Human navigation has been a topic of interest in spatial cognition from the past few decades. It has been experimentally observed that humans accomplish the task of way-finding a destination in an unknown environment by recognizing landmarks. Investigations using network analytic techniques reveal that humans, when asked to way-find their destination, learn the top ranked nodes of a network. In this paper we report a study simulating the strategy used by humans to recognize the centers of a network. We show that the paths obtained from our simulation has the same properties as the paths obtained in human based experiment. The simulation thus performed leads to a novel way of pathfinding in a network. We discuss the performance of our method and compare it with the existing techniques to find a path between a pair of nodes in a network.

Three low correlation interleaved QAM sequence families are presented here. In a CDMA setting, these sequences have the ability to transport a larger amount of data as well as enable variable-rate signaling on the reverse link. These constructions have the lowest known value of maximum correlation magnitude of any sequence family with the same alphabet.

Deficiencies in the formulation of the model for optimal design of the distributed network are pointed out. These concern the existence of communication links and routing variables for updates. Several feasible solutions, with a lower cost than the one given in the above paper for the example discussed, are presented. These establish the inadequacy of the procedure adopted to arrive at the optimal design.

A modified version of the multiple attribute tree (MAT) database organization, which uses a compact directory, is discussed. An efficient algorithm to process the directory for carrying out the node searches is presented. Statistical procedures are developed to estimate the number of nodes searched and the number of data blocks retrieved for most general and complex queries. The performance of inverted file and modified MAT organizations are compared using six real-life databases and four types of query complexities. Careful tradeoffs are established in terms of storage and access times for directory and data, query complexities, and database characteristics.