Updated on 2024/03/30

写真a

 
HAYASHI,Isao
 
Organization
Faculty of Informatics Professor
Title
Professor
Other name(s)
Professor
External link

Degree

  • 工学博士

Research Areas

  • Informatics / Soft computing

Education

  • Osaka Prefecture University   Graduate School, Division of Engineering

    - 1987

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  • Osaka Prefecture University   Faculty of Engineering

    - 1981

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    Country: Japan

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  • Osaka Prefecture University   Graduate School, Division of Engineering

    1987

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    Country: Japan

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Papers

  • Formulation of pdi-Bagging and Its Evaluation Reviewed

    Honoka Irie, Isao Hayashi

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.35, No.1, pp.603-614   2023.2

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  • Research for Matchup Analysis of Pass play in American Football with Deep Learning Reviewed

    Yuhei Yamamoto, Shigenori Tanaka, Kenji Nakamura, Chihiro Tanaka, Wenyuan Jiang, Isao Hayashi

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.32, No.1, pp.590-603   2020.2

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  • Design Evaluation of Learning Type Fuzzy Inference Using Trapezoidal Membership Function Reviewed

    Honoka Irie, Isao Hayashi

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.31, No.6, pp.908-917   2019.12

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  • Time-Series Data Analysis Using Sliding Window Based SVD for Motion Evaluation Reviewed

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang, Kenji Ishida

    Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII)   Vol.21, No.7, pp.1240-1250, DOI:10.20965/jaciii.2017.p1240 ( 7 )   1240 - 1250   2017.11

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    Language:English   Publisher:Fuji Technology Press  

    CiNii Books

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  • Extraction of Knowledge from the Topographic Attentive Mapping Network and its Application in Skill Analysis of Table Tennis

    Isao Hayashi, Masanori Fujii, Toshiyuki Maeda, Jasmin Leveille, Tokio Tasaka

    JOURNAL OF HUMAN KINETICS   55 ( 1 )   39 - 54   2017.1

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:DE GRUYTER OPEN LTD  

    The Topographic Attentive Mapping (TAM) network is a biologically-inspired classifier that bears similarities to the human visual system. In case of wrong classification during training, an attentional top-down signal modulates synaptic weights in intermediate layers to reduce the difference between the desired output and the classifier's output. When used in a TAM network, the proposed pruning algorithm improves classification accuracy and allows extracting knowledge as represented by the network structure. In this paper, sport technique evaluation of motion analysis modelled by the TAM network was discussed. The trajectory pattern of forehand strokes of table tennis players was analyzed with nine sensor markers attached to the right upper arm of players. With the TAM network, input attributes and technique rules were extracted in order to classify the skill level of players of table tennis from the sensor data. In addition, differences between the elite player, middle level player and beginner were clarified; furthermore, we discussed how to improve skills specific to table tennis from the view of data analysis.

    DOI: 10.1515/hukin-2017-0005

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  • Analysis of Structure Characteristic in Rat Cultured Neuronal Network Using Fuzzy Operator Reviewed

    Isao Hayashi, Koki Mitsumoto, Megumi Kiyotoki, Suguru N. Kudoh

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.28, No.3, pp.675-684 (2016) ( 3 )   675 - 684   2016.6

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    Language:Japanese   Publisher:Japan Society for Fuzzy Theory and Intelligent Informatics  

    We discuss how to acquire logicality, orientation, and connectivity of action potential from living neuronal network in vitro. The action potential of rat hippocampal neurons organized into complex networks is detected in a culture dish by MED system carried with 64 planar microelectrodes. We propose an analysis method to acquire logicality and orientation of action potentials detected at three electrodes of the culture dish by fuzzy operators incorporating t-norm and tconorm operators. In addition, we propose a definition of connectivity of action potentials among electrodes by fuzzy inclusion degree. Finally, we discuss the relationship between logicality and connectivity of action potentials propagating with an orientation, e.g., transmission, absorption, and diffusion. We show that fuzzy concept is useful even in living neuronal network in vitro.

    DOI: 10.3156/jsoft.28.675

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  • Knowledge Acquisition Method Based on Singular Value Decomposition for Human Motion Analysis

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING   26 ( 12 )   3038 - 3050   2014.12

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:IEEE COMPUTER SOC  

    The knowledge remembered by the human body and reflected by the dexterity of body motion is called embodied knowledge. In this paper, we propose a new method using singular value decomposition for extracting embodied knowledge from the time-series data of the motion. We compose a matrix from the time-series data and use the left singular vectors of the matrix as the patterns of the motion and the singular values as a scalar, by which each corresponding left singular vector affects the matrix. Two experiments were conducted to validate the method. One is a gesture recognition experiment in which we categorize gesture motions by two kinds of models with indexes of similarity and estimation that use left singular vectors. The proposed method obtained a higher correct categorization ratio than principal component analysis (PCA) and correlation efficiency (CE). The other is an ambulation evaluation experiment in which we distinguished the levels of walking disability. The first singular values derived from the walking acceleration were suggested to be a reliable criterion to evaluate walking disability. Finally we discuss the characteristic and significance of the embodied knowledge extraction using the singular value decomposition proposed in this paper.

    DOI: 10.1109/TKDE.2014.2316521

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  • Analysis and extraction of knowledge from body motion using singular value decomposition Reviewed

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    IEEE International Conference on Fuzzy Systems   2438 - 2443   2014.9

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

    The dexterity of body motion when performing skills are being actively studied. In this paper, singular value decomposition is used to extract the dexterous features from the time-series data of body motion. A matrix is composed by overlapping the subsets of the time-series data. The left singular vectors of the matrix are extracted as the patterns of the motion and the singular values as a scalar, by which each corresponding left singular vector affects the matrix. A gesture recognition experiment, in which we categorize gesture motions with indexes of similarity and estimation that use left singular vectors, was conducted to validate the method. Furthermore, in order to understand the features better, the features of the left singular vectors were described as fuzzy sets, and fuzzy if-then rules were used to represent the knowledge.

    DOI: 10.1109/FUZZ-IEEE.2014.6891712

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  • Description of activity of living neuronal network by fuzzy bio-indicator Reviewed

    Isao Hayashi, Suguru N. Kudoh

    IEEE International Conference on Fuzzy Systems   2424 - 2429   2014.9

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

    The culture dish describes the small fundamental world resembling human brain function. Multi-site recording system for extracellular action potentials is used for recording the activity of living neuronal networks. The living neuronal network is able to express several patterns independently, and that's meaning that it has fundamental mechanisms for intelligent information processing. In this paper, we propose a model to analyse logicality of signals and connectivity of electrodes in a culture dish of rat hippocampal neurons. We call it 'fuzzy bio-indicator'. This indicator is a kind of mapping methods to show logicality and connectivity of pulse frequency from active potential of neuronal network. We try to analyze the dynamics of action potentials of neuronal networks by the fuzzy bio-indicator, and identify the logicality and connectivity of neuronal networks through the indicator. We show here the usefulness of fuzzy bio-indicator through numerical examples and action potential detected from the culture neuronal network.

    DOI: 10.1109/FUZZ-IEEE.2014.6891880

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  • A Probabilistic WKL Rule for Incremental Feature Learning and Pattern Recognition Reviewed

    Jasmin Leveille, Isao Hayashi, Kunihiko Fukushima

    Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII)   Vol.18, No.4, pp.672-681   2014.7

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  • Neocognitron trained by winner-kill-loser with triple threshold Reviewed

    Kunihiko Fukushima, Isao Hayashi, Jasmin Leveille

    NEUROCOMPUTING   129   78 - 84   2014.4

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

    The neocognitron is a hierarchical, multi-layered neural network capable of robust visual pattern recognition. The neocognitron acquires the ability to recognize visual patterns through learning. The winner-kill-loser is a competitive learning rule recently shown to outperform standard winner-take-all learning when used in the neocognitron to perform a character recognition task. In this paper, we improve over the winner-kill-loser rule by introducing an additional threshold to the already existing two thresholds used in the original version. It is shown theoretically, and also by computer simulation, that the use of a triple threshold makes the learning process more stable. In particular, a high recognition rate can be obtained with a smaller network. (C) 2013 Elsevier B.V. All rights reserved.

    DOI: 10.1016/j.neucom.2012.05.038

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  • Description of Activity of Living Neuronal Network by Fuzzy Bio-Indicator Reviewed

    Isao Hayashi, Suguru N. Kudoh

    2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)   2424 - 2429   2014

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

    The culture dish describes the small fundamental world resembling human brain function. Multi-site recording system for extracellular action potentials is used for recording the activity of living neuronal networks. The living neuronal network is able to express several patterns independently, and that's meaning that it has fundamental mechanisms for intelligent information processing. In this paper, we propose a model to analyse logicality of signals and connectivity of electrodes in a culture dish of rat hippocampal neurons. We call it "fuzzy bio-indicator". This indicator is a kind of mapping methods to show logicality and connectivity of pulse frequency from active potential of neuronal network. We try to analyze the dynamics of action potentials of neuronal networks by the fuzzy bio-indicator, and identify the logicality and connectivity of neuronal networks through the indicator. We show here the usefulness of fuzzy bio-indicator through numerical examples and action potential detected from the culture neuronal network.

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  • Analysis and Extraction of Knowledge from Body Motion Using Singular Value Decomposition Reviewed

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)   2438 - 2443   2014

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

    The dexterity of body motion when performing skills are being actively studied. In this paper, singular value decomposition is used to extract the dexterous features from the time-series data of body motion. A matrix is composed by overlapping the subsets of the time-series data. The left singular vectors of the matrix are extracted as the patterns of the motion and the singular values as a scalar, by which each corresponding left singular vector affects the matrix. A gesture recognition experiment, in which we categorize gesture motions with indexes of similarity and estimation that use left singular vectors, was conducted to validate the method. Furthermore, in order to understand the features better, the features of the left singular vectors were described as fuzzy sets, and fuzzy if-then rules were used to represent the knowledge.

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  • Fuzzy Bio-Indicator: Evaluation of Logicality and Connectivity for Living Neuronal Network. Reviewed

    Isao Hayashi, Koki Mitsumoto, Suguru N. Kudoh

    proc. 8th International Conference on Body Area Networks(BODYNET2013)   2013.10

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

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  • Skill Analysis with Time Series Image Data Reviewed

    Toshiyuki Maeda, Masanori Fujii, Isao Hayashi

    The International Journal of Soft Computing and Software Engineering   Vol.3, No.3, pp.576-580   2013.3

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  • Singular Value Analysis through Divided Time-Series Data and its Application to Walking Difficulty Evaluation Reviewed

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013)   2013

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

    Motion time-series data observed with various sensing systems are usually analyzed to extract embodied knowledge which is remembered by the human body and reflected by the dexterity in the motion of the body. A method based on singular value analysis through divided time-series data (SVA-DTS) is proposed for extracting features from time-series data. Matrices are composed from the subsets of time-series data and the left singular vectors of the matrices are extracted as the patterns of the motion and the singular values as a scalar, by which the corresponding left singular vectors affects the matrices. The SVA-DTS was applied to a walking difficulty evaluation experiment in which three levels of walking difficulty were simulated by restricting the right knee joint. The accelerations of the middles of the shanks and the back of the waist were measured. Singular values were calculated from the normalized acceleration time-series data with the SVA-DTS. The results showed that the first singular values inferred from the acceleration data of the right shank significantly related to the increase of the restriction to the right knee. The first singular values of the acceleration data of the right shank were suggested to be reliable criteria to evaluate walking difficulty. We visualize the first singular values in a 3D space to provide intuitive information about walking difficulty which can be used as a tool for evaluating walking difficulty.

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  • Acquisition of Motion Features by Singular Value Decomposition Reviewed

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.24, No.1, pp.513-525 ( 1 )   513 - 525   2012.2

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    Language:Japanese   Publisher:Japan Society for Fuzzy Theory and Intelligent Informatics  

    Recently, various methods that analysed physical movement have been proposed. Kawato has argued that internal model with closed loop between feedback control and feedforward control is useful for sinuous movement as a model for motor control. In this paper, we consider internal model as a function model identified from observed data, and propose a model to extract the characteristic of human movement with singular value decomposition from the time-series data of various sensors. We call the knowledge acquired by the internal model embodied knowledge. In particular, we categorized gesture motions by two kinds of models with the indexes of similarity and estimation using left singular vectors. In addition, the ambulation movement is distinguished by hyperplane of three-dimension constructed by singular value. Finally we discussed characteristic and significance of the movement analysis using singular value decomposition proposed in this paper.

    DOI: 10.3156/jsoft.24.513

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    Other Link: https://jlc.jst.go.jp/DN/JALC/00389664473?from=CiNii

  • Online learning of feature detectors from natural images with the probabilistic WKL rule Reviewed

    Jasmin Leveille, Isao Hayashi, Kunihiko Fukushima

    6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS   177 - 182   2012

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

    Recent advances in machine learning and computer vision have led to the development of several sophisticated learning schemes for object recognition by convolutional networks. One relatively simple learning rule, the Winner-Kill-Loser (WKL), was shown to be efficient at learning higher-order features in the neocognitron model when used in a written digit classification task. The WKL rule is one variant of incremental clustering procedures that adapt the number of cluster components to the input data. The WKL rule seeks to provide a complete, yet minimally redundant, covering of the input distribution. It is difficult to apply this approach directly to high-dimensional spaces since it leads to a dramatic explosion in the number of clustering components. In this work, a small generalization of the WKL rule is proposed to learn from high-dimensional data, and is shown to lead mostly to V1-like oriented cells when applied to natural images.

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  • Evaluation and Visualizaton of Evacuees' Walking Difficulty in Disasters Reviewed

    Isao Hayashi, Yinlai Jiang, Shuoyu Wang

    6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS   1907 - 1910   2012

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

    Identification of the evacuees with walking difficulty will definitely lead to quick rescue and thus improve the efficiency of evacuation in times of disasters or calamities. We are developing a new method using singular value decomposition for extracting features from the time-series data which is measured with various sensors such as an accelerometer, a motion capture system and a force sensor. In this paper, we apply this method to assess walking difficulty based on three dimensional acceleration data during walking. In order to verify the usefulness of the method, three levels of walking disability in the lower limbs are simulated by constraining the knee joint and ankle joint of the right leg. The accelerations of the middle of shanks and the back of the waist are measured and analyzed after normalization. Features related to walking difficulty are acquired from the time-series acceleration data using singular value decomposition. The results showed that the first singular values inferred from the acceleration data of the right and left shanks significantly related to the increase of the constraint to the joints. The first singular values of the shanks were suggested to be reliable criteria to evaluate walking difficulty. We propose a triangular tool to provide intuitive information extracted from the first singular values to assist the evaluation of the walking difficulty.

