutional Neural Networks with Multi Scale-Aware Modules for Crowd Counting Reviewed

    Pongpisit Thanasutives, Ken-ichi Fukui, Masayuki Numao, Boonserm Kijsirikul

    Proc. 2020 25th International Conference on Pattern Recognition (ICPR2020)   2021.1

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  • Reinforcement Learning based Evolutionary Metric Filtering for High Dimensional Problems Reviewed

    Bassel Ali, Koichi Moriyama, Wasin Kalintha, Masayuki Numao, Ken-ichi Fukui

    Proc. 19th IEEE International Conference on Machine Learning and Applications (ICMLA2020)   226 - 233   2020.12

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  • Reinforcement Learning based Metric Filtering for Evolutionary Distance Metric Learning Reviewed

    Bassel Ali, Koichi Moriyama, Wasin Kalintha, Masayuki Numao, Ken-ichi Fukui

    Intelligent Data Analysis   24 ( 6 )   1345 - 1364   2020.12

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  • Explainable and Unexpectable Recommendations using Relational Learning on Multiple Domains Reviewed

    Sirawit Sopchoke, Ken-ichi Fukui, Masayuki Numao

    Intelligent Data Analysis   24 ( 6 )   1289 - 1309   2020.12

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  • Spatio-Temporal Change Detection with Granger Causality Based Cluster Sequence Mining Reviewed

    Nat Pavasant, Masayuki Numao, Ken-ichi Fukui

    Proc. 19th IEEE International Conference on Machine Learning and Applications (ICMLA2020)   551 - 558   2020.12

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  • Towards Multimodal Office Task Performance Estimation Reviewed

    Nattapat Boonprakong, Tsukasa Kimura, Ken-ichi Fukui, Kazuya Okada, Masato Ito, Hiroshi Maruyama, Masayuki Numao

    Proc. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC2020)   2020.10

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    DOI: 10.1109/smc42975.2020.9283107

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  • SleepAge Sleep Quality Assessment from Nocturnal Sound in Home Environment Reviewed

    Wasin Kalintha, Takafumi Kato, Ken-ichi Fukui

    Proc. 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2020), Procedia Computer Science   176   898 - 907   2020.9

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    DOI: 10.1016/j.procs.2020.09.085

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  • Comparative Study of Wet and Dry Systems on EEG-based Cognitive Tasks Reviewed

    Taweesak Emsawas, Tsukasa Kimura, Ken-ichi Fukui, Masayuki Numao

    Proc. The 13th International Conference on Brain Informatics 2020 (BI 2020)   318 - 318   2020.9

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    DOI: 10.1007/978-3-030-59277-6_28

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  • Spatio-Temporal Change Detection Using Granger Sequence Pattern Reviewed

    Nat Pavasant, Masayuki Numao, Ken-ichi Fukui

    Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20) Doctoral Consortium Track   5202 - 5203   2020.7

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  • A study on error detection of ocean observation data by anomaly detection Reviewed

    Yosuke Idenoue, Shogo Hayashi, Ken-ichi Fukui, Shigeki Hosoda, Satoshi Ono

    Proc. 25th International Symposium on Artificial Life and Robotics (AROB2020)   2020.1

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  • Modelling Naturalistic Work Stress Using Spectral HRV Representations and Deep Learning

    Juan Lorenzo Hagad, Ken-ichi Fukui, Masayuki Numao

    Advances in Intelligent Systems and Computing   1128   267 - 277   2020

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    DOI: 10.1007/978-3-030-39878-1_24

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  • Feasible Affect Recognition in Advertising Based on Physiological Responses from Wearable Sensors

    Taweesak Emsawas, Ken-ichi Fukui, Masayuki Numao

    Advances in Intelligent Systems and Computing   1128   27 - 36   2020

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    DOI: 10.1007/978-3-030-39878-1_3

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  • Physics-guided Neural Network with Model Discrepancy Based on Upper Troposphere Wind Prediction Reviewed

    Ken-ichi Fukui, Junya Tanaka, Tomohiko Tomita, Masayuki Numao

    Proc. IEEE 18th International Conference on Machine Learning and Applications (ICMLA 2019)   414 - 419   2019.12

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  • A Study of Upper Tropospheric Circulations over the Northern Hemisphere Prediction Using Multivariate Features by ConvLSTM Reviewed

    Ekasit Phermphoonphiphat, Tomohiko Tomita, Masayuki Numao, Ken-ichi Fukui

    Proc. The 23nd Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2019)   130 - 141   2019.12

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  • ILP Recommender System: Explainable and More Reviewed

    Sirawit Sopchoke, Ken-ichi Fukui, Masayuki Numao

    Proc. The 29th International Conference on Inductive Logic (ILP2019), Late Breaking Paper   2019.9

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  • Deep Visual Models for EEG of Mindfulness Meditation in a Workplace Setting Reviewed

    Juan Lorenzo Hagad, Ken-ichi Fukui, Masayuki Numao

    Precision Health and Medicine, Post Proc. International Workshop on Health Intelligence (W3PHIAI 2019) held in conjunction with AAAI2019   129 - 137   2019.8

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  • Efficient Decision Trees for Multi-class Support Vector Machines Using Entropy and Generalization Error Estimation Reviewed

    Pittipol Kantavat, Boonserm Kijsirikul, Patoomsiri Songsiri, Ken-ichi Fukui, Masayuki Numao

    International Journal of Applied Mathematics and Computer Science (AMCS)   28 ( 4 )   705 - 717   2019.1

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  • Analyzing the effect of video media on emotion using a VR headset platform and physiological data

    Workshop on Computation: Theory and Practice (WCTP-2018)   2018.9

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  • Concept drift detection for graph-structured classifiers under scarcity of true labels Reviewed

    Noppayut Sriwatanasakdi, Masayuki Numao, Ken-ichi Fukui

    Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI   2017-   461 - 468   2018.6

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    DOI: 10.1109/ICTAI.2017.00077

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  • Two-Stage Reinforcement Learning Algorithm for Quick Cooperation in Repeated Games Invited Reviewed

    Wataru Fujita, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao

    Transactions on Computational Collective Intelligence   28   48 - 65   2018.4

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    DOI: 10.1007/978-3-319-78301-7_3

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  • Reinforcement learning based distance metric filtering approach in clustering Reviewed

    Bassel Ali, Ken-ichi Fukui, Wasin Kalintha, Koichi Moriyama, Masayuki Numao

    2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings   2018-   1 - 8   2018.2

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    DOI: 10.1109/SSCI.2017.8280866

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  • Explainable Cross-domain Recommendations Through Relational Learning Reviewed

    S. Sopchoke, K. Fukui, M. Numao

    Proc. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), Student Abstract and Poster Program   8159 - 8160   2018.2

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  • Multimodal stability-sensitive emotion recognition based on brainwave and physiological signals Reviewed

    Nattapong Thammasan, Juan Lorenzo Hagad, Ken-ichi Fukui, Masayuki Numao

    2017 7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017   2018-   44 - 49   2018.1

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    DOI: 10.1109/ACIIW.2017.8272584

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  • Error detection in ocean data considering spatial autocorrelation Reviewed

    Shogo Hayashi, Satoshi Ono, Shigeki Hosoda, Masayuki Numao, Ken-Ichi Fukui

    Transactions of the Japanese Society for Artificial Intelligence   33 ( 3 )   2018

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    DOI: 10.1527/tjsai.D-SGAI02

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  • Quality control of ocean observation data using conditional random field Reviewed

    Yosuke Kamikawaji, Haruki Matsuyama, Ken-Ichi Fukui, Shigeki Hosoda, Satoshi Ono

    Transactions of the Japanese Society for Artificial Intelligence   33 ( 3 )   2018

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    DOI: 10.1527/tjsai.G-SGAI05

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  • Bisociative Serendipity Music Recommendation Reviewed

    Theory and Practice of Computation (Post-Proceedings of Workshop on Computation: Theory and Practice (WCTP-2017)),   199 - 210   2017.9

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  • ART-2b: Adapted ART-2a for large scale data clustering on PM2.5 mass spectra Reviewed

    Nat Pavasant, Hiroshi Furutani, Masayuki Numao, Ken-ichi Fukui

    Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017   2018-January   4813 - 4815   2017.7

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    DOI: 10.1109/BigData.2017.8258551

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  • Bat species classification by echolocation call using machine learning system Reviewed

    K. Masuda, T. Matsui, D. Fukui, K. Fukui, T. Machimura

    Mammalian Science   56 ( 1 )   1 - 15   2017.7

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    DOI: 10.11238/mammalianscience.57.19

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  • Personal Sleep Pattern Visualization via Clustering on Sound Data Reviewed

    H. Wu, T. Kato, T. Yamada, M. Numao, K. Fukui

    AAAI Workshop - Technical Report   WS-17-01 - WS-17-15   592 - 599   2017.2

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  • Multimodal fusion of EEG and musical features in music-emotion recognition Reviewed

    N. Thammasan, K. Fukui, M. Numao

    2017.2

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  • Error Detection of Ocean Depth Series Data with Area Partitioning and Using Sliding Window Reviewed

    S. Hayashi, S. Ono, S. Hosoda, M. Numao, K. Fukui

    2016.12

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  • An Investigation of Effect of Bioluminescent Light on Human using Electroencephalogram Reviewed

    N. Thammasan, M. Iwano, K. Moriyama, K. Fukui, K. Kawintiranon, Y. Buatong, S. Inagaki, T. Wazawa, T. Nagai, M. Numao

    Proc. The 23nd International Display Workshop in conjunction with Asia Display (IDW/AD2016)   57 - 60   2016.12

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  • Feature Function Design in Conditional Random Field Using Decision Tree Learning Applied to Error Detection of Ocean Observation Data Reviewed

    Y. Kamikawaji, H. Matsuyama, K. Fukui, S. Hosoda, S. Ono

    2016.12

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  • Integrating Class Information and Features in Cluster Analysis based on Evolutionary Distance Metric Learning Reviewed

    W. Kalintha, S. Ono, M. Numao, K. Fukui

    INTELLIGENT AND EVOLUTIONARY SYSTEMS, IES 2016   8   165 - 181   2016.11

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    DOI: 10.1007/978-3-319-49049-6_12

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  • Development and Application of a Multi-Objective Optimization Tool for Re-newable Energy Mix in Municipalities

    K. Hori, T. Matsui, S. Ono, K. Fukui, T. Hasuike, T. Machimura

    Transactions of the Japanese Society for Artificial Intelligence   2016.10

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  • An Investigation of Annotation Smoothing for EEG-based Continuous Music-emotion Recognition Reviewed

    N. Thammasan, K. Fukui, M. Numao

    2016.10

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  • Food CMS, Integrated Information Sharing System of Food Production, Marketing, and Consumption Reviewed

    T. Kashima, S. Matsumoto, K. Fukui, T. Hasuike

    Information Engineering Express   2 ( 3 )   33 - 42   2016.9

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    DOI: 10.52731/iee.v2.i3.85

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  • Music-emotion Recognition based on Wearable Dry-electrode Electroencephalogram Reviewed

    N. Thammasan, K. Moriyama, K. Fukui, M. Numao

    Theory and Practice of Computation (Post Proc. Workshop on Computation: Theory and Practice (WCTP-2016))   2016.9

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  • Multimodal Latent Feature Learning for Psycho-Physiological Stress Modelling and Detection Reviewed

    Proc. 7th International Workshop on Empathic Computing (IWEC 2016), in conjunction with PRICAI 2016   2016.8

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  • Development and application of the renewable energy regional optimization utility tool for environmental sustainability: REROUTES Reviewed

    Keiko Hori, Takanori Matsui, Takashi Hasuike, Ken-ichi Fukui, Takashi Machimura

    Renewable Energy   93   548 - 561   2016.8

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    DOI: 10.1016/j.renene.2016.02.051

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  • Application of annotation smoothing for subject-independent emotion recognition based on electroencephalogram Reviewed

    Nattapong Thammasan, Ken-ichi Fukui, Masayuki Numao

    Proc. 7th International Workshop on Empathic Computing (IWEC 2016)   10004   115 - 126   2016.8

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    DOI: 10.1007/978-3-319-60675-0_10

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  • Application of Deep Belief Networks in EEG-based Dynamic Music-emotion Recognition Reviewed

    N. Thammasan, K. Fukui, M. Numao

    2016.7

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  • Implementation of Integrated Information Sharing System of Food Production, Marketing, and Consumption Reviewed

    T. Kashima, S. Matsumoto, T. Hasuike, K. Fukui

    5th IIAI International Congress on Advanced Applied Informatics(IIAI-AAI)   791 - 796   2016.7

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    DOI: 10.1109/IIAI-AAI.2016.28

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  • Continuous music-emotion recognition based on electroencephalogram Reviewed

    Nattapong Thammasan, Koichi Moriyama, Ken-Ichi Fukui, Masayuki Numao

    IEICE Transactions on Information and Systems   E99D ( 4 )   1234 - 1241   2016.4

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    DOI: 10.1587/transinf.2015EDP7251

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  • Familiarity Effects in EEG-based Emotion Recognition Reviewed

    N. Thammasan, K. Moriyama, K. Fukui, M. Numao

    Brain Informatics   2016.4

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  • Kernel density compression for real-time Bayesian encoding/decoding of unsorted hippocampal spikes Reviewed

    Danaipat Sodkomkham, Davide Ciliberti, Matthew A. Wilson, Ken-Ichi Fukui, Koichi Moriyama, Masayuki Numao, Fabian Kloosterman

    Knowledge-Based Systems   94   1 - 12   2016.2

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    DOI: 10.1016/j.knosys.2015.09.013

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  • Adaptive Two-stage Learning Algorithm for Repeated Games Reviewed

    Wataru Fujita, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao

    Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART)   1   47 - 55   2016.2

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    DOI: 10.5220/0005711000470055

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  • Dynamic and Individual Emotion Recognition Based on EEG during Music Listening Invited

    Nattapong Thammasan, Ken-ichi Fukui, Koichi Moriyama, Masayuki Numao

    Theory and Practice of Computation (Post Proc. Workshop on Computation: Theory and Practice (WCTP-2014) )   89 - 100   2016.1

