Soliton switching using cascaded nonlinear-optical loop mirrors

We demonstrate multiple-peaked switching in a nonlinear-optical loop mirror and present an experimental investigation of device cascading in the soliton regime based on a sequence of two independent nonlinear-optical loop mirrors. Cascading leads to an enhanced switching response with sharper switching edges, flattened peaks, and increased interpeak extinction ratios. We observe that pulses emerging from the cascade retain the sech2 temporal profile of a soliton with minimal degradation in the spectral characteristics.

Packet switching in wide area broadband private networks

B-ISDN is a universal network which supports diverse mixes of service, applications and traffic. ATM has been accepted world-wide as the transport technique for future use in B-ISDN. ATM, being a simple packet oriented transfer technique, provides a flexible means for supporting a continuum of transport rates and is efficient due to possible statistical sharing of network resources by multiple users. In order to fully exploit the potential statistical gain, while at the same time provide diverse service and traffic mixes, an efficient traffic control must be designed. Traffic controls which include congestion and flow control are a fundamental necessity to the success and viability of future B-ISDN. Congestion and flow control is difficult in the broadband environment due to the high speed link, the wide area distance, diverse service requirements and diverse traffic characteristics. Most congestion and flow control approaches in conventional packet switched networks are reactive in nature and are not applicable in the B-ISDN environment. In this research, traffic control procedures mainly based on preventive measures for a private ATM-based network are proposed and their performance evaluated. The various traffic controls include CAC, traffic flow enforcement, priority control and an explicit feedback mechanism. These functions operate at call level and cell level. They are carried out distributively by the end terminals, the network access points and the internal elements of the network. During the connection set-up phase, the CAC decides the acceptance or denial of a connection request and allocates bandwidth to the new connection according to three schemes; peak bit rate, statistical rate and average bit rate. The statistical multiplexing rate is based on a `bufferless fluid flow model' which is simple and robust. The allocation of an average bit rate to data traffic at the expense of delay obviously improves the network bandwidth utilisation.

Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

Switching and generation of ultrashort pulses using all-fibre devices

Serial and parallel interconnection of photonic devices is integral to the construction of any all-optical data processing system. This thesis presents results from a series of experiments centering on the use of the nonlinear-optical loop mirror (NOLM) switch in architectures for the manipulation and generation of ultrashort pulses. Detailed analysis of soliton switching in a single NOLM and cascade of two NOLM's is performed, centering on primary limitations to device operation, effect of cascading on amplitude response, and impact of switching on the characteristics of incident pulses. By using relatively long input pulses, device failure due to stimulated Raman generation is postponed to demonstrate multiple-peaked switching for the first time. It is found that while cascading leads to a sharpening of the overall switching characteristic, pulse spectral and temporal integrity is not significantly degraded, and emerging pulses retain their essential soliton character. In addition, by including an asymmetrically placed in-fibre Bragg reflector as a wavelength selective loss element in the basic NOLM configuration, both soliton self-switching and dual-wavelength control-pulse switching are spectrally quantised. Results are presented from a novel dual-wavelength laser configuration generating pulse trains with an ultra-low rms inter-pulse-stream timing jitter level of 630fs enabling application in ultrafast switching environments at data rates as high as 130GBits/s. In addition, the fibre NOLM is included in architectures for all-optical memory, demonstrating storage and logical inversion of a 0.5kByte random data sequence; and ultrafast phase-locking of a gain-switched distributed feedback laser at 1.062GHz, the fourteenth harmonic of the system baseband frequency. The stringent requirements for environmental robustness of these architectures highlight the primary weaknesses of the NOLM in its fibre form and recommendations to overcome its inherent drawbacks are presented.

Gain switching of an external cavity grating-coupled surface emitting laser with wide tunability

The gain-switched, single frequency operation of an external cavity grating-coupled surface emitting laser with a wavelength tuning range of 100 nm was presented. The light in the grating section was coupled out of the laser at a specific angle to the surface of the device. Analysis showed that within the driving current range, lasing in the device only occurred when the external cavity was properly aligned.

Identifying and correcting non-Markov states in peptide conformational dynamics

Conformational transitions in proteins define their biological activity and can be investigated in detail using the Markov state model. The fundamental assumption on the transitions between the states, their Markov property, is critical in this framework. We test this assumption by analyzing the transitions obtained directly from the dynamics of a molecular dynamics simulated peptide valine-proline-alanine-leucine and states defined phenomenologically using clustering in dihedral space. We find that the transitions are Markovian at the time scale of ˜ 50 ps and longer. However, at the time scale of 30–40 ps the dynamics loses its Markov property. Our methodology reveals the mechanism that leads to non-Markov behavior. It also provides a way of regrouping the conformations into new states that now possess the required Markov property of their dynamics.

Maintenance of communication in primary classrooms : some evidence for the role of elicitation and code-switching in English medium schools in Kenya, with implications for teaching

This is a study of specific aspects of classroom interaction primary school level in Kenya. The study entailed the identification of the sources of particular communication problems during the change-over period from Kiswahili to English medium teaching in two primary schools. There was subsequently an examination of the language resources which were employed by teachers to maintain pupil participation in communication in the light of the occurrence of possibility of occurrence of specific communication problems. The language resources which were found to be significant in this regard concerned firstly the use of different elicitation types by teachers to stimulate pupils into giving responses and secondly teachers' recourse to code-switching from English to Kiswahili and vice-versa. It was also found in this study that although the use of English as the medium of instruction in the classrooms which were observed resulted in certain communication problems, some of these problems need not have arisen if teachers had been more careful in their use of language. The consideration of this finding, after taking into account the role of different elicitation types and code-switching as interpretable from data samples had certain implications which are specified in the study for teaching in Kenyan primary schools. The corpus for the study consisted of audio-recordings of English, Science and Number-Work lessons which were later transcribed. Relevant data samples were subsequently extracted from transcripts for analysis. Many of the samples have examples of cases of communication breakdowns, but they also illustrate how teachers maintained interaction with pupils who had yet to acquire an operational mastery of English. This study thus differs from most studies on classroom interaction because of its basic concern with the examination of the resources available to teachers for overcoming the problem areas of classroom communication.