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  • Neurorobot Vitroid - A living test model for embodiment brain research.

    Suguru N. Kudoh, Hidekatsu Ito, Isao Hayashi

    The 6th International Conference on Soft Computing and Intelligent Systems (SCIS), and The 13th International Symposium on Advanced Intelligence Systems (ISIS)(SCIS&ISIS)   1472 - 1475   2012

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    Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/SCIS-ISIS.2012.6505398

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    Other Link: https://dblp.uni-trier.de/db/conf/scisisis/scisisis2012.html#KudohIH12

  • A measure of localization of brain activity for the motion aperture problem using electroencephalograms Reviewed

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    Developing and Applying Biologically-Inspired Vision Systems: Interdisciplinary Concepts   208 - 223   2012

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    Language:English   Publishing type:Part of collection (book)   Publisher:IGI Global  

    When viewed through a limited-sized aperture, bars appear to move in a direction normal to their orientation. This motion aperture problem is an important rubric for analyzing the early stages of visual processing particularly with respect to the perceptual completion of motion sampled across two or more apertures. In the present study, a circular aperture was displayed in the center of the visual field. While the baseline bar moved within the aperture, two additional circular apertures appeared
    within each aperture, a "flanker bar" appeared to move. For upwards movement of the flanker lines, subjects perceived the flanker bar to be connected to the base bar, and all three parts to move upward. The authors investigated the motion perception of the moving bars by changing the line speeds, radii of the apertures, and distances between the circular apertures and then analyzed spatio-temporal brain activities by electroencephalograms (EEGs). Latencies in the brain were estimated by using equivalent current dipole source (ECD) localization for one subject. Soon after the flankers appear, ECDs, assumed to be generated by the recognition of the aperture's form, were localized along the ventral pathway. After the bars moved, the ECDs were localized along the dorsal pathway, presumably in response to motion of the bars. In addition, for the perception of grouped motion and not normal motion, ECDs were localized to the middle frontal gyrus and the inferior frontal gyrus. © 2013, IGI Global.

    DOI: 10.4018/978-1-4666-2539-6.ch009

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  • Evaluation of Walking Difficulty Using Singular Value Analysis through Divided Time-Series Data

    Jiang Yinlai, Hayashi Isao, Wang Shuoyu

    Proceedings of the Fuzzy System Symposium   28   1105 - 1110   2012

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    Language:Japanese   Publisher:Japan Society for Fuzzy Theory and Intelligent Informatics  

    Walking difficulty often happens in times of disasters. Identification of the evacuees with walking difficulty will definitely lead to quick rescue and thus improve the efficiency of evacuation. A precise and convenient method is being developed to automatically analyze the evacuees' walking. In this paper, we propose a method for assessing walking difficulty using singular value analysis through divided time-series data (SVA-DTS). In order to verify the usefulness of the proposed method, three levels of walking difficulty in the lower limbs are simulated in an experiment by constraining the knee joint and ankle joint of the right leg. The accelerations of the middle of shanks and the back of the waist are measured. The results showed that the first singular values inferred from the acceleration data of the right shank significantly related to the increase of the constraint to the joints. The first singular values of the acceleration data of the shanks were suggested to be reliable criteria to evaluate walking difficulty. We visualize the first singular values in a 3D space to provide intuitive information about walking ability which can be used as a tool for identifying the evacuees with walking difficulty.

    DOI: 10.14864/fss.28.0_1105

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  • Embodied Knowledge Extraction from Human Motion Using Singular Value Decomposition Reviewed

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)   2012

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

    Embodied knowledge is the knowledge remembered by the human body and reflected by the dexterity in the motion of the body. In this paper, we propose a new method using singular value decomposition for extracting embodied knowledge from the time-series data of the motion which is measured with various sensors such as an accelerometer, a motion capture system and a force sensor. We compose a matrix from the the time-series data and use the left singular vectors of the matrix as the patterns of the motion and the singular values as a scalar, by which each corresponding left singular vector affects the matrix. Two experiments were conducted to testify the method. One is a gesture recognition experiment in which we categorize gesture motions by two kinds of models with the indexes of similarity and estimation using left singular vectors. The other is an ambulation evaluation experiment in which we distinguished the levels of walking disability using a 3D hyperplane constructed by the singular values. Finally we discuss the characteristic and significance of the embodied knowledge extraction using singular value decomposition proposed in this paper.

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  • Biomodeling System: Interactive Connection between Cultured Neuronal Network and Moving Robot Using Fuzzy Interface Reviewed

    Isao Hayashi, Minori Tokuda, Ai Kiyohara, Takahisa Taguchi, Suguru N. Kudoh

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.23, No.5, pp.761-772   2011.10

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  • Acquisition of Embodied Knowledge on Gesture Motion by Singular Spectrum Analysis Reviewed

    Isao Hayashi, Yinlai Jiang, Shuoyu Wang

    Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII)   Vol.15, No.8, pp.1011-1018   2011.8

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  • Fuzzy bio-interface: Indicating logicality from living neuronal network and learning control of bio-robot. Reviewed

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    proc. Neural Networks (IJCNN), The 2011 International Joint Conference on Fuzzy Systems   2417 - 2423   2011.8

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

    DOI: 10.1109/IJCNN.2011.6033532

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  • Toward Time-Sensitive Structure Analysis for SPAM Filtering: A Data Mining Approach

    Atsushi Inoue, Isao Hayashi, Toshiyuki Maeda, Yoshinori Arai, Takashi Kobayashi

    2011.5

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  • In Vitro Logicality for Neuro-Robot Hybrid. Reviewed

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    Proc. of the fifteenth International Conference on Cognitive and Neural Systems (ICCNS2011), Boston, U.S.A. on May 14   84   2011.5

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  • Fuzzy Bio-Interface: Logicality of Living Neuronal Network and Control of Fuzzy Bio-Robot System. Reviewed

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    Proc. of World Conference on Soft Computing (WConSC2011), San Francisco, U.S.A. on May 25   161   2011.5

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  • Fuzzy Bio-interface: Can fuzzy set be an interface with brain? Reviewed

    Isao Hayashi, Suguru N. Kudoh

    Proc. of the 22nd Midwest Artificial Intelligence and Cognitive Science Conference (MAICS2011), Omron Plenary Lecture,Cincinnati, U.S.A. on April 16   2 - 6   2011.4

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  • Vitroid - The Robot System with an Interface Between a Living Neuronal Network and Outer World Reviewed

    Suguru N. Kudoh, Minori Tokuda, Ai Kiyohara, Chie Hosokawa, Takahisa Taguchi, Isao Hayashi

    International Journal of Mechatronics and Manufacturing System   Vol.4, No.2, pp.135-149   2011.4

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  • Neocognitron Trained by Winner-Kill-Loser with Triple Threshold Reviewed

    Kunihiko Fukushima, Isao Hayashi, Jasmin Leveille

    NEURAL INFORMATION PROCESSING, PT II   7063   628 - +   2011

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:SPRINGER-VERLAG BERLIN  

    The neocognitron is a hierarchical, multi-layered neural network capable of robust visual pattern recognition. The neocognitron acquires the ability to recognize visual patterns through learning. The winner-kill-loser is a recently introduced competitive learning rule that has been shown to improve the neocognitron's performance in character recognition. This paper proposes an improved winner-kill-loser rule, in which we use a triple threshold, instead of the dual threshold used as part of the conventional winner-kill-loser. It is shown theoretically, and also by computer simulation, that the use of a triple threshold makes the learning process more stable. In particular; a high recognition rate can be obtained with a smaller network.

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  • Acquisition of embodied knowledge on gesture motion by singular value decomposition Reviewed

    Isao Hayashi, Yinlai Jiang, Shuoyu Wang

    Journal of Advanced Computational Intelligence and Intelligent Informatics   15 ( 8 )   1011 - 1018   2011

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

    Communication is classified in terms of verbal and nonverbal information. We discuss an acquisition method of knowledge from nonverbal information. In particular, a gesture is an efficient form of nonverbal communication as well as in verbal ways, and we formulate here a method that measures similarity and estimation between gestures. A gesture includes human embodied knowledge, and therefore the visible bodily actions can communicate particular messages. However, we have infinite patterns for gesture, determined by personality. Recently, the singular spectrum analysis method is utilized as an attractive method. In this paper, we propose a new method for acquiring embodied knowledge from time-series data on gestures using singular value decomposition. The motion behavior is categorized into several clusters with similarity and estimation between interval time-series data. We discuss the usefulness of the proposed method using an example of gesture motion.

    DOI: 10.20965/jaciii.2011.p1011

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  • Recognition of Perceptual Grouping and Localization of Brain Activity in Aperture Problems Reviewed

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol.22, No.5, pp.642-651 ( 5 )   2010.10

  • Classification Accuracy Enhancement for an fNIRS Brain-Computer Interface Using Sigular Spectrum Transformation Reviewed

    Yinlai Jiang, Shuoyu Wang, Isao Hayashi

    ICIC Express Letters   Vol.4, No.6(A), pp.2195-2199   2010.9

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  • Acquisition of Logicality in Living Neuronal Networks and its Operation to Fuzzy Bio-Robot System. Reviewed

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    proc. of 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2010) in 2010 IEEE World Congress on Computational Intelligence (WCCI2010)   543 - 549   2010.9

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

    DOI: 10.1109/FUZZY.2010.5584887

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  • Three-dimensional motion analysis for gesture recognition using singular value decomposition Reviewed

    Yinlai Jiang, Isao Hayashi, Masanao Hara, Shuoyu Wang

    2010 IEEE International Conference on Information and Automation, ICIA 2010   805 - 810   2010

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

    A gesture is a form of non-verbal communication in which visible bodily actions communicate particular messages, either in place of speech or together and in parallel with spoken words. Gestures are important in the communication between human and human. It will make a robot more human-friendly to enable it to communicate with human by gestures. Our research addresses to develop a method to recognize human gestures for a guide robot that can be used in hospitals, welfare facilities, and etc. In this paper, firstly, a novel 3D motion analysis algorithm for gesture recognition using singular value decomposition (SVD) is proposed. An experiment, in which five gestures is included, is carried out to testify the effectiveness of the algorithm. The experiment results indicate that the proposed algorithm is applicable for the guide robot to recognize human gestures in guidance. ©2010 IEEE.

    DOI: 10.1109/ICINFA.2010.5512464

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  • Optimal location of wireless LAN access points using fuzzy ID3

    Isao Hayashi, Takashi Kobayashi, Yoshinori Arai, Toshiyuki Maeda, Atsushi Inoue

    Journal of Advanced Computational Intelligence and Intelligent Informatics   13 ( 2 )   128 - 134   2009

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Fuji Technology Press  

    Although wireless LAN is useful in its small size and mobility, the connection region of transmitted radio wave is strongly affected by other electric devices, consumer products, and differences in size and type of the room. Besides, wireless LAN points (APs) must exclude a personal computers without permitting to connect to the Internet. Therefore, how optimally APs are located is important. In this paper, we propose the APs' optimal location method. The proposed algorithm integrates fuzzy rules acquired by fuzzy ID3 with knowledge of security experts, and estimates the connection region for AP. We discuss how to formulate the method for setting AP optimal location and show the effectiveness of this method by illustrating the examples of AP optimal locations.

    DOI: 10.20965/jaciii.2009.p0128

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  • Acquisition of embodied knowledge on sport skill using TAM Network Reviewed

    Isao Hayashi, Toshiyuki Maeda, Masanori Fujii, Shuoyu Wang, Tokio Tasaka

    IEEE International Conference on Fuzzy Systems   1038 - 1043   2009

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    In this paper, we discuss sport technique evaluation using motion analysis model by neural networks and data mining methods. For students of university, we recorded the continuous forehand stroke of the table tennis in the video frames, and analyzed the trajectory pattern of nine marking points attached at subject's body with a coach's technique evaluation and the motion analysis model. As a result, we obtained some technique rules classified member of table tennis club, middle level player and beginner as fuzzy rules, and also estimated the movement of the marking points to improve in table tennis technique. ©2009 IEEE.

    DOI: 10.1109/FUZZY.2009.5277228

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  • Vitroid - a robot with link between living neuronal network in vitro and robot body Reviewed

    Suguru N. Kudoh, Minori Tokuda, Ai Kiyohara, Chie Hosokawa, Takahisa Taguchi, Isao Hayashi

    2008 INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION: (ICMA), VOLS 1 AND 2   374 - +   2008

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    Rat hippocampal neurons organized complex networks on a culture dish which has 64 planar microelectrodes and the spontaneous action potentials were frequently observed. The living neuronal network was able to distinguish patterns of action potentials evoked by different inputs, suggesting that a cultured neuronal network can represent and process particular states as symbols. We use a Khepera II robot and a robot made by LEGO mindstorm NXT kit as a robot body for interfacing with a living neuronal network and the outer world. We call the system "Vitroid". Vitroid has the living neurons, robot body, and direct coupling type of controllers to interface neurons with the robot. We succeeded in performing obstacle avoidance behavior with premised control rule sets. Using self-tuning fuzzy reasoning, we associated a distinct spatial pattern of electrical activity with a particular phenomenon in the outside of the culture dish.

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  • A study on Acquisition of Evaluation Rules for Subcontractors of Construction Companies Using Fuzzy ID3 Reviewed

    Sang-Yul Yang, Sung-Eun Kim, Seung-Gook Hwang, You-Dong Won, Isao Hayashi

    Journal of the Korea Institute of Intelligent Systems   Vol.17, No.5, pp.691-695   2007.7

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  • Recognition of perception and the localization for aperture problem in visual pathway of brain Reviewed

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    2007 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-8   724 - +   2007

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    The aperture problem is the one of the experiments to analyze binding mechanism of the space recognition with the human visual pathway. Nishina has already insisted that recognition of visual perception by the aperture problem depends in display time. In this paper, we discuss how other experimental parameters, e.g., radius, distance between circles, and speed of bar depend with recognition rate by measurement analysis of the perception. We simultaneously estimate the reaction latency of the perception by electroencephalograms(EEG) analysis, and we localize the brain activity area by equivalent current dipole(ECD). We then discuss the relationship between the reaction latency of the visual evoked potential(VEP), event related potential(ERP) and the localized equivalent current dipole(ECD) in the visual pathway. By these discussion, we concluded that perception would be localized with the prefrontal lobe.

