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.

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

Swept frequency biompedance analysis for the determination of body water compartments

Bioelectrical impedance analysis, (BIA), is a method of body composition analysis first investigated in 1962 which has recently received much attention by a number of research groups. The reasons for this recent interest are its advantages, (viz: inexpensive, non-invasive and portable) and also the increasing interest in the diagnostic value of body composition analysis. The concept utilised by BIA to predict body water volumes is the proportional relationship for a simple cylindrical conductor, (volume oc length2/resistance), which allows the volume to be predicted from the measured resistance and length. Most of the research to date has measured the body's resistance to the passage of a 50· kHz AC current to predict total body water, (TBW). Several research groups have investigated the application of AC currents at lower frequencies, (eg 5 kHz), to predict extracellular water, (ECW). However all research to date using BIA to predict body water volumes has used the impedance measured at a discrete frequency or frequencies. This thesis investigates the variation of impedance and phase of biological systems over a range of frequencies and describes the development of a swept frequency bioimpedance meter which measures impedance and phase at 496 frequencies ranging from 4 kHz to 1 MHz. The impedance of any biological system varies with the frequency of the applied current. The graph of reactance vs resistance yields a circular arc with the resistance decreasing with increasing frequency and reactance increasing from zero to a maximum then decreasing to zero. Computer programs were written to analyse the measured impedance spectrum and determine the impedance, Zc, at the characteristic frequency, (the frequency at which the reactance is a maximum). The fitted locus of the measured data was extrapolated to determine the resistance, Ro, at zero frequency; a value that cannot be measured directly using surface electrodes. The explanation of the theoretical basis for selecting these impedance values (Zc and Ro), to predict TBW and ECW is presented. Studies were conducted on a group of normal healthy animals, (n=42), in which TBW and ECW were determined by the gold standard of isotope dilution. The prediction quotients L2/Zc and L2/Ro, (L=length), yielded standard errors of 4.2% and 3.2% respectively, and were found to be significantly better than previously reported, empirically determined prediction quotients derived from measurements at a single frequency. The prediction equations established in this group of normal healthy animals were applied to a group of animals with abnormally low fluid levels, (n=20), and also to a group with an abnormal balance of extra-cellular to intracellular fluids, (n=20). In both cases the equations using L2/Zc and L2/Ro accurately and precisely predicted TBW and ECW. This demonstrated that the technique developed using multiple frequency bioelectrical impedance analysis, (MFBIA), can accurately predict both TBW and ECW in both normal and abnormal animals, (with standard errors of the estimate of 6% and 3% for TBW and ECW respectively). Isotope dilution techniques were used to determine TBW and ECW in a group of 60 healthy human subjects, (male. and female, aged between 18 and 45). Whole body impedance measurements were recorded on each subject using the MFBIA technique and the correlations between body water volumes, (TBW and ECW), and heighe/impedance, (for all measured frequencies), were compared. The prediction quotients H2/Zc and H2/Ro, (H=height), again yielded the highest correlation with TBW and ECW respectively with corresponding standard errors of 5.2% and 10%. The values of the correlation coefficients obtained in this study were very similar to those recently reported by others. It was also observed that in healthy human subjects the impedance measured at virtually any frequency yielded correlations not significantly different from those obtained from the MFBIA quotients. This phenomenon has been reported by other research groups and emphasises the need to validate the technique by investigating its application in one or more groups with abnormalities in fluid levels. The clinical application of MFBIA was trialled and its capability of detecting lymphoedema, (an excess of extracellular fluid), was investigated. The MFBIA technique was demonstrated to be significantly more sensitive, (P<.05), in detecting lymphoedema than the current technique of circumferential measurements. MFBIA was also shown to provide valuable information describing the changes in the quantity of muscle mass of the patient during the course of the treatment. The determination of body composition, (viz TBW and ECW), by MFBIA has been shown to be a significant improvement on previous bioelectrical impedance techniques. The merit of the MFBIA technique is evidenced in its accurate, precise and valid application in animal groups with a wide variation in body fluid volumes and balances. The multiple frequency bioelectrical impedance analysis technique developed in this study provides accurate and precise estimates of body composition, (viz TBW and ECW), regardless of the individual's state of health.