Modelling data and voice traffic over IP networks using continuous-time Markov models

Common approaches to IP-traffic modelling have featured the use of stochastic models, based on the Markov property, which can be classified into black box and white box models based on the approach used for modelling traffic. White box models, are simple to understand, transparent and have a physical meaning attributed to each of the associated parameters. To exploit this key advantage, this thesis explores the use of simple classic continuous-time Markov models based on a white box approach, to model, not only the network traffic statistics but also the source behaviour with respect to the network and application. The thesis is divided into two parts: The first part focuses on the use of simple Markov and Semi-Markov traffic models, starting from the simplest two-state model moving upwards to n-state models with Poisson and non-Poisson statistics. The thesis then introduces the convenient to use, mathematically derived, Gaussian Markov models which are used to model the measured network IP traffic statistics. As one of the most significant contributions, the thesis establishes the significance of the second-order density statistics as it reveals that, in contrast to first-order density, they carry much more unique information on traffic sources and behaviour. The thesis then exploits the use of Gaussian Markov models to model these unique features and finally shows how the use of simple classic Markov models coupled with use of second-order density statistics provides an excellent tool for capturing maximum traffic detail, which in itself is the essence of good traffic modelling. The second part of the thesis, studies the ON-OFF characteristics of VoIP traffic with reference to accurate measurements of the ON and OFF periods, made from a large multi-lingual database of over 100 hours worth of VoIP call recordings. The impact of the language, prosodic structure and speech rate of the speaker on the statistics of the ON-OFF periods is analysed and relevant conclusions are presented. Finally, an ON-OFF VoIP source model with log-normal transitions is contributed as an ideal candidate to model VoIP traffic and the results of this model are compared with those of previously published work.

How habits, social ties, and economic switching barriers affect customer loyalty in contractual service settings

While existing literature acknowledges positive effects of satisfaction and economic switching barriers for building customer loyalty, studies analyzing interactions of these antecedents reveal mixed findings. Prior research does not consider, as antecedents of switching barriers, either habits or social ties that result from shared service-usage within a family or community. This paper contributes to the literature, first, by replicating the effects of satisfaction, economic switching barriers, and their interaction with customer loyalty and word-of-mouth of subscribers to a contractual service. Second, the study empirically tests the role of social ties as a social switching barrier. Third, the study introduces and tests the effects of habits as a precursor of economic and social switching barriers. Results reveal significant positive effects of satisfaction, economic switching barriers, and social ties on customer loyalty and word-of-mouth. Additionally, economic switching barriers and social ties interact significantly with satisfaction and habits act as a precursor of economic switching barriers and social ties.

Switching barriers in the four-stage loyalty model

Oliver (1997) suggests a four-stage loyalty model proposing that loyalty consists of belief, affect, intentions, and action. Although this model has recently been subject to empirical examination, the issue of moderator variables has been largely neglected. This article fills that void by analyzing the moderating effects of switching barriers, using a sample of 589 customers of a large do-it-yourself (DIY) retailer. The results suggest that these moderators exert an influence on the development of the different stages of the loyalty sequence. Specifically, switching costs, social benefits, and attractiveness of alternatives are found to be important moderators of the links in the four-stage loyalty model.

An accurate Markov model for slotted CSMA/CA algorithm in IEEE 802.15.4 networks

In this letter we propose an Markov model for slotted CSMA/CA algorithm working in a non-acknowledgement mode, specified in IEEE 802.15.4 standard. Both saturation throughput and energy consumption are modeled as functions of backoff window size, number of contending devices and frame length. Simulations show that the proposed model can achieve a very high accuracy (less than 1% mismatch) if compared to all existing models (bigger than 10% mismatch).

Time resolved bit error rate analysis of a fast switching tunable laser for use in optically switched networks

We investigate the use of different direct detection modulation formats in a wavelength switched optical network. We find the minimum time it takes a tunable sampled grating distributed Bragg reflector laser to recover after switching from one wavelength channel to another for different modulation formats. The recovery time is investigated utilizing a field programmable gate array which operates as a time resolved bit error rate detector. The detector offers 93 ps resolution operating at 10.7 Gb/s and allows for all the data received to contribute to the measurement, allowing low bit error rates to be measured at high speed. The recovery times for 10.7 Gb/s non-return-to-zero on–off keyed modulation, 10.7 Gb/s differentially phase shift keyed signal and 21.4 Gb/s differentially quadrature phase shift keyed formats can be as low as 4 ns, 7 ns and 40 ns, respectively. The time resolved phase noise associated with laser settling is simultaneously measured for 21.4 Gb/s differentially quadrature phase shift keyed data and it shows that the phase noise coupled with frequency error is the primary limitation on transmitting immediately after a laser switching event.

Alternate wavelength-switching in a dual-wavelength mode-locked fibre laser

We report a stable, dual-wavelength mode-locked fiber laser at 1 GHz with a wavelength spacing of 0.7 nm. Alternate switching between single and dual wavelength output was also achieved by simple adjustment of the pump power.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.