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    1. S. Okumura, S. Hiwa, T. Yasuda, H. Kitae, Y. Yasuda, A. Tomie, T. Omatsu, H. Ichikawa, N. Yagi, T. Hiroyasu, "Demarcation line determination for diagnosis of gastric cancer disease range using unsupervised machine learning in magnifying narrow-band imaging," medRxiv, 2020.11.03.20189472; doi:10.1101/2020.11.03.20189472 (Nov 2020).
    2. T. Miyoshi, K. Tanioka, S. Yamamoto, H. Yadohisa, T. Hiroyasu, S. Hiwa, "Short-term effects on brain functional network caused by focused-attention meditation revealed by Tucker3 clustering on graph theoretical metrics," bioRxiv, 765693; doi:10.1101/765693 (Sep 2019). Now published in Frontiers in Human Neuroscience, doi: 10.3389/fnhum.2019.00473


    1. T. Miyoshi, K. Tanioka, S. Yamamoto, H. Yadohisa, T. Hiroyasu, S. Hiwa, "Revealing changes in brain functional networks caused by focused-attention meditation using Tucker3 clustering," Frontiers in Human Neuroscience, Volume 13, Article 473, doi:10.3389/fnhum.2019.00473 (Jan 2020).
    2. T. Yasuda, T. Hiroyasu, S. Hiwa, Y. Okada, S. Hayash, Y. Nakahata, Y. Yasuda, T. Omatsu, A. Obora, T. Kojima, H. Ichikawa, N. Yagi, "Potential of Automatic Diagnosis System with Linked Color Imaging for Diagnosis of Helicobacter Pylori Infection," Digestive Endoscopy, doi: 10.1111/den.13509 (Aug 2019).
    3. A. Fukushima, M. Sugimoto, S. Hiwa and T. Hiroyasu, "Elastic net-based prediction of IFN-β treatment response of patients with multiple sclerosis using time series microarray gene expression profiles," Scientific Reports, Volume 9, Issue 1, 1822; doi:10.1038/s41598-018-38441-2 (Feb 2019).
    4. M. Mizuno, T. Hiroyasu and S. Hiwa, "A Functional NIRS Study of Brain Functional Networks Induced by Social Time Coordination," Brain Sciences, Volume 9, Issue 2, 43; doi:10.3390/brainsci9020043 (Feb 2019).
    5. N. Okumura, K. Kobayashi, N. Ishida, T. Kagami, S. Hiwa, T. Hiroyasu and N. Koizumi, "Development of Cell Analysis Software to Evaluate Fibroblastic Changes in Cultivated Corneal Endothelial Cells for Quality Control," Cornea, Volume 37, Issue 12, Pages 1572-1578 (Dec 2018).
    6. S. Hiwa, T. Katayama and T. Hiroyasu, "Functional near‐infrared spectroscopy study of the neural correlates between auditory environments and intellectual work performance," Brain and Behavior, e01104, doi:10.1002/brb3.1104 (Sep 2018).
    7. Q. Ma, Y. Zhang, K. Yamamori, H. Furutani, S. Hiwa and T. Hiroyasu, "Markov chain analysis of evolutionary algorithms for monotonic functions," Artificial Life and Robotics, doi:10.1007/s10015-018-0463-9 (Sep 2018).
    8. K. Aoki, S. Hiwa, H. Furutani and T. Hiroyasu, "Tobit model analysis of mutations causing haemophilia," Artificial Life and Robotics, Volume 23, Issue 3, pp 287–291, doi:10.1007/s10015-018-0431-4 (Sep 2018).
    9. S. Hiwa, S. Obuchi and T. Hiroyasu, "Automated extraction of human functional brain network properties associated with working memory load through a machine learning-based feature selection algorithm," Computational Intelligence and Neuroscience, vol. 2018, Article ID 4835676, 12 pages, 2018. doi:10.1155/2018/4835676 (Apr 2018).
    10. N. Okumura, N. Ishida, K. Kakutani, A. Hongo, S. Hiwa, T. Hiroyasu and N. Koizumi, " "Development of Cell Analysis Software for Cultivated Corneal Endothelial Cells," Cornea, Volume 36, Issue 11, Pages 1387-1394 (Nov 2017).
    11. S. Hiwa, M. Miki and T. Hiroyasu, "Validity of decision mode analysis on an ROI determination problem in multichannel fNIRS data" Artificial Life and Robotics, 2017, Volume 22, Issue 3, pp 336-345, doi:10.1007/s10015-017-0362-5 (Sep 2017).
    12. S. Hiwa, K. Hanawa, R. Tamura, K. Hachisuka and T. Hiroyasu, "Analyzing Brain Functions by Subject Classification of Functional Near-Infrared Spectroscopy Data Using Convolutional Neural Networks Analysis," Computational Intelligence and Neuroscience, vol. 2016, Article ID 1841945, 9 pages, 2016. doi:10.1155/2016/1841945 (Oct 2016).
    13. S. Hiwa, M. Nishioka, T. Hiroyasu and M. Miki, "Novel Search Scheme for Multi-Objective Evolutionary Algorithms to Obtain Well-Approximated and Widely Spread Pareto Solutions," Swarm and Evolutionary Computation, Volume 22, Pages 30-46, ISSN 2210-6502, doi:10.1016/j.swevo.2015.01.004. (June 2015).
    14. S. Hiwa, T. Hiroyasu and M. Miki, "Design Mode Analysis of Pareto Solution Set for Decision-Making Support," Journal of Applied Mathematics, vol. 2014, Article ID 520209, 15 pages, doi:10.1155/2014/520209 (Nov 2014).

