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187 results on '"Li, Shi-Min"'

1. In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking

Author

Gao, Peng, Li, Shi-Min, Gao, Feng, Wang, Fei, Yuan, Ru-Yue, and Fujita, Hamido

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep learning-based methods monopolize the latest research in the field of thermal infrared (TIR) object tracking. However, relying solely on deep learning models to obtain better tracking results requires carefully selecting feature information that is beneficial to representing the target object and designing a reasonable template update strategy, which undoubtedly increases the difficulty of model design. Thus, recent TIR tracking methods face many challenges in complex scenarios. This paper introduces a novel Deep Bayesian Filtering (DBF) method to enhance TIR tracking in these challenging situations. DBF is distinctive in its dual-model structure: the system and observation models. The system model leverages motion data to estimate the potential positions of the target object based on two-dimensional Brownian motion, thus generating a prior probability. Following this, the observation model comes into play upon capturing the TIR image. It serves as a classifier and employs infrared information to ascertain the likelihood of these estimated positions, creating a likelihood probability. According to the guidance of the two models, the position of the target object can be determined, and the template can be dynamically updated. Experimental analysis across several benchmark datasets reveals that DBF achieves competitive performance, surpassing most existing TIR tracking methods in complex scenarios.

Published
2024
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4. Interactions between a central bubble and a surrounding bubble cluster

Author

Zhang, A-Man, Li, Shi-Min, Cui, Pu, Li, Shuai, and Liu, Yun-Long

Subjects
Physics - Fluid Dynamics
Abstract

The interaction of multiple bubbles is a complex physical problem. A simplified case of multiple bubbles is studied theoretically with a bubble located at the center of a circular bubble cluster. All bubbles in the cluster are equally spaced and own the same initial conditions as the central bubble. The unified theory for bubble dynamics (Zhang et al. arXiv:2301.13698) is applied to model the interaction between the central bubble and the circular bubble cluster. To account for the effect of the propagation time of pressure waves, the emission source of the wave is obtained by interpolating the physical information on the time axis. An underwater explosion experiment with two bubbles of different scales is used to validate the theoretical model. The effect of the bubble cluster with a variation in scale on the pulsation characteristics of the central bubble is studied.

Published
2023
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5. A unified theory for bubble dynamics

Author

Zhang, A-Man, Li, Shi-Min, Cui, Pu, Li, Shuai, and Liu, Yun-Long

Subjects
Physics - Fluid Dynamics
Abstract

In this work, we established a novel theory for the dynamics of oscillating bubbles such as cavitation bubbles, underwater explosion bubbles, and air bubbles. For the first time, we proposed bubble dynamics equations that can simultaneously take into consideration the effects of boundaries, bubble interaction, ambient flow field, gravity, bubble migration, fluid compressibility, viscosity, and surface tension while maintaining a unified and elegant mathematical form. The present theory unifies different classical bubble equations such as the Rayleigh-Plesset equation, the Gilmore equation, and the Keller-Miksis equation. Furthermore, we validated the theory with experimental data of bubbles with a variety in scales, sources, boundaries, and ambient conditions and showed the advantages of our theory over the classical theoretical models, followed by a discussion on the applicability of the present theory based on a comparison to simulation results with different numerical methods. Finally, as a demonstration of the potential of our theory, we modeled the complex multi-cycle bubble interaction with wide ranges of energy and phase differences and gained new physical insights into inter-bubble energy transfer and coupling of bubble-induced pressure waves.

Published
2023
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10. Target organ damage in untreated hypertensive patients with primary aldosteronism

Author

Li, Shi‐Min, primary, Huang, Jia‐Yi, additional, Zhu, Ching‐Yan, additional, Ng, Ming‐Yen, additional, Lin, Qing‐Shan, additional, Wu, Min, additional, Liu, Ming‐Ya, additional, Wang, Run, additional, Cao, Gao‐Zhen, additional, Chen, Cong, additional, Wu, Mei‐Zhen, additional, Ren, Qing‐Wen, additional, Tse, Hung‐Fat, additional, and Yiu, Kai‐Hang, additional

Published
2024
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12. Bubble collapse patterns recognition and flow field prediction based on machine learning.

