Simulated random packing of equal spheres

PACS, a computer program to simulate very slow settling of rigid equal spheres into a randomly packed bed, is described. Simulated packings of 6,000, 10,000, and 15,000 spheres are anisotropic. Mean void fraction is 0.42 and mean number of nearest neighbours 6.0. There are numerous cases of four spheres arranged in a tetrahedron, but no larger ordered regions. These findings, plus local voidage, distribution of circles in a section, angular distribution, and radial distribution are compared to theoretical and experimental results.     

Spatially resolved electrochemiluminescence on an array of electrode tips

An array of electrode tips with 6-microm center-to-center spacing, fabricated through chemical etching of an optical fiber bundle, and coated with gold, was used for initiating electrochemiluminescence (ECL) in an aqueous solution of Ru(bpy)3(2+) and tri-n-propylamine (TPrA). ECL generated at the tips of the electrodes in the array was detected with a CCD camera and exhibited both high sensitivity and high resolution. In the case in which the ECL signal could not be distinguished from the background, ECL signals could be obtained by pulsing the array and summing multiple CCD images. The behavior of this array was compared to a second array that consisted of individual electrodes insulated with an electrophoretic paint.     

Kernel CMAC with improved capability.

The cerebellar model articulation controller (CMAC) has some attractive features, namely fast learning capability and the possibility of efficient digital hardware implementation. Although CMAC was proposed many years ago, several open questions have been left even for today. The most important ones are about its modeling and generalization capabilities. The limits of its modeling capability were addressed in the literature, and recently, certain questions of its generalization property were also investigated. This paper deals with both the modeling and the generalization properties of CMAC. First, a new interpolation model is introduced. Then, a detailed analysis of the generalization error is given, and an analytical expression of this error for some special cases is presented. It is shown that this generalization error can be rather significant, and a simple regularized training algorithm to reduce this error is proposed. The results related to the modeling capability show that there are differences between the one-dimensional (1-D) and the multidimensional versions of CMAC. This paper discusses the reasons of this difference and suggests a new kernel-based interpretation of CMAC. The kernel interpretation gives a unified framework. Applying this approach, both the 1-D and the multidimensional CMACs can be constructed with similar modeling capability. Finally, this paper shows that the regularized training algorithm can be applied for the kernel interpretations too, which results in a network with significantly improved approximation capabilities.     

Bilingual LSA-based adaptation for statistical machine translation

We propose a novel approach to cross-lingual language model and translation lexicon adaptation for statistical machine translation (SMT) based on bilingual latent semantic analysis. Bilingual LSA enables latent topic distributions to be efficiently transferred across languages by enforcing a one-to-one topic correspondence during training. Using the proposed bilingual LSA framework, model adaptation can be performed by, first, inferring the topic posterior distribution of the source text and then applying the inferred distribution to an n-gram language model of the target language and translation lexicon via marginal adaptation. The background phrase table is enhanced with the additional phrase scores computed using the adapted translation lexicon. The proposed framework also features rapid bootstrapping of LSA models for new languages based on a source LSA model of another language. Our approach is evaluated on the Chinese–English MT06 test set using the medium-scale SMT system and the GALE SMT system measured in BLEU and NIST scores. Improvement in both scores is observed on both systems when the adapted language model and the adapted translation lexicon are applied individually. When the adapted language model and the adapted translation lexicon are applied simultaneously, the gain is additive. At the 95% confidence interval of the unadapted baseline system, the gain in both scores is statistically significant using the medium-scale SMT system, while the gain in the NIST score is statistically significant using the GALE SMT system.     

Perceived cultural importance and actual self-importance of values in cultural identification.

Cross-cultural psychologists assume that core cultural values define to a large extent what a culture is. Typically, core values are identified through an actual self-importance approach, in which core values are those that members of the culture as a group strongly endorse. In this article, the authors propose a perceived cultural importance approach to identifying core values, in which core values are values that members of the culture as a group generally believe to be important in the culture. In 5 studies, the authors examine the utility of the perceived cultural importance approach. Results consistently showed that, compared with values of high actual self-importance, values of high perceived cultural importance play a more important role in cultural identification. These findings have important implications for conceptualizing and measuring cultures. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Reconfigurable Microwave Photonic Filter Using Multiwavelength Erbium-Doped Fiber Laser

A microwave photonic filter using a simple and novel multiwavelength erbium-doped fiber laser (EDFL) is proposed. The filter was experimentally demonstrated featuring tunability and reconfigurability by adjustment of the output from the EDFL. The experimental results show excellent agreement with the numerical simulations.     

A comparison of stochastic programming and bi-objective optimisation approaches to robust airline crew scheduling

A prominent problem in airline crew scheduling is the pairings or Tour-of-Duty planning problem. The objective is to determine a set of pairings (or Tours-of-Duty) for a crew group to minimise the planned cost of operating a schedule of flights. However, due to unforeseen events the performance in operation can differ considerably from planning, sometimes causing significant additional recovery costs. In recent years there has been a growing interest in robust crew scheduling. Here, the aim is to find solutions that are “cheap” in terms of planned cost as well as being robust, meaning that they are less likely to be disrupted in case of delays. Taking the stochastic nature of delays into account, Yen and Birge (Transp Sci 40:3–14, 2006) formulate the problem as a two-stage stochastic integer programme and develop an algorithm to solve this problem. Based on the contradictory nature of the goals, Ehrgott and Ryan (J Multi-Criteria Decis Anal 11:139–150, 2002) formulate a bi-objective set partitioning model and employ elastic constraint scalarisation to enable the solution by set partitioning algorithms commercially used in crew scheduling software. In this study, we compare the two solution approaches. We improve the algorithm of Yen and Birge (Transp Sci 40:3–14, 2006) and implement both methods with a commercial crew scheduling software. The results of both methods are compared with respect to characteristics of robust solutions, such as the number of aircraft changes for crew. We also conduct experiments to simulate the performance of the obtained solutions. All experiments are performed using actual schedule data from Air New Zealand.