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Affiliation |
Center for Information Technology and Management |
YOKOYAMA Hiroshi
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Graduating School 【 display / non-display 】
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1985.04-1989.03
Akita University Graduated
Graduate School 【 display / non-display 】
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1991.04-1993.03
Akita University Master's Course Completed
Campus Career 【 display / non-display 】
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2015.04-2025.03
Akita University Center for Information Technology and Management Associate Professor
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2010.04-2015.03
Akita University Graduate School of Engineering and Resource Science Department of Computer Science and Engineering Lecturer
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1999.02-2010.03
Akita University Lecturer
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1998.04-1999.01
Akita University Research Assistant
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1993.04-1998.03
Akita University Research Assistant
Academic Society Affiliations 【 display / non-display 】
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1994.05-Now
United States
IEEE Computer Society
Research Areas 【 display / non-display 】
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Informatics / Computer system / VLSI testing
Research Achievements 【 display / non-display 】
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Analysis of water quality conditions of lake hachiroko using fuzzy c-means
Matsui K.
Journal of Advanced Computational Intelligence and Intelligent Informatics ( Journal of Advanced Computational Intelligence and Intelligent Informatics ) 23 ( 3 ) 456 - 464 2019.05 [Refereed]
Research paper (journal) Domestic Co-author
<p>Lake Hachiroko, Japan, has many water quality issues, evident from phenomena such as green algae blooms. Understanding the details of the surface water quality of the lake, and the effect of seasons on the quality, is important. In our previous studies, we conducted fuzzy regression analysis of remote sensing data and direct measurements of water quality. The results showed that estimation maps of water quality were well created, using only five data points of the water quality parameters. To obtain maps that are in good agreement with the experimental data, remote sensing data and water quality values should be acquired simultaneously. However, performing such simultaneous observations can affect the preparation of the water quality estimation maps. We overcame this obstacle by using fuzzy c-means clustering (FCM), and considered the effect of specific disturbances and uncertainties on the remote sensing data. Furthermore, FCM using only remote sensing data creates estimation maps in which relative water surface conditions are classified. Therefore, determining the relationship between FCM results and water quality facilitates the creation of low-cost, high-frequency water quality estimation maps. Our results indicated that FCM was particularly effective in determining the presence of suspended solids (SS) during water quality analysis. However, the relationship between FCM results and water quality has not been determined in detail. In this study, we analyzed the water quality conditions of Lake Hachiroko with FCM using the data collected by the Advanced Space-borne Thermal Emission and Reflection Radiometer on Terra and, the Operational Land Imager on Landsat-8. In addition, FCM results were compared with the maps created by fuzzy regression analysis and the actual conditions of water pollution. The results indicated that (i) the maps created using FCM are effective in determining the water surface conditions, (ii) the FCM maps using data obtained during August and September have a strong relationship with biochemical oxygen demand (BOD) and SS, and (iii) the FCM maps using data obtained during May and June have a strong relationship with chemical oxygen demand (COD), SS, and total nitrogen (T-N).</p>
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Development of a 3D Hair Simulator to Support a Hairdresser's Haircut
S. Sato, H. Yokoyama, Y. Kageyama, C. Ishizawa, M. Nishida and K. Konishi
International Journal of the Society of Materials Engineering for Resources Vol.23, No.2, (2018)(in press) 137 - 141 2018.09 [Refereed]
Research paper (journal) Domestic Co-author
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Electrical test of resistive and capacitive open defects at data bus in 3D memory IC
Masaki Hashizume, Yudai Shiraishi, Hiroyuki Yotsuyanagi, Hiroshi Yokoyama, Tetsuo Tada, Shyue-Kung Lu
Journal of Telecommunication, Electronic and Computer Engineering Volume 9, Issue 3-2 39 - 42 2017.09 [Refereed]
Research paper (journal) Domestic Co-author
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Application of Fuzzy C-means for Understanding Water Quality in Lake Hachiroko
Kageyama, Y., Izumi, A., Nishida, M., and Yokoyama
IEEJ Transactions on Electrical and Electronic Engineering Vol. 11, No. 6, p. 835-837 2016.08 [Refereed]
Research paper (journal) Domestic Co-author
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Improving Random Pattern Testability with Partial Circuit Duplication Approach
