Event argument extraction (EAE), a critical task in information extraction, aims to identify structured event information from textual sentences. However, existing Chinese EAE methods fail to effectively integrate prior semantic knowledge from event types and argument roles, resulting in suboptimal performance. Moreover, mainstream approaches exhibit limited generalization in few-shot argument recognition scenarios. To address these challenges, we propose an enhanced Machine Reading Comprehension (MRC)-based Cross-Domain Chinese Event Argument Extraction framework. Our approach systematically incorporates event-type descriptions and argument-driven question formulations into contextual representations through multi-head attention mechanisms, thereby enhancing hierarchical semantic understanding of events. Furthermore, we introduce a transfer learning strategy with boundary-aware optimization to mitigate poor boundary detection of arguments in low-resource settings. Extensive experiments on two Chinese event extraction benchmarks, ACE2005 and MEC, validate the effectiveness of our method. The proposed model achieves superior performance, improving F1 scores by 1.6% and 1.9% on argument extraction tasks, respectively. Notably, it demonstrates significant gains in few-shot argument extraction scenarios, outperforming existing baselines in cross-domain generalization.

This paper first reviews the existing techniques of surface-plane intersection in computer-aided geometric design (CAGD). The vector fields are introduced for the detection of closed intersection loops. A distance function is defined from a surface patch to an intersecting plane and the gradient of the function defines a plane vector field. The Poincare index theorem is inconclusive in detecting critical points of plane vector field. The modified Poincare theorem is developed by extending the plane vector fields into three dimensions for the conclusive test of critical points. The initial points are obtained based on loop detection and subdivision. The resulting intersections are represented using biarc spline fitting scheme. The algorithm presented in the paper requires only the surface be parametrically defined and C/sup 2/ continuous.

This paper presents a method for cutter path generation by directly intersecting the part surface with a plane to generate cutter contact (CC) points. The surface-plane intersection is traced out using the marching method. The surface patch is subdivided based on a loop detection criterion, and all the initial points can be found along the boundaries of subpatches. The biarc curve fitting is employed to fit the largest sequential data points on the intersection curve. The cutter location (CL) data is obtained for profile machining by offsetting the CC biarc curve in surface normal direction. For a general free form surface, approximation is taken to generate plane biarc curves to represent the CL data points. The method is tested in a rapid prototyping system for production a of foot last.>