Author

Chen, Hao, Ren, Shao-Fei, Li, Shi-Min, Zhang, Shuai, and Zhang, Guo-Fei

Subjects
ARTIFICIAL neural networks, PATTERN recognition systems, BOUNDARY element methods, MACHINE learning, SUPPORT vector machines, FREE surfaces
Abstract

A machine learning method is proposed to predict the collapse patterns and flow field state of underwater explosion bubbles subjected to the vertical sidewall and free surface, which can overcome the limitations of high costs of traditional experimental tests and long computation times of numerical simulations. The dataset was obtained by the boundary element method, including the cases of the bubble with different buoyancy parameters at different distances from the free surface and vertical sidewall. Due to the strong geometric nonlinearity of the bubble influenced by boundary, three classification models are adopted to identify the collapse patterns of bubbles, which are support vector machines, K nearest neighbor, and decision tree. Meanwhile, an ensemble learning (EL) model based on the three classification models is adopted to enhance the prediction accuracy. Furthermore, three regression models, which are deep neural network (DNN), extreme learning machine (ELM), and random forest (RF), were adopted and compared to predict flow field information around the bubble. The results show that EL exhibits better robustness to the distribution and proportion of samples when identifying collapse patterns. Meanwhile, compared with ELM and RF, DNN demonstrates stronger performance in capturing nonlinear relationships, especially in regions where the bubble curvature changes abruptly. Moreover, a learning rate decay strategy is proposed to effectively suppress the phenomenon of loss oscillation in the training process of DNN based on adaptive activation functions. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Temporal and Spatial Variations of Enriched Source Components in Linzizong Volcanic Succession, Tibet, and Implications for the India–Asia Collision.

Author

Liu, An-Lin, Wang, Qing, Zhu, Di-Cheng, Cawood, Peter A, Xia, Ying, Li, Shi-Min, Liu, Sheng-Ao, Huang, Fang, Liu, Li, Zhao, Zhi-Dan, and Mo, Xuan-Xue

Subjects
SPATIAL variation, YTTERBIUM, SUTURE zones (Structural geology), MAFIC rocks
Abstract

The temporal and spatial distribution of enriched source components at sites of continent–continent collision provides critical insights into mantle dynamic processes associated with subduction- and collision-related events. However, determining the origin of such enriched components remains a significant challenge. We report a comprehensive dataset of the Linzizong volcanic succession (LVS) from four locations with varying distance across-strike to the Indus–Yarlung suture in southern Tibet, which marks the exposed surface expression of the India–Asia collision zone. The LVS rocks in this study can be divided into two groups: a calc-alkaline Group 1 (69–55 Ma), mainly including basaltic–andesitic varieties, and a shoshonitic Group 2 (52–50 Ma), consisting predominantly of silicic rocks with minor mafic compositions. Group 1 samples are likely derived from the fractional crystallization of primitive basaltic melts as a result of the partial melting of a metasomatized mantle wedge. These samples are decoupled in Nd–Hf isotopic compositions, suggesting an incorporation of subducting sediment-derived melts into the mantle wedge. The influence of sediment-derived melt on the mantle source increases away from the suture zone toward Asia (i.e. from the south to the north) as indicated by the more enriched Sr, Nd, Pb, and Hf isotopic compositions, as well as elevated Th/La and La/Sm ratios. The heavy δ26Mg values, and high Ba/Th and Sr/Th ratios of samples close to the suture coincide with the dehydration of the subducting Neo-Tethyan slab. Group 2 mafic samples have depleted and coupled εNd–εHf isotopic compositions and are characterized by elevated (La/Yb)N and Dy/Yb ratios as well as low Zr/Nb ratios, indicating an origin of enriched garnet-bearing lithospheric mantle with contributions from asthenosphere-derived materials. Group 2 silicic samples are isotopically enriched both near and far away from the suture, which can be attributed to the involvement of ancient lower crust-derived melt from Tethyan Himalaya and central Lhasa subterrane basement, respectively. Our results show that the LVS are the magmatic response to late subduction (Group 1), and to initial India–Asia collision and slab breakoff (Group 2). Negative trends in the whole-rock Nd and zircon Hf isotopic compositions at ~51 Ma should be treated with caution for geodynamic interpretations, depending on the distance between the samples and the India–Asia suture. [ABSTRACT FROM AUTHOR]

Published
2022
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