Towards a unified service description language for the internet of services : requirements and first developments

Service-oriented Architectures (SOA) and Web services leverage the technical value of solutions in the areas of distributed systems and cross-enterprise integration. The emergence of Internet marketplaces for business services is driving the need to describe services, not only from a technical level, but also from a business and operational perspective. While, SOA and Web services reside in an IT layer, organizations owing Internet marketplaces are requiring advertising and trading business services which reside in a business layer. As a result, the gap between business and IT needs to be closed. This paper presents USDL (Unified Service Description Language), a specification language to describe services from a business, operational and technical perspective. USDL plays a major role in the Internet of Services to describe tradable services which are advertised in electronic marketplaces. The language has been tested using two service marketplaces as use cases.

A vibrational spectroscopic study of the phosphate mineral minyulite KAl2(OH,F)(PO4)2⋅4(H2O) and in comparison with wardite

Vibrational spectroscopy enables subtle details of the molecular structure of minyulite KAl2(OH,F)(PO4)2⋅4(H2O). Single crystals of a pure phase from a Brazilian pegmatite were used. Minyulite belongs to the orthorhombic crystal system. This indicates that it has three axes of unequal length, yet all are perpendicular to each other. The infrared and Raman spectroscopy were applied to compare the structure of minyulite with wardite. The reason for the comparison is that both are Al containing phosphate minerals. The Raman spectrum of minyulite shows an intense band at 1012 cm−1 assigned to the ν1PO43- symmetric stretching vibrations. A series of low intensity Raman bands at 1047, 1077, 1091 and 1105 cm−1 are assigned to the ν3PO43- antisymmetric stretching modes. The Raman bands at 1136, 1155, 1176 and 1190 cm−1 are assigned to AlOH deformation modes. The infrared band at 1014 cm−1 is ascribed to the PO43- ν1 symmetric stretching vibrational mode. The infrared bands at 1049, 1071, 1091 and 1123 cm−1 are attributed to the PO43- ν3 antisymmetric stretching vibrations. The infrared bands at 1123, 1146 and 1157 cm−1 are attributed to AlOH deformation modes. Raman bands at 575, 592, 606 and 628 cm−1 are assigned to the ν4 out of plane bending modes of the PO43- unit. In the 2600–3800 cm−1 spectral range, Raman bands for minyulite are found at 3661, 3669 and 3692 cm−1 are assigned to AlOH/AlF stretching vibrations. Broad infrared bands are also found at 2904, 3105, 3307, 3453 and 3523 cm−1. Raman bands at 3225, 3324 cm−1 are assigned to water stretching vibrations. A comparison is made with the vibrational spectra of wardite. Raman spectroscopy complimented with infrared spectroscopy has enabled aspects of the structure of minyulite to be ascertained and compared with that of other phosphate minerals.

Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.