Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Image acquisition and manipulation protocols for CT-PET fusion to improve the accuracy of gross tumour volume localisation for 3D conformal radiotherapy for lung cancer

Aims: To develop clinical protocols for acquiring PET images, performing CT-PET registration and tumour volume definition based on the PET image data, for radiotherapy for lung cancer patients and then to test these protocols with respect to levels of accuracy and reproducibility. Method: A phantom-based quality assurance study of the processes associated with using registered CT and PET scans for tumour volume definition was conducted to: (1) investigate image acquisition and manipulation techniques for registering and contouring CT and PET images in a radiotherapy treatment planning system, and (2) determine technology-based errors in the registration and contouring processes. The outcomes of the phantom image based quality assurance study were used to determine clinical protocols. Protocols were developed for (1) acquiring patient PET image data for incorporation into the 3DCRT process, particularly for ensuring that the patient is positioned in their treatment position; (2) CT-PET image registration techniques and (3) GTV definition using the PET image data. The developed clinical protocols were tested using retrospective clinical trials to assess levels of inter-user variability which may be attributed to the use of these protocols. A Siemens Somatom Open Sensation 20 slice CT scanner and a Philips Allegro stand-alone PET scanner were used to acquire the images for this research. The Philips Pinnacle3 treatment planning system was used to perform the image registration and contouring of the CT and PET images. Results: Both the attenuation-corrected and transmission images obtained from standard whole-body PET staging clinical scanning protocols were acquired and imported into the treatment planning system for the phantom-based quality assurance study. Protocols for manipulating the PET images in the treatment planning system, particularly for quantifying uptake in volumes of interest and window levels for accurate geometric visualisation were determined. The automatic registration algorithms were found to have sub-voxel levels of accuracy, with transmission scan-based CT-PET registration more accurate than emission scan-based registration of the phantom images. Respiration induced image artifacts were not found to influence registration accuracy while inadequate pre-registration over-lap of the CT and PET images was found to result in large registration errors. A threshold value based on a percentage of the maximum uptake within a volume of interest was found to accurately contour the different features of the phantom despite the lower spatial resolution of the PET images. Appropriate selection of the threshold value is dependant on target-to-background ratios and the presence of respiratory motion. The results from the phantom-based study were used to design, implement and test clinical CT-PET fusion protocols. The patient PET image acquisition protocols enabled patients to be successfully identified and positioned in their radiotherapy treatment position during the acquisition of their whole-body PET staging scan. While automatic registration techniques were found to reduce inter-user variation compared to manual techniques, there was no significant difference in the registration outcomes for transmission or emission scan-based registration of the patient images, using the protocol. Tumour volumes contoured on registered patient CT-PET images using the tested threshold values and viewing windows determined from the phantom study, demonstrated less inter-user variation for the primary tumour volume contours than those contoured using only the patient’s planning CT scans. Conclusions: The developed clinical protocols allow a patient’s whole-body PET staging scan to be incorporated, manipulated and quantified in the treatment planning process to improve the accuracy of gross tumour volume localisation in 3D conformal radiotherapy for lung cancer. Image registration protocols which factor in potential software-based errors combined with adequate user training are recommended to increase the accuracy and reproducibility of registration outcomes. A semi-automated adaptive threshold contouring technique incorporating a PET windowing protocol, accurately defines the geometric edge of a tumour volume using PET image data from a stand alone PET scanner, including 4D target volumes.

