FY2025 Graduation Thesis
- Konomi Shiraishi, Long-term monitoring of plastic transport in the Ishite River and Oyabe River (in Japanese)
- Yuga Kubo, Comparison of plastic degradation processes between accelerated UV degradation tests and outdoor exposure tests (in Japanese)
- Hiroki Morioke, Development and validation of a surface flow velocity measurement technique using UAVs (in Japanese)
- Haruma Shimizu, Study on noise reduction techniques for wave spectrum observation using a small buoy (in Japanese)
- Reo Tanaka, Effect of a multi-grid wave model on the accuracy of wave reproduction along the Japanese coast (in Japanese)
- Shota Kuramoto, Characterizing microplastics, including tire and road wear particles, in the Ota River basin, Hiroshima Prefecture (in Japanese)
- Chiharu Kakuto, Estimation of tire wear dust generation on land and runoff experiments (in Japanese)
FY2024 Master's Thesis
- Hiroto Oe, Development and validation of a surface transport model for terrestrial scattered plastic debris considering UV degradation and surface runoff (Outstanding Presentation Award, Master's Thesis Presentation) (in Japanese)
FY2024 Graduation Thesis
- Taiki Asayama, Validation of an AI-based monitoring technique for riverine plastic litter and assessment of its transport dynamics (in Japanese)
- Kanta Yano, Spatiotemporal variation of microplastic mass flux in a tidal reach during spring tide (in Japanese)
- Haruhiko Otori, Evaluation of fine plastic fragment generation through accelerated UV degradation and physical fragmentation experiments (in Japanese)
- Yoshiki Takata, Development of a non-contact flow velocity measurement method using image analysis (in Japanese)
- Shunsuke Komoda, An attempt to estimate the residence time of plastic litter in the Shigenobu River basin based on surface roughness (in Japanese)
- Shin Yunho, Optimization of a deep learning model for wind and wave observation using HF radar (in Japanese)
FY2023 Graduation Thesis
- Yota Iga, Tidal-cycle variation of microplastics in a tidal river (in Japanese)
- Kyosuke Takaoka, Continuous observation of macroplastic debris transport in an actual river using IoT sensing technology (in Japanese)
- Soichiro Nozawa, Differences in the UV degradation rate of plastic litter under wet and dry conditions (in Japanese)
- Tomohiro Miyake, Advantages of a deep learning model for wind and wave observation using ocean radar (in Japanese)
- Seiichi Yamamoto, Validation of detection accuracy for riverine macroplastic debris using instance segmentation (in Japanese)
FY2022 Graduation Thesis
- Ryosuke Ikezumi, Accuracy evaluation of a deep-learning-based method for measuring riverine macroplastic debris transport (in Japanese)
- Kouhei Oishi, Effectiveness of applying a deep learning model to wave spectrum estimation using HF ocean radar (in Japanese)
- Hiroto Oe, Development and validation of a degradation model for plastic litter within a river basin based on UV irradiation experiments (in Japanese)
- Atsushi Takaue, A study on the concentration distribution and dynamics of microplastics in sediments along the Shigenobu riverbank (in Japanese)
- Toi Matsuura, Contamination status of fine microplastics in river water of the Shigenobu River basin (in Japanese)
FY2021 Graduation Thesis
- Aimi Iwaki, Development of a noise-reduction filter for Doppler spectra using deep learning (in Japanese)
- Sora Uetake, Accuracy validation toward a low-cost coastal surveying system using a stereo-camera-equipped UAV (in Japanese)
- Sho Okamoto, Study on a deep learning model for general-purpose wave information extraction using HF ocean radar (in Japanese)
- Takaaki Takuwa, Basic experiments for evaluating the degradation degree of terrestrial scattered plastics (in Japanese)
- Soushi Takenaka, Comparative study of deep-learning-based detection models for riverine macroplastics (in Japanese)