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  • Biomodeling System-Interaction Between Living Neuronal Network and Outer World Reviewed

    Suguru N.Kudoh, Chie Hosokawa, Ai kiyohara, Takahisa Taguchi, Isao Hayashi

    Jurnal of Robotics and Mechatoromics   Vol.19,No.5,pp.592-600 ( 5 )   592 - 600   2007

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  • Interaction between living neuronal network and outer world by programmable multisite stimulation system Reviewed

    Suguru N. Kudoh, Ai Kiyohara, Chie Hosokawa, Takahisa Taguchi, Isao Hayashi

    2007 INTERNATIONAL SYMPOSIUM ON MICRO-NANO MECHATRONICS AND HUMAN SCIENCE, VOLS 1 AND 2   44 - +   2007

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    Rat hippocampal neurons organized complex networks on a culture dish which has 64 planner microelectrodes and action potentials of neurons were recorded from an individual electrode. MED64 system, one of multi site recording systems for extracellular action potential was used for recording network activities of living neuronal networks and for applying inputs from outer world to the network. Neurons reconstructed complicated networks along culture days, and a spatio-temporal pattern of spontaneous action potentials was drastically changed after transient high-frequency bursting activities (HFB). After HFB spatial distribution of spontaneous action potentials changed to heterogeneous one. We designed programmable multisite stimulation head amplifier, and analysis of evoked action potentials induced by the stimulator confirmed that there are some hub-like structure which has many inputs from other neurons. In addition we are developing "biomodeling system", in which living neuronal network connected to moving robot.

    DOI: 10.1109/MHS.2007.4420824

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  • Dialog Management System Using Fuzzy Hypothetical Inference of Communication System for the Care of Aged People Reviewed

    Toshiyuki Maeda, Hiroshi Tagami, Isao Hayashi

    Information Science of Hannan University   20, 1-10 ( 20 )   1 - 10   2006

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  • Interaction and intelligence in living neuronal networks connected to moving robot Reviewed

    Suguru N. Kudoh, Takahisa Taguchi, Isao Hayashi

    2006 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5   1162 - +   2006

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    The temporal patterns of spontaneous action potentials are analyzed, using the multi-site recording system for extracellular potentials of neurons and the living neuronal networks cultured on a 2-dimensional electrode arrays. We carried out the system integration for Khepera II robot and living neuronal network. We call the system as "biomodeling system". Our goal is reconstruction of the neuronal network, which can process "thinking" in the dissociated culture system.

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  • A study of orientation selectivity of tam network incorporated receptive field structure Reviewed

    Isao Hayashi, James R. Williamson

    Proceedings of the 3rd International Symposium on Autonomous Minirobots for Research and Edutainment, AMiRE 2005   187 - 192   2006

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    TAM (Topographic Attentive Mapping) network is a biologically-motivated neural network. In this paper, we define the Gabor function type receptive field and incorporate it to the TAM network's feature layer. We also discuss the orientation selectivity of the receptive field through some examples of character recognition. © 2006 Springer-Verlag Berlin Heidelberg.

    DOI: 10.1007/3-540-29344-2_28

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  • Operation of network dynamics in cultured hippocampal neurons on a multi-electrode array Reviewed

    Sugufu N. Kudoh, Isao hayashi, Ai Kiyohara, Takahisa Taguchi

    2006 IEEE INTERNATIONAL SYMPOSIUM ON MICRO-NANOMECHATRONICS AND HUMAN SCIENCE   423 - +   2006

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    Neurons reorganized complex networks on a culture dish and it seems that the living neuronal network can perform certain type of information processing. We showed that dissociated rat hippocampal neurons on a multielectrode array dish formed heterogeneous networks of functional connections. We estimated the functional connections of all combinations of pairs of neurons on the electrodes and represented them into a ''connection map". The connection map revealed that each culture contained some hub-like neurons with many functional connections. This cultured neuronal network has unique functional structures which are suitable for perform information processing and the network can re-organize functional connections between neurons in the network. So, it seems that the system can perform some intelligent behavior. We are developing the living brain robot system with premised rules which are corresponding to genetically provided interface of neural network to peripheral system. The premised rules are described by fuzzy logic and they play a role to generate instinctive behavior. The robot can avoid collision by sensor inputs from robot body to neuronal networks, and by output command from the network to motors of the robot. Now we are analyzing the change of connection map moderated by the interaction to outer world via moving robot.

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  • Structure evaluation of receptive field layer in TAM network Reviewed

    Isao Hayashi, Toshiyuki Maeda

    2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS   1541 - +   2006

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    TAM (Topographic Attentive Mapping) network is a biologically- motivated neural network with receptive fields of Gabor function. However, the receptive field's layer is monotype, and there is a lack of performance for rotating visual images. In this paper, we formulate four TAM networks with multilayer structure of extensive receptive fields. We discuss their performance and show the usefulness of TAM network using some examples of character recognition.

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  • A Proposal of TAM Network with Gabor Type Receptive Field Reviewed

    Isao Hayashi, James R. Williamson

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   18, 3, 434-442   2006

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  • Orientation selectivity of TAM network with extensive receptive field Reviewed

    Isao Hayashi, James R. Williamson

    INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MODELLING, CONTROL & AUTOMATION JOINTLY WITH INTERNATIONAL CONFERENCE ON INTELLIGENT AGENTS, WEB TECHNOLOGIES & INTERNET COMMERCE, VOL 1, PROCEEDINGS   1184 - +   2006

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    TAM (Topographic Attentive Mapping) network is a biologically-motivated neural network with Gabor function type receptive fields. However, the structure of receptive fields is a mono-layer, and there is a lack of performance for rotating images. In this paper, we formulate a new TAM network with multilayer structure of extensive receptive fields. We also show the usefulness of TAM network using some examples of character recognition.

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  • A Proposal of Pruning Method for TAM Network Reviewed

    Isao Hayashi, James R. Willia

    Transactions of the Institute of Systems, Control and Information Engineers   17, 2, 81-88 ( 2 )   81 - 88   2004

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  • ID3獲得知識を用いた無線LANアクセスポイント適正配置

    林 勲

    阪南大学情報科学研究   Vo.17, pp.48-62 ( 17 )   48 - 62   2003.3

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  • ネットワーク通信におけるファジィ情報からの位置決定アルゴリズム

    林 勲

    福山平成大学経営学部紀要   Vo.7 125頁~141頁   2002.4

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  • TAM Networkによるファジィルール獲得

    林 勲

    阪南大学情報科学研究   Vo.16, pp.22-33 ( 16 )   22 - 33   2002.3

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  • A Proposal of Fuzzy ID3 with Tuning Ability for AND Connectives

    Isao Hayashi

    Japanese Journal of Fuzzy Theory and Systems,   Vol.11, No.4, pp.431-441   2001.8

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  • 自然言語インターフェイスによるファジィ空間推論システムの提案

    林 勲

    福山平成大学経営学部紀要   Vo.6 pp.105-113   2001.4

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  • 自然言語記述における挙動のスケーラビリティ

    林 勲

    福山平成大学経営学部紀要   Vo.5, pp.115-124   2000.4

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  • A Behavior Decision System of Autonomous Agents Using Natural Language Description Reviewed

    Toshiyuki Maeda, Isao Hayashi, Motohide Umano, Lakhmi C. Jain

    International Journal of Knowledge-Based Intelligent Engineering Systems   Vol.3, No.4, pp.223-229   1999.8

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  • A Proposal of Fuzzy ID3 with Ability of Learning for AND Connectives Reviewed

    HAYASHI Isao

    pp.677-682   1999

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Books

  • Research for Supporting Tactical Analysis Concerning Pass Skeleton in American Football

    Chihiro Tanaka, Yuhei Yamamoto, Wenyuan Jiang, Shigenori Tanaka, Isao Hayashi, Kenji Nakamura, Shinsuke Nakajima( Role: Joint author)

    Image Laboratory  2022.3 

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  • Artificial Intelligence and Transdisciplinary Sciene and Technology

    Hiroshi Takahashi, Shusaku Tsumoto, Fujio Tsutsumi, Yutaka Matsuo, Satoshi Kurihara, Genshiro Kitagawa, Tetsuo Sawaragi, Isao Hayashi( Role: Joint author)

    Journal of Oukan  2021.3 

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  • Possibility of AI Table Tennis Based on Data Science

    Isao Hayashi, Honoka irie, Yuki Sekiya, Masamune Nakayama, Tetsushi Yase

    Journal of TOKEI, Japan Statistical Association  2020.6 

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  • 松下電器から生まれたファジィ家電,ニューロ・ファジィ家電

    藤原 義博, 若見 昇, 林 勲( Role: Joint author)

    知能と情報  2018.2 

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  • A Status Report of Campus Cloud Computing Services

    Hiroyuki Ebara, Isao Hayashi, Kazuhiro Kono, Tohru Kondo, Shinya Mizuno( Role: Joint author)

    2016.8 

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  • A Measure of Localization of Brain Activity for the Motion Aperture Problem Using Electroencephalograms, Developing and Applying Biologically‐Inspired Vision Systems: Interdisciplinary Concepts, M.Pomplun and J.Suzuki eds. Reviewed

    Isao Hayashi, Atsushi Moritaka, Hisashi Toyoshima, Takahiro Yamanoi( Role: Joint author)

    IGI Global  2012.11 

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  • 脳に宿る心 -認知科学・人工知能から神秘の世界に迫る-

    林 勲( Role: Sole author)

    知能と情報「書評」  2010.8 

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  • Report No.0906 of International Institute for Advanced Studies "Skill and Organization," Embodimemt of Living Neuronal Networks: A Robot Connected to Cultured Neuronal Networks Reviewed

    Isao Hayashi, Suguru N Kudoh( Role: Joint author)

    International Institute for Advanced Studies  2010.3 

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  • Passive BCI

    Isao Hayashi( Role: Sole author)

    2009.2 

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  • Neuron and Synaptic Plasticity

    Suguru N. Kudoh, Isao Hayashi, Takahisa Taguchi( Role: Joint author)

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics  2006 

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  • Proceedings of the 3rd International Symposium on Autonomous Minirobots for Research and Edutainment (AMiRE2005), A Study of Orientation Selectivity of TAM Network Incorporated Receptive Field Structure Reviewed

    HAYASHI Isao( Role: Joint author)

    Physica-Verlag/A Springer-Verlag Company  2005.9 

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  • Hybrid Information Systems: series in Advances in Soft Computing, An Integration of Fuzzy and Two-valued Logics on Natural Language Semantics Reviewed

    Isao Hayashi( Role: Joint author)

    Physica-Verlag/A Springer-Verlag Company  2001.12 

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  • ファジィとソフトコンピューティングハンドブック 第6.3節「ファジィGMDH」

    林 勲, 分担執筆, ハンドブック

    共立出版  2000.9 

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  • ファジィとソフトコンピューティングハンドブック第6.3節「ファジィGMDH」

    林 勲 分担執筆(ハンドブック)

    共立出版  2000.9 

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  • 人工知能-新世代工学シリーズ-第5章「ファジィ・ニューラルネット・遺伝的アルゴリズム」

    林 勲( Role: Joint author)

    オーム社  2000.6 

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  • 人工知能-新世代工学シリーズ- 第5章「ファジィ・ニューラルネット・遺伝的アルゴリズム」

    林 勲( Role: Joint author)

    オーム社  2000.6 

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MISC

  • Molecular Communication

    Isao Hayashi, Takashi Nakano

    Vol.30, No.3, p.158   2018.6

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  • 第15期会長に就任して ~情報シームレス化のすすめ~

    林 勲

    知能と情報   Vol.30, No.1, p.2 (2018)   2018.2

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  • 追悼Zadeh(ザデー)先生を偲んで

    林 勲

    知能と情報   Vol.29, No.6, pp.196-197 (2017)   2017.12

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  • ファジィ集合論からニューロ・ファジィへ

    林 勲

    知能と情報   Vol.29, No.6, p.202 (2017)   2017.12

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  • Science for Losing Interest

    Isao Hayashi

    Vol.28, No.3, p.63 (2016)   2016.6

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  • 『継ぐ前へ』を継承して

    林 勲

    ニッタクニュース   No.748, p.55   2016.1

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  • 理事会だより

    林 勲

    知能と情報   Vol.26, No.4, p.154   2014.8

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  • 理事会だより

    林 勲

    知能と情報   Vol.26, No.4, p.154   2014.8

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  • 理事会だより

    林 勲

    知能と情報   Vol.26, No.4, p.154   2014.8

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  • A Proposal of Analysis with Connectivity and Logicality in Cultured Neuronal Network

    林 勲, 満元 弘毅, 工藤 卓

    ファジィシステムシンポジウム講演論文集   29   189 - 192   2013.9

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  • A Method for Evaluating Gait Disturbance of Evacuees in Disasters Using Singular Value Decomposition

    27   625 - 630   2011.9

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  • Analysis of Action Potentials of Cultured Neuronal Network Using Fuzzy Operator

    Hayashi Isao, Kiyotoki Megumi, Kiyohara Ai, Taguchi Takahisa, Kudoh Suguru N

    Proceedings of the Fuzzy System Symposium   25 ( 0 )   25 - 25   2009

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    Recently, BCI(Brain computer interface) has been come into the research limelight. We have been investigating action potentials of rat hippocampal neurons cultured on a dish with 64 micro planer electrodes. However, we don't exactly comprehend logicality in micro planer electrodes. In this paper, we analyze logicality in three electrodes using fuzzy operator consisting of t-norm operator and t-conorm operator, and discuss logicality in cultured neuronal network.

