Search results for "least square"
showing 10 items of 286 documents
Simultaneous Kinetic Determination of Carbamate Pesticides after Derivatization withp-Aminophenol by Using Partial Least Squares
1996
Abstract A method has been developed for the fast spectrophotometric determination of propoxur, carbaryl, and ethiofencarb in water samples using injection analysis in the stopped-flow mode. The method is based on the reaction between p -aminophenol and the phenolic compounds obtained from the pesticides, after a previous hydrolysis with 0.05 M NaOH at room temperature for 15 min. The partial least-squares treatment of the spectrophotometry kinetic data provides a simultaneous determination of the three carbamate pesticides assayed with a relative accuracy error lower than 5% in complex mixtures also containing formetanate, which is only partially hydrolyzed under the experimental condition…
Factors affecting Nigerian teacher educators’ technology integration : Considering characteristics, knowledge constructs, ICT practices and beliefs
2020
To provide a diverse comprehension of teachers' TPACK (Technological, Pedagogical, and Content Knowledge) and how TPACK is reflected in practice, this study examined teacher educators' (TEs') conceptions of technology integration. Specifically, the main objective of the study was to investigate the factors influencing Nigerian teacher educators' technology integration using a self-completion survey administered to Nigerian teacher educators from three schools in the southern region of Nigeria. We utilized the partial least squares structural equation modeling (PLS-SEM) approach for the data analysis. Two frameworks—TPACK and Second Information Technology in Education Study (SITES)— guided t…
Multi-technique approach for qualitative and quantitative characterization of furazidin degradation kinetics under alkaline conditions
2016
Degradation of drug furazidin was studied under different conditions of environmental pH (11-13) and temperature (30-60°C). The novel approach of hybrid hard- and soft-multivariate curve resolution-alternating least squares (HS-MCR-ALS) method was applied to UV-vis spectral data to determine a valid kinetic model and kinetic parameters of the degradation process. The system was found to be comprised of three main species and best characterized by two consecutive first-order reactions. Furazidin degradation rate was found to be highly dependent on the applied environmental conditions, showing more prominent differences between both degradation steps towards higher pH and temperature. Complim…
Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy
2013
Abstract Reflectance spectroscopy provides an alternate method to non-destructively characterize key soil properties. Different approaches, including chemometrics techniques or specific absorption features, have been proposed to estimate soil properties from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance domains. The main goal of this study was to test the performance of two distinct methods for soil texture estimation by VNIR-SWIR reflectance measurements: i) the Continuum Removal (CR) technique that was used to correlate specific spectral absorption features with clay, silt and sand content, and ii) the Partial Least-Squares Regressio…
Power estimation for non-standardized multisite studies
2016
A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this…
Least-squares community extraction in feature-rich networks using similarity data
2021
We explore a doubly-greedy approach to the issue of community detection in feature-rich networks. According to this approach, both the network and feature data are straightforwardly recovered from the underlying unknown non-overlapping communities, supplied with a center in the feature space and intensity weight(s) over the network each. Our least-squares additive criterion allows us to search for communities one-by-one and to find each community by adding entities one by one. A focus of this paper is that the feature-space data part is converted into a similarity matrix format. The similarity/link values can be used in either of two modes: (a) as measured in the same scale so that one may …
Experimental validation for spectrum cartography using adaptive multi-kernels
2017
This paper validates the functionality of an algorithm for spectrum cartography, generating a radio environment map (REM) using adaptive radial basis functions (RBF) based on a limited number of measurements. The power at all locations is estimated as a linear combination of different RBFs without assuming any prior information about either power spectral densities (PSD) of the transmitters or their locations. The RBFs are represented as centroids at optimized locations, using machine learning to jointly optimize their positions, weights and Gaussian decaying parameters. Optimization is performed using expectation maximization with a least squares loss function and a quadratic regularizer. …
Missing Data
2009
In this chapter, we deal with the problem of missing data in principal component analysis (PCA) and partial least squares (PLS) methods. First, we review several statistical methods proposed in the literature for handling missing data. Both single and multiple imputation (MI) methods are studied and compared using simulated data. After this, we particularize the missing data problem for building and exploiting multivariate calibration models. Several approaches proposed in the literature are introduced and their performance compared based on several real data sets.
A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover
2014
Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR), kernel ridge regression (KRR), artificial neural networks (NN), random forest regression (RFR) and partial least squares regression (PLSR). Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, gras…
Probabilistic Self-Localization and Mapping - An Asynchronous Multirate Approach
2008
[EN] In this paper, we present a set of robust and efficient algorithms with O(N) cost for the solution of the Simultaneous Localization And Mapping (SLAM) problem of a mobile robot. First, we introduce a novel object detection method, which is mainly based on multiple line fitting method for landmark detection with regular constrained angles. Second, a line-based pose estimation method is proposed, based on LeastSquares (LS). This method performs the matching of lines, providing the global pose estimation under assumption of known Data-Association. Finally, we extend the FastSLAM (FActored Solution To SLAM) algorithm for mobile robot self-localisation and mapping by considering the asynchr…