Intersections are one of the major locations where safety is a big concern to drivers. Inappropriate driver behaviors in response to frequent changes when approaching intersections often lead to intersection-related crashes or collisions. Thus to better understand driver behaviors at intersections, especially in the dilemma zone, a Hidden Markov Model (HMM) is utilized in this study. With the discrete data processing, the observed dynamic data of vehicles are used for the inference of the Hidden Markov Model. The Baum-Welch (B-W) estimation algorithm is applied to calculate the vehicle state transition probability matrix and the observation probability matrix. When combined with the Forward algorithm, the most likely state of the driver can be obtained. Thus the model can be used to measure the stability and risk of driver behavior. It is found that drivers’ behaviors in the dilemma zone are of lower stability and higher risk compared with those in other regions around intersections. In addition to the B-W estimation algorithm, the Viterbi Algorithm is utilized to predict the potential dangers of vehicles. The results can be applied to driving assistance systems to warn drivers to avoid possible accidents.

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In this paper, we propose a novel multiresolution adaptive mesh refinement algorithm for solving initial-boundary value problems (IBVP) for evolution PDEs. The proposed algorithm dynamically adapts the grid to any existing or emerging irregularities in the solution, by refining the grid only at those places where the solution exhibits sharp features. The main advantage of the proposed grid adaptation method is that it results in a grid with a fewer number of nodes when compared to adaptive grids generated by existing multiresolution-based mesh refinement techniques. Several examples show the robustness and stability of the proposed algorithm. Introduction.It is well known that the solution of evolution PDEs is often not smooth even if the initial data are smooth. For instance, shocks may develop in hyperbolic conservation laws. To capture discontinuities in the solution with high accuracy, one needs to use a fine resolution grid. The use of a uniformly fine grid requires a large amount of computational resources in terms of both CPU time and memory. Hence, in order to solve evolution equations in a computationally efficient manner, the grid should adapt dynamically to reflect local changes in the solution.Several adaptive gridding techniques for solving PDEs have been proposed in the literature. A nice survey of the early works on the subject can be found in [5,47]. Currently, popular adaptive methods for solving PDEs are (i) moving mesh methods [2,1,4,7,6,13,14,17,29,32,35,36,45], in which an equation is derived that moves a grid of a fixed number of finite difference cells or finite elements so as to follow and resolve any local irregularities in the solution; (ii) the so-called adaptive mesh refinement method [8,9,10,11], in which the mesh is refined locally based on the difference between the solutions computed on the coarser and the finer grids, and (iii) wavelet-based or multiresolution-based methods [3,12,15,18,19,20,23,24,26,37,38,48,49,50], which take advantage of the fact that functions with localized regions of sharp transition can be compressed efficiently. Our proposed method falls under this latter category.Mallat [34] formulated the basic idea of multiresolution analysis for orthonormal wavelets in L 2 (R). Harten [19,20,21] later proposed a general framework for multiresolution representation of data by integrating ideas from three different fields, namely, theory of wavelets, numerical solution of PDEs, and subdivision schemes. Recently, Alves et al. [3] proposed an adaptive multiresolution scheme, similar to the multiresolution approach proposed by Harten [19,20] and Holmstrom [23] for solving hyperbolic

The wind turbine drive system is one of the key components in converting wind energy into electrical energy. The life prediction of drive system is very important for the maintenance of wind turbine. With increasing capacity, the wind turbine system has become more complicated. Consequently, for the life prediction of drive system, it is necessary to consider the problems of multi-information fusion of big data, quantification of time-varying dynamic loads, and analysis of multiple-damage coupling. In order to solve the above challenges, the fatigue life analysis and evaluation method considering the interaction of coupled multiple damages are proposed in this study. The hierarchical Bayesian theory with fault physics technology is introduced to deal with the uncertainty of wind turbine drive system. Then, a time-varying performance analysis model is established based on the multiple-damage coupling competition failure mechanism. Moreover, the Internet of Things (IoT) technology is introduced and combined with the proposed model. Through the data collection by IoT, the time-stress curve of drive system can be obtained. A case study about the remaining fatigue life estimation of drive system is utilized to illustrate the effectiveness of the proposed method.

The purposes are to digitalize and intellectualize current professional sports training and enrich the application scenarios of motion capture technology of moving targets based on artificial intelligence (AI) and human–computer interaction (HCI) in sports training. From an educational psychology perspective, sport techniques are a cognitive ability of sports, and a tacit knowledge. However, sports technology, language, image, and other methods play an auxiliary role in sports training. Here, a General Framework of Knowledge-Based Coaching System (KBCS) is proposed using the HCI technology and sports knowledge to accomplish autonomous and intelligent sports training. Then, the KBCS is applied to table tennis training. The athletic performance is evaluated quantitatively through the calculation of the sports features, motion recognition, and the hitting stage division in table tennis. Results demonstrate that the speed calculated by the position after mosaicking has better continuity after the initial frame of the unmarked segment is compared with the end frame of the market segment. The typical serve and return trajectories in three serving modes of slight-spin, top-spin, and back-spin, as well as the trajectories of common services and return errors, are obtained through the judgment of the serving and receiving of table tennis. Comparison results prove that the serving accuracy of slight-spin and back-spin is better than that of top-spin, and a lower serve speed has higher accuracy. Experimental results show that the level distribution of the three participants calculated by the system is consistent with the actual situation in terms of the quality of the ball returned and the standard of the motion, proving that the proposed KBCS and algorithm are useful in a small sample, thereby further improving the accuracy of pose restoration of athletes in sports training.

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Numerical simulation of low speed high Angle of attack rotating missile was carried out by using different turbulence models, and the numerical simulation results were compared with the experimental results. The results show that the SST-DDES model can well simulate the aerodynamic characteristics of the rotating missile at low speed and high Angle of attack. Under the condition of low speed and high Angle of attack, the difference of the lateral force produced by the missile’s tail fin is small, and the variation of the total missile lateral force mainly depends on the variation of the projectile body lateral force. When the Angle of attack increases from 40.1° to 60.1°, the direction of the missile’s lateral force changes. This is because with the increase of the Angle of attack, the fluid velocity perpendicular to the projectile increases, resulting in the interaction and fusion of asymmetric vortexes on the leeward side, resulting in the change of lateral force direction.

The Magnus moment characteristics of rotating missiles with Mach numbers of 1.3 and 1.5 at different altitudes and angles of attack were numerically simulated based on the transition SST model. It was found that the Magnus moment direction of the missiles changed with the increase of the angle of attack. At a low altitude, with the increase of the angle of attack, the Magnus moment direction changed from positive to negative; however, at high altitudes, with the increase of the angle of attack, the Magnus moment direction changed from positive to negative and then again to positive. The Magnus force direction did not change with the change of the altitude and the angle of attack at low angles of attack; however, it changed with altitude at an angle of attack of 30°. When the angle of attack was 20°, the interference of the tail fin to the lateral force of the missile body was different from that for other angles of attack, leading to an increase of the lateral force of the rear part of the missile body. With the increasing altitude, the position of the boundary layer with a larger thickness of the missile body moved forward, making the lateral force distribution of the missile body even. Consequently, Magnus moments generated by different boundary layer thicknesses at the front and rear of the missile body decreased and the Magnus moment generated by the tail fin became larger. As lateral force directions of the missile body and the tail were opposite, the Magnus moment direction changed noticeably. Under a high angle of attack, the Magnus moment direction of the missile body changed with the increasing altitude. The absolute value of the pitch moment coefficient of the missile body decreased with the increasing altitude.