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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa | Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Color Impression Compensation and Sharing Between Observers Based on Subjective Assessments Using Simplicial Maps Ryo Kamiyama, Jinhui Chao (Chuo Univ.) |
Interactive Evolutionary Computation (IEC) has been proposed as a method that enables color compensation by adjusting co... [more] | |
| EMCJ, IEE-EMC, IEE-SPC | 2022-12-07 13:50 |
Aichi | A Study on Measurement Method for Mode Conversion of Differential Communication Line Termination Structures Masahiro Yoshida, Yusuke Yano, Jianqing Wang (NIT), Takeshi Ishida (NoiseKen)  EMCJ2022-68 |
In recent years, the number of systems that combine multiple electronic devices has been increasing, and the importance ... [more] | EMCJ2022-68 pp.29-34 |
|
| NS, ICM, CQ, NV (Joint) |
2022-11-24 09:55 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Highly Accurate Privacy-Enhanced Federated Learning Using Data On The Server Yuta Kakizaki (TUS), Koya Sato (UEC), Keiichi Iwamura (TUS) NS2022-100 |
Federated learning is a cooperative machine learning approach that prohibits disclosing training data from distributed d... [more] | NS2022-100 pp.1-6 |
| NS, ICM, CQ, NV (Joint) |
2022-11-24 10:20 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Social Surplus Maximization Using Incentive Mechanism for Cross-Silo Federated Learning with Differential Privacy Shota Miyagoshi, Takuji Tachibana (Univ. Fukui) NS2022-101 |
In cross-silo federated learning, where multiple organizations participate, the prediction accuracy of the global model ... [more] | NS2022-101 pp.7-12 |
| PEM (2nd) |
2022-10-13 16:30 |
Hiroshima | National Institute of Technology,Kure college | Analysis of laser intensity noise for Electro-Optic sensor system with polarization simulator and Frequency-dependent noise model Mayuko Yamagishi, Haruka Kamimura, Mitsuru Shinagawa (Hosei Univ.), Jun Katsuyama, Yoshinori Matsumoto, Shin-ichiro Teduka (Yokogawa Electric Corp.) |
The EO sensor system is a non-contact electric field measurement system using laser light and an EO crystal. The sensor ... [more] | |
| MWPTHz, EST, MW, EMT, OPE, IEE-EMT [detail] | 2022-07-19 11:15 |
Hokkaido | Asahikawa Civic Culture Hall (Primary: On-site, Secondary: Online) |
A Study on Far-end Crosstalk Suppression of Differential Mode MSL by Using LCP Sheet Hayama Hisanaga, Ryosuke Suga (Aoyama Gakuin Univ.) EMT2022-11 MW2022-35 OPE2022-14 EST2022-12 MWPTHz2022-9 |
In this report, far-end crosstalk in microstrip lines was suppressed by placing a liquid crystalline polymer sheet on th... [more] | EMT2022-11 MW2022-35 OPE2022-14 EST2022-12 MWPTHz2022-9 pp.18-22 |
| EMCJ | 2022-07-14 13:35 |
Tokyo | (Primary: On-site, Secondary: Online) |
3D modeling of USB Type-C connector and signal transmission analysis by FDTD Hayato Ide (NIT,Nagano College), Taiki Kitazawa, Youngwoo Kim, Yuitch Hayashi (NAIST), Takashi Kasuga (NIT,Nagano College) EMCJ2022-28 |
Purpose of this study is discussed about degradation of the signal transmission and influence of impedance variation on ... [more] | EMCJ2022-28 pp.1-6 |
| VLD, HWS [detail] | 2022-03-08 14:55 |
Online | Online | Evaluation of Side-channel Leaks Specific to Unrolled AES Hardware Ayano Nakashima, Rei Ueno, Naofumi Homma (Tohoku Univ.) VLD2021-100 HWS2021-77 |
This paper presents the evaluation of a unique side-channel leakage occurred from the middle rounds of (pipelined) unro... [more] |
VLD2021-100 HWS2021-77 pp.135-140 |
| CCS | 2021-11-18 16:25 |
Osaka | Osaka Univ. (Primary: On-site, Secondary: Online) |
Memory Efficient Training of Neural ODE by Symplectic Adjoint Method Takashi Matsubara, Yuto Miyatake (Osaka Univ.), Takaharu Yaguchi (Kobe Univ.) CCS2021-23 |
Neural ODE learns an ordinary differential equation using neural networks, thereby modeling a continuous-time dynamics a... [more] | CCS2021-23 pp.31-36 |
| RISING (3rd) |
2021-11-17 09:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Proposal of Incentive Mechanism for Cross-Silo Federated Learning with Differential Privacy Shota Miyagoshi, Takuji Tachibana (Univ. Fukui) |
