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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 331  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
ICM, IPSJ-IOT, IPSJ-CSEC 2024-05-31
09:00
Tottori
(Primary: On-site, Secondary: Online)
Failure Point Localization Technique with Anomaly Detection
Reiko Kondo, Takeshi Kodama, Takashi Shiraishi (FUJITSU)
(To be available after the conference date) [more]
DC 2024-02-28
16:05
Tokyo Kikai-Shinko-Kaikan Bldg. DC2023-103 This study focuses on interdependent networks.
The objective of this study is to solve the problem of selecting nodes... [more]
DC2023-103
pp.53-58
NS, NWS
(Joint)
2024-01-25
13:00
Hiroshima Higashisenda Campus, HiroshimaUniversity + Online
(Primary: On-site, Secondary: Online)
[Encouragement Talk] Performance evaluation of network anomaly detection and failure scale estimation method.
Naoya Ogawa, Ryoichi Kawahara (Toyo Univ.) NS2023-159
In this paper, we evaluate the performance of the method proposed in "Network anomaly detection and failure scale estima... [more] NS2023-159
pp.1-6
LOIS, ICM 2024-01-26
10:35
Nagasaki Nagasaki Prefectural Art Museum
(Primary: On-site, Secondary: Online)
A study on determining the risk of service impact in the event of a failure in a mesh-configured network
Mayu Yamazoe, Kazuaki Akashi, Masashi Kobayashi, Hiroaki Matsubayashi, Manami Ogawa, Kenichi Tayama (NTT) ICM2023-35 LOIS2023-39
Telecommunication services are one of the most critical infrastructures. In the event of a large-scale failure, telecomm... [more] ICM2023-35 LOIS2023-39
pp.39-44
NS, RCS
(Joint)
2023-12-15
09:50
Fukuoka Kyushu Institute of Technology Tobata campus, and Online
(Primary: On-site, Secondary: Online)
[Encouragement Talk] Analysis of Features Contributing to Early Detection of Failures in 5G Core Networks Using Machine Learning
Takeru Hakii (UTokyo), Takuya Miyasaka, Junichi Kawasaki, Daiki Koyama (KDDI Research, Inc.), Norihiro Fukumoto, Akirhiro Nakao (UTokyo) NS2023-141
CNF-based 5GC, a cloud-native implementation of network functions (NFs), is increasingly using machine learning for earl... [more] NS2023-141
pp.90-96
NS, RCS
(Joint)
2023-12-15
17:10
Fukuoka Kyushu Institute of Technology Tobata campus, and Online
(Primary: On-site, Secondary: Online)
A Study of Q-drop Identification by Analyzing Receiver-Side Quality Data for Optical Transmission Systems
Kohei Watanabe, Hiroshi Yamamoto, Hiroki Date, Daisaku Shimazaki (NTT), Yutaka Fukuchi, Hideki Maeda (TUS) NS2023-153
High reliability is required for optical transmission systems, which are widely deployed as the network infrastructure f... [more] NS2023-153
pp.157-162
R 2023-12-07
16:05
Tokyo Kikai-Shinko-Kaikan Bldg
(Primary: On-site, Secondary: Online)
Formulation of Dependability/Risk-related Measures for Safety-Related Systems conforming to Functional Safety -- Systems with the Faults Detected by Proof-Testing (PT) and Subsequent Corrective Maintenance --
Yoshinobu Sato (Institute of HCI) R2023-54
The part 6 of basic safety standard of IEC 61508 describes the guidelines to estimate the dangerous failure rates (PFH) ... [more] R2023-54
pp.24-29
RISING
(3rd)
2023-10-31
13:00
Hokkaido Kaderu 2・7 (Sapporo) [Poster Presentation] CLI Command Output Parser for Automation of Failure Diagnosis of Network Devices
Keitaro Kaida (Osaka Univ.), Tatsuaki Kimura (Doshisha Univ.), Hiroshi Yamauchi (SBKK), Tetsuya Takine (Osaka Univ.)
