University of Macau

About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Computer science & Population. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.

Bullying climate and school engagement in ninth-grade students.

Abstract: BACKGROUND: Many authorities agree that bullying has a widespread impact on school climate, affecting bystanders as well as victims. This study tested the contention that a climate of bullying can have a schoolwide impact on student engagement in school. METHODS: Hierarchical linear modeling assessed the relations between student perception of bullying climate and student engagement at the individual and school level in a statewide sample of 7058 ninth graders randomly selected from 289 schools participating in the Virginia High School Safety Study. Student engagement was assessed by self-report scales measuring commitment to school and involvement in school activities. RESULTS: Individual differences in perception of school climate characterized by bullying were associated with lower commitment to school, but not less involvement in school activities. School-level differences in student perceptions of bullying climate were associated with both lower commitment to school and less involvement in school activities, after controlling for the effects of gender, race, school size, proportion of ethnic minority students in the school, and individual-level perception of bullying climate. CONCLUSION: Efforts to improve student engagement should consider the schoolwide impact of bullying on all students. Language: en

Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation

Abstract: In this paper, we present a sensorless admittance control scheme for robotic manipulators to interact with unknown environments in the presence of actuator saturation. The external environment is defined as linear models with unknown dynamics. Using admittance control, the robotic manipulator is controlled to be compliant with external torque from the environment. The external torque acted on the end-effector is estimated by using a disturbance observer based on generalized momentum. The model uncertainties are solved by using radial basis neural networks (NNs). To guarantee the tracking performance and tackle the effect of actuator saturation, an adaptive NN controller integrating an auxiliary system is designed to handle the actuator saturation. By employing Lyapunov stability theory, the stability of the closed-loop system is achieved. The experiments on the Baxter robot are implemented to verify the effectiveness of the proposed method.

Landing of a Quadrotor on a Moving Target Using Dynamic Image-Based Visual Servo Control

Abstract: This paper addresses the landing problem of a vertical take-off and landing vehicle, exemplified by a quadrotor, on a moving platform using image-based visual servo control. Observable features on a flat and textured target plane are exploited to derive a suitable control law. The target plane may be moving with bounded linear acceleration in any direction. For control purposes, the image of the centroid for a collection of landmarks is used as position measurement, whereas the translational optical flow is used as velocity measurement. The proposed control law guarantees convergence to the desired landing spot on the target plane, without estimating any parameter related to the unknown height, which is also guaranteed to remain strictly positive. Moreover, convergence is guaranteed even in the presence of bounded and possibly time-varying disturbances, resulting, for example, from the motion of the target plane, measurement errors, or wind-induced force disturbances. To improve performance, an estimator for unknown constant force disturbances is also included in the control law. Simulation and experimental results are provided to illustrate and assess the performance of the proposed controller.