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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SeMI | 2024-01-19 11:05 |
Yamanashi | Raki House Kaiji | 5G throughput prediction for 28GHz cell area using surrounding spatial information Hisashi Nagata, Riichi Kudo, kahoko takahashi, Fujita Takafumi (NIPPON TELEGRAPH AND TELEPHONE CORPORATION), Yuya Aoki, Morihiro Yoshifumi (NTT DOCOMO, INC.)  SeMI2023-67 |
Every thing is connected to the network, and the amount of mobile traffic is increasing year by year. Therefore, the use... [more] | SeMI2023-67 pp.94-99 |
| AP | 2023-10-20 11:30 |
Iwate | Iwate University (Primary: On-site, Secondary: Online) |
[Tutorial Lecture]
Wireless link quality prediction using spatial information Riichi Kudo, Kahoko Takahashi, Hisashi Nagata, Tomoya Kageyama (NTT) AP2023-124 |
The development of wireless communication technologies is accelerating to widespread the various connected devices and e... [more] | AP2023-124 pp.139-140 |
| SeMI, IPSJ-ITS, IPSJ-MBL, IPSJ-DPS | 2023-05-19 09:15 |
Okinawa | Okinawa Institute of Science and Technology (OIST) (Primary: On-site, Secondary: Online) |
An experimental evaluation of millimeter-wave link quality prediction using Wi-Fi CSI and supervised learning Shoki Ohta, Kanare Kodera, Takayuki Nishio (Tokyo Tech) SeMI2023-10 |
This study experimentally evaluates our 60 GHz band millimeter-wave (mmWave) link quality prediction method using 5 GHz ... [more] | SeMI2023-10 pp.42-45 |
| SeMI, SeMI (Joint) |
2023-01-19 17:25 |
Tokushima | Naruto grand hotel (Primary: On-site, Secondary: Online) |
[Short Paper]
An Empirical Study of Data Reduction Method for Point Cloud-based Millimeter-wave Link Quality Prediction Shoki Ohta, Takayuki Nishio (Tokyo Tech), Riichi Kudo, Kahoko Takahashi, Hisashi Nagata (NTT) SeMI2022-93 |
This study experimentally evaluates a tradeoff between prediction accuracy and the number of points on a millimeter-wave... [more] | SeMI2022-93 pp.96-100 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2022-11-29 10:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Link Prediction from Text Content by NLP Graph Embedding
-- A Study on Chinese Journal Articles -- Tzu-Ying Yang, Hsuan Lei Shao, Chih-Chuan Fan, Wei-Hsin Wang (NTNU) NLC2022-9 SP2022-29 |
Abstract This paper is an extended research of the project “The Knowledge Database/ Graph of China-studies”. The main re... [more] | NLC2022-9 SP2022-29 pp.1-4 |
| RCS, SIP, IT | 2022-01-20 15:10 |
Online | Online | [Invited Talk]
Wireless link quality prediction using physical space information in Society 5.0 Riichi Kudo, Kahoko Takahashi, Hisashi Nagata, Tomoki Murakami, Tomoaki Ogawa (NTT) IT2021-44 SIP2021-52 RCS2021-212 |
Thanks to the great advances in wireless communication systems, many types of the wireless terminals are available. It i... [more] | IT2021-44 SIP2021-52 RCS2021-212 pp.93-94 |
| CQ, MIKA (Joint) |
2021-09-10 10:40 |
Online | Online | Link Quality Prediction using Multiple cameras in Indoor Environment for Wireless LAN Systems Kahoko Takahashi, Riichi Kudo, Tomoaki Ogawa (NTT) CQ2021-53 |
This paper proposes a received power prediction scheme that uses deep-neural-network based camera image object detection... [more] | CQ2021-53 pp.77-81 |
| IA, ICSS | 2021-06-22 11:15 |
Online | Online | A Solution for Recovering Missing Links in Network Topology using Sparse Modeling Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2021-14 ICSS2021-14 |
In recent years, sparse modeling, which is a statistical approach, has been applied to many practical problems mostly in... [more] | IA2021-14 ICSS2021-14 pp.74-79 |
| SeMI, IPSJ-MBL, IPSJ-UBI [detail] | 2021-03-02 10:50 |
Online | Online | A Proposal for Location Predictive V2V Routing Considering Link Quality Masahiro Nishioka, Michiko Harayama (Gifu Univ) SeMI2020-64 |
VANETs, the automotive IoT networks, are currently drawing attention to reducing accidents and improving vehicle conveni... [more] | SeMI2020-64 pp.35-40 |
| SIP, IT, RCS | 2021-01-22 12:30 |
Online | Online | Deep Learning based Link Quality Prediction for Autonomous Mobility Robots Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa (NTT) IT2020-102 SIP2020-80 RCS2020-193 |