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    DOI: 10.1142/9789814730464_0008

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  • Learning Better Strategies with a Combination of Complementary Reinforcement Learning Algorithms Reviewed

    Wataru Fujita, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao

    Theory and Practice of Computation (Post Proc. Workshop on Computation: Theory and Practice (WCTP-2014) )   43 - 54   2016.1

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    DOI: 10.1142/9789814730464_0004

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  • Fighter or Explorer? — Classifying Player Types in a Japanese-Style Role-Playing Game from Game Metrics Invited

    Kevin Fischer, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao

    Theory and Practice of Computation (Post Proc. Workshop on Computation: Theory and Practice (WCTP-2014) )   55 - 66   2016.1

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    DOI: 10.1142/9789814730464_0005

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  • Sleep pattern discovery via visualizing cluster dynamics of sound data Reviewed

    Hongle Wu, Takafumi Kato, Tomomi Yamada, Masayuki Numao, Ken-ichi Fukui

    The 29th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2016)   460 - 471   2016

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    DOI: 10.1007/978-3-319-42007-3_40

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  • Cluster Analysis of Face Images and Literature Data by Evolutionary Distance Metric Learning Reviewed

    Wasin Kalintha, Taishi Megano, Satoshi Ono, Ken-ichi Fukui, Masayuki Numao

    Thirty-fifth SGAI International Conference on Artificial Intelligence   301 - 315   2015.12

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    DOI: 10.1007/978-3-319-25032-8_23

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  • Modeling work stress using heart rate and stress coping profiles Reviewed

    Juan Lorenzo Hagad, Koichi Moriyama, Kenichi Fukui, Masayuki Numao

    Proc. 6th International Workshop on Empathic Computing (IWEC 2015)   2015.10

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    DOI: 10.1007/978-3-319-46218-9_9

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  • Concept Drift Detection with Clustering via Statistical Change Detection Methods Reviewed

    Y. Sakamoto, K. Fukui, J. Gama, D. Nicklas, K. Moriyama, M. Numao

    Proc. The Seventh International Conference on Knowledge and Systems Engineering (KSE2015)   2015.10

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  • Concept Drift Detection with Self-Organizing Map for Damage Monitoring Reviewed

    Proc. Workshop on Computation: Theory and Practice (WCTP-2015)   2015.9

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  • Individual Sleep Pattern Characterization via Cluster Analysis of Audio Data Reviewed

    Proc. Workshop on Computation: Theory and Practice (WCTP-2015)   2015.9

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  • Investigation of Familiarity Effects in Music-Emotion Recognition based on EEG Reviewed

    N. Thammasan, K. Moriyama, K. Fukui, M. Numao

    Proc. the 2015 International Conference on Brain & Health Informatics (BIH’15)   242 - 251   2015.8

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  • Prediction as Faster Perception in a Real-time Fighting Video Game Reviewed

    K. Asayama, K. Moriyama, K. Fukui, M. Numao

    Proc. the 2015 IEEE Conference on Computational Intelligence and Games (CIG 2015)   2015.8

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  • Effects of Individual Health Topic Familiarity on Activity Patterns During Health Information Searches Reviewed

    Ira Puspitasari, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao

    JMIR Medical Informatics   3 ( 1 )   e16   2015.3

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    DOI: 10.2196/medinform.3803

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  • An analysis of player affect transitions in survival horror games Reviewed

    Vanus Vachiratamporn, Roberto Legaspi, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao

    Journal on Multimodal User Interfaces   9 ( 1 )   43 - 54   2015

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    DOI: 10.1007/s12193-014-0153-4

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  • HEALTH INFORMATION SEARCH PERSONALIZATION WITH SEMANTIC NETWORK USER MODEL Reviewed

    Ira Puspitasari, Ken-Ichi Fukui, Koichi Moriyama, Masayuki Numao

    Theory and Practice of Computation   168 - 177   2015

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  • Predictability analysis of aperiodic and periodic model for long-term human mobility using ambient sensors Reviewed

    Danaipat Sodkomkham, Roberto Legaspi, Ken-Ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Mining, Modeling, and Recommending 'Things' in Social Media, Revised Selected Papers from MUSE 2013 and MSM 2013   131 - 149   2015

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    DOI: 10.1007/978-3-319-14723-9_8

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  • Sidekick: A Tool for Helping Students Manage Behavior in Self-initiated Learning Scenarios Reviewed

    P. S. Inventado, R. Legaspi, K. Moriyama, K. Fukui, M. Numao

    International Journal of Distance Education Technologies   2014.12

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  • Item-Based Learning for Music Emotion Prediction Using EEG Data Reviewed

    P. Vateekul, N. Thammasan, K. Moriyama, K. Fukui, M. Numao

    Proc. 5th International Workshop on Empathic Computing (IWEC’14)   2014.12

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  • Predicting Consumer Familiarity with Health Topics by Query formulation and Search Result Interaction Reviewed

    I. Puspitasari, K. Fukui, K. Moriyama, M. Numao

    Proc. the 13th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2014)   1016 - 1022   2014.12

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  • A Preliminary Study on Quality Control of Oceanic Observation Data by Machine Learning Methods Reviewed

    Satoshi Ono, Haruki Matsuyama, Ken-ichi Fukui, Shigeki Hosoda

    Proc. The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES’2014)   679 - 693   2014.11

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    DOI: 10.1007/978-3-319-13359-1_52

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  • Sidekick: A tool for helping students manage behavior in selfinitiated learning scenarios

    Paul Salvador Inventado, Roberto Legaspi, Koichi Moriyama, Ken-Ichi Fukui, Masayuki Numao

    International Journal of Distance Education Technologies   12 ( 4 )   32 - 54   2014.10

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    DOI: 10.4018/ijdet.2014100103

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  • Detection of Concept Drift on an Adaptive Monitoring System

    Proc. Workshop on Computation: Theory and Practice (WCTP-2014)   2014.10

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  • Discovering seismic interactions after the 2011 Tohoku Earthquake by co-occurring cluster mining Reviewed

    Ken-ichi Fukui, Daiki Inaba, Masayuki Numao

    Transactions of the Japanese Society for Artificial Intelligence   29 ( 6 )   493 - 502   2014.9

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    DOI: 10.1527/tjsai.29.493

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  • An Implementation of Affective Adaptation in Survival Horror Games Reviewed

    V. Vachiratamporn, K. Moriyama, K. Fukui, M. Numao

    Proc. the 2014 IEEE Conference on Computational Intelligence and Games (CIG 2014)   2014.8

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  • Discovery of Damage Patterns in Fuel Cell and Earthquake Occurrence Patterns by Co-occurring Cluster Mining Reviewed

    K. Fukui, D. Inaba, M. Numao

    Proc. The 2014 AAAI Workshop for Discovery Informatics   2014.7

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  • An intelligent fighting videogame opponent adapting to behavior patterns of the user Reviewed

    Koichi Moriyama, Simón Enrique Ortiz Branco, Mitsuhiro Matsumoto, Ken-Ichi Fukui, Satoshi Kurihara, Masayuki Numao

    IEICE Transactions on Information and Systems   E97-D ( 4 )   842 - 851   2014

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    DOI: 10.1587/transinf.E97.D.842

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  • BUILDING POLICIES FOR SUPPORTIVE FEEDBACK IN SELF-DIRECTED LEARNING SCENARIOS Reviewed

    P. S. Inventado, R. Legaspi, K. Moriyama, K. Fukui, M. Numao

    Theory and Practice of Computation (Proceedings of Workshop on Computation: Theory and Practice WCTP2013)   144 - 155   2014

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  • Towards Building Incremental Affect Models in Self-Directed Learning Scenarios Reviewed

    Paul Salvador Inventado, Roberto Legaspi, Ken-ichi Fukui, Koichi Moriyama, Masayuki Numao

    Proceedings of the 21st International Conference on Computers in Education (ICCE2013)   2013.11

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  • Building Incremental Affect Models to Help Students Annotate and Analyze Their Behavior in Self-Directed Learning Scenarios Reviewed

    P. S. Inventado, R. Legaspi, K. Fukui, K. Moriyama, M. Numao

    Proc. of Workshop on Computation: Theory and Practice (WCTP-2013)   2013.10

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  • APP: Aperiodic and Periodic Model for Long-Term Human Mobility Prediction Using Ambient Simple Sensors Reviewed

    D. Sodkomkham, R. Legaspi, K. Fukui, K. Moriyama, S. Kurihara, M. Numao

    Proc. of 4th International Workshop on Mining Ubiquitous and Social Environments (MUSE)   2013.9

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  • Personalization Approach in Health Information Retrieval System Reviewed

    I. Puspitasari, K. Fukui, K. Moriyama, M. Numao

    Proc. of 4th International Workshop on Empathic Computing (IWEC'13)   2013.8

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  • An Architecture for Identifying and Using Effective Learning Behavior to Help Students Manage Learning Reviewed

    P.S. Inventado, R. Legaspi, K. Moriyama, K. Fukui, M. Numao

    Proc. of Formative Feedback in Interactive Learning Environments   2013.7

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  • Towards Building Incremental Affect Models in Self-Directed Learning Scenarios Reviewed

    P. S. Inventado, R. Legaspi, K. Fukui, K. Moriyama, M. Numao

    Proc. of the 21st International Conference on Computers in Education (ICCE 2013)   2013.4

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  • Evolutionary distance metric learning approach to semi-supervised clustering with neighbor relations Reviewed

    Ken-Ichi Fukui, Satoshi Ono, Taishi Megano, Masayuki Numao

    Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI   398 - 403   2013

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    DOI: 10.1109/ICTAI.2013.66

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  • Intelligent analysis for evaluating physical degradation using acoustic emission Reviewed

    K. Fukui, K. Sato, T. Hashida, J. Mizusaki, M. Numao

    ECS Transactions   57 ( 1 )   571 - 580   2013

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    DOI: 10.1149/05701.0571ecst

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  • Identification of effective learning behaviors Reviewed

    Paul Salvador Inventado, Roberto Legaspi, Rafael Cabredo, Koichi Moriyama, Ken-Ichi Fukui, Satoshi Kurihara, Masayuki Numao

    Proc. The 16th International Conference on Artificial Intelligence in Education (AIED 2013)   670 - 673   2013

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    DOI: 10.1007/978-3-642-39112-5-85

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  • Estimating Emotions on Music Based on Brainwave Analyses Reviewed

    Yu Yamano, Rafael Cabredo, Paul Salvador, Inventado, Roberto Legaspi, Koichi Moriyama, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    The 3rd International Workshop on Empathic Computing (IWEC-2012)   1 - 10   2012.9

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  • Investigating the Relation between Brainwaves and Emotions in Music Reviewed

    Yu Yamano, Rafael Cabredo, Paul Salvador, Inventado, Roberto Legaspi, Koichi Moriyama, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    Workshop on Computation: Theory and Practice (WCTP-2012)   1 - 10   2012.9

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  • Mining of Co-occurring Clusters for Damage Pattern Extraction of a Fuel Cell Reviewed

    Daiki Inaba, Ken-ichi Fukui, Kazuhisa Sato, Junichirou Mizusaki, Masayuki Numao

    Transactions of the Japanese Society for Artificial Intelligence   27 ( 3 )   121 - 132   2012

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    DOI: 10.1527/tjsai.27.121

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  • Time-Interval Clustering in Sequence Pattern Recognition as Tool for Behavior Modeling Reviewed

    Roberto Legaspi, Danaipat Sodkomkham, Kazuya Maruo, Kenichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Theory and Practice of Computation (Post Proc. Workshop on Computation: Theory and Practice WCTP-2011)   174 - 186   2012

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  • Co-occurring cluster mining for damage patterns analysis of a fuel cell Reviewed

    Daiki Inaba, Ken-ichi Fukui, Kazuhisa Sato, Junichirou Mizusaki, Masayuki Numao

    Proc. The 16th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD2012)   49 - 60   2012

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    DOI: 10.1007/978-3-642-30220-6_5

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  • Neighborhood-based smoothing of external cluster validity measures Reviewed

    Ken-ichi Fukui, Masayuki Numao

    Proc. The 16th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD2012)   354 - 365   2012

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    DOI: 10.1007/978-3-642-30217-6_30

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  • Time-Interval Clustering in Sequential Pattern Recognition Towards Predictive Modeling of Human Characteristics Reviewed

    Roberto Legaspi, Danaipat Sodkomkham, Kazuya Maruo, Kenichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Proceedings of the Workshop on Computation: Theory and Practice (WCTP2011)   2011.9

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  • Clustering Multiple and Flexible Time Intervals in Sequential Patterns Towards Predictive Modeling of Human Gait Behavior Reviewed

    Roberto Legaspi, Danaipat Sodkomkham, Kazuya Maruo, Kenichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Proceedings of the International Workshop on Finding Patterns of Human Behaviors in Network and Mobility Data (NEMO)   2011.9

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  • Mining Frequent Sequences with Flexible Time Intervals Reviewed

    Kazuya Maruo, Danaipat Sodkomkham, Ken-ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Proceedings of the 1st International Workshop of Sensor Data Mining (IWSDM2011)   2011.6

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  • Extraction of Essential Events Using SOM and KeyGraph: Application to Damage Analysis on of Fuel Cells Reviewed

    T. Kitagawa, K. Fukui, K. Sato, J. Mizusaki, M. Numao

    Transactions on Mathematical Modeling and its Applications   4 ( 2 )   55 - 66   2011.3

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    Other Link: http://id.nii.ac.jp/1001/00073757/

  • Topographic measure based on external criteria for self-organizing map Reviewed

    Ken-ichi Fukui, Masayuki Numao

    Proc. Workshop on Self-Organizing Maps WSOM2010 (Lecture Notes in Computer Science)   6731   131 - 140   2011

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    DOI: 10.1007/978-3-642-21566-7_13

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  • Exploring melodic motif to support an affect-based music compositional intelligence Reviewed

    Roberto Legaspi, Akinobu Ueda, Rafael Cabredo, Takayuki Nishikawa, Kenichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Proceedings - 2011 3rd International Conference on Knowledge and Systems Engineering, KSE 2011   219 - 225   2011

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    DOI: 10.1109/KSE.2011.42

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  • Visualization of Damage Progress in Solid Oxide Fuel Cells Reviewed

    FUKUI Ken-ichi, AKASAKI Shogo, SATO Kazuhisa, MIZUSAKI Junichiro, MORIYAMA Koichi, KURIHARA Satoshi, NUMAO Masayuki

    JEE   6 ( 3 )   499 - 511   2011

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    The fuel cell is regarded as a highly efficient, low-pollution power generation system. In particular, Solid Oxide Fuel Cell (SOFC) has a high generation efficiency. However, a crucial issue in putting SOFC to practical use is the establishment of a technique for evaluating the deterioration. We previously developed a technique by which to measure the mechanical damage of SOFC using the Acoustic Emission (AE) method. In the present paper, we applied the kernel Self-Organizing Map (SOM), which is an extended neural network model, to produce a cluster map reflecting the similarity of AE events. The obtained map visualized the change in occurrence patterns of similar AE events, revealing four phases of damage progress. The methodology of the present study provides a common foundation for a comprehensive damage evaluation system and a damage monitoring system.

