Assessment of Speech Dialog Systems using Multi-Modal Cognitive Load Analysis and Driving Performance Metrics

In this paper, cognitive load analysis via acoustic- and CAN-Bus-based driver performance metrics is employed to assess two different commercial speech dialog systems (SDS) during in-vehicle use. Several metrics are proposed to measure increases in stress, distraction and cognitive load and we compare these measures with statistical analysis of the speech recognition component of each SDS. It is found that care must be taken when designing an SDS as it may increase cognitive load which can be observed through increased speech response delay (SRD), changes in speech production due to negative emotion towards the SDS, and decreased driving performance on lateral control tasks. From this study, guidelines are presented for designing systems which are to be used in vehicular environments.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

Event-related potential (ERP) correlates of impaired visuospatial memory in schizophrenia

Previous studies have reported that patients with schizophrenia demonstrate impaired performance during working memory (WM) tasks. The current study aimed to determine whether WM impairments in schizophrenia are accompanied by reduced slow wave (SW) activity during on-line maintenance of mnemonic information. Event-related potentials were obtained from patients with schizophrenia and well controls as they performed a visuospatial delayed response task. On 50% of trials, a distractor stimulus was introduced during the delay. Compared with controls, patients with schizophrenia produced less SW memory negativity, particularly over the right hemisphere, together with reduced frontal enhancement of SW memory negativity in response to distraction. The results indicate that patients with schizophrenia generate less maintenance phase neuronal activity during WM performance, especially under conditions of distraction.

The manipulation of apoptosis-related genes to generate resistance to Fusarium wilt and water stress in banana

