A detailed investigation of classification methods for vowel speech imagery recognition

Accurate and fast decoding of speech imagery from electroencephalographic (EEG) data could serve as a basis for a new generation of brain computer interfaces (BCIs), more portable and easier to use. However, decoding of speech imagery from EEG is a hard problem due to many factors. In this paper we focus on the analysis of the classification step of speech imagery decoding for a three-class vowel speech imagery recognition problem. We empirically show that different classification subtasks may require different classifiers for accurately decoding and obtain a classification accuracy that improves the best results previously published. We further investigate the relationship between the classifiers and different sets of features selected by the common spatial patterns method. Our results indicate that further improvement on BCIs based on speech imagery could be achieved by carefully selecting an appropriate combination of classifiers for the subtasks involved.

Splitting the fast and slow motions in molecular dynamics simulations based on the change of cold potential well bottom

Abstract. The atomic motion is coupled by the fast and slow components due to the high frequency vibration of atoms and the low frequency deformation of atomic lattice, respectively. A two-step approximate method was presented to determine the atomic slow motion. The first step is based on the change of the location of the cold potential well bottom and the second step is based on the average of the appropriate slow velocities of the surrounding atoms. The simple tensions of one-dimensional atoms and two-dimensional atoms were performed with the full molecular dynamics simulations. The conjugate gradient method was employed to determine the corresponding location of cold potential well bottom. Results show that our two-step approximate method is appropriate to determine the atomic slow motion under the low strain rate loading. This splitting method may be helpful to develop more efficient molecular modeling methods and simulations pertinent to realistic loading conditions of materials.

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Propagation of the fast magnetosonic wave in a tokamak plasma

The propagation of the fast magnetosonic wave in a tokamak plasma has been investigated at low power, between 10 and 300 watts, as a prelude to future heating experiments.

The attention of the experiments has been focused on the understanding of the coupling between a loop antenna and a plasma-filled cavity. Special emphasis has been given to the measurement of the complex loading impedance of the plasma. The importance of this measurement is that once the complex loading impedance of the plasma is known, a matching network can be designed so that the r.f. generator impedance can be matched to one of the cavity modes, thus delivering maximum power to the plasma. For future heating experiments it will be essential to be able to match the generator impedance to a cavity mode in order to couple the r.f. energy efficiently to the plasma.

As a consequence of the complex impedance measurements, it was discovered that the designs of the transmitting antenna and the impedance matching network are both crucial. The losses in the antenna and the matching network must be kept below the plasma loading in order to be able to detect the complex plasma loading impedance. This is even more important in future heating experiments, because the fundamental basis for efficient heating before any other consideration is to deliver more energy into the plasma than is dissipated in the antenna system.

The characteristics of the magnetosonic cavity modes are confirmed by three different methods. First, the cavity modes are observed as voltage maxima at the output of a six-turn receiving probe. Second, they also appear as maxima in the input resistance of the transmitting antenna. Finally, when the real and imaginary parts of the measured complex input impedance of the antenna are plotted in the complex impedance plane, the resulting curves are approximately circles, indicating a resonance phenomenon.

The observed plasma loading resistances at the various cavity modes are as high as 3 to 4 times the basic antenna resistance (~ .4 Ω). The estimated cavity Q’s were between 400 and 700. This means that efficient energy coupling into the tokamak and low losses in the antenna system are possible.

Space-charge-limited current in fast neutron irradiated silicon

DC and transient measurements of space-charge-limited currents through alloyed and symmetrical n^+ν n^+ structures made of nominally 75 kΩcm ν-type silicon are studied before and after the introduction of defects by 14 MeV neutron radiation. In the transient measurements, the current response to a large turn-on voltage step is analyzed. Right after the voltage step is applied, the current transient reaches a value which we shall call "initial current" value. At longer times, the transient current decays from the initial current value if traps are present.

