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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIS, ITE-BCT | 2020-10-02 10:00 |
Online | Online | A study on ANC using multiple virtual microphone Itsuki Kojima, Keisuke Okano, Kouhei Matsuhisa, Naoto Sasaoka, Yoshio Itoh (Tottori Univ.)  SIS2020-22 |
Active Noise Control(ANC) system reduces noise for using anti-noise. The ANC system using a virtual sensing method has b... [more] | SIS2020-22 pp.61-65 |
| SeMI, RCS, NS, SR, RCC (Joint) |
2019-07-11 10:40 |
Osaka | I-Site Nanba（Osaka） | [Poster Presentation]
Experimental Verification of Adaptive Superframe Change for a Multihop Mobile Sensor Network Hiroto Maruo, Shinsuke Hara (Osaka City Univ.), Takuma Hamagami, Yasukata Kawamoto (OKI), Hiroyuki Yomo (Kansai Univ.), Hiroyuki Okuhata (Soliton) RCC2019-26 NS2019-62 RCS2019-119 SR2019-38 SeMI2019-35 |
In the AccuWiSe (Accurate Wireless Sensing) system, which can wirelessly collect vital data from a number of exercisers ... [more] | RCC2019-26 NS2019-62 RCS2019-119 SR2019-38 SeMI2019-35 pp.79-83(RCC), pp.105-109(NS), pp.101-105(RCS), pp.111-115(SR), pp.93-97(SeMI) |
| CNR | 2019-06-13 16:40 |
Tokyo | Cloud-based VSLAM for Robotics utilizing Adaptive Video Streaming Natsuki Kai, Takahiro Shiroshima, Hiroshi Yoshida (NEC) CNR2019-9 |
Cloud sensing that collects enormous sensor data over cloud network and recognizes around sensors' environments by power... [more] | CNR2019-9 pp.43-48 |
|
| ASN | 2019-01-28 14:40 |
Kagoshima | Kyuukamura Ibusuki | Deep Reinforcement Learning-Based Optimum Channel Control for Wireless LAN Kota Nakashima, Syotaro Kamiya, Kazuki Ohtsu, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura (Kyoto Univ.) ASN2018-80 |
This report proposes deep reinforcement learning-based channel selection method when access points (APs) are located den... [more] | ASN2018-80 pp.13-18 |
| NS, ASN, RCC, RCS, SR (Joint) |
2017-07-19 11:55 |
Hokkaido | Hokkaido Univ. | A Pool Control Method for Adaptive Group Testing with Boolean Compressed Sensing Yujia Lu (Kyoto Univ.), Kazunori Hayashi (Osaka City Univ.) RCC2017-14 NS2017-35 RCS2017-97 SR2017-31 ASN2017-19 |
Adaptive group testing determines a pool (a set of items to be tested) for the next test based on past test results, and... [more] | RCC2017-14 NS2017-35 RCS2017-97 SR2017-31 ASN2017-19 pp.25-30(RCC), pp.39-44(NS), pp.25-30(RCS), pp.47-52(SR), pp.43-48(ASN) |
| WBS, RCC, ITS | 2016-12-01 13:00 |
Kagawa | Sunport Hall Takamatsu | [Poster Presentation]
A New Pool Control Method for Boolean Compressed Sensing Based Adaptive Group Testing Yujia Lu, Kazunori Hayashi (Kyoto Univ.) WBS2016-52 ITS2016-19 RCC2016-41 |
Adaptive group testing determines a pool (set of items to be tested) used in the next test on the basis of previous test... [more] | WBS2016-52 ITS2016-19 RCC2016-41 pp.25-30 |
| SANE | 2016-11-24 14:50 |
Overseas | National Taipei University of Technology (NTUT) | [Poster Presentation]
