Search results for "STATISTICS"

Statistical properties of the capacity of Rice channels with MRC and EGC

2009

In this paper, we have studied the statistical properties of the capacity of Rice channels for both maximal ratio combining (MRC) and equal gain combining (EGC) schemes. We have analyzed the effect of the number of diversity branches and the amplitude of the line-of-sight (LOS) components in the diversity branches on the statistics of the channel capacity. Specifically, we have derived analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the capacity of Rice channels when using MRC and EGC. It is observed that if the number of diversity branches or the amplitude of the LOS…

Double counting individuals in meta-analysis artificially inflates precision. Comment on "Device-measured light-intensity physical activity and morta…

2019

Machine Learning Methods for Spatial and Temporal Parameter Estimation

2020

Monitoring vegetation with satellite remote sensing is of paramount relevance to understand the status and health of our planet. Accurate and constant monitoring of the biosphere has large societal, economical, and environmental implications, given the increasing demand of biofuels and food by the world population. The current democratization of machine learning, big data, and high processing capabilities allow us to take such endeavor in a decisive manner. This chapter proposes three novel machine learning approaches to exploit spatial, temporal, multi-sensor, and large-scale data characteristics. We show (1) the application of multi-output Gaussian processes for gap-filling time series of…

Semisupervised kernel orthonormalized partial least squares

2012

This paper presents a semisupervised kernel orthonormalized partial least squares (SS-KOPLS) algorithm for non-linear feature extraction. The proposed method finds projections that minimize the least squares regression error in Hilbert spaces and incorporates the wealth of unlabeled information to deal with small size labeled datasets. The method relies on combining a standard RBF kernel using labeled information, and a generative kernel learned by clustering all available data. The positive definiteness of the kernels is proven, and the structure and information content of the derived kernels is studied. The effectiveness of the proposed method is successfully illustrated in standard UCI d…

Semisupervised Kernel Feature Extraction for Remote Sensing Image Analysis

2014

This paper presents a novel semisupervised kernel partial least squares (KPLS) algorithm for nonlinear feature extraction to tackle both land-cover classification and biophysical parameter retrieval problems. The proposed method finds projections of the original input data that align with the target variable (labels) and incorporates the wealth of unlabeled information to deal with low-sized or underrepresented data sets. The method relies on combining two kernel functions: the standard radial-basis-function kernel based on labeled information and a generative, i.e., probabilistic, kernel directly learned by clustering the data many times and at different scales across the data manifold. Th…

Evidentials and Epistemic Modality

2018

Abstract This chapter deals with the relation between the notional domains of information source and epistemic modality. It surveys various approaches to this relation and the cross-linguistic patterns of the way in which linguistic units (of diverse formats) with evidential or epistemic meanings develop extensions whereby they encroach into each other’s domains. Meaning extensions in either direction can adequately be captured, and confusion between both domains can be avoided, only if in the analysis of the meaning of such units (a) an onomasiological and semasiological perspective and (b) a coded-inferred divide are distinguished. Thus, epistemic extensions often arise as Generalized Con…

Latent Semantic Description of Iconic Scenes

2005

It is proposed an approach for the automatic description of scenes using a LSA–like technique. The described scenes are composed by a set of elements that can be geometric forms or iconic representation of objects. Every icon is characterized by a set of attributes like shape, colour and position. Each scene is related to a set of sentences describing their content. The proposed approach builds a data driven vector semantic space where the scenes and the sentences are mapped. A new scene can be mapped in this created space accordingly to a suitable metric. Preliminary experimental results show the effectiveness of the procedure.

A family of kernel anomaly change detectors

2014

This paper introduces the nonlinear extension of the anomaly change detection algorithms in [1] based on the theory of reproducing kernels. The presented methods generalize their linear counterparts, under both the Gaussian and elliptically-contoured assumptions, and produce both improved detection accuracies and reduced false alarm rates. We study the Gaussianity of the data in Hilbert spaces with kernel dependence estimates, provide low-rank kernel versions to cope with the high computational cost of the methods, and give prescriptions about the selection of the kernel functions and their parameters. We illustrate the performance of the introduced kernel methods in both pervasive and anom…

TH-C-AUD A-07: Evaluation of the Correction Factor Due to the Lack of Full Scatter Conditions in Cs-137 and Ir-192 Brachytherapy Dosimetric Studies

2008

Purpose: Use of a finite phantom to derive dose rate distributions around brachytherapysources implies a lack of backscattering material near the phantom periphery. Conventional planning algorithms and newly‐developed 3D correction algorithms are based on physics data under full scatter conditions. Presently, most published Monte Carlodosimetric studies have been obtained using either a spherical phantom (15cm in radius) or a cylinder phantom (40×40cm2). The study objective was to derive a simple relationship to correlate the radial dose function, g(r), obtained for each one of these phantoms to that obtained for an unbounded phantom. Method and Materials: Assuming bare point sources of 137…

Website quality and internal business factors: An empirical investigation in the Italian wine industry

2016

Purpose The purpose of this paper is dual. The first is to assess the quality of websites of Italian wineries, using the Web Assessment Index (WAI), and compare e-commerce and e-marketing websites. The second is to verify the existence of a relationship between the website quality and business revenue, on one hand, and the characteristics of managers, on the other. Design/methodology/approach A two-step survey was carried out to respond to the aims of the study. First, a sample of wineries was contacted to capture information on both the wineries and managerial characteristics. On the basis of the observed data, a second step of the analysis was performed taking into consideration 84 winer…