GEVA: geometric variability-based approaches for identifying patterns in data

This paper, arising from population studies, develops clustering algorithms for identifying patterns in data. Based on the concept of geometric variability, we have developed one polythetic-divisive and three agglomerative algorithms. The effectiveness of these procedures is shown by relating them to classical clustering algorithms. They are very general since they do not impose constraints on the type of data, so they are applicable to general (economics, ecological, genetics...) studies. Our major contributions include a rigorous formulation for novel clustering algorithms, and the discovery of new relationship between geometric variability and clustering. Finally, these novel procedures give a theoretical frame with an intuitive interpretation to some classical clustering methods to be applied with any type of data, including mixed data. These approaches are illustrated with real data on Drosophila chromosomal inversions.     

Inverse central ordering for the Newton interpolation formula

Numerical Algorithms - An inverse central ordering of the nodes is proposed for the Newton interpolation formula. This ordering may improve the stability for certain distributions of nodes. For...     

Inequalities for Volumes of Simplices in Terms of Their Faces

By generalizing some well-known results, we first obtain an inequality involving the volume and product of s-contents of s-faces of an n-simplex. Using this we generalize two inequalities maximizing the volume of one or two simplices in terms of their edge lengths.     

Quantum Nonlocality of Photon Pairs in Interference in a Mach-Zehnder Interferometer

Nonlocal character of entangled photon pairs generated in spontaneous parametric downconversion is demonstrated. One photon from a pair propagates through a Mach-Zehnder interferometer and is detected in coincidence-count measurement with its twin. Width of the coincidence-count interference pattern (measured for various values of path difference in the Mach-Zehnder interferometer) depends on spectral width of the twin as a result of entanglement of photons in a pair. The experimental setup is analyzed for a Gaussian spectral filter and a Fabry-Perot resonator. It is shown that nonlocal interference is much stronger for cw pumping in comparison with femtosecond pulsed pumping for values of parameters commonly used in spontaneous parametric downconversion experiments.     

Locally graded minimal non CC-groups arep-groups

The research of the two last authors has been supported by DGICYT (Spain) PS88-0085.     

FeSiB Amorphous Alloy Prepared by Mechano-Synthesis

In this work we show that mechano-synthesis is a good method to prepare the FeSiB amorphous alloy starting from Fe, Si, B pure elements with relative atomic composition of 75, 15 and 10%, respectively. We have used a high-energy ball-milling system keeping the material under an Ar atmosphere. The evolution of the microstructure inside the grains is followed by X-ray diffraction and Mössbauer spectroscopy at room temperature. The dependence of crystalline size, lattice parameter and hyperfine parameters on milling time is discussed. Our results show that the milled samples obtained after 10 h of milling contained a bcc structure in the amorphous matrix. After 19 h of milling the sample became fully amorphous.     

System Dynamics Modelling for Residential Energy Efficiency Analysis and Management

A System Dynamics model to simulate the substitution of installed household appliances by more efficient ones is presented. The model allows the construction of scenarios and also the analyses of several other issues such as: alternatives for technology penetration, electricity consumption growth, gas consumption growth and effects of pricing policies on various energy demands. The proposed methodology has been applied to assist the decision process in relation to gas penetration policies. The model also supports policy making on energy efficiency and it allows the calculation of total energy savings under different scenarios. Furthermore, government underpricing policies on tariffs and appliance acquisition (longer loan terms, lower interest rates and grace periods) may also be analysed.     

1H NMR and UV-visible data fusion for determining Sudan dyes in culinary spices

Two data fusion strategies (variable and decision level) combined with a multivariate classification approach (Partial Least Squares-Discriminant Analysis, PLS-DA) have been applied to get benefits from the synergistic effect of the information obtained from two spectroscopic techniques: UV-visible and ¹H NMR. Variable level data fusion consists of merging the spectra obtained from each spectroscopic technique in what is called “meta-spectrum” and then applying the classification technique. Decision level data fusion combines the results of individually applying the classification technique in each spectroscopic technique. Among the possible ways of combinations, we have used the fuzzy aggregation connective operators. This procedure has been applied to determine banned dyes (Sudan III and IV) in culinary spices. The results show that data fusion is an effective strategy since the classification results are better than the individual ones: between 80 and 100% for the individual techniques and between 97 and 100% with the two fusion strategies.