基于互信息和类电磁机制优化算法的医学图像配准研究*

采用互信息来描述图像配准的效果,应用类电磁机制优化算法搜索配准所对应的空间变换参数,并借鉴POWELL优化算法,在局部搜索过程中采用了黄金分割点一维搜索方法进行搜索,实验结果表明提出的算法可以很好的脱离局部最优解,同时可以达到较好的配准精度,并具有较好的时效性。     

Enhancing intelligent agent collaboration for flow optimization of railroad traffic

Intelligent agents have successfully solved the train pathing problem on a small portion of railroad network [Tsen, 1995, Ph.D. Thesis, Carnegie Mellon University, USA]. As the railroad network grows, it is imperative that the agents collaborate to operate as efficiently as possible. In this paper, the authors demonstrate a collaboration protocol based on a conditional measure of agent effectiveness. Because agent effectiveness is not directly measurable, a suitable metric for agent effectiveness is introduced. Where typically agents run with uniform frequency, the collaboration protocol schedules the agents with a frequency proportional to their expected effectiveness. This protocol introduced a 10-fold improvement in the agent efficiency when tested with a simulation program on a portion of the Burlington Northern railroad.     

Effect of drowsiness on driving performance variables of commercial vehicle drivers

Driver drowsiness is a major safety concern, especially among commercial vehicle drivers, and is responsible for thousands of accidents and numerous fatalities every year. The design of a drowsiness detection system is based on identifying suitable driver-related and/or vehicle-related variables that are correlated to the driver’s level of drowsiness. Among different candidates, vehicle control variables seem to be more promising since they are unobtrusive, easy to implement, and cost effective. This paper focuses on in-depth analysis of different driver-vehicle control variables, e.g., steering angle, lane keeping, etc. that are correlated with the level of drowsiness. The goal is to find relationships and to characterize the effect of a driver’s drowsiness on measurable vehicle or driving variables and set up a framework for developing a drowsiness detection system. Several commercial drivers were tested in a simulated environment and different variables were recorded. This study shows that drowsiness has a major impact on lane keeping and steering control behavior. The correlation of the number and type of accidents with the level of drowsiness was also examined. Significant patterns in lateral position variations and steering corrections were observed, and two phases of drowsiness-related degradation in steering control were identified. The two steering degradation phases examined are suitable features for use in drowsiness detection systems.