本企画は、(一社)北陸地域づくり協会の研究助成事業により実施しています。
成果の一部を財団発行の助成研究論文集の冊子で閲覧可能です。
上述の遠隔観察・操作技術は、新潟県長岡市が主催とする地域継続型シンクタンク「NaDeC BASE」を通して、「長岡技術科学大学・長岡技術科学大学卒業の佐世保高専教員」から提供されたものです。既知・公知の随分前から確立された技術で安定的な遠隔操作が可能です。興味のある企業、個人は「NaDeC BASE」に問い合わせをお願いします。
ここに「NaDeC BASE」および「佐世保高専」・「長岡高専」・「長岡技術科学大学」への謝辞を表記します。
A. Abbas, J. Mosseri, J. Lex, J. Toor, B. Ravi, E. Khalil, and C. Whyne: “Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty”, International Journal of Medical Informatics, Vol. 158, 104670, 2022.
Construction Department of Ebetsu city: Ebetsu city snow countermeasures basic plan, pp. 1-28 (2007) (in Japanese)
D. Guo, N. Pepin, K. Yang, J. Sun, and D. Li.; Local changes in snow depth dominate the evolving pattern of eleva-tion-dependent warming on the Tibetan Plateau, Science Bulletin, (2021) Vol. 66, pp. 1146-1150.
D. Yan, N. Ma, and Y. Zhang.; Development of a fine-resolution snow depth product based on the snow cover probability for the Tibetan Plateau, Journal of Hydrology, (2022) Vol. 604, 127027, pp. 1-16.
F. Ramirez, R. Salinas, and R. Carnicer: “Tracking fiducial markers with discriminative correlation filters”, Image and Vision Computing, Vol. 107, 104094, 2021.
H. Balanji, A. Turgut, and L. Tunc: “A novel vision-based calibration framework for industrial robotic manipulators”, Robotics and Computer-Integrated Manufacturing, Vol. 73, 102243, 2022.
H. Sano: “Development of snow cover detection sensor using image processing method”, Annual report of ti-ikigijutsu, Industrial Technology Center of Fukui prefecture, Vol. 16, No. 2, pp. 1-10, 2003 (in Japanese)
H. Sarmadi, R. Salinas, M. Berbís, A. Luna, and R. Carnicer: “Joint scene and object tracking for cost-Effective augmented reality guided patient positioning in radiation therapy”, Computer Methods and Programs in Biomedicine, Vol. 209, 106296, 2021.
H. Shimoata: “Risk factors and prevention of dementia”, Annual report of Institute of Health and Nutrition Nagoya University of Arts and Sciences, Vol. 7, pp. 1-14, 2015 (in Japanese)
H. Takenaka, and M. Soga.; Development of a support system for reviewing and learning historical events by active simu-lation using AR markers, Procedia Computer Science, (2019) Vol. 159, pp. 2355-2363.
J. Donager, T. T. Sankey, A. J. S. Meador, J. B. Sankey, and A. Springer.; Integrating airborne and mobile lidar data with UAV photogrammetry for rapid assessment of changing forest snow depth and cover, Science of Remote Sensing, (2021) Vol. 4, 100029, pp. 1-12.
J. Liu, R. Chen, Y. Ding, C. Han, and S. Ma.; Snow process monitoring using time-lapse structure-from-motion photogram-metry with a single camera, Cold Regions Science and Technology, (2021) Vol. 190, 103355, pp. 1-12.
J. Mayer, K. Boretzky, C. Douma, E. Hoemann, and A. Zilges: “Classical and machine learning methods for event reconstruction in NeuLAND”, Nuclear Inst. and Methods in Physics Research, Section A, Vol. 1013, 165666, 2021.
J. Revuelto, E. A. Gonzalez, I. V. Gayan, E. Lacroix, E. Izagirre, G. R. López, and J. I. L. Moreno.; Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain, Cold Regions Science and Technology, (2021) Vol. 190, 10334, pp. 1-12.
J. W. Yang, L. M. Jiang, J. Lemmetyinen, J. M. Pan, K. Loujus, and M. Takala.; Improving snow depth estimation by coupling HUT-optimized effective snow grain size parameters with the random forest approach, Remote Sensing of Environment, (2021) Vol. 264, 112630, pp. 1-19.
K. Maier, A. Nascetti, W. Pelt, and G. Rosqvist.; Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation, ISPRS Journal of Photogrammetry and Remote Sensing, (2022) Vol. 186, pp. 1-18.
M. Ishiguro, S. Matsui, M. Nakagawa, T. Tajiri, S. Kaneko, and Y. Yoshii: “Compression and extrusion processes for snow disposal using a rectangular cross-section die container”, JSDE, Vol. 53, Issue 1, pp. 69-84, 2018.
M. Ishiguro, K. Dan, K. Nakasora, Y. Morino, Y. Yoshii, and T. Chaki: “Increase of snow compaction density by repeated artificial snow consolidation formation”, JIIAE, Vol. 8, No. 3, pp. 104-111, 2020.
M. Ishiguro, Y. Yoshii, and T. Chaki.; Impulsive repeated snow compaction for snow removal assist, ISATE2022, S2R5-P2, (2022) pp. 1-6.