    DOI: 10.14864/fss.25.0.25.0

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  • A Consideration on Sport Skill Evaluation Using Motion Analysis Model by Neural Network

    24   297 - 302   2008.9

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  • Vitroid as a test tube-in vitro learning in neuro-robot system.

    工藤卓, 徳田農, 清原藍, 清原藍, 細川千絵, 林勲, 田口隆久, 田口隆久

    生体・生理工学シンポジウム論文集   23rd   2008

  • In vitro learning in neuro-robot system.

    Kudoh Suguru N, Tokuda Minori, Kiyohara Ai, Taguchi Takahisa, Hayashi Isao

    Proceedings of the Fuzzy System Symposium   24 ( 0 )   44 - 44   2008

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    Rat hippocampal neurons were cultured on a dish with 64 micro planer electrodes. A complexnetwork of neurons was formed and the network was able to distinguish patterns of action potentials evokedby different electrical current inputs. We integrated a living neuronal network and a Khepera II robot orrobot made by LEGO mindstorm NX kit as a body for contacting to outside world. Using self-tuning fuzzyreasoning, we associated a distinct spatial pattern of evoked action potentials with a particular phenomenonin the outside of the culture dish. We succeeded in performing collision avoidance behaviour with premisedcontrol rule sets. During collision avoidance, the responding pattern of evoked action potentials was stableand robust against perturbation to spontaneous network activity. These results suggest that a culturedneuronal network can represent particular states as symbols corresponding to outside world.

    DOI: 10.14864/fss.24.0.44.0

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  • Recognition of outer world performed by dissociated neurons.

    清原藍, 清原藍, 工藤卓, 徳田農, 細川千絵, 田口隆久, 林勲

    インテリジェント・システム・シンポジウム講演論文集   17th   2007

  • Biomodeling System: Analysis of Aadaptive Learning in Cultured Neuronal Network Using Fuzzy Logic

    Hayashi Isao, Tokuda Minori, Kiyohara Ai, Taguchi Takahisa, Kudoh N. Suguru

    Proceedings of the Fuzzy System Symposium   23 ( 0 )   565 - 565   2007

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    We have already proposed "biomodeling system", in which the "top-down bio-processing" for sending actuator signals to robot from living neuronal network cultured on a 2-dimensional electrode arrays, and the "bottom-up robot-processing" for electrical stimulation to living neuronalnetwork from robot are connected between neuronal network and robot. In this paper, we discuss two kinds of learning mechanism, which are plasticity learning of living neural network and adaptability learning of fuzzy logic using the tracking estimation of Khepera II in a straight lane.Our goal is reconstruction of the neuronal network, which can process "thinking" in the dissociated culture system.

    DOI: 10.14864/fss.23.0.565.0

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  • Biologically Inspired Model:脳神経・知覚・ロボティクスによるハイブリッドシステムを目指して

    林勲, 山ノ井高洋, 工藤卓

    インテリジェント・システム・シンポジウム講演論文集   17th   2007

  • Neuron and synaptic plasticity

    KUDOH Suguru N, HAYASHI Isao, TAGUCHI Takahisa

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   18 ( 3 )   362 - 368   2006.6

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    シナプスは神経細胞間の情報伝達端子であり,シナプス伝達効率の可塑的な変化は脳における情報処理の実体である.細胞内情報伝達系の主要なメッセンジャーであるCaイオンは,シナプス可塑性の発現に重要な役割を果たし,最終的に神経伝達物質受容体分子の電気化学的特性と分子数の制御によって,あるいは神経伝達物質の放出機構の制御によって,シナプス伝達効率が調整されている.また,シナプスは細胞内分子ネットワークと神経細胞ネットワークという階層間の相互作用の場ともなっており,こうした階層性が,柔軟性とロバスト性を併せ持った,生物特有の優れた情報処理特性の源泉ではないかと考えている.

    DOI: 10.3156/jsoft.18.3_362

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  • A Biomodeling System by Cultured Neuronal Network of Rat Hippocampus Connected to Moving Robot

    Hayashi Isao, Taguchi Takahisa, Kudoh Suguru N

    Proceedings of the Fuzzy System Symposium   22 ( 0 )   137 - 137   2006

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    Language:Japanese   Publisher:Japan Society for Fuzzy Theory and Intelligent Informatics  

    The patterns of spontaneous action potentials are analyzed using the multi-site recording system for the living neuronal networks cultured on a 2-dimensional electrode arrays. In this paper, we constructed ``biomodeling system'' for Khepera II robot and living neuronal network through fuzzy logic. Our goal is reconstruction of the neuronal network, which can process ``thinking'' in the dissociated culture system.

    DOI: 10.14864/fss.22.0.137.0

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Presentations

  • Evaluation of Bagging-type Ensemble Method Generating Virtual Data

    Honoka Irie, Isao Hayashi

    Proc. of the 20th World Congress of the International Fuzzy Systems Association (IFSA2023)  2023.8 

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    Language:English   Presentation type:Oral presentation (general)  

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  • Harmonized Fitness: Research Results on Health Smart Network with Ensemble of Exercise and Music

    Isao Hayashi, Michiyuki Hirokane, Yukio Horiguchi, Masataka Tokumaru, Arash Yazdanbakhsh

    Proc. of the 39th Fuzzy System Symposium, Japan Society for Fuzzy Theory and Intelligent Informatics  2023.9 

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  • A Proposal of Directional Virtual Data in pdi-BoostingG

    Honoka Irie, Isao Hayashi

    Proc. of the 39th Fuzzy System Symposium, Japan Society for Fuzzy Theory and Intelligent Informatics  2023.9 

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  • Influence of Number of Virtual Data Generated in pdi-Bagging

    Honoka Irie, Tadashi Nakano, Isao Hayashi

    2023.4 

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  • Acquisition of Ball Trajectory and Tactics in Table Tennis from Broadcast Video

    Isao Hayashi, Honoka Irie, Feng Yangyun, Kazuto Yoshida, Miran Kondric

    2023.4 

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  • AIデータサイエンスから視るしなやかな意思決定

    林 勲, 入江 穂乃香

    2023.3 

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  • pdi-Bagging: A Proposal of Bagging-type Ensemble Method Generating Virtual Data

    Honoka Irie, Isao Hayashi

    2023.2 

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  • 卓球放送映像でのボール軌道追跡のためのオクルージョン処理の提案

    馮 楊蘊, 入江 穂乃香, 林 勲

    2023.1 

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  • Harmonized Fitness: Introduction of Research Topics on Health Smart Network with Ensemble of Exercise and Music

    Isao Hayashi, Michiyuki Hirokane, Yukio Horiguchi, Masataka Tokumaru, Arash Yazdanbakhsh

    Proc. of the 38th Fuzzy System Symposium, Japan Society for Fuzzy Theory and Intelligent Informatics  2022.9 

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  • Occlusion Solution and its Evaluation for Ball Trajectory Estimation Acquired from Broadcast Video of Table Tennis

    Feng Yangyun, Honoka Irie, Isao Hayashi

    Proc. of the 38th Fuzzy System Symposium, Japan Society for Fuzzy Theory and Intelligent Informatics  2022.9 

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  • A Proposal of Ensemble Learning "pdi-BoostingG" and its Evaluation

    Honoka Irie, Isao Hayashi

    Proc. of the 38th Fuzzy System Symposium, Japan Society for Fuzzy Theory and Intelligent Informatics  2022.9 

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  • In-Patient Fall Prevention: Approaches in Data Science vs Empirical Management

    Atsushi Inoue, Eiichiro Ueda, Takeo Hata, Isao Hayashi, Yukio Horiguchi, Hiroharu Kawanaka, Chintaka Premachandra

    NursingCongress2022  2022.9 

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  • 放送映像からの卓球ボール軌道の検出とラリー軌跡の可視化

    馮 楊蘊, 入江 穂乃香, 林 勲

    2022.1 

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  • アンサンブル型機械学習を用いた画像不均衡データでの車種識別法の提案

    入江 穂乃香, 林 勲, 堅多 達也

    2022.1 

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  • データの不均衡を回避ししなやかな知識を獲得するアンサンブル機械学習

    林 勲, 入江 穂乃香

    2022.1 

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  • Tactics Knowledge Representation Based on Ball Trajectory Acquired from Broadcast Video of Table Tennis by Deep Learning

    Isao Hayashi, Yangyun Feng, Honoka Irie

    2021.12 

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  • Vehicle Type Discrimination in Large-scale Outdoor Parking Lot Using pdi-Bagging

    Honoka Irie, Isao Hayashi, Tatsuya Katada

    2021.9 

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  • Harmonized Fitness: Health Smart Network with Ensemble of Exercise and Music

    Isao Hayashi, Michiyuki Hirokane, Yukio Horiguchi, Masataka Tokumaru, Arash Yazdanbakhsh

    2021.9 

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  • A Proposal of Ensemble Learning "pdi-Boosting" Inheriting Virtual Data and Fuzzy Rules

    Honoka Irie, Isao Hayashi

    2021.9 

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  • AIの活用現場

    林 勲

    2021.6 

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  • 人を育てるAI卓球

    林 勲

    2020.12 

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  • Trajectory Tracking Method for Table Tennis from Broadcast Video

    Isao Hayashi, Yuki Sekiya, Honoka Irie, Masaki Ogino

    2020.9 

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  • ファジィAIで人を育てる卓球ロボットの開発

    林 勲

    2020.8 

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  • Proposal of Class Determination Method for Generated Virtual Data in pdi-Bagging

    Honoka Irie, Isao Hayashi

    2020.6 

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  • Ensemble Learning to Generate Virtual Data for Pattern Recognition and Its Possibility of Application to Strategy Inference in Table Tennis

    Isao Hayashi, Honoka Irie

    Proc. of the 23th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2019)  2019.12 

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  • 日本知能情報ファジィ学会と横幹知

    林 勲

    第10回横幹連合コンファレンス講演論文集,パネル討論「人工知能と横幹知」  2019.11 

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  • Performance Evaluation of pdi-Bagging by Generation of Correct-Error Virtual Data

    Honoka Irie, Isao Hayashi

    Proc. of the 29th Symposium on Fuzzy, Artificial Intelligence, Neural Networks and Computational Intelligence  2019.9 

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  • AI Coach: Learning Table Tennis Strategy Rules from Video

    Isao Hayashi, Masaki Ogino, Honoka Irie, Sho Tamaki, Kazuto Yoshida, Miran Kondric

    Proc. of the 16th International Table Tennis Federation (ITTF) Sports Science Congress (ITTF-SSC2019)  2019.4 

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  • 動作における脳内切り替え機能学習性とスポーツ習熟性

    林 勲, 入江 穂乃香

    日本知能情報ファジィ学会第1回動きの様相から先を読む研究会  2019.3 

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  • 卓球研究とAI

    林 勲

    ITS三鷹第6回「荻村さんの夢」展  2018.12 

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  • 卓球戦略ボードプロジェクト(AIコーチ)

    林 勲

    ハイパフォーマンススポーツカンファレンス(HPC2018)プレセミナー  2018.10 

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  • Development of Image Processing System to Realize Table Tennis Strategy Board

    Isao Hayashi, Masaki Ogino, Honoka Irie, Sho Tamaki, Kazuto Yoshida, Miran Kondric

    Proc. of Japan Table Tennis Association Sports Science and Medicine Committee International Meeting 2018 (JTTA-SSMC2018)  2018.9 

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  • Research for Visualization System and Match-up Analysis of Pass play in American Football

    Chihiro Tanaka, Yuhei Yamamoto, Wenyuan Jiang, Kenji Nakamura, Shigenori Tanaka, Isao Hayashi

    Proc. of the 34st Fuzzy System Symposium  2018.9 

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  • Characterization of Hyperparameter of Learning Type Trapezoidal Fuzzy Inference

    Honoka Irie, Isao Hayashi

    Proc. of the 34st Fuzzy System Symposium  2018.9 

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  • U-NetによるCT画像における脊椎の自動検出

    鎌田 理詩, 菊池 眞之, 庄野 逸, 林 勲, 福島 邦彦

    電子情報通信学会ニューロコンピューティング (NC) 研究会発表論文集  2018.3 

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  • Automatic detection of spine in CT image by U-Net

    Mikoto Kamata, Kunihiko Fukushima, Hayaru Shouno, Isao Hayashi, Masayuki Kikuchi

    Proc. of the 2018 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP`18)  2018.3 

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  • しなやかな判断のためのデータ解析モデル

    林 勲

    第22回関西大学先端科学技術推進機構先端科学技術シンポジウム講演集  2018.1 

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  • データからモデルを眺める:しなやかな行動・判断のデータ解析法とスポーツ情報学

    林 勲

    第19 回日本知能情報ファジィ学会九州支部学術講演会予稿集  2017.12 

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  • Monitoring of Respiratory Cycles Utilizing Sensors on Sleeping Mat

    Douglas E. Dow, Yukio Horiguchi, Yoshiki Hirai, Isao Hayashi

    Proc. of the ASME 2017 International Mechanical Engineering Congress and Exposition (IMECE2017)  2017.11 

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  • Data Science of "Shinayakana" Decision on Advanced Computational Intelligence

    Isao Hayashi

    Proc. of the 5th International Workshop on Frontier of Science and Technology (FST2017) and the 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII2017)  2017.11 

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  • Importance of Shoulder in Playing Table Tennis: Skill Visualization Using Fuzzy Rules Acquired by TAM Network

    Isao Hayashi, Honoka Irie, Toshiyuki Maeda, Masanori Fujii, Tokio Tasaka

    Proc. of Japan Table Tennis Association Sports Science and Medicine Committee International Meeting 2017 (JTTA-SSMC2017)  2017.9 

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  • Fuzzy Set Training for Sleep Apnea Classification

    Douglas E. Dow, Isao Hayashi

    Proc. of the Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS2017)  2017.6 

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  • Visualization of table tennis skill by neural networks and fuzzy inference

    Isao Hayashi, Honoka Irie, Toshiyuki Maeda, Masanori Fujii, Tokio Tasaka

    Proc. of the 15th International Table Tennis Federation (ITTF) Sports Science Congress (ITTF-SSC2017)  2017.5 

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  • Data Science of "Shinayakana" Decision on Technical Marketing

    Isao Hayashi

    Special Talking of Department of Information and Communication Engineering, Kyungnam University  2017.4 