    DOI: 10.1299/jee.6.499

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  • Extraction of Essential Events with Application to Damage Evaluation on Fuel Cells Reviewed

    Teppei Kitagawa, Ken-ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Masayuki Numao

    Smart Innovation, Systems and Technologies (Post Proc. of the 2nd International Workshop on Combining Intelligent Methods and Applications (CIMA-10))   8   89 - 108   2011

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    DOI: 10.1007/978-3-642-19618-8_6

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  • Kullback-Leibler Divergence Based Kernel SOM for Visualization of Damage Process on Fuel Cells Reviewed

    Ken-ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Masayuki Numao

    Proc. of 22th IEEE International Conference on Tools with Artificial Intelligence (ICTAI-10)   1   233 - 240   2010.10

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  • Three-Subagent Adapting Architecture for Fighting Videogames Reviewed

    Simon E. Ortiz B, Koichi Moriyarna, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    PRICAI 2010: TRENDS IN ARTIFICIAL INTELLIGENCE   6230   649 - +   2010.8

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  • 固体酸化物燃料電池における損傷過程の可視化 Reviewed

    福井 健一, 赤崎 省悟, 佐藤 一永, 水崎 純一郎, 森山 甲一, 栗原 聡, 沼尾 正行

    日本機械学会論文集A編   2010.2

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  • Addressing the problems of data-centric physiology-affect relations modeling Reviewed

    Roberto Legaspi, Ken-Ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao, Merlin Suarez

    International Conference on Intelligent User Interfaces, Proceedings IUI   21 - 30   2010

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    DOI: 10.1145/1719970.1719974

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  • Positing a Growth-Centric Approach in Empathic Ambient Human-System Interaction Invited

    R. Legaspi, K. Fukui, K. Moriyama, S. Kurihara, M. Numao

    Human-Computer Systems Interaction   2009.10

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  • Growth Analysis of Neighbor Network for Evaluation of Damage Progress Reviewed

    Ken-ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Proc. the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09)   933 - 940   2009.4

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    DOI: 10.1007/978-3-642-01307-2_98

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  • Compilation to Visualize the Dynamic Clusters by the Adapted Self- Organizing Network Reviewed

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Transactions of the Japanese Society for Artificial Intelligence   23 ( 5 )   319 - 329   2008.9

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    DOI: 10.1527/tjsai.23.319

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  • Reinforcement Learning on a Futures Market Simulator Invited Reviewed

    Koichi Moriyama, Mitsuhiro Matsumoto, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    Journal of Universal Computer Science   14 ( 7 )   1136 - 1153   2008.6

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    DOI: 10.3217/jucs-014-07-1136

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  • Self-improving Empathy Learning Reviewed

    Roberto Legaspi, Satoshi Kurihara, Ken-ichi Fukui, Koichi Moriyama, Masayuki Numao

    Proc. 5th International Conference on Information Technology and Applications (ICITA-08)   2008.4

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  • Reinforcement learning on a futures market simulator Reviewed

    Koichi Moriyama, Mitsuhiro Matsumoto, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    Journal of Universal Computer Science   14 ( 7 )   1136 - 1153   2008

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  • Pheromone approach to the adaptive discovery of sensor-network topology Reviewed

    Hiroshi Tamaki, Ken-Ichi Fukui, Masayuki Numao, Satoshi Kurihara

    Proceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008   41 - 47   2008

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    DOI: 10.1109/WIIAT.2008.143

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  • An empathy learning problem for HSI: To be empathic, self-improving and ambient Reviewed

    Roberto Legaspi, Satoshi Kurihara, Ken-Ichi Fukui, Koichi Moriyama, Masayuki Numao

    2008 Conference on Human System Interaction, HSI 2008   209 - 214   2008

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    DOI: 10.1109/HSI.2008.4581435

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  • Sequence-based SOM: Visualizing Transition of Dynamic Clusters Reviewed

    Ken-Ichi Fukui, Masahiro Kimura, Kazumi Saito, Masayuki Numao

    Proceedings - 2008 IEEE 8th International Conference on Computer and Information Technology, CIT 2008   47 - 52   2008

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    DOI: 10.1109/CIT.2008.4594648

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  • Acquisition of Sensor-Network Topology Based on Multi-Agent Pheromonal Coordination Reviewed

    Hiroshi Tamaki, Ken-ichi Fukui, Masayuki Numao, Satoshi Kurihara

    Proc. the Workshop on Heterogeneous Agent Systems and Complex Networks in European Conference on Complex Systems (ECCS-07)   2007.10

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  • Combining Burst Extraction Method and Sequence-based SOM for Evaluation of Fracture Dynamics in Solid Oxide Fuel Cell Reviewed

    Ken-ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Kazumi Saito, Masayuki Numao

    Proc. 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI-07)   ( 2 )   193 - 196   2007.10

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    DOI: 10.1109/ICTAI.2007.94

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  • フェロモンを介したエージェント協調モデルによるセンサー隣接関係構築法の提案 Reviewed

    玉置洋, 福井健一, 沼尾正行, 栗原聡

    情報科学技術レターズ   vol.6   153 - 156   2007.9

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  • 固体酸化物燃料電池における破壊ダイナミクスの可視化法 Reviewed

    福井健一, 佐藤一永, 水崎純一郎, 斉藤和巳, 沼尾正行

    情報科学技術レターズ   6   5 - 8   2007.9

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  • Interpretable Likelihood for Vector Representable Topic Reviewed

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Proc. 11th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems (KES-07)   4694   202 - 209   2007.9

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  • Reinforcement learning on a futures market simulator Reviewed

    Koichi Moriyama, Mitsuhiro Matsumoto, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    JOURNAL OF UNIVERSAL COMPUTER SCIENCE   14 ( 7 )   1136 - 1153   2007.5

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  • ベクトル表現可能な機械抽出トピックの定量的評価法 Reviewed

    福井健一, 斉藤和巳, 木村昌弘, 沼尾正行

    情報処理学会論文誌:数理モデル化と応用   48 ( 6 )   1 - 11   2007.3

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  • Automatic acquisition of sensor-network topology based on pheromone communication model Reviewed

    Hiroshi Tamaki, Ken-ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    4th International Conference on Networked Sensing Systems, INSS   292   2007

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    DOI: 10.1109/INSS.2007.4297434

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  • Extracting human behaviors with infrared sensor network Reviewed

    Seiichi Honda, Ken-ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    4th International Conference on Networked Sensing Systems, INSS   122 - 125   2007

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    DOI: 10.1109/INSS.2007.4297404

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  • Visualization Architecture Based on SOM for Two-Class Sequential Data Reviewed

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Proc. 10th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems (KES-06)   929 - 936   2006.10

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    DOI: 10.1007/11893004_119

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  • CONCORによるリンク解析を反映したWeb文書の要約

    山下 長義, 福井 健一, 森山 甲一, 栗原 聡, 沼尾 正行

    第5回情報科学技術フォーラム (FIT2006) 講演論文集   2006.9

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  • Getting Daily Human Habitual Behaviours from Infrared Sensor Network Reviewed

    Satoshi Kurihara, Seiichi Honda, Kenichi Fukui, Koichi Moriyama, Masayuki Numao, Kensuke Fukuda, Toshio Hirotsu, Toshihiro Takada, Toshiharu Sugawara

    Proceedings of the 3rd International Conference on Networked Sensing Systems (INSS2006)   2006.6

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  • A Cluster-based Predictive Modeling to Improve Pedagogic Reasoning Reviewed

    Roberto Legaspi, Raymund Sison, Kenichi Fukui, Masayuki Numao

    COMPUTERS IN HUMAN BEHAVIOR   24 ( 2 )   153 - 172   2005.12

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    DOI: 10.1016/j.chb.2007.01.007

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  • Predicting High-level Student Responses Using Conceptual Clustering Reviewed

    Roberto Legaspi, Raymund Sison, Kenichi Fukui, Masayuki Numao

    Frontiers in Artificial Intelligence and Applications   2005.11

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  • Visualizing Dynamics of the Hot Topics Using Sequence-Based Self-organizing Maps Reviewed

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Proc. 9th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems (KES-05)   745 - 751   2005.9

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  • Numerical Simulation of Pulsating Flow in Contraction Pipe Reviewed

    Kohge K, Minemura K, Fukui K

    2005.4

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Books

  • Pythonで学ぶAI活用入門

    福井健一( Role: Sole author)

    日本技能教育開発センター  2020.2 

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  • 識別・予測・異常検知 : Pythonと実例で学ぶ機械学習

    福井 健一( Role: Sole author)

    オーム社  2018.11  ( ISBN:9784274222788

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    Total pages:viii, 148p   Language:Japanese  

    CiNii Books

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  • 群知能とデータマイニング

    Abraham, Ajith, Grosan, Crina, Ramos, Vitorino, 訳)栗原 聡, 福井 健一

    東京電機大学出版局  2012.7  ( ISBN:9784501550905

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    Total pages:xviii, 307p   Language:Japanese  

    CiNii Books

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MISC

  • 機械学習による睡眠評価と睡眠改善に向けて Invited

    福井健一, 加藤隆史

    人工知能   35 ( 4 )   495 - 503   2020.7

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  • 学生論文特集の発行にあたって

    福井健一

    電子情報通信学会和文論文誌D   J107-D ( 4 )   138 - 139   2024.4

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  • 機械学習による振動データからの転がり軸受の余寿命予測

    福井健一

    時系列データ解析における課題対応と解析例, 情報機構   259 - 270   2024.1

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  • ハイテク推進セミナー AIによる音響・振動データからの知識発見と予測

    福井健一

    生産と技術, 生産技術振興協会   75 ( 2 )   2023.3

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    Publishing type:Internal/External technical report, pre-print, etc.  

    J-GLOBAL

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  • Micro Defect Detection and Remaining Useful Life Prediction of Rolling Bearing by Machine Learning

    福井健一

    ターボ機械   51 ( 3 )   2023

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    J-GLOBAL

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  • 機械学習による回転機器の初期欠陥検出と余寿命予測

    福井健一

    機械学習・デ ィープラーニングによる”異常検知”技術と活用事例集, 技術情報協会   297 - 309   2022.12

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  • 機械学習による回転機器の異常検知

    福井健一

    プラントのDX化による生産 性の向上、保全の高度化, 技術情報協会   369 - 379   2022.4

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  • Development of a Machine Learning Algorithm to Improve Defect Detection Accuracy for Rolling Bearings

    北井正嗣, 赤松良信, 福井健一

    NTN Technical Review   ( 88 )   2021

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    J-GLOBAL

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  • The Past and Present of AI and Prospects in Manufacture

    福井健一

    NTN Technical Review   ( 88 )   2021

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    J-GLOBAL

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  • 睡眠中の生体活動に基づく睡眠個性の可視化と良否判別

    福井健一

    ウェアラブル医療・ヘルスケア機器の技術と市場, シーエムシー出版   108 - 114   2020.10

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  • 機械学習モデルの性能評価方法 Invited

    福井健一

    データ分析の進め方及び AI・機械学習導入の指南, 情報機構   121 - 127   2020.6

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  • 機械学習による異常検知法 Invited

    福井健一

    機械学習を中心とした異常検知技術と応用提案, 情報機構   15 - 16   2019.11

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  • 睡眠中の生体活動に基づく睡眠個性の可視化と良否判別 Invited

    福井健一

    BIO INDUSTRY   36 ( 11 )   79 - 86   2019.11

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  • AI活用による回転機器における微小欠陥の異常検知 Invited

    福井健一

    人と共生するAI革命ー人と共生するAI革命―活用事例からみる生活・産業・社会の未来展望, NTS   201 - 208   2019.6

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  • (書評)フリーソフトではじめる機械学習入門 Python/Wekaで実践する理論とアルゴリズム Invited

    福井健一

    人工知能   33 ( 4 )   2018.7

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  • 人工知能による良質な睡眠の解析技術〜「いびき,歯ぎしり,体動」の音から睡眠の特徴を分析する〜 Invited

    福井健一

    人工知能の導入による生産性、効率性の向上、新製品開発への活用, 技術情報協会   259 - 268   2018.5

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  • 特集「人工知能と人材」にあたって

    福井健一, 芦川将之

    人工知能   33 ( 3 )   258   2018.5

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  • 2016年度研究会優秀賞受賞論 文紹介,”Proposition of Kernelized Evolutionary Distance Metric Learning for Semisupervised Clustering”

    Kalintha Wasin, 小野智司, 沼尾正行, 福井健一

    人工知能   33 ( 1 )   60 - 61   2018.1

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    Authorship:Last author   Language:Japanese   Publishing type:Rapid communication, short report, research note, etc. (scientific journal)  

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  • 音から睡眠の良否を判別する人工知能技術 Invited

    福井健一

    日経ビッグデータ   2017.10

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  • (編集委員今年の抱負2017) AI技術者人材育成

    福井健一

    人工知能   32 ( 1 )   68   2017.1

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  • (会議報告) CEC2015

    福井健一

    人工知能   30 ( 4 )   556   2015.7

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  • 事象系列データからの共起性マイニング─燃料電池の損傷間および地震間の相互作用抽出─ Invited

