Personnel Information

写真a

NAKAGAWA Masao


Title

Assistant professor

Field

Field of Data Science

Date of Birth

1969
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Research Interests 【 display / non-display 】

  • Systems Engineering

  • Human Factors

  • Weibull Analysis

  • Reliability Engineering

  • Informatics

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Graduating School 【 display / non-display 】

  • Osaka Institute of Technology， Faculty of Engineering， Department of Industrial Management

    University， 1993， Graduated， Japan

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Graduate School 【 display / non-display 】

  • Konan University， Graduate School, Division of Science and Technology

    Doctor's Course， 2008.03， Other， Japan

  • Osaka Institute of Technology， Graduate School, Division of Engineering， Industrial and Manufacturing Systems Engineering

    Master's Course， 1995.03， Completed， Japan

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Degree 【 display / non-display 】

  • Ph.D. in Engineering， Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Control and system engineering， Konan University， Thesis， 2008.03

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Campus Career 【 display / non-display 】

  • Shiga University Data Science and AI Innovation Research Promotion Center，Assistant professor， 2022.04 - Now

  • Shiga University Center for Education and Research of Data Science，Assistant professor， 2019.04 - 2022.03

  • Shiga University Center for Education and Research of Data Science，Assistant professor， 2018.01 - 2019.03

  • Shiga University Center for Information Processing，Assistant professor， 2018.01 - 2019.03

  • Shiga University Center for Information Processing，Assistant， 2016.04 - 2017.12

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Association Memberships 【 display / non-display 】

  • Information Processing Society of Japan， 2001.01 - Now

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Research Areas 【 display / non-display 】

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Social systems engineering

  • Informatics / Computational science

  • Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Control and system engineering

  • Informatics / Intelligent informatics

  • Informatics / Human interface and interaction

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Research Career 【 display / non-display 】

  • Human-Computer Interaction， 1996.08 - Now

    Man-machine system Intelligence Information Processing Statistical analysis，Individual

  • Evaluation for Visual Sensorory Function under Multiple Modal Attributes， 1996.08 - Now

    Image Processing Computer Vision Multiple Modalities，Individual

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Papers 【 display / non-display 】

  • A Study on Skills Evaluation and the Classification Method for Panels in Material Defect Inspection， vol.63 (2) (p.98 - 103) ， 2014.02, Masao NAKAGAWA, Hidetoshi NAKAYASU and Tetsuya MIYOSHI

    Research paper (scientific journal)， Multiple Authorship

  • Analysis of Evacuation Behavior in Aircraft Accident Using Evacuation Model Based on MAS， 2013 International Conference on Biometrics and Kansei Enginerring (p.172 - 177) ， 2013.07, Tetsuya Miyoshi, Hidetoshi Nakayasu, Midori MORI, Masao Nakagawa

    Research paper (international conference proceedings)， Multiple Authorship

  • Human Cognitive Reliability Analysis on Drivers Using Simulator Experiments， Journal of Japan Industrial Management Association， vol.62 (p.1 - 8) ， 2012.02, Hidetoshi Nakayasu, Masao Nakagawa, Tetsuya Miyoshi and Patrick Patterson

    Research paper (scientific journal)， Multiple Authorship

  • IMPROVEMENT OF DETECTION PROBABILITY OF INSPECTION PANEL BY MULTIPLE MODARITIES， IADIS International Interfaces and Human Computer Interaction 2011， 2011.07, Hidetoshi Nakayasu, Masao Nakagawa, Tetsuya Miyoshi and Patrick Patterson

    Research paper (international conference proceedings)， Multiple Authorship

  • Simulation Model for Urgent Evacuation at Aircraft Accident， vol.77 (776) (p.1491 - 1503) ， 2011.04, Tetsuya MIYOSHI, Hidetoshi NAKAYASU, Yuki UENO, Masao NAKAGAWA

    Research paper (scientific journal)， Multiple Authorship

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Review Papers 【 display / non-display 】

  • Fundamental and Applications Related to Data Science, Machine Learning and Statistical Processing - 2. Fundamentals of Machine Learning， the society of materials science, japan， Journal of the society of materials science, japan， vol.73 (8) (p.682 - 688) ， 2024.08, Yasutoshi Nomura, Masao Nakagawa

    DOI:10.2472/jsms.73.682, Article, review, commentary, editorial, etc. (scientific journal), Multiple Authorship

  • Fundamental and Applications Related to Data Science, Machine Learning and Statistical Processing - 1. An Introduction to Data Science and AI， the society of materials science, japan， Journal of the society of materials science, japan， vol.73 (7) (p.618 - 624) ， 2024.07, Masao Nakagawa, Yasutoshi Nomura

    DOI:10.2472/jsms.73.618, Article, review, commentary, editorial, etc. (scientific journal), Multiple Authorship

  • Statistical Estimation of S-N Curves Based on Static Strength Characteristic Values of Metallic Materials and Future Prospects， the society of materials science, japan， Journal of the society of materials science, japan， vol.70 (12) (p.931 - 937) ， 2021.12, Tsutomu ITO, Yuki NAKAMURA, Kazutaka MUKOYAMA, Akiyoshi SAKAIDA, Masao NAKAGAWA, Kenji OKADA, Tatsuo SAKAI

