Subspace filtering approach based on orthogonal projection for better analysis of stressed speech under clean and noisy environments

This study explores a novel subspace projection-based approach for analysis of stressed speech. Studies have shown that stress influences the speech production system and it results in a large acoustic variation between the neutral and the stressed speech. This degrades the discrimination capability of an automatic speech recognition system trained on neutral speech when tested on stressed speech. An effort is made to reduce the acoustic mismatch by explicitly normalizing the stress-specific attributes. The stress-specific divergences are normalized by exploiting the subspace filtering technique. To accomplish this, an orthogonal projection based linear relationship between the speech and the stress information has been explored to filter an effective speech subspace, which consists of speech information. Speech subspace is constructed using K-means clustering followed by singular value decomposition method using neutral speech data. The speech and the stress information are separated by projecting the stressed speech orthogonally onto an effective speech subspace. Experimental results indicate that, the bases of an effective subspace comprises the first few eigenvectors corresponding to the highest eigenvalues. To further improve the system performance, both the neutral and the stressed speech are projected onto the lower dimensional subspace. The projections derived using the neutral speech employs heteroscedastic linear discriminant analysis in maximum likelihood linear transformations-based semi-tied adaptation framework. Consistent improvements are noted for the proposed technique in all the discussed cases.     

Two new control signal approaches for obtaining the MRAS-CDM and a real-time application

The coefficient diagram method (CDM) is one of the most effective control design methods. It creates control systems that are very stable and robust with responses without the overshoot and small settling time. Furthermore, all control parameters of the control systems are changed by varying some adjustment parameters in CDM depending on the demands. The model reference adaptive systems (MRAS) are the systems that follow and change the control parameters according to a given model reference system. There are several methods to combine the CDM with MRAS. One of these is to use the MRAS parameters as a gain of the CDM parameters. Another is to directly use the CDM parameters as the MRAS parameters. In the industrial applications, the system parameters can be changed frequently, but if the controller, by self-tuning, recalculates and develops its own parameters continuously, the system becomes more robust. Also, if the poles of the controlled systems approach the jw axis, the response of the closed-loop MRAS becomes more and more insufficient. In order to obtain better results, CDM is combined with a self-tuning model reference adaptive system. Systems controlled by a model reference adaptive controller give responses with small or without overshoot, have small settling times, and are more robust. Thus, in this paper, a hybrid combination of MRAS and CDM is developed and two different control structures of the control signal are investigated. The two methods are compared with MRAS and applied to real-time process control systems.     

Adaptive target recognition

Target recognition is a multilevel process requiring a sequence of algorithms at low, intermediate and high levels. Generally, such systems are open loop with no feedback between levels and assuring their performance at the given probability of correct identification (PCI) and probability of false alarm (Pf) is a key challenge in computer vision and pattern recognition research. In this paper, a robust closed-loop system for recognition of SAR images based on reinforcement learning is presented. The parameters in model-based SAR target recognition are learned. The method meets performance specifications by using PCI and Pf as feedback for the learning system. It has been experimentally validated by learning the parameters of the recognition system for SAR imagery, successfully recognizing articulated targets, targets of different configuration and targets at different depression angles.     

Cholesterol is critical to the integrity of neuronal porosome/fusion pore

Secretion is one of the most fundamental cellular processes. Porosomes have been demonstrated as the universal secretory machinery in cells. Earlier studies determine the presence of a number of proteins in porosomes, among them the N- and P/Q-type calcium channels, actin, syntaxin-1, synaptotagmin-1, vimentin, the N-ethylmaleimide-sensitive factor (NSF), the chloride channel CLC-3, and the alpha subunit of the heterotrimeric GTP-binding protein G(o). Studies demonstrate that t-SNAREs localize at the base of porosomes, and directly interact with calcium channels. In the present study, we demonstrate that Syntaxin-1 co-localizes with cholesterol in solubilized synaptosomal membrane preparations. Depletion of cholesterol, results in the dissociation of both Syntaxin-1 and N-type calcium channel from neuronal porosomes. Thus, cholesterol participates as an integral component of the neuronal porosome complex, and is required for its stability.     

Stochastic models for recognition of occluded targets

Recognition of occluded objects in synthetic aperture radar (SAR) images is a significant problem for automatic target recognition. Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise. In this paper, we present a hidden Markov modeling based approach for recognizing objects in SAR images. We identify the peculiar characteristics of SAR sensors and using these characteristics we develop feature based multiple models for a given SAR image of an object. The models exploiting the relative geometry of feature locations or the amplitude of SAR radar return are based on sequentialization of scattering centers extracted from SAR images. In order to improve performance we integrate these models synergistically using their probabilistic estimates for recognition of a particular target at a specific azimuth. Experimental results are presented using both synthetic and real SAR images.     

