Titlebook: Artificial Intelligence and Machine Learning; First International Hai Jin,Yi Pan,Jianfeng Lu Conference proceedings 2024 The Editor(s) (if

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Deep Learning for Protein-Protein Contact Prediction Using Evolutionary Scale Modeling (ESM) Featurction and drug design. Traditional experimental methods for identifying these sites are expensive and time-consuming, prompting the emergence of computational forecasting tools. However, the performance of these tools tends to be limited due to single experimental training data and other limitations

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FedTag: Towards Automated Attack Investigation Using Federated Learning,, and the security of their systems is usually reflected in traces, logs, and some monitoring information, which record inter-service interactions and intra-service behaviors, respectively. Existing attack detection methods require a lot of manual intervention to label the data and have a large over

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Enhanced Prototypical Network for Few-Shot Named Entity Recognition,ance in addressing issues in few-shot settings. Traditional prototypical networks face issues such as inaccurate representation of O-class entities and poor distribution of entity prototypes. This paper presents an Enhanced Prototypical Network (EPN) for few-shot Named Entity Recognition, mainly inc

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Regularized DNN Based Adaptive Compensation Algorithm for Gateway Power Meter in Ultra-High Voltageporting power energy scheduling and market transactions. However, as key data acquisition devices, the operation performance of ultra-high voltage substation energy meters exhibits instability under different environmental conditions, and even small metering errors can lead to significant discrepanc

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Contrastive Learning Based on AMR Graph for Logic Reasoning,recent years, more challenging MRC datasets have been introduced, such as ReClor and LogiQA datasets. These datasets place a greater emphasis on evaluating the logical reasoning abilities of models. To enhance the model‘s logical reasoning capabilities, we propose the AMR-CL method, a contrastive le

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