This project is aimed to solve the problem of flight delay prediction. This problem does not only affect airlines but it can cause multiple problems in different sectors i.e., commercial (Cargo aviation), passenger av...
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The increasing sophistication of spoofing, mimicry, and deepfake technologies exposes critical vulnerabilities in voice authentication systems, including the inability to generalize across diverse attack types, relian...
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This study investigates the presence of biases in large language models (LLMs), specifically focusing on how these models process and reflect inter-state conflict *** research has often lacked the standardized dataset...
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Constraints on graph data expressed in the Shapes Constraint Language (SHACL) can be quite complex. This brings the challenge of efficient validation of complex SHACL constraints on graph data. This challenge is ...
This research paper primarily investigates the application and performance of traditional machine learning and quantum computing in Natural Language Processing (NLP), with a focus on sentiment analysis tasks. By compa...
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Infectious/Contagious diseases remain a significant global health challenge, necessitating accurate identification to mitigate their spread. The widespread adoption of wearable healthcare devices capable of continuous...
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Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed dat...
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Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed data is undoubtedly higher than that of original data, and adopted association measure method does not well balance effectiveness and efficiency. To address above two issues, this paper proposes a novel association-based representation improvement method, named as AssoRep. AssoRep first obtains the association between features via distance correlation method that has some advantages than Pearson’s correlation coefficient. Then an improved matrix is formed via stacking the association value of any two features. Next, an improved feature representation is obtained by aggregating the original feature with the enhancement matrix. Finally, the improved feature representation is mapped to a low-dimensional space via principal component analysis. The effectiveness of AssoRep is validated on 120 datasets and the fruits further prefect our previous work on the association data reconstruction.
Proposing an avant-garde solution for optimizing student inquiries within the academic institution, an advanced conversational AI agent is introduced. This cutting-edge chatbot seamlessly integrates into the universit...
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With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***...
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With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their *** address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree *** algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical *** our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical *** results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.
Antimicrobial susceptibility testing (AST) stands as a cornerstone in modern healthcare, necessitating precise and prompt detection of resistance patterns to guide antimicrobial stewardship. Traditional clinical micro...
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