Modelling of some biological materials using continuum mechanics

Continuum mechanics provides a mathematical framework for modelling the physical stresses experienced by a material. Recent studies show that physical stresses play an important role in a wide variety of biological processes, including dermal wound healing, soft tissue growth and morphogenesis. Thus, continuum mechanics is a useful mathematical tool for modelling a range of biological phenomena. Unfortunately, classical continuum mechanics is of limited use in biomechanical problems. As cells refashion the �bres that make up a soft tissue, they sometimes alter the tissue's fundamental mechanical structure. Advanced mathematical techniques are needed in order to accurately describe this sort of biological `plasticity'. A number of such techniques have been proposed by previous researchers. However, models that incorporate biological plasticity tend to be very complicated. Furthermore, these models are often di�cult to apply and/or interpret, making them of limited practical use. One alternative approach is to ignore biological plasticity and use classical continuum mechanics. For example, most mechanochemical models of dermal wound healing assume that the skin behaves as a linear viscoelastic solid. Our analysis indicates that this assumption leads to physically unrealistic results. In this thesis we present a novel and practical approach to modelling biological plasticity. Our principal aim is to combine the simplicity of classical linear models with the sophistication of plasticity theory. To achieve this, we perform a careful mathematical analysis of the concept of a `zero stress state'. This leads us to a formal de�nition of strain that is appropriate for materials that undergo internal remodelling. Next, we consider the evolution of the zero stress state over time. We develop a novel theory of `morphoelasticity' that can be used to describe how the zero stress state changes in response to growth and remodelling. Importantly, our work yields an intuitive and internally consistent way of modelling anisotropic growth. Furthermore, we are able to use our theory of morphoelasticity to develop evolution equations for elastic strain. We also present some applications of our theory. For example, we show that morphoelasticity can be used to obtain a constitutive law for a Maxwell viscoelastic uid that is valid at large deformation gradients. Similarly, we analyse a morphoelastic model of the stress-dependent growth of a tumour spheroid. This work leads to the prediction that a tumour spheroid will always be in a state of radial compression and circumferential tension. Finally, we conclude by presenting a novel mechanochemical model of dermal wound healing that takes into account the plasticity of the healing skin.

Mind change complexity of learning logic programs

The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. This paper shows that an effective version of Shinohara’s notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. Let Omega be a notation for the first limit ordinal. Then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m >0, the class of languages defined by formal systems of length <= m: • is identifiable in the limit from positive data with a mind change bound of Omega (power)m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of Omega × m. The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded Prolog programs, including Shapiro’s linear programs, Arimura and Shinohara’s depth-bounded linearly covering programs, and Krishna Rao’s depth-bounded linearly moded programs. It is also noted that the bound for learning from positive data is tight for the example classes considered.

Nitrogen fertilizer management for nitrous oxide (N2O) mitigation in intensive corn (Maize) production: an emissions reduction protocol for US Midwest agriculture

Nitrous oxide (N2O) is a major greenhouse gas (GHG) product of intensive agriculture. Fertilizer nitrogen (N) rate is the best single predictor of N2O emissions in row-crop agriculture in the US Midwest. We use this relationship to propose a transparent, scientifically robust protocol that can be utilized by developers of agricultural offset projects for generating fungible GHG emission reduction credits for the emerging US carbon cap and trade market. By coupling predicted N2O flux with the recently developed maximum return to N (MRTN) approach for determining economically profitable N input rates for optimized crop yield, we provide the basis for incentivizing N2O reductions without affecting yields. The protocol, if widely adopted, could reduce N2O from fertilized row-crop agriculture by more than 50%. Although other management and environmental factors can influence N2O emissions, fertilizer N rate can be viewed as a single unambiguous proxy—a transparent, tangible, and readily manageable commodity. Our protocol addresses baseline establishment, additionality, permanence, variability, and leakage, and provides for producers and other stakeholders the economic and environmental incentives necessary for adoption of agricultural N2O reduction offset projects.

