A comparative evaluation of low-cycle fatigue behavior of type 316LN base metal, 316 weld metal,and 316LN/316 weld joint

A comparative evaluation of the low-cycle fatigue (LCF) behavior of type 316LN base metal, 316 weld metal, and 316LN/316 weld joints was carried out at 773 and 873 K. Total strain-controlled LCF tests were conducted at a constant strain rate of 3 × 10⁻³ s⁻¹ with strain amplitudes in the range ±0.20 to ±1.0 pct. Weld pads with single V and double V configuration were prepared by the shielded metal-arc welding (SMAW) process using 316 electrodes for weld-metal and weld-joint specimens. Optical microscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) of the untested and tested samples were carried out to elucidate the deformation and the fracture behavior. The cyclic stress response of the base metal shows a very rapid hardening to a maximum stress followed by a saturated stress response. Weld metal undergoes a relatively short initial hardening followed by a gradual softening regime. Weld joints exhibit an initial hardening and a subsequent softening regime at all strain amplitudes, except at low strain amplitudes where a saturation regime is noticed. The initial hardening observed in base metal has been attributed to interaction between dislocations and solute atoms/complexes and cyclic saturation to saturation in the number density of slip bands. From TEM, the cyclic softening in weld metal was ascribed to the annihilation of dislocations during LCF. Type 316LN base metal exhibits better fatigue resistance than weld metal at 773 K, whereas the reverse holds true at 873 K. The weld joint shows the lowest life at both temperatures. The better fatigue resistance of weld metal is related to the brittle transformed delta ferrite structure and the high density of dislocations at the interface, which inhibits the growth rate of cracks by deflecting the crack path. The lower fatigue endurance of the weld joint was ascribed to the shortening of the crack initiation phase caused by surface intergranular crack initiation and to the poor crack propagation resistance of the coarse-grained region in the heat-affected zone.     

Predictive models for multibiometric systems

Recognizing a subject given a set of biometrics is a fundamental pattern recognition problem. This paper builds novel statistical models for multibiometric systems using geometric and multinomial distributions. These models are generic as they are only based on the similarity scores produced by a recognition system. They predict the bounds on the range of indices within which a test subject is likely to be present in a sorted set of similarity scores. These bounds are then used in the multibiometric recognition system to predict a smaller subset of subjects from the database as probable candidates for a given test subject. Experimental results show that the proposed models enhance the recognition rate beyond the underlying matching algorithms for multiple face views, fingerprints, palm prints, irises and their combinations.     

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.