High power pulses generation is one of the major topics discussed in the thesis. Although gain switching is the simplest way for ultrashort pulse generation, it proves to be quite effective to deliver high energy pulses on condition that the pumping pulses with extremely fast rising time and high enough amplitude are applied on specially designed pulse generators. In the experiment on a grating-coupled surface emitting laser (GCSEL), peak power as high as 1W was achieved even when its spectral bandwidth was controlled within 0.2nm. Another experiment shows violet picosecond pulses with peak power as high as 7W was achieved when the intensive electrical pulses were applied on optimised DC bias to pump on InGaN violet diode laser. The physical mechanism of this phenomenon, as we considered, may attributed to the self-organised quantum dots structure in the laser. Control of pulse quality, including spectral quality and temporal profile, is an important issue for high power pulse generation. The ways to control pulse quality described in the thesis are also based on simple and effective techniques. For instance, GCSEL used in our experiment has a specially designed air-grating structure for out-coupling of optical signals; hence, a tiny flat aluminium mirror was placed closed to the grating section and resulted in a wavelength tuning range over 100nm and the best side band suppression ratio of 40dB. Self-seeding, as an effective technique for spectral control of pulsed lasers, was demonstrated for the first time in a violet diode laser. In addition, control of temporal profile of the pulse is demonstrated in an overdriven DFB laser. Wavelength tuneable fibre Bragg gratings were used to tailor the huge energy tail of the high power pulse. The whole system was compact and robust. The ultimate purpose of our study is to design a new family of compact ultrafast diode lasers. Some practical ideas of laser design based on gain-switched and Q-switched devices are also provided in the end.

Surface compositional changes in GaAs due to RF plasmas of different gases have been investigated by XPS and etch rates were measured using AFM. Angular Resolved XPS (ARXPS) was also employed for depth analysis of the composition of the surface layers. An important role in this study was determination of oxide thickness using XPS data. The study of surface - plasma interaction was undertaken by correlating results of surface analysis with plasma diagnosis. Different experiments were designed to accurately measure the BEs associated with the Ga 3d, Ga 2P3/2 and LMM peaks using XPS analysis and propose identification in terms of the oxides of GaAs. Along with GaAs wafers, some reference compounds such as metallic Ga and Ga2O3 powder were used. A separate study aiming the identification of the GaAs surface oxides formed on the GaAs surface during and after plasma processing was undertaken. Surface compositional changes after plasma treatment, prior to surface analysis are considered, with particular reference to the oxides formed in the air on the activated surface. Samples exposed to ambient air for different periods of time and also to pure oxygen were analysed. Models of surface processes were proposed for explanation of the stoichiometry changes observed with the inert and reactive plasmas used. In order to help with the understanding of the mechanisms responsible for surface effects during plasma treatment, computer simulation using SRIM code was also undertaken. Based on simulation and experimental results, models of surface phenomena are proposed. Discussion of the experimental and simulated results is made in accordance with current theories and published results of different authors. The experimental errors introduced by impurities and also by data acquisition and processing are also evaluated.

There is an increasing emphasis on the use of software to control safety critical plants for a wide area of applications. The importance of ensuring the correct operation of such potentially hazardous systems points to an emphasis on the verification of the system relative to a suitably secure specification. However, the process of verification is often made more complex by the concurrency and real-time considerations which are inherent in many applications. A response to this is the use of formal methods for the specification and verification of safety critical control systems. These provide a mathematical representation of a system which permits reasoning about its properties. This thesis investigates the use of the formal method Communicating Sequential Processes (CSP) for the verification of a safety critical control application. CSP is a discrete event based process algebra which has a compositional axiomatic semantics that supports verification by formal proof. The application is an industrial case study which concerns the concurrent control of a real-time high speed mechanism. It is seen from the case study that the axiomatic verification method employed is complex. It requires the user to have a relatively comprehensive understanding of the nature of the proof system and the application. By making a series of observations the thesis notes that CSP possesses the scope to support a more procedural approach to verification in the form of testing. This thesis investigates the technique of testing and proposes the method of Ideal Test Sets. By exploiting the underlying structure of the CSP semantic model it is shown that for certain processes and specifications the obligation of verification can be reduced to that of testing the specification over a finite subset of the behaviours of the process.