Before the irradiation, the initial current density-voltage characteristics J(V) agree quantitatively with the theory of trap-free space-charge-limited current in solids. We obtain for the electron mobility a temperature dependence which indicates that scattering due to impurities is weak. This is expected for the high purity silicon used. The drift velocity-field relationships for electrons at room temperature and 77°K, derived from the initial current density-voltage characteristics, are shown to fit the relationships obtained with other methods by other workers. The transient current response for t > 0 remains practically constant at the initial value, thus indicating negligible trapping.

Measurement of the initial (trap-free) current density-voltage characteristics after the irradiation indicates that the drift velocity-field relationship of electrons in silicon is affected by the radiation only at low temperature in the low field range. The effect is not sufficiently pronounced to be readily analyzed and no formal description of it is offered. In the transient response after irradiation for t > 0, the current decays from its initial value, thus revealing the presence of traps. To study these traps, in addition to transient measurements, the DC current characteristics were measured and shown to follow the theory of trap-dominated space-charge-limited current in solids. This theory was applied to a model consisting of two discrete levels in the forbidden band gap. Calculations and experiments agreed and the capture cross-sections of the trapping levels were obtained. This is the first experimental case known to us through which the flow of space-charge-limited current is so simply representable.

These results demonstrate the sensitivity of space-charge-limited current flow as a tool to detect traps and changes in the drift velocity-field relationship of carriers caused by radiation. They also establish that devices based on the mode of space-charge-limited current flow will be affected considerably by any type of radiation capable of introducing traps. This point has generally been overlooked so far, but is obviously quite significant.

Methods for melting temperature calculation

Melting temperature calculation has important applications in the theoretical study of phase diagrams and computational materials screenings. In this thesis, we present two new methods, i.e., the improved Widom's particle insertion method and the small-cell coexistence method, which we developed in order to capture melting temperatures both accurately and quickly.

We propose a scheme that drastically improves the efficiency of Widom's particle insertion method by efficiently sampling cavities while calculating the integrals providing the chemical potentials of a physical system. This idea enables us to calculate chemical potentials of liquids directly from first-principles without the help of any reference system, which is necessary in the commonly used thermodynamic integration method. As an example, we apply our scheme, combined with the density functional formalism, to the calculation of the chemical potential of liquid copper. The calculated chemical potential is further used to locate the melting temperature. The calculated results closely agree with experiments.

We propose the small-cell coexistence method based on the statistical analysis of small-size coexistence MD simulations. It eliminates the risk of a metastable superheated solid in the fast-heating method, while also significantly reducing the computer cost relative to the traditional large-scale coexistence method. Using empirical potentials, we validate the method and systematically study the finite-size effect on the calculated melting points. The method converges to the exact result in the limit of a large system size. An accuracy within 100 K in melting temperature is usually achieved when the simulation contains more than 100 atoms. DFT examples of Tantalum, high-pressure Sodium, and ionic material NaCl are shown to demonstrate the accuracy and flexibility of the method in its practical applications. The method serves as a promising approach for large-scale automated material screening in which the melting temperature is a design criterion.

We present in detail two examples of refractory materials. First, we demonstrate how key material properties that provide guidance in the design of refractory materials can be accurately determined via ab initio thermodynamic calculations in conjunction with experimental techniques based on synchrotron X-ray diffraction and thermal analysis under laser-heated aerodynamic levitation. The properties considered include melting point, heat of fusion, heat capacity, thermal expansion coefficients, thermal stability, and sublattice disordering, as illustrated in a motivating example of lanthanum zirconate (La₂Zr₂O₇). The close agreement with experiment in the known but structurally complex compound La₂Zr₂O₇ provides good indication that the computation methods described can be used within a computational screening framework to identify novel refractory materials. Second, we report an extensive investigation into the melting temperatures of the Hf-C and Hf-Ta-C systems using ab initio calculations. With melting points above 4000 K, hafnium carbide (HfC) and tantalum carbide (TaC) are among the most refractory binary compounds known to date. Their mixture, with a general formula Ta_xHf_1-xC_y, is known to have a melting point of 4215 K at the composition Ta₄HfC₅, which has long been considered as the highest melting temperature for any solid. Very few measurements of melting point in tantalum and hafnium carbides have been documented, because of the obvious experimental difficulties at extreme temperatures. The investigation lets us identify three major chemical factors that contribute to the high melting temperatures. Based on these three factors, we propose and explore a new class of materials, which, according to our ab initio calculations, may possess even higher melting temperatures than Ta-Hf-C. This example also demonstrates the feasibility of materials screening and discovery via ab initio calculations for the optimization of "higher-level" properties whose determination requires extensive sampling of atomic configuration space.

