This study conducts a thorough examination of malware detection using machine learning
techniques, focusing on the evaluation of various classification models using the Mal-API …

Twitter bot detection has become a crucial task in efforts to combat online misinformation,
mitigate election interference, and curb malicious propaganda. However, advanced Twitter …

Monitoring the health status of patients in the Intensive Care Unit (ICU) is a critical aspect of
providing superior care and treatment. The availability of large-scale electronic health …

Stroke prediction plays a crucial role in preventing and managing this debilitating condition.
In this study, we address the challenge of stroke prediction using a comprehensive dataset …

Transportation agencies need to assess ramp metering performance when deploying or
expanding a ramp metering system. The evaluation of a ramp metering strategy is primarily …

Research on social bot detection plays a crucial role in maintaining the order and reliability
of information dissemination while increasing trust in social interactions. The current …

Textual backdoor attacks pose significant security threats. Current detection approaches,
typically relying on intermediate feature representation or reconstructing potential triggers …

The rapid and accurate identification of bot accounts in online social networks is an ongoing
challenge. In this paper, we propose BotTriNet, a unified embedding framework that …

To develop the most appropriate control strategy and monitor, maintain, and evaluate the
traffic performance of the freeway weaving areas, state and local Departments of …

Monitoring the health status of patients and predicting mortality in advance is vital for
providing patients with timely care and treatment. Massive medical signs in Electronic Health …