TAMURA Hiroki

写真a

Title

Professor

Research Fields, Keywords

Information and communication

Mail Address

E-mail address

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Graduating School 【 display / non-display 】

  • 　
    -
    1998.03

    University of Miyazaki   Faculty of Engineering   Department of Electrical and Electronic Engineering   Graduated

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Graduate School 【 display / non-display 】

  • 　
    -
    2000.03

    University of Miyazaki  Graduate School, Division of Engineering  Master's Course  Completed

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Degree 【 display / non-display 】

  • Kyushu University -  Doctor (Engineering)

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Field of expertise (Grants-in-aid for Scientific Research classification) 【 display / non-display 】

  • Intelligent informatics

  • Kansei informatics

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Papers 【 display / non-display 】

  • Automatic Sleep Disorders Classification Using Ensemble of Bagged Tree Based on Sleep Quality Features

    Edita Rosana Widasari, Koichi Tanno, Hiroki Tamura

    Electronics   9   2020.03  [Refereed]

    Joint Work

  • The long short-term memory based on i-vector extraction for conversational speech gender identification approach

    Barlian Henryranu Prasetio,Hiroki Tamura,Koichi Tanno

    Artificial Life and Robotics     2020.01  [Refereed]

    Joint Work

    DOI

  • High-PSRR, Low-Voltage CMOS Current Mode Reference Circuit Using Self-Regulator with Adaptive Biasing Technique

    KONDO Kenya, TAMURA Hiroki, TANNO Koichi

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   103   486 - 491   2020  [Refereed]

    Joint Work

    　View Summary

    <p>In this paper, we propose the low voltage CMOS current mode reference circuit using self-regulator with adaptive biasing technique. It drastically reduces the line sensitivity (LS) of the output voltage and the power supply voltage dependence of the temperature coefficient (TC). The self-regulator used in the proposed circuit adaptively generates the minimum voltage required the reference core circuit following the PVT (process, voltage and temperature) conditions. It makes possible to improve circuit performances instead of slightly increasing minimum power supply voltage. This proposed circuit has been designed and evaluated by SPICE simulation using TSMC 65nm CMOS process with 3.3V (2.5V over-drive) transistor option. From simulation results, LS is reduced to 0.0065%/V under 0.8V < <i>V<sub>DD</sub></i> < 3.0V. TC is 67.6ppm/°C under the condition that the temperature range is from -40°C to 125°C and <i>V<sub>DD</sub></i> range is from 0.8V to 3.0V. The power supply rejection ratio (PSRR) is less than -80.4dB when <i>V<sub>DD</sub></i> is higher than 0.8V and the noise frequency is 100Hz. According to the simulation results, we could confirm that the performances of the proposed circuit are improved compared with the conventional circuit.</p>

    DOI CiNii

  • A study on the gaze range calculation method during an actual car driving using eyeball angle and head angle information

    Sakurai K., Tamura H.

    Sensors (Switzerland)   19   2019.11  [Refereed]

    Joint Work

    　View Summary

    © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Car operation requires advanced brain function. Currently, evaluation of the motor vehicle driving ability of people with higher brain dysfunction is medically unknown and there are few evaluation criteria. The increase in accidents by elderly drivers is a social problem in Japan, and a method to evaluate whether elderly people can drive a car is needed. Under these circumstances, a system to evaluate brain dysfunction and driving ability of elderly people is needed. Gaze estimation research is a rapidly developing field. In this paper, we propose the gaze calculation method by eye and head angles. We used the eye tracking device (TalkEyeLite) made by Takei Scientific Instruments Cooperation. For our image processing technique, we estimated the head angle using the template matching method. By using the eye tracking device and the head angle estimate, we built a system that can be used during actual on-road car operation. In order to evaluate our proposed method, we tested the system on Japanese drivers during on-road driving evaluations at a driving school. The subjects were one instructor of the car driving school and eight general drivers (three 40–50 years old and five people over 60 years old). We compared the gaze range of the eight general subjects and the instructor. As a result, we confirmed that one male in his 40s and one elderly driver had narrower gaze ranges.

    DOI

  • Semi-supervised deep time-delay embedded clustering for stress speech analysis

    Prasetio B., Tamura H., Tanno K.

    Electronics (Switzerland)   8   2019.11  [Refereed]

    Joint Work

    　View Summary

    © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Real stressed speech is affected by various aspects (individual characteristics and environment) so that the stress patterns are diverse and different on each individual. To this end, in our previous work, we performed an unsupervised clustering method that able to self-learning manner by mapping the feature representations of the stress speech and clustering tasks simultaneously, called deep time-delay embedded clustering (DTEC). However, DTEC has not confirmed yet the compatibility between the output class and informational classes. Therefore, we proposed semi-supervised time-delay embedded clustering (SDTEC) as a new framework of semi-supervised in DTEC. SDTEC incorporates the prior information of pairwise constraints in the embedding layer and simultaneously learns the feature representation and the clustering assignments. The prior information was used to guide the clustering procedure so that the points that belong to the incorrect cluster can be corrected. The effectiveness of the proposed SDTEC was evaluated by comparing it with some baseline methods in terms of the clustering error rate (CER). Moreover, to demonstrate SDTEC’s capabilities, we conducted a comprehensive ablation study. Based on experiment results, SDTEC outperformed the baseline methods and achieves state-of-the-art results in semi-supervised clustering.

    DOI

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Review Papers 【 display / non-display 】

  • Robot and Neuroscience Technology: Computational and Engineering Approaches in Medicine

    Hiroki Tamura, Shangce Gao, Qixin Cao, Chuntao Leng, Hui Yu, Harold Szu

    Computational Intelligence and Neuroscience     2016  [Refereed]  [Invited]

    Introduction and explanation (scientific journal)   Joint Work

    DOI

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Presentations 【 display / non-display 】

  • Development of indoor user location tracking system using RFID smartphone

    Y. Furukawa，H. Tamura，K. Tanno

    Proc. of The 2015 Int. Symp. on Applied Mechanics and Robotics  2015.08  -  2015.08  JSTさくらサイエンスプラン、宮崎大学、上海交通大学

  • Development of imouse Cursor Control System Using Surface EMG and Facial Direction

    Y. Cheng，H. Tamura，K. Tanno

    Proc. of The 2015 Int. Symp. on Applied Mechanics and Robotics  2015.08  -  2015.08  JSTさくらサイエンスプラン、宮崎大学、上海交通大学

  • Development of Mouse Cursor Control System using EOG under 3 Electrodes Method

    M. Yan, H.Tamura, K. Tanno

    Proc. of The 2015 Int. Symp. on Applied Mechanics and Robotics  2015.08  -  2015.08  JSTさくらサイエンスプラン、宮崎大学、上海交通大学

  • A Study on the Human Motion State Estimation Method Using the Waveform of One Acceleration Sensor

    H.Matsumoto，H. Tamura，K. Tanno

    Proc. of The 2015 Int. Symp. on Applied Mechanics and Robotics  2015.08  -  2015.08  JSTさくらサイエンスプラン、宮崎大学、上海交通大学

  • Development of the Communication System using ElectroOculogram and Camera

    Sou GO， Mingmin Yan， Hiroki Tamura， Koichi Tanno

    The Seventh International Conference on Innovative Computing, Information and Control (ICICIC2012)  2012.11  -  2012.11  ICIC International

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