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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 184 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
10:25
Okinawa Okinawa Institute of Science and Technology Feature scaling in spectral classification of high dimensional data
Momo Matsuda, Keiichi Morikuni, Akira Imakura, Tetsuya Sakurai (Univ. Tsukuba) IBISML2018-2
We consider the classification problem for high dimensional data. Using prior knowledge on the labels of partial samples... [more] IBISML2018-2
pp.9-14
ET 2018-05-19
11:20
Kanagawa National Institute of Special Needs Education Sharing the results of a Moodle course material clickstream analysis and examining its effect on students
Konomu Dobashi (Aichi Univ.) ET2018-5
A face-to-face blended-type lesson was previously carried out using Moodle in PC classes attended by a large number of s... [more] ET2018-5
pp.23-28
PRMU, MVE, IPSJ-CVIM [detail] 2018-01-18
09:30
Osaka   Trajectory semantic segmentation based on behavior models
Daisuke Ogawa, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda (Hiroshima Univ.) PRMU2017-112 MVE2017-33
In many cases, such as trajectories clustering and classification, we often divide a trajectory into segments as preproc... [more] PRMU2017-112 MVE2017-33
pp.1-7
MoNA 2017-12-21
14:40
Tokyo Ochanomizu University A Study of Decentralization for Data Mining System Implemented with Fully Homomorphic Encryption
Yuri Yamamoto, Masato Oguchi (Ochanomizu Univ.) MoNA2017-37
For promoting utilization of big data, outsourcing systems have been proposed in which transaction data such as purchase... [more] MoNA2017-37
pp.49-53
IMQ 2017-12-15
13:55
Shizuoka Shizuoka University, Hamamatsu Campus A Study of Diagnostic Imaging System for Coded Defect Detection of Certain Viewpoints on Multi-view 3D CG Images
Norifumi Kawabata (Chiba Univ.) IMQ2017-21
At present, in the engineering fields, the medical application for multi-view 3D images and 8K UHDTV images is advanced ... [more] IMQ2017-21
pp.7-12
CAS, MSS, IPSJ-AL [detail] 2017-11-17
11:15
Tokyo   [Invited Talk] Open Data of Air Traffic and its Application
Megumi Oka, Yutaka Fukuda (ENRI) CAS2017-53 MSS2017-37
The Ministry of Land, Infrastructure and Transport of Japan has formulated a long-term vision for future air traffic sys... [more] CAS2017-53 MSS2017-37
pp.95-100
KBSE 2017-11-10
15:45
Shizuoka   Estimation of business rules using Associations analysis
Takuya Saruwatari, Akio Jin, Masayuki Inoue, Teruko Miyata, Daisuke Hamuro (NTT), Noriaki Izumi (AIST) KBSE2017-27
Recently, IT system renewal projects are increased along with aging of IT systems. In such a project, it is necessary to... [more] KBSE2017-27
pp.7-12
VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2017-11-06
14:55
Kumamoto Kumamoto-Kenminkouryukan Parea An Approach to Selection of Classifiers and their Thresholds for Machine Learning Based Fail Chip Prediction
Daichi Yuruki, Satoshi Ohtake (Oita Univ), Yoshiyuki Nakamura (Renesas Electronics) VLD2017-36 DC2017-42
Today, semiconductor technologies have developed and advance the integration density of LSI circuits.
A technique which... [more]
VLD2017-36 DC2017-42
pp.55-60
SDM 2017-10-26
09:30
Miyagi Niche, Tohoku Univ. [Invited Talk] Utilization of Big Data for Innovation in Semiconductor Memory Manufacturing -- Comprehensive Big-Data-Based Monitoring System for Yield Analysis in Semiconductor Manufacturing --
Hiroshi Akahori (Toshiba Memory), Kouta Nakata, Ryohei Orihara, Yoshiaki Mizuoka, Kentaro Takagi (Toshiba), Kenichi Kadota, Takaharu Nishimura, Yukako Tanaka, Hidetaka Eguchi (Toshiba Memory) SDM2017-55
In this work, we focus on yield analysis task where engineers identify the cause of failure from wafer failure map patte... [more] SDM2017-55
pp.31-33
ISEC, WBS, IT 2017-03-10
16:00
Tokyo TOKAI University Development of Security Incident Symptomatic Analysis function in SIAS
Mitsumu Katsuno, Hiroki Sakamoto, Hiroyuki Ookawa, Takashi Yamaguchi, Eiji Nunohiro (TUIS), Akira Orita, Tatsuya Sekiguchi (HISYS.ISR) IT2016-134 ISEC2016-124 WBS2016-110
(To be available after the conference date) [more] IT2016-134 ISEC2016-124 WBS2016-110
pp.223-228
CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] 2017-03-10
09:30
Okinawa Kumejima Island Pass/Fail Prediction in LSI Test Considering Fail Die Characteristics.
