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A Research on Carbon Neutral Electricity System with Variable Renewable Energy based on Grid Forming Inverter
Full text link福井大学博士(工学)2025doctoral thesi
Development of XAFS Measurement Method for High-Temperature Molten Material：– Method Development and Measurement of Yttria Stabilized Zirconia Melt –
Full text link2000 Kを超える高温融体の熱物性予測計算に用いられるポテンシャルの妥当性確認や精度向上のため、高温融体の構造解析手法が必要である。本研究では高温融体のXAFS測定手法の開発を目的とし、プレート加熱法を提案した。高融点のW板を使用し、リボン型プレートとU字型プレートでイットリア安定化ジルコニアのXAFS測定を実施した。U字型プレートを用いた測定では3000 Kを超える高温融体のXAFSスペクトルやX線回折パターンを取得することができた。In order to validate and improve the accuracy of potentials used in thermophysical property prediction calculations for high-temperature melts above 2000 K, a structural analysis method for high-temperature melts is needed. In this study, a plate heating method was proposed to develop an XAFS measurement for high-temperature melts. The XAFS measurements of yttria stabilized zirconia were carried out using a ribbon plate and a U-shaped plate with a high melting point of tungsten. The XAFS spectra and X-ray diffraction patterns of high temperature melts above 3000 K were obtained by using the U-shaped plate.journal articl
More Evidence on the Unergative-Unaccusative Distinction in Second Language Grammars
Full text linkThis study presents new evidence for the structural unergative-unaccusative distinction,
in second language (L2) grammars, focusing on elementary-level Japanese-speaking
learners of English (JLEs). The underlying distinction of unergatives-unaccusatives is
often obscured on the surface strings due to independent syntactic properties such as
feature-driven subject movement (in English) or headedness (in Japanese). Nevertheless,
based on previous findings, elementary-level JLEs are expected to have reset headedness
but have not acquired subject movement. Then, the resulting representation would not
involve the properties obscuring the underlying unergative-unaccusative distinction and
potentially exhibit it on the surface strings in L2 English. Following these observations,
we carefully designed test sentences with un/grammatical word orders that elementary-
level JLEs would generate and conducted an acceptability judgment task with native
speakers of English and elementary-/intermediate-level JLEs. The results showed that,
in contrast to native controls and intermediate learners, who exhibited target-like patterns,
elementary-level JLEs incorrectly accepted ungrammatical word orders only with
unaccusatives (e.g., *When did arrive the train?) but not those with unergatives (e.g.,
*Where did dance the man?). This discrepancy can be attributed to the sensitivity to the
structural distinction of unergative-unaccusative verbs, and our data provide evidence for
the creative construction of an interlanguage in L2 acquisition.journal articl
Real-time and highly accurate position estimation system by GNSS/IMU fusion with nonlinear transformation filters
Full text linkGlobal Navigation Satellite Systems (GNSS) are widely used in transportation and autonomous driving, but face challenges like reduced accuracy in urban areas and ionospheric effects. This study integrates GNSS and Inertial Measurement Unit (IMU) data using an Unscented Kalman Filter (UKF) for real-time positioning, implemented on a Raspberry Pi. Experiments on mountain roads showed that the UKF achieved accuracy similar to GNSS in straight sections but degraded in curves due to insufficient orientation updates. The system used GNSS at 1 Hz and IMU at 300 Hz, processed via Python. Improvements in orientation updates and computational efficiency remain key challenges.departmental bulletin pape
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User Action Recognition Using a Fabric Pressure Distribution Sensor in an Electric Wheelchair for Soil Cultivation
Full text linkAdvancements in robotics technology and information and communication technology have significantly affected agriculture, especially systems that aid workers. Soil cultivation often requires prolonged bending, which results in physical strain. A commercially available work wheelchair reduces back strain, but lacks power assistance and relies on leg movements. In a previous study, we developed an electric wheelchair with a fabric pressure-distribution sensor on the seat. This sensor, combined with a fuzzy controller, aids movement by measuring the center of pressure fluctuations and reducing leg strain. However, it does not recognize user’s actions, such as standing or sitting, and requires the wheelchair to stop. This study introduced a user-action recognition system using a wheelchair seat pressure sensor. This system accurately recognizes user actions through deep learning time-series data. We evaluated data augmentation and multi-user data to enhance the performance. The results show improved prediction accuracy for action recognition in the test scenarios.journal articl