A current-mode based Field-Programmable Analog Array for signal processing applications

This paper presents a new approach to develop Field Programmable Analog Arrays (FPAAs),(1) which avoids excessive number of programming elements in the signal path, thus enhancing the performance. The paper also introduces a novel FPAA architecture, devoid of the conventional switching and connection modules. The proposed FPAA is based on simple current mode sub-circuits. An uncompounded methodology has been employed for the programming of the Configurable Analog Cell (CAC). Current mode approach has enabled the operation of the FPAA presented here, over almost three decades of frequency range. We have demonstrated the feasibility of the FPAA by implementing some signal processing functions.

Planar waveguides based on nanocrystalline and Er3+ doped SnO2

Luminescent SnO2: x%mol Er3+ (x=0.1-2.0) thin films have been spin coated on borosilicate and silica substrates from water colloidal suspensions that could be prepared containing up to 40% in weight SnO2 nanocrystalline powders. High Resolution Transmission Electron Microscopy results show the well known SnO2 cassiterite structure and nanocrystallites around 10 nm in diameter, corroborating results from X-ray diffraction. Mono and multi layers have been prepared from the stable colloidal suspensions and films thickness was observed to increase linearly, up to 200 nm, with the colloidal suspensions nanoparticles amount. Excitation and emission spectra have been measured and Er3+ ions were found to be essentially incorporated into the cassiterite structure, substituting for Sn4+, for doping concentration lower than 0.05 mol%. Er3+ ions also appear segregated at the grains surface for higher doping concentration. The optical parameters (refractive index, thickness and propagating modes) of a waveguide sample were measured at 632.8 and 543.4 nm by the prism coupling technique. A monomodal waveguide was obtained with attenuation loss of 3.5 dB/cm along a 2.5 cm optical path.

Mechanistic insights into the reaction between VO2+ and propene based on a DFT study

Calculations based on density functional theory have been carried out to investigate the free energy profiles at singlet and triplet electronic states associated with the gas-phase ion/molecule reactions of VO2++ ((1)A(1)/(3)A) with propene. The complex potential energy Surfaces, including Six reaction pathways (three dehydrogenation and three oxygen transfer processes), have been explored and analyzed. Along dehydrogenation reactive channels, three final products can be obtained: V(OH)(2)(+) ((1)Sigma(+)/(3)Sigma(-)) and allene (path Dehl), being the most kinetically and thermodynamically favorable reaction pathway, V(OH)(2)(+) ((1)Sigma(+)/(3)Sigma(-)) and propyne (path Deh2),and VO2+ ((1)A(1)/(3)A) and H-2 plus allene (path Deh3). The oxyoenation processes can yield its final products Vo(+) ((1)Delta/(3)Sigma) and acetone (path Ox1), VO+ ((1)Delta/(3)Sigma 2) and propanaldehyde (path Ox2), and VO+ ((1)Delta/(3)Sigma) and H-2 and propenaldehyde (path Ox3). Both paths Deh1 and Deh2 are associated with two consecutive hydrogen transfer processes from carbon atoms of the propene fragment to vanadyl oxygen atoms, while in path Deh3 the second hydrogen migration takes place to the vanadiurn atorn followed by the formation ola hydrogen molecule. Both paths Ox1 and Ox2 comprise an intramolecular hydrogen transfer between the ethylenic moiety of the propene fragment, while two consecutive hydrogen transfer processes take place from the propene fragment to oxygen and vanadium atoms of the vanadyl moiety along path Ox3. Three crossing points between both electronic states take place along path Deh1 (CP-Deh1) and path Deh2 (CP-Deh2) and in the entrance channel of oxidation processes (CP-Ox). A comparison with previous works on related reactions VO2+ + C2H4, VO2 + C2H6, and VO2+ + C3H8 allows us to rationalize the different reactivity patterns.

Programmable PFC based hybrid multipulse power rectifier for ultra clean power application

A novel hybrid three-phase rectifier is proposed. It is capable to achieve high input power factor (PF) and low total harmonic input currents distortion (THDI). The proposed hybrid high power rectifier is composed by a standard three-phase six-pulse diode rectifier (Graetz bridge) with a parallel connection of single-phase Sepic rectifiers in each three-phase rectifier leg. Such topology results in a structure capable of programming the input current waveform and providing conditions for obtaining high input power factor and low harmonic current distortion. In order to validate the proposed hybrid rectifier, this work describes its principles, with detailed operation, simulation, experimental results, and discussions on power rating of the required Sepic converters as related to the desired total harmonic current distortion. It is demonstrated that only a fraction of the output power is processed through the Sepic converters, making the proposed solution economically viable for very high power installations, with fast investment payback. Moreover, retrofitting to existing installations is also feasible since the parallel path can be easily controlled by integration with the existing dc-link. A prototype has been implemented in the laboratory and it was fully demonstrated to both operate with excellent performance and be feasibly implemented in higher power applications.