The increasing demand for high capacity data storage requires decreasing the head-to-tape gap and reducing the track width. A problem very often encountered is the development of adhesive debris on the heads at low humidity and high temperatures that can lead to an increase of space between the head and media, and thus a decrease in the playback signal. The influence of stains on the playback signal of reading heads is studied using RAW (Read After Write) tests and their influence on the wear of the heads by using indentation technique. The playback signal has been found to vary and the errors to increase as stains form a patchy pattern and grow in size to form a continuous layer. The indentation technique shows that stains reduce the wear rate of the heads. In addition, the wear tends to be more pronounced at the leading edge of the head compared to the trailing one. Chemical analysis of the stains using ferrite samples in conjunction with MP (metal particulate) tapes shows that stains contain iron particles and polymeric binder transferred from the MP tape. The chemical anchors in the binder used to grip the iron particles now react with the ferrite surface to create strong chemical bonds. At high humidity, a thin layer of iron oxyhydroxide forms on the surface of the ferrite. This soft material increases the wear rate and so reduces the amount of stain present on the heads. The stability of the binder under high humidity and under high temperature as well as the chemical reactions that might occur on the ferrite poles of the heads influences the dynamic behaviour of stains. A model of stain formation taking into account the channels of binder degradation and evolution upon different environmental conditions is proposed.

Firstly, dispersion-managed (DM) solitons in fibre lines employing a weak dispersion map are analysed by means of a perturbation approach. In the case of small dispersion map strengths the average pulse dynamics is described by a perturbation approach (NLS) equation. Applying a perturbation theory, based on the Inverse Scattering Transform method, an analytic expression for the envelope of the DM soliton is derived. This expression correctly predicts the power enhancement arising from the dispersion management. Secondly, autosoliton transmission in DM fibre systems with periodical in-line deployment of nonlinear optical loop mirrors (NOLMs) is investigated. The use of in-line NOLMs is addressed as a general technique for all-optical passive 2R regeneration of return-to-zero data in high speed transmission system with strong dispersion management. By system optimisation, the feasibility of ultra-long single-channel and wavelength-division multiplexed data transmission at bit-rates ³ 40 Gbit s-1 in standard fibre-based systems is demonstrated. The tolerance limits of the results are defined. Thirdly, solutions of the NLS equation with gain and normal dispersion, that describes optical pulse propagation in an amplifying medium, are examined. A self-similar parabolic solution in the energy-containing core of the pulse is matched through Painlevé functions to the linear low-amplitude tails. The analysis provides a full description of the features of high-power pulses generated in an amplifying medium.

The development of reconfigurable antennas is considered to be very promising in modern and future communication systems. Reconfigurable antennas have made use of many reconfiguration techniques that are centred upon switching mechanisms such as p-i-n diodes or MEMS. Other techniques such as optical switches, mechanical structure changing or the ability to change the permeability or permittivity of smart substrate materials have also been used. Reconfigurable antennas have created new horizons for many types of applications especially in Cognitive Radio, Multiple Input Multiple Output Systems, personal communication systems, satellites and many other applications. Cognitive Radio is one of the potential wireless applications that may place severe demands on RF systems designers and particularly antenna designers, when it comes to providing exible radio front-ends capable of achieving the set objectives of the technology. The aim of this work is to investigate possible roles that different categories of reconfigurable antenna can play in cognitive and smart radio. Hence, the research described in this thesis focuses on investigating some novel methods to frequency-reconfigure compact ultra-wideband antennas to work in different bands; this will offer additional filtering to the radio front-end. In the ultra-wideband mode, the antenna senses the spectrum for available bands with less congestion and interference and hence decides on the most suitable part to be reconfigured to, allowing reliable and efficient communication links between the radio devices. Ultra-wideband antenna with reconfigurable integrated notch capability is also demonstrated to provide further enhancement to interference rejection and improve the overall communication link. Furthermore, the design of novel pattern and polarisation reconfigurable antennas will be also investigated to assist Cognitive Radio through spatial rather than frequency means. An ultimate target for this research is to combine different degrees of reconfiguration into one compact, state of the art antenna design that meets the growing demand of cognitive and smart radio devices for more intelligent and multi-functional wireless devices within the personal area network domains and beyond.

