Humans are adept in simultaneously following multiple goals, but the neural mechanisms for maintaining specific goals and distinguishing them from other goals are incompletely understood. For short time scales, working memory studies suggest that multiple mental contents are maintained by theta-coupled reactivation, but evidence for similar mechanisms during complex behaviors such as goal-directed navigation is scarce. We examined intracranial electroencephalography recordings of epilepsy patients performing an object-location memory task in a virtual environment. We report that large-scale electrophysiological representations of objects that cue for specific goal locations are dynamically reactivated during goal-directed navigation. Reactivation of different cue representations occurred at stimulus-specific hippocampal theta phases. Locking to more distinct theta phases predicted better memory performance, identifying hippocampal theta phase coding as a mechanism for separating competing goals. Our findings suggest shared neural mechanisms between working memory and goal-directed navigation and provide new insights into the functions of the hippocampal theta rhythm.

In this paper, a methodology which allows automated and efficient reconstruction of three-dimensional (3-D) geometric building models from an Airborne Laser Scanning (ALS) point cloud is introduced and its performance is analyzed and evaluated. The proposed method avoids abnormal and/or infinite solutions which are typically encountered in previously published methods that use the rooftop primitive adjacency matrix to solve the critical rooftop vertices. In particular, first, an improved random sample consensus (RANSAC) algorithm is proposed to segment the rooftop primitives, i.e., the planar patches that constitute rooftops, of each building or group of connected buildings. The algorithm successfully maintains topological consistency among primitives and avoids under-and over-segmentation with high efficiency. Second, a novel Voronoi-based primitive boundary extraction algorithm under constraints of outer and inner building boundaries is introduced in order to extract each primitive boundary. In this algorithm, the adjacent segmented primitive relationships among the various primitives are preserved by a subgraph of the Voronoi diagram so that the reconstructed neighbor primitives are seamlessly connected. Third, in order to refine the boundary shapes of primitives with irregular geometry, various criteria for making the boundary adjustments more effective are proposed. In this way, more regular 3-D buildings can be produced. Finally, the primitive boundary simplification criteria are formally introduced to generate compact 3-D building models. By using the simplification criteria, nonadjacency between neighbor primitives, intersection between boundaries, and self-intersections are, to a great extent, avoided. Numerous experimental results obtained using multiple data sets, including data from the cities of Toronto and Enschede as well as from the Niagara area, have shown that the proposed methodology has excellent performance and it can produce watertight 3-D polyhedral building models.Index Terms-Airborne laser scanning (ALS), building boundary extraction, rooftop segmentation, three dimensional (3-D) building reconstruction, topological consistency, Voronoi-based diagrams.

Abstract-Most of the nodes in ad hoc networks rely on batteries, which requires energy saving. Hence, numerous energyefficient routing algorithms have been proposed for solving this problem. In this paper, we exploit the benefits of cross-layer information exchange, such as the knowledge of the Frame Error Rate (FER) in the physical layer, the maximum number of retransmissions in the Medium Access Control (MAC) layer and the number of relays in the network layer. Energy-consumptionbased Objective Functions (OF) are invoked for calculating the end-to-end energy consumption of each potentially available route for both Traditional Routing (TR) and for our novel Opportunistic Routing (OR), respectively. We also improve the TR and the OR with the aid of efficient Power Allocation (PA) for further reducing the energy consumption. For the TR, we take into account the dependencies amongst the links of a multi-hop route, which facilitates a more accurate performance evaluation than upon assuming the links that are independent. Moreover, two energy-efficient routing algorithms are designed based on Dijkstra's algorithm. The algorithms based on the energy OF provide the theoretical bounds, which are shown to be close to the bound found from exhaustive search, despite the significantly reduced complexity of the former. Finally, the endto-end throughput and the end-to-end delay of this system are analyzed theoretically and a new technique of characterizing the delay distribution of OR is proposed. The simulation results show that our energy-efficient OR outperforms the TR and that their theoretical analysis accurately matches the simulation results.