Highly advanced mobility robots are expected to be managed, monitored, or efficiently controlled by using wireless commu... [more] | IT2020-102 SIP2020-80 RCS2020-193 pp.218-223 |
| IA | 2020-10-01 13:15 |
Online | Online | A Study on Recovering Network Topology with Missing Links using Sparse Modeling Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2020-3 |
In recent years, sparse modeling, which is a statistical approach, has been applied to many practical problems mostly in... [more] | IA2020-3 pp.10-13 |
| IBISML | 2020-03-11 09:45 |
Kyoto | Kyoto University (Cancelled but technical report was issued) |
Knowledge Graph Completion by Separating Transition and Score Functions Kenta Hama, Takashi Matsubara, Kuniaki Uehara (Kobe Univ.) IBISML2019-41 |
A knowledge graph is represented by a set of two entities and the relations, and used for various tasks such as informat... [more] | IBISML2019-41 pp.59-62 |
| RCS, SR, SRW (Joint) |
2020-03-06 11:30 |
Tokyo | Tokyo Institute of Technology (Cancelled but technical report was issued) |
A Study on Load Balancing in V2N Uplink using In-Advanced QoS Notification Ryo Hasegawa, Eiji Okamoto (NIT), Hidenori Akita (DENSO) RCS2019-379 |
Recently, the demands for utilizing the 5th Generation mobile communication system (5G) to connected cars and autonomous... [more] | RCS2019-379 pp.303-308 |
| MIKA (2nd) |
2019-10-03 11:15 |
Hokkaido | Hokkaido Univ. | [Poster Presentation]
Vision information based wireless link quality prediction Kahoko Takahashi, Riichi Kudo, Takeru Inoue, Kohei Mizuno (NTT) |
The advancement of wireless communication technologies is accelerating the widespread use of the various connected devic... [more] | |
| CQ | 2019-08-27 16:15 |
Hokkaido | Hakodate arena | [Invited Talk]
Potentiality of machine learning based next generation wireless communication systems for smart connected devices Riichi Kudo, Kahoko Takahashi, Takeru Inoue, Kohei Mizuno (NTT) CQ2019-72 |
The connected devices which are autonomously operated need to recognize its position and surrounding environment by usin... [more] | CQ2019-72 pp.79-84 |
| NS | 2019-04-18 16:50 |
Kagoshima | Tenmonkan Vision Hall | [Invited Talk]
An Introduction of Social Network Analysis Techniques and their Applications to Socially Aware Networking Sho Tsugawa (Univ. of Tsukuba) NS2019-10 |
Socially aware networking is an emerging research field that aims to improve the current networking technologies and rea... [more] | NS2019-10 pp.55-60 |
| SR | 2018-05-24 10:30 |
Tokyo | Tokyo big sight | [Invited Talk]
Wireless Link Quality Prediction And Wireless Control Through Machine Learning Takayuki Nishio (Kyoto Univ.) SR2018-1 |
In this talk, wireless link quality prediction and control methods based on supervised learning from sensing information... [more] | SR2018-1 pp.1-6 |
| NS, IN (Joint) |
2018-03-02 13:30 |
Miyazaki | Phoenix Seagaia Resort | MPR Selection and Routing Methods Using Link Disconnection Prediction in OLSR Protocol Wataru Nagata, Akira Toyozaki, Masaki Hanada (Tokyo Univ. of Information Sciences), Hidehiro Kanemitsu (Waseda Univ.), Yasuo Nagai (Tokyo Univ. of Information Sciences) IN2017-134 |
OLSR is one of well-known proactive protocols for MANETs. OLSR may cause the reduction of network performance because ... [more] |
IN2017-134 pp.267-272 |
| IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2017-02-20 11:30 |
Hokkaido | Hokkaido Univ. | A note on quantification of relationship between users and musical pieces using graph structure analysis (2)
-- Verification of using link prediction -- Shohei Kinoshita, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a quantification method of relationship between users and musical pieces.Our proposed relationship i... [more] | |
| ITE-ME, IE, EMM, LOIS, IEE-CMN [detail] | 2016-09-16 14:00 |
Aichi | Aichi Prefectural University | A study on the Multiple Label Propagation Algorithm Considering Properties of the LOD Toshitaka Maki, Kazuki Takahashi, Toshihiko Wakahara, Akihiro Yamaguchi (FIT), Akihisa Kodate (Tsuda), Toru Kobayashi (Nagasaki Univ), Sonehara Noboru (NII) LOIS2016-24 IE2016-61 EMM2016-50 |
The label propagation is a semi-supervised learning method to grant to classification labels to the nodes under the assu... [more] | LOIS2016-24 IE2016-61 EMM2016-50 pp.49-54 |
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