Examining psychosocial influences on speeding in Australian and Chinese contexts : a social learning approach

Speeding remains a significant contributing factor to road trauma internationally, despite increasingly sophisticated speed management strategies being adopted around the world. Increases in travel speed are associated with increases in crash risk and crash severity. As speed choice is a voluntary behaviour, driver perceptions are important to our understanding of speeding and, importantly, to designing effective behavioural countermeasures. The four studies conducted in this program of research represent a comprehensive approach to examining psychosocial influences on driving speeds in two countries that are at very different levels of road safety development: Australia and China. Akers’ social learning theory (SLT) was selected as the theoretical framework underpinning this research and guided the development of key research hypotheses. This theory was chosen because of its ability to encompass psychological, sociological, and criminological perspectives in understanding behaviour, each of which has relevance to speeding. A mixed-method design was used to explore the personal, social, and legal influences on speeding among car drivers in Queensland (Australia) and Beijing (China). Study 1 was a qualitative exploration, via focus group interviews, of speeding among 67 car drivers recruited from south east Queensland. Participants were assigned to groups based on their age and gender, and additionally, according to whether they self-identified as speeding excessively or rarely. This study aimed to elicit information about how drivers conceptualise speeding as well as the social and legal influences on driving speeds. The findings revealed a wide variety of reasons and circumstances that appear to be used as personal justifications for exceeding speed limits. Driver perceptions of speeding as personally and socially acceptable, as well as safe and necessary were common. Perceptions of an absence of danger associated with faster driving speeds were evident, particularly with respect to driving alone. An important distinction between the speed-based groups related to the attention given to the driving task. Rare speeders expressed strong beliefs about the need to be mindful of safety (self and others) while excessive speeders referred to the driving task as automatic, an absent-minded endeavour, and to speeding as a necessity in order to remain alert and reduce boredom. For many drivers in this study, compliance with speed limits was expressed as discretionary rather than mandatory. Social factors, such as peer and parental influence were widely discussed in Study 1 and perceptions of widespread community acceptance of speeding were noted. In some instances, the perception that ‘everybody speeds’ appeared to act as one rationale for the need to raise speed limits. Self-presentation, or wanting to project a positive image of self was noted, particularly with respect to concealing speeding infringements from others to protect one’s image as a trustworthy and safe driver. The influence of legal factors was also evident. Legal sanctions do not appear to influence all drivers to the same extent. For instance, fear of apprehension appeared to play a role in reducing speeding for many, although previous experiences of detection and legal sanctions seemed to have had limited influence on reducing speeding among some drivers. Disregard for sanctions (e.g., driving while suspended), fraudulent demerit point use, and other strategies to avoid detection and punishment were widely and openly discussed. In Study 2, 833 drivers were recruited from roadside service stations in metropolitan and regional locations in Queensland. A quantitative research strategy assessed the relative contribution of personal, social, and legal factors to recent and future self-reported speeding (i.e., frequency of speeding and intentions to speed in the future). Multivariate analyses examining a range of factors drawn from SLT revealed that factors including self-identity (i.e., identifying as someone who speeds), favourable definitions (attitudes) towards speeding, personal experiences of avoiding detection and punishment for speeding, and perceptions of family and friends as accepting of speeding were all significantly associated with greater self-reported speeding. Study 3 was an exploratory, qualitative investigation of psychosocial factors associated with speeding among 35 Chinese drivers who were recruited from the membership of a motoring organisation and a university in Beijing. Six focus groups were conducted to explore similar issues to those examined in Study 1. The findings of Study 3 revealed many similarities with respect to the themes that arose in Australia. For example, there were similarities regarding personal justifications for speeding, such as the perception that posted limits are unreasonably low, the belief that individual drivers are able to determine safe travel speeds according to personal comfort with driving fast, and the belief that drivers possess adequate skills to control a vehicle at high speed. Strategies to avoid detection and punishment were also noted, though they appeared more widespread in China and also appeared, in some cases, to involve the use of a third party, a topic that was not reported by Australian drivers. Additionally, higher perceived enforcement tolerance thresholds were discussed by Chinese participants. Overall, the findings indicated perceptions of a high degree of community acceptance of speeding and a perceived lack of risk associated with speeds that were well above posted speed limits. Study 4 extended the exploratory research phase in China with a quantitative investigation involving 299 car drivers