Search results for "Mean squared error"
showing 10 items of 145 documents
Use of Guided Regularized Random Forest for Biophysical Parameter Retrieval
2018
This paper introduces a feature selection method based on random forest -the Guided Regularized Random Forest (GRRF)- which can be used in classification and regression tasks. The method is based on the regularization of the information gain in the random forest nodes to obtain a subset of relevant and non-redundant features. The proposed method is used as a preliminary step In the process of retrieving biophysical parameters from a hyperspectral image. Preliminary experiments show that we can reduce the RMSE of the retrievals by around 7% for the Leaf Area Index and around 8% for the fraction of vegetation cover when compared to the results using random forest features.
Some Examples for Solving Clinical Problems Using Neural Networks
2001
In this paper neural networks are presented for solving some pharmaceutical problems. We have predicted and prevented patients with potential risk of post-Chemotherapy Emesis and potentially intoxicated patients treated with Digoxin. Neural networks have been also used for predicting Cyclosporine A concentration and Erythropoietin concentrations. Several neural networks (multilayer perceptron for classification tasks and Elman and FIR networks for prediction) and classical methods have been used. Results show how neural networks are very suitable tools for classification and prediction tasks, outperforming the classical methods. In a neural approach it is not strictly necessary to assume a …
Parameter optimization for amplify-and-forward relaying with imperfect channel estimation
2009
Cooperative diversity is a promising technology for future wireless networks. In this paper, we consider a cooperative communication system operating in an amplify-and-forward (AF) mode with an imperfectly-known relay fading channel. It is assumed that a pilot symbol assisted modulation (PSAM) scheme with linear minimum mean square estimator (LMMSE) is used for the channel estimation. A simple and easy-to-evaluate asymptotical upper bound (AUB) of the symbol-error-rate (SER) is derived for uncoded AF cooperative systems with quadrature amplitude modulation (QAM) constellations. Based on the AUB, we propose a criterion for the choice of parameters in the PSAM scheme, i.e., the pilot spacing …
A three-factor optimisation strategy for micellar liquid chromatography
2000
An interpretive optimisation methodology for micellar liquid chromatography (MLC) is shown, taking into account pH, surfactant (sodium dodecyl sulphate) and organic modifier (propanol) concentration. Two objectives are considered: to develop a highly practical straightforward three-factor optimisation for practical MLC, and, in order to avoid unecessary experiments, to link two and three-factor optimisations through a step-wise construction of the experimental design at different pH levels. The whole pH range for an ODS column (from 3 to 7) is covered. The proposed strategy was thoroughly evaluated using the chromatographic data from 81 experimental mobile phases, applied to the separation …
Advantages of fitting contrast curves using logistic function: a technical note.
2013
Objective The aim of this article is to demonstrate how the contrast properties of an imaging system can be ideally fitted with the use of stripe patterns and the logistic function. Study Design Stripe patterns with defined amounts of line pairs (lp/mm) per mm (10-20 lp/mm) were recorded with the use of digital photostimulable storage phosphor. Scan data and normalized image data were analyzed with the use of ImageJ and MatLab to calculate different contrast curves. Results For original scan data, the goodness of fit was 0.0000019 (sum of squared error [SSE]). The R-square was 0.9998. For normalized data the goodness of fit was 0.0007 (SSE) and the R-square 0.998. An amount of 50% contrast …
Demultiplexing Visible and Near-Infrared Information in Single-Sensor Multispectral Imaging
2016
In this paper, we study a single-sensor imaging system that uses a multispectral filter array to spectrally sample the scene. Our system captures information in both visible and near-infrared bands of the electromagnetic spectrum. Due to manufacturing limitations, the visible filters in this system also transmit the NIR radiation. Similarly, visible light is transmitted by the NIR filter, leading to inaccurate mixed spectral measurements. We present an algorithm that resolves this issue by separating NIR and visible information. Our method achieves this goal by exploiting the correlation of multispectral images in both spatial and spectral domains. Simulation results show that the mean squa…
Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines
2007
This paper proposes a twofold approach for therapeutic drug monitoring (TDM) of kidney recipients using support vector machines (SVMs), for both predicting and detecting Cyclosporine A (CyA) blood concentrations. The final goal is to build useful, robust, and ultimately understandable models for individualizing the dosage of CyA. We compare SVMs with several neural network models, such as the multilayer perceptron (MLP), the Elman recurrent network, finite/infinite impulse response networks, and neural network ARMAX approaches. In addition, we present a profile-dependent SVM (PD-SVM), which incorporates a priori knowledge in both tasks. Models are compared numerically, statistically, and in…
TOPS-MODE approach for the prediction of blood-brain barrier permeation.
2004
The blood-brain barrier permeation has been investigated by using a topological substructural molecular design approach (TOPS-MODE). A linear regression model was developed to predict the in vivo blood-brain partitioning coefficient on a data set of 119 compounds, treated as the logarithm of the blood-brain concentration ratio. The final model explained the 70% of the variance and it was validated through the use of an external validation set (33 compounds of the 119, MAE = 0.33), a leave-one-out crossvalidation (q(2) = 0.65, S(press) = 0.43), fivefold full crossvalidation (removing 28 compounds in each cycle, MAE = 33, RMSE = 0.43) and the prediction of +/- values for an external test set …
Comparison of near and mid infrared spectroscopy as green analytical tools for the determination of total polar materials in fried oils
2017
Abstract Total polar materials (TPM) are used as an indicator of the quality in the frying oil because of high values may be harmful for human health. Spanish legislation establishes the maximum level of total polar materials for frying fats and oils for human consumption around 25% (w/w). Official methods to monitor oil quality are time consuming and use a lot of chemicals; therefore it is necessary a simple and quick analytical technique to evaluate fried oils. Transmittance near-infrared (NIR) and attenuated total reflection mid-infrared (ATR-MIR) spectroscopy measurements, combined with partial least squares (PLS) regression, offer alternatives to determine TPM in fried oils with relati…
Performance of TES method over urban areas at a high spatial resolution scale
2013
The Temperature and Emissivity Separation (TES) algorithm is used to retrieve the LSE and LST values from hyperspectral sensors. In this work we analyse the performance of this methodology over urban areas. Three different sources of error in the processing chain of the remote sensing imagery are detected: the algorithm itself, the atmospheric correction and the 3D structure of the urban scenes. The TITAN tool is used to model all the radiative components of the signal registered by a sensor. Results show that: first, the TES algorithm used reproduces the LSE (LST) of urban materials within an RMSE of 0.017 (0.9 K). Second, 20 % of uncertainty in the water vapour content of the total atmosp…