    福井健一, 沼尾正行

    人工知能   30 ( 2 )   238 - 246   2015.3

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)   Publisher:人工知能学会 ; 2014-  

    CiNii Books

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    Other Link: http://id.nii.ac.jp/1004/00001795/

  • 特集「データ中心科学」にあたって

    福井健一

    人工知能   30 ( 2 )   207 - 208   2015.3

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  • (編集委員会企画ー社会とAIの羅針盤2015) 人と調和したデータ中心科学

    福井健一

    人工知能   30 ( 1 )   32   2015.1

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  • (会議報告) AAAI2014

    福井健一

    人工知能   29 ( 6 )   740 - 741   2014.11

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  • (文献紹介) Machine Learning that Matters Invited

    福井健一

    人工知能   29 ( 2 )   217 - 219   2014.3

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  • Editors' Introduction to "Green AI"

    28 ( 4 )   512 - 513   2013.7

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    CiNii Books

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  • データマイニング・オントロジー工学による燃料電池の信頼性診断・知識管理基盤技術 Invited

    福井健一, 高藤淳, 佐藤一永, 沼尾正行, 溝口理一郎

    人工知能   28 ( 4 )   535 - 542   2013.7

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    Authorship:Lead author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)   Publisher:人工知能学会  

    CiNii Books

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    Other Link: http://id.nii.ac.jp/1004/00008310/

  • オーガナイズドセッション報告 IOS-01 「Application Oriented Principles of Machine Learning and Data Mining」

    ナッティー チョラウィト, 福井健一

    人工知能学会誌   27 ( 6 )   672 - 672   2012.11

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  • OS-19 グリーンAI : AIによる環境貢献(オーガナイズドセッション報告,<特集>2012年度人工知能学会全国大会(第26回))

    柴田 博仁, 森 幹彦, 福井 健一, 松井 孝典

    人工知能学会誌   27 ( 6 )   668 - 669   2012.11

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    Language:Japanese   Publishing type:Meeting report   Publisher:一般社団法人 人工知能学会  

    DOI: 10.11517/jjsai.27.6_668

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  • 視覚的データマイニングによる固体酸化物燃料電池の損傷評価支援

    福井健一

    KRF report, 関西エネルギー・リサイクル科学研究振興財団   6 - 7   2011

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  • Tracking and Visualizing the Cluster Dynamics by Sequence-based SOM Invited

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Self-Organizing Maps, IN-TECH   97 - 112   2010

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Presentations

  • ニューラル演算子から法則発見まで Invited

    福井 健一

    名大ISEE研究集会「情報科学技術との融合による太陽圏物理学の新展開」  2024.9 

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    Event date: 2024.9

    Presentation type:Oral presentation (general)  

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  • 人工知能による睡眠個性可視化と良否判別 Invited

    福井健一

    日本顎口腔機能学会学術大会プログラム・事前抄録集  2022 

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    Event date: 2022

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  • 時空間データからの知識発見と予測:睡眠・気象・産業へのAI応用 Invited

    福井 健一

    人工知能学会 第135回 知識ベースシステム研究会  2025.8 

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  • Enhancing Sound-Based Sleep Quality Assessment by Multimodal Knowledge Distillation

    Haoyu Lu, Takafumi Kato, Ken-ichi Fukui

    2025年度 人工知能学会全国大会(第39回)  2025.5 

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  • Multi-Model Data Transfer by Knowledge Distillation for Enhancing Precipitation Nowcasting

    QIHANG WANG, Tomohiko Tomita, Ken-ichi Fukui

    2025.5 

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  • Uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery

    Pongpisit Thanasutives, Ken-ichi Fukui

    2024.11 

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  • 睡眠音に基づくVAE-LSTMによる睡眠良否判別とTimeSHAPによる睡眠個性の分析

    玉井慎太郎, 沼尾正行, 福井健一

    2024年度人工知能学会全国大会(第38回)  2024.5 

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  • Gated Variable Selection Neural Network for Multimodal Sleep Quality Assessment

    Yue Chen, Takashi Morita, Tsukasa Kimura, Takafumi Kato, Masayuki Numao, Ken-ichi Fuku

    2023.6 

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  • 機械学習による転がり軸受の微小欠陥検出と余寿命予測 Invited

    福井健一

    ターボ機械協会第168回セミナー「ターボ機械とICT/IoT技術」  2023.6 

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  • 階層ベイズを用いた欠陥進展下の転がり軸受の余寿命曲線推定

    北井正嗣, 赤松良信, 藤原宏樹, 谷僚二, 沼尾正行, 福井健一

    2021年度人工知能学会全国大会(第35回)  2021.6 

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  • Learning to Solve Multiple Partial Differential Equations Using Physics-informed Neural Networks

    Pongpisit Thanasutives, Masayuki Numao, Ken-ichi Fukui

    2021.6 

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  • Spatio-Temporal Change Detection Using Granger Causal Relation

    Nat Pavasant, Masayuki Numao, Ken-ichi Fukui

    2020年度人工知能学会全国大会(第34回)  2020.6 

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  • データ駆動とモデル駆動の融合によるディープラーニングと気象予測 Invited

    福井健一

    IT連携フォーラムOACIS第36回シンポジウム  2019.7 

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  • 物理過程に基づくニューラルネットワークを用いたモデル残差項の学習

    田中潤也, 冨田智彦, 沼尾正行, 福井健一

    2019年度人工知能学会全国大会(第33回)  2019.6 

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  • Sleep Pattern Modelling for Quality Prediction based on Sound Data

    Hongle Wu, Takafumi Kato, Masayuki Numao, Ken-ichi Fukui

    電子情報通信学会人工知能と知識処理研究会  2017.11 

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  • Proposition of Kernelized Evolutionary Distance Metric Learning for Semi-supervised Clustering

    Wasin Kalinta, Satoshi Ono, Masayuki Numao, Ken-ichi Fukui

    人工知能学会第109回知識ベースシステム研究会(SIG-KBS)  2016.11 

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  • 深層学習を用いたメロディ生成とその参照情報

    諏訪辺拓, 森田尭, 福井健一, 沼尾正行

    情報処理学会研究報告(Web)  2024 

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  • 機械学習のクラスタリング技術を用いたアリソフ気候区分の改訂

    島袋琉, 冨田智彦, 福井健一

    日本気象学会大会講演予稿集(CD-ROM)  2022 

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  • Selection of features for Impressionist painting recommendations

    桂田紗希, 森田尭, 木村司, 福井健一, 沼尾正行

    人工知能学会全国大会論文集(Web)  2022 

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  • Machine Learning Prediction of Precipitation in Metro Manila, Philippines

    野田明羅, 高橋幸弘, 久保田尚之, 福井健一, 佐藤光輝

    日本地球惑星科学連合大会予稿集(Web)  2022 

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  • Time Series Classification with a Few Shapelets

    小寺謙斗, 沼尾正行, 福井健一

    人工知能学会全国大会論文集(Web)  2020 

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  • Evaluation and Analysis of Video Contents Using Physiological Information and VR Environment

    浦地勇人, 松村昂輝, HAGAD Juan Lorenzo, 福井健一, 沼尾正行

    人工知能学会全国大会論文集(Web)  2019 

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  • Sleep Pattern Modelling for Quality Prediction based on Sound Data (人工知能と知識処理)

    WU Hongle, KATO Takafumi, NUMAO Masayuki, FUKUI Ken-ichi

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報  2017.11  電子情報通信学会

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  • Big Data Analysis of Single Particle Mass Spectrum Data for Chemical Characterization of PM2.5: An Example from the Analysis of Beijing PM2.5 Observation

    FURUTANI Hiroshi, Nat Pavasant, FUKUI Kenichi, MAEDA Kouki, TOYODA Michisato, KIMOTO Takashi, MA Tao, DUAN Fengkui, MA Yongliang, HE Kebin

    2017 

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    Language:Japanese  

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  • Proposition of Kernelized Evolutionary Distance Metric Learning for Semi-supervised Clustering (「知識表現・知識獲得とその応用」および一般)

    Kalintha Wasin, Ono Satoshi, Numao Masayuki, Fukui Ken-ichi

    知識ベースシステム研究会  2016.11  人工知能学会

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    Language:English  

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  • A Development of Multi-objective Optimization Support System for Renewable Energy Implementation : REROUTES

    2016.10 

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    Language:Japanese  

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  • Structure Visualization of Oceanic Data using Clustering

    2016.7 

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    Event date: 2016.7

    Language:Japanese  

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  • Structure Visualization of Oceanic Data using Clustering

    2016.7 

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    Event date: 2016.7

    Language:Japanese  

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  • 進化計算による再生可能エネルギーミックスの多目的最適化

    堀 啓子, 松井 孝典, 小野 智司, 福井 健一, 蓮池 隆, 町村 尚

    人工知能学会全国大会論文集  2016  一般社団法人 人工知能学会

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    Event date: 2016

    Language:Japanese  

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  • Dry electrode EEG-based music emotion recognition

    Proc. The 19th SANKEN International The 14 SANKEN Nanotechnology Symposium  2015.12 

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    Language:English  

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  • 教師なし学習における非データ分布依存型コンセプトドリフト検出手法の検証

    坂本 悠輔, 福井 健一, Joao Gama, Daniela Nicklas, 森山 甲一, 沼尾 正行

    情報処理学会研究報告. MPS, 数理モデル化と問題解決研究報告  2015.2  一般社団法人情報処理学会

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    Event date: 2015.2

    Language:Japanese  

    近年,コンピュータやセンサ技術の発達からデータをデータストリームとして連続的に獲得できる環境が増加している.しかし,現在これらの豊富なデータから十分に知識を獲得できているとは言えない.データストリームに対して学習手法を用いて知識の獲得を試みる際には,時間の経過と共に学習すべき概念が変化すること,つまりコンセプトドリフトに対応する必要がある.そのための方法の一つとしてコンセプトドリフト検出手法がある.これまで,コンセプトドリフト検出手法の研究は教師あり学習を中心に行われてきた.教師なし学習においても研究は行われ,一定の成果は収めたが計算量が大きいという欠点があった.そこで,本研究では,教師なし学習において計算量の少ないコンセプトドリフト検出手法を目指して,教師あり学習と信号処理において効果が確認されているコンセプトドリフト検出手法を応用し実験を行った.その結果,今後のコンセプトドリフト検出手法の開発において重要な知見を得た.

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  • 再生可能エネルギーミックスの地域別最適化とクラスタリングによる需給特性の俯瞰

    堀 啓子, 松井 孝典, 蓮池 隆, 福井 健一, 町村 尚

    人工知能学会全国大会論文集  2015  一般社団法人 人工知能学会

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    Event date: 2015

    Language:Japanese  

    &lt;p&gt;本研究では、自身が開発した再生可能エネルギーの地域別最適化および評価ツールを用い、日本の全市区町村を対象にファジィ数理モデルによって再生可能エネルギーの組み合わせ最適解および評価指標の値を算出した。更に得られた解を用いてエネルギー需給や地域特性によるクラスタリングを行うことで、市区町村を類型化し、地域適合型のエネルギー計画策定に資する知見を得た。&lt;/p&gt;

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  • Estimating Affects on Music with Machine Learning

    2015 

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    Language:Japanese  

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  • Acceleration of learning strategies in repeated games using reinforcement learning

    2015 

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    Event date: 2015

    Language:Japanese  

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  • Prediction of the Opponent's Position and Action in a Fighting Video Game with the Linear Extrapolation and the k-Nearest Neighbor Method

    2015 

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  • 順序や生起間隔を考慮したクラスタ系列パターン抽出法の提案(機械学習によるバイオデータマインニング,一般)

    岡田 佳之, 福井 健一, 沼尾 正行

    電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習  2014.6  一般社団法人電子情報通信学会

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    Event date: 2014.6

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    本研究では,我々が以前に提案した共起クラスタマイニング(CCM)という手法の改良に取り組む.共起クラスタマイニングとは,複数のクラスタ間における共起性とクラスタ内の類似性を同時に考慮し,共起する2つのクラスタの範囲を決定する手法である.しかし,これまでクラスタ内の事象の時系列上の前後関係や生起間隔は簡単のため考慮していない.そこで今回は,新たにそれらを含めたクラスタ系列パターンの抽出を目指す.その中で,ベイズ推定を用いた手法を提案する.

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  • Facial Image Clustering by Evolutionary Distance Metric Learning

    MEGANO Taishi, ONO Satoshi, FUKUI Ken-ichi, NINOMIYA Kohki, NUMAO Masayuki, NAKAYAMA Shigeru

    Technical report of IEICE. Multimedia and virtual environment  2014.1  The Institute of Electronics, Information and Communication Engineers

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    In data mining and machine learning, the definition of distance between two data points substantially affects clustering and classification tasks. We previous work by the author proposed a distance metric learning method based on a clustering index with neighbor relation that simultaneously evaluates inter- and intra-clusters. This method requires the number of all pairwise constraints, whereas general distance metric learning methods requires. This study is an attempt to apply this method for facial image clustering.

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  • Learning to coordinate in repeated games using ensemble reinforcement learning

    2014 

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  • 共起クラスタマイニングー数値観測量の事象系列に対する頻出パターン抽出ー

    稲場大樹, 福井健一, 沼尾正行

    全国大会講演論文集  2013.3  一般社団法人情報処理学会

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    Event date: 2013.3

    Language:Japanese  

    本研究では、波形や位置情報など特徴量で表される事象の系列から、系列データ上で互いに近接しており、かつ頻出する事象のペアである共起パターンを抽出する「共起クラスタマイニング」という手法を提案する。提案手法は、時系列上におけるクラスタ「間」の共起性と、特徴空間におけるクラスタ「内」の類似性を同時に考慮して、2つのクラスタの範囲を決定する手法である。まず、人工データを用いて単純な共起パターン抽出法(2段階法)と提案手法の評価を行った。次に、実データへの適用例として、燃料電池の損傷評価試験から得られた波形データと、2011年の東北地方太平洋沖地震の震源リストデータへ適用し、共起パターンの抽出を行った。

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  • J056011 Information Technique for Improvement of Reliability on Solid Electrochemical Devices

    SATO Kazuhisa, FUKUI Kenichi, NUMAO Masayuki, KUWATA Naoaki, KAWAMURA Junichi, HASHIDA Toshiyuki

    Mechanical Engineering Congress, Japan  2012.9  The Japan Society of Mechanical Engineers

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    Event date: 2012.9

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    New energy conversion systems develop in environmental fields, and make its presence greater and greater. Data mining method was developed in order to investigate the mechanical and electrochemical degradations process of solid electrochemical devices under operating conditions. By using this method, it was possible to show and help the possibility that detailed degradation process can be evaluated visually and in real-time, even when applied to modules at the actual equipment level. On the other hand, as service science intends to scientifically reveal the mechanism and principle in order to create new energy devices, there emerges a lot of interdisciplinary approach of the brand-new field. While traditional marketing theories have provided frameworks of how to grasp, reach, and lure as many customers as possible, none of them can externalize the functional structure of any service knowledge, and offer methodology of handling them on computer. Aiming at computationally utilizing any service knowledge, we discuss service ontology by both analogies with functional ontology on ontology engineering, and by comparison with typical marketing theory. In addition, we introduce case study that are based on ontology, and show how to create knowledge by this theory.

