Mengying Shu

You are already at the latest version Employee retention represents a critical challenge for organizations, with high turnover rates impacting operational continuity and financial stability. This research introduces an optimized feature selection framework for predicting employee attrition using machine learning techniques. The study employs a hybrid approach integrating filter, wrapper, and embedded methods to identify the most influential predictors while reducing dimensionality by 60%.

Zhongwen Zhou , Siwei Xia, Mengying Shu, Hong Zhou Abstract Medical report generation demands accurate abnormality detection and precise description generation from CT images. While large language models have shown promising results in natural language processing tasks, their application in medical imaging analysis faces challenges due to the complexity of fine-grained feature detection and the requirement for domain-specific knowledge.

The flow in intake manifold of a heavily downsized internal combustion engine has increased levels of unsteadiness due to the reduction of cylinder number and manifold arrangement. The turbocharger compressor is thus exposed to significant pulsating backpressure. This paper studies the response of a centrifugal compressor to this unsteadiness using an experimentally validated numerical method.