A new, fast response CO2 sensor

The inability of emissions reduction methods to meet upcoming legislation without an unacceptable increase in vehicle cost is a major problem of automobile manufacturer. This work aims to develop a cost-effective reduction of automobile emissions. A prototype CO2 sensor with 5 msec response time was built and bench tested, then used on an engine. The sensor design was based on standard emissions measurement technology using non-dispersive IR absorption. An improved sensor has now been completed with significant improvements in terms of signal to noise ratio and long-term stability. The improved sensor will be used to measure CO2 concentrations on three different engines. The results will then be used to validate engine and catalyst models and to propose control strategies aimed at reducing overall emissions. A brief description of the sensor itself was presented. Original is an abstract.

Computational fluid-structure interaction methods for simulation of inflatable aerodynamic decelerators

Inflatable aerodynamic decelerators have potential advantages for planetary re-entry in robotic and human exploration missions. It is theorized that volume-mass characteristics of these decelerators are superior to those of common supersonic/subsonic parachutes and after deployment they may suffer no instabilities at high Mach numbers. A high fidelity computational fluid-structure interaction model is employed to investigate the behavior of tension cone inflatable aeroshells at supersonic speeds up to Mach 2.0. The computational framework targets the large displacements regime encountered during the inflation of the decelerator using fast level set techniques to incorporate boundary conditions of the moving structure. The preliminary results indicate large but steady aeroshell displacement with rich dynamics, including buckling of the inflatable torus that maintains the decelerator open under normal operational conditions, owing to interactions with the turbulent wake. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

Fast L0-based sparse signal recovery

This paper develops an algorithm for finding sparse signals from limited observations of a linear system. We assume an adaptive Gaussian model for sparse signals. This model results in a least square problem with an iteratively reweighted L2 penalty that approximates the L0-norm. We propose a fast algorithm to solve the problem within a continuation framework. In our examples, we show that the correct sparsity map and sparsity level are gradually learnt during the iterations even when the number of observations is reduced, or when observation noise is present. In addition, with the help of sophisticated interscale signal models, the algorithm is able to recover signals to a better accuracy and with reduced number of observations than typical L1-norm and reweighted L1 norm methods. ©2010 IEEE.

TRANSIENT SCANNING ELECTRON BEAM ANNEALING METHODS USED TO STUDY DIFFUSION AND DEFECTS IN IMPLANTED SILICON.

Rapid thermal annealing of arsenic and boron difluoride implants, such as those used for source/drain regions in CMOS, has been carried out using a scanning electron beam annealer, as part of a study of transient diffusion effects. Three types of e-beam anneal have been performed, with peak temperatures in the range 900 -1200 degree C; the normal isothermal e-beam anneals, together with sub-second fast anneals and 'dual-pulse' anneals, in which the sample undergoes an isothermal pre-anneal followed by rapid heating to the required anneal temperature is less than 0. 5s. The diffusion occuring during these anneal cycles has been modelled using SPS-1D, an implant and diffusion modelling program developed by one of the authors. This has been modified to incorporate simulated temperature vs. time cycles for the anneals. Results are presented applying the usual equilibrium clustering model, a transient point-defect enhancement to the diffusivity proposed recently by Fair and a new dynamic clustering model for arsenic. Good agreement with SIMS measurements is obtained using the dynamic clustering model, without recourse to a transient defect model.

