Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NC, MBE (Joint) |
2024-03-11 11:15 |
Tokyo |
The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Discrimination between dementia groups and healthy elderlies based on time-series variations of functional connectivity Chisho Takeoka, Toshimasa Yamazaki (KIT), Yoshiyuki Kuroiwa, Kimihiro Fujino, Toshiaki Hirai (Teikyo), Hidehiro Mizusawa (NCNP) MBE2023-70 |
Alzheimer’s disease is the most famous dementia in the world. Electroencephalography (EEG), which is excellent at time r... [more] |
MBE2023-70 pp.9-12 |
SeMI, IPSJ-UBI, IPSJ-MBL |
2024-02-29 15:50 |
Fukuoka |
|
Development and Evaluation of the Water Flow Prediction Model for Remote Control of Sluice Gates in the Onga River Takahiro Ueno (Fukuoka Univ.), Koki Ozono (AJP), Masayoshi Ohashi (Fukuoka Univ.) SeMI2023-77 |
Our laboratory is engaged in the research and development of a system for the remote control and monitoring of sluice ga... [more] |
SeMI2023-77 pp.37-41 |
ICM, NS, CQ, NV (Joint) |
2023-11-22 09:00 |
Ehime |
Ehime Prefecture Gender Equality Center (Primary: On-site, Secondary: Online) |
Evaluation of Improvement Plans to Increase the Efficiency of Performance Data Transfer for Server Systems Chika Iiyama (Ocha Univ.), Akira Hirai, Mari Yamaoka, Naoto Fukumoto (Fujitsu), Masato Oguchi (Ocha Univ.) NS2023-117 |
In recent years, demand for shared use of multiple servers has been increasing. In order to perform load balancing on th... [more] |
NS2023-117 pp.38-43 |
NS |
2023-10-05 13:25 |
Hokkaido |
Hokkaidou University + Online (Primary: On-site, Secondary: Online) |
[Invited Lecture]
IoT Device Identification based on Traffic Pattern Analysis with Two-stage Clustering Mizuki Asano, Takumi Miyoshi, Taku Yamazaki (Shibaura Inst. Tech.) NS2023-90 |
In recent years, the realization of smart homes, which will provide more effective and comfortable lifestyles by leverag... [more] |
NS2023-90 pp.105-110 |
WIT |
2023-06-16 16:15 |
Okinawa |
Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
Proposing a Feature-Analysis Method of Finger-Movement Data for Predicting Cognitive Function of Elderly People Hayato Seiichi, Sinan Chen, Atsuko Hayashi, Masahide Nakamura (Kobe Univ.) WIT2023-6 |
In recent years, a growing body of research has suggested a relationship between cognitive function and manual dexterity... [more] |
WIT2023-6 pp.30-35 |
NLP, MSS |
2023-03-15 10:40 |
Nagasaki |
(Primary: On-site, Secondary: Online) |
Spectral analysis of synchropahsor data in a campus distribution grid: Comparison of numerical methods Munetaka Noguchi (Osaka Prefecture Univ.), Yoshihiko Susuki (Kyoto Univ.), Atsushi Ishigame (Osaka Metropolitan Univ.) MSS2022-64 NLP2022-109 |
Recently, the so-called micro-Phasor Measurement Unit (μPMU) with high-resolution capability has been expected as a new ... [more] |
MSS2022-64 NLP2022-109 pp.11-16 |
RISING (3rd) |
2022-10-31 13:00 |
Kyoto |
Kyoto Terrsa (Day 1), and Online (Day 2, 3) |
[Poster Presentation]
Network Anomaly Detection Method Based on Communication Volume Changes in Edge Switches Yuya Nakanishi, Shingo Ata (Osaka City Univ.) |
Early detection of failures and anomalies that occur in the network and prompt recovery processing are essential for sta... [more] |
|
PRMU |
2022-10-21 10:45 |
Tokyo |
Miraikan - The National Museum of Emerging Science and Innovation (Primary: On-site, Secondary: Online) |
Subspace based Anomaly Detection Takumi Kanai, Naoya Sogi (Univ. Tsukuba), Atsuto Maki (KTH), Kazuhiro Fukui (Univ. Tsukuba) PRMU2022-25 |
In this paper, we propose a change point detection method in time series data by incorporating the concept of difference... [more] |
PRMU2022-25 pp.18-23 |
SIP |
2022-08-25 14:15 |
Okinawa |
Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Multiresolution Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to Riverbed State Estimation Eisuke Kobayashi, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka (Niigata Univ.) SIP2022-54 |
In this report, we propose a method that incorporates multi-resolution representation into Convolutional-Sparse-Coded Dy... [more] |
SIP2022-54 pp.25-30 |
KBSE, SWIM |
2022-05-20 15:00 |
Tokyo |
(Primary: On-site, Secondary: Online) |
