A hybrid generative/discriminative framework to train a semantic parser from an un-annotated corpus

We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HM-SVMs). The HVS model is an extension of the basic discrete Markov model in which context is encoded as a stack-oriented state vector. The HM-SVMs combine the advantages of the hidden Markov models and the support vector machines. By employing a modified K-means clustering method, a small set of most representative sentences can be automatically selected from an un-annotated corpus. These sentences together with their abstract annotations are used to train an HVS model which could be subsequently applied on the whole corpus to generate semantic parsing results. The most confident semantic parsing results are selected to generate a fully-annotated corpus which is used to train the HM-SVMs. The proposed framework has been tested on the DARPA Communicator Data. Experimental results show that an improvement over the baseline HVS parser has been observed using the hybrid framework. When compared with the HM-SVMs trained from the fully-annotated corpus, the hybrid framework gave a comparable performance with only a small set of lightly annotated sentences. © 2008. Licensed under the Creative Commons.

Bridging large and small scales of water models using hybrid Molecular Dynamics/Fluctuating Hydrodynamics framework

This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.

Capabilities for strategic flexibility:a cognitive content framework

Different forms of strategic flexibility allow for reactive adaptation to different changing environments and the proactive driving of change. It is therefore becoming increasingly important for decision makers to not only possess marketing capabilities, but also the capabilities for strategic flexibility in its various forms. However, our knowledge of the relationships between decision makers’ different ways of thinking and their capabilities for strategic flexibility is limited. This limitation is constraining research and understanding. In this article we develop a theoretical cognitive content framework that postulates relationships between different ways of thinking about strategy and different information-processing demands. We then outline how the contrasting beliefs of decision makers may influence their capabilities to generate different hybrid forms of strategic flexibility at the cognitive level. Theoretically, the framework is embedded in resource-based theory, personal construct theory and schema theory. The implications for research and theory are discussed.

Zr-containing hybrid organic-inorganic mesoporous materials:hydrophobic acid catalysts for biodiesel production

Zirconium-containing periodic mesoporous organosilicas (Zr-PMOs) with varying framework organic content have been synthesized through a direct synthesis method. These materials display the excellent textural properties of the analogous inorganic solid acid Zr-SBA-15 material. However, the substitution of silica by organosilicon species provides a strong hydrophobic character. This substitution leads to meaningful differences in the environment surrounding the zirconium metal sites, leading the modification of the catalytic properties of these materials. Although lower metal incorporation is accomplished in the final materials, leading to a lower population of metal sites, hydrophobisation leads to an impressive beneficial effect on the intrinsic catalytic activity of the zirconium sites in biodiesel production by esterification/transesterification of free fatty acid -containing feedstock. Moreover, the catalytic activity of the highly hybridised materials is hardly affected in presence of large amounts of water, confirming their very good water-tolerance. This makes Zr-PMO materials interesting catalysts for biodiesel production from highly acidic water-containing feedstock. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The franchise dilemma:entrepreneurial characteristics, relational contracting, and opportunism in hybrid governance

Using franchise data, we identify that entrepreneurial characteristics of franchisees partially impact on their opportunistic tendencies. Further, relational contracting increases franchisee opportunism by strengthening the opportunism-enhancing impact of entrepreneurial characteristics. These findings point to a key dilemma franchisors need to be aware of: Entrepreneurially minded franchisees who might be better at exploiting market opportunities for their units may also behave more opportunistically, if given the chance through a more relational contracting regime. At the same time, if they perceive the contractual framework as being too rigid, they may be less able to leverage their capabilities, become dissatisfied, and exit the system.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

CO adsorption over Pd nanoparticles:a general framework for IR simulations on nanoparticles

CO vibrational spectra over catalytic nanoparticles under high coverages/pressures are discussed from a DFT perspective. Hybrid B3LYP and PBE DFT calculations of CO chemisorbed over Pd4 and Pd13 nanoclusters, and a 1.1 nm Pd38 nanoparticle, have been performed in order to simulate the corresponding coverage dependent infrared (IR) absorption spectra, and hence provide a quantitative foundation for the interpretation of experimental IR spectra of CO over Pd nanocatalysts. B3LYP simulated IR intensities are used to quantify site occupation numbers through comparison with experimental DRIFTS spectra, allowing an atomistic model of CO surface coverage to be created. DFT adsorption energetics for low CO coverage (θ → 0) suggest the CO binding strength follows the order hollow > bridge > linear, even for dispersion-corrected functionals for sub-nanometre Pd nanoclusters. For a Pd38 nanoparticle, hollow and bridge-bound are energetically similar (hollow ≈ bridge > atop). It is well known that this ordering has not been found at the high coverages used experimentally, wherein atop CO has a much higher population than observed over Pd(111), confirmed by our DRIFTS spectra for Pd nanoparticles supported on a KIT-6 silica, and hence site populations were calculated through a comparison of DFT and spectroscopic data. At high CO coverage (θ = 1), all three adsorbed CO species co-exist on Pd38, and their interdiffusion is thermally feasible at STP. Under such high surface coverages, DFT predicts that bridge-bound CO chains are thermodynamically stable and isoenergetic to an entirely hollow bound Pd/CO system. The Pd38 nanoparticle undergoes a linear (3.5%), isotropic expansion with increasing CO coverage, accompanied by 63 and 30 cm− 1 blue-shifts of hollow and linear bound CO respectively.

A hybrid measurement systems analysis and uncertainty of measurement approach for industrial measurement in the light controlled factory

The uncertainty of measurements must be quantified and considered in order to prove conformance with specifications and make other meaningful comparisons based on measurements. While there is a consistent methodology for the evaluation and expression of uncertainty within the metrology community industry frequently uses the alternative Measurement Systems Analysis methodology. This paper sets out to clarify the differences between uncertainty evaluation and MSA and presents a novel hybrid methodology for industrial measurement which enables a correct evaluation of measurement uncertainty while utilising the practical tools of MSA. In particular the use of Gage R&R ANOVA and Attribute Gage studies within a wider uncertainty evaluation framework is described. This enables in-line measurement data to be used to establish repeatability and reproducibility, without time consuming repeatability studies being carried out, while maintaining a complete consideration of all sources of uncertainty and therefore enabling conformance to be proven with a stated level of confidence. Such a rigorous approach to product verification will become increasingly important in the era of the Light Controlled Factory with metrology acting as the driving force to achieve the right first time and highly automated manufacture of high value large scale products such as aircraft, spacecraft and renewable power generation structures.