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An exact dynamic stiffness method is proposed for the free vibration analysis of multi-body systems consisting of flexible beams and rigid bodies. The theory is sufficiently general in that the rigid bodies can be of any shape or size, but importantly, the theory permits connections of the rigid bodies to any number beams at any arbitrary points and oriented at any arbitrary angles. For beam members, a range of theories including the Bernoulli-Euler and Timoshenko theories are applied. The assembly procedure for the beam and rigid body properties is simplified without resorting to matrix inversion. The difficulty generally encountered in computing the problematic J0 count when applying the Wittrick-Williams algorithm for modal analysis has been overcome. Applications of different beam theories for both axial and bending vibrations have enabled the examination of the role played by rigid-body parameters on the multibody system's dynamic behaviour. Some exact benchmark results are provided and compared with published results and with finite element solutions. This research provides an exact and highly efficient analysis tool for multibody system dynamics which is for the free vibration analysis, ideally suited for optimization and inverse problems such as modal parameter identification.

The fully autonomous operation of multirotor unmanned air vehicles (UAVs) in many applications requires support of precision landing. Onboard camera and fiducial marker have been widely used for this critical phase due to its low cost and high effectiveness. This paper proposes a six-degrees-of-freedom (DoF) pose estimation solution for UAV landing based on an artificial marker and a micro-electromechanical system (MEMS) inertial measurement unit (IMU). The position and orientation of the landing maker are measured in advance. The absolute position and heading of the UAV are estimated by detecting the marker and extracting corner points with the onboard monocular camera. To achieve continuous and reliable positioning when the marker is occasionally shadowed, IMU data is fused by an extended Kalman filter (EKF). The error terms of the IMU sensor are modeled and estimated. Field experiments show that the positioning accuracy of the proposed system is at centimeter level, and the heading error is less than 0.1 degrees. Comparing to the marker-based approach, the roll and pitch angle errors decreased by 33% and 54% on average. Within five seconds of vision outage, the average drifts of the horizontal and vertical position were 0.41 and 0.09 m, respectively.

In this Letter, we propose a phase drift cancellation method for remote radio frequency transfer. Phase fluctuation along the transmission fiber, which is induced by temperature and pressure changes, is measured and compensated by a heterodyne optoelectronic delay-locked loop. The control loop consists of a heterodyne optoelectronic phase detector, a microwave delay module, and the loop filter. We demonstrate the concept by transmitting a 10 GHz microwave frequency over 50 km single-mode fiber, with subpicosecond jitters measured at the remote end.

This article reports a study of the effects of inference training and text repetition on Chinese university students’ performance of two listening information-transfer tasks that provided built-in measures of their comprehension and opportunities for the acquisition of ten unknown target words embedded in the listening texts. One group just listened to the text once, a second group three times, while the third listened three times and received inference-training support. The results showed that text repetition had a positive effect on both comprehension and vocabulary acquisition. However, the inference-training had no additional effect. The study lends support to the findings of previous studies which have shown that repeated opportunities to process oral input have a positive effect on listening comprehension and extends these studies by showing that it also facilitates incidental vocabulary acquisition.