recruited from car washes in Beijing. Results revealed a relatively inexperienced sample with less than 5 years driving experience, on average. One third of participants perceived that the certainty of penalties when apprehended was low and a similar proportion of Chinese participants reported having previously avoided legal penalties when apprehended for speeding. Approximately half of the sample reported that legal penalties for speeding were ‘minimally to not at all’ severe. Multivariate analyses revealed that past experiences of avoiding detection and punishment for speeding, as well as favourable attitudes towards speeding, and perceptions of strong community acceptance of speeding were most strongly associated with greater self-reported speeding in the Chinese sample. Overall, the results of this research make several important theoretical contributions to the road safety literature. Akers’ social learning theory was found to be robust across cultural contexts with respect to speeding; similar amounts of variance were explained in self-reported speeding in the quantitative studies conducted in Australia and China. Historically, SLT was devised as a theory of deviance and posits that deviance and conformity are learned in the same way, with the balance of influence stemming from the ways in which behaviour is rewarded and punished (Akers, 1998). This perspective suggests that those who speed and those who do not are influenced by the same mechanisms. The inclusion of drivers from both ends of the ‘speeding spectrum’ in Study 1 provided an opportunity to examine the wider utility of SLT across the full range of the behaviour. One may question the use of a theory of deviance to investigate speeding, a behaviour that could, arguably, be described as socially acceptable and prevalent. However, SLT seemed particularly relevant to investigating speeding because of its inclusion of association, imitation, and reinforcement variables which reflect the breadth of factors already found to be potentially influential on driving speeds. In addition, driving is a learned behaviour requiring observation, guidance, and practice. Thus, the reinforcement and imitation concepts are particularly relevant to this behaviour. Finally, current speed management practices are largely enforcement-based and rely on the principles of behavioural reinforcement captured within the reinforcement component of SLT. Thus, the application of SLT to a behaviour such as speeding offers promise in advancing our understanding of the factors that influence speeding, as well as extending our knowledge of the application of SLT. Moreover, SLT could act as a valuable theoretical framework with which to examine other illegal driving behaviours that may not necessarily be seen as deviant by the community (e.g., mobile phone use while driving). This research also made unique contributions to advancing our understanding of the key components and the overall structure of Akers’ social learning theory. The broader SLT literature is lacking in terms of a thorough structural understanding of the component parts of the theory. For instance, debate exists regarding the relevance of, and necessity for including broader social influences in the model as captured by differential association. In the current research, two alternative SLT models were specified and tested in order to better understand the nature and extent of the influence of differential association on behaviour. Importantly, the results indicated that differential association was able to make a unique contribution to explaining self-reported speeding, thereby negating the call to exclude it from the model. The results also demonstrated that imitation was a discrete theoretical concept that should also be retained in the model. The results suggest a need to further explore and specify mechanisms of social influence in the SLT model. In addition, a novel approach was used to operationalise SLT variables by including concepts drawn from contemporary social psychological and deterrence-based research to enhance and extend the way that SLT variables have traditionally been examined. Differential reinforcement was conceptualised according to behavioural reinforcement principles (i.e., positive and negative reinforcement and punishment) and incorporated concepts of affective beliefs, anticipated regret, and deterrence-related concepts. Although implicit in descriptions of SLT, little research has, to date, made use of the broad range of reinforcement principles to understand the factors that encourage or inhibit behaviour. This approach has particular significance to road user behaviours in general because of the deterrence-based nature of many road safety countermeasures. The concept of self-identity was also included in the model and was found to be consistent with the definitions component of SLT. A final theoretical contribution was the specification and testing of a full measurement model prior to model testing using structural equation modelling. This process is recommended in order to reduce measurement error by providing an examination of the psychometric properties of the data prior to full model testing. Despite calls for such work for a number of decades, the current work appears to be the only example of a full measurement model of SLT. There were also a number of important practical implications that emerged from this program of research. Firstly, perceptions regarding speed enforcement tolerance thresholds were highlighted as a salient influence on driving speeds in both countries. The issue of enforcement tolerance levels generated considerable discussion among drivers in both countries, with Australian drivers reporting lower perceived tolerance levels than Chinese drivers. It was clear that many drivers used the