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regressionanalysis, etc ; radiometry; reflectance; remote sensing; variance; Show all 5 Subjects
Abstract:
... This study addresses the problem of shadows in multi-temporal imagery, which is a key issue with change detection approaches based on image comparison. We apply image-to-image radiometric normalizations including histogram matching (HM), mean-variance (MV) equalization, linear regression based on pseudo-invariant features (PIF-LR), and radiometric control sets (RCS) representing high- and low-refl ...
... The article Estimation of rainfall intensity–duration–frequency curves at ungauged locations using quantile regression methods, written by D. Ouali, A. J. Cannon, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 28 May, 2018 without open access. ...
... Panel‐count data arise when each study subject is observed only at discrete time points in a recurrent event study, and only the numbers of the event of interest between observation time points are recorded (Sun and Zhao, 2013). However, sometimes the exact number of events between some observation times is unknown and what we know is only whether the event of interest has occurred. In this articl ...
regressionanalysis, etc ; governance; models; planning; questionnaires; water reuse; Texas; Show all 7 Subjects
Abstract:
... Securing sources for water reuse and coordinating efforts of water governing agencies to do so are critical to realizing the potential of reused water to provide nearly 24% of the water demand of the San Antonio Region, defined as regions “L” and “K” by the Texas Water Development Board (TWDB). This research identifies key governance factors that contribute to increasing water reuse within the wat ...
regressionanalysis, etc ; Bayesian theory; air temperature; economic sectors; Show all 4 Subjects
Abstract:
... Air temperature is a significant meteorological variable that affects social activities and economic sectors. In this paper, a non-parametric and a parametric approach are used to forecast hourly air temperature up to 24 h in advance. The former is a regression model in the Functional Data Analysis framework. The nonlinear regression operator is estimated using a kernel function. The smoothing par ...
... In ecological studies, researchers often try to convey the analysis results to individual level based on aggregate data. In order to do this correctly, the possibility of ecological bias should be studied and addressed. One of the key ideas used to address the ecological bias issue is to derive the ecological model from the individual model and to check whether the parameter of interest in the ind ...
... Kong et al. (2016, Biometrics 72, 364–371) presented a quantile regression kernel machine (QRKM) test for robust analysis of genetic marker‐set association studies. A potential limitation of QRKM is the permutation‐based test design may be unscalable for the massive sizes of modern datasets. In this article, we present an alternative strategy for p‐value calculation of QRKM, which is capable of sp ...
regressionanalysis, etc ; data collection; urbanization; Show all 3 Subjects
Abstract:
... This study aims to analyse the processes and patterns of peri-urbanization using diurnal earth observation data-sets from onboard DMSP–Operational Linescan System. In this study, multiple correlation, simple and conditional linear regression are used to find out the degree of relationship and spatial behavioural pattern of the factors responsible for the urbanization. All the factors are standardi ...
regressionanalysis, etc ; air pollution control; meteorological parameters; neural networks; nitrates; pollutants; pollution; prediction; China; Show all 9 Subjects
Abstract:
... Peroxyacyl nitrates (PANs) are important secondary pollutants in ground-level atmosphere. Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during specific pollution events. In this study, four models based on the back-propagation (BP) artificial neural network (ANN) and multiple linear regression (MLR) methods were used to predict ...
regressionanalysis, etc ; Bayesian theory; electric power; models; renewable energy sources; wind speed; Show all 6 Subjects
Abstract:
... Accurate wind speed forecasting is helpful for reducing the instantaneous fluctuation of voltage, and also has great practical significance on power dispatching and plan. There are two problems in wind speed forecasting: loss of details when transforming the high-resolution data into the low-resolution data and outliers existing in our data. So, a sparse Bayesian-based robust functional regression ...
regressionanalysis, etc ; deforestation; diet; fearfulness; foods; foodways; global warming; ingestion; insects; marketing; pathogens; social behavior; surveys; Show all 13 Subjects
Abstract:
... Insects are a highly sustainable and nutritious source of protein, and, thus, incorporating insects in to Western food culture is one way to address major global challenges like global warming and deforestation. Consumer studies show, however, that Westerners’ willingness to eat insect-containing food is low. One formidable barrier is the perception that insects are disgusting, and it is generally ...