Optimum-Path Forest Classifier for Large Scale Biometric Applications

This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. The existing Gauss-Laguerre Wavelet based coding scheme is used for iris encoding. The performance of the OPF and two other - Hamming and Bayesian - classifiers, is compared using small, medium, and large-scale databases. Such a comparison shows that the OPF has faster response for large-scale databases, thus performing better than the more accurate, but slower, classifiers.

A Fast Large Scale Iris Database Classification with Optimum-Path Forest Technique: A Case Study

Majority of biometric researchers focus on the accuracy of matching using biometrics databases, including iris databases, while the scalability and speed issues have been neglected. In the applications such as identification in airports and borders, it is critical for the identification system to have low-time response. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. This paper investigates several classifiers, which are widely used in iris recognition papers, and the response time along with accuracy. The existing Gauss-Laguerre Wavelet based iris coding scheme, which shows perfect discrimination with rotary Hamming distance classifier, is used for iris coding. The performance of classifiers is compared using small, medium, and large scale databases. Such comparison shows that OPF has faster response for large scale database, thus performing better than more accurate but slower Bayesian classifier.

A novel programmable PFC based hybrid rectifier for ultra clean power application

A novel hybrid high power rectifier capable to achieve unity power factor is proposed in this paper. Single-phase SEPIC rectifiers are associated in parallel with each leg of three-phase 6-pulse diode rectifier resulting in a programmable input current waveform structure. In this paper it is described the principles of operation of the proposed converter with detailed simulation and experimental results. For a total harmonic distortion of the input line current (THDI) less than 2% the rated power of the SEPIC rectifiers is 33%. Therefore, power rating of the SEPIC parallel converters is a fraction of the output power, on the range of 20% to 33% of the nominal output power, making the proposed solution economically viable for high power installations, with fast pay back of the investment. Moreover, retrofits to existing installations are also possible with this proposed topology, since the parallel path can be easily controlled by integration with the already existing de-link. Experimental results are presented for a 3 kW implemented prototype, in order to verify the developed analysis.

Programmable PFC based hybrid multipulse power rectifier for utility interface of power electronic converters

In this paper it is proposed a novel hybrid three-phase rectifier capable to achieve high input power factor (PF), and low total harmonic distortion in the input currents (THDI). The proposed hybrid high power rectifier is composed by a standard three-phase 6-pulses diode rectifier (Graetz bridge) with a parallel connection of single-phase Boost rectifiers in each three-phase rectifier leg. Such topology results in a structure capable of programming the input current waveform and providing conditions for obtaining high input power factor and low harmonic current distortion. In order to validate the proposed hybrid rectifier, this paper describes its principles of operation, with detailed experimental results and discussions on power rating of the required Boost converters as related to the desired total harmonic current distortion. It is demonstrated that only a fraction of the output power is processed through the Boost converters, making the proposed solution economically viable for very high power installations, with fast pay back of the investment. Moreover, retrofitting to existing installations is also feasible since the parallel path can be easily controlled by integration with the existing de-link. A prototype rated at 6 kW has been implemented in laboratory and fully demonstrated its operation, performance and feasibility to high power applications. © 2005 IEEE.

Path analysis and expected response in indirect selection for grain yield in soybean

This study aimed to determine the best auxiliary trait for indirect selection of soybean grain yield, through path analysis and in avoidance of the adverse effects of multicollinearity and expected response. Seventy-nine F5 soybean genotypes from the cross FT-Cometa x Bossier were used. The populations were distributed on the field was the families inserted with replicated controls. Primary and secondary traits of grain yield were evaluated in four phenotypically superior plants per family. The traits number of pods, height and number of nodes were considered as the most important, showing the best combination of direct effect and genotypic correlation. The number of pods achieved the highest expected gain through the estimation method based on the selection differential. On the other hand, plant height, by the method based on selection intensity, was not a good indicator of the most productive plants.

Infrared face recogniton by optimum-path forest

This paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.

Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation. © 2010 Springer-Verlag.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

Latin America on its path into the digital age: where are we?

Includes bibliography

Improving the accuracy of the optimum-path forest supervised classifier for large datasets

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the training set. Identification of outliers is based on a penalty computed for each sample in the training set from the corresponding number of imputable false positive and false negative classification of samples. This approach enhances the accuracy of OPF while still gaining in classification time, at the expense of a slight increase in training time. © 2010 Springer-Verlag.

Improving accuracy and speed of optimum-path forest classifier using combination of disjoint training subsets

The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind of classifier can be important for many applications. In this paper we report a fast method to combine OPF-based classifiers trained with disjoint training subsets. Given a fixed number of subsets, the algorithm chooses random samples, without replacement, from the original training set. Each subset accuracy is improved by a learning procedure. The final decision is given by majority vote. Experiments with simulated and real data sets showed that the proposed combining method is more efficient and effective than naive approach provided some conditions. It was also showed that OPF training step runs faster for a series of small subsets than for the whole training set. The combining scheme was also designed to support parallel or distributed processing, speeding up the procedure even more. © 2011 Springer-Verlag.