老舍英文话剧The Spear that Demolishes Five Tigers at Once是对其短篇小说《断魂枪》的改写。在剧本里,老舍不再像英译《离婚》时那样以批判中国文化为旨归,而是通过改写颂扬中国文化,并把文化传统中的"刚性文化"特质与西...老舍英文话剧The Spear that Demolishes Five Tigers at Once是对其短篇小说《断魂枪》的改写。在剧本里,老舍不再像英译《离婚》时那样以批判中国文化为旨归,而是通过改写颂扬中国文化,并把文化传统中的"刚性文化"特质与西方新型的科学技术结合,从而建构他自1930年代就开始思考并不断丰富的中国精神文化现代化的"内涵"。展开更多
Spear Phishing Attacks(SPAs)pose a significant threat to the healthcare sector,resulting in data breaches,financial losses,and compromised patient confidentiality.Traditional defenses,such as firewalls and antivirus s...Spear Phishing Attacks(SPAs)pose a significant threat to the healthcare sector,resulting in data breaches,financial losses,and compromised patient confidentiality.Traditional defenses,such as firewalls and antivirus software,often fail to counter these sophisticated attacks,which target human vulnerabilities.To strengthen defenses,healthcare organizations are increasingly adopting Machine Learning(ML)techniques.ML-based SPA defenses use advanced algorithms to analyze various features,including email content,sender behavior,and attachments,to detect potential threats.This capability enables proactive security measures that address risks in real-time.The interpretability of ML models fosters trust and allows security teams to continuously refine these algorithms as new attack methods emerge.Implementing ML techniques requires integrating diverse data sources,such as electronic health records,email logs,and incident reports,which enhance the algorithms’learning environment.Feedback from end-users further improves model performance.Among tested models,the hierarchical models,Convolutional Neural Network(CNN)achieved the highest accuracy at 99.99%,followed closely by the sequential Bidirectional Long Short-Term Memory(BiLSTM)model at 99.94%.In contrast,the traditional Multi-Layer Perceptron(MLP)model showed an accuracy of 98.46%.This difference underscores the superior performance of advanced sequential and hierarchical models in detecting SPAs compared to traditional approaches.展开更多
文摘老舍英文话剧The Spear that Demolishes Five Tigers at Once是对其短篇小说《断魂枪》的改写。在剧本里,老舍不再像英译《离婚》时那样以批判中国文化为旨归,而是通过改写颂扬中国文化,并把文化传统中的"刚性文化"特质与西方新型的科学技术结合,从而建构他自1930年代就开始思考并不断丰富的中国精神文化现代化的"内涵"。
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under Grant Number(DGSSR-2023-02-02513).
文摘Spear Phishing Attacks(SPAs)pose a significant threat to the healthcare sector,resulting in data breaches,financial losses,and compromised patient confidentiality.Traditional defenses,such as firewalls and antivirus software,often fail to counter these sophisticated attacks,which target human vulnerabilities.To strengthen defenses,healthcare organizations are increasingly adopting Machine Learning(ML)techniques.ML-based SPA defenses use advanced algorithms to analyze various features,including email content,sender behavior,and attachments,to detect potential threats.This capability enables proactive security measures that address risks in real-time.The interpretability of ML models fosters trust and allows security teams to continuously refine these algorithms as new attack methods emerge.Implementing ML techniques requires integrating diverse data sources,such as electronic health records,email logs,and incident reports,which enhance the algorithms’learning environment.Feedback from end-users further improves model performance.Among tested models,the hierarchical models,Convolutional Neural Network(CNN)achieved the highest accuracy at 99.99%,followed closely by the sequential Bidirectional Long Short-Term Memory(BiLSTM)model at 99.94%.In contrast,the traditional Multi-Layer Perceptron(MLP)model showed an accuracy of 98.46%.This difference underscores the superior performance of advanced sequential and hierarchical models in detecting SPAs compared to traditional approaches.
