1,125 research outputs found
新しい軟骨弾性係数測定法による膝関節軟骨の弾性係数低下は組織学的な早期軟骨変性所見を正確に反映する
京都大学新制・課程博士博士(医学)甲第25186号医博第5072号京都大学大学院医学研究科医学専攻(主査)教授 安達 泰治, 教授 森本 尚樹, 教授 羽賀 博典学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDFA
MotionAug: Augmentation with Physical Correction for Human Motion Prediction
This paper presents a motion data augmentation scheme incorporating motion
synthesis encouraging diversity and motion correction imposing physical
plausibility. This motion synthesis consists of our modified Variational
AutoEncoder (VAE) and Inverse Kinematics (IK). In this VAE, our proposed
sampling-near-samples method generates various valid motions even with
insufficient training motion data. Our IK-based motion synthesis method allows
us to generate a variety of motions semi-automatically. Since these two schemes
generate unrealistic artifacts in the synthesized motions, our motion
correction rectifies them. This motion correction scheme consists of imitation
learning with physics simulation and subsequent motion debiasing. For this
imitation learning, we propose the PD-residual force that significantly
accelerates the training process. Furthermore, our motion debiasing
successfully offsets the motion bias induced by imitation learning to maximize
the effect of augmentation. As a result, our method outperforms previous
noise-based motion augmentation methods by a large margin on both Recurrent
Neural Network-based and Graph Convolutional Network-based human motion
prediction models. The code is available at
https://github.com/meaten/MotionAug.Comment: Accepted at CVPR202
Fast Inference and Update of Probabilistic Density Estimation on Trajectory Prediction
Safety-critical applications such as autonomous vehicles and social robots
require fast computation and accurate probability density estimation on
trajectory prediction. To address both requirements, this paper presents a new
normalizing flow-based trajectory prediction model named FlowChain. FlowChain
is a stack of conditional continuously-indexed flows (CIFs) that are expressive
and allow analytical probability density computation. This analytical
computation is faster than the generative models that need additional
approximations such as kernel density estimation. Moreover, FlowChain is more
accurate than the Gaussian mixture-based models due to fewer assumptions on the
estimated density. FlowChain also allows a rapid update of estimated
probability densities. This update is achieved by adopting the \textit{newest
observed position} and reusing the flow transformations and its
log-det-jacobians that represent the \textit{motion trend}. This update is
completed in less than one millisecond because this reuse greatly omits the
computational cost. Experimental results showed our FlowChain achieved
state-of-the-art trajectory prediction accuracy compared to previous methods.
Furthermore, our FlowChain demonstrated superiority in the accuracy and speed
of density estimation. Our code is available at
\url{https://github.com/meaten/FlowChain-ICCV2023}Comment: Accepted at ICCV202
Immunostimulation-Mediated Anti-tumor Activity of Bamboo (Sasa senanensis) Leaf Extracts Obtained Under ‘Vigorous’ Condition
Traditional Japanese medicine uses the leaves of Kumaizasa bamboo extracted in hot water at 100°C. For this study, we developed a new, ‘vigorous’ extraction method involving steps at 100, 121 and 196°C. This procedure not only yielded greater amounts of extract but also with significant increase in immunostimulating activity, which induces activation of human natural killer (NK) cells, macrophages and potent induction of IL-2, IL-12 and IFN-γ in tumor bearing mice. The efficacy of the extract to facilitate phagocytosis and nitric oxide production by mouse peritoneal macrophages was determined and compared with that of 1,3-β-glucan. Anti-tumor activity was evaluated in vivo in several mouse tumor models (S-180, C38 and Meth-A). Oral administration of the extracts was carried out when tumor reached size of approximately 6 mm at concentrations of 0.05% or higher. The extracts significantly suppressed tumor growth in S-180 and C38 tumor models. Overall survival was significantly prolonged in the treatment group than that of control. Activation of macrophages and NK cells by the extracts suggests that the anti-tumor efficacy of the extract is mediated by immunopotentiation. The extracts resolved into three major fractions (F-I, F-II and F-III) in Sephadex gel chromatography. Fraction F-I consists of 1,3-β-glucan and stimulated both macrophages and NK cells suggesting that it may be the primary immunopotentiating factor in suppressing cancer. Fraction F-III has potent free radical scavenging effects and may play an important role in cancer prevention. These results warrant further translation and clinical investigations
Remote defect imaging for plate-like structures based on the scanning laser source technique
In defect imaging with a scanning laser source technique, the use of a fixed receiver realizes stable measurements of flexural waves generated by laser at multiple rastering points. This study discussed the defect imaging by remote measurements using a laser Doppler vibrometer as a receiver. Narrow-band burst waves were generated by modulating laser pulse trains of a fiber laser to enhance signal to noise ratio in frequency domain. Averaging three images obtained at three different frequencies suppressed spurious distributions due to resonance. The experimental system equipped with these newly-devised means enabled us to visualize defects and adhesive objects in plate-like structures such as a plate with complex geometries and a branch pipe.44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOLUME 37, 16–21 July 2017, Provo, Utah, USATakahiro Hayashi, Atsuya Maeda, and Shogo Nakao, "Remote defect imaging for plate-like structures based on the scanning laser source technique", AIP Conference Proceedings 1949, 090006 (2018) https://doi.org/10.1063/1.503156
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