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  • Fuzzy Logic Training for Predicting Age of Rats

    Isao Hayashi

    Proc. of the 10th International Conference on Bio-Inspired Information and Communications Technologies (BICT2017)  2017.3 

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  • 脳工学におけるしなやかな判断のデータサイエンス

    林 勲

    日本機械学会バイオロボティクス研究会講演会,第20回日本知能情報ファジィ学会しなやかな行動の脳工学研究部会研究会,関西学院大学「私立大学戦略的研究基盤形成支援事業」  2017.3 

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  • しなやか判断のデータサイエンス

    林 勲

    近畿大学大学院商学研究科FD研修会  2017.2 

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  • しなやかな判断のデータサイエンス

    林 勲

    近畿大学大学院商学研究科FD研修会  2017.2 

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  • Visualization and Acquisition of Knowledge of Table Tennis Skill by Visual Neural Networks

    Isao Hayashi, Masanori Fujii, Toshiyuki Maeda, Tokio Tasaka

    Proc. of the 71st Annual Meeting of the Japanese Society of Physical Fitness and Sports Medicine  2016.9 

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  • Visualization and Acquisition of Knowledge of Table Tennis Skill by Visual Neural Networks

    Isao Hayashi, Masanori Fujii, Toshiyuki Maeda, Tokio Tasaka

    2016.9 

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  • An Analysis for Switching of Feedback and Feedforward Mechanism in Motor Internal Model

    Isao Hayashi, Sayaka Kita, Masaki Ogino, Jasmin Leveille

    Proc. of the 8th International Conference on Soft Computing and Intelligent Systems and the 17th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2016)  2016.8 

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  • Diagnosis of Axial Force of High-strength Bolts for Vibration Frequency Data Using Pattern Recognition

    Yoshiki Tsuji, Michiyuki Hirokane, Isao Hayashi, Hideyuki Konishi

    Proc. of the Safety Engineering Symposium 2016  2016.6 

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  • Recognition for Switching of Feedback and Feedforward Process in Motor Internal Model

    Isao Hayashi, Masaki Ogino, Sayaka Kita, Jasmin Leveille

    Proc. of the 9th International Conference on Bio-Inspired Information and Communications Technologies (BICT2015)  2015.12 

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  • A Proposal of Permutation Data Structure Method for Sequential Learning Type Classifier in Brain Computer Interface

    Isao Hayashi, Hatsumi Miyauchi

    Proc. of the 31st Fuzzy System Symposium  2015.9 

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  • A Representation of Skill Knowledge of Table Tennis by Neural Network

    Isao Hayashi, Toshiyuki Maeda, Masanori Fujii, Tokio Tasaka

    Proc. of the 14th ITTF Sports Science Congress and the 5th World Racquet Sports Congress (ITTFSSC2015)  2015.4 

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  • 脳認知ロボティックスによる橋梁診断スキームの構築

    林 勲, 古田 均, 広兼 道幸, 荻野 正樹

    研究拠点形成支援経費成果報告書  2014.12 

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  • Extraction of Attributes and Knowledge Rules for Sport Skill by TAM Network

    Isao Hayashi, Toshiyuki Maeda, Masanori Fujii, Tokio Tasaka

    Proc. of the 7th International Conference on Soft Computing and Intelligent Systems and the 15th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2014)  2014.12 

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  • A Proposal of Adaboost Type TAM Network and Its Application to Sport Skill Analysis

    Isao Hayashi, Masanori Fujii, Toshiyuki Maeda, Tokio Tasaka

    Proc. of the 8th International Conference on Bio-Inspired Information and Communications Technologies (BICT2014)  2014.12 

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  • Improvement of Concentration of Numeracy by Mozart Effect

    Isao Hayashi, Masaki Ogino, Masao Horie, Ayami Yatsuzuka, Jasmin Leveille

    Proc. of the 8th International Conference on Bio-Inspired Information and Communications Technologies (BICT2014)  2014.12 

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  • A Software Suite for Large-scale Video- and Image-Based Analytics

    Jasmin Leveille, Isao Hayashi

    Proc. of the 8th International Conference on Bio-Inspired Information and Communications Technologies (BICT2014)  2014.12 

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  • SVD-based Feature Extraction from Time-series Motion Data and Its Application to Gesture Recognition

    Isao Hayashi, Shuoyu Wang, Yinlai Jiang

    Proc. of the 8th International Conference on Bio-Inspired Information and Communications Technologies (BICT2014)  2014.12 

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  • Sport Skill Classification Using Time Series Motion Picture Data

    Toshiyuki Maeda, Masanori Fujii, Isao Hayashi, Tokio Tasaka

    Proc. of the 40th Annual Conference of the IEEE Industrial Electronics Society (IECON2014)  2014.10 

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  • Recognition of Feedforward Change of Motor Internal Model

    Isao Hayashi, Sayaka Kita, Masaki Ogino

    Proc. of the 30th Fuzzy System Symposium  2014.9 

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  • Description of Activity of Living Neuronal Network by Fuzzy Bio-Indicator

    Isao Hayashi, Suguru N. Kudoh

    Proc. of 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2014)  2014.7 

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  • Analysis and Extraction of Knowledge from Body Motion Using Singular Value Decomposition

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    Proc. of 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2014)  2014.7 

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  • 周波数分割と脳波計測によるモーツアルト効果の分析

    林 勲, 堀江 政生

    日本知能情報ファジィ学会 第106回関西支部例会  2014.3 

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  • Evaluation of Rehabilitation Condition in Walk Training by Acceleration Measurement

    Ryosuke Yuzawa, Shuoyu Wang, Yinlai Jiang, Isao Hayashi

    Proc. of the 2013 Conference on Technical Division of Systems and Information of the Society of Instrument and Control Engineers (ISIS2013)  2013.11 

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  • Fuzzy Bio-Indicator: Evaluation of Logicality and Connectivity for Living Neuronal Network

    Isao Hayashi, Koki Mitsumoto, Suguru N. Kudoh

    Proc. of the 8th International Conference on Body Area Networks (BodyNets2013)  2013.10 

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  • An Analysis of Mozart's Effect with Filtering of Low Range and High Range

    Isao Hayashi, Shrestha Satish, Masao Horie, Ayami Yatsuzuka, Jasmin Leveille

    Proc. of the 29th Fuzzy System Symposium  2013.9 

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  • A Proposal of Analysis with Connectivity and Logicality in Cultured Neuronal Network

    Isao Hayashi, Koki Mitsumoto, Suguru N. Kudoh

    Proc. of the 29th Fuzzy System Symposium  2013.9 

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  • Singular Value Analysis through Divided Time-Series Data and its Application to Walking Difficulty Evaluation

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    Proc. of 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2013)  2013.7 

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  • An Adaptive Ensemble Model for Brain-Computer Interfaces

    Isao Hayashi, Shinji Tsuruse

    Proc. of 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2013)  2013.7 

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  • Three-staged Neocognitron: Optimal Thereshold and Thinning-out of Cells

    Chihiro Yamamoto, Isao Hayashi, Kunihiko Fukushima

    The Institute of Electronics, Information and Communication Engineers  2013.3 

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  • Instruction of Emotion Using Brain Activity: Collaborative Learning Type BCI between Human and Reinforcement Learning

    Ayumi Tanaka, Masaki Ogino, Isao Hayashi

    Proc. of Human-Agent Interaction Symposium 2012  2012.12 

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  • A Characterization of Collaborative Learning Type BCI Using Reinforcement Learning

    Isao Hayashi

    Proc. of Human-Agent Interaction Symposium 2012  2012.12 

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  • Evaluation and Visualizaton of Evacuees' Walking Difficulty in Disasters

    Isao Hayashi, Yinlai Jiang, Shuoyu Wang

    Japan Society for Fuzzy Theory and Intelligent Informatics  2012.11 

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    Venue:Kobe  

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  • Neurorobot Vitroid - A Living Test Model for Embodiment Brain Research

    Suguru N. Kudoh, Isao Hayashi

    Japan Society for Fuzzy Theory and Intelligent Informatics  2012.11 

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    Venue:Kobe  

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  • An Evaluation of pdi-Boosting for Brain-Computer Interfaces

    Isao Hayashi, Shinji Tsuruse

    Japan Society for Fuzzy Theory and Intelligent Informatics  2012.11 

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    Venue:Kobe  

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  • Online Learning of Feature Detectors from Natural Images with Probabilistic WKL Rule

    Jasmin L´eveill´e, Isao Hayashi, Kunihiko Fukushima

    Japan Society for Fuzzy Theory and Intelligent Informatics  2012.11 

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    Venue:Kobe  

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  • 特異値分解による身体動作の特徴表現

    林 勲, 姜 銀来, 王 碩玉

    人工知能学会  2012.9 

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  • Evaluation of Walking Difficulty Using Singular Value Analysis through Divided Time-Series Data

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    Japan Society for Fuzzy Theory and Intelligent Informatics  2012.9 

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  • An Efficiency of Boosting Algorithm by Probabilistic Data Interpolation for Brain-Computer Interface

    Isao Hayashi, Shinji Tsuruse

    Japan Society for Fuzzy Theory and Intelligent Informatics  2012.9 

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  • Leveraging Indicator-based Ensemble Selection in Evolutionary Multiobjective Optimization Algorithms

    Dung H. Phan, Junichi Suzuki, Isao Hayashi

    Proc. of Genetic and Evolutionary Computation Conference (GECCO2012), Recombination of 21st International Conference on Genetic Algorithms (ICGA) and 17th Annual Genetic Programming Conference (GP)  2012.7 

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  • 知能・情報・ファジィの研究 - 過去・現在・未来に向けて -

    林 勲

    日本知能情報ファジィ学会,第100回記念例会関西支部例会記念パネルディスカッション  2012.7 

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  • A Proposal for Applying pdi-Boosting to Brain-Computer Interfaces

    Isao Hayashi, Shinji Tsuruse, Junichi Suzuki, Robert Thijs Kozma

    Proc. of 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2012) in 2012 IEEE World Congress on Computational Intelligence (WCCI2012)  2012.6 

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  • Quantitative Evaluation of Walking Disability Using Singular Value Decomposition

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    Proc. of 2012 Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012)  2012.5 

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  • Visual Evaluation of Gesture Motion and Walking Difficulty Using Singular Value Decomposition

    Isao Hayashi, Yinlai Jiang, Shuoyu Wang

    Proc. of the 12th Annual Meeting of Vision Sciences Society (VSS2012)  2012.5 

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  • BIBEA: Boosted Indicator Based Evolutionary Algorithm for Multiobjective Optimization

    Dung H. Phan, Junichi Suzuki, Isao Hayashi

    Proc. of the 15th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2011)  2011.12 

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  • Quantitative Assessment of Fall-Limping by Acceleration Analysis Using Singular Value Decomposition

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang, Kenji Ishida

    Proc. of International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII2011)  2011.11 

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  • あいまいさがどう役立つか - ファジィ推論の基礎および身体知の活用法 -

    林 勲

    日本知能情報ファジィ学会,第4回関西支部ソフトコンピューティング企業セミナー,滋賀県ものづくりIT研究会ビジネスセミナー「ファジィ技術で競争力アップ」  2011.11 

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  • Neocognitron Trained by Winner-Kill-Loser with Triple Threshold

    Kunihiko Fukushima, Isao Hayashi, Jasmin L´eveill´e

    Proc. of 2011 International Conference on Neural Information Processing (ICONIP2011)  2011.11 

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  • Analysis of the Types of Corporate Culture Using Fuzzy ID3

    Jong-Dai Gi, Seung-Gook Hwang, Bong-Gyeong Park, Jignesh Panchal, Isao Hayashi

    Proc. of 12th International Symposium on Advanced Intelligent Systems (ISIS2011)  2011.9 

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  • A Method for Evaluating Gait Disturbance of Evacuees in Disasters Using Singular Value Decomposition

    Yinlai Jiang, Isao Hayashi, Shuoyu Wang

    Proc. of the 27th Fuzzy System Symposium  2011.9 

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  • Online Competitive Incremental-decremental Clustering with the Winner-Kill-Loser Rule

    Jasmin L´eveill´e, Isao Hayashi, Kunihiko Fukushima, Massimiliano Versace

    Proc. of the Annual Meeting of Neuroinformatics (INCF2011)  2011.9 

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  • Fuzzy Bio-Interface: Indicating Logicality from Living Neuronal Network and Learning Control of Bio-Robot

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    Proc. of the International Joint Conference on Neural Networks (IJCNN2011)  2011.8 

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  • Toward Time-Sensitive Structure Analysis for SPAM Filtering: A Data Mining Approach

    Atsushi Inoue, Isao Hayashi, Toshiyuki Maeda, Yoshinori Arai, Takashi Kobayashi

    Proc. of World Conference on Soft Computing (WConSC2011)  2011.5 

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  • Fuzzy Bio-Interface: Logicality of Living Neuronal Network and Control of Fuzzy Bio-Robot System

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    Proc. of World Conference on Soft Computing (WConSC2011)  2011.5 

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  • In Vitro Logicality for Neuro-Robot Hybrid

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    Proc. of the fifteenth International Conference on Cognitive and Neural Systems (ICCNS2011)  2011.5 

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  • A Measure of Localization of Brain Activity for the Motion Aperture Problem Using Electroencephalograms

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    Proc. of the 11th Annual Meeting of Vision Sciences Society (VSS2011)  2011.5 

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  • Fuzzy Bio-interface: Can fuzzy set be an interface with brain?