    Refereed Conference Papers

    1. S. Hiwa and T.Hiroyasu, "Manifold learning on time-varying functional connectivity matrices: A case study on meditation data," The 25th Annual Meeting of the Organization for Human Brain Mapping, Rome, Italy (June 2019).
    2. L. Perino, A. Fujii, T. Waku, A. Kobayashi, S. Hiwa and T.Hiroyasu, "Solution exploration using multi-objective genetic algorithm for determining experiment candidate," Proceedings of the 2018 conference on Genetic and Evolutionary Computation (GECCO 2018), pp. 1584-1589, ACM (July 2018).
    3. S. Hiwa and T.Hiroyasu, "Evolutionary optimization approach to explore the functional network organization during meditation," The 24th Annual Meeting of the Organization for Human Brain Mapping, Singapore (June 2018).
    4. S. Hiwa, M.Iizuka and T.Hiroyasu, "Characterizing the meditative state based on functional connectivity and low-frequency fluctuation," The 23rd Annual Meeting of the Organization for Human Brain Mapping, Vancouver, Canada (June 2017).
    5. T. Hiroyasu and S. Hiwa, "Brain functional state analysis of mindfulness using graph theory and functional connectivity," AAAI Spring Symposium - Technical Report, vol. SS-17-01 - SS-17-08, pp. 675–680, 2017 (Mar 2017).
    6. S. Hiwa, Y. Kohri, K. Hachisuka and T. Hiroyasu, "Region-of-Interest Extraction of fMRI data using Genetic Algorithms." 2016 IEEE Symposium Series on Computational Intelligence (SSCI 2016), Athens, Greece, (Dec 2016).
    7. K. Harada, M. Tanaka, S. Hiwa, H. Zille, S. Mostaghim and T. Hiroyasu, "Functional brain network extraction using a genetic algorithm with a kick-out method." Evolutionary Computation, CEC 2016. IEEE Congress on, Vancouver, Canada (Jul 2016).
    8. S. Hiwa, T. Hiroyasu, H. Yokouchi, M. Miki and M. Nishioka, "Reference point-based search scheme for multiobjective evolutionary algorithm," in: Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on, pp. 1666--1672 (Nov 2012).
    9. S. Hiwa, T. Hiroyasu and M. Miki, "Hybrid optimization using DIRECT, GA, and SQP for global exploration," in: Evolutionary Computation, CEC 2007. IEEE Congress on, pp.1709--1716 (Sep 2007).
    10. M. Miki, S. Hiwa and T. Hiroyasu, "Simulated Annealing using an Adaptive Search Vector," Cybernetics and Intelligent Systems, 2006 IEEE Conference on, pp.1--6 (Jun 2006).

    Non-Refereed Conference Papers

    1. S. Hiwa and T. Hiroyasu, "Detecting meditative states through meta-state matching with time-varying functional connectivity matrices," 2017 Neuroscience Meeting Planner. Washington, D.C.: Society for Neuroscience (Nov 2017).
    2. S. Hiwa, M. Iizuka and T. Hiroyasu, "Graph theoretical analysis of functional connectivity network during breath-counting mindfulness meditation," 2016 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience (Nov 2016).

