Imbalanced datasets pose significant challenges for training classifier models. In this paper, we investigate the efficacy of ensemble strategies to enhance classification performance for both majority and minority pl...
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In this paper we deal with the projective equivalence problem for parameterized curves in an n-dimensional space. A simple linear method for deriving projective differential invariants of curves in an n-dimensional sp...
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Peanut ranks among the foremost cash crops in China. Accurate and timely understanding of peanut planting is very important for governments at all levels to manage production and formulate related policies. In this st...
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Transfer-based attacks against black-box neural network models have received increasing attention because they are more realistic scenarios, but how to produce highly transferable adversarial examples on the surrogate...
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In recent years,with the great success of pre-trained language models,the pre-trained BERT model has been gradually applied to the field of source code ***,the time cost of training a language model from zero is very ...
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In recent years,with the great success of pre-trained language models,the pre-trained BERT model has been gradually applied to the field of source code ***,the time cost of training a language model from zero is very high,and how to transfer the pre-trained language model to the field of smart contract vulnerability detection is a hot research direction at *** this paper,we propose a hybrid model to detect common vulnerabilities in smart contracts based on a lightweight pre-trained languagemodel BERT and connected to a bidirectional gate recurrent *** downstream neural network adopts the bidirectional gate recurrent unit neural network model with a hierarchical attention mechanism to mine more semantic features contained in the source code of smart contracts by using their *** experiments show that our proposed hybrid neural network model SolBERT-BiGRU-Attention is fitted by a large number of data samples with smart contract vulnerabilities,and it is found that compared with the existing methods,the accuracy of our model can reach 93.85%,and the Micro-F1 Score is 94.02%.
The effects of post-annealing on amorphous InGaZnO (a-IGZO) TFTs with ultrathin atomic layer deposited (ALD) AlOx gate insulator (GI) were investigated. The non-annealed devices exhibited uncontrollable gate leakage c...
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Harmony Search Algorithm (HS) is a new meta-heuristic algorithm based on music creation process. The algorithm has been widely used in many fields because of its simple and flexible structure and fewer controlled para...
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Crime against women is a pressing issue that requires comprehensive analysis and effective solutions. This research paper employs geospatial analysis to investigate the spatial patterns and dynamics of crime against w...
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This research aims to predict energy consumed per person by applying various Machine Learning Algorithms. Many vital factors like Energy intensity, access to electricity, GDP growth, renewable energy, etc. are taken i...
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Research on drug side effects contributes to reducing health risks for patients and decreasing drug development costs. In recent years, machine learning methods have emerged as prominent tools to support analyzing and...
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