Search results for "Drift"
showing 10 items of 321 documents
Long‐Term Tillage and Cropping System Effects on Chemical and Biochemical Characteristics of Soil Organic Matter in a Mediterranean Semiarid Environm…
2015
Several studies have reported how tillage and cropping systems affect quantity, quality, and distribution of soil organic matter (SOM) along the profile. However, the effect of soil management on the chemical structure of SOM and on its hydrophobic and hydrophilic components has been little investigated. In this work, the long-term (19 years) effects of two cropping systems (wheat monoculture and wheat/faba bean rotation) and three tillage managements (conventional, reduced, and no tillage) on some chemical characteristics of SOM and their relationships with labile carbon (C) pools were evaluated. Soil samples were taken from the topsoil (0–15 cm) of a Chromic Haploxerert (central Sicily, I…
Development of a 3D CZT detector prototype for Laue Lens telescope
2010
We report on the development of a 3D position sensitive prototype suitable as focal plane detector for Laue lens telescope. The basic sensitive unit is a drift strip detector based on a CZT crystal, (similar to 19x8 mm(2) area, 2.4 mm thick), irradiated transversally to the electric field direction. The anode side is segmented in 64 strips, that divide the crystal in 8 independent sensor (pixel), each composed by one collecting strip and 7 (one in common) adjacent drift strips. The drift strips are biased by a voltage divider, whereas the anode strips are held at ground. Furthermore, the cathode is divided in 4 horizontal strips for the reconstruction of the third interaction position coord…
Effectiveness of local feature selection in ensemble learning for prediction of antimicrobial resistance
2008
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift (CD), complicates the task of learning a robust model. Different ensemble learning (EL) approaches (that instead of learning a single classifier try to learn and maintain a set of classifiers over time) have been shown to perform reasonably well in the presence of concept drift. In this paper we study how much local feature selection (FS) can improve ensemble performance for da…
Vertical and lateral drift corrections of scanning probe microscopy images
2010
A procedure is presented for image correction of scanning probe microscopy data that is distorted by linear thermal drift. The procedure is based on common ideas for drift correction, which the authors combine to a comprehensive step-by-step description of how to measure drift velocities in all three dimensions and how to correct the images using these velocities. The presented method does not require any knowledge about size or shape of the imaged structures. Thus, it is applicable to any type of scanning probe microscopy image, including images lacking periodic structures. Besides providing a simple, ready-to-use description of lateral and vertical drift correction, they derive all formul…
Adaptive time window linear regression algorithm for accurate time synchronization in wireless sensor networks
2015
In this article we propose a new algorithm for time synchronization in wireless sensor networks. The algorithm is based on linear regression to achieve long-term synchronization between the clocks of different network motes. Since motes are built using low-cost hardware components, usually their internal local clocks are not very accurate. In addition, there are other effects that affect the clock precision, such as: environmental conditions, supply voltage, aging, manufacturing process. Because some of these causes are external and unpredictable, the clock drift between two motes can change in a random way. Due to these changes, the optimum time window used for performing the linear regres…
Service innovation methodologies I : what can we learn from service innovation and new service development research? : report no 1 from the TIPVIS-pr…
2007
This report presents a review of service innovation and service development literature. The main purpose of the review is to identify normative implications for service innovation methodologies. Three separate reviews are conducted and reported; an open search review based on specific search terms of relevance to service innovation methodologies, a review of articles in four of the most influential journals on service innovation/service development, and a review focusing contributions applying normative approaches and/or principles. Some of the main conclusions from the review support previous findings that the service innovation process is less formal and that it is more difficult to ident…
Boards' involvement in firm strategy : how can a board be effectively involved in strategy formulation and contribute to firm's successfulness
2006
Masteroppgave i økonomi og administrasjon 2006 - Høgskolen i Agder, Kristiansand The role of the board of directors in firm strategy has been subject of debate for a long time. Many researches have been done from different perspectives particularly on this issue. The purpose of this thesis is to study the role of the board of directors in firm strategy. This study will further investigate on how the board of directors can be effectively involved in strategy formulation for the firms and through this to contribute to the firms' successfulness. Board of directors is a group of individuals who are elected by the shareholders of a corporation and assigned to carry out certain tasks on behalf of…
Concept Drift Detection Using Online Histogram-Based Bayesian Classifiers
2016
In this paper, we present a novel algorithm that performs online histogram-based classification, i.e., specifically designed for the case when the data is dynamic and its distribution is non-stationary. Our method, called the Online Histogram-based Naïve Bayes Classifier (OHNBC) involves a statistical classifier based on the well-established Bayesian theory, but which makes some assumptions with respect to the independence of the attributes. Moreover, this classifier generates a prediction model using uni-dimensional histograms, whose segments or buckets are fixed in terms of their cardinalities but dynamic in terms of their widths. Additionally, our algorithm invokes the principles of info…
Online Estimation of Discrete Densities
2013
We address the problem of estimating a discrete joint density online, that is, the algorithm is only provided the current example and its current estimate. The proposed online estimator of discrete densities, EDDO (Estimation of Discrete Densities Online), uses classifier chains to model dependencies among features. Each classifier in the chain estimates the probability of one particular feature. Because a single chain may not provide a reliable estimate, we also consider ensembles of classifier chains and ensembles of weighted classifier chains. For all density estimators, we provide consistency proofs and propose algorithms to perform certain inference tasks. The empirical evaluation of t…
Handling local concept drift with dynamic integration of classifiers : domain of antibiotic resistance in nosocomial infections
2006
In the real world concepts and data distributions are often not stable but change with time. This problem, known as concept drift, complicates the task of learning a model from data and requires special approaches, different from commonly used techniques, which treat arriving instances as equally important contributors to the target concept. Among the most popular and effective approaches to handle concept drift is ensemble learning, where a set of models built over different time periods is maintained and the best model is selected or the predictions of models are combined. In this paper we consider the use of an ensemble integration technique that helps to better handle concept drift at t…