Browse results

Kah Chun Lau and Ravindra Pandey

The rich chemistry of boron compounds are often found dominated by its structural dimensionality and chemical bonding from which some of the qualitative features of boron clusters can easily be extracted. In this article, we review such features to discuss structural properties of Bn clusters. In both small-cluster regime of n ≤ 20 and largecluster regime of n ≥ 20, the preferred topological structures are the result of the interplay between bonding factors related to the delocalized π bonds and the inter-icosahedral and intra-icosahedral bonds. The bulk fragments of boron are also expected to become a competitive isomeric configuration with the increase in the cluster-size, in contrast to 3D spherical cages observed in the large carbon clusters

Sandeep Nigam, Chiranjib Majumder and S.K. Kulshreshtha

Ab initio calculations were performed to asses the aromatic behavior of mixed tetramer neutral cluster (Be2N2, Be2P2, Mg2N2, Mg2P2). Harmonic vibrational analysis has been performed to ensure the stability of the optimized geometries. The analysis of structure, vibrational frequencies, and molecular orbitals indicates that all these tetramer favor planar atomic configuration as the lowest energy structure and exhibit the characteristics of aromaticity (planarity and two π- electrons in the delocalized molecular orbital). Other than this, the aromatic character of these clusters has been verified based on established criteria of aromaticity such as chemical (extra stability), and magnetic criteria i.e. by calculating Nuclear Independent Chemical Shift (NICS) at the ring centers. The extra electronic stability of these clusters towards donating or accepting of electrons is also reflected in the calculated large ionization potential and low electron affinity

Advanced Robotics

The International Journal of the Robotics Society of Japan. Published jointly with the Robotics Society of Japan

This journal has been acquired by Taylor & Francis. For more information, please click here.

W. Kuechler, V. K. Vaishnavi and S. Petter

The manner in which the research and development efforts of different groups, each focused on a different aspect of a single complex computing artifact (e.g., database), evolve and mutually support the development of the artifact as a whole has fascinated researchers, economists, and philosophers of science alike. In this paper we propose the Aggregate General Design Cycle (AGDC), an aggregated form of the General Design Cycle (GDC), as a predictive model of the evolution over time of a computing research community of interest. We begin by demonstrating that the GDC accurately depicts the progress of any individual research effort. We then propose that multiple research and development efforts on a theme, even when conducted by nominally distinct groups (i.e. computer science cf. information systems; academics cf. practitioners) are predicted by the AGDC. We provide support for the proposal through a longitudinal meta-bibliographic study of database research.

E. Francomano, C. Lodato, S. Lopes and A. Tortorici

A fundamental problem in the processing of image sequences is the computation of the velocity field of the apparent motion of brightness patterns usually referred to optical flow. In this paper a novel optical flow estimator based on a bivariate quasi-interpolant operator is presented. Namely, a non linear minimizing technique has been employed to compute the velocity vectors by modeling the flow field with a 2D quasi-interpolant operator based on centered cardinal B-spline functions. In this way an efficient computational scheme for optical flow estimate is provided. In addition the large solving linear systems involved in the process are sparse. Experiments on several image sequences have been carried out in order to investigate the performance of the optical flow estimator.

M. Breuß

We discuss some important issues arising when approximating numerically stabilised inverse diffusion processes. We prove rigorously the necessity of a minmod-type stabilisation. Furthermore, we give rigorously verified assertions concerning the occurence of undesirable staircasing aka terracing artefacts. The theoretical results are supplemented by numerical tests.

Kaasschieter, Landman and Pel

F. Rodenas, P. Mayo, D. Ginestar and G. Verdú

One method successfully employed to denoise digital images is the diffusive iterative filtering. An important point of this technique is the estimation of the stopping time of the diffusion process. In this paper, we propose a stopping time criterion based on the evolution of the negentropy of the ’noise signal’ with the diffusion parameter. The nonlinear diffusive filter implemented with this stopping criterion is evaluated by using several noisy test images with different statistics. Assuming that images are corrupted by additive Gaussian noise, a statistical measure of the Gaussianity can be used to estimate the amount of noise removed from noisy images. In particular, the differential entropy function or, equivalently, the negentropy are robust measures of the Gaussianity. Because of computational complexity of the negentropy function, it is estimated by using an approximation of the negentropy introduced by Hyv¨arinen in the context of independent component analysis.

Jesús Rodríguez-López, Salvador Romaguera and Oscar Valero

The theory of nonsymmetric topology has been successfully applied to the theory of complexity of algorithms. In 1995, Schellekens introduced a quasi-pseudo-metric space in order to obtain a mathematical model for the study of complexity of algorithms. Here, we provide a mathematical context to study the asymptotic complexity of algorithms.