    Isao Hayashi, Suguru N. Kudoh

    Proc. of the 22nd Midwest Artificial Intelligence and Cognitive Science Conference (MAICS2011)  2011.4 

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  • Embodied Knowledge of Gesture Motion Acquired by Singular Spectrum Analysis

    Isao Hayashi, Yinlai Jiang, Shuoyu Wang

    Proc. of the First International Conference on Vulnerability and Risk Analysis and Management (ICVRAM2011) and the Fifth International Symposium on Uncertainty Modeling and Analysis (ISUMA2011)  2011.4 

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  • Introduction of My Research: motion feature extraction and TAM network

    Isao Hayashi

    Vision Club, Department of Cognitive and Neural Systems, Boston University  2010.12 

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  • Introduction of My Research: logicality of living neural networks and bio-robot

    Isao Hayashi

    Vision Laboratory, Department of Cognitive and Neural Systems, Boston University  2010.11 

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  • Pattern Analysis of Core Competency of CEO Using Fuzzy ID3

    Bong-Gyeong Park, Seung-Gook Hwang, Jignesh Panchal, Isao Hayashi

    Proc. of Asian Network for Quality (ANQ) Congress 2010  2010.10 

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  • Application of TAM Network to Integrity Assessment of Concrete Slabs

    Kenta Tanaka, Takashi Miyaguchi, Michiyuki Hirokane, Isao Hayashi

    Proc. of the 26th Fuzzy System Symposium  2010.9 

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  • A Proposal of Boosting Algorithm by Probabilistic Data Interpolation for Brain-Computer Interface

    Isao Hayashi, Shinji Tsuruse

    Proc. of the 26th Fuzzy System Symposium  2010.9 

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  • An Analysis of Usefulness of Collaborative Learning Using Reinforcement Learning in BCI

    Isao Hayashi, Kunihiko Fukushima

    Proc. of the 26th Fuzzy System Symposium  2010.9 

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  • A Proposal of Structure Analysis Method for Spam Filtering

    Takashi Kobayashi, Ayane Tsujino, Rie Sasaki, Toshiyuki Maeda, Yoshinori Arai, Atsushi Inoue, Isao Hayashi

    Human Interface 2010  2010.9 

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  • Discrimination of NIRS Signal Data of Calculation Task Using pdi-Boosting Method

    Shinji Tsuruse, Isao Hayashi

    Human Interface 2010,  2010.9 

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  • Acquisition of Logicality in Living Neuronal Networks and its Operation to Fuzzy Bio-Robot System

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Minori Tokuda, Suguru N. Kudoh

    Proc. of 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2010) in 2010 IEEE World Congress on Computational Intelligence (WCCI2010)  2010.7 

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  • Three-dimensional Motion Analysis for Gesture Recognition Using Singular Value Decomposition

    Yinlai Jiang, Isao Hayashi, Masanao Hara, Shuoyu Wang

    Proc. of 2010 IEEE International Conference on Information and Automation (ICIA2010)  2010.6 

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  • Application of Intelligent Robots to Robot Land

    Isao Hayashi, Suguru N. Kudoh

    Proc. of KIIS Spring Conference 2010, Special Talking in KIIS Spring Conference 2010  2010.4 

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  • Edge Extraction for the Neocognitron

    Yuki Makino, Masayuki Kikuchi, Kunihiko Fukushima, Isao Hayashi, Hayaru Shouno

    The Institute of Electronics, Information and Communication Engineers Technical Report  2010.3 

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  • Neocognitron Trained by a New Competitive Learning

    Kunihiko Fukushima, Isao Hayashi, Hayaru Shouno, Masayuki Kikuchi, Yuki Makino

    The Institute of Electronics, Information and Communication Engineers Technical Report  2010.3 

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  • A Proposal of Boosting Algorithm for Brain-Computer Interface Using Probabilistic Data Interpolation

    Isao Hayashi, Shinji Tsuruse

    The Institute of Electronics, Information and Communication Engineers Technical Report  2010.3 

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  • Estimation of Cracks in Concrete Composite Slabs Using TAM Network

    Takashi Miyaguchi, Michiyuki Hirokane, Isao Hayashi

    Proc. of the 24th Reliability Symposium  2009.12 

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  • Acquisition of Embodied Knowledge on Sport Skill Using TAM Network

    Isao Hayashi, Toshiyuki Maeda, Masanori Fujii, Shuoyu Wang, Tokio Tasaka

    Proc. of 2009 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2009)  2009.8 

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  • Analysis of Action Potentials of Cultured Neuronal Network Using Fuzzy Operator

    Isao Hayashi, Megumi Kiyotoki, Ai Kiyohara, Takahisa Taguchi, Suguru N. Kudoh

    Proc. of the 25th Fuzzy System Symposium  2009.7 

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  • Fundamental Study of Collaborative Learning Consisting of Reinforcement Learning and Brain Signal in BCI

    Isao Hayashi, Ryota Miwa, Masanori Sennami

    Proc. of the 25th Fuzzy System Symposium  2009.7 

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  • Fundamental Study of Path Finding Method Using Reinforcement Learning and Brain Signal in Disasters

    Isao Hayashi, Ryota Miwa, Kunihiko Fukushima, Masahiro Hori

    Proc. of the Safety Engineering Symposium 2009  2009.7 

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  • Evaluation of Structure Safety in Concrete Floor Slab Using TAM Network

    Takashi Miyaguchi, Michiyuki Hirokane, Isao Hayashi

    Proc. of the Safety Engineering Symposium 2009  2009.7 

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  • A Consideration on Embodied Knowledge of Table Tennis

    Masanori Fujii, Toshiyuki Maeda, Tokio Tasaka, Shuoyu Wang, Isao Hayashi

    Proc. of the 23th Annual Conference of the Japanese Society for Artificial Intelligence  2009.6 

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  • Analysis of Embodied Knowledge Using Data-Mining Methods from Image Data

    Toshiyuki Maeda, Isao Hayashi, Tokio Tasaka, Shuoyu Wang, Masanori Fujii

    Proc. of the 23th Annual Conference of the Japanese Society for Artificial Intelligence  2009.6 

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  • Acquisition of Skill Knowledge on Table Tennis Using TAM Network

    Isao Hayashi, Masanori Fujii, Tokio Tasaka, Shuoyu Wang, Shuoyu Wang

    Proc. of the 23th Annual Conference of the Japanese Society for Artificial Intelligence  2009.6 

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  • ニューロ動作解析手法によるスポーツ技能の身体知獲得

    林 勲, 前田 利之, 藤井 政則, 王 碩玉, 田阪 登紀夫

    日本知能情報ファジィ学会,脳と知覚研究会第5回ワークショップ  2008.12 

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  • A Robot Body for Embodiment of Living Neuroal Network

    HAYASHI,Isao, HAYASHI Isao

    Proc. of the 9th Conference on Technical Division of System Integration of the Society of Instrument and Control Engineers  2008.12 

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  • Acquisition of Embodied KnowLedge on Table Tennis Technique Using Motion Analysis Model by TAM Network

    HAYASHI Isao

    Proc. of the 2008 Conference on Technical Division of Systems and Information of the Society of Instrument and Control Engineers  2008.11 

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  • TAMネットワークによる卓球技能評価の検討

    林 勲, 前田 利之, 藤井 政則, 王 碩玉, 田阪 登紀夫

    人工知能学会身体知研究会第2回研究会予稿集  2008.11 

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  • Spatio-temporal analysis of brain activities on aprture problem

    Atsushi Moritaka, Takahiro Ymanoi, Hisashi Toyoshima, Isao Hayashi, Hidetoshi Nonaka

    Proc. of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems(SCIS&ISIS2008)  2008.9 

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  • Estimation of brain activity for perception of aperture problem

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    Proc. of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advance Intelligent Systems(SCIS&ISIS2008)  2008.9 

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  • A robust pattern of neuronal responce to outer phenomena in ”vitroid”,the hybrid neuro-robot

    Suguru N. Kudoh, Minori Tokuda, Ai Kiyohara, Chie Hosokawa, Takahisa TAguchi, Isao Hayashi

    Proc. of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2008)  2008.9 

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  • Fundamental Study of Table Tennis Technique Evalution Using Motion Analysis System

    HAYASHI,Isao, HAYASHI Isao

    Proc. of the 59th Conference of Japan Society of Physical Education, Health and Sport Sciences  2008.9 

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  • A Consideration on Sport Skill Evaluation Using Motion Analysis Model by Neural Network

    HAYASHI Isao

    Proc. of the 24th Fuzzy System Symposium  2008.9 

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  • In Vitro Learning in Neurorobot System

    HAYASHI,Isao, HAYASHI Isao

    Proc. of the 24th Fuzzy System Symposium  2008.9 

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  • VItroid - A robot with link between living neuronal network in vitro and robot body

    Suguru N.Kudoh, Minori Tokuda, Ai Kiyohara, Chie HOsokawa, Takahisa TAguchi, Isao Hayashi

    Proc. of 2008 IEEE International Conference on Mechatronics and Automation (ICMA2008)  2008.8 

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  • Neuronal responces to Sensor Input in the Miniature Neuro-Robot-Hybrid

    SUguru N. kudoh, Minori Tokuda, Ai Kiyohara, Isao Hayashi, Chie HOsokawa, Takahisa Taguchi

    Proc.of the 6th International Meeting on Substorate-Integrated Micro ElectrodeArrays(MEA2008)  2008.7 

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  • 画像データからの知識獲得手法によるスポーツ技能の解析

    前田 利之, 林 勲, 藤井 政則, 王 碩玉, 田阪 登紀夫

    電気学会 産業応用部門 産業計測制御研究会  2008.3 

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  • Aperture錯視における脳内処理部位の推定と比較

    森高 篤司, 山ノ井 高洋, 豊島 恒, 林 勲

    日本知能情報ファジィ学会,脳と知覚研究会第4回ワークショップ  2008.2 

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  • Interaction between living nuroral network and outer world by programmable multisite stimulation system

    Suguru N.kudoh, Ai Kiyohara, Chie Hosokawa, Takahisa Taguchi, Isao Hayashi

    Proc.of 2007 IEEE International Symposium on Micro-Nano Mechatronics and Human Science(MHS2007)  2007.11 

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  • Recognition of preception and the Localization for aperture problem in visual pathway of brain

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    Proc. of 2007IEEE International Conference on Systems,Man and Cybernetics(SMC2007)  2007.10 

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  • エンタテインメントとしてのバイオ・ロボティクスハイブリット

    工藤 卓, 徳田 農, 清原 藍, 細川 藍, 細川 千絵, 田口 隆久, 林 勲

    情報処理学会,エンタテインメントコンピューティング研究会,エンタテインメントコンピューティング2007(EC2007)  2007.10 

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  • Fuzzy TAM Network Model with SOM

    Jung-Pyo Hong, Seung-Gook Hwang, Sang-Yong Rhee, Young-Man Park, Isao Hayashi

    Proc.of 8th International Symposium on Advanced Intelligent Systems(ISIS2007)  2007.9 

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  • Lerning and Memory in Living Neuronal Networks Connected to Moving Robot

    Isao Hayashi, Takahisa Taguchi, Suguru N.kuboh

    Proc. of 8th Internatinal Symposium on Advanced Intelligent Systems(ISIS2007)  2007.9 

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  • Biologically Inspired Modelsfor Living Neuronal Network and Early Vision of Brain

    Isao Hayashi, Takahisa Taguchi, Sugul N.Kudoh

    2007.9 

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  • Lerningand Memory in Living Neuronal Networks through Fuzzy Model

    Isao Hayashi, Takahisa Taguchi, Suguru N.Kudoh

    2007.9 

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  • Biomodeling System:Analysis of Adaptive Lerning in Cultured Neuronal Network Using Fuzzy Logic

    Isao Hayashi, Minori Tokuda, Ai Kiyohara, Takahisa Taguchi, Suguru N. Kudoh

    Proc. of the 23th Fuzzy System Symposium  2007.8 

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  • Biomodeling System:Analysis of Adaptive Lerning in Cultured Neuronal Network Using Fuzzy Logic

    HAYASHI Isao

    2007.8 

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  • Biologically Inspired Model:A Hybrid System by Living Neurons,Brain,Preception and Robptics

    HAYASHI Isao

    2007.8 

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  • Recognition of outer world performed by dissociated neurons

    HAYASHI,Isao, HAYASHI Isao

    2007.8 

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  • Recognition of Cracks on Concrete Structures Using Evolutional Image processing

    Michiyuki Hirokane, Isao Hayashi, Hitoshi Furuta, H.Takiuchi, I..Nakajima

    Proc.of the 10th International Conference on Applications of Statistics and Probability in Civil Engneering(ICASP10)  2007.7 

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  • Biomodeling Robot System Connected to Living Neuronal Network

    Isao Hayashi, Suguru N. Kudoh

    International Symposium in Science and Technology at Kansai University 2007--Collaboration between ASEAN Countries in Enviroment and Life Science--  2007.7 

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  • 神経回路に宿る思考,ゆらぎ,そして神経回路網における意味生成

    林 勲, 工藤 卓

    国際高等研究所,スキルと組織第6回研究会  2007.3 

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  • Interpolating Vectors for Robust Pattern Recognition

    Kunihiko Fukushima, Isao Hayashi

    The Institute of Electronics, Information and Communication Engineers  2007.3 

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    Grant-in-Aid for Scientific Research

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  • The Cognitive Agent by the Bio-robotics Hybrid

    Suguru N. Kudoh, Ai Kiyohara, Isao Hayashi, Takahisa Taguchi

    IEE Japan  2006.12 

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    Grant-in-Aid for Scientific Research

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  • Interaction with Environment of the Semi-Artificial Neural Network Composed by Living Neurons

    Suguru N. Kudoh, Ai Kiyohara, Isao Hayashi, Masaaki Suzuki, Munehiro Yamaguchi, Takahisa Taguchi

    The Society of Instrument and Control Engineers  2006.11 

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    Grant-in-Aid for Scientific Research

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  • Structure Evaluation of Receptive Field Layer in TAM Network

    Isao Hayashi, Toshiyuki Maeda

    IEEE SMC  2006.11 

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    Grant-in-Aid for Scientific Research

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  • Operation of Network Dynamics in Cultured Hippocampal Neurons on a Multi-electrode Array

    Suguru N. Kudoh, Isao Hayashi, Takahisa Taguchi

    IEEE Robotics and Automation Society  2006.11 

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    Grant-in-Aid for Scientific Research

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  • Pattern Analysis on Core Competency Model for Subcontractors of Construction Companies Using Fuzzy TAM Network

    Sung-Eun Kim, Seung-Gook Hwang, Yong-Soo Kim, Isao Hayashi

    Japan Society for Fuzzy Theory and Intelligent Informatics  2006.9 

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    Grant-in-Aid for Scientific Research

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  • Biologically Motivated Systems: A Fuzzy System for Living Neuronal Networks and Early Vision of Brain

