The synthesis and properties of some hydrazines

A new synthetic method, applicable to the preparation of a wide range of hydrazine derivatives, is described. This involves the diborane reduction of a hydrazone, or, more conveniently, the reductive-condensation of a hydrazine and the appropriate aldehyde (or ketone). The method gives high yields and provides a particularly simple route to the relatively inaccessible 1,2-disubstituted hydrazines bearing a different group on each nitrogen. The new method has also been applied to the preparation of 1,2-disubstituted hydrazines with the same group on both nitrogens (via the azine), the very rare 1 ,2-disubstituted hydrazines bearing a tert-butyl group, trisubstituted hydrazines and monosubstituted hydrazines. Application of the reaction to the preparation of diaziridines has also been investigated. A mechanism for the reduction, supported by the isolation of a boron-containing intermediate, is suggested. Some limitations of the procedure are discussed. A general i.r. method of distinguishing the isomeric disubstituted hydrazines, as stable salts, has been developed. This has the advantages of speed and simplicity over previous methods. The mass spectra of a series of monosubstituted hydrazines, a series of 1,2-disubstituted hydrazines and some 1-benzoyl 2-alkylhydrazines have been examined in detail. The spectra are generally dominated byα -cleavage processes and the compounds show a variety of interesting rearrangement reactions. The mass spectra of some 1, 1-disubstituted hydrazines and some trisubstituted hydrazines have also been examined. Rearrangement processes occurring in the mass spectrum of tropylium fluoroborate have been examined. Similar rearrangements have been found in the spectrum of trityl fluoroborate and may be of general occurrence in the mass spectra of aromatic fluoroborates. Chemical shift values for some groups on hydrazine nitrogen are recorded and the results of tumour inhibitory tests on some hydrazines are also given.

Gaussian processes and SVM: Mean field results and leave-one-out

In this chapter, we elaborate on the well-known relationship between Gaussian processes (GP) and Support Vector Machines (SVM). Secondly, we present approximate solutions for two computational problems arising in GP and SVM. The first one is the calculation of the posterior mean for GP classifiers using a `naive' mean field approach. The second one is a leave-one-out estimator for the generalization error of SVM based on a linear response method. Simulation results on a benchmark dataset show similar performances for the GP mean field algorithm and the SVM algorithm. The approximate leave-one-out estimator is found to be in very good agreement with the exact leave-one-out error.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50-100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

People, technology, processes and risk knowledge sharing

The present global economic crisis creates doubts about the good use of accumulated experience and knowledge in managing risk in financial services. Typically, risk management practice does not use knowledge management (KM) to improve and to develop new answers to the threats. A key reason is that it is not clear how to break down the “organizational silos” view of risk management (RM) that is commonly taken. As a result, there has been relatively little work on finding the relationships between RM and KM. We have been doing research for the last couple of years on the identification of relationships between these two disciplines. At ECKM 2007 we presented a general review of the literature(s) and some hypotheses for starting research on KM and its relationship to the perceived value of enterprise risk management. This article presents findings based on our preliminary analyses, concentrating on those factors affecting the perceived quality of risk knowledge sharing. These come from a questionnaire survey of RM employees in organisations in the financial services sector, which yielded 121 responses. We have included five explanatory variables for the perceived quality of risk knowledge sharing. These comprised two variables relating to people (organizational capacity for work coordination and perceived quality of communication among groups), one relating to process (perceived quality of risk control) and two related to technology (web channel functionality and RM information system functionality). Our findings so far are that four of these five variables have a significant positive association with the perceived quality of risk knowledge sharing: contrary to expectations, web channel functionality did not have a significant association. Indeed, in some of our exploratory regression studies its coefficient (although not significant) was negative. In stepwise regression, the variable organizational capacity for work coordination accounted for by far the largest part of the variation in the dependent variable perceived quality of risk knowledge sharing. The “people” variables thus appear to have the greatest influence on the perceived quality of risk knowledge sharing, even in a sector that relies heavily on technology and on quantitative approaches to decision making. We have also found similar results with the dependent variable perceived value of Enterprise Risk Management (ERM) implementation.

Business processes and knowledge management

Knowledge has been a subject of interest and inquiry for thousands of years since at least the time of the ancient Greeks, and no doubt even before that. “What is knowledge” continues to be an important topic of discussion in philosophy. More recently, interest in managing knowledge has grown in step with the perception that increasingly we live in a knowledge-based economy. Drucker (1969) is usually credited as being the first to popularize the knowledge-based economy concept by linking the importance of knowledge with rapid technological change in Drucker (1969). Karl Wiig coined the term knowledge management (hereafter KM) for a NATO seminar in 1986, and its popularity took off following the publication of Nonaka and Takeuchi’s book “The Knowledge Creating Company” (Nonaka & Takeuchi, 1995). Knowledge creation is in fact just one of many activities involved in KM. Others include sharing, retaining, refining, and using knowledge. There are many such lists of activities (Holsapple & Joshi, 2000; Probst, Raub, & Romhardt, 1999; Skyrme, 1999; Wiig, De Hoog, & Van der Spek, 1997). Both academic and practical interest in KM has continued to increase throughout the last decade. In this article, first the different types of knowledge are outlined, then comes a discussion of various routes by which knowledge management can be implemented, advocating a process-based route. An explanation follows of how people, processes, and technology need to fit together for effective KM, and some examples of this route in use are given. Finally, there is a look towards the future.