GPU-BASED ADAPTIVE LOCAL KRIGING APPLIED TO RECOVERING SURFACE DEFORMATION Meng-Che Wu (NSPO), Wen-Yen Chang (NDHU), Yang-Lang Chang, Sheng-Yung Shih (NTUT), Chihyuan Chu (G-AVE), Bormin Huang (UW) SANE2016-79 |
Synthetic aperture radar (SAR) is an active remote sensing instrument to measure the landscape. Differential interferome... [more] | SANE2016-79 pp.145-147 |
| RCS, RCC, ASN, NS, SR (Joint) |
2016-07-21 10:50 |
Aichi | [Poster Presentation]
Cardinality Estimation of Positive Items for Boolean Compressed Sensing Based Adaptive Group Testing Yujia Lu, Kazunori Hayashi (Kyoto Univ.) RCC2016-22 NS2016-56 RCS2016-109 SR2016-39 ASN2016-30 |
Adaptive group testing using boolean compressed sensing requires information on the number of positive items for effecti... [more] | RCC2016-22 NS2016-56 RCS2016-109 SR2016-39 ASN2016-30 pp.51-56(RCC), pp.33-38(NS), pp.81-86(RCS), pp.51-56(SR), pp.33-38(ASN) |
|
| PRMU, IE, MI, SIP | 2016-05-20 14:40 |
Aichi | Sequential Pool-Design for Adaptive Boolean Compressive Sensing Yohei Kawaguchi, Masahito Togami (Hitachi) SIP2016-27 IE2016-27 PRMU2016-27 MI2016-27 |
A new method for solving adaptive Boolean compressive sensing is proposed. A conventional method determining a pool for... [more] |
SIP2016-27 IE2016-27 PRMU2016-27 MI2016-27 pp.141-145 |
|
| SANE | 2015-11-24 13:45 |
Overseas | AIT, Bangkok, Thailand | Adaptive Nearest Feature Space Method for Remote Sensing Images Classification Yang-Lang Chang (NTUT), Chihyuan Chu (G-AVE), Hirokazu Kobayashi (OIT), Tzu-Wei Tseng (NTUT) SANE2015-62 |
In this paper a novel technique based on nearest feature space (NFS), known as adaptive nearest feature space (ANFS), is... [more] | SANE2015-62 pp.71-74 |
| MICT, ASN, MoNA (Joint) |
2015-01-26 16:45 |
Wakayama | Nanki Shirahama | [Technology Exhibit]
Real-Time Vital Sign Monitoring System for Men during Exercise Takunori Shimazaki, Shinsuke Hara (Osaka City Univ.) MoNA2014-77 ASN2014-133 MICT2014-64 |
If we can monitor heart rate (HR) in real-time from athletes during hard training and from schoolchildren during physica... [more] | MoNA2014-77 ASN2014-133 MICT2014-64 pp.87-90(MoNA), pp.131-134(ASN), pp.47-50(MICT) |
| ICD, SDM | 2014-08-04 10:50 |
Hokkaido | Hokkaido Univ., Multimedia Education Bldg. | A 28nm High-k/MG Heterogeneous Multi-Core Mobile Application Processor with 2GHz Cores and Low-Power 1GHz Cores Mitsuhiko Igarashi, Toshifumi Uemura, Ryo Mori, Hiroshi Kishibe, Masaaki Taniguchi, Kohei Wakahara, Toshiharu Saito, Masaki Fujigaya, Kazuki Fukuoka, Koji Nii, Takeshi Kataoka, Toshihiro Hattori (Renesas Electronics) SDM2014-64 ICD2014-33 |
This paper presents power management and low power techniques of our heterogeneous quad/octa-core mobile application pro... [more] | SDM2014-64 ICD2014-33 pp.11-16 |
| MICT, WBS | 2014-07-29 12:30 |
Osaka | Osaka City Univ. (Umeda Satellite) | [Poster Presentation]
Heart Rate Sensing Using Adaptive Canceller for Motion Artifact during Exercise Takunori Shimazaki, Shinsuke Hara (Osaka City Univ.) WBS2014-9 MICT2014-23 |
Photoplethysmography (PPG)-based heart rate (HR) sensing during exercise is essential not only for early detecting hazar... [more] | WBS2014-9 MICT2014-23 pp.7-11 |