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  • Metric Learning based on Global Cluster Validity Index

    2012.2 

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  • Extracting Time Series Motifs for Emotion and Behavior Modeling

    Masayuki Numao, Rafael Cabredo, Danaipat Sodkomkham, Kazuya Maruo, Roberto Legaspi, Ken-ichi Fukui, Koichi Moriyama, Satoshi Kurihara

    Proceedings of the 15th SANKEN International Symposium  2012.1 

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  • Association Rule-based Analysis of Neighborhood Server Logs

    2012 

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  • Damage Pattern Analysis of a Fuel Cell by Co-occurring Cluster Mining

    2012 

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  • Extraction of Damage Patterns of a Fuel Cell by Clustering Considering Co-occurrence between Events

    INABA Daiki, FUKUI Ken-ichi, SATO Kazuhisa, MIZUSAKI Junichirou, NUMAO Masayuki

    2011.11  The Institute of Electronics, Information and Communication Engineers

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    Solid oxide fuel cell (SOFC) is an efficient generator and researched for practical use. However, one of the problems is the durability. In this study, we research the mechanical correlations among components of SOFC by analyzing the co-occurrence of acoustic emission (AE) events which are caused by damage. Then we propose a novel method for mining patterns from the numerical data like AE. The proposed method extracts patterns of two clusters considering co-occurrence between clusters and similarity within each cluster. We applied the proposed method to AE data, and acquired novel knowledge about damage mechanism of SOFC from the results.

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  • Extracting frequent sequences with flexible time interval from time series data

    2011.1 

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  • Recommendation Based on Users' Similar Habits of Mobile Applications

    2011 

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    Language:Japanese  

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  • Automatic composition system considering music structure including melody

    2011 

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  • An Interesting Opponent for Fighting Videogames

    ORTIZ B. SIMON E., MORIYAMA KOICHI, FUKUI KEN-ICHI, KURIHARA SATOSHI, NUMAO MASAYUKI

    2010.3 

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    Other Link: http://id.nii.ac.jp/1001/00068064/

  • Extraction of Damage Patterns on Fuel Cell

    2010.2 

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    Other Link: http://id.nii.ac.jp/1001/00068009/

  • Performance of Kernel SOM Considering Adjacency for Damage Evaluation

    2010.1 

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    Other Link: http://id.nii.ac.jp/1001/00067622/

  • Adaptive AI in a Fighting Videogame

    Simon E, Ortiz B, Koichi Moriyama, Mitsuhiro Matsumoto, Ken-ichi Fukui, Satoshi Kurihara, Masayuki Numao

    Proceedings of the 13th SANKEN International Symposium  2010.1 

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  • Applying a Cost-effective and Efficient Data-centric Approach to the Physiology-Affect Relations Modeling Domain

    Roberto Legaspi, Ken-ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao, Merlin Suarez

    Proceedings of the 13th SANKEN International Symposium  2010.1 

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  • Positing a Growth-Centric Approach in Empathic Ambient Human-System Interaction Invited

    R. Legaspi, K. Fukui, K. Moriyama, S. Kurihara, M. Numao

    HUMAN-COMPUTER SYSTEMS INTERACTION: BACKGROUNDS AND APPLICATIONS  2009.10 

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  • リズムを含めた楽曲構造を考慮した自動作曲システム

    上田 明頌, 西川 敬之, 福井 健一, 森山 甲一, 栗原 聡, 沼尾 正行

    人工知能学会全国大会(第23回)論文集  2009.6 

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  • Acquiring listerners' sensibility information using a music structure containing rhythm

    2009 

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  • Music Recommendation System that Predicts Affective Changes Based on Brain Wave Analysis

    2009 

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  • Evaluation Method for Mechanical Performance of Solid Oxide Fuel Cell under Simulated Operating Conditions

    Kazuhisa Sato, Ken-ichi Fukui, Masayuki Numao, Toshiyuki Hashida, Junichiro Mizusaki

    Proc. ASME 7th International Fuel Cell Science, Engineering and Technology Conference  2009 

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  • A study of damage progress by growth analysis of neighbor network

    2008.11 

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  • Obtaining the Topological Map of Sensor Network with Pheromone System

    Hiroshi Tamaki, Ken-ichi Fukui, Masayuki Numao, Satoshi Kurihara

    Proc. of the 11th SANKEN International Symposium  2008.2 

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  • Visualization of Cluster Transition utilizing Self-Organizing Network

    2008 

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  • Extracting correlation of files for constructing time-based user interface in desktop search

    2007.12 

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  • Reliability Evaluation of SOFC under Simulated Operating Condition

    Kazuhisa Sato, Norihiro Imanaka, Ken-ichi Fukui, Masayuki Numao, Shintaro Kyotani, Keiji Yashiro, Tatsuya Kawada, Toshiyuki Hashida, Junichiro Mizusaki

    Proc. 10th International Symposium on Solid Oxide Fuel Cells (SOFC-X) (Electrochemical Society Transactions)  2007.6 

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  • Constructing the sensor topology map of infrared sensor network using ant colony optimization

    2007.3 

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  • Evaluation of Fracture Dynamics in SOFC by Burst Extraction Method and Sequence-based SOM

    Ken-ichi Fukui, Kazuhisa Saito, Junichiro Mizusaki, Kazumi Saito, Masayuki Numao

    Proc. 11th SANKEN International Symposium  2007.2 

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  • Evaluation of Sequential AE Signals in SOFC Utilizing SOM

    Norihiro Imanaka, Ken-ichi Fukui, Kazuhisa Sato, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

    Proceedings of the 5th 21st Century COE "Towards Creating New Industry Based on Inter-Nanoscience" International Symposium  2006.12 

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  • センサネットワークによる識別子を用いない人物別行動抽出 (第23回センシングフォーラム 資料--センシング技術の新たな展開と融合) -- (セッション1B3 ネットワークセンシングシステム)

    本田 誠一, 福井 健一, 森山 甲一

    センシングフォ-ラム資料  2006.10  〔計測自動制御学会〕

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  • Keyword Extraction using Link Analysis Based on CONCOR

    Nagayoshi Yamashita, Ken-ichi Fukui, Koichi Moriyama, Masayuki Numao, Satoshi Kurihara

    日本ソフトウェア科学会 ネットワークが創発する知能研究会 第2回ワークショップ(JWEIN2006) 講演論文集  2006.9 

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  • Web Documents Summarization using Link Analysis Based on CONCOR

    YAMASHITA Nagayoshi, FUKUI Kenichi, MORIYAMA Koichi, NUMAO Masayuki, KURIHARA Satoshi

    IPSJ SIG Notes. ICS  2006.7  Information Processing Society of Japan (IPSJ)

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    Event date: 2006.7

    Language:Japanese  

    In this paper, we propose a framework to extracting significant words in the Web using link structure. We use the global method in social network 'CONCOR' for link analysis. This is based on the assumption that if the link patterns of two sites and links are the same, then these two sites also contain the same in contents. In the first phase, the whole network consisting of sites are divided into clusters using CONCOR. Subsequently, by using the method we propose, we identify similarity sites. Comparing a site with other sites in the same cluster and with the similarity sites for the site, we assign higher weights to nouns that exist in two sites in common. By using link analysis to language processing, we could discover significant words.

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    Other Link: http://id.nii.ac.jp/1001/00050183/

  • Evaluation of Vector Representable Topics that were Extracted Automatically

    FUKUI Ken-ichi, SAITO Kazumi, KIMURA Masahiro, NUMAO Masayuki

    IPSJ SIG Notes  2006.5  Information Processing Society of Japan (IPSJ)

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    Event date: 2006.5

    Language:Japanese  

    Automatic topic extraction from a large number of documents is useful to figure out an entire picture of the documents or to classify the documents. Here, it is an important issue to evaluate the automatically extracted topics, however, even if manually-labeled documents are obtained, it is impossible to compare automatically and manually derived topics due to complexity and uncertainty of the topics' structure. As the objective is vector representable topic extractions such as Latent Semantic Analysis, in this paper we tried to evaluate the interpretability of automatically extracted topics using the manulally-labeled documents. We validated the proposed evaluation method using topics extracted from Japanese and English news articles.

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    Other Link: http://id.nii.ac.jp/1001/00033150/

  • A visualization method of sensor's relationship from chronological order of sensor data

    NAKAMURA Kazushi, FUKUI Kenichi, MORIYAMA Koichi, KURIHARA Satoshi, NUMAO Masayuki

    IPSJ SIG Notes. ICS  2005.8  Information Processing Society of Japan (IPSJ)

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    Event date: 2005.8

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    We propose the visualization method of sensor's relationship from chronological order of sensor data, without elaborate prior configuration or geometorical infomation of sensors. It is useful to build a frame of new interaction in ubiquitous environment. We extract a human custom action pattern to give it to sensor network environment and learn it, and ubiquitous environment offering appropriate services to is demanded. It seems that automatic configuration of a massively sensor network becomes need for ubiquitous environmental realization. In this paper, we describe a trial to extract relationship of the experimental sensor network and visualize it.

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    Other Link: http://id.nii.ac.jp/1001/00050228/

  • 時系列センサーデータからのセンサー隣接関係の可視化

    中村 和志, 福井 健一, 森山 甲一, 栗原 聡, 沼尾 正行

    電子情報通信学会技術研究報告  2005.8 

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  • SBSOM: Self-Organizing Map for visualizing structure in the time series of hot topics

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

    Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining  2004.12 

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  • Numerical Simulation of Pulsating Flow in Contraction Pipe

    Fukui, K, Kohge, K, Minemura, K

    Proc. 5th JSME-KSME Fluids Engineering Conference  2002.11 

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  • 時空間点過程データに対するグレンジャー因果性検定の局所密度推定による精度向上

    竹中敦史, 福井健一

    情報処理学会 第153回数理モデル化と問題解決研究会  2025.6 

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  • 快さと興奮状態を反映した音楽生成

    田邉 柊太, 福井 健一, 大谷 紀子, 沼尾 正行

    2025年度 人工知能学会全国大会(第39回)  2025.5 

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  • プレス成形シミュレーションを対象とした形状予測サロゲートモデル

    大岸 寛之, 西村 真治, 加茂 和史, 岡田 拓記, 福井 健一, 伊原 涼平

    2025年度 人工知能学会全国大会(第39回)  2025.5 

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  • Music Therapy for Dialysis Stress Relief and Machine Learning-Based Classification

    JIYUAN ZHANG, Ken-ichi Fukui, Tsukasa Kimura, Noriko Otani, Tetsuya Ohira, Masayuki Numao

    2025.5 

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  • Uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery

    Pongpisit Thanasutives, Ken-ichi Fukui

    The 28th SANKEN International Symposium  2025.1 

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  • Enhancing sound-based sleep quality assessment by multimodal knowledge distillation

    Lu Haoyu, Takafumi Kato, Ken-ichi Fukui

    The 28th SANKEN International Symposium  2025.1 

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  • Investigation of the Potential for Long-Lead-Time Nowcasting of Heavy Rainfall in Kyushu Using a Deep Learning Model with Wide-Area Satellite Observations

    Ryu Shimabukuro, Tomohiko Tomita, Tsuyoshi Yamaura, Kenichi Fukui

    The 2024 American Geophysical Union (AGU) Fall Meeting  2024.12 

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  • 教師なし機械学習アルゴリズムを用いた アリソフの全球気候区分図の更新

    島袋琉, 冨田智彦, 福井健一

    2023年度人工知能学会全国大会(第37回)  2023.6 

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  • 教師なし機械学習アルゴリズムを用いた アリソフの全球気候区分図の更新

    島袋琉, 冨田智彦, 福井健一

    日本地球惑星科学連合(JpGU)2023年大会  2023.5 

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  • Robust Data-driven PDE Discovery by Forward Best-subset Selection

    Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui

    2022.11 

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  • AIによる音響・振動データからの知識発見と予測 Invited

    福井健一

    生産技術振興協会 ハイテク推進セミナー  2022.11 

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  • 機械学習による異常検知の基礎と回転機器の欠陥検出への応用 Invited

    福井健一

    精密工学会超精密位置決め専門委員会講演会  2022.6 

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  • 機械学習のクラスタリング技術を用いたアリソフ気候区分の改訂

    島袋琉, 冨田智彦, 福井健一

    気象学会第43回九州支部発表会  2022.3 

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  • 機械学習による異常検知と回転機器の欠陥検出への応用 Invited

    福井健一

    情報処理学会中国支部主催講演会  2022.3 

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  • AIによる睡眠の視覚化と良否判別 Invited

    福井健一

    第30回日本睡眠環境学会学術大会 パネルディスカッション 次は何? 睡眠環境科学と近接領域と-未来へ繋ぐ-  2022.2 

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  • Soft Periodic Convolutional Recurrent Network for Spatiotemporal Climate Forecast and Periodicity Analysis

    Ekasit PHERMPHOONPHIPHAT, 冨田智彦, 森田尭, 沼尾正行, 福井健一

    人工知能学会合同研究会2021 第20回データ指向構成マイニングとシミュレーション研究会  2021.11 

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  • Adversarial Multi-task Learning Algorithm for Solving Partial Differential Equations