A comparative study of the effect of calibration conditions on the water equivalence of a range of gel dosimeters

Gel dosimeters are of increasing interest in the field of radiation oncology as the only truly three-dimensional integrating radiation dosimeter. There are a range of ferrous-sulphate and polymer gel dosimeters. To be of use, they must be water-equivalent. On their own, this relates to their radiological properties as determined by their composition. In the context of calibration of gel dosimeters, there is the added complexity of the calibration geometry; the presence of containment vessels may influence the dose absorbed. Five such methods of calibration are modelled here using the Monte Carlo method. It is found that the Fricke gel best matches water for most of the calibration methods, and that the best calibration method involves the use of a large tub into which multiple fields of different dose are directed. The least accurate calibration method involves the use of a long test tube along which a depth dose curve yields multiple calibration points.

A comparative study of the effect of calibration conditions on the water equivalence of a range of gel dosimeters

Gel dosimeters are of increasing interest in the field of radiation oncology as the only truly three-dimensional integrating radiation dosimeter. There are a range of ferrous-sulphate and polymer gel dosimeters. To be of use, they must be water-equivalent. On their own, this relates to their radiological properties as determined by their composition. In the context of calibration of gel dosimeters, there is the added complexity of the calibration geometry; the presence of containment vessels may influence the dose absorbed. Five such methods of calibration are modelled here using the Monte Carlo method. It is found that the Fricke gel best matches water for most of the calibration methods, and that the best calibration method involves the use of a large tub into which multiple fields of different dose are directed. The least accurate calibration method involves the use of a long test tube along which a depth dose curve yields multiple calibration points.

Statistical modeling to determine resonant frequency information present in combustion chamber pressure signals

A statistical modeling method to accurately determine combustion chamber resonance is proposed and demonstrated. This method utilises Markov-chain Monte Carlo (MCMC) through the use of the Metropolis-Hastings (MH) algorithm to yield a probability density function for the combustion chamber frequency and find the best estimate of the resonant frequency, along with uncertainty. The accurate determination of combustion chamber resonance is then used to investigate various engine phenomena, with appropriate uncertainty, for a range of engine cycles. It is shown that, when operating on various ethanol/diesel fuel combinations, a 20% substitution yields the least amount of inter-cycle variability, in relation to combustion chamber resonance.

Oxidative potential of logwood and pellet burning particles assessed by a novel profluorescent nitroxide probe

This study reports the potential toxicological impact of particles produced during biomass combustion by an automatic pellet boiler and a traditional logwood stove under various combustion conditions using a novel profluorescent nitroxide probe BPEAnit. This probe is weakly fluorescent, but yields strong fluorescence emission upon radical trapping or redox activity. Samples were collected by bubbling aerosol through an impinger containing BPEAnit solution, followed by fluorescence measurement. The fluorescence of BPEAnit was measured for particles produced during various combustion phases, at the beginning of burning (cold start), stable combustion after refilling with the fuel (warm start) and poor burning conditions. For particles produced by the logwood stove under cold-start conditions significantly higher amounts of reactive species per unit of particulate mass were observed compared to emissions produced during a warm start. In addition, sampling of logwood burning emissions after passing through a thermodenuder at 250oC resulted in an 80-100% reduction of the fluorescence signal of BPEAnit probe, indicating that the majority of reactive species were semivolatile. Moreover, the amount of reactive species showed a strong correlation with the amount of particulate organic material. This indicates the importance of semivolatile organics in particle-related toxicity. Particle emissions from the pellet boiler, although of similar mass concentration, were not observed to lead to an increase in fluorescence signal during any of the combustion phases.

Design and implementation of sensor networks for the observation and research of harmful algal blooms in southern California coastal waters

Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

The delta-phase spectrum with application to voice activity detection and speaker recognition

For several reasons, the Fourier phase domain is less favored than the magnitude domain in signal processing and modeling of speech. To correctly analyze the phase, several factors must be considered and compensated, including the effect of the step size, windowing function and other processing parameters. Building on a review of these factors, this paper investigates a spectral representation based on the Instantaneous Frequency Deviation, but in which the step size between processing frames is used in calculating phase changes, rather than the traditional single sample interval. Reflecting these longer intervals, the term delta-phase spectrum is used to distinguish this from instantaneous derivatives. Experiments show that mel-frequency cepstral coefficients features derived from the delta-phase spectrum (termed Mel-Frequency delta-phase features) can produce broadly similar performance to equivalent magnitude domain features for both voice activity detection and speaker recognition tasks. Further, it is shown that the fusion of the magnitude and phase representations yields performance benefits over either in isolation.

