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A fluorometric system utilizing the single photon counting technique which records the decay of the intensity and the anisotropy of fluorescence following pulse excitation is described. Both macroscopic observations on cellular suspensions and measurements on individual cells under an optical microscope are possible. The system is so designed to permit precise evaluation of complex anisotropy decays, which is essential for studies of cells or tissues. Data are processed by a method which properly analyzes these complex decays. A preliminary study on erythrocyte membrane has confirmed the high resolution and precision of the system.

Aggregate Nearest Neighbor (ANN) queries developing from Nearest Neighbor (NN) queries are the relatively new query type in spatial database and data mining. An ANN queries return the object that minimizes an aggregate distance function with respect to a set of query points. Because of the multiple query points, ANN queries are much more complex than NN queries. For optimizing the query processing and improving the query efficiency, many ANN queries algorithms utilizes pruning strategies. In this paper, we propose two points projecting based ANN queries algorithms which can efficiently prune the data points without indexing. We project the query points into special "line", on which we analyses their distributing, then pruning the search space. Unlike many other algorithms based on the data index mechanisms, our algorithms avoid the curse of dimensionality and are effective and efficient in both high dimensional space and metric space. We conduct experimental studies using both real dataset and synthetic datasets to compare and evaluate their efficiencies.

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