Committee 
Date Time 
Place 
Paper Title / Authors 
Abstract 
Paper # 
RCS 
20230614 10:40 
Hokkaido 
Hokkaido University, and online (Primary: Onsite, Secondary: Online) 
Physical Layer Authentication Based on Mahalanobis Distance Over Spacially Correlated MIMO Channels Kenta Miwa (UEC), Kengo Ando, Giuseppe Abreu (CU), Koji Ishibashi (UEC) RCS202334 
This paper focuses on an authentication of a legitimate transmitter over multipleinput multipleoutput (MIMO) channels ... [more] 
RCS202334 pp.3742 
DC 
20211210 15:45 
Kagawa 
(Primary: Onsite, Secondary: Online) 
Study on Detection Method of the Level Crossing Rod Breakage using the Machine Learning Hiroshi Shida (NESCO), Noriyuki Shiraishi (JR Shikoku), Hiroshi Takahashi (Ehime Univ) DC202162 
The level crossing is the only part, which public road intersects a railroad. The level crossing rod is an important equ... [more] 
DC202162 pp.3843 
HIP 
20211021 14:25 
Online 
Online 
Performance Indicator for Linking Eye and Body Movements Shuichi Fukuda (Keio Univ) HIP202135 
With materials getting soft, it becomes necessary to directly interact with objects. Until now, we could understand
h... [more] 
HIP202135 pp.2934 
DC 
20201211 14:40 
Hyogo 
(Primary: Onsite, Secondary: Online) 
Study on Approach for the NS type Electric Point Machine Maintenance using Condition Based Maintenance Hiroshi Shida (JR WEST), Yuki Misaki (JR Shikoku), Hiroshi Takahashi (Ehime Univ) DC202064 
We study on approach for the condition based maintenance (CBM) about NS type electric point machine used widely in Japan... [more] 
DC202064 pp.2732 
DC 
20191220 15:40 
Wakayama 

Study on ConditionBased Maintenance of Railway Signal Equipment using the Machine Learning Hiroshi Shida (JR West), Akihiro Tamura, Takashi Ninomiya, Hiroshi Takahashi (Ehime Univ) DC201983 
Dependable systems are required high safety and reliability. Recently, conditionbased maintenance(CBM) is expected to m... [more] 
DC201983 pp.2530 
IBISML 
20171110 13:00 
Tokyo 
Univ. of Tokyo 
Safe Screening for Large Margin Metric Learning Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST) IBISML201764 
Large margin metric learning learns the optimal Mahalanobis distance for classification problem based on the margin maxi... [more] 
IBISML201764 pp.219226 
CPSY, RECONF, VLD, IPSJSLDM, IPSJARC [detail] 
20170124 16:55 
Kanagawa 
Hiyoshi Campus, Keio Univ. 
FPGA Implementation of Mahalanobis DistanceBased Outlier Detection for Streaming Data Yuto Arai, Shin'ichi Wakabayashi, Shinobu Nagayama, Masato Inagi (Hiroshima City Univ.) VLD201691 CPSY2016127 RECONF201672 
This paper focuses on a method to detect outliers in streaming data, and proposes a fast FPGA implementation of outlier ... [more] 
VLD201691 CPSY2016127 RECONF201672 pp.141146 
BioX, ITEME, ITEIST [detail] 
20160620 14:40 
Ishikawa 
IshikawaShikoKinenBunkaKoryukan 
Personal identification using the characteristics of floor vibration during walking Ryosuke Sugimoto, Yuma Mano, Juhyon Kim, Kazuki Nakajima (Univ. of Toyama) BioX20161 
(To be available after the conference date) [more] 
BioX20161 pp.1518 
VLD, CPSY, RECONF, IPSJSLDM, IPSJARC [detail] 
20160119 14:20 
Kanagawa 
Hiyoshi Campus, Keio University 
GPGPU Implementation of the MSD Method for Outlier Detection and Its Experimental Evaluation Shotaro Asano, Masato Inagi, Shinobu Nagayama, Shin'ichi Wakabayashi (Hiroshima City Univ.) VLD201583 CPSY2015115 RECONF201565 
In recent years，as the information，communication and sensing technologies advance，data streams have been continuously gr... [more] 
VLD201583 CPSY2015115 RECONF201565 pp.3742 
IBISML 
20151126 15:00 
Ibaraki 
Epochal Tsukuba 
[Poster Presentation]
Approximate Distribution Followed by A Principal Component Term Corresponding with the Population Eigenvalue of zero value in the Q Statistic Yasuyuki Kobayashi (Teikyo Univ.) IBISML201552 
The Mahalanobis distance requires all the population eigenvalues of the population covariance matrix larger than zero. H... [more] 
IBISML201552 pp.17 
IBISML 
20150305 16:45 
Kyoto 
Kyoto University 
Effects of Numerical Errors against Sample Mahalanobis Distances Yasuyuki Kobayashi (Teikyo Univ.) IBISML201490 
I have studied the detail conditions that the numerical errors of sample Mahalanobis distances (T^2=y^' S^(1) y) of the... [more] 
IBISML201490 pp.3946 
IBISML 
20141117 17:00 
Aichi 
Nagoya Univ. 
[Poster Presentation]
Approximate Models of Probability Distributions for Principal Components of Sample Mahalanobis Distances
 About Each Element and Partial Sum of Sample Mahalanobis Distances  Yasuyuki Kobayashi (Teikyo Univ.) IBISML201437 
Probability distributions of the principal components and their partial sum, into which a sample Mahalanobis distance is... [more] 
IBISML201437 pp.1724 
IT 
20140717 10:10 
Hyogo 
Kobe University 
Distance Metric Learning with Low Computational Complexity based on Ensemble of Lowdimensional Matrixes Hiroshi Saito, Fumihiro Yamazaki, Kenta Mikawa, Masayuki Goto (Waseda Univ.) IT201412 
The distance metric learning is the approach which enables to acquire a good metric for automatic data classification. I... [more] 
IT201412 pp.712 
IBISML 
20140306 14:30 
Nara 
Nara Women's University 
Study about OverLearning Phenomenon of Sample Mahalanobis Distances Yasuyuki Kobayashi (Teikyo Univ.) IBISML201370 
When the learning sample size n is near the dimensionality p, the discrepant phenomenon between the distribution of the ... [more] 
IBISML201370 pp.2330 
PRMU, IPSJCVIM, MVE [detail] 
20140124 10:40 
Osaka 

