Browsing by Author "Guesalaga, Andres"

Now showing 1 - 7 of 7
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    A 3D trajectory for undersampling k-space in MRSI applications
    (ELSEVIER SCIENCE INC, 2007) Uribe, Sergio; Guesalaga, Andres; Mir, Roberto; Guarini, Marcelo; Irarrazaval, Pablo
    Magnetic resonance spectroscopic imaging (MRSI) is a noninvasive technique for producing spatially localized spectra. MRSI presents the important challenge of reducing the scan time while maintaining the spatial resolution. The preferred approach for this is to use time-varying readout gradients to collect the spatial and chemical-shift information. Fast, three-dimensional (3D) spatial encoded methods also reduce the scan time. Despite the existence of several new and faster 3D encoded methods, or k-space trajectories, for magnetic resonance imaging (MRI), only stack of spirals and echo planar have been studied in 3D MRSI. A novel formulation for designing fast, 3D k-space trajectory applicable to 3D MRSI is presented. This approach is simple and consists of rays expanding from the origin of k-space into a revolving sphere, collecting spectral data of all 3D spatial k-space at different times in the same scan. This article describes this new method and presents some results of its application to 3D MRSI. This technique allows some degree of undersampling; hence, it is possible to reconstruct high-quality undersampled spectroscopic imaging in order to recognize different compounds in short scan times. Additionally, the method is tested in regular 3D MRI. This proposed method can also be used for dynamic undersampled imaging. (c) 2007 Elsevier Inc. All rights reserved.
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    A portable method to estimate wood basic density from increment cores using spectroscopic techniques
    (SAGE PUBLICATIONS LTD, 2010) Galleguillos Hart, Cristobal; Paulina Fernandez, M.; Guesalaga, Andres
    The aim of this paper is to report the use of spectroscopic techniques for the measurement of basic wood density in Eucalyptus nitens, using samples in a state similar to that found in the field; so the current design can later be extended to a portable instrument that could eventually estimate the wood characteristics of a standing tree. Model calibration was carried out using wet samples taken from eight-year-old trees. Each sample was scanned to acquire two types of spectra: Raman and near infrared (NIR). Several pre-processing techniques were applied to the spectra in order to obtain the best possible prediction models for wood basic density using partial least squares (PLS) regression. The model selection criteria were based on maximising the coefficients of determination R-c(2) and r(v)(2) and minimising the root mean square error (RMSE). The potential of NIR for this purpose was demonstrated; r(v)(2) up to 0.87 and RMSEP down to 8.6 kg m(-3) were obtained. Raman spectroscopy proved to be unfit for the application, yielding extremely low correlation values and models with low predictive capabilities.
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    Analysis of high-efficiency solar cells in mobile robot applications
    (ASME, 2007) Calderon, Francisco; Luders, Allan; Wettergreen, David; Teza, James; Guesalaga, Andres
    This technical brief analyzes the performance of triple-junction solar cells on a mobile robot. Although originally designed for satellite use, it is demonstrated that triple-junction cells are effective in terrestrial applications. This makes them particularly suitable for systems with limited size and mass but high-power requirements such as a mobile robot. A testing station was specially constructed to characterize triple-junction and conventional silicon cell performance in different environments and to compare their effectiveness. Additional field tests were carried out with an autonomous robot in order to check the ability to deliver sufficient power to varying loads. Results show that they surpass conventional technologies with efficiencies higher than 22%, so they can be considered as an alternative technology for power sources on board of terrestrial mobile robots.
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    Comparative study of wine tannin classification using Fourier transform mid-infrared spectrometry and sensory analysis
    (SOC APPLIED SPECTROSCOPY, 2007) Fernandez, Katherina; Labarca, Ximena; Bordeu, Edmundo; Guesalaga, Andres; Agosin, Eduardo
    Wine tannins are fundamental to the determination of wine quality. However, the chemical and sensorial analysis of these compounds is not straightforward and a simple and rapid technique is necessary. We analyzed the mid-infrared spectra of white, red, and model wines spiked with known amounts of skin or seed tannins, collected using Fourier transform mid-infrared (FT-MIR) transmission spectroscopy (400-4000 cm(-1)). The spectral data were classified according to their tannin source, skin or seed, and tannin concentration by means of discriminant analysis (DA) and soft independent modeling of class analogy (SIMCA) to obtain a probabilistic classification. Wines were also classified sensorially by a trained panel and compared with FT-MIR. SIMCA models gave the most accurate classification (over 97%) and prediction (over 60%) among the wine samples. The prediction was increased (over 73%) using the leave-one-out cross-validation technique. Sensory classification of the wines was less accurate than that obtained with FT-MIR and SINICA. Overall, these results show the potential of FT-MIR spectroscopy, in combination with adequate statistical tools, to discriminate wines with different tannin levels.
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    Comparison of vibration mitigation controllers for adaptive optics systems
    (OPTICAL SOC AMER, 2012) Guesalaga, Andres; Neichel, Benoit; Rigaut, Francois; Osborn, James; Guzman, Dani
    Vibrations are detrimental to the performance of modern adaptive optics (AO) systems. In this paper, we describe new methods tested to mitigate the vibrations encountered in some of the instruments of the Gemini South telescope. By implementing a spectral analysis of the slope measurements from several wavefront sensors and an imager, we can determine the frequencies and magnitude of these vibrations. We found a persistent vibration at 55 Hz with others occurring occasionally at 14 and 100 Hz. Two types of AO controllers were designed and implemented, Kalman and H-infinity, in the multiconjugate AO tip-tilt loop. The first results show a similar performance for these advanced controllers and a clear improvement in vibration rejection and overall performance over the classical integrator scheme. It is shown that the reduction in the standard deviation of the residual slopes (as measured by wavefront sensors) is highly dependent on turbulence, wind speed, and vibration conditions, ranging-in terms of slopes RMS value-from an almost negligible reduction for high speed wind to a factor of 5 for a combination of low wind and strong vibrations. (c) 2012 Optical Society of America
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    Modeling a MEMS deformable mirror using non-parametric estimation techniques
    (OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Myers, Richard; Guesalaga, Andres; Sanchez Lasheras, Fernando
    Using non-parametric estimation techniques, we have modeled an area of 126 actuators of a micro-electro-mechanical deformable mirror with 1024 actuators. These techniques produce models applicable to open-loop adaptive optics, where the turbulent wavefront is measured before it hits the deformable mirror. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. Our experiments have achieved positioning errors of 3.1% rms of the peak-to-peak wavefront excursion. (C) 2010 Optical Society of America
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    Using artificial neural networks for open-loop tomography
    (OPTICAL SOC AMER, 2012) Osborn, James; De Cos Juez, Francisco Javier; Guzman, Dani; Butterley, Timothy; Myers, Richard; Guesalaga, Andres; Laine, Jesus
    Modern adaptive optics (AO) systems for large telescopes require tomographic techniques to reconstruct the phase aberrations induced by the turbulent atmosphere along a line of sight to a target which is angularly separated from the guide sources that are used to sample the atmosphere. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. We compare our ANN method with a standard least squares type matrix multiplication method and to the learn and apply method developed for the CANARY MOAO instrument. The ANN is trained with a large range of possible turbulent layer positions and therefore does not require any input of the optical turbulence profile. It is therefore less susceptible to changing conditions than some existing methods. We also exploit the non-linear response of the ANN to make it more robust to noisy centroid measurements than other linear techniques. (C) 2012 Optical Society of America