Search results for "Regression"

A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network

2016

International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…

Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data

2022

In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photo…

La rigenerazione del fegato dopo epatectomia: un’analisi mediante regressione multipla del volume futuro residuo epatico mediante l’utilizzo di tomog…

2011

Systems level approach reveals the correlation of endoderm differentiation of mouse embryonic stem cells with specific microstructural cues of fibrin…

2014

Stem cells receive numerous cues from their associated substrate that help to govern their behaviour. However, identification of influential substrate characteristics poses difficulties because of their complex nature. In this study, we developed an integrated experimental and systems level modelling approach to investigate and identify specific substrate features influencing differentiation of mouse embryonic stem cells (mESCs) on a model fibrous substrate, fibrin. We synthesized a range of fibrin gels by varying fibrinogen and thrombin concentrations, which led to a range of substrate stiffness and microstructure. mESCs were cultured on each of these gels, and characterization of the diff…

Biomass Assessment of Agricultural Crops Using Multi-temporal Dual-Polarimetric TerraSAR-X Data

2019

The biomass of three agricultural crops, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), was studied using multi-temporal dual-polarimetric TerraSAR-X data. The radar backscattering coefficient sigma nought of the two polarization channels HH and VV was extracted from the satellite images. Subsequently, combinations of HH and VV polarizations were calculated (e.g. HH/VV, HH + VV, HH × VV) to establish relationships between SAR data and the fresh and dry biomass of each crop type using multiple stepwise regression. Additionally, the semi-empirical water cloud model (WCM) was used to account for the effect of crop biomass on radar backscatter …

Authentication of extra virgin olive oils by Fourier-transform infrared spectroscopy

2010

Fourier-transform infrared spectroscopy (FTIR), followed by multivariate treatment of the spectral data, was used to classify vegetable oils according to their botanical origin, and also to establish the composition of binary mixtures of extra virgin olive oil (EVOO) with other low cost edible oils. Oil samples corresponding to five different botanical origins (EVOO, sunflower, corn, soybean and hazelnut) were used. The wavelength scale of the FTIR spectra of the oils was divided in 26 regions. The normalized absorbance peak areas within these regions were used as predictors. Classification of the oil samples according to their botanical origin was achieved by linear discriminant analysis (…

Analysis of Caffeine, Sweeteners, and Other Additives in Beverages by Vibrational Spectroscopy

2001

This chapter presents a review of the scientific literature on the use of vibrational spectroscopy, near-infrared (NIR), mid-infrared (mid-IR), and Raman, for the analysis of caffeine, sweeteners, and other additives in beverages and related products. Direct analysis procedures of coffee and tea, for both classification according to precedence or variety and quantitative determination of caffeine, are available. For beverage analysis, caffeine has been determined by direct attenuated total reflection (ATR) measurement or by transmission spectroscopy in the mid-IR region after extraction with chloroform. Different strategies have been employed for the analysis of sweeteners in beverages and …

Use of electronic nose to determine defect percentage in oils. Comparison with sensory panel results

2010

Abstract An electronic nose based on an array of 6 metal oxide semiconductor sensors was used, jointly with linear discriminant analysis (LDA) and artificial neural network (ANN) method, to classify oils containing the five typical virgin olive oil (VOO) sensory defects (fusty, mouldy, muddy, rancid and winey). For this purpose, these defects, available as single standards of the International Olive Council, were added to refined sunflower oil. According to the LDA models and the ANN method, the defected samples were correctly classified. On the other hand, the electronic nose data was used to predict the defect percentage added to sunflower oil using multiple linear regression models. All …

Ārvalstu tiešo investīciju ietekmējošie faktori Latvijā

2015

Bakalaura darba „Ārvalstu tiešo investīciju ietekmējošie faktori Latvijā” galvenais mērķis ir izpētīt ienākošo ārvalstu tiešo investīciju ietekmējošos faktorus Latvijā. Balstoties uz zinātniskajiem pētījumiem, tiek noskaidroti iespējamie faktori, kas ietekmē ĀTI. Viena no darbā izmantotajām metodēm ir MKM daudzfaktoru regresijas analīze. Šajā analīzē tiek izmantoti ceturkšņu dati un aplūkotais periods ir no 2001. gada līdz 2014. gadam. Tiek noskaidrots, ka tirgus lielums, tirgus atvērtība un iegūldījumu atdeve pozitīvi ietekmē ienākošās ĀTI plūsmas Latvijā, kamēr tādi faktori kā inflācija, darbaspēka izmaksas, valūtas vērtība un ĀTI novēlotās vērtības netiek novērtēti kā statistiski nozīmīg…

ANALISI GIS E MODELLI STATISTICI PER LA VALUTAZIONE DELLA SUSCETTIBILITÀ DA FRANA A SCALA DI BACINO: IL CASO STUDIO DEL BACINO DEL TORRENTE MARVELLO

Lo studio condotto nel presente lavoro di tesi ha affrontato il tema della valutazione, a scala di bacino idrografico, della suscettibilità ai fenomeni di tipo colamento, attraverso l’applicazione di modelli statistici e tecniche di analisi spaziale GIS. La fase iniziale della preparazione di un modello di suscettibilità da frana prevede la realizzazione di un inventario degli eventi verificatesi nell’area di studio. Questo passo è di fondamentale importanza, considerando che proprio attraverso l’archivio frane è possibile analizzare ed individuare le condizioni che in passato hanno favorito l’innesco dei movimenti di versante. L’identificazione di queste condizioni, infatti, consente di pr…