The following papers by members of the Center for Artificial Intelligence Research have been accepted\/published in top-tier international journals\/conferences in each research area in FY 2021.<\/p>\n\n\n\n
Specialty on Numerical Algorithms<\/strong> Specialty on Machine Learning<\/strong> [3] Bernardo B. Gatto, Eulanda Miranda dos Santos, Alessandro L. [4] Erica K. Shimomoto, Fran\u00e7ois Portet, Kazuhiro Fukui: [5] Bernardo B. Gatto, Eulanda M. dos Santos, Marco A.F. Molinetti, [6] Shimon Nakaune, Satoshi Iizuka, Kazuhiro Fukui: [7] Taro Tezuka, Deependra Kumar, Sima Singh, Iyo Koyanagi, Toshie Specialty on Big Data \/ Crowdsourcing<\/strong> [9] Masaki Matsubara, Ria Mae Borromeo, Sihem Amer-Yahia, Atsuyuki Morishima: Specialty on Service Engineering<\/strong> [11] Ayane Nakamura, Tuan Phung-Duc, Hiroyasu Ando: [12] Tuan Phung-Duc, Kohei Akutsu, Ken\u2019ichi Kawanishi, Osama Salameh, [13] Cheng-Ying Hsieh, Tuan Phung-Duc, Yi Ren, Jyh-Cheng Chen: Specialty on Mobility<\/strong> [15] Huiping Zhou, Makoto Itoh, Satoshi Kitazaki: [16] Yuichi Saito, Yuta Watahiki, Chokiu Leung, Huiping Zhou, Makoto Itoh: [17] Jieun Lee, Genya Abe, Kenji Sato, Makoto Itoh: [18] Huiping Zhou, Keita Kamijo, Makoto Itoh, Satoshi Kitazaki: [19] Yusuke Yamani, Shelby K Long, Jieun Lee, James Unverricht, Makoto Itoh: [20] Jieun Lee, Yusuke Yamani, Shelby K. Long, James Unverricht, Makoto Itoh: [21] Yuichi Saito, Fumio Sugaya, Shintaro Inoue, Pongsathorn [22] Yuichi Saito, Ryoma Yoshimi, Shinichi Kume, Xun Shen, Akito [23] Yuichi Saito, Ryoma Yoshimi, Shinichi Kume, Masahiro Imai, Akito The following papers by members of the Center for Artificial Intelligence Research have been accepted\/publishe […]<\/p>\n","protected":false},"author":520,"featured_media":2289,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_locale":"en_US","_original_post":"https:\/\/air.tsukuba.ac.jp\/?p=2264","vkexunit_cta_each_option":"","footnotes":""},"categories":[9,1],"tags":[],"class_list":["post-2443","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications","category-info","en-US"],"_links":{"self":[{"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/posts\/2443","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/users\/520"}],"replies":[{"embeddable":true,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/comments?post=2443"}],"version-history":[{"count":1,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/posts\/2443\/revisions"}],"predecessor-version":[{"id":2444,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/posts\/2443\/revisions\/2444"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/media\/2289"}],"wp:attachment":[{"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/media?parent=2443"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/categories?post=2443"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/air.tsukuba.ac.jp\/wp-json\/wp\/v2\/tags?post=2443"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
[1] Akira Imakura, Hiroaki Inaba, Yukihiko Okada, Tetsuya Sakurai:
Interpretable collaborative data analysis on distributed data,
Expert Systems with Applications, Vol. 177,<\/em> Article 114891, 2021.
See also: https:\/\/doi.org\/10.1016\/j.eswa.2021.114891<\/a><\/p>\n\n\n\n
[2] Naoya Sogi, Rui Zhu, Jing-Hao Xue, Kazuhiro Fukui:
Constrained mutual convex cone method for image set based recognition,
Pattern Recognition, Vol. 121,<\/em> Article 108190, 2022.
See also: https:\/\/doi.org\/10.1016\/j.patcog.2021.108190<\/a><\/p>\n\n\n\n
Koerich, Kazuhiro Fukui, Waldir S. S. Junior:
Tensor analysis with n-mode generalized difference subspace,
Expert Systems with Applications, Vol. 171,<\/em> Article 114559, 2021.
See also: https:\/\/doi.org\/10.1016\/j.eswa.2020.114559<\/a><\/p>\n\n\n\n
Text classification based on the word subspace representation,
Pattern Analysis and Application, Vol. 24,<\/em> No. 3, pp. 1075-1093, 2021.
See also: https:\/\/doi.org\/10.1007\/s10044-021-00960-6<\/a><\/p>\n\n\n\n
Kazuhiro Fukui:
Multilinear clustering via tensor Fukunaga\u2013Koontz transform with
Fisher eigenspectrum regularization,
Applied Soft Computing, Vol. 113,<\/em> Article 107899, 2021.
See also: https:\/\/doi.org\/10.1016\/j.asoc.2021.107899<\/a><\/p>\n\n\n\n
Skeleton-aware text image super-resolution,
Proceedings of the British Machine Vision Conference,<\/em> 2021.
See also: https:\/\/www.bmvc2021-virtualconference.com\/conference\/papers\/paper_1482.html<\/a><\/p>\n\n\n\n
Naoi, Masanori Sakaguchi:
Real-time, automatic, open-source sleep stage classification system
using single EEG for mice,
Scientific Reports, Vol. 11<\/em>, Article 11151, 2021.
See also: https:\/\/doi.org\/10.1038\/s41598-021-90332-1<\/a><\/p>\n\n\n\n
[8] Hiroyoshi Ito, Christos Faloutsos:
DualCast: Friendship-preference co-evolution forecasting for
attributed networks,
Proceedings of the SIAM International Conference on Data Mining, <\/em>2022.
