We performed the full experiments, using our network implementation of component probabilistic indexing and retrieval model. Documents were enhanced with a list of semi-automatically generated two-word phrases, and queries with automatic Boolean expressions. An item self-learning procedure was used to initiate network edge weights for retrieval. Initial results submitted were above median for a...

We report a new algorithm, called the self-adjusting algorithm, to construct an aperiodic optical superlattice in which multiple nonlinear optical parametric processes can be realized simultaneously with high conversion efficiency. The numerical simulations show that a self-adjusting algorithm has obvious advantages that are due to its own physical process and feedback function. Especially in c...

OBJECTIVE This report compares self-reported diabetes in the National Health Interview Survey (NHIS) with diabetes identified using the Medicare Chronic Condition (CC) Summary file. BACKGROUND NHIS records have been linked with Medicare data from the Centers for Medicare & Medicaid Services. The CC Summary file, one of several linked files derived from Medicare claims data, contains indicator...

Measurements on a high-performance Ethernet are shown to match well a truncated Cauchy probability distribution, with a much better fit over smaller file/request sizes than the commonly used Pareto distribution. We observe self similar characteristics in the traffic at both file servers and at a CPU server elsewhere in the network, which targets, predominantly, file and web servers. This sugges...

File systems typically hold newly written data in a cache for a short period of time before writing to disk. Because many files are short-lived, by caching file blocks for longer than their lifetime disk operations are avoided. We evaluate the performance of using an on-line learning algorithm to predict the best timeout to use before committing a data-block to disk. We create a loss function b...