Power spectrum model of visual masking: simulations and empirical data

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

The wealth effects of commercial bank securities issuances announcement

Banks are often excluded in corporate finance research mainly because of the regulatory concerns. Compares to non-bank firms, banks are heavily regulated due to its special economic role of money and the uncertainty. Heavy regulation on banks could reduce the information asymmetry between the managers and investor by limiting the behaviour of banks at the time of the Seasoned Equity Offering (SEO), and by increasing the incentive for banks to avoid excessive risk-taking. Therefore, the market may be less likely to assume that bank issued securities signal information that the bank is overvalued compared to their non-bank counterparts. The objective of this thesis is therefore to examine commercial banks issued securities announcement effect. Three interrelated research questions are addressed in this thesis: 1) What is the difference in convertible bond announcement effect between banks and non-banks firm? 2) What is the difference in SEO announcement effect between banks and non-banks? 3) How do the stringency levels of bank regulation impact on the announcement effects of bank issued SEO? By using the U.S. convertible bond and SEO data from 1982 to 2012, I find that the bank issued a convertible bond and SEO announcement experience higher cumulative abnormal return than non-bank. This is consistent with the view that bank regulation reveals positive information about banks. Since banks are heavily regulated, the market is less likely to assume that the issuance of the convertible bond and SEO by banks signals information that is overvalued. These results are robust after controlling for a number of firm-, issue-, and market-specific characteristics. These results are robust by considering the different categories of non-bank industries by undertaking tests in relation to the differences in the CARS upon convertible bond/ SEO across industries, as well as the unbalanced sample between banks and non-banks by using the matched sample analysis. However, the relation between the stringency level of bank regulation and bank issued securities announcement effect may be nonlinear. As hypothesised, I find that bank regulation has an inverted U-shaped relation with the announcement effect of bank SEO by using the SEO data across 21 countries from 2001 to 2012. Under a less bank regulation environment, the market reacts more positively to the bank SEO announcement for an increase in the level of bank regulation. However, the bank SEO announcement effects become more negative if the bank regulation becomes too stringent. This inverted U-shaped relationship is robust after I use the exogenous cross-country, cross-year variation in the timing of the Basel II adoption as the instrument to assess the causal impact of bank regulation on SEO announcement effects. However, the stringency of regulation does not have a significant impact on the announcement effects of involuntary bank equity issuance.

High body mass index is not a barrier to physical activity: Analysis of international rugby players' anthropometric data

Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.

A Petrov-Galerkin method for a singularly perturbed ordinary differential equation with non-smooth data

In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.