    Pongpisit Thanasutives, Masayuki Numao, Ken-ichi Fukui

    日本地球惑星科学連合2021年大会  2021.6 

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  • 変分敵対的ドメインニューラルネットワークによる個人差を考慮した睡眠評価

    石丸竣哉, 沼尾正行, 福井健一

    2021年度人工知能学会全国大会(第35回)  2021.6 

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  • 時系列観測によるRNNおよびLSTMモデルを使用した降水量予測と比較

    張賀, 冨田智彦, 福井健一, 小野智司

    日本地球惑星科学連合2021年大会  2021.6 

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  • 機械学習を用いたフィリピン・マニラ首都圏における降雨の直前予測

    野田明羅, 高橋幸弘, 久保田尚之, 福井健一, 佐藤光輝

    日本地球惑星科学連合2021年大会  2021.6 

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  • 海洋観測データの異常検知におけるデータ合成の有用性の基礎検討

    井手上陽祐, 福井健一, 細田滋毅, 小野智司

    計測自動制御学会第48回知能システムシンポジウム  2021.3 

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  • A Periodic Convolutional Recurrent Network Model for Climate Prediction

    Ekasit Phermphoonphiphat, Tomohiko Tomita, Masayuki Numao, Ken-ichi Fukui

    2020.6 

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  • 機械学習による睡眠状態解析 Invited

    福井健一

    高エネルギー密度科学のシミュレーションとデータビリティに関する研究会  2020.1 

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  • Spatio-temporal Change Detection Using Pattern Time Signature

    Nat Pavsant, 沼尾正行, 福井健一

    人工知能学会第118回知識ベースシステム研究会(SIG-KBS)  2019.11 

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  • 睡眠環境音に基づく睡眠個性の可視化と良否判別 Invited

    福井健一

    大阪大学新技術説明会  2019.2 

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  • 特徴選択と;段の外れ値検出手法による微小欠陥を含む転がり軸受の欠陥検出法

    北井正嗣, 赤松良信, 福井健一

    情報処理学会第120回数理モデル化と問題解決(MPS)研究会  2018.9 

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  • Pythonではじめる機械学習入門 Invited

    福井健一

    計測自動制御学会中国支部 計測自動制御シンポジウム2018  2018.9 

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  • 物理過程に基づくニューラルネットワーク構築の検討

    田中潤也, 冨田智彦, 沼尾正行, 福井健一

    電子情報通信学会人工知能と知識処理研究会  2018.8 

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  • Climate Forecasting by ConvLSTM on Segmented Region

    パームプーンピパット エカシット, 冨田智彦, 沼尾正行, 福井健一

    電子情報通信学会人工知能と知識処理研究会  2018.8 

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  • 特徴選択と2段の外れ値検出手法による転がり軸受の欠陥検出精度向上方法の提案

    北井正嗣, 赤松良信, 福井健一

    計測自動制御学会第45回知能システムシンポジウム  2018.3 

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  • 物理法則に基づくニューラルネットワーク構築の検討 ー対流圏上層の風予測を例にー

    田中潤也, 冨田智彦, 沼尾正行, 福井健一

    情報処理学会第117回数理モデル化と問題解決研究発表会(MPS研究会)  2018.3 

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  • Sleep Pattern Visualization via Clustering on Sound Data

    Wu Hongle, 加藤隆史, 山田朋美, 沼尾正行, 福井健一

    第31回人工知能学会全国大会  2017.5 

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  • 空間的自己相関を考慮した海洋データのエラー検知

    林勝悟, 小野智司, 細田滋毅, 沼尾正行, 福井健一

    第31回人工知能学会全国大会  2017.5 

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  • Introduction to Machine Learning Invited

    Ken-ichi Fukui

    RIME Joint Research Workshop  2017.3 

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  • Knowledge Discovery from Sequence of Event Data Invited

    Ken-ichi Fukui

    RIEC Annual Meeting on Collaborative Research Projects  2017.2 

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  • 近傍法による海洋深度系列データのエラー検知

    林勝悟, 小野智司, 細田滋毅, 沼尾正行, 福井健一

    第26回インテリジェント・システム・シンポジウム(FAN2016)  2016.10 

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  • 機械学習を用いた海洋観測データの良否識別の試み

    上川路洋介, 松山開, 福井健一, 細田滋毅, 小野智司

    日本海洋学会 2016年度秋季大会  2016.9 

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  • クラスタリングによる海洋データの構造視覚化

    林勝悟, 細田滋毅, 小野智司, 沼尾正行, 福井健一

    情報処理学会 第108回数理モデル化と問題解決(MPS)研究会  2016.7 

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  • 海洋観測データの良否識別を目的とした条件付確率場における素性関数の自動設計の試み

    上川路洋介, 松山開, 福井健一, 細田滋毅, 小野智司

    第30回人工知能学会全国大会  2016.6 

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  • Sleep Pattern Discovery and Visualization based on Clustering of Sound Events

    Wu Hongle, 加藤隆史, 山田朋美, 沼尾正行, 福井健一

    第30回人工知能学会全国大会  2016.6 

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  • Sleep Pattern Characterization via Cluster Analysis of Audio Data

    Hongle Wu, Ken-ichi Fukui, Takafumi Kato, Masayuki Numao

    人工知能学会 第106回 知識ベースシステム研究会(SIG-KBS)  2015.11 

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  • Semi-supervised Evolutionary Distance Metric Learning for Clustering

    Kalintha Wasin, 福井健一, 小野智司, 女鹿野大志, 森山甲一, 沼尾正行

    第29回人工知能学会全国大会  2015.5 

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  • 多次元数値観測量の事象系列に対するクラスタ系列パターンの抽出

    岡田佳之, 福井健一, 沼尾正行

    第29回人工知能学会全国大会  2015.5 

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  • 系列ラベリング手法による海洋観測データの良否識別

    松山開, 田中舜也, 西元千恵, 小野智司, 福井健一, 細田滋毅

    第29回人工知能学会全国大会  2015.5 

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  • 教師なし学習における非データ分布依存型コンセプトドリフト検出手法の検証

    坂本悠輔, 福井健一, Gama Joao, Nicklas Daniela, 森山甲一, 沼尾正行

    情報処理学会第102回数理モデル化と問題解決研究発表会  2015.3 

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  • マルチラベルクラスタリングを対象とした進化型多目的距離計量学習

    女鹿野大志, 福井健一, 沼尾正行, 小野智司

    第42回SICE 知能システムシンポジウム  2015.3 

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  • 機械学習によるアルゴデータの良否識別

    松山開, 小野智司, 福井健一, 細田 滋毅

    日本海洋学会春季大会  2015.3 

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  • 進化的距離計量学習への多目的最適化アルゴリズムの適用

    女鹿野大志, 福井健一, 小野智司

    電気・情報関係学会九州支部第67回連合大会  2014.9 

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  • 条件付確率場を用いた海洋観測データの良否分類

    松山開, 小野智司, 福井健一, 細田滋毅

    電気・情報関係学会九州支部第67回連合大会  2014.9 

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  • 適応型モニタリングシステムにおけるコンセプトドリフト検出に向けた初期実験

    坂本悠輔, 福井健一, Daniela Nicklas, 森山甲一, 沼尾正行

    人工知能学会 第102回知識ベースシステム研究会(SIG-KBS)  2014.7 

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  • 順序や生起間隔を考慮したクラスタ系列パターン抽出法の提案

    岡田佳之, 福井 健一, 沼尾 正行

    第98回情報処理学会数理モデル化と問題解決研究会  2014.6 

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  • 機械学習による海洋観測データの良否分類に向けた初期検討

    松山開, 小野智司, 福井健一, 細田滋毅

    第28回人工知能学会全国大会  2014.5 

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  • 持続可能なコンセプトドリフト適応型モニタリングシステムの提案

    坂本悠輔, 福井健一, Nicklas Daniela, 森山甲一, 沼尾正行

    第28回人工知能学会全国大会  2014.5 

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  • 共起クラスタマイニングによる東日本大震災の地震活動の相互作用の抽出

    岡田佳之, 稲場大樹, 福井 健一, 沼尾 正行

    第28回人工知能学会全国大会  2014.5 

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  • 進化的距離学習を用いた顔画像クラスタリング

    女鹿野大志, 小野智司, 福井健一, 二宮公紀, 沼尾正行, 中山茂

    電子情報通信学会 技術研究報告 パターン認識・メディア理解  2014.1 

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  • 大域的クラスタ妥当性指標に基づく距離学習における適応度景観の可視化

    女鹿野大志, 福井健一, 小野智司, 沼尾正行, 中山茂

    情報処理学会 第95回数理モデル化と問題解決研究会  2013.9 

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  • 共起クラスタマイニングによる地震発生パターン抽出

    福井健一, 稲場大樹, 沼尾正行

    第27回人工知能学会全国大会  2013.6 

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  • 東日本大震災における地震発生パターンの共起分析

    稲場大樹, 福井健一, 沼尾正行

    日本地球惑星科学連合2013年度連合大会  2013.5 

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  • 半教師有りクラスタリングのための進化型距離学習

    福井健一, 小野智司, 沼尾正行

    計測自動制御学会第40回知能システムシンポジウム  2013.3 

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  • 大域的クラスタ指標に基づく距離学習への適応型差分進化法の適用

    小野智司, 福井健一, 堤田沙由里, 澤井陽輔, 中山茂, 沼尾正行

    第4回進化計算学会研究会  2013.3 

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  • 共起クラスタマイニング ー数値観測量の事象系列に対する頻出パターン抽出ー

    稲場大樹, 福井健一, 沼尾正行

    第75回情報処理学会全国大会  2013.3 

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  • Data Mining for Revealing Damage Phenomena in a Fuel Cell Invited

    Ken-ichi Fukui

    The 16th SANKEN International Symposium  2013.1 

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  • 共起クラスタマイニングを用いた東日本大震災における地震発生パターンの抽出

    稲場大樹, 福井健一, 沼尾正行

    工知能学会 第3回データ指向構成マイニングとシミュレーション研究会(SIG-DOCMAS)  2012.11 

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  • 大域的クラスタ妥当性指標に基づく差分進化による距離学習

    福井健一, 小野智司, 沼尾正行

    人工知能学会 第3回データ指向構成マイニングとシミュレーション研究会(SIG-DOCMAS)  2012.11 

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  • 固体型電池の信頼性向上のための情報処理技術の活用

    佐藤 一永, 福井 健一, 沼尾 正行, 桑田 直明, 河村 純一, 橋田 俊之

    日本機械学会2012年度年次大会  2012.9 

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  • Revealing Damage Mechanism of a Fuel Cell: Data Mining for a Physical Phenomenon Invited

    Ken-ichi Fukui

    Workshop on Computation: Theory and Practice (WCTP-2012)  2012.9 

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  • 共起クラスタマイニングによる燃料電池の損傷パターン分析

    稲場大樹, 福井健一, 佐藤一永, 水崎純一郎, 沼尾正行

    第26回人工知能学会全国大会  2012.6 

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  • 固体エネルギー変換デバイス信頼性向上のための情報処理技術の必要性 Invited

    佐藤 一永, 橋田 俊之, 福井 健一, 高藤 淳, 沼尾 正行

    第26回人工知能学会全国大会(OS招待講演)  2012.6 

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  • 相関ルールに基づく近傍サーバログ分析

    北川哲平, 福井健一, 鈴木聖人, 冨士井裕之, 山口慶大, 沼尾正行

    第26回人工知能学会全国大会  2012.6 

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  • 大域的クラスタ妥当性指標に基づく距離学習

    福井健一, 沼尾正行

    情報処理学会 第87回数理モデル化と問題解決研究会  2012.3 

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  • 事象間の共起関係を考慮したクラスタリングによる燃料電池の損傷パターン抽出

    稲場大樹, 福井健一, 佐藤一永, 水崎純一郎, 沼尾正行

    第14回 情報論的学習理論ワークショップ (IBIS2011)  2011.11 

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  • 実数値空間上の頻出パターン最大化によるパターン抽出法

    稲場大樹, 福井健一, 佐藤一永, 水崎純一郎, 沼尾正行

    第25回人工知能学会全国大会  2011.6 

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  • Kernel SOMによる燃料電池の視覚的損傷評価

    福井健一, 北川哲平, 佐藤一永, 水崎純一郎, 沼尾正行

    第25回人工知能学会全国大会  2011.6 

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  • キーグラフとSOMを用いた稀な重要事象の抽出-燃料電池の損傷評価を例に-

    北川哲平, 福井健一, 佐藤一永, 水崎純一郎, 沼尾正行

    情報処理学会 第80回数理モデル化と問題解決研究会  2010.9 

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  • キーグラフとSOMを用いた燃料電池の損傷共起分析

    北川哲平, 福井健一, 佐藤一永, 水崎純一郎, 森山甲一, 栗原聡, 沼尾正行

    第24回人工知能学会全国大会  2010.6 

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  • 位相を導入したSOMの性能評価尺度

    福井健一, 沼尾正行

    第11回自己組織化マップ研究会  2010.3 

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  • 燃料電池における損傷パターン抽出

    赤崎省悟, 福井健一, 佐藤一永, 水崎純一郎, 栗原聡, 沼尾正行

    情報処理学会 第77回数理モデル化と問題解決研究会  2010.3 

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  • 固体酸化物燃料電池の損傷評価支援のための視覚的データマイニング

    福井健一, 赤崎省悟, 佐藤一永, 水崎純一郎, 沼尾正行

    電子情報通信学会 人工知能と知識処理研究会  2010.1 

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  • カーネルSOMによる損傷評価のための隣接性を考慮した分類性能評価

    福井健一, 赤崎省悟, 佐藤一永, 水崎純一郎, 森山甲一, 栗原聡, 沼尾正行

    情報処理学会 第75回数理モデル化と問題解決研究会研究報告  2009.9 

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  • 楽曲の部分構造と全体構造を考慮した自動作曲システム

    西川敬之, 大谷紀子, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第23回)論文集  2009.6 

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  • データマイニング技術とAE法によるSOFCの機械特性評価法 Invited

