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Paper Abstract and Keywords
Presentation 2022-01-28 12:10
A Study on Detection of Subjects with Unique Brain Structures Using Eigenvalues of Laplacian Matrices
Ohisi Yuki, Taniguchi Toyoaki, Segawa Eriko, Sakumoto Yusuke (Kwansei Gakuin Univ) CQ2021-93
Abstract (in Japanese) (See Japanese page) 
(in English) In order to understand the complex behavior of brains, many works have analyzed macroscale connectomes between the aggregation of nerve cells in the brain. The analysis of macroscale connectomes would be useful in detecting subjects (e.g., subjects with psychiatric disorders) with a unique connectome. In this paper, we discuss a method for detecting subjects with a unique connectome based on LAD (Laplacian Anomaly Detection), which have been used to detect anomalies in social. networks and communication networks. In addition, through experiments using actual connectome data, we evaluate the accuracy of the method based on LAD.
Keyword (in Japanese) (See Japanese page) 
(in English) Network Analysis / Spectral Graph Theory / Laplacian Matrix / Anomaly Detection / Brain Connectome / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 357, CQ2021-93, pp. 94-99, Jan. 2022.
Paper # CQ2021-93 
Date of Issue 2022-01-20 (CQ) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF CQ2021-93

Conference Information
Committee CQ CBE  
Conference Date 2022-01-27 - 2022-01-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Kanazawa（Ishikawa Pref.） 
Topics (in Japanese) (See Japanese page) 
Topics (in English) AR/VR, Broadcasting Service, Video/Voice Services Quality, High Realistic, User Behavior/Psychology, User Experience, Media Quality, Network Quality and QoS Control, Networks and Communications at Disaster, User Behavior, Machine Learning, Video Communication, etc. 
Paper Information
Registration To CQ 
Conference Code 2022-01-CQ-CBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Detection of Subjects with Unique Brain Structures Using Eigenvalues of Laplacian Matrices 
Sub Title (in English)  
Keyword(1) Network Analysis  
Keyword(2) Spectral Graph Theory  
Keyword(3) Laplacian Matrix  
Keyword(4) Anomaly Detection  
Keyword(5) Brain Connectome  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Ohisi Yuki  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
2nd Author's Name Taniguchi Toyoaki  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
3rd Author's Name Segawa Eriko  
3rd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
4th Author's Name Sakumoto Yusuke  
4th Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
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Speaker Author-1 
Date Time 2022-01-28 12:10:00 
Presentation Time 25 minutes 
Registration for CQ 
Paper # CQ2021-93 
Volume (vol) vol.121 
Number (no) no.357 
Page pp.94-99 
#Pages 6 
Date of Issue 2022-01-20 (CQ) 

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