In cross-silo federated learning, where multiple companies/organizations participate, the prediction accuracy of the glo... [more] | |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 10:55 |
Online | Online | A Study on Decentralized Machine Learning with Differential Privacy based on Input Perturbation Masakazu Okamoto, Koya Sato, Keiichi Iwamura (Tokyo Univ. of Science) SR2021-34 |
Distributed machine learning eliminates the need for users to disclose their data to the out of the terminal since train... [more] | SR2021-34 pp.67-72 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 13:25 |
Online | Online | An Evaluation of Learning Accuracy in Federated Learning with Local Differential Privacy Yuta Kakizaki, Koya Sato, Keiichi Iwamura (Tokyo Univ. of Science) SR2021-37 |
In federated learning, where each device learns cooperatively without disclosing the training data, the privacy level ca... [more] | SR2021-37 pp.87-93 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 13:25 |
Online | Online | Training Neural ODE by Symplectic Integrator Takashi Matsubara, Yuto Miyatake (Osaka Univ.), Takaharu Yaguchi (Kobe Univ.) NC2021-2 IBISML2021-2 |
A differential equation model using neural networks, neural ODE, enables use to model a continuous-time dynamics and pr... [more] | NC2021-2 IBISML2021-2 pp.9-14 |
| RCS | 2021-06-24 13:30 |
Online | Online | Comparison of Differential OFDM Systems Employing Multiple Differential Detection with Channel Prediction in Doubly Selective Channels Taichi Fujita, Kota Iwamoto, Hiroshi Kubo (Ritsumeikan Univ.) RCS2021-56 |
In this paper, we compare the performance of differential orthogonal frequency division multiplexing (OFDM) for underwat... [more] | RCS2021-56 pp.163-168 |
| RCS | 2021-06-24 13:40 |
Online | Online | A Transmission Efficiency Improvement Scheme for Software Acoustic MODEMs of Differential OFDM Koki Toyoda, Hiroshi Kubo (Ritsumeikan Univ.) RCS2021-57 |
This paper discusses differential orthogonal frequency division multiplexing (DOFDM) software modems for underwater acou... [more] | RCS2021-57 pp.169-174 |
| NLP, CCS | 2021-06-11 13:55 |
Online | Online | A Blending Stabilization Method of Discrete Mechanics and Nonlinear Optimization for 2-dimensional Nonlinear Films Makoto Koike, Tatsuya Kai (Tokyo Univ. of Science) NLP2021-7 CCS2021-7 |
The aim of this study is to develop a stabilization control method for 2-dimensional nonlinear film, which is one of th... [more] | NLP2021-7 CCS2021-7 pp.28-33 |
| EMCJ | 2021-01-22 14:40 |
Online | Online | Construction of 3D Analysis Model due to Signal Transmission Evaluation in Connector Taiki Kitazawa (NIT,Nagano College), Hiroyuki Ueda, Fujimoto Daisuke, Youngwoo Kim, Hayashi Yuichi (NAIST), Kasuga Takashi (NIT,Nagano College) EMCJ2020-67 |
As high-speed transmission of big data progresses, Signal Integrity (SI) degradation and Electromagnetic Interference (E... [more] | EMCJ2020-67 pp.18-23 |
| KBSE, SC | 2020-11-13 15:04 |
Online | Online + Kikai-Shinko-Kaikan Bldg. (Primary: Online, Secondary: On-site) |
[Poster Presentation]
Prototype Tool to Detect Difference between State Machine Diagrams toward Automation of Providing Educational Feedback to Learners Mitsutada Goshima, Shinpei Ogata (Shinshu Univ.), Erina Makihara (Doshisha Univ.), Kozo Okano (Shinshu Univ.) KBSE2020-15 SC2020-19 |
State machine diagrams in UML are useful for system development and other purposes because they represent discrete behav... [more] | KBSE2020-15 SC2020-19 p.30 |
| COMP | 2020-10-23 13:15 |
Osaka | Osaka Univ. (Primary: On-site, Secondary: Online) |
[Invited Talk]
Index reduction for differential-algebraic equations with mixed matrices Satoru Iwata, Taihei Oki (The Univ. of Tokyo), Mizuyo Takamatsu (Chuo Univ.) COMP2020-12 |
Differential-algebraic equations (DAEs) are widely used for the modeling of dynamical systems. The difficulty in numeric... [more] | COMP2020-12 p.9 |
| IBISML | 2020-10-21 14:40 |
Online | Online | IBISML2020-23 |
Continuous deep learning architectures have recently re-emerged as variants of Neural Ordinary Differential Equations (N... [more] | IBISML2020-23 p.41 |
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