Analysis of the “Crack characteristic signal” using ageneralized scattering matrix representation

Electromagnetic properties of a system formed by an open-ended rectangular waveguide and a surface crack/slot in a metallic specimen are described in this paper. Scanning a crack on a metal surface changes the reflection coefficient of the incident dominant mode. A model as a function of relative crack location within the waveguide aperture (i.e., crack moving with respect to the waveguide aperture) is desired to describe and optimize practical crack detection applications. Hence, the change in the reflection coefficient for a generalized system encompassing empty, filled, and finite cracks located at an arbitrary position inside the waveguide aperture, is evaluated. A moment solution approach is employed, and a magnetic current density M is introduced over the common aperture formed by the waveguide and the crack. Subsequently, the junction formed by the waveguide and the cracked metallic surface is separated into two systems. A numerical solution employing the method of moments is obtained, and the reflection coefficient at the waveguide aperture is expressed in terms of the generalized scattering matrix. The convergence behavior is studied to determine an optimized set of basis functions and the optimal number of higher order modes for a fast and accurate solution. Numerical results presented in this paper include the evaluation of the field distribution over the waveguide aperture. Finally, the theoretical and measured crack characteristic signals are compared     

Kinetics of the chemical bath deposition of ZnSe films

Thin films of ZnSe were obtained by chemical bath deposition from a solution containing ZnCl₂, hydrazine (NH₂)₂H₂O, NH₃, and Na₂SSeO₃. The influence of the concentration of the components and of the temperature on the growth rate was studied. A hypothesis for a ZnSe formation process is proposed. The technological parameters for the preparation of thin dense films of sphalerite structure with a high transparency in the solar spectrum region are defined.     

A general formulation for admittance of an open-ended rectangular waveguide radiating into stratified dielectrics

A general approach is presented for calculating the aperture admittance of a rectangular waveguide radiating into layered dielectric media. The two specific geometries of stratified, lossy dielectric media that are addressed terminate into either an infinite half-space or a perfectly conducting surface. The geometries describe two prevalent categories of layered dielectric composites and coatings that often are encountered in practical microwave nondestructive evaluation applications. Solutions are found initially by constructing a complete set of field components and subsequently enforcing the continuity of power flow across the aperture interface of the waveguide. Final results are presented as a superposition of transverse electric and magnetic components of the aperture admittance. The solutions presented allow the systematic calculation of admittance in the presence of arbitrary multilayer media, which in turn may be related to experimentaly measurable quantities of interest. With the practical assumption of dominant mode incidence on the aperture, the final expressions may be implemented without intense computational power, which often is desirable in practice where inaccuracies due to random errors and instrumentation sensitivity render incorporation of more rigorous solutions inefficient. Numerically simulated data also are presented to verify and interpret the results.     

Thermocapillary stability during gravity flow of a liquid film

Thermocapillary rupture of a film under conditions of turbulent undulatory flow is associated with the buildup of wave motion on its surface. Here an approximate solution to the problem and criterial relations are obtained for determining the limits of stable film flow.Notation _min, kg/m·sec minimum irrigation intensity at which no film rupture occurs - ₁, kg/m· sec irrigation intensity at which the first dry spot appears - q, W/m² thermal flux density - _D, °C temperature at the rupture section - x, m space coordinate along the warm surface in the direction of flow - y, m coordinate in the direction normal to the warm surface - _o, m mean thickness of the film between large waves - _c, m thickness of the continuous layer - _cr, m critical film thickness - _o=/_o andl _o=l _o/_o dimensionless initial amplitude and length of a wave - , sec^–1 recurrence frequency of large waves - t_cr, sec time till thermocapillary rupture of a film - t_p, sec time of penetration of a thermal perturbation through the film thickness - u, m/sec velocity of thermocapillary flow of the liquid - , W/m·°C thermal conductivity - c_p, kJ/kg·°C specific heat - , kg/m linear density - , N·sec/m² dynamic viscosity - a, m²/sec thermal diffusivity - , N/m surface tension - , N/m² tangential stress at the film surface - L, m length of the warm pipe segment - L_o, m distance from the inlet to the section where wave motion at the film surface occurs - ¯w, m/sec mean velocity of downward flow of liquid in the film - , m mean thickness of the laminar layer - g, m²/sec free-fall acceleration due to gravity Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 39, No. 4, pp. 581–591, October, 1980.     

