Breast ultrasound segmentation is challenged by strong noise, low contrast, and ambiguous lesion boundaries. Although deep models achieve high accuracy, their heavy computational cost limits deployment on portable ultrasound devices. In contrast, lightweight networks often struggle to preserve fine boundary details. To address this gap, we propose the lightweight boundary-aware network. A MobileNetV3-based encoder with the atrous spatial hyramid pooling is integrated for efficient multi-scale representation learning. The applied the lightweight boundary-aware block uses an adaptive fusion to combine efficient channel attention and depthwise spatial attention to enhance discriminative capability with minimal computational overhead. A boundary-guided dual-head decoding scheme injects explicit boundary priors and enforces boundary consistency to sharpen and stabilize margin delineation. Experiments on curated BUSI* and BUET* datasets demonstrate that the proposed network achieves 82.8% Dice, 38 px HD95, and real-time inference speeds (123 FPS GPU / 19 FPS CPU) using only 1.76M parameters. They show that this proposed network can offer a highly favorable balance between accuracy and efficiency.

Residual vibration of industrial manipulators can limit positioning efficiency and dynamic accuracy during high-speed motion. This study develops an integrated vibration-suppression framework for a rigid-link manipulator with flexible-joint dynamics. A controller-oriented rigid–flexible model with lumped disturbances is established, and a disturbance observer (DOB) is employed as the inner-loop compensation layer under a small-gain robustness constraint. On the compensated nominal model, partial eigenstructure assignment (PESA) selectively increases the damping of the retained flexible modes while preserving the rigid-body eigenstructure associated with trajectory tracking. A pose-dependent gain-scheduling mechanism further updates the PESA feedback gain to accommodate configuration-dependent modal-frequency variation. Numerical comparisons with conventional PID, standalone DOB, and standalone PESA demonstrate improved residual-vibration attenuation and settling behavior. Hardware tests on an Aubo i5 manipulator, with 16-channel responses directly acquired under the respective control configurations, further show an approximately 80% reduction in the representative low-frequency vibration amplitude relative to the PID baseline under the considered operating condition.