The work described in this thesis provides an optical study of pre-breakdown events in liquid dielectrics. A small scale rig employing a 50SI test cell with viewing windows, as part of a high voltage co-axial line, enabled short rise time pulses to be applied to a non-uniform test gap. For the liquid dielectric, changes of refractive index resulting from applied voltage were rendered visible by means of a Schlieren optical system. A high speed image converter camera enabled rapidly changing pre-breakdown phenomena to be photographically recorded at framing speeds up to 107 per second. Scattered light photographs were taken by orthogonal flash illumination under both pulse and direct voltage conditions, allowing large format macrophotography. Using a piezoelectric transducer placed within the test cell, and a photomultiplier to view the gap region, a relationship has also been established between the generation of mechanical waves, light scintillation and conduction current pulses. From the photographic records and conventional parameter measurements there exists strong evidence for the presence of a gaseous phase in processes leading to the electrical breakdown of liquid dielectrics even under pulse conditions.

This thesis presents an automated framework for activity analysis in multi-camera setups. We start with the calibration of cameras particularly without overlapping views. An algorithm is presented that exploits trajectory observations in each view and works iteratively on camera pairs. First outliers are identified and removed from observations of each camera. Next, spatio-temporal information derived from the available trajectory is used to estimate unobserved trajectory segments in areas uncovered by the cameras. The unobserved trajectory estimates are used to estimate the relative position of each camera pair, whereas the exit-entrance direction of each object is used to estimate their relative orientation. The process continues and iteratively approximates the configuration of all cameras with respect to each other. Finally, we refi ne the initial configuration estimates with bundle adjustment, based on the observed and estimated trajectory segments. For cameras with overlapping views, state-of-the-art homography based approaches are used for calibration. Next we establish object correspondence across multiple views. Our algorithm consists of three steps, namely association, fusion and linkage. For association, local trajectory pairs corresponding to the same physical object are estimated using multiple spatio-temporal features on a common ground plane. To disambiguate spurious associations, we employ a hybrid approach that utilises the matching results on the image plane and ground plane. The trajectory segments after association are fused by adaptive averaging. Trajectory linkage then integrates segments and generates a single trajectory of an object across the entire observed area. Finally, for activities analysis clustering is applied on complete trajectories. Our clustering algorithm is based on four main steps, namely the extraction of a set of representative trajectory features, non-parametric clustering, cluster merging and information fusion for the identification of normal and rare object motion patterns. First we transform the trajectories into a set of feature spaces on which Meanshift identi es the modes and the corresponding clusters. Furthermore, a merging procedure is devised to re fine these results by combining similar adjacent clusters. The fi nal common patterns are estimated by fusing the clustering results across all feature spaces. Clusters corresponding to reoccurring trajectories are considered as normal, whereas sparse trajectories are associated to abnormal and rare events. The performance of the proposed framework is evaluated on standard data-sets and compared with state-of-the-art techniques. Experimental results show that the proposed framework outperforms state-of-the-art algorithms both in terms of accuracy and robustness.