Text-Independent Speaker Verification for Real Fast-Varying Noisy Environments

Investigating Speaker Verification in real-world noisy environments, a novel feature extraction process suitable for suppression of time-varying noise is compared with a fine-tuned spectral subtraction method. The proposed feature extraction process is based on approximating the clean speech and the noise spectral magnitude with a mixture of Gaussian probability density functions (pdfs) by using the Expectation-Maximization algorithm (EM). Subsequently, the Bayesian inference framework is applied to the degraded spectral coefficients, and by employing Minimum Mean Square Error Estimation (MMSE), a closed form solution for the spectral magnitude estimation task is derived. The estimated spectral magnitude finally is incorporated into the Mel-Frequency Cepstral Coefficients (MFCCs) front-end of a baseline text-independent speaker verification system, based on Probabilistic Neural Networks, which participated successfully in the 2002 NIST (National Institute of Standards and Technology of USA) Speaker Recognition Evaluation. A comparative study of the proposed technique for real-world noise types demonstrates a significant performance gain compared to the baseline speech features and to the spectral subtraction enhancement method. Improvements of the absolute speaker verification performance with more than 27% for 0 dB signal-to-noise ratio (SNR), compared to the MFCCs, and with more than 13% for –5 dB SNR, compared to the spectral subtraction version, were obtained in the case of a passing-by aircraft scenario.     

Affective speech interface in serious games for supporting therapy of mental disorders

We describe a novel design, implementation and evaluation of a speech interface, as part of a platform for the development of serious games. The speech interface consists of the speech recognition component and the emotion recognition from speech component. The speech interface relies on a platform designed and implemented to support the development of serious games, which supports cognitive-based treatment of patients with mental disorders. The implementation of the speech interface is based on the Olympus/RavenClaw framework. This framework has been extended for the needs of the specific serious games and the respective application domain, by integrating new components, such as emotion recognition from speech. The evaluation of the speech interface utilized purposely collected domain-specific dataset. The speech recognition experiments show that emotional speech moderately affects the performance of the speech interface. Furthermore, the emotion detectors demonstrated satisfying performance for the emotion states of interest, Anger and Boredom, and contributed towards successful modelling of the patient’s emotion status. The performance achieved for speech recognition and for the detection of the emotional states of interest was satisfactory. Recent evaluation of the serious games showed that the patients started to show new coping styles with negative emotions in normal stress life situations.     

Speech segmentation using regression fusion of boundary predictions

In the present work we study the appropriateness of a number of linear and non-linear regression methods, employed on the task of speech segmentation, for combining multiple phonetic boundary predictions which are obtained through various segmentation engines. The proposed fusion schemes are independent of the implementation of the individual segmentation engines as well as from their number. In order to illustrate the practical significance of the proposed approach, we employ 112 speech segmentation engines based on hidden Markov models (HMMs), which differ in the setup of the HMMs and in the speech parameterization techniques they employ. Specifically we relied on sixteen different HMMs setups and on seven speech parameterization techniques, four of which are recent and their performance on the speech segmentation task have not been evaluated yet. In the evaluation experiments we contrast the performance of the proposed fusion schemes for phonetic boundary predictions against some recently reported methods. Throughout this comparison, on the established for the phonetic segmentation task TIMIT database, we demonstrate that the support vector regression scheme is capable of achieving more accurate predictions, when compared to other fusion schemes reported so far.     

Phone duration modeling: overview of techniques and performance optimization via feature selection in the context of emotional speech

Accurate modeling of prosody is prerequisite for the production of synthetic speech of high quality. Phone duration, as one of the key prosodic parameters, plays an important role for the generation of emotional synthetic speech with natural sounding. In the present work we offer an overview of various phone duration modeling techniques, and consequently evaluate ten models, based on decision trees, linear regression, lazy-learning algorithms and meta-learning algorithms, which over the past decades have been successfully used in various modeling tasks. Furthermore, we study the opportunity for performance optimization by applying two feature selection techniques, the RReliefF and the Correlation-based Feature Selection, on a large set of numerical and nominal linguistic features extracted from text, such as: phonetic, phonologic and morphosyntactic ones, which have been reported successful on the phone and syllable duration modeling task. We investigate the practical usefulness of these phone duration modeling techniques on a Modern Greek emotional speech database, which consists of five categories of emotional speech: anger, fear, joy, neutral, sadness. The experimental results demonstrated that feature selection significantly improves the accuracy of phone duration prediction regardless of the type of machine learning algorithm used for phone duration modeling. Specifically, in four out of the five categories of emotional speech, feature selection contributed to the improvement of the phone duration modeling, when compared to the case without feature selection. The M5p trees based phone duration model was observed to achieve the best phone duration prediction accuracy in terms of RMSE and MAE.