meso-Porphyrinylphosphine Oxides: Mono- and Bidentate Ligands for Supramolecular Chemistry and the Crystal Structures of Monomeric [10,20-Diphenylporphyrinatonickel(II)-5,15-diyl]-bis-[P(O)Ph2] and Polymeric Self-Coordinated ([10,20-Diphenylporphyrinatozinc(II)-5,15-diyl]-bis-[P(O)Ph2])

A series of porphyrins substituted in one or two meso-positions by diphenylphosphine oxide groups has been prepared by the palladium catalysed reaction of diphenylphosphine or its oxide with the corresponding bromoporphyrins. Compounds {MDPP-[P(O)Ph2]n} (M = H2, Ni, Zn; H2DPP = 5,15-diphenylporphyrin; n = 1, 2) were isolated in yields of 60-95%. The reaction is believed to proceed via the conventional oxidative addition, phosphination and reductive elimination steps, as the stoichiometric reaction of η1-palladio(II) porphyrin [PdBr(H2DPP)(dppe)] (H2DPP = 5,15-diphenylporphyrin; dppe = 1,2-bis(diphenylphosphino)ethane) with diphenylphosphine oxide also results in the desired mono-porphyrinylphosphine oxide [H2DPP-P(O)Ph2]. Attempts to isolate the tertiary phosphines failed due to their extreme air-sensitivity. Variable temperature 1H NMR studies of [H2DPP-P(O)Ph2] revealed an intrinsic lack of symmetry, while fluorescence spectroscopy showed that the phosphine oxide group does not behave as a "heavy atom" quencher. The electron withdrawing effect of the phosphine oxide group was confirmed by voltammetry. The ligands were characterised by multinuclear NMR and UV-visible spectroscopy as well as mass spectrometry. Single crystal X-ray crystallography showed that the bis(phosphine oxide) nickel(II) complex {[NiDPP-[P(O)Ph2]2} is monomeric in the solid state, with a ruffled porphyrin core and the two P=O fragments on the same side of the average plane of the molecule. On the other hand, the corresponding zinc(II) complex formed infinite chains through coordination of one Ph2PO substituent to the neighbouring zinc porphyrin through an almost linear P=O---Zn unit, leaving the other Ph2PO group facing into a parallel channel filled with disordered water molecules. These new phosphine oxides are attractive ligands for supramolecular porphyrin chemistry.

The conversion of lignocellulosics to levulinic acid

Biomass represents an abundant and relatively low cost carbon resource that can be utilized to produce platform chemicals such as levulinic acid. Current processing technology limits the cost-effective production of levulinic acid in commercial quantities from biomass. The key to improving the yield and effi ciency of levulinic acid production from biomass lies in the ability to optimize and isolate the intermediate products at each step of the reaction pathway and reduce re-polymerization and side reactions. New technologies (including the use of microwave irradiation and ionic liquids) and the development of highly selective catalysts would provide the necessary step change for the optimization of key reactions. A processing environment that allows the use of biphasic systems and/or continuous extraction of products would increase reaction rates, yields and product quality. This review outlines the chemistry of levulinic acid synthesis and discusses current and potential technologies for producing levulinic acid from lignocellulosics.

Linking ambulance, emergency department and hospital admissions data : understanding the emergency journey

Objective: to assess the accuracy of data linkage across the spectrum of emergency care in the absence of a unique patient identifier, and to use the linked data to examine service delivery outcomes in an emergency department setting. Design: automated data linkage and manual data linkage were compared to determine their relative accuracy. Data were extracted from three separate health information systems: ambulance, ED and hospital inpatients, then linked to provide information about the emergency journey of each patient. The linking was done manually through physical review of records and automatically using a data linking tool (Health Data Integration) developed by the CSIRO. Match rate and quality of the linking were compared. Setting: 10, 835 patient presentations to a large, regional teaching hospital ED over a two month period (August-September 2007). Results: comparison of the manual and automated linkage outcomes for each pair of linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of between 75% and 99%; and a positive predictive value of between 88% and 95%. Conclusions: Our results indicate that automated linking provides a sound basis for health service analysis, even in the absence of a unique patient identifier. The use of an automated linking tool yields accurate data suitable for planning and service delivery purposes and enables the data to be linked regularly to examine service delivery outcomes.