The Radical Versus Non-radical Reactive Intermediates in the Iron(III) Porphyrin Catalyzed Oxidation Reactions by Hydroperoxides, Hydrogen Peroxide and Iodosylarene

In the catalytic reaction of an iron(III) porphyrin with t-BuOOH, CumOOH, H₂O₂ and C₆F₅IO, cyclohexene was used as a probe substrate. The selective hydroxylation of cyclohexene by hydroperoxides proceeds through radical path and this has been utilized for successful dioxygen activation/autooxidation. For other oxidants epoxide was the major product and the reactions proceed through non-radical path.     

Micro-stress distribution within polycrystalline aggregate

Summary The three-dimensional Poisson-Voronoi model, which is topologically equivalent to the microstructure of real ceramics and metals, has been used to study the stress distribution within a simulated polycrystalline aggregate having 200 grains. Micro-stresses such as the maximum principal stress, maximum shear stress, first invariant of stress, and Von-Mises stress are found to vary systematically with the anisotropy of single crystal.     

Oxygen-enrichment of YBa2Cu3 YBa2Cu3O7-δ using the fluidization techniqueusing the fluidization technique

The oxygen-deficient phase of the highT _c superconductor, YBa₂Cu₃O₇, was oxygen-enriched using the fluidization technique to give good superconducting properties. The normal method of oxygen treatment at 900°C for 24 h and at 600°C for 24 h has been reduced to just one treatment at 600°C for 12 h by the fluidization technique to achieve almost the same strength of superconducting signal for the YBa₂Cu₃O₇ powder, which establishes the attractiveness of the latter route for the large-scale preparation of superconducting material. The particle sizes were in the range 0–90, 90–180 and 180–420 μm. The fluidized particles were crystalline with orthorhombic distortion.T _c ^onset , estimated using the a.c. magnetic susceptibility method, was 91·3 K. The volume fraction of superconducting material in the product was 83·7–85·3%, one of the highest values reported so far for YBa₂Cu₃O₇.     

Microarchitectures for Managing Chip Revenues under Process Variations

As transistor feature sizes continue to shrink intothe sub-90nm range and beyond, the effects of process variationson critical path delay and chip yields have amplified. A commonconcept to remedy the effects of variation is speed-binning, bywhich chips from a single batch are rated by a discrete range offrequencies and sold at different prices. In this paper, we discussstrategies to modify the number of chips in different bins andhence enhance the profits obtained from them. Particularly, wepropose a scheme that introduces a small Substitute Cacheassociated with each cache way to replicate the data elementsthat will be stored in the high latency lines. Assuming a fixedpricing model, this method increases the revenue by as much as13.8% without any impact on the performance of the chips.     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

The C-loss function for pattern classification

This paper presents a new loss function for neural network classification, inspired by the recently proposed similarity measure called Correntropy. We show that this function essentially behaves like the conventional square loss for samples that are well within the decision boundary and have small errors, and L₀ or counting norm for samples that are outliers or are difficult to classify. Depending on the value of the kernel size parameter, the proposed loss function moves smoothly from convex to non-convex and becomes a close approximation to the misclassification loss (ideal 0–1 loss). We show that the discriminant function obtained by optimizing the proposed loss function in the neighborhood of the ideal 0–1 loss function to train a neural network is immune to overfitting, more robust to outliers, and has consistent and better generalization performance as compared to other commonly used loss functions, even after prolonged training. The results also show that it is a close competitor to the SVM. Since the proposed method is compatible with simple gradient based online learning, it is a practical way of improving the performance of neural network classifiers.     

A method for automatic classification of gender based on text- independent handwriting

Handwriting recognition is used for the prediction of various demographic traits such as age, gender, nationality, etc. Out of all the applications gender prediction is mainly admired topic among researchers. The relation between gender and handwriting can be seen from the physical appearance of the handwriting. This research work predicts gender from handwriting using the landmarks of differences between the two genders. We use the shape or visual appearance of the handwriting for extracting features of the handwriting such as slanteness (direction), area (no of pixels occupied by text), perimeter (length of edges), etc. Classification is carried out using the Support Vector Machine (SVM) as a classifier which transforms the nonlinear problem into linear using its kernel trick, logistic regression, KNN and at the end to enhance the classification rates we use Majority Voting. The experimental results obtained on a dataset of 282 writers with 2 samples per writer shows that the proposed method attains appealing performance on writer detection and text-independent environment.

     

Estimation of impact forces during multi-point collisions involving small deformations

Multibody System Dynamics - Collision between hard objects causes abrupt changes in the velocities of the system, which are characterized by very large contact forces over very small time...     

HSIC-based affinity measure for learning on graphs

Pattern Analysis and Applications - The performance of graph-based learning techniques largely relies on the edges defined between the vertices of the graph. These edges that represent the affinity...