Microstructure of MmM(5)/Mg multi-layer films prepared by magnetron sputtering

Microstructure of MmNi(3.5)(CoAlMn)(1.5)/Mg (here Mm denotes La-rich mischmetal) multi-layer hydrogen storage thin films prepared by direct current magnetron sputtering was investigated by cross-sectional transmission electron microscopy (XTEM). It was shown that the MMM5 layers are composed of two regions: an amorphous region with a thickness of similar to 4nm at the bottom of the layers and a randomly orientated nanocrystallite region on the top of the amorphous region and the Mg layers consist of typical columnar crystallite with their [001] direction nearly parallel to the growth direction. The mechanism for the formation of the above microstructure characteristics in the multi-layer thin films has been proposed. Based on the microstructure feature of the multi-layer films, mechanism for the apparent improvement of hydrogen absorption/desorption kinetics was discussed. (c) 2005 Elsevier B.V. All rights reserved.

Globally optimal on-line learning rules for multi-layer neural networks

We present a method for determining the globally optimal on-line learning rule for a soft committee machine under a statistical mechanics framework. This rule maximizes the total reduction in generalization error over the whole learning process. A simple example demonstrates that the locally optimal rule, which maximizes the rate of decrease in generalization error, may perform poorly in comparison.

Efficient THz radiation from a nanocrystalline silicon-based multi-layer photomixer

In this paper we propose a novel type of multiple-layer photomixer based on amorphous/nano-crystalline-Si. Such a device implies that it could be possible to enhance the conversion efficiency from optical power to THz emission by increasing the absorption length and by reducing the device overheating through the use of substrates with higher thermal conductivity compared to GaAs. Our calculations show that the output power from a two-layer Si-based photomixer is at least ten times higher than that from conventional LT-GaAs photomixers at 1 THz.

Physical characteristics of localized surface plasmons resulting from nano-scale structured multi-layer thin films deposited on D-shaped optical fiber

Novel surface plasmonic optical fiber sensors have been fabricated using multiple coatings deposited on a lapped section of a single mode fiber. UV laser irradiation processing with a phase mask produces a nano-scaled surface relief grating structure resembling nano-wires. The resulting individual corrugations produced by material compaction are approximately 20 μm long with an average width at half maximum of 100 nm and generate localized surface plasmons. Experimental data are presented that show changes in the spectral characteristics after UV processing, coupled with an overall increase in the sensitivity of the devices to surrounding refractive index. Evidence is presented that there is an optimum UV dosage (48 joules) over which no significant additional optical change is observed. The devices are characterized with regards to change in refractive index, where significantly high spectral sensitivities in the aqueous index regime are found, ranging up to 4000 nm/RIU for wavelength and 800 dB/RIU for intensity. © 2013 Optical Society of America.

On the k-anonymization of time-varying and multi-layer social graphs

The popularity of online social media platforms provides an unprecedented opportunity to study real-world complex networks of interactions. However, releasing this data to researchers and the public comes at the cost of potentially exposing private and sensitive user information. It has been shown that a naive anonymization of a network by removing the identity of the nodes is not sufficient to preserve users’ privacy. In order to deal with malicious attacks, k -anonymity solutions have been proposed to partially obfuscate topological information that can be used to infer nodes’ identity. In this paper, we study the problem of ensuring k anonymity in time-varying graphs, i.e., graphs with a structure that changes over time, and multi-layer graphs, i.e., graphs with multiple types of links. More specifically, we examine the case in which the attacker has access to the degree of the nodes. The goal is to generate a new graph where, given the degree of a node in each (temporal) layer of the graph, such a node remains indistinguishable from other k-1 nodes in the graph. In order to achieve this, we find the optimal partitioning of the graph nodes such that the cost of anonymizing the degree information within each group is minimum. We show that this reduces to a special case of a Generalized Assignment Problem, and we propose a simple yet effective algorithm to solve it. Finally, we introduce an iterated linear programming approach to enforce the realizability of the anonymized degree sequences. The efficacy of the method is assessed through an extensive set of experiments on synthetic and real-world graphs.