ABSTRACT
Trajectory tracking on a low-speed vehicle using the model predictive control (MPC) algorithm usually assumes a simple road terrain. This assumption does not correspond to the actual road situation, leading to low tracking accuracy. Therefore, a trajectory tracking method considering road curvature based on MPC is proposed in this paper. In this method, the controller can automatically switch between MPC types. Linear model predictive control (LMPC) is selected for small road curvatures, while nonlinear model predictive control (NMPC) is employed for large road curvatures. In addition, the NMPC algorithm in this work considers the effect of road curvature on tracking accuracy, making it suitable for tracking time-varying curvature roads. To verify the feasibility of the algorithm, simulation comparisons with the basic MPC model were carried out at different testing roads and vehicle longitudinal speeds. The results indicate that the method significantly improves trajectory tracking accuracy, all while ensuring real-time calculations. The intelligent switching capability of control models based on road curvature allows its application to track trajectories on arbitrarily complex roads.
ABSTRACT
Background: Previous studies have shown that the traditional Chinese medicine (TCM) called "compound healthy ear agent" (CHEA) had anti-apoptosis effects in cochlear hair cells and spiral ganglion neurons, and could protect mice hearing against presbycusis or age-related hearing loss (AHL), as well as aminoglycoside antibiotic-induced ototoxicity. Because its mechanisms of action are still unclear, we investigated the mechanism of action of CHEA against AHL in mice using proteomics techniques. Methods: Eighteen C57BL/6J mice at 1 month of age were randomly divided into three groups: (A) drinking water until 2 months of age, K2M); (B) drinking water until 7 months of age to induce AHL, K7M; (C) drinking water containing CHEA daily until 7 months of age as treatment group, Z7M. At 2 or 7 months mice were sacrificed and their cochleae were removed for proteomics analysis. Results: The numbers of proteins with a false discovery rate (FDR) < 1% were respectively 5873 for qualitative and 5492 for quantitative statistics. The numbers of proteins with differential enrichment at least 1.5-fold (p < 0.05) were respectively 351 for K7M vs K2M groups, 52 for Z7M vs K7M groups, 264 for Z7M vs K2M groups. The differentially expressed proteins in the Z7M group were involved in synaptic molecular transmission, energy metabolism, immune response, antioxidant defenses, and anti-apoptosis. Conclusion: The TCM CHEA played a protective role against AHL in mice by regulating the expression of specific proteins and genes in cochlear hair cells and spiral ganglion neurons. Besides the pathways expected to be involved (antioxidant and anti-apoptosis), proteins related to immune response is a new finding of the present study.
ABSTRACT
Age-related hearing loss (AHL) or presbycusis is steadily increasing due to the overall aging of the Chinese population. Traditional Chinese medicine (TCM) has long been used to prevent and treat deafness, but its effectiveness and mechanism of action are still uncertain. The present study tested a TCM preparation called "Jian Er" in a mouse model of prebycusis.
ABSTRACT
Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.