regressionanalysis, etc ; geomorphology; hydrology; inventories; landscapes; landslides; models; prediction; rapid methods; Show all 9 Subjects
Abstract:
... Rapid assessment of spatial distribution of earthquake-induced landslides could provide valuable information in the emergency response phase. Previous studies proposed global analyses with the aim of predicting earthquake-induced landslide distributions in near real-time. However, in all those studies, mapping units are constituted by pixels, which do not reflect homogeneously distributed physical ...
regressionanalysis, etc ; aerosols; chemical composition; emissions; macrophages; monitoring; particulates; ships; toxicity; Show all 9 Subjects
Abstract:
... In this study, weekly samples of ambient PM0.25 (particulate matter with an aerodynamic diameter <0.25 μm) were collected in three contrasting locations, including central Los Angeles (USC), north Long Beach (NLB), and the Port of Long Beach (PRT), during June and July of 2017 to evaluate the chemical composition of ambient PM0.25 and identify the sources that contribute to the oxidative potential ...
regressionanalysis, etc ; crystallization; dispersions; firmness; models; oils; rheology; storage modulus; sugars; sweets; temperature; Show all 11 Subjects
Abstract:
... The relationship between microscopic and macroscopic properties in fat-continuous dispersions is multifaceted compared to bulk oils, which limits the ability to extrapolate results from bulk systems towards complex formulations. The impact of confectioner’s sugar on the crystallization and rheology of palm oil (PO) and mid-fraction blend (PMF) was investigated in this study. Adding sugar significa ...
regressionanalysis, etc ; General Circulation Models; ecology; humans; hydrology; permafrost; support vector machines; China; Show all 8 Subjects
Abstract:
... Frozen ground degradation profoundly impacts the hydrology, ecology and human society on the Tibetan Plateau (TP) and the downstream regions. The spatial distribution and potential changes of permafrost and maximum thickness of seasonally frozen ground (MTSFG) on the TP is of great importance and needs more in-depth studies. This study maps the permafrost and MTSFG distribution in the baseline per ...
regressionanalysis, etc ; assets; earthquakes; economic development; humans; residential housing; risk; risk assessment; risk reduction; China; Show all 10 Subjects
Abstract:
... Diagnosing all components of risk is essential in earthquake loss attribution science, but quantitative estimates on how sensitive the earthquake-induced direct economic losses (DELs) are to changes in hazard, exposure and vulnerability is rarely known. Here the relationship between earthquake DELs and earthquake magnitude (Ms), asset value exposure (K), proportion of non-steel-concrete residentia ...
regressionanalysis, etc ; atmospheric precipitation; models; prediction; radar; uncertainty; Central European region; Czech Republic; Show all 8 Subjects
Abstract:
... The study presents a new method nowcasting precipitation called the Ensemble Tree Method (ETM), which gives probability forecast of accumulated precipitation based on the extrapolation of radar reflectivity. ETM combines a tree model with a Bootstrap technique. It forecasts the probability that the hourly accumulated precipitation exceeds a given threshold for cells of 3 by 3 km size.ETM was teste ...
regressionanalysis, etc ; algorithms; altitude; atmospheric precipitation; disasters; drought; evapotranspiration; gauges; global warming; rivers; temperature; watersheds; China; Show all 13 Subjects
Abstract:
... This study explores the respective contributions of precipitation and temperature variability to the trends of the duration and severity of the dryness/wetness, and takes the Pearl River basin (PRB) in the southern China as a study example. The Standardized Precipitation Evapotranspiration Index (SPEI), which uses the monthly precipitation and temperature as input variables, was calculated based o ...
regressionanalysis, etc ; chocolate; emotions; females; food consumption; food intake; potato chips; sensory evaluation; surveys; women; Show all 10 Subjects
Abstract:
... The current study examined the relation between women's food intake and their conformity to feminine norms after a negative mood induction, as well as the potential moderating role of expressive suppression. Female participants (N = 197) watched a sad movie clip, partook in a taste test in which they consumed potato chips and chocolate, and completed a survey with questions designed to assess conf ...
regressionanalysis, etc ; assets; case studies; models; natural gas; probability; system optimization; Show all 7 Subjects
Abstract:
... In this paper, a risk-based optimization methodology for a maintenance schedule considering Process Variables (PVs), is developed within the framework of asset integrity assessment. To this end, an integration of Dynamic Bayesian Network, Damage Modelling and sensitivity analysis are implemented to clarify the behaviour of failure probability, considering the exogenous undisciplinable perturbation ...