Abstract-In CAD/CAM modeling, objects are represented using the Boundary Representation (ANSI Brep) model. Detection of possible intersection between objects can be based on the objects' boundaries (i.e., triangulated surfaces), and computed using triangle-triangle intersection. Usually only a cross intersection algorithm is needed; however, it is beneficial to have a single robust and fast intersection detection algorithm for both cross and coplanar intersections. For qualitative spatial reasoning, a general-purpose algorithm is desirable for accurately differentiating the relations in a region connection calculus, a task that requires consideration of intersection between objects. Herein we present a complete uniform integrated algorithm for both cross and coplanar intersection. Additionally, we present parametric methods for classifying and computing intersection points. This work is applicable to most region connection calculi, particularly VRCC-3D+, which detects intersections between 3D objects as well as their projections in 2D that are essential for occlusion detection.

The ubiquitous adoption of portable smart devices has enabled a new way of communication via Pocket Switched Networks (PSN), whereby messages are routed by personal devices inside the pockets of ever-moving people. PSNs provide opportunities for various interesting applications such as locationbased social networking, geolocal advertising, and military missions in active battlefields where the central communication tower is unavailable. One key challenge of the successful roll-out of PSN applications is the difficulty of achieving high message delivery ratio due to the dynamic nature of moving people and spatialtemporal sparsity in such networks. In this paper, we propose a novel message routing approach, called ChitChat, which exploits users' direct and transient social interests via discriminatory gossiping to penetrate messages deeper into the network. Our approach enables message carriers to make opportunistic and distributed routing decisions based on the likelihood a potential message receiver will meet individuals that have a high chance to forward the message to the destination. Our experimental results have demonstrated that our approach achieves higher delivery ratios against the two more recent state-of-the-art algorithms, while maintaining a lower communication overhead against flooding and reducing the amount of time messages remain idle in buffers.

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