The ability to track and monitor animals in the wild presents a challenge in both hardware and software development. This is a challenge facing all sensor networks, where there is a requirement for more computation to take place at the nodes whilst expending minimal battery life. In this paper we look at applying reinforcement learning on accelerometer data collected from a lion tag to learn a ...

The sampling plan for the mean for correlated data is studied. The Operating Characteristic (OC) of the variable sampling plan for mean for correlated data are calculated and compared with the OC of known σ case.

Weighted sampling without replacement has proved to be a very important tool in designing new algorithms. Efraimidis and Spirakis (IPL 2006) presented an algorithm for weighted sampling without replacement from data streams. Their algorithm works under the assumption of precise computations over the interval [0, 1]. Cohen and Kaplan (VLDB 2008) used similar methods for their bottom-k sketches. ...

Data mining in relational data poses unique opportunities and challenges. In particular, relational autocorrelation provides an opportunity to increase the predictive power of statistical models, but it can also mislead investigators using traditional sampling approaches to evaluate data mining algorithms. We investigate the problem and provide new sampling approaches that correct the bias asso...

Simulating the conformational dynamics of biomolecules is extremely difficult due to the rugged nature of their free energy landscapes and multiple long-lived, or metastable, states. Generalized ensemble (GE) algorithms, which have become popular in recent years, attempt to facilitate crossing between states at low temperatures by inducing a random walk in temperature space. Enthalpic barriers ...

This thesis presents statistical sampling scheme optimization for geo-environmental purposes on the basis of hyperspectral data. It integrates derived products of the hyperspectral remote sensing data into individual sampling schemes. Five different issues are being dealt with. First, the optimized sampling scheme is presented to select samples that represent different ontological categories. T...