Search results for "regression model"
showing 10 items of 53 documents
Airborne-laser-scanning-derived auxiliary information discriminating between broadleaf and conifer trees improves the accuracy of models for predicti…
2020
Managing forests for ecosystem services and biodiversity requires accurate and spatially explicit forest inventory data. A major objective of forest management inventories is to estimate the standing timber volume for certain forest areas. In order to improve the efficiency of an inventory, field based sample-plots can be statistically combined with remote sensing data. Such models usually incorporate auxiliary variables derived from canopy height models. The inclusion of forest type variables, which quantify broadleaf and conifer volume proportions, has been shown to further improve model performance. Currently, the most common way of quantifying broadleaf and conifer forest types is by ca…
“Natural wine” consumers and interest in label information: An analysis of willingness to pay in a new Italian wine market segment
2019
Abstract Increasing public attention to issues of health and environmental sustainability has contributed to a growing consumer demand for “natural” food and drinks. As has been observed, this trend has also affected the wine market, leading to the spread of so-called “natural wine”. According to the literature, consumers who are aware of the social and environmental impact of their consumption choices pay more attention to the information displayed on the label as a tool to reduce the risk associated with their purchase. This study seeks to identify which consumers are willing to pay for natural wine and to understand what information on the label influences their choice. This study is one…
District heating networks: enhancement of the efficiency
2019
International audience; During the decades the district heating's (DH) advantages (more cost-efficient heat generation and reduced air pollution) overcompensated the additional costs of transmission and distribution of the centrally produced thermal energy to consumers. Rapid increase in the efficiency of low-power heaters, development of separated low heat density areas in cities reduce the competitiveness of the large centralized DH systems in comparison with the distributed cluster-size networks and even local heating. Reduction of transmission costs, enhancement of the network efficiency by optimization of the design of the DH networks become a critical issue. The methodology for determ…
Trajectories of stress biomarkers and anxious-depressive symptoms from pregnancy to postpartum period in women with a trauma history
2019
Background: Cross-sectional studies have found that a trauma history can be associated with anxious-depressive symptomatology and physiological stress dysregulation in pregnant women. Methods: This prospective study examines the trajectories of both anxiety and depressive symptoms and salivary cortisol and alpha-amylase biomarkers from women with (n = 42) and without (n = 59) a trauma history at (i) 38th week of gestation (T1), (ii) 48 hours after birth (T2), and (iii) three months after birth (T3). Results: The quantile regression model showed that trauma history was associated with higher cortisol levels at T1 and this difference was sustained along T2 and T3. Conversely, there were no si…
Optimized and automated estimation of vegetation properties: Opportunities for Sentinel-2
2014
La Biosfera es uno de los principales sistemas que conforman la Tierra. Su estudio permite comprender la relación entre la vegetación y el ciclo del carbono y cómo éste puede ser afectado por los cambios en los niveles de CO2 y los usos de suelo. Para el estudio de estas dinámicas a escala global y local, han sido desarrollados diversos modelos que son representaciones de la realidad en una escala y complejidad más simple. Parte de las variables de entrada de estos modelos son obtenidas mediante medidas de teledetección gracias al Global Climate Observing System (GCOS), que ha determinado un conjunto de 50 variables climáticas esenciales que contribuyen a los estudios de cambio climático qu…
Healthcare students’ flu vaccine uptake in the last 5 years and future vaccination acceptance: is there a possible association?
2020
Background:Despite the free-of-charge offer of influenza vaccines to at-risk subgroups, vaccine coverage remains low and far from the target, probably due to the false myths and misperceptions. We aimed to explore the healthcare students’ vaccination behavior and beliefs to find any association between vaccination uptake during the last 5 years and future vaccination acceptance.Study design:A multicentre cross-sectional study.Methods:From Oct 2017 to Nov 2018, the Italian healthcare students from 14 different universities in 2017/2018 were enrolled, through an online and anonymous questionnaire previously validated. Absolute and relative frequencies were calculated and Pearson's Chi-square …
Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms and the development of the software A…
2014
Background. This thesis consist of parts(i)Introduction in wich we present the clinical problem of rhinitis;(ii)the methods to evaluate the diagnostic choises;(iii)the rational errors in Allergy,(iv)the experimental part of thesis with wich we developed the software ARTSTAT,wich is the application of the analysis reported.Objective: We studied the ability of the logistic regression model obtained by the evaluaqtion of a database, to detect patients with positive allergy skin prick test(SPT)and patients with negative SPT. The model developed was valitated using the data set obtained from another medical institution. Methods: The analysis was carried out using a database obtained from a quest…
Prediction models based on soil properties for evaluating the uptake of eight heavy metals by tomato plant (Lycopersicon esculentum Mill.) grown in a…
2021
The aim of this study is to design de novo prediction models in order to gauge the likely uptake of eight heavy metals (Al, Cr, Cu, Fe, Mn, Ni, Pb and Zn) by Lycopersicon esculentum, the tomato plant. Uptake was assessed within the plant’s root, stem, leaf and fruit tissues, respectively. The plant was cultivated in soil amended by different application rates of sewage sludge, i.e. 0, 10, 20, 30 and 40 g/kg. The roots exhibited markedly elevated heavy metal concentrations compared to the above-ground plant components, with the exception of the quantity of Ni in the leaves. Apart from Al, Fe and Mn, a bioconcentration factor >1 was identified for all heavy metals. Excluding Ni in the leaves,…
An Extension of the DgLARS Method to High-Dimensional Relative Risk Regression Models
2020
In recent years, clinical studies, where patients are routinely screened for many genomic features, are becoming more common. The general aim of such studies is to find genomic signatures useful for treatment decisions and the development of new treatments. However, genomic data are typically noisy and high dimensional, not rarely outstripping the number of patients included in the study. For this reason, sparse estimators are usually used in the study of high-dimensional survival data. In this paper, we propose an extension of the differential geometric least angle regression method to high-dimensional relative risk regression models.
Krill herd algorithm-based neural network in structural seismic reliability evaluation
2018
ABSTRACTIn this research work, the relative displacement of the stories has been determined by means of a feedforward Artificial Neural Network (ANN) model, which employs one of the novel methods for the optimization of the artificial neural network weights, namely the krill herd algorithm. For the purpose of this work, the area, elasticity, and load parameters were the input parameters and the relative displacement of the stories was the output parameter. To assess the precision of the feedforward (FF) model optimized using the Krill Herd Optimization (FF-KH) algorithm, comparison of results has been performed relative to the results obtained by the linear regression model, the Genetic Alg…