concept of an enforcement tolerance in determining their driving speed, primarily with the desire to drive faster than the posted speed limit, yet remaining within a speed range that would preclude apprehension by police. The quantitative results from Studies 2 and 4 added support to these qualitative findings. Together, the findings supported previous research and suggested that a travel speed may not be seen as illegal until that speed reaches a level over the prescribed enforcement tolerance threshold. In other words, the enforcement tolerance appears to act as a ‘de facto’ speed limit, replacing the posted limit in the minds of some drivers. The findings from the two studies conducted in China (Studies 2 and 4) further highlighted the link between perceived enforcement tolerances and a ‘de facto’ speed limit. Drivers openly discussed driving at speeds that were well above posted speed limits and some participants noted their preference for driving at speeds close to ‘50% above’ the posted limit. This preference appeared to be shaped by the perception that the same penalty would be imposed if apprehended, irrespective of what speed they travelling (at least up to 50% above the limit). Further research is required to determine whether the perceptions of Chinese drivers are mainly influenced by the Law of the People’s Republic of China or by operational practices. Together, the findings from both studies in China indicate that there may be scope to refine enforcement tolerance levels, as has happened in other jurisdictions internationally over time, in order to reduce speeding. Any attempts to do so would likely be assisted by the provision of information about the legitimacy and purpose of speed limits as well as risk factors associated with speeding because these issues were raised by Chinese participants in the qualitative research phase. Another important practical implication of this research for speed management in China is the way in which penalties are determined. Chinese drivers described perceptions of unfairness and a lack of transparency in the enforcement system because they were unsure of the penalty that they would receive if apprehended. Steps to enhance the perceived certainty and consistency of the system to promote a more equitable approach to detection and punishment would appear to be welcomed by the general driving public and would be more consistent with the intended theoretical (deterrence) basis that underpins the current speed enforcement approach. The use of mandatory, fixed penalties may assist in this regard. In many countries, speeding attracts penalties that are dependent on the severity of the offence. In China, there may be safety benefits gained from the introduction of a similar graduated scale of speeding penalties and fixed penalties might also help to address the issue of uncertainty about penalties and related perceptions of unfairness. Such advancements would be in keeping with the principles of best practice for speed management as identified by the World Health Organisation. Another practical implication relating to legal penalties, and applicable to both cultural contexts, relates to the issues of detection and punishment avoidance. These two concepts appeared to strongly influence speeding in the current samples. In Australia, detection avoidance strategies reported by participants generally involved activities that are not illegal (e.g., site learning and remaining watchful for police vehicles). The results from China were similar, although a greater range of strategies were reported. The most common strategy reported in both countries for avoiding detection when speeding was site learning, or familiarisation with speed camera locations. However, a range of illegal practices were also described by Chinese drivers (e.g., tampering with or removing vehicle registration plates so as to render the vehicle unidentifiable on camera and use of in-vehicle radar detectors). With regard to avoiding punishment when apprehended, a range of strategies were reported by drivers from both countries, although a greater range of strategies were reported by Chinese drivers. As the results of the current research indicated that detection avoidance was strongly associated with greater self-reported speeding in both samples, efforts to reduce avoidance opportunities are strongly recommended. The practice of randomly scheduling speed camera locations, as is current practice in Queensland, offers one way to minimise site learning. The findings of this research indicated that this practice should continue. However, they also indicated that additional strategies are needed to reduce opportunities to evade detection. The use of point-to-point speed detection (also known as sectio

Structural health monitoring : vibration-based damage detection and condition assessment of bridges

Structural health is a vital aspect of infrastructure sustainability. As a part of a vital infrastructure and transportation network, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs are a difficult burden for infrastructure owners. The structural health monitoring (SHM) systems proposed recently are incorporated with vibration-based damage detection techniques, statistical methods and signal processing techniques and have been regarded as efficient and economical ways to assess bridge condition and foresee probable costly failures. In this chapter, the recent developments in damage detection and condition assessment techniques based on vibration-based damage detection and statistical methods are reviewed. The vibration-based damage detection methods based on changes in natural frequencies, curvature or strain modes, modal strain energy, dynamic flexibility, artificial neural networks, before and after damage, and other signal processing methods such as Wavelet techniques, empirical mode decomposition and Hilbert spectrum methods are discussed in this chapter.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Coding speech signals at very low rates (below 1 kb/s) with high intelligibility