    Isao Hayashi, Takahiro Yamanoi, Suguru N. Kudoh

    Japan Society for Fuzzy Theory and Intelligent Informatics  2006.9 

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    Grant-in-Aid for Scientific Research

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  • A Biomodeling System by Cultured Neuronal Network of Rat Hippocampus Connected to Moving Robot

    Isao Hayashi, Takahisa Taguchi, Suguru N. Kudoh

    Japan Society for Fuzzy Theory and Intelligent Informatics  2006.9 

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  • A Functional Comparison of Receptive Field Structure in TAM Network

    Isao Hayashi, Kunihiko Fukushima

    Japan Society for Fuzzy Theory and Intelligent Informatics  2006.9 

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  • Recognition of Perceptual Grouping and Localization of Brain Activity in Aperture Problems

    Isao Hayashi, Hisashi Toyoshima, Takahiro Yamanoi

    Japan Society for Fuzzy Theory and Intelligent Informatics  2006.9 

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  • Recognition of Cracks in Concrete Structures Using Gabor Function

    Hiroyuki Takiuchi, Michiyuki Hirokane, Isao Hayashi

    Japan Society for Fuzzy Theory and Intelligent Informatics  2006.9 

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  • Biomodeling Robot Systems Connected to Living Neural Network

    Isao Hayashi, SUguru N.Kudoh

    2006.8 

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  • Biomodeling System by Living Neuronal Network Connected to Moving Robot

    Isao Hayashi, Takahisa Taguchi, Suguru N. Kudoh

    Proc. of International Symposium on Artificial Brain with Emotion and Learning (ISABEL2006)  2006.8 

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    Grant-in-Aid for Scientific Research

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  • Interaction and Intelligence in Living Neuronal Networks Connected to Moving Robot

    Suguru N. Kudoh, Takahisa Taguchi, Isao Hayashi

    IEEE Fuzzy Society  2006.7 

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  • Synaptic Potentiation Re-organized Functional Connections in a cultured Neuronal Network Connected to a Moving Robot

    Suguru N.Kudoh, Isao Hayashi, Takahisa Taguchi

    Proc.of the 5th International Meeting on Substrate-Integrated Micro ElectrodeArrays(MEA2006)  2006.7 

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  • 環境と相互作用するラット海馬神経細胞分散培養系

    工藤 卓, 林 勲, 田口 隆久

    電気学会,電子・情報・システム部門,医用・生体工学研究会  2006.4 

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  • ガボール関数を用いたひび割れ抽出に関する研究

    広兼 道幸, 林 勲, 政森 理恵子, 瀧内 裕之, 園田 麻里子

    第8回土木・建築ソフトコンピューティング応用シンポジウム講演論文集  2006.2 

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  • Orientation Selectivity of TAM NetworkExtensive Receptive Field

    Isao Hayashi, James R.Williamson

    Proc. of the International Conference on Computational Intelligence for Modelling Control and Automation(CIMCA2005)  2005.11 

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  • 脳内初期視覚モデルによる方位選択性と知識再構築

    林勲

    バイオメディカルファジィシステム学会2005年度年次大会講演論文集  2005.10 

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  • A Study of Orientation Slectivity of TAM Network Incorporated Receptive Receptive Field Structure

    Isao Hayashi, James R.Willamson

    Proc.of the 3rd International Symposium on Autonomous Minirobots for Research and Edutainment(AMiRE2005)  2005.9 

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  • 広範囲受容野をTAMネットワークの提案

    林 勲, ジェームス R.ウィリアムソン

    第21回ファジィシステムシンポジウム講演論文集  2005.9 

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  • An Application Fuzzy ID3 to Wireless LAN Access Point Optimal Location Problem

    Isao hayashi

    Proc. of the 4th Interantional Conference on Machine Learning and Cybernetics(ICMLC2005)  2005.8 

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  • TAM ネットワークの方位選択性に対する基礎検討

    林 勲, 鹿野 徳幸

    日本知能情報ファジィ学会,第24回ファジィワークショップ  2005.3 

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  • Orientation Slectivity by TAM Network using Gabor Function Type Receptive Field

    Isao hayashi, james R.Williamson

    Proc. of the 5th International Conference on Recent Advances in Soft Computing(RASC2004)  2004.12 

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  • TAM ネットワークにおける受容野入力構造と知能再構築

    林 勲, 馬野 元秀

    日本知能情報ファジィ学会,ファジィ・コンピューティング研究会大16回ワークショップ,脳と知覚研究会第1回ワークショップ  2004.11 

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  • Model of Early Vision for Perceptual Grouping:TAM Network

    Isao Hayashi, Hwang Seung Gook

    Special Talking in 2004 Workshop of METEC,Kyungnam University and Korea Fuzzy Logic and Intelligent Systems Society(KFIS Workshop2004)  2004.10 

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  • A Formulation of Reception field Type Input Layer for TAM Netowork Using Gabor Function

    Isao Hayashi, Hiroma mwd, Jams R. Williamson

    Proc.of 2004 IEEE International Conference on Fuzzy Systems(FUZZ-IEEE2004)  2004.7 

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  • Recceptive Field Type Input Layer of TAM Network using Gabor Function

    HAYASHI Isao

    2004.6 

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  • Structuralization of Early Vison for Perceptual Grouping in Apertures

    Isao Hayashi, Gentaro Shinpaku

    Proc. of the Internatinal workshop on Fuzzy Systems and Innovational Computing 2004(FIC2004)  2004.6 

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  • Gabor受容野導入型TAM Network

    林 勲

    日本知能情報ファジィ学会,第64回関西支部例会  2004.5 

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  • 脳内初期視覚処理モデルと知能情報機構

    林 勲

    日本知能情報ファジィ学会,第6回北海道支部講演会  2004.3 

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  • 脳内初期視覚処理モデルと知覚グルーピング

    林 勲

    オムロン(株)技術本部コントロール研究所講演  2004.2 

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  • 脳内初期視覚処理の計算論的モデル:知覚グルーピング

    林 勲

    大16回自律分散システム・シンポジイウム講演会論文集  2004.1 

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  • ガボール関数を用いたTAM Network の受容野入力構造の提案

    林 勲, 前田 裕正

    日本知能情報ファジィ学会,ファジィ・コンピューティング研究会第15回ワークショップ  2003.12 

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  • Apeture問題における輪郭運動知覚

    林 勲, 親泊 元太郎

    日本知能情報ファジィ学会,ファジィ・コンピューティング研究会第15回ワークショップ  2003.12 

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  • 視覚系ニューロモデルとファジィ知識獲得

    林 勲

    産業技術総合研究所人間系特別研究体,第105回人間系セミナー  2003.10 

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  • A formulation of Kouwledge Restructuring Type TAM Network

    Isao Hayashi, James R. Williamson

    proc. of 2003 IEEE International Conference on Systems,Man and Cybernetics(SMC2003)  2003.10 

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  • A Formulatiom of fuzzy TAM Network with Gabor Type Recptive Fields

    Isao Hayashi, Hiromasa Maeda

    Proc.of the 4th International Symposium on Advanced Intelligent Systems(ISIS2003)  2003.9 

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  • Aperture 問題における輪郭運動知覚と注意との関連について

    林 勲, 親泊 元太郎

    第19回ファジイシステムシンポジウム講演論文集  2003.9 

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  • Aperture 問題における輪郭運動速度に対する知覚認識

    林 勲

    第14回日本ファジィ学会ファジィコンピューティング研究会ワークショップ  2002.12 

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  • ファジィ TAM Network における知識再構築法

    林 勲

    第14回日本ファジィ学会ファジィコンピューティング研究会ワークショップ  2002.12 

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  • Knowledge Restructuring in Fuzzy TAM Network

    HAYASHI Isao

    The 9th International Conference on Neural Information Processing ( ICONIP '02 )  2002.11 

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  • Fusion Models of Fuzzy Logic and Neural Networks

    HAYASHI Isao

    Plenary Talk  2002.11 

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  • TAM Networkにおけるプルーニング機能の有用性について

    林 勲

    第1回情報処理学会情報科学技術フォーラム  2002.9 

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  • An Integration of Fuzzy and Two-Valued Logics on Spatial Depiction

    HAYASHI Isao

    The sixth International Conference on Knowledge-Based Intelligent Information Engineering and Allied Technologies (KES2002)  2002.9 

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  • Aperture問題における輪郭運動方位と速度に対する知覚について

    林 勲

    第18回日本ファジィ学会ファジィシステムシンポジウム  2002.8 

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  • ファジィTAM Networkにおける獲得知識の再構築法

    林 勲

    第18回ファジィ学会ファジィシステムシンポジウム  2002.8 

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  • An Analysis of Aperture Problem Using Fuzzy Rules Acquired from TAM Network

    Isao Hayashi

    2002 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2002) in 2002 IEEE World Congress on Computational Intelligence (WCCI2002)  2002.5 

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  • Fusion Model between Fuzzy Logic and Neural Networks

    Isao Hayashi

    Special Talk at the department of Neural Information Processing,University of Ulm  2002.2 

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  • An Integration of Fuzzy and Two-valued Logics on Natural Language Semantics

    Toshiyuki Maeda, Isao Hayashi, Motohide Umano, Lakhmi C.jain

    Proc.of the First International Workshop on Hybrid Infomation Systems(HIS'01)  2001.12 

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  • Aperture問題のルール抽出による一解析法

    林 勲

    第11回計測自動制御学会FANインテリジェントシステムシンポジウム  2001.9 

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  • TAM NetworkによるAperture問題の一考察

    林 勲

    第17回日本ファジィ学会ファジィシステムシンポジウム  2001.9 

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  • Acquisition of Fuzzy Knowledge from Topographic Mixture Networks with Attentional Feedback

    Isao Hayashi

    The International Joint Conference on Neural Networks (IJCNN '01)  2001.7 

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  • A Study on Pruning Methods for TAM Network

    Isao Hayashi

    The Fifth International Conference on Cognitive and Neural Systems  2001.6 

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  • 視覚系ニューロモデル

    林 勲

    第51回日本ファジィ学会関西支部例会  2001.4 

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  • 数理・シミュレーションアプローチと感情社会学とおよびシステム論的家族療法との関わりに関する考察

    林 勲

    計測自動制御学会システム工学部会知能工学部会共催研究会「社会組織のマルチエージェントシステム分析~数理とシミュレーションからのアプローチ~」  2001.3 

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  • 感情規則による二重拘束の形式的記述

    林 勲

    第31回数理社会学会大会  2001.3 

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  • TAM Networkのルール抽出法と視覚心理実験への試み

    林 勲

    第12回日本ファジィ学会ファジィコンピューティング研究会ワークショップ  2000.12 

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  • 二重拘束仮説に対する計算論的アプローチの試論

    林 勲

    第12回日本ファジィ学会ファジィコンピューティング研究会ワークショップ  2000.12 

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  • 感情規則と三者関係の認知的斉合性を用いた二重拘束のモデル

    林 勲

    第48回日本グループダイナミックス学会大会  2000.9 

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  • TAM Networkのプルーニング手法の一提案

    林 勲

    第16回日本ファジィ学会ファジィシステムシンポジウム  2000.9 

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  • A Proposal of Fuzzy Spatial Reasoning System with Natural Language Input

    Isao Hayashi

    Joint meeting of the 4th World Multiconference on Systemics,Cybernetics and Informatics (SCI2000) and the 6th International Conference on Information Systems Analysis and Synthesis (ISAS2000)  2000.7 

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  • A Re-Interpretation of Double Bind from the Viewpoints of Sociology of Emotions and Group Dynamics

    Isao Hayashi

    The Tenth Annual International Conference of the Society for Chaos Theory in Psychology and Life Sciences (SCTPLS2000)  2000.7 

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  • A Study on Unimodality of Information Entropy in Learning Type Fuzzy ID3

    Isao Hayashi

    The International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS2000)  2000.6 

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Works

  • ファジィシステムシンポジウムの改革と進展

    林 勲

    2019.8

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Awards

  • 2023年度貢献賞

    2023.9   日本知能情報ファジィ学会  

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  • 2023年度功績賞

    2023.9   日本知能情報ファジィ学会  

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  • 2019年度貢献賞

    2020.9   日本知能情報ファジィ学会  

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    Country:Japan

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  • 2019 Kansai University, "Gakuno-jitsuge Award" (Academic Realization Award)

    2020.8   Kansai University  

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    Country:Japan

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  • 平成30年度貢献賞

    2018.9   日本知能情報ファジィ学会  

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  • 平成29年度貢献賞

    2017.9   日本知能情報ファジィ学会  

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    Country:Japan

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  • 平成26年度貢献賞

    2014.9   日本知能情報ファジィ学会  

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    Country:Japan

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  • Best Session Paper Award

    2013.11   The 14th International Symposium on Advanced Intelligent Systems (ISIS2013)  

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  • 平成25年度貢献賞

    2013.9   日本知能情報ファジィ学会  

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    Country:Japan

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  • The 2012 Paper Award

    2012.9   Japan Society for Fuzzy Theory and Intelligent Informatics  

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    Country:Japan

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  • 平成21年度貢献賞

    2009.7   日本知能情報ファジィ学会  

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    Country:Japan

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  • Best Presentation Award

    2008.9   The Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2008)  

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  • Recognition Award

    2007.9   The 9th International Symposium on Advanced Intelligent Systems (ISIS2007)  

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  • 平成2年度電気関係学会関西支部連合大会講演会奨励賞

    1991.4   電気関係学会関西支部  

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    Country:Japan

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Research Projects

  • Development of AI Board Extracting Table Tennis Strategy from Broadcast Video Using Virtual Data Generation Type Fuzzy Bagging

    Grant number:20K11981  2020.4 - 2025.3

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

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    Grant amount:\4550000 ( Direct Cost: \3500000 、 Indirect Cost:\1050000 )

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  • Establishment of evaluation system for athlete's brain status based on fixational eye movement and visual function

    Grant number:16K12996  2016.4 - 2019.3

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

    SHIMEGI SATOSHI

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

    Sport athletes try to exert a high performance constantly, but the performance level varies day by day, being considered to ascribe to the brain state. The motion vision ability to process the visual information concerning the movement of a ball or a person is directly linked to the visuomotor performance in the athletes of fastball sports such as table tennis. Therefore, we have established a motion direction detection (MDD) task using dynamic random dot stimulation to measure a motion vision. The measured motion vision fluctuated daily, correlating with the performance of a successive visuomotor task requiring to respond physically to a fast moving target. We searched the factors influencing the motion vision, and found that non-REM sleep in a specific time zone is related to the motion vision. Therefore, the stabilization and optimization of brain state through high quality sleeping can keep motion vision at higher level, improving the performance in athletes with fastball sports.