| MICT, RCC | 2014-05-30 11:10 |
Tokyo | Kikai-Shinko-Kaikan Bldg | Optimization of Adaptive Filter Parameters in PPG-Based Motion Artifact Cancellation for Heart Rate Sensing Takunori Shimazaki, Shinsuke Hara (Osaka City Univ.) RCC2014-14 MICT2014-14 |
Photoplethysmography (PPG)-based heart rate (HR) sensing during exercise is essential not only for early detecting hazar... [more] | RCC2014-14 MICT2014-14 pp.69-72 |
| CS, CAS, SIP | 2014-03-07 13:00 |
Osaka | Osaka City University Media Center | Pool size control of boolean compressive sensing for adaptive group testing Yohei Kawaguchi, Tatsuhiko Osa, Shubhranshu Barnwal, Hisashi Nagano, Masahito Togami (Hitachi) CAS2013-128 SIP2013-174 CS2013-141 |
We propose a new method for adaptive group testing. A non-adaptive group testing based on boolean compressive sensing ha... [more] | CAS2013-128 SIP2013-174 CS2013-141 pp.221-225 |
| SR | 2014-01-24 09:00 |
Miyagi | Tohoku Univ. | Improved WLAN load capacity prediction using the ratio of application QoE satisfaction Kazuto Yano, Mariko Sekiguchi, Masayuki Ariyoshi, Kiyoshi Kobayashi (ATR) SR2013-85 |
In order to provide enough level of QoE to more applications with more importance operating on a shared frequency band, ... [more] | SR2013-85 pp.43-50 |
| PRMU | 2013-03-14 11:45 |
Tokyo | Real-time 3D tracking of pages and its condition assessment for book digitization based on adaptive capture Shohei Noguchi, Miho Tamei, Masahiro Yamada, Yoshihiro Watanabe, Masatoshi Ishikawa (Univ. of Tokyo) PRMU2012-188 |
We report a new book digitization system and new adaptive capture method that enables to obtain high-resolution document... [more] | PRMU2012-188 pp.49-54 |
|
| RCS, SR, SRW (Joint) |
2013-03-01 11:30 |
Tokyo | Waseda Univ. | Least Mean Square Algorithm with Application to Improved Adaptive Sparse Channel Estimation Guan Gui, Wei Peng, Fumiyuki Adachi (Tohoku Univ.) RCS2012-359 |
Least mean square (LMS) based adaptive algorithms have been attracted much attention since their low computational compl... [more] | RCS2012-359 pp.447-452 |
| US, EA (Joint) |
2013-01-25 13:10 |
Kyoto | Kambaikan, Doshisha Univ. | [Invited Talk]
Recent Advances on Active Noise Control: Open Issues and Innovative Applications Yoshinobu Kajikawa (Kansai Univ.) US2012-106 EA2012-137 |
The problem of acoustic noise is becoming increasingly serious with the growing use of industrial and medical equipment,... [more] | US2012-106 EA2012-137 pp.101-106(US), pp.103-108(EA) |
| USN, IPSJ-UBI | 2008-07-18 13:15 |
Tokyo | Tokyo Denki University （Tokyo) | A Traveling Wave-based Data Gathering Scheme Adaptive to Sensing Requirements for Wireless Sensor Networks Yoshiaki Taniguchi, Naoki Wakamiya, Masayuki Murata (Osaka Univ.), Takashi Fukushima (Kobe Steel., LTD) USN2008-29 |
In wireless sensor networks, frequency of sensing and data gathering depends on application requirements and dynamic sur... [more] | USN2008-29 pp.105-110 |
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