    福井健一

    第51回固体イオニクス研究会  2009.3 

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  • データマイニング技術による固体型電池の機械特性評価法 Invited

    福井健一

    東北大学多元物質科学研究所 先進融合研究若手講演会  2009.3 

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  • Positing A Growth-Centric Learning of Empathy Models in HSI

    レガスピ ロベルト, 福井 健一, 森山 甲一, 栗原 聡, 沼尾 正行

    人工知能学会全国大会(第22回)論文集  2008.6 

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  • カーネルSOMを用いた波形信号のスペクトル形状を考慮したクラスタリングと可視化

    赤崎省悟, 福井健一, 佐藤一永, 水崎純一郎, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第22回)論文集  2008.6 

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  • クラスタのダイナミクスを可視化するSequence-based SOMに関する一考察

    福井健一, 斉藤和巳, 木村昌弘, 沼尾正行

    人工知能学会 第4回データマイニングと統計数理研究会  2007.7 

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  • An Architectural Framework for an Ambient Empathic Support

    玉置洋, 福井健一, 沼尾正行, 栗原聡

    人工知能学会 第79回知識ベースシステム研究会資料 (SIG-KBS-A702)  2007 

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  • フェロモンコミュニケーションモデルに基づくセンサー隣接関係の自動取得

    玉置洋, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第21回)論文集 CD-ROM  2007 

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  • 脳波の解析に基づく個人感性獲得による自動作曲

    杉本知仁, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第21回)論文集 CD-ROM  2007 

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  • Multiple-part学習による個人感性獲得機構

    西川敬之, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第21回)論文集 CD-ROM  2007 

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  • 赤外線センサーネットワークによる人物追跡

    本田誠一, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第20回)論文集  2006 

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  • 楽曲構造における個人感性獲得機構

    橋本雄弥, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第20回)論文集  2006 

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  • 自己組織化マッピング手法を用いたSOFCの損傷可視化に関する研究

    佐藤一永, 今中規景, 福井健一, 八代圭司, 沼尾正行, 川田達也, 湯上浩雄, 橋田俊之, 水崎純一郎

    電気化学会 第15回SOFC研究発表会  2006 

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  • センサネットワークによる識別子を用いない人物別行動抽出

    本田誠一, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    計測自動制御学会 第23回センシングフォーラム計測部門大会予稿集  2006 

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  • 動体検知情報の階層的クラスタリングによる人物行動解析

    安場直史, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第20回)論文集  2006 

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  • U-MartにおけるQ学習エージェントの設計と評価

    松本光弘, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    人工知能学会全国大会(第20回)論文集  2006 

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  • ブロックモデルによるリンク解析を用いたWeb文書からの重要語抽出

    山下長義, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    情報処理学会 第144回知能と複雑系研究会研究報告  2006 

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  • CONCORによるリンク解析を反映したWeb文書の要約

    山下長義, 福井健一, 森山甲一, 栗原聡, 沼尾正行

    第5回情報科学技術フォーラム (FIT2006) 講演論文集  2006 

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  • 自己組織化マップによる教師情報を用いた可視化アーキテクチャの提案-時系列医療データの可視化を例に

    福井健一, 沼尾正行, 斉藤和巳, 木村昌弘

    情報処理学会知能と複雑系研究会・電子情報通信学会人工知能と知識処理研究会共催  2005.8 

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  • 時系列を考慮した自己組織化マップによるホットトピックの可視化

    福井健一, 斉藤和巳, 木村昌弘, 沼尾正行

    関西機械学習統計研究会  2005.3 

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Industrial property rights

  • 劣化状況予測システム、および劣化状況予測方法

    福井 健一, 北井 正嗣

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    Application no:特願2022-44489 

    Announcement no:特開2023-138012  Date announced:2023.9

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  • 余寿命予測システム、余寿命予測装置、および余寿命予測プログラム

    福井 健一, 北井 正嗣

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    Application no:特願2019180234 

    Patent/Registration no:特許第7290221号  Date registered:2023.6 

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  • 教師情報付学習データ生成方法、機械学習方法、教師情報付学習データ生成システム及びプログラム

    小野 智司, 前原 宗太朗, 福井 健一, 冨田 智彦

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    Application no:特願2017162548 

    Patent/Registration no:特許第6989841号  Date registered:2021.12 

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  • 欠陥検出システム、欠陥モデル作成プログラム、および欠陥検出プログラム

    福井 健一, 北井 正嗣

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    Application no:特願2018-036642 

    Patent/Registration no:特許第06950891号  Date registered:2021.9 

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  • 余寿命予測システム、余寿命予測装置、および余寿命予測プログラム

    福井 健一, 北井 正嗣

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    Application no:特願2019-180226 

    Patent/Registration no:特許第7430317号  Date registered:2024.2 

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Awards

  • 大阪大学賞(教育貢献部門)

    2022.11   大阪大学  

    福井健一

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  • 第34回全国大会優秀賞(国際セッション口頭発表部門)

    2020.7   人工知能学会  

    Nat Pavasant, Masayuki Numao, Ken-ichi Fukui

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  • Outstanding Reviewer

    2018.3   Elsevier, Knowledge-Based Systems  

    福井 健一

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  • 2016年度研究会優秀賞

    2017.4   人工知能学会  

    Wasin Kalinta, Satoshi Ono, Masayuki Numao, Ken-ichi Fukui

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  • FAN最優秀論文賞

    2016.10   第26回インテリジェント・システム・シンポジウム  

    林勝悟, 小野智司, 細田滋毅, 沼尾正行, 福井健一

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  • 大阪大学総長による表彰

    2013.10   大阪大学  

    福井 健一

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  • 大阪大学総長奨励賞研究部門

    2013.8   大阪大学  

    福井 健一

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  • 2012年度研究会優秀賞

    2013.4   人工知能学会  

    稲場大樹, 福井健一, 沼尾正行

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  • 第25回全国大会優秀賞(口頭発表部門)

    2011.7   人工知能学会  

    福井 健一

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  • IEEE Computer & Information Technology (CIT 2008), Best Paper Award

    2008.7  

    Ken-ichi Fukui, Kazumi Saito, Masahiro Kimura, Masayuki Numao

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  • The 26th SANKEN International Symposium, Poster Presentation Award

    2023.1  

    Shintaro Tamai, Yue Chen, Takashi Morita, Tsukasa Kimura, Masayuki Numao, Ken-ichi Fukui

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  • 人工知能と知識処理研究会研究奨励賞

    2018.8   電子情報通信学会  

    田中潤也, 冨田智彦, 沼尾正行, 福井健一

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  • 東北支部春季大会 ポスターセッション銅賞

    2018.5   資源・素材学会  

    薮田佳絵, 熊田圭悟, 佐藤一永, 橋田俊之, 碇智文, 福井健一, 沼尾 正行

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  • Best Workshop Paper Award

    2016.8   The Workshops at The 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2016)  

    Nattapong Thammasan, Ken-ichi Fukui, Masayuki Numao

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  • The 8th International Conference on Agents and Artificial Intelligence (ICAART2016), Best Student Paper Award

    2016.2  

    Wataru Fujita, Koichi Moriyama, Ken-ichi Fukui, and Masayuki Numao

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  • 2012年度年次大会 講演優秀賞

    2012.9   日本機械学会  

    佐藤 一永, 福井 健一, 沼尾 正行, 桑田 直明, 河村 純一, 橋田 俊之

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  • 第26回全国大会 大会優秀賞(口頭発表部門)

    2012.7   人工知能学会  

    稲場大樹, 福井健一, 佐藤一永, 水崎純一郎, 沼尾正行

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  • 第23回センシングフォーラム 研究・技術奨励賞

    2006.10   計測自動制御学会  

    本田誠一, 福井健一, 森山甲一, 栗原聡, 沼尾正行

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Research Projects

  • 気象防災のAI活用:大規模基盤モデルのタスク適応性を深化させる

    Grant number:25H00784  2025.4 - 2029.3

    日本学術振興会  科学研究費助成事業  基盤研究(A)

    関山 剛, 川畑 拓矢, 幾田 泰酵, 山口 宗彦, 福井 健一

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    Grant amount:\60320000 ( Direct Cost: \46400000 、 Indirect Cost:\13920000 )

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  • 複数の要因を考慮した深層学習による日常の睡眠の質推定と要因分析

    Grant number:22K19832  2022.6 - 2024.3

    日本学術振興会  科学研究費助成事業  挑戦的研究(萌芽)

    福井 健一, 加藤 隆史

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    Authorship:Principal investigator 

    Grant amount:\6370000 ( Direct Cost: \4900000 、 Indirect Cost:\1470000 )

    本研究は,非接触かつ簡便な計測が可能な「睡眠中の音響」を基に,個人差や環境差など,睡眠に影響を及ぼす複数の要因を同時に考慮して日常の「睡眠の質」を推定する深層学習モデルを開発することを目的としている.現状のウェアラブルデバイスでは日常の睡眠の質を適切に評価できていない.睡眠音には睡眠を特徴付ける様々な生体活動(いびき,歯ぎしり,体動等)や周囲の環境音など多様な情報が含まれるため,従来のウェアラブルデバイスでは困難であった総合的な睡眠評価が可能になる.さらに身体・環境などの要因分析ができれば,睡眠の評価に留まらず改善案の提示や,快適な睡眠環境の制御との連携につながる.
    本年度は,1.これまで収集してきた自宅環境における睡眠データの拡充,2.音特徴の個人差・環境差の低減法の論文化,3.身体・環境要因を加味したマルチモーダル深層学習モデルに関して研究を行った.1.自宅環境の睡眠実験について,本年度は新たに13名(30代,40代)の被験者実験を行った.2.これまで研究を行ってきたドメイン適応を用いた音特徴の個人差・環境差の低減法に関して,ハイパーパラメータの影響に関する追加実験を行い,現在,国際ジャーナルに投稿中である.3.因子選択機能を持つマルチモーダル深層学習モデルを2種類考案した.100名以上(20代から60代)・各1ヶ月間の自宅環境における睡眠データを用いた検証実験から,音による睡眠パターンの重要性に加えて,身体・環境特徴により睡眠の良否判別精度の向上の確認と共に,年代毎に特徴的な要因があることが確認された.

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  • Meteorological downscaling and atmospheric environment prediction using deep learning

    Grant number:21H03593  2021.4 - 2026.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

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    Authorship:Coinvestigator(s) 

    Grant amount:\17030000 ( Direct Cost: \13100000 、 Indirect Cost:\3930000 )

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  • Development of neural networks based on physical models and exploration of meteorological physics

    Grant number:19K22876  2019.6 - 2021.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Challenging Research (Exploratory)

    Fukui Ken-ichi

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    Authorship:Principal investigator 

    Grant amount:\6370000 ( Direct Cost: \4900000 、 Indirect Cost:\1470000 )

    In this work, we tackled the following two researches. Frist, we proposed a deep learning architecture that can decompose and output known physical model component and model residual component. Then, we verified the accuracy of the proposed method with the task of estimating the wind velocity in the upper troposphere from the atmospheric conditions in the lower layer. The validity of the wind vector distribution of the residual component by the proposed method was justified from the knowledge of meteorology. Second, we proposed an improvement method by multi-task learning and adversarial exsample generation for the method of obtaining the value of the solution at an arbitrary position of the partial differential equation, by automatic differentiation and deep learning. We confirmed the improvement of estimation accuracy for some basic PDEs.

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  • Causality Mining from Event Sequence Data and Its Applications to Causality Discovery in Earthquakes and Damages

    Grant number:15K16052  2015.4 - 2018.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Young Scientists (B)

    Fukui Ken-ichi

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    Authorship:Principal investigator 

    Grant amount:\3900000 ( Direct Cost: \3000000 、 Indirect Cost:\900000 )

    In this research, we proposed a new data mining algorithm, called Cluster Sequence Mining (CSM), which extracts occurrence correlation between events from multidimensional event series data. Furthermore, we extended the correspondence relation when calculating the time interval between events to one-to-many or many-to-one, by formulating as a minimum cost elastic matching problem, and devised a method to uniquely obtain corresponding event pairs. This aimed at improving the accuracy of Bayesian estimation. As a result of the evaluation experiment using artificial data, accuracy improvement was confirmed in the proposed method, especially when the event densely exists on the time axis as compared with the conventional method. Furthermore, we showed examples of applying this method to damage correlation analysis of fuel cells and occurring correlation analysis between earthquakes.

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  • 半教師あり進化型距離学習に関する基礎および応用研究

    2014.1 - 2014.12

    栢森情報科学振興財団  研究助成(一般研究) 

    福井健一,小野智司

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  • Establishment of Co-occurring Cluster Mining and Its Environmental Contribution

    Grant number:24650068  2012.4 - 2015.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Challenging Exploratory Research

    KEN-ICHI Fukui

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    Authorship:Principal investigator 

    Grant amount:\3900000 ( Direct Cost: \3000000 、 Indirect Cost:\900000 )

    In this research, as an objective is to infer interaction between events, we developed a novel mining algorithm that extracts pairs of clusters in which events co-occur, from a observed event sequence data. Firstly, by using simulated data, we validated that the proposed method can extract co-occurring clusters more accurately compared with a two-step method. Next, we applied the proposed method to damage analysis on a fuel cell, and confirmed that our method can extract valid mechanical interactions among members of the fuel cell from Acoustic Emission event sequence. Lastly, we also applied the method to analysis of Earthquake occurrences after the 2011 Tohoku Earthquake, and the results suggested interactions among asperities.

