Search results for "Least squares"
showing 10 items of 268 documents
Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples
2016
Abstract. Image processing of X-ray-computed polychromatic cone-beam micro-tomography (μXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squar…
Eco-Friendly Estimation of Heavy Metal Contents in Grapevine Foliage Using In-Field Hyperspectral Data and Multivariate Analysis
2019
Heavy metal monitoring in food-producing ecosystems can play an important role in human health safety. Since they are able to interfere with plants’ physiochemical characteristics, which influence the optical properties of leaves, they can be measured by in-field spectroscopy. In this study, the predictive power of spectroscopic data is examined. Five treatments of heavy metal stress (Cu, Zn, Pb, Cr, and Cd) were applied to grapevine seedlings and hyperspectral data (350−2500 nm), and heavy metal contents were collected based on in-field and laboratory experiments. The partial least squares (PLS) method was used as a feature selection technique, and multiple linear regressions (…
Burned bones forensic investigations employing near infrared spectroscopy
2017
The use of near infrared (NIR) spectroscopy was evaluated, by using chemometric tools, for the study of the environmental impact on burned bones. Spectra of internal and external parts of burned bones, together with sediment samples, were treated by Principal Component Analysis and cluster classification as exploratory techniques to select burned bone samples, less affected by environmental processes, to properly carry out forensic studies. Partial Least Square Discriminant Analysis was used to build a model to classify bone samples based on their burning conditions, providing an efficient and accurate method to discern calcined and carbonized bone. Additionally, Partial Least Square regres…
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…
Integration of gradient based and response surface methods to develop a cascade optimisation strategy for Y-shaped tube hydroforming process design
2010
International audience; In the last years a strong research effort was produced in order to develop and design new forming technologies able to overcome the typical drawbacks of traditional forming operations. Among such new technologies, hydroforming proved to be one of the most promising. The design of tube hydroforming operations is mainly aimed to prevent bursting or buckling occurrence and such issues can be pursued only if a proper control of both material feeding history and internal pressure path during the process is performed.In this paper, a proper optimisation strategy was developed on Y-shaped tube hydroforming process which is characterized by a quite complex process mechanics…
Adjusted bat algorithm for tuning of support vector machine parameters
2016
Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…
Nonlinear statistical retrieval of surface emissivity from IASI data
2017
Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…
Stature and long-term labor market outcomes: Evidence using Mendelian randomization.
2017
We use the Young Finns Study (N = ∼2000) on the measured height linked to register-based long-term labor market outcomes. The data contain six age cohorts (ages 3, 6, 9, 12, 15 and 18, in 1980) with the average age of 31.7, in 2001, and with the female share of 54.7. We find that taller people earn higher earnings according to the ordinary least squares (OLS) estimation. The OLS models show that 10 cm of extra height is associated with 13% higher earnings. We use Mendelian randomization, with the genetic score as an instrumental variable (IV) for height to account for potential confounders that are related to socioeconomic background, early life conditions and parental investments, which ar…
Infrared microspectroscopic determination of collagen cross-links in articular cartilage
2017
Collagen forms an organized network in articular cartilage to give tensile stiffness to the tissue. Due to its long half-life, collagen is susceptible to cross-links caused by advanced glycation end-products. The current standard method for determination of cross-link concentrations in tissues is the destructive high-performance liquid chromatography (HPLC). The aim of this study was to analyze the cross-link concentrations nondestructively from standard unstained histological articular cartilage sections by using Fourier transform infrared (FTIR) microspectroscopy. Half of the bovine articular cartilage samples ( n = 27 ) were treated with threose to increase the collagen cross-linking whi…
Fourier transform infrared analysis of commercial formulations for Varroa treatment
2017
A comparative study has been carried out between univariate and multivariate calibration strategies for the simultaneous determination of camphor, thymol, menthol and eucalyptol in commercial formulations used for Varroa treatment. Absorbance peak heights of the transmission mid-infrared (MIR) spectra of individual monoterpenes, prepared in dichloromethane, were measured at 1737, 1151, 1022 and 980 cm−1 (corrected with a base-line at 1933 cm−1) for camphor, thymol, menthol and eucalyptol, respectively. Data were processed using the proportional equations approach in univariate mode. For multivariate calibration, partial least squares (PLS) regression based on a classical 42 design for stand…