Search results for "Robustness"
showing 10 items of 512 documents
RPPanalyzer Toolbox: An improved R package for analysis of reverse phase protein array data
2014
Analysis of large-scale proteomic data sets requires specialized software tools, tailored toward the requirements of individual approaches. Here we introduce an extension of an open-source software solution for analyzing reverse phase protein array (RPPA) data. The R package RPPanalyzer was designed for data preprocessing followed by basic statistical analyses and proteomic data visualization. In this update, we merged relevant data preprocessing steps into a single user-friendly function and included a new method for background noise correction as well as new methods for noise estimation and averaging of replicates to transform data in such a way that they can be used as input for a new t…
Tests of Independence Based on Sign and Rank Covariances
2003
In this paper three different concepts of bivariate sign and rank, namely marginal sign and rank, spatial sign and rank and affine equivariant sign and rank, are considered. The aim is to see whether these different sign and rank covariances can be used to construct tests for the hypothesis of independence. In some cases (spatial sign, affine equivariant sign and rank) an additional assumption on the symmetry of marginal distribution is needed. Limiting distributions of test statistics under the null hypothesis as well as under interesting sequences of contiguous alternatives are derived. Asymptotic relative efficiencies with respect to the regular correlation test are calculated and compar…
On using novel “Anti-Bayesian” techniques for the classification of dynamical data streams
2017
The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, and it changes without any prior “warning”. Secondly, the manner in which it changes is also unknown. Thirdly, and more interestingly, the model operates with the assumption that the correct classes of previously-classified patterns become available at a juncture after their appearance. This paper pioneers the use of unreported novel schemes that can classify such dynamical data streams by invoking the recently-introduced “Anti-Bayesian” (AB) techniques. Contrary to the Bayesian paradigm, that compare…
Predictive modeling of aryl hydrocarbon receptor (AhR) agonism
2020
Abstract The aryl hydrocarbon receptor (AhR) plays a key role in the regulation of gene expression in metabolic machinery and detoxification systems. In the recent years, this receptor has attracted interest as a therapeutic target for immunological, oncogenic and inflammatory conditions. In the present report, in silico and in vitro approaches were combined to study the activation of the AhR. To this end, a large database of chemical compounds with known AhR agonistic activity was employed to build 5 classifiers based on the Adaboost (AdB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP) and Support Vector Machine (SVM) algorithms, respectively. The built classifier…
Experimental characterization of the RFID STENTag for passive vascular monitoring
2012
The possibility to monitor biological process in evolution and in particular the state of implanted devices such as vascular stent, has been recently proposed as one of the most challenging and fascinating application of the RFID passive technology. However, several issues are still in question and need to be analyzed in order to evaluate the real medical and sensing effectiveness of the proposed implantable radio sensor. The aim of this work is to experimentally evaluate the robustness of the RFID platform, its accuracy and its reproducibility as well as the effectiveness of the proposed sensing approach in term of human variability and pathology evolution.
Use of Reinforcement Learning in Two Real Applications
2008
In this paper, we present two sucessful applications of Reinforcement Learning (RL) in real life. First, the optimization of anemia management in patients undergoing Chronic Renal Failure is presented. The aim is to individualize the treatment (Erythropoietin dosages) in order to stabilize patients within a targeted range of Hemoglobin (Hb). Results show that the use of RL increases the ratio of patients within the desired range of Hb. Thus, patients' quality of life is increased, and additionally, Health Care System reduces its expenses in anemia management. Second, RL is applied to modify a marketing campaign in order to maximize long-term profits. RL obtains an individualized policy depe…
Shifting of wrapped phase maps in the frequency domain using a rational number
2016
The number of phase wraps in an image can be either reduced, or completely eliminated, by transforming the image into the frequency domain using a Fourier transform, and then shifting the spectrum towards the origin. After this, the spectrum is transformed back to the spatial domain using the inverse Fourier transform and finally the phase is extracted using the arctangent function. However, it is a common concern that the spectrum can be shifted only by an integer number, meaning that the phase wrap reduction is often not optimal. In this paper we propose an algorithm than enables the spectrum to be frequency shifted by a rational number. The principle of the proposed method is confirmed b…
Sensorless Control of Induction-Motor Drive Based on Robust Kalman Filter and Adaptive Speed Estimation
2014
This paper deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth-order extended Kalman filters (EKFs), rotor flux is estimated by means of a fourth-order descriptor-type robust KF, which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. E…
Self-calibration of a PTZ Camera Using New LMI Constraints
2013
In this paper, we propose a very reliable and flexible method for self-calibrating rotating and zooming cameras - generally referred to as PTZ (Pan-Tilt-Zoom) cameras. The proposed method employs a Linear Matrix Inequality (LMI) resolution approach and allows extra tunable constraints on the intrinsic parameters to be taken into account during the process of estimating these parameters. Furthermore, the considered constraints are simultaneously enforced in all views rather than in a single reference view. The results of our experiments show that the proposed approach allows for significant improvement in terms of accuracy and robustness when compared against state of the art methods.
An automatic filtering algorithm for SURF-based registration of remote sensing images
2017
International audience; The registration of remote sensing images has been often a necessary step for further analyses of images taken at different times, different viewing geometry or with different sensors. For this task there exists many approaches. This paper focuses on the feature-based category of image registration methods. Particularly, we propose an improvement of the SURF algorithm on the point matching step. Indeed, in order to achieve a correct registration, a good matching of feature point is required. However The presence of outliers lead to a fail in the registration. Therefore, in this paper, we introduce an efficient method devoted to the detection and removal of such outli…