sc pipes is a SystemC package for building and simulating models of pipelined systems. To use sc pipes, a designer familiar with SystemC should have very little to learn. To create a pipeline simulation with sc pipes, the user builds an sc module for each stage to be used in the pipeline, with only minor di erences from the way such a module would be built in a SystemC program without sc pipes. The user then builds an scp pipeline object, passing to its constructor an expression describing the pipeline's con guration.

The purpose of this project was to determine the nonwinter and winter home ranges of porcupines in a mixed hardwood forest in northern New York and to monitor den activity to determine daily and seasonal changes in den use. Primarily, I a) measured the home range of three radio collared porcupines to determine seasonal and yearly variability; b) monitored den usage to determine time of day of peak activity, seasonal activity differences, and instances of den sharing; and c) observed sexual differences in home range and den usage.

This study covers five Aptian stratigraphic sections of shallow-marine platform carbonates from southern Croatia, located on the islands of Korčula, Hvar, Mljet, and the Pelješac Penninsula. The observed succession was deposited in the interior of the Bahama-like Adriatic Platform in the Tethys Ocean.

The North American porcupine (Erethizon dorsatum) currently occupies a wide range of terrestrial habitats across the United States and is expanding its range to include much of the North American continent (Ilse and Hellgren, 2001). It is the only porcupine in North America, and its habitat includes hemlock and deciduous forests, which often brings it into close contact with humans who have monopolized such areas for development and agriculture (Roze, 1989).

Classification trees are used with a categorical response variable. The goal of a classification tree is to derive a model that predicts to which category a particular subject or individual belongs, based one or more explanatory factors. For example, we could use a classification tree to predict the diagnosis (Benign or Malignant) of a particular patient based upon information obtained by doctors through scanned images. These classification trees are displayed as a decision tree that has a start node which then branches into other nodes.

The fretted terrain on Mars (found 30°N to 50°N and 0°E to 80°E) is a transitional zone between highly cratered uplands and younger, less cratered lowlands, which exhibits flat-topped, steep-walled mesas and knobs (Sharp, 1973). These mesas and knobs are separated by younger flat-lying lowlands and lineated lobate debris aprons thought to result from ice-facilitated mass-wasting process from either ground or atmospheric sources.

In Summer 2009 I participated in the NSF-funded SURF-IT (Summer Undergraduate Research Fellowship in Information Technology) at the University of California, Santa Cruz. This REU (Research Experience for Undergraduates) involved creating an iPhone/iPod Touch application called Teenvity that is designed to motivate teenagers to exercise by playing games that require movement. The application is molded to the user’s personality; the system selects an agent, motivational phrases, and games to suggest to the user based on a short personality test.

The Central Limit Theorem (CLT) states that the distribution of the sample mean of independent and identically distributed random variables converges to the normal distribution as the sample size increases. A common rule of thumb is to consider sample sizes greater than 30 as "large enough" samples to use the CLT as an approximation. However, the "large enough" depends on how non-normal the individual observations are distributed.

Markov Chain Monte Carlo (MCMC) methods are powerful algorithms that enable statisticians to explore information about probability distributions through computer simulations when exact theoretical methods are not feasible. The Gibbs sampler, for example, allows us to gather information about marginal and joint distributions of multivariate densities assuming that we know information about the conditional distributions. Of particular interest is the use of MCMC methods in Bayesian statistics to help estimate posterior distributions.

Baseball is the great American pastime. In this study we examine different aspects of baseball games to determine what factors play a role in predicting the winning team for a specific game or an entire season. To predict who is likely to win individual games, we consider factors such as each team’s offensive or defensive ability, past game scores, and previous winning percentage. In particular, we examine the extent to which a team playing at home has an advantage over the visiting team.