Surface profile prediction and analysis applied to turning process

An approach for the prediction of surface profile in turning process using Radial Basis Function (RBF) neural networks is presented. The input parameters of the RBF networks are cutting speed, depth of cut and feed rate. The output parameters are Fast Fourier Transform (FFT) vector of surface profile for the prediction of surface profile. The RBF networks are trained with adaptive optimal training parameters related to cutting parameters and predict surface profile using the corresponding optimal network topology for each new cutting condition. A very good performance of surface profile prediction, in terms of agreement with experimental data, was achieved with high accuracy, low cost and high speed. It is found that the RBF networks have the advantage over Back Propagation (BP) neural networks. Furthermore, a new group of training and testing data were also used to analyse the influence of tool wear and chip formation on prediction accuracy using RBF neural networks

Random sampling technique for ultra-fast computations of molecular opacities for exoplanet atmospheres

Opacities of molecules in exoplanet atmospheres rely on increasingly detailed line-lists for these molecules. The line lists available today contain for many species up to several billions of lines. Computation of the spectral line profile created by pressure and temperature broadening, the Voigt profile, of all of these lines is becoming a computational challenge. We aim to create a method to compute the Voigt profile in a way that automatically focusses the computation time into the strongest lines, while still maintaining the continuum contribution of the high number of weaker lines. Here, we outline a statistical line sampling technique that samples the Voigt profile quickly and with high accuracy. The number of samples is adjusted to the strength of the line and the local spectral line density. This automatically provides high accuracy line shapes for strong lines or lines that are spectrally isolated. The line sampling technique automatically preserves the integrated line opacity for all lines, thereby also providing the continuum opacity created by the large number of weak lines at very low computational cost. The line sampling technique is tested for accuracy when computing line spectra and correlated-k tables. Extremely fast computations (~3.5e5 lines per second per core on a standard current day desktop computer) with high accuracy (< 1 % almost everywhere) are obtained. A detailed recipe on how to perform the computations is given.Comment: Accepted for publication in A&

Analysis of superfamily specific profile-profile recognition accuracy

BACKGROUND: Annotation of sequences that share little similarity to sequences of known function remains a major obstacle in genome annotation. Some of the best methods of detecting remote relationships between protein sequences are based on matching sequence profiles. We analyse the superfamily specific performance of sequence profile-profile matching. Our benchmark consists of a set of 16 protein superfamilies that are highly diverse at the sequence level. We relate the performance to the number of sequences in the profiles, the profile diversity and the extent of structural conservation in the superfamily. RESULTS: The performance varies greatly between superfamilies with the truncated receiver operating characteristic, ROC(10), varying from 0.95 down to 0.01. These large differences persist even when the profiles are trimmed to approximately the same level of diversity. CONCLUSIONS: Although the number of sequences in the profile (profile width) and degree of sequence variation within positions in the profile (profile diversity) contribute to accurate detection there are other superfamily specific factors

Breaking the mass / anisotropy degeneracy in the Coma cluster

We provide the first direct lifting of the mass/anisotropy degeneracy for a cluster of galaxies, by jointly fitting the line of sight velocity dispersion and kurtosis profiles of the Coma cluster, assuming an NFW tracer density profile, a generalized-NFW dark matter profile and a constant anisotropy profile. We find that the orbits in Coma must be quasi-isotropic, and find a mass consistent with previous analyses, but a concentration parameter 50% higher than expected in cosmological N-body simulations. We then test the accuracy of our method on realistic non-spherical systems with substructure and streaming motions, by applying it to the ten most massive structures in a cosmological N-body simulation. We find that our method yields fairly accurate results on average (within 20%), although with a wide variation (factor 1.7 at 1 sigma) for the concentration parameter, with decreased accuracy and efficiency when the projected mean velocity is not constant with radius.Comment: 5 pages, oral presentation at IAU Colloquium 195, Outskirts of Galaxy Clusters: intense life in the suburbs, ed. A. Diaferi

Fast search of sequences with complex symbol correlations using profile context-sensitive HMMS and pre-screening filters

Recently, profile context-sensitive HMMs (profile-csHMMs) have been proposed which are very effective in modeling the common patterns and motifs in related symbol sequences. Profile-csHMMs are capable of representing long-range correlations between distant symbols, even when these correlations are entangled in a complicated manner. This makes profile-csHMMs an useful tool in computational biology, especially in modeling noncoding RNAs (ncRNAs) and finding new ncRNA genes. However, a profile-csHMM based search is quite slow, hence not practical for searching a large database. In this paper, we propose a practical scheme for making the search speed significantly faster without any degradation in the prediction accuracy. The proposed method utilizes a pre-screening filter based on a profile-HMM, which filters out most sequences that will not be predicted as a match by the original profile-csHMM. Experimental results show that the proposed approach can make the search speed eighty times faster

Daytime ClO over McMurdo in September 1987: Altitude profile retrieval accuracy

During the 1987 National Ozone Expedition, mm-wave emission line spectra of the 278.6 GHz rotational stratospheric ClO were observed at McMurdo Station, Antarctica. The results confirm the 1986 discovery of a lower stratospheric layer with approximately 100 times the normal amount of ClO; the 1987 observations, made with a spectrometer bandwidth twice that used in 1986, make possible a more accurate retrieval of the altitude profile of the low altitude component of stratospheric ClO from the pressure broadened line shape, down to approximately 16 km. The accuracy of the altitude profile retrievals is discussed, using the daytime (09:30 to 19:30, local time) data from 20 to 24 September, 1987 as an example. The signal strength averaged over this daytime period is approx. 85 percent of the midday peak value. The rate of ozone depletion implied by the observed ClO densities is also discussed

Surface Profile Height Measurement Using Optical Interferometry Method

Interferometer is one of the methods that are used for measuring surface profile with high accuracy reach to the order of 1/1000 of the wavelength of the light. The accuracy in a given interferomter depends on many factors such as the light source properties and environmental mechanical vibration. This poster illustrates a method to increase the accuracy of Linnik interferometer for nano-scale measurements