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Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| 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 |
|
| 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 |
| 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 |
| 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 |
| 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] | |
| DE, IPSJ-DBS | 2019-12-24 16:55 |
Tokyo | National Institute of Informatics | Yuichiro Sakazaki, Rin Adachi, Jun Rokui (univ. of Shizuoka) DE2019-32 |
We proposed a model that integrates several types of data by multiple regression analysis and performs future prediction... [more] | DE2019-32 pp.93-98 |
| ET | 2018-03-03 16:05 |
Kochi | Kochi University of Technology (Eikokuji Campus) | Modeling the temporal change of student proficiency using records in e-learning Midori Kodama, Takahiro Hata, Ippei Shake (NTT) ET2017-132 |
Estimating student’s proficiency from the records of learning system is the key technology to provide adaptive learning ... [more] | ET2017-132 pp.249-252 |
| SP, SIP, EA | 2017-03-01 15:55 |
Okinawa | Okinawa Industry Support Center | [Invited Talk]
Multikernel Adaptive Filtering: Signal Processing and Machine Learning Masahiro Yukawa (Keio Univ.) EA2016-113 SIP2016-168 SP2016-108 |
We present the multikernel adaptive filtering and introduce its recent advances. Multikernel adaptive filtering is a rec... [more] | EA2016-113 SIP2016-168 SP2016-108 pp.177-182 |
| ASN | 2014-05-29 14:30 |
Tokyo | Convention Hall, RCAST, The University of Tokyo | [Poster Presentation]
A proposal for an agricultural environmental control system based on wireless sensor networks and machine learning Yukimasa Kaneda, Hirofumi Ibayashi, Yuya Suzuki (Shizuoka Univ.), Naoki Oishi (Research Institute of Agric.), Hiroshi Mineno (Shizuoka Univ.) ASN2014-22 |
In recent years , agricultural support using ICT has been actively conducted.An example of such system is monitoring env... [more] | ASN2014-22 pp.75-76 |
| NLP | 2014-01-21 11:00 |
Hokkaido | Niseko Park Hotel | Automated Forex Trading System Using the Nonlinear Portfolio Model Hirotake Wachi, Vu Tat Thanh, Satoshi Inose (Ibaraki Univ.), Atsushi Kannari (MS&AD), Tomoya Suzuki (Ibaraki Univ.) NLP2013-132 |
In our previous studies (S.Inose, 2013) the nonlinear portfolio model was proposed and its usefulness was confirmed in s... [more] | NLP2013-132 pp.19-24 |
| NC, NLP | 2013-01-24 14:10 |
Hokkaido | Hokkaido University Centennial Memory Hall | Characterizing financial crisis by means of the Three states random field Ising model Mitsuaki Murota, Jun-ichi Inoue (Hokkaido Univ.) NLP2012-115 NC2012-105 |
We extend the formulation of time-series prediction using Ising model given by Kaizouji (2001) or Higano et.al. (2012) b... [more] | NLP2012-115 NC2012-105 pp.67-72 |
| NC | 2012-01-26 15:40 |
Hokkaido | Future University Hakodate | Critical phenomena in mean-field Ising models and time-series prediction Shunsuke Higano, Jun-ichi Inoue (Hokkaido Univ.) NC2011-108 |
We propose a theoretical framework to predict several time-series simultaneously by using cross-correlations in fin... [more] |
NC2011-108 pp.65-70 |
| NC, NLP | 2011-01-26 10:55 |
Hokkaido | Hokakido Univ. | Research of Automatic Prediction of Chaos Time-Series Data by 2D Lattice Coupled Oscillators System Tatsuya Sasaki, Masayuki Yamauchi (Hiroshima Inst. of Tech.), Yoshifumi Nishio (Tokushimahima Univ.) NLP2010-159 NC2010-123 |
We can see the time-series data in this natural world, and human economic activity has a lot of time-series data. If a... [more] |
NLP2010-159 NC2010-123 pp.193-198 |
| NLP, CAS | 2010-08-03 13:20 |
Tokushima | Naruto University of Education | Automation of Prediction of Chaos Time-Series Data by using 3x3 Lattice-Shaped System of Coupled Oscillators by Inductors Tatsuya Sasaki, Takeo Imoto, Masayuki Yamauchi (Hiroshima Inst. of Tech.), Yoshifumi Nishio (Tokushima Univ) CAS2010-59 NLP2010-75 |
\begin{eabstract} We can say that it is very important to predict the time-series data. Recently, various researches f... [more] |
CAS2010-59 NLP2010-75 pp.141-146 |
| NLP | 2010-07-13 11:40 |
Ishikawa | Ishikawa Prefectural Bunkyo Hall | Prediction of Temperature-Time-Series data by Coupled Oscillators System with Printed-Spiral Inductor. Toru Tanaka, Kazuhisa Yoshimatsu (Hiroshima Inst. of Tech.), Takeo Imoto, Masayuki Yamauchi (Hiroshima Inst. of Tech.), Mamoru Tanaka (Sophia Univ.) NLP2010-46 |
Predictions of time-series data in natural world are very important. For example, if nonlinear time-series-data are pr... [more] |
NLP2010-46 pp.85-90 |
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