Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem

Phonetic drift

This chapter provides an overview of research on the phonetic changes that occur in one’s native language (L1) due to recent experience in another language (L2), a phenomenon known as phonetic drift. Through a survey of empirical findings on segmental and suprasegmental acoustic properties, the chapter examines the features of the L1 that are subject to phonetic drift, the cognitive mechanism(s) behind phonetic drift, and the various factors that influence the likelihood of phonetic drift. In short, virtually all aspects of L1 speech are subject to drift, but different aspects do not drift in the same manner, possibly due to multiple routes of L2 influence coexisting at different levels of L1 phonological structure. In addition to the timescale of these changes, the chapter discusses the relationship between phonetic drift and attrition as well as some of the enduring questions in this area.https://drive.google.com/open?id=1eQbh17Z4YsH8vY_XjCHGqi5QChfBKcAZhttps://drive.google.com/open?id=1eQbh17Z4YsH8vY_XjCHGqi5QChfBKcAZhttps://drive.google.com/open?id=1eQbh17Z4YsH8vY_XjCHGqi5QChfBKcAZAccepted manuscriptAccepted manuscrip

Experimental study of factors influencing the risk of drift from field sprayers Part 2: Spray application technique.

Recently, spray drift and its effects have become an important aspect of risk assessment in the registration process of pesticides in Belgium. In this regulation, drift reducing spray application techniques can be used to reduce buffer zones. The purpose of this research is to measure and compare the amount of drift sediment for different spray application techniques under field conditions. A drift prediction equation for the reference spraying was used to compare other spraying techniques with the reference spraying, under different weather conditions. Drift measurements were performed for several combinations of nozzle type (flat fan, low-drift, air injection) and size (ISO 02, 03, 04 and 06), spray pressure (2, 3 and 4 bar), driving speed (4, 6, 8 and 10 km.h-1) and spray boom height (0.3, 0.5 and 0.75 m). Nozzle type as well as spray pressure, driving speed and spray boom height, have an important effect on the amount of spray drift. Larger nozzle sizes, lower spray pressures and driving speeds and lower spray boom heights generally reduce spray drift. Concerning nozzle types, air injection nozzles have the highest drift reduction potential followed by the low-drift nozzles and the standard flat fan nozzles

Drift of Riffle Beetles (Coleoptera: Elmidae) in a Small Illinois Stream

The daily and seasonal periodicities of drift of riffle beetles were examined in Polecat Creek. Illinois. during the spring and summer of 1978. Drift samples were collected from a single site over four 24-h periods. Dubiraphia vittata adults comprised 72% of the total numerical sample and exhibited greatest mean daily drift density in September. Macronychus glabratus adults were also common in drift collections, with highest densities re- corded during .\u27.lay and August. The drift of D. vittata and M. glabratus exhibited distinct patterns of die! periodicity with peaks occurring in the early hours of darkness. Substantial differences in drift densities between adult and larval stages were evident for D. vittata and M. glabratus. in both cases the adults were more prone to drift

Metropolis Integration Schemes for Self-Adjoint Diffusions

We present explicit methods for simulating diffusions whose generator is self-adjoint with respect to a known (but possibly not normalizable) density. These methods exploit this property and combine an optimized Runge-Kutta algorithm with a Metropolis-Hastings Monte-Carlo scheme. The resulting numerical integration scheme is shown to be weakly accurate at finite noise and to gain higher order accuracy in the small noise limit. It also permits to avoid computing explicitly certain terms in the equation, such as the divergence of the mobility tensor, which can be tedious to calculate. Finally, the scheme is shown to be ergodic with respect to the exact equilibrium probability distribution of the diffusion when it exists. These results are illustrated on several examples including a Brownian dynamics simulation of DNA in a solvent. In this example, the proposed scheme is able to accurately compute dynamics at time step sizes that are an order of magnitude (or more) larger than those permitted with commonly used explicit predictor-corrector schemes.Comment: 54 pages, 8 figures, To appear in MM