H. Yokoyama, Wen Xiaoqing and H. Tamamoto
IEICE Trans. on Information and Systems Vol. E81-D, No. 7 pp. 654-659 1998.07 [Refereed]
Research paper (journal) Domestic Co-author
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Learning data conditions for resolution improvement using UAV data
Kai Matsui, Hikaru Shirai, Yoichi Kageyama and Hiroshi Yokoyama
2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020 ( 2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020 ) 2020.12 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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Recovery of Defective TSVs with A Small Number of Redundant TSVs in 3D Stacked ICs
伊喜利 勇貴,橋爪 正樹, 四柳 浩之, 横山 洋之, Lu Shyue-Kung
the 21st IEEE Workshop on RTL and High Level Testing 2020.11 [Refereed]
Research paper (international conference proceedings) International Co-author
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Temperature Sensing with a Relaxation Oscillator in CMOS ICs
Fumiya Sako , Yuki Ikiri , Masaki Hashizume , Hiroyuki Yotsuyanagi ,Hiroshi Yokoyama , and Shyue-Kung Lu
ITC-CSCC 2020 - 35th International Technical Conference on Circuits/Systems, Computers and Communications ( ITC-CSCC 2020 - 35th International Technical Conference on Circuits/Systems, Computers and Communications ) 141 - 144 2020.07 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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Fuzzy C-Means with Stepwise Level Slice Processing for Water Quality Analysis in Lake Hachiroko
Kai Matsui, Yoichi Kageyama , Hiroshi Yokoyama
The 7th International Conference on Intellignet Systems and Image Processing 2019 (Taipei Taiwan) 292 - 298 2019.09 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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GA based Efficient Weight Set Generation Method for Power Aware Weighted Random BIST
Hiroshi Yokoyama and Yoichi Kageyama
The 19th workshop on RTL and high level testing (WRTLT2018) Paper No. 19, USB-MEMORY 2018.10 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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Matsui Kai, Shirai Hikaru, Kageyama Yoichi, Yokoyama Hiroshi
Proceedings of the Japan Joint Automatic Control Conference ( The Japan Joint Automatic Control Conference ) 63 ( 0 ) 236 - 239 2020.11 [Refereed]
Research paper (research society, symposium materials, etc.) Domestic Co-author
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Matsui Kai, Kageyama Yoichi, Yokoyama Hiroshi
Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2018 ( 0 ) 105 - 106 2018.01
Research paper (research society, symposium materials, etc.) Domestic Co-author
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Ishinomaki Yugo, Yokoyama Hiroshi, Kageyama Yoichi
Proceedings of the Japan Joint Automatic Control Conference ( The Japan Joint Automatic Control Conference ) 61 ( 0 ) 364 - 365 2018 [Refereed]
Research paper (research society, symposium materials, etc.) Domestic Co-author
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Traveling Route Derivation Method in Logistics Warehouses with A* and Genetic Algorithm
Sugihara Kaito, Ito Yudai, Kageyama Yoichi, Yokoyama Hiroshi, Hashimoto Shuji, Sato Noriaki
Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2022 ( 0 ) 60 - 61 2022
The modern distribution industry demands improved efficiency of their logistics systems to lower prices while maintaining product quality. However, the efficiency of "picking", performing collection work in the racks in a warehouse, which accounts for a large percentage of the total cost of logistics, has not yet improved.
In this study, we propose a traveling route derivation method that allows the warehouse layout to be set arbitrarily. Specifically, we have combined the A* and genetic algorithms to reduce the walking distance of picking workers to improve picking efficiency in a warehouse. Furthermore, we have simulated the route derivation during picking work by assuming practical work, compared the walking distances with the brute-force method, and evaluated the usefulness of the proposed method. -
Development of Interactive E-learning Contents for Understanding of Mathematical Concepts
KOBAYASHI Yayoi, YAMAMOTO Minoru, YOKOYAMA Hiroshi, KOBAYASHI Mahito
Bulletin of Seirei Women's Junior College ( Seirei Women's Junior College ) 50 ( 0 ) 102 - 108 2022
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Water Quality Analysis of Lake Hachiroko Using Fuzzy C-means Clustering with ASTER Data
MATSUI Kai, KAGEYAMA Yoichi, NISHIDA Makoto, YOKOYAMA Hiroshi
Proceedings of the Fuzzy System Symposium ( Japan Society for Fuzzy Theory and Intelligent Informatics ) 33 ( 0 ) 731 - 732 2017
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◆Original paper【 display / non-display 】
◆International conference proceedings【 display / non-display 】
◆Research society, Symposium materials, etc.【 display / non-display 】
◆Other【 display / non-display 】
Grant-in-Aid for Scientific Research 【 display / non-display 】
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Grant-in-Aid for Scientific Research(B)
Project Year： 2017.04 - 2021.03
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Grant-in-Aid for Scientific Research(B)
Project Year： 2017.04 - 2021.03
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Grant-in-Aid for Scientific Research(B)
Project Year： 2017.03 - 2021.03