Oscillation and Nonoscillation Criteria for Nonlinear Dynamic Systems on Time Scales

We consider the nonlinear dynamic system Δ()=()(()),Δ()=−(,()). We establish some necessary and sufficient conditions for the existence of oscillatory and nonoscillatory solutions with special asymptotic properties for the system. We generalize the known results in the literature. Some examples are included to illustrate the results

EXISTENCE FOR NONOSCILLATORY SOLUTIONS OF FORCED HIGHER-ORDER NONLINEAR NEUTRAL DYNAMIC EQUATIONS

Abstract. In this paper, we first study the existence of nonoscillatory solutions of dy- on a time scale T. By using Krasnosel'skii's fixed point theorem and some new techniques, we obtain sufficient conditions for the existence of nonoscillatory solutions for general p i (t), f i (x) and q(t) which means that they are allowed oscillate. Then, we extend our results to equations of the form [x(t) + p(t)x(τ (t))] ∆ m + F (t, x(δ(t))) = q(t). We establish sufficient and necessary conditions for the existence of nonoscillatory solutions of this equation. Our results not only generalize and improve the known results stated for differential and difference equations using the time scale theory, but also improve some of the results for dynamic equations on time scales. Some examples are included to illustrate the results

The Effects of Weather on Passenger Flow of Urban Rail Transit

Predicting passenger flow on urban rail transit is important for the planning, design and decision-making of rail transit. Weather is an important factor that affects the passenger flow of rail transit by changing the travel mode choice of urban residents. This study aims to explore the influence of weather on urban rail transit ridership, taking four cities in China as examples, Beijing, Shanghai, Guangzhou and Chengdu. To determine the weather effect on daily ridership rate, the three models were proposed with different combinations of the factors of temperature and weather type, using linear regression method.   The large quantities of data were applied to validate the developed models.  The results show that in Guangzhou, the daily ridership rate of rail transit increases with increasing temperature. In Chengdu, the ridership rate increases in rainy days compared to sunny days. While, in Beijing and Shanghai, the ridership rate increases in light rainfall and heavy rainfall (except moderate rainfall) compared to sunny days. The research findings are important to understand the impact of weather on passenger flow of urban rail transit. The findings can provide effective strategies to rail transit operators to deal with the fluctuation in daily passenger flow

Efficient-VRNet: An Exquisite Fusion Network for Riverway Panoptic Perception based on Asymmetric Fair Fusion of Vision and 4D mmWave Radar

Panoptic perception is essential to unmanned surface vehicles (USVs) for autonomous navigation. The current panoptic perception scheme is mainly based on vision only, that is, object detection and semantic segmentation are performed simultaneously based on camera sensors. Nevertheless, the fusion of camera and radar sensors is regarded as a promising method which could substitute pure vision methods, but almost all works focus on object detection only. Therefore, how to maximize and subtly fuse the features of vision and radar to improve both detection and segmentation is a challenge. In this paper, we focus on riverway panoptic perception based on USVs, which is a considerably unexplored field compared with road panoptic perception. We propose Efficient-VRNet, a model based on Contextual Clustering (CoC) and the asymmetric fusion of vision and 4D mmWave radar, which treats both vision and radar modalities fairly. Efficient-VRNet can simultaneously perform detection and segmentation of riverway objects and drivable area segmentation. Furthermore, we adopt an uncertainty-based panoptic perception training strategy to train Efficient-VRNet. In the experiments, our Efficient-VRNet achieves better performances on our collected dataset than other uni-modal models, especially in adverse weather and environment with poor lighting conditions. Our code and models are available at \url{https://github.com/GuanRunwei/Efficient-VRNet}