Experimental investigation on micromilling of oxygen-free, high-conductivity copper using tungsten carbide, chemistry vapour deposition and single-crystal diamond micro tools

Insufficient experimental data from various micro tools limit industrial application of the micromilling process. This paper presents an experimental comparative investigation into micromilling of oxygen-free, high-conductivity copper using tungsten carbide (WC), chemistry vapour deposition (CVD) diamond, and single-crystal diamond micromilling tools at a uniform 0.4mm diameter. The experiments were carried out on an ultra-precision micromilling machine that features high dynamic accurate performance, so that the dynamic effect of the machine tool itself on the cutting process can be reduced to a minimum. Micromachined surface roughness and burr height were characterized using white light interferometry, a scanning electron microscope (SEM), and a precision surface profiler. The influence of variation of cutting parameters, including cutting speeds, feedrate, and axial depth of cut, on surface roughness and burr formation were analysed. The experimental results show that there exists an optimum feedrate at which best surface roughness can be achieved. Optical quality surface roughness can be achieved with CVD and natural diamond tools by carefully selecting machining conditions, and surface roughness, Ra, of the order of 10nm can also be obtained when using micromilling using WC tools on the precision micromilling machine.EU FP6 MASMICRO projec

An investigation of nanoindentation tests on the single crystal copper thin film via an AFM and MD simulation

Nanoindentation tests performed in an atomic force microscope have been utilized to directly measure the mechanical properties of single crystal metal thin films fabricated by the vacuum vapor deposition technique. Nanoindentation tests were conducted at various indentation depths to study the effect of indentation depths on the mechanical properties of thin films. The results were interpreted by using the Oliver-Pharr method with which direct observation and measurement of the contact area are not required. The elastic modulus of the single crystal copper film at various indentation depths was determined as 67.0±6.9GPa on average which is in reasonable agreement with the results reported by others. The indentation hardness constantly increases with decreasing indentation depth, indicating a strong size effect. In addition to the experimental work, a three-dimensional nanoindentation model of molecular dynamics (MD) simulations with embedded atom method (EAM) potential is proposed to elucidate the mechanics and mechanisms of nanoindentation of thin films from the atomistic point of view. MD simulations results also show that due to the size effect the plastic deformation via amorphous transformation is more favorable than via the generation and propagation of dislocations in nanoindentation of single crystal copper thin films

Optical stark effect in the 2-photon spectrum of NO

A large optical Stark effect has been observed in the two-photon spectrum X(2)Pi yields A(2)Sigma(+)_ in NO. It is explained as a near-resonant process in which the upper state of the two-photon transition is perturbed by interactions with higher-lying electronic states coupled by the laser field. A theoretical analysis is presented along with coupling parameters determined from ab initio wave functions. The synthetic spectrum reproduces the major experimental features

Radiative penguin Bs decays at Belle

We report searches for the radiative penguin decays Bs to phi gamma and Bs to gamma gamma based on a 23.6 fb-1 data sample collected with the Belle detector at the KEKB e+e- energy-asymmetric collider operating at the Upsilon(5S) resonance.Comment: On behalf of the Belle Collaboration. To appear in the proceedings of the International Europhysics Conference on High Energy Physics (EPS-HEP2007), Manchester, England, 19-25 July 2007. 3 pages, 2 figure

A minimax search algorithm for robust continuous speech recognition

In this paper, we propose a novel implementation of a minimax decision rule for continuous density hidden Markov-model-based robust speech recognition. By combining the idea of the minimax decision rule with a normal Viterbi search, we derive a recursive minimax search algorithm, where the minimax decision rule is repetitively applied to determine the partial paths during the search procedure. Because of the intrinsic nature of a recursive search, the proposed method can be easily extended to perform continuous speech recognition. Experimental results on Japanese isolated digits and TIDIGITS, where the mismatch between training and testing conditions is caused by additive white Gaussian noise, show the viability and efficiency of the proposed minimax search algorithm.published_or_final_versio

Improving Viterbi Bayesian predictive classification via sequentialBayesian learning in robust speech recognition

We extend our previously proposed Viterbi Bayesian predictive classification (VBPC) algorithm to accommodate a new class of prior probability density function (PDF) for continuous density hidden Markov model (CDHMM) based robust speech recognition. The initial prior PDF of CDHMM is assumed to be a finite mixture of natural conjugate prior PDF's of its complete-data density. With the new observation data, the true posterior PDF is approximated by the same type of finite mixture PDF's which retain the required most significant terms in the true posterior density according to their contribution to the corresponding predictive density. Then the updated mixture PDF is used to improve the VBPC performance. The experimental results on a speaker-independent recognition task of isolated Japanese digits confirm the viability and the usefulness of the proposed technique.published_or_final_versio

Robust speech recognition based on a Bayesian prediction approach

We study a category of robust speech recognition problem in which mismatches exist between training and testing conditions, and no accurate knowledge of the mismatch mechanism is available. The only available information is the test data along with a set of pretrained Gaussian mixture continuous density hidden Markov models (CDHMMs). We investigate the problem from the viewpoint of Bayesian prediction. A simple prior distribution, namely constrained uniform distribution, is adopted to characterize the uncertainty of the mean vectors of the CDHMMs. Two methods, namely a model compensation technique based on Bayesian predictive density and a robust decision strategy called Viterbi Bayesian predictive classification are studied. The proposed methods are compared with the conventional Viterbi decoding algorithm in speaker-independent recognition experiments on isolated digits and TI connected digit strings (TIDTGITS), where the mismatches between training and testing conditions are caused by: (1) additive Gaussian white noise, (2) each of 25 types of actual additive ambient noises, and (3) gender difference. The experimental results show that the adopted prior distribution and the proposed techniques help to improve the performance robustness under the examined mismatch conditions.published_or_final_versio

Sequential Bayesian learning of CDHMM based on finite mixture approximation of its prior/posterior density

Proposes a sequential Bayesian learning strategy of a continuous-density hidden Markov model (CDHMM) based on a finite mixture approximation of its prior/posterior density. The initial prior density of the CDHMM is assumed to be a finite mixture of natural conjugate prior probability density functions (PDFs) of the complete-data density. With the new observation data, the true posterior PDF is approximated by the same type of finite-mixture PDFs which retain the required most significant terms in the true posterior density according to their contribution to the corresponding Bayesian predictive density by using an N-best beam search algorithm. Then, the updated mixture PDF is used in the VBPC (Viterbi Bayesian predictive classification) method to deal with unknown mismatches in robust speech recognition. Experimental results on a speaker-independent recognition task of isolated Japanese digits confirm the viability and the usefulness of the proposed method.published_or_final_versio