Fingerprint indexing based on novel features of minutiae triplets

We are concerned with accurate and efficient indexing of fingerprint images. We present a model-based approach, which efficiently retrieves correct hypotheses using novel features of triangles formed by the triplets of minutiae as the basic representation unit. The triangle features that we use are its angles, handedness, type, direction, and maximum side. Geometric constraints based on other characteristics of minutiae are used to eliminate false correspondences. Experimental results on live-scan fingerprint images of varying quality and NIST special database 4 (NIST-4) show that our indexing approach efficiently narrows down the number of candidate hypotheses in the presence of translation, rotation, scale, shear, occlusion, and clutter. We also perform scientific experiments to compare the performance of our approach with another prominent indexing approach and show that the performance of our approach is better for both the live scan database and the ink based database NIST-4.     

Comparative evaluation of strain controlled low cycle fatigue behaviour of solution annealed and prior cold worked 316L(N) stainless steel

The effect of 20% prior cold work on low cycle fatigue (LCF) behaviour of type 316L(N) stainless steel (SS) was studied at 873 K by conducting total axial strain controlled tests in air with strain amplitudes in the range ±0.25% to ±1.0%. The cyclic deformation behaviour of 20% prior cold worked (PCW) material was compared with the LCF response of solution annealed (SA) alloy tested under similar conditions. The cyclic stress response (CSR) of 316L(N) SS in the PCW condition was characterized by a short period of hardening followed by prolonged softening prior to failure, whereas SA material exhibited a significant hardening regime followed by stress saturation. Interrupted tests on PCW material were carried out at different stages of CSR in order to determine the underlying mechanisms as reflected in substructural changes. The fatigue life in the solution annealed condition was similar to that of the PCW material at higher strain amplitudes of testing (≥±0.5%) while at lower strain amplitudes, the PCW material exhibited longer life.     

Influence of Tool Rotational Speed and Post-Weld Heat Treatments on Friction Stir Welded Reduced Activation Ferritic-Martensitic Steel

The effects of tool rotational speed (200 and 700 rpm) on evolving microstructure during friction stir welding (FSW) of a reduced activation ferritic-martensitic steel (RAFMS) in the stir zone (SZ), thermo-mechanically affected zone (TMAZ), and heat-affected zone (HAZ) have been explored in detail. The influence of post-weld direct tempering (PWDT: 1033 K (760 °C)/ 90 minutes + air cooling) and post-weld normalizing and tempering (PWNT: 1253 K (980 °C)/30 minutes + air cooling + tempering 1033 K (760 °C)/90 minutes + air cooling) treatments on microstructure and mechanical properties has also been assessed. The base metal (BM) microstructure was tempered martensite comprising Cr-rich M₂₃C₆ on prior austenite grain and lath boundaries with intra-lath precipitation of V- and Ta-rich MC precipitates. The tool rotational speed exerted profound influence on evolving microstructure in SZ, TMAZ, and HAZ in the as-welded and post-weld heat-treated states. Very high proportion of prior austenitic grains and martensite lath boundaries in SZ and TMAZ in the as-welded state showed lack of strengthening precipitates, though very high hardness was recorded in SZ irrespective of the tool speed. Very fine-needle-like Fe₃C precipitates were found at both the rotational speeds in SZ. The Fe₃C was dissolved and fresh precipitation of strengthening precipitates occurred on both prior austenite grain and sub-grain boundaries in SZ during PWNT and PWDT. The post-weld direct tempering caused coarsening and coalescence of strengthening precipitates, in both matrix and grain boundary regions of TMAZ and HAZ, which led to inhomogeneous distribution of hardness across the weld joint. The PWNT heat treatment has shown fresh precipitation of M₂₃C₆ on lath and grain boundaries and very fine V-rich MC precipitates in the intragranular regions, which is very much similar to that prevailed in BM prior to FSW. Both the PWDT and PWNT treatments caused considerable reduction in the hardness of SZ. In the as-welded state, the 200 rpm joints have shown room temperature impact toughness close to that of BM, whereas 700 rpm joints exhibited very poor impact toughness. The best combination of microstructure and mechanical properties could be obtained by employing low rotational speed of 200 rpm followed by PWNT cycle. The type and size of various precipitates, grain size, and evolving dislocation substructure have been presented and comprehensively discussed.