Bananas are susceptible to a diverse range of biotic and abiotic stresses, many of which cause serious production constraints worldwide. One of the most destructive banana diseases is Fusarium wilt caused by the soil-borne fungus, Fusarium oxysporum f. sp. cubense (Foc). No effective control strategy currently exists for this disease which threatens global banana production. Although disease resistance exists in some wild bananas, attempts to introduce resistance into commercially acceptable bananas by conventional breeding have been hampered by low fertility, long generation times and association of poor agronomical traits with resistance genes. With the advent of reliable banana transformation protocols, molecular breeding is now regarded as a viable alternative strategy to generate disease-resistant banana plants. Recently, a novel strategy involving the expression of anti-apoptosis genes in plants was shown to result in resistance against several necrotrophic fungi. Further, the transgenic plants showed increased resistance to a range of abiotic stresses. In this thesis, the use of anti-apoptosis genes to generate transgenic banana plants with resistance to Fusarium wilt was investigated. Since water stress is an important abiotic constraint to banana production, the resistance of the transgenic plants to water stress was also examined. Embryogenic cell suspensions (ECS) of two commercially important banana cultivars, Grand Naine (GN) and Lady Finger (LF), were transformed using Agrobacterium with the anti-apoptosis genes, Bcl-xL, Bcl-xL G138A, Ced-9 and Bcl- 2 3’ UTR. An interesting, and potentially important, outcome was that the use of anti-apoptosis genes resulted in up to a 50-fold increase in Agrobacterium-mediated transformation efficiency of both LF and GN cells over vector controls. Regenerated plants were subjected to a complete molecular characterisation in order to detect the presence of the transgene (PCR), transcript (RT-PCR) and gene product (Western blot) and to determine the gene copy number (Southern blot). A total of 36 independently-transformed GN lines (8 x Bcl-xL, 5 x Bcl-xL G138A, 15 x Ced-9 and 8 x Bcl-2 3’ UTR) and 41 independently-transformed LF lines (8 x Bcl-xL, 7 x BclxL G138A, 13 x Ced-9 and 13 x Bcl-2 3’ UTR) were identified. The 41 transgenic LF lines were multiplied and clones from each line were acclimatised and grown under glasshouse conditions for 8 weeks to allow monitoring for phenotypic abnormalities. Plants derived from 3 x Bcl-xL, 2 x Ced-9 and 5 x Bcl-2 3’ UTR lines displayed a variety of aberrant phenotypes. However, all but one of these abnormalities were off-types commonly observed in tissue-cultured, non-transgenic banana plants and were therefore unlikely to be transgene-related. Prior to determining the resistance of the transgenic plants to Foc race 1, the apoptotic effects of the fungus on both wild-type and Bcl-2 3’ UTR-transgenic LF banana cells were investigated using rapid in vitro root assays. The results from these assays showed that apoptotic-like cell death was elicited in wild-type banana root cells as early as 6 hours post-exposure to fungal spores. In contrast, these effects were attenuated in the root cells of Bcl-2 3’ UTR-transgenic lines that were exposed to fungal spores. Thirty eight of the 41 transgenic LF lines were subsequently assessed for resistance to Foc race 1 in small-plant glasshouse bioassays. To overcome inconsistencies in rating the internal (vascular discolouration) disease symptoms, a MatLab-based computer program was developed to accurately and reliably assess the level of vascular discolouration in banana corms. Of the transgenic LF banana lines challenged with Foc race 1, 2 x Bcl-xL, 3 x Ced-9, 2 x Bcl-2 3’ UTR and 1 x Bcl-xL G138A-transgenic line were found to show significantly less external and internal symptoms than wild-type LF banana plants used as susceptible controls at 12 weeks post-inoculation. Of these lines, Bcl-2 3’ UTR-transgenic line #6 appeared most resistant, displaying very mild symptoms similar to the wild-type Cavendish banana plants that were included as resistant controls. This line remained resistant for up to 23 weeks post-inoculation. Since anti-apoptosis genes have been shown to confer resistance to various abiotic stresses in other crops, the ability of these genes to confer resistance against water stress in banana was also investigated. Clonal plants derived from each of the 38 transgenic LF banana plants were subjected to water stress for a total of 32 days. Several different lines of transgenic plants transformed with either Bcl-xL, Bcl-xL G138A, Ced-9 or Bcl-2 3’ UTR showed a delay in visual water stress symptoms compared with the wild-type control plants. These plants all began producing new growth from the pseudostem following daily rewatering for one month. In an attempt to determine whether the protective effect of anti-apoptosis genes in transgenic banana plants was linked with reactive oxygen species (ROS)-associated programmed cell death (PCD), the effect of the chloroplast-targeting, ROS-inducing herbicide, Paraquat, on wild-type and transgenic LF was investigated. When leaf discs from wild-type LF banana plants were exposed to 10 ìM Paraquat, complete decolourisation occurred after 48 hours which was confirmed to be associated with cell death and ROS production by trypan blue and 3,3-diaminobenzidine (DAB) staining, respectively. When leaf discs from the transgenic lines were exposed to Paraquat, those derived from some lines showed a delay in decolourisation, suggesting only a weak protective effect from the transgenes. Finally, the protective effect of anti-apoptosis genes against juglone, a ROS-inducing phytotoxin produced by the causal agent of black Sigatoka, Mycosphaerella fijiensis, was investigated. When leaf discs from wild-type LF banana plants were exposed to 25 ppm juglone, complete decolourisation occurred after 48 hours which was again confirmed to be associated with cell death and ROS production by trypan blue and DAB staining, respectively. Further, TdT-mediated dUTP nick-end labelling (TUNEL) assays on these discs suggested that the cell death was apoptotic. When leaf discs from the transgenic lines were exposed to juglone, discs from some lines showed a clear delay in decolourisation, suggesting a protective effect. Whether these plants are resistant to black Sigatoka is unknown and will require future glasshouse and field trials. The work presented in this thesis provides the first report of the use of anti-apoptosis genes as a strategy to confer resistance to Fusarium wilt and water stress in a nongraminaceous monocot, banana. Such a strategy may be exploited to generate resistance to necrotrophic pathogens and abiotic stresses in other economically important crop plants.

Near real-time prediction of Zenith Tropospheric Delays for position estimation over long-baseline CORS network