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  • 睡眠に影響を与える環境因子の寄与度の調査

    2022.7 - 2023.6

    ダイキン工業株式会社  共同研究 

    福井健一

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  • 降水の時空間変動予測への機械学習技術の適用

    Grant number:20221322  2022.5 - 2023.3

    物質・デバイス領域共同研究拠点  物質・デバイス領域共同研究課題  基盤共同研究

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    Grant type:Competitive

    Grant amount:\130000 ( Direct Cost: \130000 )

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  • Meteorological downscaling and atmospheric environment prediction using deep learning

    Grant number:23K21747  2021.4 - 2026.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

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    Grant amount:\17030000 ( Direct Cost: \13100000 、 Indirect Cost:\3930000 )

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  • 物流自動化技術の研究

    2020.4 - 2022.3

    株式会社ダイフク  共同研究 

    福井健一

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  • AI を用いた転がり軸受の余寿命予測

    2017.9 - 2022.3

    NTN株式会社  共同研究 

    福井健一

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  • Representative Learning for Structured Data and Its Application to Two Real World Problems with Different Characteristics

    Grant number:16K12490  2016.4 - 2019.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Challenging Exploratory Research

    Ono Satoshi

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    Grant amount:\3380000 ( Direct Cost: \2600000 、 Indirect Cost:\780000 )

    This study proposed representative learning methods using deep neural networks such as convolutional neural network and recurrent neural network and other machine learning techniques for structured data, e.g., change detection of slight patterns on one dimensional sequential data. In addition, this study focused two real world problems: quality control of ocean observation data as one-dimensional sequential data and decoding distorted two-dimensional data as two-dimensional sequential data and confirmed that incorporating the proposed methods into conventional method such as conditional random field and Markov random field achieved the performance of practical level in these problems.

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  • Development of An Intelligent Decision Support System for Renewable Energy Mix Optimization

    Grant number:16K00651  2016.4 - 2019.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

    Matsui Takanori, FUKUI Ken'ichi, HASUIKE Takashi

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    Authorship:Collaborating Investigator(s) (not designated on Grant-in-Aid) 

    Grant amount:\4680000 ( Direct Cost: \3600000 、 Indirect Cost:\1080000 )

    With the strong demand for transition to the carbon circulating society in the global society, a dramatic transition to an energy system based on renewable energy is required. It is necessary to identify the nexus structure that the introduction of renewable energy shapes and design appropriate technologies and institutional designs based on backcasting approach with multiple viewpoints such as supply stability and feasibility, economic contribution to locals, diverse stakeholders participation, harmony with regional natural ecosystems
    From this background, in this study, we attempted to develop a decision support system for introducing a renewable energy mix that can assess the future image of the community and the achievement of sustainable development.

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  • Development of visualization technologies for battery security society

    Grant number:15K12467  2015.4 - 2017.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Challenging Exploratory Research

    Hashida Toshiyuki, SATO Kazuhisa, SUZUKI Ken, FUKUI Ken-ichi

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    Grant amount:\3770000 ( Direct Cost: \2900000 、 Indirect Cost:\870000 )

    This study presents technologies of visualizing the mechanical damage in Li ion secondary cells and solid oxide fuel cells (SOFCs) using acoustic emission (AE) method and laser microscope technique. For Li ion secondary cells, we have developed an AE/laser microscope technique for monitoring the dimensional change in Si-electrodes due to Li ion migration and the associated delamination of the Si-electrode from the substrate. Three stages in the Li ion migration process has been newly discovered in this study. We have also succeeded to detect the mechanical damages such as vertical cracking and delamination induced by the electro-chemical oxidation in the operation of SOFCs, and proposed a self-organization map of the mechanical damages on the basis of the AE monitoring. The above- mentioned technologies are expected to provide a viable foundation for the development of battery security society.

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  • 次世代エネルギーデバイスに対する人工知能技術に基づく損傷評価法

    2012.11 - 2013.10

    国立研究開発法人科学技術振興機構(JST)  研究成果展開事業 研究成果最適展開支援プログラムA-STEP  フィージビリティスタディステージ 探索タイプ

    福井健一

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  • Construction of Empathic Computation Mechanism

    Grant number:23300059  2011.4 - 2014.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

    NUMAO Masayuki, KURIHARA Satoshi, MORIYAMA Koichi, FUKUI Ken-ichi, LEGASPI Roberto

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    Authorship:Collaborating Investigator(s) (not designated on Grant-in-Aid) 

    Grant amount:\19760000 ( Direct Cost: \15200000 、 Indirect Cost:\4560000 )

    We have developed an algorithm for feeling analysis and conducted experiments. As well as brain waves, we employed some sensors to accomplish higher accuracy. For a horror game, heart rate is quite useful. Although we have been using six adjective pairs for evaluation based on questionnaires, we have introduced valence and arousal to evaluate emotion based on sensors.
    We use a genetic algorithm for composition, whose chromosome representation, operators and fitness function are important. By using symbiotic evolution, we have introduced motif structure to melody, and have investigated its effect, by which we have approached more sophisticated composition.

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  • データマイニング技術による固体酸化物燃料電池の機械的特性評価に関する研究

    2009.4 - 2010.3

    関西エネルギー・リサイクル科学研究振興財団  若手奨励研究

    福井健一

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    Authorship:Principal investigator 

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  • Multi-Perspective Data Mining for Evaluation of Mechanical Property of Solid-Type Battery

    Grant number:21700165  2009 - 2011

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Young Scientists (B)

    FUKUI Kenichi, NUMAO Masayuki, SATO Kazuhisa, MIZUSAKI Junichiro

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    Authorship:Principal investigator 

    Grant amount:\2600000 ( Direct Cost: \2000000 、 Indirect Cost:\600000 )

    This research developed a data analysis foundation of damage events for revealing mechanical property and monitoring Solid Oxide Fuel Cells(SOFC). By utilizing various data mining techniques, this work focused especially the following three points :(1) Automatic classification of damage events and visualization of damage process,(2) Detection of change points of damage process, and(3) Extraction of mechanical relations among members.

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Teaching Experience

  • AI基礎

    2025.9 - Present Institution:関西大学ビジネスデータサイエンス学部

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  • Knowledge Informatics

    2016 - 2024 Institution:Osaka University, Graduate School of Information Science and Technology

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  • ビジネスアクティブラーニング1

    2025.9 - Present Institution:関西大学ビジネスデータサイエンス学部

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  • Basic Practices

    2025 - Present Institution:Kansai University

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  • A Door to Academia

    2020 Institution:Osaka University

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  • Advanced Introduction to Information Physical Science

    2015 - 2024 Institution:Osaka University, Graduate School of Information Science and Technology, Department of Information and Physical Sciences

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  • Fundamentals of Information Science

    2014 Institution:School of Engineering, Osaka University, Department of Applied Science

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  • Exercises in Information Physics and Sciences I

    2011 - 2014 Institution:School of Engineering, Osaka University, Department of Applied Science

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Social Activities

  • 第69回日本学生科学賞中央審査委員

    読売新聞社  2025.5 - Present

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    Type:Other

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  • 有識者として助言

    Role(s): Advisor

    国土交通省  下水道革新的技術実証事業(B-DASHプロジェクト)  2020.9 - 2022.3

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    Type:Other

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  • 知識情報学

    Role(s): Lecturer

    一般社団法人データビリティコンソーシアム  実データで学ぶ人工知能講座  2019 - Present

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    Type:Visiting lecture

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  • 知識情報学

    Role(s): Lecturer

    NEDO  特別講座「実データで学ぶ人工知能講座」  2017.10 - 2020.3

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    Type:Visiting lecture

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  • 知識情報学

    Role(s): Lecturer

    ダイキン工業  AI人材育成講座  2017.7 - 2023.6

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    Type:Visiting lecture

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  • 機械学習基礎

    Role(s): Lecturer

    パナソニック  AI人材育成講座  2016.6 - 2018.9

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    Type:Research consultation

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  • 学術相談

    Role(s): Advisor

    ファナック株式会社  2023.10 - 2025.3

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    Type:Research consultation

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  • The Key Points on Machine Learning Systems

    Role(s): Lecturer

    一般財団法人海外産業人材育成協会(AOTS)  アフリカ向けオンライン研修  2023.2

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    Type:Visiting lecture

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  • 技術顧問

    Role(s): Advisor

    株式会社GeekGuild  2022.10 - 2024.3

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    Type:Research consultation

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  • 機械学習による音響に基づく日常の睡眠評価

    Role(s): Lecturer

    パナソニックDAY2.0 ライフサイエンス・セミナー  2022.8

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    Type:Seminar, workshop

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  • AIは何ができるのかー睡眠分析と気象予測への応用ー

    Role(s): Lecturer

    大阪府高齢者大学校  2022 - Present

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    Type:Visiting lecture

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  • 機械学習による睡眠個性の可視化と良否判別

    Role(s): Lecturer

    キャンパスクリエイト  第3回オンラインセミナー 産学連携オープンイノベーション 〜睡眠、ストレスフリー、QOL〜  2020.6

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    Type:Seminar, workshop

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  • 実例で学ぶ機械学習〜AIによる睡眠状態解析/機器の異常検知〜

    Role(s): Lecturer

    HiBiS  IT勉強会 ディープラーニングラボ広島  2020.6

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    Type:Seminar, workshop

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  • Pythonによる機械学習入門

    Role(s): Lecturer

    ISSM戦略フォーラム  2019.12

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    Type:Lecture

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  • 学術相談

    Role(s): Advisor

    ミツミ電機株式会社  2018.9 - 2019.3

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    Type:Research consultation

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  • 学術相談

    Role(s): Advisor

    パナソニック株式会社  2018.8 - 2020.3

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    Type:Research consultation

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  • グリーンAI~人工知能による環境貢献~

    Role(s): Lecturer

    社団法人産業環境管理協会、日本経済新聞社  エコプロ2017  2017.12

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    Type:Seminar, workshop

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Media Coverage

  • NTNと阪大、転がり軸受の余寿命をAIで高精度に予測 Internet

    日経BP  日経クロステック  2023.8

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    Author:Other 

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  • 睡眠環境音に基づく睡眠個性の可視化と良否判別 Internet

    フジサンケイビジネスアイ  2019.8

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    Author:Myself 

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  • 音からの睡眠の質を推定 TV or radio program

    テレビ大阪  ニュースリアル  2017.12

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    Author:Other 

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  • AI、音で睡眠の特徴分析 Newspaper, magazine

    日経産業新聞  2017.4

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  • 人工知能で睡眠の質を把握 TV or radio program

    NHK  関西ニュース  2017.3

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  • 阪大、スマートフォンやタブレット端末で録音された音から睡眠個性を視覚化するAI技術を開発 Internet

    日本経済新聞電子版  2017.3

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    Author:Other 

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  • 睡眠の質、AIで寝室の音から解析 阪大がソフト開発 Newspaper, magazine

    日本経済新聞  2016.10

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    Author:Other 

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  • AI技術者 講座で育成 パナソニックと阪大 Newspaper, magazine

    日経産業新聞  2016.6

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    Author:Other 

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Academic Activities

  • 文部科学省 気候変動予測先端研究プログラム 協力者

    2025.1 - Present

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    Type:Scientific advice/Review 

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  • IJCAI-2022, IJCAI-2023, IJCAI-2024, IJCAI-2025, Program Committee Member

    Role(s): Peer review

    The International Joint Conference on Artificial Intelligence 

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    Type:Peer review 

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  • AAAI-2024, AAAI-2025, AAAI-2026, Program Committee Member

    Role(s): Peer review

    The Annual AAAI Conference on Artificial Intelligence 

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    Type:Peer review 

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  • PAKDD2020, PAKDD2021, PAKDD2022, PAKDD2024, PAKDD2025, Program Committee Member

    Role(s): Peer review

    Pacific-Asia Conference on Knowledge Discovery and Data Mining 

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    Type:Peer review 

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  • IJCAI 2020, IJCAI 2021, Senior Program Committee Member

    Role(s): Review, evaluation, Peer review

    The International Joint Conference on Artificial Intelligence 

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    Type:Peer review 

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  • ECAI2020, ECAI2025, Program Committee Member

    Role(s): Peer review

    European Conference on Artificial Intelligence 

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    Type:Peer review 

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  • SCAI2021, SCAI2022, SCAI2022-Winter, SCAI2023, SCAI2023-Winter, SCAI2024, SCAI2024-Winter, Program Committee Member

    Role(s): Peer review

    International Conference on Smart Computing and Artificial Intelligence 

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    Type:Peer review 

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  • CANDAR2018,CANDAR2019,CANDAR2020,CANDAR2021,CANDAR2022,CANDAR2023,CANDAR2024, Program Committee Member

    Role(s): Peer review

    International Symposium on Computing and Networking 

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    Type:Peer review 

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  • GCA’18, GCA’19, GCA’20, GCA’21, GCA’22, GCA’23, GCA’24, Program Committee Member

    Role(s): Peer review

    International Workshop on GPU Computing and AI 

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    Type:Peer review 

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  • IDW’18, Program Committee Member

    Role(s): Peer review

    International Display Workshop 

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    Type:Peer review 

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  • GCCE-2021, OS-AIR: Artificial Intelligence & Robotics, Reviewer

    Role(s): Peer review

    IEEE 10th Global Conference on Consumer Electronics 

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    Type:Peer review 

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  • IWEC-2013, Program Committee Member

    Role(s): Peer review

    4th International Workshop on Empathic Computing 

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    Type:Peer review 

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  • The 21st International Conference on Persuasive Technology 2026, Program Committee Member

    Role(s): Peer review

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    Type:Academic society, research group, etc. 

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  • WCTP-2012, WCTP-2013, WCTP-2014, WCTP-2016, WCTP-2017, WCTP-2018, WCTP-2019, WCTP-2023, Program Committee Member

    Role(s): Peer review

    Workshop on Computation: Theory and Practice 

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    Type:Peer review 

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  • SMC2017, SMC2019, SMC2020, Technical Program Committee Member

    Role(s): Peer review

    IEEE International Conference on Systems, Man, and Cybernetics 

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    Type:Peer review 

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  • International Conference on Artificial Intelligence Applications and Innovations (AIAI 2025), Program Committee Member

    Role(s): Peer review

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    Type:Peer review 

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  • BMOT2016, BMOT2017, BMOT2018, BMOT2019, BMOT2020, Program Committee Member

    Role(s): Peer review

    International Conference on Business Management of Technology 

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    Type:Peer review 

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  • PDPTA’16, PDPTA’17, PDPTA’18, Program Committee Member

    Role(s): Peer review

    Workshop on Mathematical Modeling and Problem Solving 

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    Type:Peer review 

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  • SDM-2014, International Program Committee Member

    Role(s): Peer review

    1st International Conference on Sustainable Design and Manufacturing 

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    Type:Peer review 

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