Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep ...
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In this work, we put forward and demonstrate a bi-direction free-space visible light communication (VLC) system supporting multiple moveable receivers (Rxs) using a light-diffusing optical fiber (LDOF). The downlink (...
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Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety ...
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ISBN:
(数字)9798331513283
ISBN:
(纸本)9798331513290
Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety of landing platforms are required. In this context, this paper presents a servo-visual controller that uses pattern detection and color segmentation techniques to identify take-off/landing platforms and estimate their current orientation. The proposed system was subjected to experimental validation with four platforms positioned in different orientations, heights, and positions, demonstrating its versatility in various conditions. Our study addresses the Flying Robots Trial League challenge, which emulates mapping and inspection tasks in offshore platforms.
Hypertension is a noncommunicable disease (NCD) that causes global concern, high costs and a high number of deaths. Internet of Things, Ubiquitous Computing, and Cloud Computing enable the development of systems for r...
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Exceptional point (EP)-based optical sensors exhibit exceptional sensitivity but poor detectivity. Slightly off EP operation boosts detectivity without much loss in sensitivity. We experimentally demonstrate a high-de...
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The phenomenon of urbanization in Indonesia is inevitable. The new residential and economic centers in suburban areas is also a problem in city development. The gradual planning and development of smart cities in a li...
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Graph neural networks are a promising deep learning method that can apply graph structures to various tasks. In real-world scenarios, we often have heterogeneous graphs, wherein different node and edge types capture c...
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Graph neural networks are a promising deep learning method that can apply graph structures to various tasks. In real-world scenarios, we often have heterogeneous graphs, wherein different node and edge types capture complex interactions between nodes. High-dimensional node features provide rich information about the target nodes. Conventional heterogeneous graph neural networks (HGNN) focus more on graph structures than node features and may have difficulties extracting knowledge from complex node features. In this study, we propose a novel framework, the tree-boosted heterogeneous graph neural network abbreviated as TreeXGNN, which could efficiently and automatically extract target node features via gradient-boosted decision trees (GBDT). It integrates community structure information with proper fusion modules and a shared feature space design on HGNN. We achieved state-of-the-art performance on the three well-known heterogeneous graph benchmark datasets, IMDB, DBLP, and ACM, and significantly improved performance compared to previous studies. Our work paves the foundation for integrating tree-based models to boost HGNNs for general community analysis.
We theoretically propose and experimentally demonstrate nonlocal metasurfaces rationally designed using symmetry-breaking principles to manipulate the optical wavefront with a geometric phase selective to custom ellip...
In basketball game, players need to learn how to take a next appropriate action by judging various situations with surrounding players through team practice. Such decision-making capabilities in individual practice wi...
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Exceptional points (EPs) are critical points in the parameter space of non-Hermitian systems, where two or more eigenvalues and eigenvectors simultaneously coalesce. The remarkable physics and behavior of waves at the...
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Exceptional points (EPs) are critical points in the parameter space of non-Hermitian systems, where two or more eigenvalues and eigenvectors simultaneously coalesce. The remarkable physics and behavior of waves at these EPs have raised considerable attention. Previous research has accessed EPs in parity-time (PT) symmetric systems through spatially modulated parameters. Using acoustics, this Letter demonstrates a different family of EPs in classical wave systems that emerge from coordinated modulation of mass density and loss/gain in time. This condition can create nonreciprocal coupling between arbitrary modes at the EPs, leading to exotic behaviors such as unilateral frequency conversion and linear amplification of waves that are unattainable at conventional time-invariant systems. Moreover, these phenomena can be attained with only loss, and acoustic gain via modal energy transfer is demonstrated in a loss-only system at such EPs. Our work marries time-varying systems with EPs, which could open new avenues for wave manipulation.
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