Decay heat in fast reactors with transuranic fuels

In this work, we performed an evaluation of decay heat power of advanced, fast spectrum, lead and molten salt-cooled reactors, with flexible conversion ratio. The decay heat power was calculated using the BGCore computer code, which explicitly tracks over 1700 isotopes in the fuel throughout its burnup and subsequent decay. In the first stage, the capability of the BGCore code to accurately predict the decay heat power was verified by performing a benchmark calculation for a typical UO2 fuel in a Pressurized Water Reactor environment against the (ANSI/ANS-5.1-2005, "Decay Heat Power in Light Water Reactors," American National Standard) standard. Very good agreement (within 5%) between the two methods was obtained. Once BGCore calculation capabilities were verified, we calculated decay power for fast reactors with different coolants and conversion ratios, for which no standard procedure is currently available. Notable differences were observed for the decay power of the advanced reactor as compared with the conventional UO2 LWR. The importance of the observed differences was demonstrated by performing a simulation of a Station Blackout transient with the RELAP5 computer code for a lead-cooled fast reactor. The simulation was performed twice: using the code-default ANS-79 decay heat curve and using the curve calculated specifically for the studied core by BGCore code. The differences in the decay heat power resulted in failure to meet maximum cladding temperature limit criteria by ∼100 °C in the latter case, while in the transient simulation with the ANS-79 decay heat curve, all safety limits were satisfied. The results of this study show that the design of new reactor safety systems must be based on decay power curves specific to each individual case in order to assure the desired performance of these systems. © 2009 Elsevier B.V. All rights reserved.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.

Splitting the Fast and Slow Motions in Molecular Dynamics Simulations Based on the Change of Cold Potential Well Bottom

The atomic motion is coupled by the fast and slow components due to the high frequency vibration of atoms and the low frequency deformation of atomic lattice, respectively. A two-step approximate method was presented to determine the atomic slow motion. The first step is based on the change of the location of the cold potential well bottom and the second step is based on the average of the appropriate slow velocities of the surrounding atoms. The simple tensions of one-dimensional atoms and two-dimensional atoms were performed with the full molecular dynamics simulations. The conjugate gradient method was employed to determine the corresponding location of cold potential well bottom. Results show that our two-step approximate method is appropriate to determine the atomic slow motion under the low strain rate loading. This splitting method may be helpful to develop more efficient molecular modeling methods and simulations pertinent to realistic loading conditions of materials.

Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

Ultrasonic relaxation kinetics on fast deuteron transfer reaction

Propylamine has been selected to investigate the isotope effect of a fast deuteron transfer reaction by ultrasonic relaxation method. Ultrasonic absorption coefficients of propylamine in heavy water (D2O) at 25 degrees C in the concentration range from 0.0107 to 0.6300 mol dm(-3) have been measured by pulse and resonance methods over the frequency range from 0.8 to 220 MHz. A Debye-type single relaxation absorption has been observed in the solution. From the dependence of the ultrasonic relaxation parameters on the concentration and solution pH, the source of the observed relaxation has been attributed to a perturbation of the chemical equilibrium associated with the deuteron transfer reaction. The rate and equilibrium constants have been determined by the measurement of the deuteroxyl ion concentration dependence of the relaxation frequency. Also the standard volume change of the reaction has been determined from the concentration dependence of the maximum absorption per wavelength and the adiabatic compressibility has been calculated from the density and the sound velocity in the solution. These results have then been compared with those obtained for propylamine in light water (H2O). The forward rate constant is greater and the reverse rate constant is smaller in DO than in H2O. The standard volume change for deuteron transfer is greater than that for proton transfer reaction, and the adiabatic compressibility shows a similar trend. These data support an argument that there exists a stronger hydrogen bond in D2O than in H2O. The difference of the stability in the intermediate states, R-ND3+... OD- and R-NH3+... OH-, has also been considered from the results of the isotope effects.