    Article, review, commentary, editorial, etc. (scientific journal), Multiple Authorship

  • Historical Review on Origin and Application to Metal Fatigue of Probit and Staircase Methods and Their Future Prospects， the society of materials science, japan， Journal of the society of materials science, japan， vol.69 (3) (p.190 - 196) ， 2020.03, Masatoshi KURODA, Akiyoshi SAKAIDA, Noriyasu OGUMA, Masao NAKAGAWA, Takashi MATSUMURA and Tatsuo SAKAI

    Article, review, commentary, editorial, etc. (scientific journal), Multiple Authorship

  • What is Reliability Engineering， the society of materials science, japan， Journal of the society of materials science, japan， vol.63 (7) (p.570) ， 2014.07, Masao NAAKAGAWA

    Article, review, commentary, editorial, etc. (scientific journal), Single Author

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Presentations 【 display / non-display 】

  • 26th Fuzzy System Symposium, Domestic presentation， 2010.09， Quasi-optimization of Urgent Evacuation in Aircraft Accident using AAMAS Simulation， Oral presentation (general)

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Research Grants & Projects 【 display / non-display 】

  • ，Grant-in-Aid for Scientific Research(C)Grant-in-Aid for Scientific Research(C)，2022

  • ，Grant-in-Aid for Scientific Research(C)Grant-in-Aid for Scientific Research(C)，2015.04 - 2018.03

  • ，Sensitivity Analysis of Inspection for Reliability-Based Composite Material Design Based on Human Factor，Grant-in-Aid for Scientific Research(C)Grant-in-Aid for Scientific Research(C)，2003.04 - 2007.03

    Recently, an evaluation method of detection probability has been proposed by the authors for the measurement and evaluation of the industrial products based on the human detectable ability. In the psychometric mesurement, distributed parameta of pychometric curve had been presumed using Probit method concerning the three kinds of atribute of size, flatness degree and grayscale. Moreover, in this thesis, we propose an efficient method for the experiment and evaluation by Staircase method for the practical uses, and the detection probability of Staircase method is compared with that of Probit method, taking an example of experiments in which the methods are applied to measure the perception stimulation of panels, or subjects, concerning the three atributes that are extracted from the defect images in the inspection of FRP (fiber reinforced plastics) poroduct. In conclusion, the proposed method will be overviewed its efficiency and proved for the practical estimation uses of the parameter
    of pychometric function. From these works, the following three points are conclusions.
    1.Staircase method, the proposed evaluation method, showed that the experiment efficiency could be improved in the comparison with Probit method. In the actual experiment, the proposed method could reduce the number of trials to 43% or less compared with Probit method. As a result, it has indicated that it is effective to reduce the burden of panel in defect detection work.
    2.As for the PSE (subjective, equivalent value) mean value by Staircase method, a close value to the result of parameter estimation by Probit method was obtained. As a result, the practical possibility as a threshold of automatic check has been proved to be as good as Probit method.
    3.When the proposal technique was applied to perception stimulation with the three attributes extracted from defect image of FRP product, the coefficient of variations of subjective, equivalent value (PSE) proved larger than the result by Probit method in any attributes. Therefore, this result has indicated that proper attention is to be paid when the presumption is made at the confidence interval using decentralization and standard deviation.

  • ，STUDY ON IMAGE PROCESSING ANALYSIS SYSTEM OF COMPOSITES MATERIALS FOR PRACTICAL APPLICATION OF RELIABILITY DESIGN，Grant-in-Aid for Scientific Research(C)Grant-in-Aid for Scientific Research(C)，1999.04 - 2003.03

    On the other hand, a visual inspection process has been holding the problem
    in productivity, since the performance of a precision and a speed will be degraded by fatigue of the inspector. In order to meet these problems, some research works were tried for the standardization of an operation time of visual inspection, though it is not reached to the place which fixes a good evaluation measure. On the other hand, the development of productivity and performance for computerized inspection system which have a feature of recognition like human being has been left with a lots of problems unsolved.
    This paper deals with the automated visual inspection method for advanced manufacturing in order to enhance human skill with machine performance for improved management of product flexibility and product quality. The defective picture sampling process based on the proposed algorithm is performed for original picture image for a check of the industrial product. In the proposed algorithm, three kinds of inspection information such as location, size and level of defects are treated for clustering image data.

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Preferred joint research theme 【 display / non-display 】

  • ICT(情報通信技術), 知(ナレッジ)の表現, モデル化, システム設計, 情報処理, コンピュータ・シミュレーション, Cooperative Research with Industry-University research organizations and private agencies., Technical Consultation, Funded Research, Cooperative Research, Other

  • 【キーワード】データ解析／コンピュータ・シミュレーション／レジリエンス・エンジニアリング／ヒューマン・コンピュータ・インタラクション

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Charge of on-campus class subject 【 display / non-display 】

  • データサイエンス入門演習，2024.10 - 2025.03

  • プログラミング１演習，2024.04 - 2024.09

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Social Contribution 【 display / non-display 】

  • 05，2014.05

  • 07，2013.07

  • 05，2013.05

  • 02，2013.02

  • 09，2010.09

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