Practical Application of Self-Adaptive Anomaly Detection Method Using XAI Shimon Sumita, Hiroyuki Nakagawa, Tatsuhiro Tsuchiya (Osaka Univ.) KBSE2022-3 SWIM2022-3 |
In this study, we examine the use of XAI to improve the performance of a self-adaptive anomaly detection method. As a sp... [more] |
KBSE2022-3 SWIM2022-3 pp.13-18 |
MICT, EMCJ (Joint) |
2022-03-04 16:25 |
Online |
Online |
A synchronized measurement system for WBAN channel modeling by human motion parameters Akira Saito, Takahiro Aoyagi (Tokyo Tech) MICT2021-111 |
The development of WBAN channel models requires a lot of experiments and simulations. In order to reduce the number of e... [more] |
MICT2021-111 pp.53-58 |
RCS, SIP, IT |
2022-01-20 13:40 |
Online |
Online |
Received Power Prediction of 60 GHz Millimeter-Wave Propagation in Indoor Environment from Time-Series Images Using Neural Networks Khanh Nam Nguyen, Kenichi Takizawa (NICT) IT2021-55 SIP2021-63 RCS2021-223 |
A millimeter-wave (mmWave) indoor propagation environment with obstacles in 60 GHz frequency band is set up where receiv... [more] |
IT2021-55 SIP2021-63 RCS2021-223 pp.149-154 |
IN |
2022-01-18 11:35 |
Online |
Online |
Evaluation on Prediction Method for Missing Probability of Sensor Value based on Hierarchical Structure of Missing Value Norifumi Hirata, Osamu Maeshima, Kiyohito Yoshihara (KDDI Research) IN2021-25 |
Collecting sensor data via networks is important for IoT (Internet of Things) services.However, sensors sometimes have m... [more] |
IN2021-25 pp.7-12 |
PRMU |
2021-12-16 15:25 |
Online |
Online |
[Short Paper]
Evaluation of Time Series Causal Discovery Method Using Plant Simulator Kazuki Koyama, Daigo Fujiwara, Keisuke Kiritoshi, Tomomi Okawachi, Tomonori Izumitani (NTT Communications), Keisuke Asahara, Shohei Shimizu (Shiga Univ.) PRMU2021-34 |
In order to improve operation, the use of process data consisting of time-series data from sensors and other sources is ... [more] |
PRMU2021-34 pp.57-60 |
IN, IA (Joint) |
2021-12-16 14:50 |
Hiroshima |
Higashi-Senda campus, Hiroshima Univ. (Primary: On-site, Secondary: Online) |
[Short Paper]
Collecting and Analyzing Campus Wireless LAN Quality Information Using Time-Series Database Atsuto Nakano, Tohru Kondo, Reiji Aibara (HU) IA2021-32 |
Wireless LAN in campus network is an essential communications infrastructure that supports education and research activi... [more] |
IA2021-32 pp.22-23 |
CQ, ICM, NS, NV (Joint) |
2021-11-26 17:15 |
Fukuoka |
JR Hakata Stn. Hakata EkiHigashi Rental Room (Primary: On-site, Secondary: Online) |
Proposal of change detection technology using cluster transition tensor Shoko Takahashi, Kei Takeshita (NTT) CQ2021-75 |
As in all service fields, the AI-based operation automation is progressing in the communication field as well.
Once the... [more] |
CQ2021-75 pp.49-54 |
NLP, CCS |
2021-06-11 10:50 |
Online |
Online |
A Study on Prediction of Synchrophasor Time-Series Data of In-Campus Distribution Voltage Using Gaussian Process Regression Munetaka Noguchi (Osaka Pref Univ.), Yoshihiko Susuki (Osaka Pref Univ./JST), Atsushi Ishigame (Osaka Pref Univ.) NLP2021-3 CCS2021-3 |
Due to recent penetration of distributed energy resources, dynamics of power distribution systems have been complicated ... [more] |
NLP2021-3 CCS2021-3 pp.10-13 |
IBISML |
2021-03-03 11:15 |
Online |
Online |
IBISML2020-46 |
Developing a profitable trading strategy is a central problem in the financial industry. In this presentation, we develo... [more] |
IBISML2020-46 p.38 |
HCGSYMPO (2nd) |
2020-12-15 - 2020-12-17 |
Online |
Online |
Development and evaluation of time series labeling tool based on work occurrence prediction for restaurant service Karimu Kato, Takahiro Miura, Ryosuke Ichikari, Takashi Okuma, Takeshi Kurata (AIST) |
The cost to create training data for supervised learning has been a problem. Particularly, it takes a long time to label... [more] |
|
LOIS |
2020-03-12 11:05 |
Okinawa |
Nobumoto Ohama Memorial Hall (Cancelled but technical report was issued) |
Distributed active learning achieving both of monitoring and efficient time-series data sampling for edge computing Osamu Saisho, Keiichiro Kashiwagi, Yui Saito, Tomoyuki Fujino (NTT) LOIS2019-73 |
For edge computing, there is still a great demand to upload only meaningful data to cloud,. However there is no practica... [more] |
LOIS2019-73 pp.97-101 |