Suchergebnisse

Social Media and Online Communities -- HGNN-T5 PEGASUS: A Hybrid Approach for Chinese Long Text Summarization -- Prompt-based and Two-stage Training for Few-shot Text Classification -- A Fine-Grained Image Description Generation Method Based on Joint Objectives -- Analyzing Collective Intelligence through Sentiment Networks in Self-Organized Douban Communities -- Similarity Metrics and Visualization of Scholars Based on Variational Graph Normalized Auto-Encoders -- Scholar Influence Maximization via Opinion Leader and Graph Embedding Regression in Social Networks -- Incremental Inductive Dynamic Network Community Detection -- Er-EIR: A Chinese Question Matching Model based on Word-level and Sentence-level Interaction Features -- MOOC dropout prediction using learning process model and LightGBM algorithm -- Nonnegative Matrix Factorization Based on Topology-And-Attribute-Matching Degree for Community Detection -- Unsupervised Multi-population Evolutionary Algorithm for Community Detection in Attributed Networks -- Parallel High Utility Itemset Mining Algorithm on the Spark -- ABCD-HN: An Artificial Network Benchmark for Community Detection on Heterogeneous Networks -- A Multi-Behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning -- How hypergraph-to-graph conversion affects cooperative working visualization: A Multi-metric evaluation -- Vessel Traffic Flow Prediction and Analysis Based on Ship Big Data -- TGPPN: A Transformer and Graph Neural Network based Point Process Network Model -- Dynamic Network Link Prediction Based on Attention and Time Perception -- User's Emotional Diffusion and Public Opinion Evolution Under Public Health Emergencies -- Mobile Edge Computing Offloading Strategy Based on Deep Reinforcement Learning -- Study of Mental Model in Human-Computer Interaction Based on EEG Signal Data -- Collaborative Mechanisms, Models, Approaches, Algorithms and Systems -- A Scholarly Information Retrieval System Incorporating Recommendation with Semantic Similarity -- DAG-based Task Scheduling Optimization in Heterogeneous Distributed Systems -- A Distributed Cross-layer Protocol for Sleep Scheduling and Data Aggregation in Wireless Sensor Networks -- Time Split Network for Temporal Knowledge Graph Completion -- Deep Q-learning Based Circuit Breaking Method for Micro-services in Cloud Native Systems -- FRS4CPP: A Fair Recommendation Strategy Considering Interests of Users; Providers and Platform -- Accelerating Unsupervised Federated Graph Neural Networks Via Semi-Asynchronous Communication -- Life Cycles and Self-organized Criticality of Vietnam Empires: Based on Sandpile Model -- Multi-source Autoregressive Entity Linking Based on Generative Method -- Improving Voice Style Conversion via Self-Attention VAE with Feature Disentanglement -- Deep Reinforcement Learning for Delay and Energy-aware Task Scheduling in Edge Clouds -- A Comprehensive Review of the Oversmoothing in Graph Neural Networks -- A Foreground Feature Embedding Network for Object Detection in Remote Sensing Images -- Visitors Vis: Interactive Mining of Suspected Medical Insurance Fraud Groups -- CERender: Real-time Cloud Rendering Based on Cloud-Edge Collaboration -- Auxiliary Diagnosis of Pneumonia Based on Convolutional Attention and Parameter Migration -- End-to-end Relation-Enhanced Learnable Graph Self-attention Network for Knowledge Graphs Embedding -- Research on Signal Detection and System Recognition Techniques in Private Internet of Things -- Research on Traffic Flow Prediction and Traffic Light Timing Recommendation Technology Based on Vehicle Data Analysis -- Towards Distributed Graph Representation Learning.

The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) is a critical unanswered question. We inferred 5,642 weekly activity anomalies from the meteorology-adjusted differences in spaceborne tropospheric NO(2) column concentrations after the 2020 COVID-19 outbreak relative to the baseline from 2016 to 2019. Two satellite observations reveal reincreasing economic activity associated with lifting control measures that comes together with accelerating COVID-19 cases before the winter of 2020/2021. Application of the near-real-time satellite NO(2) observations produces a much better prediction of the deceleration of COVID-19 cases than applying the Oxford Government Response Tracker, the Public Health and Social Measures, or human mobility data as alternative predictors. A convergent cross-mapping suggests that economic activity reduction inferred from NO(2) is a driver of case deceleration in most of the territories. This effect, however, is not linear, while further activity reductions were associated with weaker deceleration. Over the winter of 2020/2021, nearly 1 million daily COVID-19 cases could have been avoided by optimizing the timing and strength of activity reduction relative to a scenario based on the real distribution. Our study shows how satellite observations can provide surrogate data for activity reduction during the COVID-19 pandemic and monitor the effectiveness of containment to the pandemic before vaccines become widely available.