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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| R | 2023-12-07 14:40 |
Tokyo | Kikai-Shinko-Kaikan Bldg (Primary: On-site, Secondary: Online) |
Optimal CBM policy for a degrading system with two weighted components Shinji Kawano, Nobuyuki Tamura (Hosei Univ.)  R2023-51 |
We consider a system in which the degradation of two components follows a Wiener process with different drifts, and a fa... [more] | R2023-51 pp.6-11 |
| AI | 2023-09-12 14:55 |
Hokkaido | Event-Driven Reinforcement Learning with Semi Markov Models for Stable Air-Conditioning Control Hayato Chujo, Arai Sachiyo (Chiba Univ) AI2023-16 |
This study deals with air conditioning control that optimizes room temperature by switching heaters on/off. The control ... [more] | AI2023-16 pp.83-86 |
|
| DC, SS | 2022-10-25 10:00 |
Fukushima | (Primary: On-site, Secondary: Online) |
A note on performance and sensitivity analysis of self-adaptive systems using parametric Markov decision processes Junjun Zheng, Hiroyuki Nakagawa, Tatsuhiro Tsuchiya (Osaka Univ.) SS2022-21 DC2022-27 |
This paper considers the sensitivity analysis for a self-adaptive system with uncertain parameters. The system behavior ... [more] | SS2022-21 DC2022-27 pp.1-5 |
| R | 2022-10-07 15:15 |
Fukuoka | (Primary: On-site, Secondary: Online) |
A Note on Pull-Type Security Patch Management Policies for Intrusion Tolerant Systems Junjun Zheng (Osaka Univ.), Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2022-37 |
This paper considers the pull-type security patch management policies for intrusion tolerant systems. A composite stocha... [more] | R2022-37 pp.31-36 |
| R | 2022-06-16 14:50 |
Online | Online | A Note on Interval Reliability Analysis of Intrusion Tolerant Systems Subject to DoS Attacks Junjun Zheng (Ritsumeikan Univ.), Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2022-8 |
This paper focuses on the transient behavior of intrusion tolerant systems with preventive maintenance subject to DoS (D... [more] | R2022-8 pp.13-18 |
| MSS, NLP | 2022-03-29 10:05 |
Online | Online | Relationship between Computational Performance and Task Difficulty of Reinforcement Learning Methods Using Reward Machines Ryuji Watanabe, Gouhei Tanaka (The Univ. of Tokyo) MSS2021-70 NLP2021-141 |
In reinforcement learning, it is necessary to take into account the history of past state transitions during learning fo... [more] | MSS2021-70 NLP2021-141 pp.77-82 |
| IBISML | 2022-03-09 14:55 |
Online | Online | Infinite SCAN: Joint Estimation of Changes and the Number of Word Senses with Gaussian Markov Random Fields Seiichi Inoue, Mamoru Komachi (TMU), Toshinobu Ogiso (NINJAL), Hiroya Takamura (AIST), Daichi Mochihashi (ISM) IBISML2021-47 |
In this study, we propose a hierarchical Bayesian model that can automatically estimate the number of senses for each wo... [more] | IBISML2021-47 pp.61-68 |
| NLP | 2021-12-18 11:05 |
Oita | J:COM Horuto Hall OITA | Markov Binary Sequences Generated by Post-Processing Based on Nonlinear Feedback Shift Registers Akio Tsuneda (Kumamoto Univ.), Naruaki Maeda (NEC) NLP2021-59 |
In general, random numbers are required to be uniform and uncorrelated. However, it is known that correlated random numb... [more] | NLP2021-59 pp.72-75 |
| QIT (2nd) |
2021-12-01 15:20 |
Online | Online | Non-Markovian dynamics of the quantum Otto cycle Miku Ishizaki, Naomichi Hatano (UTokyo), Hiroyasu Tajima (UEC) |
From the viewpoint of investigating the efficient use of heat by means of quantum resources, quantum heat engines, which... [more] | |
| R | 2021-10-22 15:25 |
Online | Online | A Note on Sensitivity Analysis of Software Rejuvenation Model with Markov Regenerative Process Junjun Zheng (Ritsumeikan Univ.), Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2021-32 |
This paper considers the parametric sensitivity of a software rejuvenation model for transaction systems. The system beh... [more] | R2021-32 pp.13-18 |
