This field intervention trial evaluated the effect of a 5-week mindfulness-based curriculum on teacher-ratings of student classroom behavior at a Richmond, CA public elementary school, and examined if the addition of more sessions provided added benefit to student outcomes. Seventeen teachers reported on the classroom behaviors of 409 children (83 % enrolled in a California free lunch program and 95.7 % ethnic minority) in kindergarten through sixth grade at pre-intervention, immediate post-intervention, and 7 weeks post-intervention. Results showed that teachers reported improved classroom behavior of their students (i.e., paying attention, self-control, participation in activities, and caring/respect for others) that lasted up to 7 weeks post-intervention. Overall, improvements were not bolstered by the addition of extra sessions, with the exception of paying attention. The implications of this study are limited due to the lack of a mindfulness program-naïve control group, yet findings suggest that mindfulness training might benefit teacher-based perceptions of improved classroom behavior in a public elementary school, which has practice implications for improving the classroom learning environment for lower-income and ethnically-diverse children.
Traffic congestion is a significant problem in recent years because of the everincreasing number of vehicles in the roads and the poor management of traffic. Traffic congestions are not constant throughout the day. They are changing from time to time. Present traffic controllers have fixed time intervals for red, yellow and green signal lights and therefore, cannot provide a better solution for the dynamic traffic congestion during the day. Computer vision technology can be used to create an intelligent traffic controlling system which can adapt its time intervals according to the real traffic. In the existing traffic controlling systems, a wastage of the green signal duration occurs as fixed green signal duration assigned for a phase is sometimes larger than the actual requirement. Hence, the other roads at the intersection have to wait, in vain, with more traffic, until that fixed green time period is over. In the proposed method, real time traffic image sequences are analyzed by using image processing in order to obtain the actual traffic area. Then, time for green light is assigned according to that traffic area. Hence, the wastage of green signal duration is eliminated by the proposed method since it allocates time for the green signal that is sufficient for the actual traffic
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