This thesis presents an original approach to parametric speech coding at rates below 1 kbitsjsec, primarily for speech storage applications. Essential processes considered in this research encompass efficient characterization of evolutionary configuration of vocal tract to follow phonemic features with high fidelity, representation of speech excitation using minimal parameters with minor degradation in naturalness of synthesized speech, and finally, quantization of resulting parameters at the nominated rates. For encoding speech spectral features, a new method relying on Temporal Decomposition (TD) is developed which efficiently compresses spectral information through interpolation between most steady points over time trajectories of spectral parameters using a new basis function. The compression ratio provided by the method is independent of the updating rate of the feature vectors, hence allows high resolution in tracking significant temporal variations of speech formants with no effect on the spectral data rate. Accordingly, regardless of the quantization technique employed, the method yields a high compression ratio without sacrificing speech intelligibility. Several new techniques for improving performance of the interpolation of spectral parameters through phonetically-based analysis are proposed and implemented in this research, comprising event approximated TD, near-optimal shaping event approximating functions, efficient speech parametrization for TD on the basis of an extensive investigation originally reported in this thesis, and a hierarchical error minimization algorithm for decomposition of feature parameters which significantly reduces the complexity of the interpolation process. Speech excitation in this work is characterized based on a novel Multi-Band Excitation paradigm which accurately determines the harmonic structure in the LPC (linear predictive coding) residual spectra, within individual bands, using the concept 11 of Instantaneous Frequency (IF) estimation in frequency domain. The model yields aneffective two-band approximation to excitation and computes pitch and voicing with high accuracy as well. New methods for interpolative coding of pitch and gain contours are also developed in this thesis. For pitch, relying on the correlation between phonetic evolution and pitch variations during voiced speech segments, TD is employed to interpolate the pitch contour between critical points introduced by event centroids. This compresses pitch contour in the ratio of about 1/10 with negligible error. To approximate gain contour, a set of uniformly-distributed Gaussian event-like functions is used which reduces the amount of gain information to about 1/6 with acceptable accuracy. The thesis also addresses a new quantization method applied to spectral features on the basis of statistical properties and spectral sensitivity of spectral parameters extracted from TD-based analysis. The experimental results show that good quality speech, comparable to that of conventional coders at rates over 2 kbits/sec, can be achieved at rates 650-990 bits/sec.

Adaptive instantaneous frequency estimation: Techniques and algorithms

This thesis deals with the problem of the instantaneous frequency (IF) estimation of sinusoidal signals. This topic plays significant role in signal processing and communications. Depending on the type of the signal, two major approaches are considered. For IF estimation of single-tone or digitally-modulated sinusoidal signals (like frequency shift keying signals) the approach of digital phase-locked loops (DPLLs) is considered, and this is Part-I of this thesis. For FM signals the approach of time-frequency analysis is considered, and this is Part-II of the thesis. In part-I we have utilized sinusoidal DPLLs with non-uniform sampling scheme as this type is widely used in communication systems. The digital tanlock loop (DTL) has introduced significant advantages over other existing DPLLs. In the last 10 years many efforts have been made to improve DTL performance. However, this loop and all of its modifications utilizes Hilbert transformer (HT) to produce a signal-independent 90-degree phase-shifted version of the input signal. Hilbert transformer can be realized approximately using a finite impulse response (FIR) digital filter. This realization introduces further complexity in the loop in addition to approximations and frequency limitations on the input signal. We have tried to avoid practical difficulties associated with the conventional tanlock scheme while keeping its advantages. A time-delay is utilized in the tanlock scheme of DTL to produce a signal-dependent phase shift. This gave rise to the time-delay digital tanlock loop (TDTL). Fixed point theorems are used to analyze the behavior of the new loop. As such TDTL combines the two major approaches in DPLLs: the non-linear approach of sinusoidal DPLL based on fixed point analysis, and the linear tanlock approach based on the arctan phase detection. TDTL preserves the main advantages of the DTL despite its reduced structure. An application of TDTL in FSK demodulation is also considered. This idea of replacing HT by a time-delay may be of interest in other signal processing systems. Hence we have analyzed and compared the behaviors of the HT and the time-delay in the presence of additive Gaussian noise. Based on the above analysis, the behavior of the first and second-order TDTLs has been analyzed in additive Gaussian noise. Since DPLLs need time for locking, they are normally not efficient in tracking