This paper presents the preliminary results in establishing a strategy for predicting Zenith Tropospheric Delay (ZTD) and relative ZTD (rZTD) between Continuous Operating Reference Stations (CORS) in near real-time. It is anticipated that the predicted ZTD or rZTD can assist the network-based Real-Time Kinematic (RTK) performance over long inter-station distances, ultimately, enabling a cost effective method of delivering precise positioning services to sparsely populated regional areas, such as Queensland. This research firstly investigates two ZTD solutions: 1) the post-processed IGS ZTD solution and 2) the near Real-Time ZTD solution. The near Real-Time solution is obtained through the GNSS processing software package (Bernese) that has been deployed for this project. The predictability of the near Real-Time Bernese solution is analyzed and compared to the post-processed IGS solution where it acts as the benchmark solution. The predictability analyses were conducted with various prediction time of 15, 30, 45, and 60 minutes to determine the error with respect to timeliness. The predictability of ZTD and relative ZTD is determined (or characterized) by using the previously estimated ZTD as the predicted ZTD of current epoch. This research has shown that both the ZTD and relative ZTD predicted errors are random in nature; the STD grows from a few millimeters to sub-centimeters while the predicted delay interval ranges from 15 to 60 minutes. Additionally, the RZTD predictability shows very little dependency on the length of tested baselines of up to 1000 kilometers. Finally, the comparison of near Real-Time Bernese solution with IGS solution has shown a slight degradation in the prediction accuracy. The less accurate NRT solution has an STD error of 1cm within the delay of 50 minutes. However, some larger errors of up to 10cm are observed.

Analysis of phasor measurement method in tracking the power frequency of distorted signals

This paper presents an analysis of phasor measurement method for tracking the fundamental power frequency to show if it has the performance necessary to cope with the requirements of power system protection and control. In this regard, several computer simulations presenting the conditions of a typical power system signal especially those highly distorted by harmonics, noise and offset, are provided to evaluate the response of the Phasor Measurement (PM) technique. A new method, which can shorten the delay of estimation, has also been proposed for the PM method to work for signals free of even-order harmonics.

Clustering of ad-hoc microphone arrays for robust blind beamforming

This paper proposes a clustered approach for blind beamfoming from ad-hoc microphone arrays. In such arrangements, microphone placement is arbitrary and the speaker may be close to one, all or a subset of microphones at a given time. Practical issues with such a configuration mean that some microphones might be better discarded due to poor input signal to noise ratio (SNR) or undesirable spatial aliasing effects from large inter-element spacings when beamforming. Large inter-microphone spacings may also lead to inaccuracies in delay estimation during blind beamforming. In such situations, using a cluster of microphones (ie, a sub-array), closely located both to each other and to the desired speech source, may provide more robust enhancement than the full array. This paper proposes a method for blind clustering of microphones based on the magnitude square coherence function, and evaluates the method on a database recorded using various ad-hoc microphone arrangements.

Robust speech recognition using speech enhancement

Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly as the level of background noise is increased. Speech enhancement is a popular method for making ASR systems more ro- bust. Single-channel spectral subtraction was originally designed to improve hu- man speech intelligibility and many attempts have been made to optimise this algorithm in terms of signal-based metrics such as maximised Signal-to-Noise Ratio (SNR) or minimised speech distortion. Such metrics are used to assess en- hancement performance for intelligibility not speech recognition, therefore mak- ing them sub-optimal ASR applications. This research investigates two methods for closely coupling subtractive-type enhancement algorithms with ASR: (a) a computationally-efficient Mel-filterbank noise subtraction technique based on likelihood-maximisation (LIMA), and (b) in- troducing phase spectrum information to enable spectral subtraction in the com- plex frequency domain. Likelihood-maximisation uses gradient-descent to optimise parameters of the enhancement algorithm to best fit the acoustic speech model given a word se- quence known a priori. Whilst this technique is shown to improve the ASR word accuracy performance, it is also identified to be particularly sensitive to non-noise mismatches between the training and testing data. Phase information has long been ignored in spectral subtraction as it is deemed to have little effect on human intelligibility. In this work it is shown that phase information is important in obtaining highly accurate estimates of clean speech magnitudes which are typically used in ASR feature extraction. Phase Estimation via Delay Projection is proposed based on the stationarity of sinusoidal signals, and demonstrates the potential to produce improvements in ASR word accuracy in a wide range of SNR. Throughout the dissertation, consideration is given to practical implemen- tation in vehicular environments which resulted in two novel contributions – a LIMA framework which takes advantage of the grounding procedure common to speech dialogue systems, and a resource-saving formulation of frequency-domain spectral subtraction for realisation in field-programmable gate array hardware. The techniques proposed in this dissertation were evaluated using the Aus- tralian English In-Car Speech Corpus which was collected as part of this work. This database is the first of its kind within Australia and captures real in-car speech of 50 native Australian speakers in seven driving conditions common to Australian environments.

