Relative stabilities of condensed face sharing mono- and di-carboranes: CB20H18 and C2B19H18+

The relative energies of triangular face sharing condensed macro polyhedral carboranes: CB20H18 and C2B19H18+ derived from mono- and di-substitution of carbons in (4) B21H18- is calculated at B3LYP/6-31G* level. The relative energies, H center dot center dot center dot H non-bonding distances, NICS values, topological charge analysis and orbital overlap compatibility connotes the face sharing condensed macro polyhedral mono-carboranes, 8 (4-CB20H18) to be the lowest energy isomer. The di-carba- derivative, (36) 4,4'a-C2B19H18+ with carbons substituted in a different B-12 cage in (4) B21H18- in anti-fashion is the most stable isomer among 28 possibilities. This structure has less non-bonding H center dot center dot center dot H interaction and is in agreement with orbital-overlap compatibility, and these two have the pivotal role in deciding the stability of these clusters. An estimate of the inherent stability of these carboranes is made using near-isodesmic equations which show that CB20H18 (8) is in the realm of the possible. (C) 2015 Elsevier B.V. All rights reserved.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.

SMO: An Integrated Approach to Intra-array and Inter-array Storage Optimization

The polyhedral model provides an expressive intermediate representation that is convenient for the analysis and subsequent transformation of affine loop nests. Several heuristics exist for achieving complex program transformations in this model. However, there is also considerable scope to utilize this model to tackle the problem of automatic memory footprint optimization. In this paper, we present a new automatic storage optimization technique which can be used to achieve both intra-array as well as inter-array storage reuse with a pre-determined schedule for the computation. Our approach works by finding statement-wise storage partitioning hyper planes that partition a unified global array space so that values with overlapping live ranges are not mapped to the same partition. Our heuristic is driven by a fourfold objective function which not only minimizes the dimensionality and storage requirements of arrays required for each high-level statement, but also maximizes inter statement storage reuse. The storage mappings obtained using our heuristic can be asymptotically better than those obtained by any existing technique. We implement our technique and demonstrate its practical impact by evaluating its effectiveness on several benchmarks chosen from the domains of image processing, stencil computations, and high-performance computing.