the continuously changing frequencies of non-stationary signals, i.e. signals with time-varying spectra. Nonstationary signals are of importance in synthetic and real life applications. An example is the frequency-modulated (FM) signals widely used in communication systems. Part-II of this thesis is dedicated for the IF estimation of non-stationary signals. For such signals the classical spectral techniques break down, due to the time-varying nature of their spectra, and more advanced techniques should be utilized. For the purpose of instantaneous frequency estimation of non-stationary signals there are two major approaches: parametric and non-parametric. We chose the non-parametric approach which is based on time-frequency analysis. This approach is computationally less expensive and more effective in dealing with multicomponent signals, which are the main aim of this part of the thesis. A time-frequency distribution (TFD) of a signal is a two-dimensional transformation of the signal to the time-frequency domain. Multicomponent signals can be identified by multiple energy peaks in the time-frequency domain. Many real life and synthetic signals are of multicomponent nature and there is little in the literature concerning IF estimation of such signals. This is why we have concentrated on multicomponent signals in Part-H. An adaptive algorithm for IF estimation using the quadratic time-frequency distributions has been analyzed. A class of time-frequency distributions that are more suitable for this purpose has been proposed. The kernels of this class are time-only or one-dimensional, rather than the time-lag (two-dimensional) kernels. Hence this class has been named as the T -class. If the parameters of these TFDs are properly chosen, they are more efficient than the existing fixed-kernel TFDs in terms of resolution (energy concentration around the IF) and artifacts reduction. The T-distributions has been used in the IF adaptive algorithm and proved to be efficient in tracking rapidly changing frequencies. They also enables direct amplitude estimation for the components of a multicomponent

Modelling photochemical production of fine particulates in a toluene/NOx/water vapour system

This work investigates the computer modelling of the photochemical formation of smog products such as ozone and aerosol, in a system containing toluene, NOx and water vapour. In particular, the problem of modelling this process in the Commonwealth Scientific and Industrial Research Organization (CSIRO) smog chambers, which utilize outdoor exposure, is addressed. The primary requirement for such modelling is a knowledge of the photolytic rate coefficients. Photolytic rate coefficients of species other than N02 are often related to JNo2 (rate coefficient for the photolysis ofN02) by a simple factor, but for outdoor chambers, this method is prone to error as the diurnal profiles may not be similar in shape. Three methods for the calculation of diurnal JNo2 are investigated. The most suitable method for incorporation into a general model, is found to be one which determines the photolytic rate coefficients for N02, as well as several other species, from actinic flux, absorption cross section and quantum yields. A computer model was developed, based on this method, to calculate in-chamber photolysis rate coefficients for the CSIRO smog chambers, in which ex-chamber rate coefficients are adjusted by accounting for variation in light intensity by transmittance through the Teflon walls, albedo from the chamber floor and radiation attenuation due to clouds. The photochemical formation of secondary aerosol is investigated in a series of toluene-NOx experiments, which were performed in the CSIRO smog chambers. Three stages of aerosol formation, in plots of total particulate volume versus time, are identified: a delay period in which no significant mass of aerosol is formed, a regime of rapid aerosol formation (regime 1) and a second regime of slowed aerosol formation (regime 2). Two models are presented which were developed from the experimental data. One model is empirically based on observations of discrete stages of aerosol formation and readily allows aerosol growth profiles to be calculated. The second model is based on an adaptation of published toluene photooxidation mechanisms and provides some chemical information about the oxidation products. Both models compare favorably against the experimental data. The gross effects of precursor concentrations (toluene, NOx and H20) and ambient conditions (temperature, photolysis rate) on the formation of secondary aerosol are also investigated, primarily using the mechanism model. An increase in [NOx]o results in increased delay time, rate of aerosol formation in regime 1 and volume of aerosol formed in regime 1. This is due to increased formation of dinitrocresol and furanone products. An increase in toluene results in a decrease in the delay time and an increase in the rate of aerosol formation in regime 1, due to enhanced reactivity from the toluene products, such as the radicals from the photolysis of benzaldehyde. Water vapor has very little effect on the formation of aerosol volume, except that rates are slightly increased due to more OH radicals from reaction with 0(1D) from ozone photolysis. Increased temperature results in increased volume of aerosol formed in regime 1 (increased dinitrocresol formation), while increased photolysis rate results in increased rate of aerosol formation in regime 1. Both the rate and volume of aerosol formed in regime 2 are increased by increased temperature or photolysis rate. Both models indicate that the yield of secondary particulates from hydrocarbons (mass concentration aerosol formed/mass concentration hydrocarbon precursor) is proportional to the ratio [NOx]0/[hydrocarbon]0