Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are ***...
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Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.
In this study,relevant work on autonomy evaluation(AE)in recent years was comprehensively reviewed and classified from the perspective of task models,and a closed-loop task models based theoretical framework for AE wa...
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In this study,relevant work on autonomy evaluation(AE)in recent years was comprehensively reviewed and classified from the perspective of task models,and a closed-loop task models based theoretical framework for AE was *** main contributions of this study are as follows.1)A taxonomy for AE based on task models was introduced to classify current theories,methods and standards.2)The limitations of the current autonomous evaluation methods were addressed to provide a theoretical framework for quantitative evaluation based on task models,and evaluation metrics for each stage were proposed based on the AE theoretical framework.3)Qualitative analyses of the superiority of the proposed AE framework based on the closed-loop task models were *** study attempts to provide a reference for researchers and engineers in the autonomous unmanned systems field and inspire future development of AE.
Dear Editor,Scene understanding is an essential task in computer *** ultimate objective of scene understanding is to instruct computers to understand and reason about the scenes as humans *** vision is a research fram...
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Dear Editor,Scene understanding is an essential task in computer *** ultimate objective of scene understanding is to instruct computers to understand and reason about the scenes as humans *** vision is a research framework that unifies the explanation and perception of dynamic and complex scenes.
Dear Editor,This letter proposes a new pattern matching method based on word embedding and dynamic time warping(DTW)to identify groups of similar alarm ***,alarm messages are transformed into numeric values that repre...
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Dear Editor,This letter proposes a new pattern matching method based on word embedding and dynamic time warping(DTW)to identify groups of similar alarm ***,alarm messages are transformed into numeric values that represent alarms and also reflect the relationships between alarm ***,similarities between numerically encoded alarm flood sequences are calculated by DTW and groups of similar floods are identified via *** effectiveness of the proposed method is demonstrated by a case study with alarm&event data obtained from a public industrial simulation model.
With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the...
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The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast response. However, due to the inherent nonlinearity of multiplication, it brings certain d...
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Driving in interactive dynamic traffic is a huge challenge for autonomous vehicles, especially for motion planning. The autonomous vehicle not only needs to predict the future states of the social vehicles to avoid a ...
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The evaluation of regional geological hazard susceptibility is of great significance to the prevention and control of geological hazard. In this paper, the "4-20"Lushan earthquake disaster area as the resear...
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The inter-class similarity of facial expressions is one of the key challenges in Facial Expression Recognition(FER).In this manuscript,a Latent Facial Action Units Network(LAUNet) is proposed for the problem of inter-...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
The inter-class similarity of facial expressions is one of the key challenges in Facial Expression Recognition(FER).In this manuscript,a Latent Facial Action Units Network(LAUNet) is proposed for the problem of inter-class similarity of facial expressions in *** proposed method recognizes subtle differences between facial expressions by learning Latent Facial Action Units Features(LAUFs).Specifically,LAUNet is composed of two parts:the Latent Facial Action Units Features Extraction Network(LEN) and the Latent Facial Action Units Selection Network(LSN).Firstly,LEN extracts LAUFs from the feature map of the backbone using the spatial attention ***,taking advantage of the channel attention mechanism,LSN captures the latent relationships between features from LAUFs to select effective features for *** are performed on the dataset after removing the invalid data of non-face images from the original FER2013 *** with some previous state-of-the-art methods,LAUNet achieves the highest accuracy rate of 71.31%.Depending on the backbone,LAUNet can improve the accuracy by up to 5.46% compared to the original architecture of the backbone.
A Multimodal Emotion Perception model with Audio and Visual modalities(MEP-AV) is proposed to detect the individual emotions in public *** framework of MEP-AV model consists of four parts,i.e.,data collection module,a...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
A Multimodal Emotion Perception model with Audio and Visual modalities(MEP-AV) is proposed to detect the individual emotions in public *** framework of MEP-AV model consists of four parts,i.e.,data collection module,audio expression analysis module,visual expression analysis module and multimodal fusion *** order to ensure that the emotion perception results meet the requirement of short-term continuity,a Context-Aware Decision-Level Fusion(CADLF) model is proposed and applied in multimodal fusion *** CADLF model estimates the affective status by using context information of multimodal *** short-term continuity is considered to improve the accuracy of the emotion perception *** experiment results evaluated by various metrics demonstrate that the performance of the multimodal structure is improved compared with that of unimodal emotion *** MEP-AV model using multimodal fusion algorithm provides the accuracies of70.89% and 77.07% in valence and arousal *** F1-scores reaches 70.2% and 75.6% respectively,indicating the boost performance on emotion perception.
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