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  • Neural information decoding by estimation of the dynamic functional connectivity

    Grant number:19200018  2007 - 2010

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

    KUDOH SuguruN., HAYASHI Isao, HOSOKAWA Chie

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    Grant amount:\38090000 ( Direct Cost: \29300000 、 Indirect Cost:\8790000 )

    In this study, we developed analytical methods to elucidate dynamical changing of the pattern of activity in living neuronal network and using the methods, we discovered hysterical effects of living neuronal network on evoked activity. Moreover, the novel technique, which estimates the logic of the neuronal connectivity pattern adapting a fuzzy operator, was established. This is the technique of extracting the regularity and logicalness of a functional connectivity pattern between neurons using T-norm and T-conorm operator. Using the finding about the duration of the stimuli dependent status variation of a living neuronal network, the dynamical clustering analysis technique was established for the culture system, and a program for dynamical-decoding was developed. Furthermore, the small mobile robot was connected to the dissociated culture system as a vehicle for an interaction to the external world. The system with feeds back the input from sensors on the robot body to a culture system was developed. This neuro-robot system is useful as a platform for a substantiation test of the methods of neuronal decoding.

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  • Formulation and Knowledge Acquisition of Bio-closed-loop System by Cultured Neuronal Network of Rat Hippocampus Connected to Moving Robot

    Grant number:18500181  2006 - 2008

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

    HAYASHI Isao, UMANO Motohide, FUKUSHIMA Kunihiko, KUDOH Suguru

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    Grant amount:\4260000 ( Direct Cost: \3600000 、 Indirect Cost:\660000 )

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  • Meta-Learning Mechanism of the Learning by Switching Knowledge Representations

    Grant number:18500177  2006 - 2008

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

    UMANO Motohide, SETA Kazuhisa, HAYASHI Isao

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    Grant amount:\4160000 ( Direct Cost: \3500000 、 Indirect Cost:\660000 )

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  • Studies of human depth perception using a reverse perspective illusion and its application to diagnostics in clinical medicine.

    Grant number:16300085  2004 - 2007

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

    HAYASHI Takefumi, HAYASHI Isao, AMEMIYA Toshihiko, INUI Toshio, SUZUKI Kimihiro

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    Grant amount:\14860000 ( Direct Cost: \14200000 、 Indirect Cost:\660000 )

    This research project was worked on to explore top-down and bottom-up mechanisms of human depth perception using a reverse perspective illusion and to apply the findings to a diagnostics of a psychiatric disease in clinical medicine. Obtained results are described on below.
    Internal mechanism of the reverse perspective illusion was measured by fMRI. It was found that each brain area of BA19/39, BA37/19 and BA7 are strongly activated when the illusion is perceived. Further more, in case of the stimuli which has no pictorial cues for the illusion, as subjects made efforts to 'see' the illusion, activations were also found in frontal lobe. These results show the interactions between the top-down and the bottom-up processes during the illusion.
    To study the influence of the pictorial cues on the illusion, a paired comparison method and the binocular disparity adjusting method was applied to evaluate the strength of the illusion. These methods ware compared to the conventional method which measure the distance between the subject and the reverse perspective object. The results show good agreements. It was confirmed that the newly developed methods can be used effectively to evaluate the strength of the illusion and influence of the pictorial cues.
    Psychological experiments to study basic properties of depth perception were performed. Eye movement, influence of body motion, surface perception from binocular disparity, depth perception from motion parallax, depth perception from 2D pictorial cues, were studied independently and made it dear about the basic property of depth perception.
    An experimental system using a stereo computer graphics technology was developed to present reverse perspective illusion by changing parameters (such as pictorial cues, geometrical factors, and binocular disparities). A perception experiment of the illusion was made to subjects of the sleep deprivation state using the system, and made it clear that the sensitivity to the perception of the illusion falls by sleep deprivation. This indicates the possibility of the application the results of the experiment to diagnostics of the psychiatric disease.

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  • Construction of Neural Network acquiring an Internal Model of Visual Perceptual Grouping

    Grant number:14580433  2002 - 2004

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

    HAYASHI Isao, UMANO Motohide

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    Grant amount:\3000000 ( Direct Cost: \3000000 )

    In the human visual system, the visual modalities are detected at visual cells in the retina, the lateral geniculate nucleus(LGN) and the primary visual cortex (V1). Aperture problem is a kind of experiments for analyzing the binding mechanism for motion processing in the early visual system. A circle aperture where a bar is moving in the background is first displayed at the computer display. Two other circles appear next at both sides of the center circle, but two bars are also moving in the background, and the bar's orientation is different from the center's. If subjects perceived three bars as a bar, the center bar's moving orientation would be changed as same as at the both sides of circle's. This perceptual grouping is strongly depending on the display time. On the other hand, visual models and neural networks based on the human visual system have been proposed, e.g., BCS, FCS, ARTMAP, fuzzy ARTMAP and TAM Network. TAM (Topographic Attentive Mapping) Network is a biologically-motivated neural network. TAM Network is analogous to receptive field, LGN, and V1 in the structure from the input layer to the output layer. When the network makes an incorrect error, the attentional mechanism is invoked based on the feedback signals and inhibitory synapses, and the error is adjusted to be smaller. In this research, the following researches are studied.
    1.Perceptual rates are estimated changing the display time, radius, distance between circles, and the dependency of display time on radius and distance between circles is confirmed.
    2.The curve of perceptual rates for display time is convex.
    3.Fuzzy rules are acquired from aperture's data using TAM Network, and the usefulness of feedback signals and inhibitory synapses of TAM Network is shown.
    By these researches, we show the possibility of the decreasing of perceptual rate in the late display time more than 550ms. The usefulness of the feedback signals and the inhibitory synapses of TAM Network is also shown.

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  • Implementation of Explanatory-Rule Acquisition System from Data with Numeric and Symbolic Attributes

    Grant number:12680393  2000 - 2002

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

    UMANO Motohide, HAYASHI Isao, OKADA Makoto

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    Grant amount:\1900000 ( Direct Cost: \1900000 )

    We propose a method to acquire explanatory fuzzy rules from a data set with numeric and symbolic attributes. Examples of acquired fuzzy rules are the followings:
    Most data of {sex = male}{age = young} are {class = A} with coverage 0.91
    Almost all data of {sex = female}{height = middle} are {class = B} with coverage 0.73
    where "sex" and "class" are symbolic attributes and "age" and "height" are numeric ones, "young" and "middle" are fuzzy sets of attributes "age" and "height," respectively, and "most" is a fuzzy quantifier in the proportion.
    Since a real data set includes noise and errors, we can not apply conventional methods studied in a various fields. We use a fuzzy ID3-based algorithm to generate a fuzzy decision tree for a specified class. From a decision tree, we extract a piece of fuzzy knowledge from a path of the root to a class node by evaluating its understandability (the number of nodes) and informativeness (coverage of the specified data). We have implemented a explanatory-rule acquisition system based on the method.

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  • 典型的ファジィ知識と例外的ファジィ知識を抽出可能な知識獲得システムの作成

    Grant number:10680390  1998 - 2000

    日本学術振興会  科学研究費助成事業  基盤研究(C)

    佐藤 浩, 林 勲, 宇野 裕之

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    Grant amount:\2500000 ( Direct Cost: \2500000 )

    データに雑音や誤差や矛盾などが含まれる場合に、典型的ファジィ知識と例外的ファジィ知識の抽出が可能な知識獲得システムを作成することを目的としている。
    今年度は、次のことを行なった。
    ●典型的ファジィ知識の抽出方法の定式化:抽出されたファジィ知識に対する各データの正確度により、そのデータを取り除く方法について考察した。しきい値を利用する方法や度合い付きで取り除く方法などが考えられる。また、このような典型的知識と例外的知識を用いてどのように推論するかについても議論した結果、データの個数による重み付けと、結果の分散による方法が有効であることが分かった。
    ●適用する学習方式の決定:知識抽出法としては、ファジィ・ニューラルネットワークによるファジィルールの抽出方法を用いた。また、典型的なデータからの知識抽出と例外的なデータからの知識抽出には同じ方法を用いた。
    ●シュミレーション・プログラムの作成:項目(1)と(2)の手法をシュミレーションするプログラムを作成した。そして、いくつかのデータについて、典型的ファジィ知識と例外的なファジィ知識の抽出を試みた。本手法を用いない方法よりも、少ないルールで、良い正確率を得ることができた。

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Social Activities

  • 日本知能情報ファジィ学会 第13期 副会長

    2013.5 - 2015.5

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  • 日本神経回路学会 2013年度~2016年度 理事

    2013.4 - 2017.3

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  • 電子情報通信学会 ニューロコンピューティング(NC)研究会幹事

    2013.4 - 2015.3

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  • システム制御情報学会 第57期 理事

    2013.1 - 2013.9

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  • 日本知能情報ファジィ学会 第29回ファジィ システム シンポジウム 大会委員長

    2013.1 - 2013.9

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  • The 6th International Conference on Soft Computing and Intelligent Systems, and the 13th International Symposium on Advanced Intelligent Systems (SCIS-ISIS2012), Vice General Chair

    2012.11

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  • 日本知能情報ファジィ学会 関西支部支部長

    2009 - 2011

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  • 日本知能情報ファジィ学会 学会賞選考委員

    2007 - 2011

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  • 日本知能情報ファジィ学会 理事(監事)

    2007 - 2009

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  • 日本知能情報ファジイ学会 事業委員会委員

    2007 - 2009

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  • 日本知能情報ファジィ学会 第24回ファジィシステムシンポジウムプログラム委員長

    2007 - 2008

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  • 経済産業省技術戦略マップローリング事業委託費検討委員会,日本知能情報ファジイ学会選出委員

    2007 - 2008

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  • 財団法人国際高等研究所 研究プロジェクト「スキルと組織」研究員

    2006 - 2009

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  • 日本知能情報ファジィ学会 理事(事業),事業委員会委員長

    2005 - 2007

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  • 計測自動制御学会 システム・情報部門自律分散システム部会 運営委員

    2005 - 2006

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  • 日本知能情報ファジイ学会 脳と知覚研究部会代表幹事

    2004 - 2011

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  • システム制御情報学会 第48期・第49期編集委員

    2004 - 2006

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  • Jounal of Advanced Computational Intelligence and Intelligent Informatics(JACIII),Member of Editorial Board

    2004

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  • 日本知能情報ファジイ学会 事業委員会副委員長

    2003 - 2005

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  • 日本知能情報ファジイ学会 表彰委員会委員

    2003 - 2005

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  • 文部科学省科学技術振興調整費NRVプロジェクト外部評価委員

    2003 - 2004

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  • International Journal of Hybrid Intelligent Systems, Member of Editional Board

    2003

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  • 日本知能情報ファジィ学会 関西支部運営委員

    2001 - 2011

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Media Coverage

  • 生成AI 人間に責任 Newspaper, magazine

    読売新聞  夕刊,解説委員の視点・渡辺達治,p.6  2023.8

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  • 関西大学科学技術振興会座談会 Newspaper, magazine

    日刊工業新聞  朝刊,pp.14-15  2022.10

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  • 期待しすぎず 人間の相棒に:他分野に導入 AI弱点も Newspaper, magazine

    読売新聞  夕刊,解説委員の視点・渡辺達治,p.6  2020.5

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  • 進化する超絶技巧!スーパーロボットアーム大集結 TV or radio program

    日本放送協会NHK Eテレ  サイエンスZERO  2019.2

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  • 自動運転技術と人工知能 TV or radio program

    朝日放送ABCラジオ  堀江政生の「ほりナビ・クロス」  2016.10

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  • 人工知能 TV or radio program

    朝日放送ABCラジオ  堀江政生の「ほりナビ」  2016.2

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  • モーツアルト効果 TV or radio program

    朝日放送ABCラジオ  堀江政生の「ほりナビ」  2012.11

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  • 利口な制御技術,ファジー制御とニューロ技術を融合 Newspaper, magazine

    日本産業新聞  朝刊  1989.6

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  • 「ファジー」応用へ成果続々 Newspaper, magazine

    朝日新聞  夕刊  1988.8

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  • ファジィコンピューター,学習機能加え新システム Newspaper, magazine

    西日本新聞  朝刊  1988.8

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  • ファジィ推論に学習機能,システム開発に成功 Newspaper, magazine

    西日本新聞  夕刊  1988.8

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  • 理想の装置制御発表,神経回路とファジー結合 Newspaper, magazine

    日本経済新聞  朝刊  1988.5

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Devising educational methods

  • ・専門演習・卒業研究(学部)研究スケジュールをウェブカレンダーで相互管理し、研究の進捗状況をメーリングリストで議論するとともに、毎週、個別の研究打ち合わせを実施している。また、春期と夏期に各1回程度の合宿形式の研究発表会を実施している。 ・専門演習・卒業研究(学部)学会等への参加及び発表を課している。 ・専門演習(学部)論文読解とその内容報告の発表会を実施している。 ・卒業研究(学部)研究発表を輪番制で課している。 ・インテリジェント・コンピューティング(学部)毎週、講義教材をウェブ上で提示するとともに、ビデオ活用により理解を促進している。また、年1回程度、学外講演者を招聘し最新研究を紹介している。 ・ネットワークコンピューティング実習(学部)毎週、授業の補助教材をネットメモリ領域で提示している。 ・日本事情(学部)ビデオ、議論、レポート活用により、留学生の会話能力の向上に配慮している。 ・導入ゼミ(学部)議論と発表を重視し、数回程度のコンピュータ実習を導入している。

Teaching materials

  • ・インテリジェント・コンピューティング(学部)講義教材のウェブ提示 http://www.res.kutc.kansai-u.ac.jp/~ihaya/files.html

Teaching method presentations

  •  特になし

Special notes on other educational activities

  • ・卒業研究の成果を学会、シンポジウム、国際学会等で発表している。