Electromyographic activity in lower limb muscles is temporally associated with the slow phase of oxygen uptake during cycling

Although the "slow" phase of pulmonary oxygen uptake (Vo2) appears to represent energetic processes in contracting muscle, electromyographic evidence tends not to support this. The present study assessed normalized integrated electromyographic (NIEMG) activity in eight muscles that act about the hip, knee and ankle during 8 min of moderate (ventilatory threshold) cycling in six male cyclists. (Vo2) was measured breath by breath during four repeated trials at each of the two intensities. Moderate and very heavy exercise followed a 4-min period of light exercise (50 W). During moderate exercise the slow (Vo2) phase was absent and NIEMG in all muscles did not increase after the first minute of exercise. During very heavy exercise, the slow phase emerged (time delay=58 ± 16 s) and increased progressively (time constant=120 ± 35 s) to an amplitude (0.83 ± 0.16 L/min) that was approximately 21% of the total (Vo2) response. This slow (Vo2) phase coincided with a significant increase in NIEMG in most muscles, and differences in NIEMG activities between the two intensities revealed "slow" muscle activation profiles that differed between muscles in terms of the onset, amplitude and shape of these profiles. This supports the hypothesis that the slow (Vo2) phase is a function of these different slow muscle activation profiles.

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.

Epidemiology

The aim of this chapter is to provide you with a basic understanding of epidemiology, and to introduce you to some of the epidemiological concepts and methods used by researchers and practitioners working in public health. It is hoped that you will recognise how the principles and practice of epidemiology help to provide information and insights that can be used to achieve better health outcomes for all. Epidemiology is fundamental to preventive medicine and public health policy. Rather than examine health and illness on an individual level, as clinicians do, epidemiologists focus on communities and population health issues. The word epidemiology is derived from the Greek epi (on, upon), demos (the people) and logos (the study of). Epidemiology, then, is the study of that which falls upon the people. Its aims are to describe health-related states or events, and through systematic examination of the available information, attempt to determine their causes. The ultimate goal is to contribute to prevention of disease and disability and to delay mortality. The primary question of epidemiology is: why do certain diseases affect particular population groups? Drawing upon statistics, the social and behavioural sciences, the biological sciences and medicine, epidemiologists collect and interpret information to assist in the prevention of new cases of disease, eradicate existing disease and prolong the lives of people who have disease.

Poster Abstract : A sensor network for compression and streaming of GPS trajectory data

We present the design and deployment results for PosNet - a large-scale, long-duration sensor network that gathers summary position and status information from mobile nodes. The mobile nodes have a fixed-sized memory buffer to which position data is added at a constant rate, and from which data is downloaded at a non-constant rate. We have developed a novel algorithm that performs online summarization of position data within the buffer, where the algorithm naturally accommodates data input and output rate mismatch, and also provides a delay-tolerant approach to data transport. The algorithm has been extensively tested in a large-scale long-duration cattle monitoring and control application.

Exercise intensity influences NEAT in overweight and obese adults

PURPOSE: To determine the effect of acute bouts of moderate- and high-intensity walking exercise on non-exercise activity thermogenesis (NEAT) in overweight and obese adults. ---------- METHOD: 16 participants performed a single bout of either moderate-intensity walking exercise (MIE) or high-intensity walking exercise (HIE) on two separate occasions. The MIE consisted of walking for 60 minutes on a motorized treadmill at 6 km.h. The 60-minute HIE session consisted of walking in 5-min intervals at 6 km.h and 10% grade followed by 5-min at 0% grade. NEAT was assessed by accelerometer on three days before, the day of, and three days following the exercise sessions. ---------- RESULTS: There was no significant difference in NEAT vector magnitude (counts.min) between the pre-exercise period (days 1-3) and the exercise day (day 4) for either MIE or HIE protocol. In addition, there was no change in NEAT during the three days following the MIE session, however NEAT increased by 16% on day 7 (post-exercise) compared with exercise day (P = 0.32). However during the post-exercise period following the HIE session, NEAT was increased by 25% on day 7 compared with the exercise day (P = 0.08), and by 30-33% compared with pre-exercise period (day 1, day 2 and day 3); P = 0.03, 0.03, 0.02, respectively. ---------- CONCLUSION: A single bout of either MIE or HIE did not alter NEAT on the exercise day or on the first two days following the exercise session. However, monitoring NEAT on a third day allowed the detection of a 48-h delay in increased NEAT after performing HIE. A longer-term intervention is needed to determine the effect of accumulated exercise sessions over a week on NEAT.

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