293 research outputs found

    BIOMECHANICAL ANALYSIS OF WALKING AND TAKING-OFF ON SPRINGBOARD OF JIANGSU DIVING ATHLETES

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    Priority event and key event ,in the Chinese Olympic strategy, diving is becoming more difficult, i.e., advantage means difficult high-quality performance. As walking on springboard and jumping is key to diving performance, it is vital to study diving athletes to improve their diving skills

    The Royalflush System for VoxCeleb Speaker Recognition Challenge 2022

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    In this technical report, we describe the Royalflush submissions for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). Our submissions contain track 1, which is for supervised speaker verification and track 3, which is for semi-supervised speaker verification. For track 1, we develop a powerful U-Net-based speaker embedding extractor with a symmetric architecture. The proposed system achieves 2.06% in EER and 0.1293 in MinDCF on the validation set. Compared with the state-of-the-art ECAPA-TDNN, it obtains a relative improvement of 20.7% in EER and 22.70% in MinDCF. For track 3, we employ the joint training of source domain supervision and target domain self-supervision to get a speaker embedding extractor. The subsequent clustering process can obtain target domain pseudo-speaker labels. We adapt the speaker embedding extractor using all source and target domain data in a supervised manner, where it can fully leverage both domain information. Moreover, clustering and supervised domain adaptation can be repeated until the performance converges on the validation set. Our final submission is a fusion of 10 models and achieves 7.75% EER and 0.3517 MinDCF on the validation set

    THEORETICAL ANALYSES ON "SPLASH" FORMATION OF COMPETITIVE DIVING

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    Based upon our work in theoretical analysis and computer simulation of the impact process between diver and water, the purpose of this study was to analyze mechanisms of "splash" formation. The entry technique with palms facing each other was simplified as water entry of a "wedged" object. The entry technique with internal rotation of the arms to form a flat impact surface with the palms was simplified as water entry of a "rectangle". Finally, the water entry with rotation was treated as water entry of a "rotating rectangle", Further mechanical analyses were performed to synthesize "splash" formation mechanisms of these different objects under various impact conditions, and formulate a splash control theory that combines an active impact and a "massaging" motion of water by both hands

    Multi-level structured self-attentions for distantly supervised relation extraction

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    Attention mechanisms are often used in deep neural networks for distantly supervised relation extraction (DS-RE) to distinguish valid from noisy instances. However, traditional 1- D vector attention models are insufficient for the learning of different contexts in the selection of valid instances to predict the relationship for an entity pair. To alleviate this issue, we propose a novel multi-level structured (2-D matrix) self-attention mechanism for DS-RE in a multi-instance learning (MIL) framework using bidirectional recurrent neural networks. In the proposed method, a structured word-level self-attention mechanism learns a 2-D matrix where each row vector represents a weight distribution for different aspects of an instance regarding two entities. Targeting the MIL issue, the structured sentence-level attention learns a 2-D matrix where each row vector represents a weight distribution on selection of different valid instances. Experiments conducted on two publicly available DS-RE datasets show that the proposed framework with a multi-level structured self-attention mechanism significantly outperform state-of-the-art baselines in terms of PR curves, P@N and F1 measures

    Multiplexed genotyping of single nucleotide polymorphisms using microarray technology

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