M. Ishiguro, T. Futayama, Y. Yoshii, and T. Chaki.; Simple Remote Place Snowpack Depth Evaluation Procedure using Open Source Software, (2022) JIIAE, Vol. 10, pp. 77-83.
M. Ito, and M. Miura.; Evaluation of stationary colour AR markers for camera-based student response analyser, Procedia Computer Science, (2016) Vol. 96, pp. 904-911.
M. Kopp, Y. Tuo, and M. Disse.; Fully automated snow depth measurements from time-lapse images applying a convolutional neural network, Science of the Total Environment, (2009) Vol. 697, 134213, pp. 1-10.
M. Naji, S. Filali, K. Aarika, E. Benlahmar, R. Abdelouhahid, and O. Debauche: “Machine learning algorithms for breast cancer prediction and diagnosis”, Procedia Computer Science, Vol. 191, pp. 487-492, 2021.
M. Neges, C. Koch, M. König, and M. Abramovici.; Combining visual natural markers and IMU for improved AR based indoor navigation, Advanced Engineering Informatics, (2017) Vol. 31, pp. 18-31.
M. Sokolowska, M. Mazurek, M. Majer, and M. Podpora: “Classification of user attitudes in Twitter – beginners guide to selected Machine Learning libraries”, IFAC-PaperOnLine, Vol. 52, Issue 27, pp. 394-399, 2019.
M. Tateno.; Fundamental research on automatic hot water spreading type snow melting equipment for roofs and gardens, Graduation thesis of National Institute of Technology, Toyama College, (2021) pp. 1-14. (in Japanese).
M. Zaremehrjardy, S. Razavi, and M. Faramarzi.; Assessment of the cascade of uncertainty in future snow depth projections across watersheds of mountainous, foothill, and plain area in northern latitudes, Journal of Hydrology, (2021) Vol. 598, 125735, pp. 1-17.
P. Boonbrahm, C. Kaewrat, and S. Boonbrahm.; Effective collaborative design of large virtural 3D model using multiple AR markers, Procedia Manufacturing, (2020) Vol. 42, pp. 387-392.
Q. Wu.; Season-dependent effect of snow depth on soil microbial biomass and enzyme activity in a temperate forest in Northeast China, Catena, (2020) Vol. 195, 104760, pp. 1-11.
R. G. Mihalyi, K. Pathak, N. Vaskevicius, T. Fromm, and A. Birk.; Robust 3D object modeling with a low-cost RGBD-sensor and AR-markers for applications with untrained end-users, Robotics and Autonomous Systems, (2015) Vol. 66, pp. 1-17.
R. Waller and L. Visagie: “Pose estimation for cubesat docking”, IFAC-PapersOnLine, Vol. 54, Issue 21, pp. 216-221, 2021
S. Matsumura: New social challenges from 2006 heavy snowfall, Proceedings of NIED Snow and Ice Research 2006, pp. 7-12 (2006) (in Japanese)
S. Miyamoto: “Snow-melting system and de-icing system on road surface using natural thermal energy sources”, J. of Snow Eng. of Japan, Vol. 17, No. 1, pp. 35-53, 2001 (in Japanese)
T. Asada: “Prevalence of dementia in Japan”, Clin. Neurol, Vol. 52, No. 11, pp. 962-964, 2012 (in Japanese)
T. Futayama.; A fundamental research of remote place snowpack depth evaluation using sound cognization and image processing, Graduation thesis of National Institute of Technology, Toyama College, (2022) pp. 1-8. (in Japanese).
T. Takeda, K. Kondo, H. Hirai, and C. Murata: “Psychosocial factors as predictors for dementia among community-dwelling older people”, Asian Journal of Occupational Therapy, Vol. 26, No. 1, pp. 55-65, 2007 (in Japanese)
Toyama Prefecture Regional Promotion Division.; Fact-finding survey on the living conditions of villages in hilly and mountainous area in Toyama Prefecture, (2020) pp. 1-2. (in Japanese).
X. Ge, J. Zhu, D. Lu, D. Wu, F. Yu, and X. Wei.; Effect of canopy composition on snow depth and be-low-the-snow-temperature regimes in the temperate secondary forest ecosystem, Northeast China, Agricultural and Forest Meteorology, (2022) Vol. 313, 108744, pp. 1-16.
Y. Kang, and S. Han.; An alternative method for smartphone input using AR markers, Journal of Computational Design and Engineering, (2014) Vol. 1, pp. 153-160.
Y. Zhong, Z. Wang, A. Yalamanchili, A. Yadav, B. Srivatsa, S. Saripalli, and S. Bukkapatnam: “Image-based flight control of unmanned aerial vehicles for material handling in custom manufacturing”, Journal of Manufacturing Systems, Vol. 56, pp. 615-621, 2020
Z. Li, P. Chen, N. Zheng, and H. Liu.; Accuracy analysis of GNSS-IR snow depth inversion algorithms, Advances in Space Research, (2021) Vol. 67, pp. 1317-1332.
Z. J. Suriano, D. A. Robinson, and D. J. Leathers.; Changing snow depth in the Great Lakes basin, Anthropocene, (2019) Vol. 26, 100208, pp. 1-11.