This paper investigates the use of strategies to enhance an existing machine learning tool, C4.5, to deal with concept drift and non-determinism in a time series domain. Temporal prediction is a difficult problem faced in most human endeavours. While many specialised time series prediction techniques have been developed, these techniques have limitations. Most are restricted to modeling whole s...

Traditional approaches to data mining are based on an assumption that the process that generated or is generating a data stream is static. Although this assumption holds for many applications, it does not hold for many others. Consider systems that build models for identifying important e-mail. Through interaction with and feedback from a user, such a system might determine that particular e-ma...

What is genetic drift? Say you have a population of 5,000 people. That makes 10,000 copies of each gene. Imagine a gene where 3,000 of those copies are of one particular allele or type. In the next generation, there won’t necessarily be exactly 3,000 copies again. There may be 3,050 or 2,960 copies instead. Some gametes get randomly picked out of all the possible gametes that could have been us...

Gyrokinetic theories, even ‘global’ models, typically rely on a separation in scale (in perpendicular wavelength) between the fluctuations and system scale. In such models direct simulation of system-scale dynamics like magnetohydrodynamic (MHD) motion is formally not consistent. Drift-kinetic theory, other hand, may be directly applied to model MHD-ordered behaviour. I review long-wavelength l...

The Neutrino Factory (NF) concept includes several channels that treat muon beam to allow its capture into the accelerating part of the complex [1]. There must be a "drift" channel where pions decay generating muons. In this channel a correlation develops between muon energy and its position (mass separation). Due to a very high beam emittance and energy spread after the target, a high magnetic...

This paper explores the use of the standard approach for proving runtime bounds in discrete domains—often referred to as drift analysis—in the context of optimization on a continuous domain. Using this framework we analyze the (1+1) Evolution Strategy with one-fifth success rule on the sphere function. To deal with potential functions that are not lower-bounded, we formulate novel drift theorem...

Enteric, Zoonotic and Vector-Borne Diseases, Public Health Ontario, Canada Adult mosquito surveillance programs provide a primary means to understand mosquito vector population dynamics, but such data are typically sparse in space and irregular in time, due to the limit to the available resources for trapping and/or extreme physical conditions. Particularly, missing observations often encounter...

Designing effective feature and handling the model drift problem are two important aspects for online visual tracking. For feature representation, gradient and color features are most widely used, but how to effectively combine them for visual tracking is still an open problem. In this paper, we propose a rich feature descriptor, MC-HOG, by leveraging rich gradient information across multiple c...

The purpose for wireless sensor networks is to deploy low cost sensors with sufficient computing and communication capabilities to support networked sensing applications. Even when the sensors are properly calibrated at the time of their deployment, they develop drift in their readings leading to biased sensor measurements. Noting that a physical phenomenon in a certain area follows some spatio...

During natural viewing large saccades shift the visual gaze from one target to another every few hundreds of milliseconds. The role of microsaccades (MSs), small saccades that show up during long fixations, is still debated. A major debate is whether MSs are used to redirect the visual gaze to a new location or to encode visual information through their movement. We argue that these two functio...