See also: https:\/\/doi.org\/10.1137\/1.9781611977172.6<\/a><\/p>\n\n\n\n
Task assignment strategies for crowd worker ability improvement,
Proceedings of the ACM on Human-Computer Interaction,<\/em> 2021.
See also: https:\/\/doi.org\/10.1145\/3479519<\/a><\/p>\n\n\n\n
[10] Hiroki Saishu, Kota Kudo, Yuichi Takano:
Sparse Poisson regression via mixed-integer optimization,
PLoS ONE, Vol. 16, No. 4,<\/em> Article e0249916.
See also: https:\/\/doi.org\/10.1371\/journal.pone.0249916<\/a><\/p>\n\n\n\n
Queueing analysis of a car\/ride-share system,
Annals of Operations Research, Vol. 310, No. 2,<\/em> pp. 661-682, 2022.
See also: https:\/\/doi.org\/10.1007\/s10479-021-04313-8<\/a><\/p>\n\n\n\n
Sabine Wittevrongel:
Queueing models for cognitive wireless networks with sensing time of
secondary users,
Annals of Operations Research, Vol. 310, No. 2,<\/em> pp. 641-660, 2022.
See also: https:\/\/doi.org\/10.1007\/s10479-021-04118-9<\/a><\/p>\n\n\n\n
Design and analysis of dynamic block-setup reservation algorithm for
5G network slicing,
IEEE Transactions on Mobile Computing (accepted)<\/em>.
See also: https:\/\/doi.org\/10.1109\/TMC.2022.3169034<\/a><\/p>\n\n\n\n
[14] Yuichi Saito, Makoto Itoh, Toshiyuki Inagaki:
Bringing a vehicle to a controlled stop: Effectiveness of a dual-control
scheme for identifying driver drowsiness and preventing
lane departures under partial driving automation requiring
hands-on-wheel,
IEEE Transactions on Human-Machine Systems, Vol. 52, No. 1<\/em>, pp. 74-86, 2022.
See also: https:\/\/doi.org\/10.1109\/THMS.2021.3123171<\/a><\/p>\n\n\n\n
How does explanation-based knowledge influence driver take-over to
conditional driving automation?,
IEEE Transactions on Human-Machine Systems, Vol. 51, No. 3,<\/em> pp. 188-197, 2021.
See also: https:\/\/doi.org\/10.1109\/THMS.2021.3051342<\/a><\/p>\n\n\n\n
Effect of verbal messages with reminders to communicate driving
situations to alter driver behavior in conditional driving automation,
Transportation Research Part F: Psychology and Behaviour, Vol. 85,<\/em>
pp. 69-82, 2022.
See also: https:\/\/doi.org\/10.1016\/j.trf.2022.01.003<\/a><\/p>\n\n\n\n
Developing human-machine trust: Impacts of prior instruction and
automation failure on driver trust in partially automated vehicles,
Transportation Research Part F: Psychology and Behaviour, Vol. 81,<\/em>
pp. 384-395, 2021.
See also: https:\/\/doi.org\/10.1016\/j.trf.2021.06.013<\/a><\/p>\n\n\n\n
Effects of explanation-based knowledge regarding system functions and
driver\u2019s roles on driver takeover during conditionally automated
driving: A test track study,
Transportation Research Part F: Psychology and Behaviour, Vol. 77<\/em>,
pp. 1-9, 2021.
See also: https:\/\/doi.org\/10.1016\/j.trf.2020.11.015<\/a><\/p>\n\n\n\n
Does automation trust evolve from a leap of faith? An analysis using
a reprogrammed pasteurizer simulation task,
Applied Ergonomics, Volume 100<\/em>, Article 103674, 2022.
See also: https:\/\/doi.org\/10.1016\/j.apergo.2021.103674<\/a>.<\/p>\n\n\n\n
Revisiting human-machine trust: A replication study of Muir & Moray
(1996) using a simulated pasteurizer plant task,
Ergonomics, Vol. 64, No. 9,<\/em> pp. 1132-1145, 2021.
See also: https:\/\/doi.org\/10.1080\/00140139.2021.1909752<\/a><\/p>\n\n\n\n
Raksincharoensak, Hideo Inoue:
A context-aware driver model for determining recommended speed in
blind intersection situations,
Accident Analysis and Prevention, Vol. 163<\/em>, Article 106447, 2021.
See also: https:\/\/doi.org\/10.1016\/j.aap.2021.106447<\/a><\/p>\n\n\n\n
Yamasaki, Ryosuke Matsumi, Takuma Ito, Toshiki Kinoshita, Shintaro
Inoue, Tsukasa Shimizu, Masao Nagai, Hideo Inoue, Pongsathorn
Raksincharoensak:
Effectiveness of a driver assistance system with deceleration control
and brake hold functions in stop sign intersection scenarios,
IEEE Transactions on Intelligent Transportation Systems (accepted)<\/em>.
See also: https:\/\/doi.org\/10.1109\/TITS.2021.3085847<\/a><\/p>\n\n\n\n
Yamasaki, Takuma Ito, Shintaro Inoue, Tsukasa Shimizu, Masao Nagai,
Hideo Inoue, Pongsathorn Raksincharoensak:
Effects of a driver assistance system with foresighted deceleration
control on the driving performance of elderly and younger drivers,
Transportation Research Part F: Traffic Psychology and Behaviour, Vol.<\/em>
77,<\/em> pp. 221-235, 2021.
See also: https:\/\/doi.org\/10.1016\/j.trf.2020.12.017<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"