With the rapid growth and diversification of communication services, networks operated by telecom carriers have become i... [more]
R 2023-09-28
14:20
Fukuoka
(Primary: On-site, Secondary: Online)
Copula models based on left-truncated and competing risks data -- Likelihood inference based on field studies --
Takeshi Emura (ISM), Hirofumi Michimae (Kitasato Univ.) R2023-39
In the collection method of failure data (field life data) in field tests, unobserved failure occurs before the collecti... [more] R2023-39
pp.12-15
R 2023-09-28
15:20
Fukuoka
(Primary: On-site, Secondary: Online)
Polynomial Failure Models: Theory and Applications
Tadashi Dohi, Hiroyuki Okamura (Hiroshima Univ.) R2023-41
In this paper we summarize two polynomial failure models, where the lifetime distributions are described by canonical po... [more] R2023-41
pp.22-27
R 2023-09-28
15:45
Fukuoka
(Primary: On-site, Secondary: Online)
Functional safety assessment of multiple protection-layers with self-diagnosis and common-cause failures
Yoshinobu Sato (IHQI) R2023-42
In the present paper, firstly necessary and sufficient conditions for safety functions (SFs) to form multi-protection la... [more] R2023-42
pp.28-33
NS, IN, CS, NV
(Joint)
2023-09-08
09:30
Miyagi Tohoku University
(Primary: On-site, Secondary: Online)
Network anomaly detection and failure scale estimation method
Naoya Ogawa, Ryoichi Kawahara (Toyo Univ.) NS2023-57
In this paper, we propose a network anomaly detection and failure scale estimation method using AI. For anomaly detectio... [more] NS2023-57
pp.32-37
NS, IN, CS, NV
(Joint)
2023-09-08
13:55
Miyagi Tohoku University
(Primary: On-site, Secondary: Online)
Joint Experiment of Interworking Multi-vendors' AI via TM Forum Open API toward Autonomic QoS Management of Cloud Native Services
Takahiro Hirayama, Masahiro Jibiki (NICT), Takuya Miyasaka (KDDI/KDDI Research Inc.), Toshiki Watanabe, Satoshi Akabori, Takayuki Kuroda (NEC) NS2023-63
Constant monitoring and agile management of cloud-native network functions (CNFs) are the essential to prevent serious d... [more] NS2023-63
pp.65-70
LQE, OPE, CPM, EMD, R 2023-08-24
16:40
Miyagi Tohoku university
(Primary: On-site, Secondary: Online)
[Invited Talk] Failure Mode and Analytical Method for Chip Components -- Analysis Example and Correspondence to Miniaturization --
Akira Saito (Murata) R2023-25 EMD2023-20 CPM2023-30 OPE2023-69 LQE2023-16
Higher reliability of electric components is demanded with the evolution of AI and the automatic driving. Electric chara... [more] R2023-25 EMD2023-20 CPM2023-30 OPE2023-69 LQE2023-16
pp.45-50
CPSY, DC, IPSJ-ARC [detail] 2023-08-03
09:00
Hokkaido Hakodate Arena
(Primary: On-site, Secondary: Online)
Proposal of Data Protection Features using Peak Shift Method of Drive Failure Risk
Takaki Nakamura (Tohoku Univ.), Hitoshi Kamei (Kagawa Univ.) CPSY2023-8 DC2023-8
We propose a peak shift method for data protection that considers time-series changes in drive failure risk and the risk... [more] CPSY2023-8 DC2023-8
pp.1-6
ICM 2023-07-14
10:25
Hokkaido Sun Reflation Hakodate
(Primary: On-site, Secondary: Online)
[Encouragement Talk] Autonomous VPN Management Method Supported by Network Information Sharing Platform KANVAS and Automatic System Designer Weaver
Kazuki Tanabe (NEC), Kanta Kuchii, Takao Kondo, Kosuke Mori (Keio Univ.), Takayuki Kuroda, Kozo Satoda (NEC), Fumio Teraoka (Keio Univ.) ICM2023-20
In this paper, we propose an autonomous operation technology for VPNs by collaboration of KANVAS (Knowledge base system ... [more] ICM2023-20
pp.46-51
RCS, IN, NV
(Joint)
2023-05-25
11:55
Kanagawa Keio University (Hiyoshi Campus), and online
(Primary: On-site, Secondary: Online)
Failure Intermediate Node Detection and Notification Methods in Wireless Multihop Network
Riki Okase, Hiroaki Higaki (Tokyo Denki Univ.) IN2023-5
This paper proposes novel methods for failure node detection and its notification in a wireless multihop network.
By ex... [more]
IN2023-5
pp.23-28
ICM 2023-03-17
14:15
Okinawa Okinawa Prefectural Museum and Art Museum
(Primary: On-site, Secondary: Online)
Study and applicability evaluation of autonomous estimation for network failure
Fumika Asai, Li Di, Norio Yamamoto, Haruhisa Nozue, Kenichi Tayama (NTT) ICM2022-59
With the recent large-scale network failures, rapid identification of suspected fault points and service recovery are be... [more] ICM2022-59
pp.95-100
R 2023-03-10
13:50
Hiroshima
(Primary: On-site, Secondary: Online)
Failure Sign Detection by State Path Analysis for Fare Collection System -- Evaluation by Sequential Pattern Mining with Mechatronics Knowledge --
Ken Ueno, Misato Ishikawa, Yuko Kobayashi, Takamitsu Sunaoshi (Toshiba), Kiyoku Endo (Toshiba Automation Systems Service) R2022-50
To detect failure sign on Fare Collection System (FCS) which has low failure rate accurately, we need the mechatronics k... [more] R2022-50
pp.13-18
R 2023-03-10
16:40
Hiroshima
(Primary: On-site, Secondary: Online)
A Study on a Statistical Detection Method for Cascading Failure of Bearings Based on Copula Models
Mitsuhiro Kimura (Hosei Univ.), Shuhei Ota (Kanagawa Univ.) R2022-56
The present paper analyzes the IMS dataset from an accelerated testing environment of four coaxially mounted roller elem... [more] R2022-56
pp.47-52
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