Distributed processing, reconfigurable processes and active network

The fast spread of the Internet and the increasing demands of the service are leading to radical changes in the structure and management of underlying telecommunications systems. Active networks (ANs) offer the ability to program the network on a per-router, per-user, or even per-packet basis, thus promise greater flexibility than current networks. To make this new network paradigm of active network being widely accepted, a lot of issues need to be solved. Management of the active network is one of the challenges. This thesis investigates an adaptive management solution based on genetic algorithm (GA). The solution uses a distributed GA inspired by bacterium on the active nodes within an active network, to provide adaptive management for the network, especially the service provision problems associated with future network. The thesis also reviews the concepts, theories and technologies associated with the management solution. By exploring the implementation of these active nodes in hardware, this thesis demonstrates the possibility of implementing a GA based adaptive management in the real network that being used today. The concurrent programming language, Handel-C, is used for the description of the design system and a re-configurable computer platform based on a FPGA process element is used for the hardware implementation. The experiment results demonstrate both the availability of the hardware implementation and the efficiency of the proposed management solution.

The Synthesis and properties of functionalised polymers

The aim of this project was to synthesise fluorinated polymers that might act as hot material in a guest-host system for use in non-linear optical applications. These polymers would be expected to have the advantage over materials such as poly(vinylidene fluoride) which is known to be incompatible with many nlo active materials. A series of bicyclic fluorinated monomers was prepared by the reaction of fluorinated dienophiles with cyclopentadiene in a series of Diels-Alder reactions. The monomers were purified and then used in ring opening metathesis polymerisation. The materials were then characterised by gel permeation chromatography and nuclear magnetic resonance spectroscopy and cast as films for determination of their activities as nlo materials using a Nd/YAG laser system. The second harmonic intensity of each was measured relative to quartz. However no materials of significant activity were produced. In an attempt to produce polymers that might subsequently be functionalised the polymerisation of 1,2-methylenedioxybenzene and 1,4-benzodioxane was investigated.

Studies on the generalisation of Gaussian processes and Bayesian neural networks

The assessment of the reliability of systems which learn from data is a key issue to investigate thoroughly before the actual application of information processing techniques to real-world problems. Over the recent years Gaussian processes and Bayesian neural networks have come to the fore and in this thesis their generalisation capabilities are analysed from theoretical and empirical perspectives. Upper and lower bounds on the learning curve of Gaussian processes are investigated in order to estimate the amount of data required to guarantee a certain level of generalisation performance. In this thesis we analyse the effects on the bounds and the learning curve induced by the smoothness of stochastic processes described by four different covariance functions. We also explain the early, linearly-decreasing behaviour of the curves and we investigate the asymptotic behaviour of the upper bounds. The effect of the noise and the characteristic lengthscale of the stochastic process on the tightness of the bounds are also discussed. The analysis is supported by several numerical simulations. The generalisation error of a Gaussian process is affected by the dimension of the input vector and may be decreased by input-variable reduction techniques. In conventional approaches to Gaussian process regression, the positive definite matrix estimating the distance between input points is often taken diagonal. In this thesis we show that a general distance matrix is able to estimate the effective dimensionality of the regression problem as well as to discover the linear transformation from the manifest variables to the hidden-feature space, with a significant reduction of the input dimension. Numerical simulations confirm the significant superiority of the general distance matrix with respect to the diagonal one.In the thesis we also present an empirical investigation of the generalisation errors of neural networks trained by two Bayesian algorithms, the Markov Chain Monte Carlo method and the evidence framework; the neural networks have been trained on the task of labelling segmented outdoor images.

The growth, structure and properties of sputtered barium titanate thin films

The design and construction of a sputtering system for the deposition of barium titanate thin films is described. The growth and structure of barium titanate films deposited on a variety of substrates including amorphous carbon fi1ms, potassium bromide single crystals, and polycrystalline gold films has been studied. Films deposited on all substrates at room temperature were amorphous. Polycrystalline titanate films were formed on polycrystalline and amorphous substrates at temperatures above 450°C while films with a pronounced texture could be expitaxially deposited on single crystal potassium bromide above a temperature of only 200°C. Results of dielectric measurements made on the films are reported. Amorphous films were highly insulating (resistivities ~1014 ohm.cm with dielectric constants of between 10 and 20.