* Wataru Takei, Katsuya Hosobori, Tsuyoshi Kato (Gunma Univ.), Shinichiro Omachi (Tohoku Univ.) PRMU2013113 MVE201354 
In computer vision, image crassification has been one of the central
tasks and studied by many researchers.
To deal w... [more] 
PRMU2013113 MVE201354 pp.201206 
PRMU, IBISML, IPSJCVIM [detail] 
20130902 10:00 
Tottori 

A proposal of simple correcting scheme for sample Mahalanobis distances using Delta method Yasuyuki Kobayashi (Teikyo Univ.) PRMU201337 IBISML201317 
In statistical machine learning technology, it is difficult to ignore errors between sample Mahalanobis distances estima... [more] 
PRMU201337 IBISML201317 pp.2530 
PRMU, MVE, IPSJCVIM (Joint) [detail] 
20130124 10:40 
Kyoto 

A Study on Recognition Algorithm of Low Quality Handprinted Characters Using Feature Selection Method Based on the Criterion of Skewness Maximization Masato Suzuki, Daisuke Kitakoshi (TNCT), Akiyo Matsumoto (Tohoku Gakuin Univ.) PRMU2012110 MVE201275 
Mahalanobis distance is a quadratic descriminant function which can reognize handprinted characters
in high accuracy by... [more] 
PRMU2012110 MVE201275 pp.251256 
PRMU 
20121004 15:50 
Chiba 

Construction of the guide system on Android tablets Yasuaki Miyauti, Yuji Nakagawa (Ehime Univ.) PRMU201259 
The guide system which shows a visitor the information on a showpiece is offered in a part of museum or art museum. We d... [more] 
PRMU201259 pp.4145 
MBE 
20111013 13:50 
Osaka 
Osaka ElectroCommunication University 
A consideration of diagnosis support to pancreas cancer using data mining from blood exam Tatsunori Tanaka, Tetsuo Sato, Kotaro Minato (NAIST), Yasushi Matsumura (Osaka U Hospital) MBE201152 
The purpose of this study is to extract factors correlated with pancreatic cancer and to develop a method of discriminan... [more] 
MBE201152 pp.1317 
CPSY, DC, IPSJSLDM, IPSJEMB [detail] 
20110318 09:40 
Okinawa 

Examination of network fault detection method by use of AFM Isao Shimokawa, Toshiaki Tarui, Hiroki Miyamoto, Tomohiro Baba (hitachi) CPSY201071 DC201070 
We proposed network fault detection method for quickly specifying the router and the server that became a bottleneck in ... [more] 
CPSY201071 DC201070 pp.3138 