Approximate axial symmetries from continuous time quantum walks

The analysis of complex networks is usually based on key properties such as small-worldness and vertex degree distribution. The presence of symmetric motifs on the other hand has been related to redundancy and thus robustness of the networks. In this paper we propose a method for detecting approximate axial symmetries in networks. For each pair of nodes, we define a continuous-time quantum walk which is evolved through time. By measuring the probability that the quantum walker to visits each node of the network in this time frame, we are able to determine whether the two vertices are symmetrical with respect to any axis of the graph. Moreover, we show that we are able to successfully detect approximate axial symmetries too. We show the efficacy of our approach by analysing both synthetic and real-world data. © 2012 Springer-Verlag Berlin Heidelberg.

Information theoretic prototype selection for unattributed graphs

In this paper we propose a prototype size selection method for a set of sample graphs. Our first contribution is to show how approximate set coding can be extended from the vector to graph domain. With this framework to hand we show how prototype selection can be posed as optimizing the mutual information between two partitioned sets of sample graphs. We show how the resulting method can be used for prototype graph size selection. In our experiments, we apply our method to a real-world dataset and investigate its performance on prototype size selection tasks. © 2012 Springer-Verlag Berlin Heidelberg.

Supervised learning of graph structure

Graph-based representations have been used with considerable success in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the methodology available for learning structural representations from sets of training examples is relatively limited. In this paper we take a simple yet effective Bayesian approach to attributed graph learning. We present a naïve node-observation model, where we make the important assumption that the observation of each node and each edge is independent of the others, then we propose an EM-like approach to learn a mixture of these models and a Minimum Message Length criterion for components selection. Moreover, in order to avoid the bias that could arise with a single estimation of the node correspondences, we decide to estimate the sampling probability over all the possible matches. Finally we show the utility of the proposed approach on popular computer vision tasks such as 2D and 3D shape recognition. © 2011 Springer-Verlag.

Safer and more efficient terminals: the role of movement, behaviour and evacuation simulation in design

Abstract not available

Safer by design

Abstract not available

Quantum kernels for unattributed graphs using discrete-time quantum walks

In this paper, we develop a new family of graph kernels where the graph structure is probed by means of a discrete-time quantum walk. Given a pair of graphs, we let a quantum walk evolve on each graph and compute a density matrix with each walk. With the density matrices for the pair of graphs to hand, the kernel between the graphs is defined as the negative exponential of the quantum Jensen–Shannon divergence between their density matrices. In order to cope with large graph structures, we propose to construct a sparser version of the original graphs using the simplification method introduced in Qiu and Hancock (2007). To this end, we compute the minimum spanning tree over the commute time matrix of a graph. This spanning tree representation minimizes the number of edges of the original graph while preserving most of its structural information. The kernel between two graphs is then computed on their respective minimum spanning trees. We evaluate the performance of the proposed kernels on several standard graph datasets and we demonstrate their effectiveness and efficiency.

Sir Edwin Landseer, R. A.,

"Some works in private collections mentioned in this book": p. 70-71.

N. m. r. and infrared spectroscopic studies of hydrogen bonding in hindered alcohols. An instance of a true hydrogen bonded dimer in an alcohol

Hydrogen bonding in the highly hindered alcohol 2,4-dimethyl-3-ethyl-3-pentanol has been studied by proton n.m.r. and infrared spectroscopy. This alcohol associates to form a dimer but no higher hydrogen bonded species; hence the monomer–dimer equilibrium can be studied without interference from competing processes. Spectral and thermodynamic properties for the hydrogen bonding are reported.

Análisis de la Corporación J.R Lindley S.A. : caso Inca Kola

Inca Kola es una bebida gasificada del Perú y elaborada por la Corporación Lindley, que ha conservado el liderazgo en el mercado peruano desde su creación, a pesar del ingreso de bebidas internacionales y de bebidas que tienen un menor precio. Desde su creación, la corporación se enfocó en vincular la bebida con la identidad peruana; estrategia que ha sido efectiva y se pueden comprobar por el liderazgo que presenta en el mercado. En los noventa, la corporación Lindley tuvo que enfrentar un escenario turbulento debido al ingreso de Coca Cola y Pepsi, sin embargo, estas no desplazaron a Inca Kola a pesar del poder de marketing que cuentan. En este sentido, el objetivo del presente trabajo es estudiar cómo la Corporación Lindley mantiene su bebida "Inca Kola" como una especialidad en el Perú, por medio de la metodología de las tres vías propuesto por Joskow. Los resultados indican que existen leyes que salvaguardan la marca Inca Kola, tanto en el ámbito nacional como internacional y que gracias a la alianza entre la corporación Lindley y Coca Cola Company, se puso fin a la competencia, aumentando las barreras de ingreso en el sector de bebidas, y como resultado la corporación pudo enfocar sus esfuerzos en seguir vinculando la bebida con la cultura peruana y modernizar sus diferentes plantas de envasado. Las conclusiones más resaltantes indican que la corporación Lindley se apalancó en el Entorno Institucional informal para captar las preferencia de los peruanos, en otras palabras vinculó una bebida aprovechando las características que tienen los consumidores peruano, los cuales tienen lazos muy fuertes con productos que asocian con la identidad nacional. En la vía de la Moderna Organización Industrial se observa que la bebida sigue liderando las ventas con un precio mayor que los competidores, indicando que la corporación tiene una estrategia de diferenciación. Respecto a la vía de la estructura de gobernaza, la corporación pudo alinear sus transacciones con los proveedores de insumos y distribuidores para garantizar la calidad, precio y a asegurando su activo especifico más importante, la marca "Inca Kola". Estas características son propias de las Especialidades.