Search results for "Machine"
showing 10 items of 2592 documents
A family of kernel anomaly change detectors
2014
This paper introduces the nonlinear extension of the anomaly change detection algorithms in [1] based on the theory of reproducing kernels. The presented methods generalize their linear counterparts, under both the Gaussian and elliptically-contoured assumptions, and produce both improved detection accuracies and reduced false alarm rates. We study the Gaussianity of the data in Hilbert spaces with kernel dependence estimates, provide low-rank kernel versions to cope with the high computational cost of the methods, and give prescriptions about the selection of the kernel functions and their parameters. We illustrate the performance of the introduced kernel methods in both pervasive and anom…
Content based segmentation of patterned wafers
2004
We extend our previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer in- spection is based on the comparison of the same area on two neigh- boring dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, seg- mentation is required to create a mask and apply an optimal thresh- old in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. We show a method to anticipate these variation…
Integration of multiple range and intensity image pairs using a volumetric method to create textured three-dimensional models
2001
We present a volumetric approach to three-dimensional (3D) object modeling that differs from previous techniques in that both object texture and geometry are considered in the reconstruc- tion process. The motivation for the research is the simulation of a thermal tire inspection station. Integrating 3D geometry information with two-dimensional thermal images permits the thermal informa- tion to be displayed as a texture map on the tire structure, enhanc- ing analysis capabilities. Additionally, constructing the tire geometry during the inspection process allows the tire to be examined for structural defects that might be missed if the thermal data were textured onto a predefined model. Exp…
Validation of a Reinforcement Learning Policy for Dosage Optimization of Erythropoietin
2007
This paper deals with the validation of a Reinforcement Learning (RL) policy for dosage optimization of Erythropoietin (EPO). This policy was obtained using data from patients in a haemodialysis program during the year 2005. The goal of this policy was to maintain patients' Haemoglobin (Hb) level between 11.5 g/dl and 12.5 g/dl. An individual management was needed, as each patient usually presents a different response to the treatment. RL provides an attractive and satisfactory solution, showing that a policy based on RL would be much more successful in achieving the goal of maintaining patients within the desired target of Hb than the policy followed by the hospital so far. In this work, t…
Restricted Neighborhood Search Clustering Revisited: An Evolutionary Computation Perspective
2013
Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of groups of proteins strictly related, can be useful to predict protein functions. Clustering techniques have been widely employed to detect significative biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions in…
Sensorless control of permanent magnet synchronous motors for wide speed range applications
2006
This paper deals with sensorless control of Interior Permanent Magnet Synchronous Motors (IPMS) based on the estimation of speed and rotor angular position. The above estimate is based on the injection of high frequency stator currents able to generate a signal similar to that generated by a resolver connected to the axis of the motor. A new digital algorithm has been designed to demodulate the above signal whose implementation can be carried out on the same DSP that processes the control algorithm. In this paper a new scheme of speed and angular position estimator is proposed and justified on the theoretic point of view. The experimental results here shown validate the effectiveness of the…
Hidden Markov Random Field model and BFGS algorithm for Brain Image Segmentation
2016
Brain MR images segmentation has attracted a particular focus in medical imaging. The automatic image analysis and interpretation became a necessity. Segmentation is one of the key operations to provide a crucial decision support to physicians. Its goal is to simplify the representation of an image into items meaningful and easier to analyze. Hidden Markov Random Fields (HMRF) provide an elegant way to model the segmentation problem. This model leads to the minimization problem of a function. BFGS (Broyden-Fletcher-Goldfarb-Shanno algorithm) is one of the most powerful methods to solve unconstrained optimization problem. This paper presents how we combine HMRF and BFGS to achieve a good seg…
Optimization of the straightness measurements on rough surfaces by Monte Carlo simulation
2013
Summary The straightness error of a coordinate measuring machine (CMM) is determined by measuring a rule standard. Thanks to a reversal technique, the straightness uncertainty of the CMM is theoretically dissociated from the straightness uncertainty of the rule. However, stochastic variations of the whole measurement system involve uncertainties of the CMM straightness error. To quantify these uncertainties, different sources of stochastic variations are listed with their associated probability density functions. Then Monte Carlo methods are performed first to quantify error and secondly to optimize measurement protocol. It is shown that a 5-measurement distance from 0.1 mm to each measurem…
Intra-cardiac Signatures of Atrial Arrhythmias Identified by Machine Learning and Traditional Features
2021
Intracardiac devices separate atrial arrhythmias (AA) from sinus rhythm (SR) using electrogram (EGM) features such as rate, that are imperfect. We hypothesized that machine learning could improve this classification.
IMPROVING CNC MACHINE TOOLS ACCURACY USING MODELING AND COMPUTER SIMULATION TECHNIQUES
2007
Abstract The position was one of the first parameters that required the introduction of automatic control process. One of the most representative applications is represented by the feed drives of the computer numerically controlled (CNC) machine tools. Today, it is possible to use computer simulation techniques in analysing and synthesising position control systems. Thus, the behaviour of the CNC machine tools feed drives can be treated much more realistically. It is the purpose of this paper to show how simulation can be used to accurately represent, predict and improve the performance of a CNC machine tool feed servo drives.