931 resultados para Jenifer Roberts
Resumo:
Laboratory Fourier transform spectroscopy of pure water vapor and water vapor mixed with air has been conducted between 1200 and 8000 cm−1 and at temperatures between 293 and 351 K with the purpose of detecting and characterizing the water vapor continuum. The spectral features of the continuum within the major water absorption bands are presented and compared where possible to those from previous experimental studies and to the commonly used MT_CKD and CKD models. It was observed that in the main, both models adequately capture the general spectral form of the continuum; however, there were a number of exceptions. Overall, there is no evidence to indicate that MT_CKD is an improvement upon the older CKD model in these spectral regions. There was generally good agreement between our results and those of other experimental investigators. The general mathematical forms of the self-continuum temperature dependence, given by both Roberts et al. (1976) and CKD/MT_CKD, fit well to the experimental continuum in these spectral regions. However, the range of temperatures over which we made measurements is not sufficient to discriminate between these two forms or to exclude the possibility of other forms of temperature dependence being more appropriate. At the same time, the actual parameters currently used in CKD/MT_CKD to describe the temperature dependence in many spectral regions cannot reproduce the observed strong spectral variation in the temperature dependence. It has not been possible to make definitive conclusions about the magnitude of the continuum absorption in the far wings of the absorption bands investigated here.
Resumo:
A series of half-sandwich bis(phosphine) ruthenium acetylide complexes [Ru(C CAr)(L-2)Cp'] (Ar = phenyl, p-tolyl, 1-naphthyl, 9-anthryl; L2 = (PPh3)(2), Cp' = Cp; L-2 = dppe; Cp' = Cp*) have been examined using electrochemical and spectroelectrochemical methods. One-electron oxidation of these complexes gave the corresponding radical cations [Ru(C CAr)(L2)Cp'](+). Those cations based on Ru(dppe)Cp*, or which feature a para-tolyl acetylide substituent, are more chemically robust than examples featuring the Ru(PPh3)(2)Cp moiety, permitting good quality UV-Vis-NIR and IR spectroscopic data to be obtained using spectroelectrochemical methods. On the basis of TD DFT calculations, the low energy (NIR) absorption bands in the experimental electronic spectra for most of these radical cations are assigned to transitions between the beta-HOSO and beta-LUSO, both of which have appreciable metal d and ethynyl pi character. However, the large contribution from the anthryl moiety to the frontier orbitals of [Ru(C CC14H9)(L2)CP'](+) suggests compounds containing this moiety should be described as metal-stabilised anthryl radical cations.
Electrochemical studies of bi- and polymetallic complexes featuring acetylide based bridging ligands
Resumo:
Acetylide-based bridging ligands have been widely used in the preparation of complexes that display a degree of electronic interaction between metal-based redox groups located at the ligand termini. The electrochemical response of these systems has been selectively reviewed, with a focus on the variation in properties that accompany changes in the structure of the bridging ligand and the nature of the metal groups.
Resumo:
The syntheses and characterizations of several complexes containing ferrocenylethynyl and ferrocene-1,1'-bis(ethynyl) groups attached to M(PP)Cp'[M = Fe, Ru, PP = dppe, Cp'= Cp*; M = Ru, Os, PP = (PPh3)(2), dppe, Cp' = Cp] are described. Reactions with tetracyanoethene have given either tetracyanobuta-1,3-dienyl or eta(3)-allylic derivatives, while addition of Me+ afforded the corresponding vinylidene derivatives. Some electrochemical measurements are discussed in terms of electronic communication between the redox-active M(PP)Cp' groups through the ferrocene nucleus. The molecular structures of 14 of these complexes have been determined by crystallographic methods.
Resumo:
Real-world text classification tasks often suffer from poor class structure with many overlapping classes and blurred boundaries. Training data pooled from multiple sources tend to be inconsistent and contain erroneous labelling, leading to poor performance of standard text classifiers. The classification of health service products to specialized procurement classes is used to examine and quantify the extent of these problems. A novel method is presented to analyze the labelled data by selectively merging classes where there is not enough information for the classifier to distinguish them. Initial results show the method can identify the most problematic classes, which can be used either as a focus to improve the training data or to merge classes to increase confidence in the predicted results of the classifier.
Resumo:
A unique parameterization of the perspective projections in all whole-numbered dimensions is reported. The algorithm for generating a perspective transformation from parameters and for recovering parameters from a transformation is a modification of the Givens orthogonalization algorithm. The algorithm for recovering a perspective transformation from a perspective projection is a modification of Roberts' classical algorithm. Both algorithms have been implemented in Pop-11 with call-out to the NAG Fortran libraries. Preliminary monte-carlo tests show that the transformation algorithm is highly accurate, but that the projection algorithm cannot recover magnitude and shear parameters accurately. However, there is reason to believe that the projection algorithm might improve significantly with the use of many corresponding points, or with multiple perspective views of an object. Previous parameterizations of the perspective transformations in the computer graphics and computer vision literature are discussed.
Resumo:
Where users are interacting in a distributed virtual environment, the actions of each user must be observed by peers with sufficient consistency and within a limited delay so as not to be detrimental to the interaction. The consistency control issue may be split into three parts: update control; consistent enactment and evolution of events; and causal consistency. The delay in the presentation of events, termed latency, is primarily dependent on the network propagation delay and the consistency control algorithms. The latency induced by the consistency control algorithm, in particular causal ordering, is proportional to the number of participants. This paper describes how the effect of network delays may be reduced and introduces a scalable solution that provides sufficient consistency control while minimising its effect on latency. The principles described have been developed at Reading over the past five years. Similar principles are now emerging in the simulation community through the HLA standard. This paper attempts to validate the suggested principles within the schema of distributed simulation and virtual environments and to compare and contrast with those described by the HLA definition documents.
Resumo:
A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.
Resumo:
Measured process data normally contain inaccuracies because the measurements are obtained using imperfect instruments. As well as random errors one can expect systematic bias caused by miscalibrated instruments or outliers caused by process peaks such as sudden power fluctuations. Data reconciliation is the adjustment of a set of process data based on a model of the process so that the derived estimates conform to natural laws. In this paper, techniques for the detection and identification of both systematic bias and outliers in dynamic process data are presented. A novel technique for the detection and identification of systematic bias is formulated and presented. The problem of detection, identification and elimination of outliers is also treated using a modified version of a previously available clustering technique. These techniques are also combined to provide a global dynamic data reconciliation (DDR) strategy. The algorithms presented are tested in isolation and in combination using dynamic simulations of two continuous stirred tank reactors (CSTR).