Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.

Reduction of truncation errors in planar, cylindrical and partial spherical near-field antenna measurements

A method to reduce truncation errors in near-field antenna measurements is presented. The method is based on the Gerchberg-Papoulis iterative algorithm used to extrapolate band-limited functions and it is able to extend the valid region of the calculated far-field pattern up to the whole forward hemisphere. The extension of the valid region is achieved by the iterative application of a transformation between two different domains. After each transformation, a filtering process that is based on known information at each domain is applied. The first domain is the spectral domain in which the plane wave spectrum (PWS) is reliable only within a known region. The second domain is the field distribution over the antenna under test (AUT) plane in which the desired field is assumed to be concentrated on the antenna aperture. The method can be applied to any scanning geometry, but in this paper, only the planar, cylindrical, and partial spherical near-field measurements are considered. Several simulation and measurement examples are presented to verify the effectiveness of the method.

Mutual Coupling Reduction Techniques in Electronic Steering Antennas in X Band

This work provides the development of an antenna for satellite communications onboard systems based on the recommendations ITU-R S.580-6 [1] and ITU-R S.465-5 [2]. The antenna consists of printed elements grouped in an array, working in a frequency band from 7.25 up to 8.4 GHz (15% of bandwidth). In this working band, transmission and reception are included simultaneously. The antenna reaches a gain about 31 dBi, has a radiation pattern with a beam width smaller than 10oand dual circular polarization. It has the capability to steer in elevation through a Butler matrix to 45

Methods for noise reduction in far-field patterns obtained from cylindrical near-field antenna measurements

Two different methods to reduce the noise power in the far-field pattern of an antenna as measured in cylindrical near-field (CNF) are proposed. Both methods are based on the same principle: the data recorded in the CNF measurement, assumed to be corrupted by white Gaussian and space-stationary noise, are transformed into a new domain where it is possible to filter out a portion of noise. Those filtered data are then used to calculate a far-field pattern with less noise power than that one obtained from the measured data without applying any filtering. Statistical analyses are carried out to deduce the expressions of the signal-to-noise ratio improvement achieved with each method. Although the idea of the two alternatives is the same, there are important differences between them. The first one applies a modal filtering, requires an oversampling and improves the far-field pattern in all directions. The second method employs a spatial filtering on the antenna plane, does not require oversampling and the far-field pattern is only improved in the forward hemisphere. Several examples are presented using both simulated and measured near-field data to verify the effectiveness of the methods.

Application of postprocessing techniques methods for noise reduction in cylindrical near field antenna measurements

Three different methods to reduce the noise power in the far-field pattern of an antenna when it is measured in a cylindrical near field system are presented and compared. The first one is based on a modal filtering while the other two are based on spatial filtering, either on an antenna plane or either on a cylinder of smaller radius. Simulated and measured results will be presented.

Reduction of front-metallization grid shading in concentrator cells through laser micro-grooved cover glass

Concentrator solar cell front-grid metallizations are designed so that the trade-off between series resistance and shading factor (SF) is optimized for a particular irradiance. High concentrator photovoltaics (CPV) typically requires a metallic electrode pattern that covers up to 10% of the cell surface. The shading effect produced by this front electrode results in a significant reduction in short-circuit current (I SC) and hence, in a significant efficiency loss. In this work we present a cover glass (originally meant to protect the cell surface) that is laser-grooved with a micrometric pattern that redirects the incident solar light towards interfinger regions and away from the metallic electrodes, where they would be wasted in terms of photovoltaic generation. Quantum efficiency (QE) and current (I)-voltage (V) characterization under concentration validate the proof-of-concept, showing great potential for CPV applications