Complementary Phone Error training

This paper introduces a novel method for the training of a complementary acoustic model with respect to set of given acoustic models. The method is based upon an extension of the Minimum Phone Error (MPE) criterion and aims at producing a model that makes complementary phone errors to those already trained. The technique is therefore called Complementary Phone Error (CPE) training. The method is evaluated using an Arabic large vocabulary continuous speech recognition task. Reductions in word error rate (WER) after combination with a CPE-trained system were obtained with up to 0.7% absolute for a system trained on 172 hours of acoustic data and up to 0.2% absolute for the final system trained on nearly 2000 hours of Arabic data.

Training and assignment of multi-skilled workers for implementing seru production systems

Confronted with high variety and low volume market demands, many companies, especially the Japanese electronics manufacturing companies, have reconfigured their conveyor assembly lines and adopted seru production systems. Seru production system is a new type of work-cell-based manufacturing system. A lot of successful practices and experience show that seru production system can gain considerable flexibility of job shop and high efficiency of conveyor assembly line. In implementing seru production, the multi-skilled worker is the most important precondition, and some issues about multi-skilled workers are central and foremost. In this paper, we investigate the training and assignment problem of workers when a conveyor assembly line is entirely reconfigured into several serus. We formulate a mathematical model with double objectives which aim to minimize the total training cost and to balance the total processing times among multi-skilled workers in each seru. To obtain the satisfied task-to-worker training plan and worker-to-seru assignment plan, a three-stage heuristic algorithm with nine steps is developed to solve this mathematical model. Then, several computational cases are taken and computed by MATLAB programming. The computation and analysis results validate the performances of the proposed mathematical model and heuristic algorithm. © 2013 Springer-Verlag London.

Excitation energy dependent raman signatures of ABA- and ABC-stacked few-layer graphene

The dependence of the Raman spectrum on the excitation energy has been investigated for ABA-and ABC- stacked few-layer graphene in order to establish the fingerprint of the stacking order and the number of layers, which affect the transport and optical properties of few-layer graphene. Five different excitation sources with energies of 1.96, 2.33, 2.41, 2.54 and 2.81â €...eV were used. The position and the line shape of the Raman 2D, G*, N, M, and other combination modes show dependence on the excitation energy as well as the stacking order and the thickness. One can unambiguously determine the stacking order and the thickness by comparing the 2D band spectra measured with 2 different excitation energies or by carefully comparing weaker combination Raman modes such as N, M, or LOLA modes. The criteria for unambiguous determination of the stacking order and the number of layers up to 5 layers are established.