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

Compliance with international financial reporting standards (IFRS) and the value relevance of accounting information in emerging stock markets : evidence from Kuwait

Since the 1960s, the value relevance of accounting information has been an important topic in accounting research. The value relevance research provides evidence as to whether accounting numbers relate to corporate value in a predicted manner (Beaver, 2002). Such research is not only important for investors but also provides useful insights into accounting reporting effectiveness for standard setters and other users. Both the quality of accounting standards used and the effectiveness associated with implementing these standards are fundamental prerequisites for high value relevance (Hellstrom, 2006). However, while the literature comprehensively documents the value relevance of accounting information in developed markets, little attention has been given to emerging markets where the quality of accounting standards and their enforcement are questionable. Moreover, there is currently no known research that explores the association between level of compliance with International Financial Reporting Standards (IFRS) and the value relevance of accounting information. Motivated by the lack of research on the value relevance of accounting information in emerging markets and the unique institutional setting in Kuwait, this study has three objectives. First, it investigates the extent of compliance with IFRS with respect to firms listed on the Kuwait Stock Exchange (KSE). Second, it examines the value relevance of accounting information produced by KSE-listed firms over the 1995 to 2006 period. The third objective links the first two and explores the association between the level of compliance with IFRS and the value relevance of accounting information to market participants. Since it is among the first countries to adopt IFRS, Kuwait provides an ideal setting in which to explore these objectives. In addition, the Kuwaiti accounting environment provides an interesting regulatory context in which each KSE-listed firm is required to appoint at least two external auditors from separate auditing firms. Based on the research objectives, five research questions (RQs) are addressed. RQ1 and RQ2 aim to determine the extent to which KSE-listed firms comply with IFRS and factors contributing to variations in compliance levels. These factors include firm attributes (firm age, leverage, size, profitability, liquidity), the number of brand name (Big-4) auditing firms auditing a firm’s financial statements, and industry categorization. RQ3 and RQ4 address the value relevance of IFRS-based financial statements to investors. RQ5 addresses whether the level of compliance with IFRS contributes to the value relevance of accounting information provided to investors. Based on the potential improvement in value relevance from adopting and complying with IFRS, it is predicted that the higher the level of compliance with IFRS, the greater the value relevance of book values and earnings. The research design of the study consists of two parts. First, in accordance with prior disclosure research, the level of compliance with mandatory IFRS is examined using a disclosure index. Second, the value relevance of financial statement information, specifically, earnings and book value, is examined empirically using two valuation models: price and returns models. The combined empirical evidence that results from the application of both models provides comprehensive insights into value relevance of accounting information in an emerging market setting. Consistent with expectations, the results show the average level of compliance with IFRS mandatory disclosures for all KSE-listed firms in 2006 was 72.6 percent; thus, indicating KSE-listed firms generally did not fully comply with all requirements. Significant variations in the extent of compliance are observed among firms and across accounting standards. As predicted, older, highly leveraged, larger, and profitable KSE-listed firms are more likely to comply with IFRS required disclosures. Interestingly, significant differences in the level of compliance are observed across the three possible auditor combinations of two Big-4, two non-Big 4, and mixed audit firm types. The results for the price and returns models provide evidence that earnings and book values are significant factors in the valuation of KSE-listed firms during the 1995 to 2006 period. However, the results show that the value relevance of earnings and book values decreased significantly during that period, suggesting that investors rely less on financial statements, possibly due to the increase in the available non-financial statement sources. Notwithstanding this decline, a significant association is observed between the level of compliance with IFRS and the value relevance of earnings and book value to KSE investors. The findings make several important contributions. First, they raise concerns about the effectiveness of the regulatory body that oversees compliance with IFRS in Kuwait. Second, they challenge the effectiveness of the two-auditor requirement in promoting compliance with regulations as well as the associated cost-benefit of this requirement for firms. Third, they provide the first known empirical evidence linking the level of IFRS compliance with the value relevance of financial statement information. Finally, the findings are relevant for standard setters and for their current review of KSE regulations. In particular, they highlight the importance of establishing and maintaining adequate monitoring and enforcement mechanisms to ensure compliance with accounting standards. In addition, the finding that stricter compliance with IFRS improves the value relevance of accounting information highlights the importance of full compliance with IFRS and not just mere adoption.

Wandering and the physical environment

Background/Rationale Guided by the need-driven dementia-compromised behavior (NDB) model, this study examined influences of the physical environment on wandering behavior. Methods Using a descriptive, cross-sectional design, 122 wanderers from 28 long-term care (LTC) facilities were videotaped 10 to 12 times; data on wandering, light, sound, temperature and humidity levels, location, ambiance, and crowding were obtained. Associations between environmental variables and wandering were evaluated with chi-square and t tests; the model was evaluated using logistic regression. Results In all, 80% of wandering occurred in the resident’s own room, dayrooms, hallways, or dining rooms. When observed in other residents’ rooms, hallways, shower/baths, or off-unit locations, wanderers were likely (60%-92% of observations) to wander. The data were a good fit to the model overall (LR [logistic regression] χ2 (5) = 50.38, P < .0001) and by wandering type. Conclusions Location, light, sound, proximity of others, and ambiance are associated with wandering and may serve to inform environmental designs and care practices.

The candidate : a novella and examination of Australian Gothic crime fiction

Australia is a land without haunted castles or subterranean corridors, without ancient graveyards or decaying monasteries, a land whose climate is rarely gloomy. Yet, the literary landscape is splattered with shades of the Gothic genre. This Gothic heritage is especially evident within elements of nineteenth century Australian sensation fiction. Australian crime fiction in the twentieth century, in keeping with this lineage, repeatedly employs elements of the Gothic, adapting and appropriating these conventions for literary effect. I believe that a ‘mélange’ of historical Gothic crime traditions could produce an exciting new mode of Gothic crime writing in the Australian context. As such, I have written a contemporary literary experiment in a Gothic crime ‘hybrid’ style: this novella forms my creative practice. The accompanying exegesis is a critical study of a selection of Australian literary works that exhibit the characteristics of both Gothic and crime genres. Through an analysis of these creative works, this study argues that the interlacing of Gothic traditions with crime writing conventions has been a noteworthy practice in Australian fiction during both the nineteenth and twentieth centuries and these literary tropes are interwoven in the writing of ‘The Candidate’, a Gothic crime novella.

Predicting effects of monotony on driver’s vigilance

Monotony has been identified as a contributing factor to road crashes. Drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.

Conifer defence against insects: microarray gene expression profiling of Sitka spruce (Picea sitchensis) induced by mechanical wounding or feeding by spruce budworms (Choristoneura occidentalis) or white pine weevils (Pissodes strobi) reveals large

Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant defence. Refined expression analysis using gene-specific primers and real-time PCR for selected transcripts was in agreement with microarray results for most genes tested. This study provides the first large-scale survey of insect-induced defence transcripts in a gymnosperm and provides a platform for functional investigation of plant-insect interactions in spruce. Induction of spruce genes of octadecanoid and ethylene signalling, terpenoid biosynthesis, and phenolic secondary metabolism are discussed in more detail.