| R | 2021-06-12 14:00 |
Online | Online (Zoom) | An approximate method of network resirience Yasumasa Sagawa, Natsumi Takahashi, Tetushi Yuge (NDA) R2021-11 |
Resilience is an index that takes into account not only the reduction of damage caused by system failures, but also the ... [more] | R2021-11 pp.1-6 |
| R | 2021-05-28 14:10 |
Online | Online | A note on local sensitivity analysis of stationary solutions for Markov regenerative processes Junjun Zheng (Ritsumeikan Univ.), Jiahao Zhang, Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2021-4 |
Because of high power and flexibility, Markov regenerative process (MRGP) is widely used for modeling and evaluating the... [more] | R2021-4 pp.19-24 |
| RCS, SR, SRW (Joint) |
2021-03-05 16:30 |
Online | Online | [Invited Lecture]
A Hazardous Spot Detection Framework by Mobile Sensing and V2V Opportunistic Networks Yoshito Watanabe, Yozo Shoji (NICT) SR2020-88 |
This study proposes a framework to detect hazardous spots on roads by combining mobile sensing on commercial-use vehicle... [more] | SR2020-88 pp.91-98 |
| IBISML | 2021-03-03 14:25 |
Online | Online | Markov Decision Processes for Simultaneous Control of Multiple Objects with Different State Transition Probabilities in Each Cluster Yuto Motomura, Akira Kamatsuka, Koki Kazama, Toshiyasu Matsushima (Waseda Univ.) IBISML2020-49 |
In this study, we propose an extended MDP model, which is a Markov decision process model with multiple control objects ... [more] | IBISML2020-49 pp.47-54 |
| IT | 2020-12-02 10:00 |
Online | Online | Policy Optimization Based on Bayesian Decision Theory in Learning Period on Markov Decision Process Naoki Ichijo, Yuta Nakahara, Yuto Motomura, Toshiyasu Matsushima (Waseda Univ.) IT2020-31 |
In Markov decision process(MDP) problems with an unknown transition probability, a learning agent has to learn the unkno... [more] | IT2020-31 pp.38-43 |
| RCS | 2020-06-25 14:30 |
Online | Online | A Study on Signal Detection in Massive MIMO Using MCMC Kazushi Matsumura, Junichiro Hagiwara, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Takanori Sato (Hokkaido Univ.) RCS2020-38 |
MIMO is a new technology for wireless transmission; as the number of antennas increases, the computational complexity of... [more] | RCS2020-38 pp.91-95 |
| NC, MBE (Joint) |
2020-03-06 13:25 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
A finite state markov-chain approximation of the intermittent control model during human quiet standing using a finite element analysis of its Fokker-Planck equation Keigo Togame, Akihiro Nakamura, Yasuyuki Suzuki, Taishin Nomura (Osaka Univ.) MBE2019-96 |
The intermittent control during human quiet standing is a hypothetical neural control strategy that we have proposed in ... [more] | MBE2019-96 p.83 |
| PRMU | 2019-12-19 10:30 |
Oita | A switching Markov model for evaluation of food functionality Tsukasa Hokimoto, Toshio Uchiyama (HIU) PRMU2019-46 |
For analytic purposes of the scientific processes on how food influence our health, the measurement data on medical or g... [more] | PRMU2019-46 pp.1-6 |
|
| R | 2019-11-28 14:10 |
Osaka | Central Electric Club | Non-homogeneous Markov Process Modeling for Software Reliability Assessment Siqiao Li, Tadashi Dohi, Hiroyuki Okamura (Hiroshima U.) R2019-44 |
In this paper, we focus on non-homogeneous Markov processes, which are generalizations of the well-known non-homogeneous... [more] | R2019-44 pp.7-12 |
| R | 2019-11-28 15:35 |
Osaka | Central Electric Club | A Note on Optimal Rejuvenation Policies for Non-Markovian Availability Models with Aperiodic Checkpointing Junjun Zheng (Ritsumeikan Univ.), Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2019-47 |
In this paper, we present non-Markovian availability models for capturing the dynamics of system behavior of an operatio... [more] | R2019-47 pp.23-28 |
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