A hybrid dual-branch model with recurrence plots and transposed transformer for stock trend prediction.

Stock trend prediction is a significant challenge due to the inherent uncertainty and complexity of stock market time series. In this study, we introduce an innovative dual-branch network model designed to effectively address this challenge. The first branch constructs recurrence plots (RPs) to capture the nonlinear relationships between time points from historical closing price sequences and computes the corresponding recurrence quantifification analysis measures.

Prevalence of mental health problems and associated risk factors among military healthcare workers in specialized COVID-19 hospitals in Wuhan, China: A cross-sectional survey.

Introduction: China has been severely affected by coronavirus disease 2019 (COVID-19) since December 2019. Military healthcare workers in China have experienced many pressures when combating COVID-19. This study aimed to investigate the current psychological status and associated risk factors among military healthcare workers.

A Modified Extended Kalman Filter for a Two-Antenna GPS/INS Vehicular Navigation System.

Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and measurement noise are critical factors to avoid numerical problems and obtain stable and accurate estimates. In this paper, a modified extended Kalman filter (EKF) is proposed by properly adapting the statistics of state process and observation noises through the innovation-based adaptive estimation (IAE) method.