Takazumi Sato, Michiko Inoue (NAIST) CPSY2016-144 DC2016-90
Various kinds of tests are applied to LSIs in several satages to ship only fully reliable products.However, a lot of kin... [more] CPSY2016-144 DC2016-90
pp.291-296
DC 2017-02-21
12:00
Tokyo Kikai-Shinko-Kaikan Bldg. An Approach to Performance Improvement of Machine Learning Based Fail Chip Discrimination
Daichi Yuruki, Satoshi Ohtake (Oita Univ), Yoshiyuki Nakamura (Renesas System Design) DC2016-77
Today, advancements of semiconductor technology have progress to high integration of LSI circuits.
A technique which ke... [more]
DC2016-77
pp.17-22
NLC, IPSJ-IFAT 2017-02-10
13:55
Osaka   Detecting Earthquake Survivors with Serious Mental Damage
Tatsuya Aoki (Tokyo Tech), Tetsuya Nasukawa, Katsumasa Yoshikawa (IBM Research), Hiroya Takamura, Manabu Okumura (Tokyo Tech) NLC2016-48
The 2011 Great East Japan Earthquake and 2016 Kumamoto Earthquakes had a great impact to numerous people all over the wo... [more] NLC2016-48
pp.65-70
ET 2017-01-28
16:30
Kanagawa National Institute of Special Needs Education Development of a Method for Analyzing Source Code Editing Processes to Estimate Students' Learning Situations
Kei Ishiwada, Yasuhiko Morimoto (TGU), Shoichi Nakamura, Hiroki Nakayama (FU), Youzou Miyadera (TGU) ET2016-92
In the programming exercise lesson, it is expected that estimating learning situation based on the source code editing p... [more] ET2016-92
pp.75-80
IA 2017-01-27
15:50
Tokyo Kikai-Shinko-Kaikan Bldg. B3 Kenshu-2 room Development and evaluation of population monitoring system that assumes outdoor events
Keita Arai (Nagaoka Univ. of Tech.), Hiroshi Yamamoto (Ritsumeikan Univ.), Yamazaki Katsuyuki (Nagaoka Univ. of Tech.) IA2016-87
It is important to manage the number of visitors in order to improve the event quality and to keep visitors' safety in a... [more] IA2016-87
pp.49-54
ICD, CPSY 2016-12-15
10:55
Tokyo Tokyo Institute of Technology Proposal of anonymization methods for secondary use considering data properties
Yuichi Nakamura, Takahiro Hosoe, Hiroaki Nishi (Keio Univ.) ICD2016-53 CPSY2016-59
Applications for secondary use of data, which is a usage that is not same as an original purpose to obtain the data, hav... [more] ICD2016-53 CPSY2016-59
pp.13-18
ET 2016-07-09
11:50
Miyagi Tohoku Gakuin University Development of a Tool for Analyzing the Edit Histories of Programs to Estimate the Learning Situations
Kei Ishiwada, Yasuhiko Morimoto (Tokyo Gakugei Univ.), Shoichi Nakamura (Fukushima Univ.), Youzou Miyadera (Tokyo Gakugei Univ.) ET2016-25
In this study, we aim to estimate students’ learning situations in the Programming Exercise class, based on their progra... [more] ET2016-25
pp.21-26
ET 2016-06-11
13:00
Aichi Nagoya Institute of Technology Time Series Cross Section tables to monitor the course materials page views -- Development of Excel macro for Time Series Cross Section analysis --
Konomu Dobashi (Aichi Univ.) ET2016-12
To enable teachers to monitor student engagement and improve classroom instruction, a data mining method and an Excel ma... [more] ET2016-12
pp.25-30
RECONF 2016-05-19
14:55
Kanagawa FUJITSU LAB. *
Kasha Yamamoto, Tetsuya Asai, Masato Motomura (Hokkaido Univ.) RECONF2016-10
In recent years, the amount of data to be processed in the data center has increased exprosively. Therefore the data min... [more] RECONF2016-10
pp.47-52
CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2016-03-25
15:45
Nagasaki Fukue Bunka Hall/Rodou Fukushi Center A consideration on variation correction for fail prediction in LSI test
Ryo Ogawa (NAIST), Yoshiyuki Nakamura (Renesas Semiconductor Package & Test Solutions), Michiko Inoue (NAIST) CPSY2015-158 DC2015-112
Recently, a test cost reduction using data mining has been attracted. It is expected to reduce the cost by predicting fa... [more] CPSY2015-158 DC2015-112
pp.271-276
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