    Domestic Conference Papers

    1. 日和 悟,廣安知之,"マインドフルネスを「見える化」する:脳の動的機能的結合に基づく瞑想状態," 日本マインドフルネス学会第4回大会(最優秀研究賞受賞) (2017年12月).
    2. 日和 悟,廣安知之,"脳機能イメージングによる瞑想状態の特徴抽出と検出," 第8回横幹連合コンファレンス (2017年12月).
    3. 日和 悟,飯塚まり,廣安知之,"自発性脳活動の強度と機能的結合度に基づく瞑想時脳状態の低次元表現," 第31回人工知能学会全国大会論文集 (2017年5月).
    4. 日和 悟, 廣安知之, 飯塚まり, "脳機能情報に基づく瞑想状態解析手法の提案," 日本マインドフルネス学会第3回大会 (2016年11月).
    5. 日和 悟,飯塚まり,廣安知之,"脳機能情報による瞑想状態の検討," 第30回人工知能学会全国大会論文集 1G4-OS-11a-1 (2016年6月).
    6. 日和 悟,廣安知之,三木光範,"大域的最適化のための複数最適化手法の動的制御法," 日本機械学会 第7回最適化シンポジウム (2006年12月).
    7. 日和 悟,廣安知之,三木光範,"大域的最適化のための複数最適化手法の動的制御法," 日本機械学会 第16回設計工学・システム部門講演会 (2006年11月).
    8. 三木光範,日和 悟,廣安知之,"適応的探索ベクトルをもつシミュレーテッドアニーリング," 日本機械学会 第18回計算力学講演会 (2005年11月).
    9. 日和 悟,三木光範,廣安知之,"多目的シミュレーテッドアニーリングを用いた知的LED照明システム," 情報処理学会 第67回全国大会 (2005年3月).
    10. 三木光範,廣安知之,日和 悟,實田 健,"ダミー目的関数をもつ多目的確率的山登り法,"情報処理学会 情報科学技術フォーラム (2004年9月).

    Bulletin Papers

    1. 日和 悟 "マインドフルネスとウェルビーイング," 特集「心とVR」,日本バーチャルリアリティ学会誌 第23巻,1号,30-34 (2018年3月).
    2. 三木光範,日和 悟,廣安知之,"LEDを用いた調色用照明システムの基礎的検討," 同志社大学理工学研究報告 Vol.46, No.3, pp 9-18 (2005年10月).


    1. 日和 悟 "Chapter 5 マインドフルネス状態の推定," 飯塚まり編「進化するマインドフルネス」: ウェルビーイングへと続く道,創元社(2018年5月).


    1. 「ウェルビーイングを日本視点で考える。ドミニク・チェン、石川善樹らの参加する研究会レポート」 bound bow (2018.06.26)
    2. 「幸せ高める脳活動解析」京都新聞夕刊 (2018.6.23)


    1. 日和 悟 "脳活動状態定量化方法および脳活動状態計測装置," 特願2016-182662 (2016年9月)
    2. S. Hiwa "Secondary battery state-of-charge estimating device and secondary battery state-of-charge estimating method," PCT/JP2016/000545(WO2016129248 A1) (Feb 2016)
    3. 日和 悟 "二次電池の充電状態推定装置および充電状態推定方法," 特願2015-026704 (2015年2月)
    4. T. Omi, K. Miura, S. Hiwa, T. Iida, K. Kakutani, "Battery state estimation device and method of estimating battery state," PCT/JP2015/001027(WO2015133103 A1) (Feb 2015)
    5. 近江 亨, 三浦謙一, 日和 悟, 飯田琢磨, 角谷和重, "電池の状態推定装置,および,電池の状態推定方法," 特願2014-040460 (2014年3月)
    6. S. Hiwa "Pulse-width-modulated waveform generation device," PCT/JP2013/004474(WO2014024402 A1), (Jul 2013)
    7. 日和 悟 "パルス幅変調波形生成装置," 特願2012-173551 (2012年8月)
    8. 日和 悟, 青木祐二, "DC/DC コンバータ" 特願2011-006594 (特開2012-151926) (2011年1月)