Performance Measurement of the IP packet networks mainly comprise of monitoring the network performance in terms of packet losses and delays. If used appropriately, these network parameters (i.e. delay, loss and bandwidth etc) can indicate the performance status of the network and they can be used in fault and performance monitoring, network provisioning, and traffic engineering. Globally, there is a growing need for accurate network measurement to support the commercial use of IP networks. In wireless networks, transmission losses and communication delays strongly affect the performance of the network. Compared to wired networks, wireless networks experience higher levels of data dropouts, and corruption due to issues of channel fading, noise, interference and mobility. Performance monitoring is a vital element in the commercial future of broadband packet networking and the ability to guarantee quality of service in such networks is implicit in Service Level Agreements. Active measurements are performed by injecting probes, and this is widely used to determine the end to end performance. End to end delay in wired networks has been extensively investigated, and in this thesis we report on the accuracy achieved by probing for end to end delay over a wireless scenario. We have compared two probing techniques i.e. Periodic and Poisson probing, and estimated the absolute error for both. The simulations have been performed for single hop and multi- hop wireless networks. In addition to end to end latency, Active measurements have also been performed for packet loss rate. The simulation based analysis has been tried under different traffic scenarios using Poisson Traffic Models. We have sampled the user traffic using Periodic probing at different rates for single hop and multiple hop wireless scenarios. 5 Active probing becomes critical at higher values of load forcing the network to saturation much earlier. We have evaluated the impact of monitoring overheads on the user traffic, and show that even small amount of probing overhead in a wireless medium can cause large degradation in network performance. Although probing at high rate provides a good estimation of delay distribution of user traffic with large variance yet there is a critical tradeoff between the accuracy of measurement and the packet probing overhead. Our results suggest that active probing is highly affected by probe size, rate, pattern, traffic load, and nature of shared medium, available bandwidth and the burstiness of the traffic.

The method of using Fuzzy Sets Theory(FST) and Fuzzy Reasoning(FR) to aid reliability evaluation in a complex and uncertain environment is studied, with special reference to electrical power generating system reliability evaluation. Device(component) reliability prediction contributes significantly to a system's reliability through their ability to identify source and causes of unreliability. The main factors which affect reliability are identified in Reliability Prediction Process(RPP). However, the relation between reliability and each affecting factor is not a necessary and sufficient one. It is difficult to express this kind of relation precisely in terms of quantitative mathematics. It is acknowledged that human experts possesses some special characteristics that enable them to learn and reason in a vague and fuzzy environment based on their experience. Therefore, reliability prediction can be classified as a human engineer oriented decision process. A fuzzy knowledge based reliability prediction framework, in which speciality rather than generality is emphasised, is proposed in the first part of the thesis. For this purpose, various factors affected device reliability are investigated and the knowledge trees for predicting three reliability indices, i.e. failure rate, maintenance time and human error rate are presented. Human experts' empirical and heuristic knowledge are represented by fuzzy linguistic rules and fuzzy compositional rule of inference is employed as inference tool. Two approaches to system reliability evaluation are presented in the second part of this thesis. In first approach, fuzzy arithmetic are conducted as the foundation for system reliability evaluation under the fuzzy envimnment The objective is to extend the underlying fuzzy concept into strict mathematics framework in order to arrive at decision on system adequacy based on imprecise and qualitative information. To achieve this, various reliability indices are modelled as Trapezoidal Fuzzy Numbers(TFN) and are proceeded by extended fuzzy arithmetic operators. In second approach, the knowledge of system reliability evaluation are modelled in the form of fuzzy combination production rules and device combination sequence control algorithm. System reliability are evaluated by using fuzzy inference system. Comparison of two approaches are carried out through case studies. As an application, power generating system reliability adequacy is studied. Under the assumption that both unit reliability data and load data are subjectively estimated, these fuzzy data are modelled as triangular fuzzy numbers, fuzzy capacity outage model and fuzzy load model are developed by using fuzzy arithmetic operations. Power generating system adequacy is evaluated by convoluting fuzzy capacity outage model with fuzzy load model. A fuzzy risk index named "Possibility Of Load Loss" (POLL) is defined based on the concept of fuzzy containment The proposed new index is tested on IEEE Reliability Test System (RTS) and satisfactory results are obtained Finally, the implementation issues of Fuzzy Rule Based Expert System Shell (FRBESS) are reported. The application of ERBESS to device reliability prediction and system reliability evaluation is discussed.