Performance of an adaptive homodyne receiver in the presence of multipath, Rayleigh-fading and time-varying quadrature errors

In this paper, we carry out a detailed performance analysis of the blind source separation based I/Q corrector operating at the baseband. Performance of the digital I/Q corrector is evaluated not only under time-varying phase and gain errors but also in the presence of multipath and Rayleigh fading channels. Performance under low-SNR and different modulation formats and constellation sizes is also evaluated. What is more, BER improvement after correction is illustrated. The results indicate that the adaptive algorithm offers adequate performance for most communication applications hence, reducing the matching requirements of the analog front-end enabling higher levels of integration.

A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Do financial distress and liquidity crises affect value and size premiums?

This study investigates the impact of liquidity crises on the relationship between stock (value and size) premiums and default risk in the US market. It first examines whether financial distress can explain value and size premiums, and then, subsequently, aims to determine whether liquidity crises increase the risk of value and size premium investment strategies. The study employs a time-varying approach and a sample of US stock returns for the period between January 1982 and March 2011, a period which includes the current liquidity crisis, so as to examine the relationship between default risk, liquidity crises and value and size premiums. The findings indicate that the default premium has explanatory power for value and size and premiums, which affect firms with different characteristics. We also find that liquidity crises may actually increase the risks related to size and value premium strategies.

Equitable representation in councils: theory and an application to the United Nations Security Council

We analyze democratic equity in council voting games (CVGs). In a CVG, a voting body containing all members delegates decision-making to a (time-varying) subset of its members, as describes, e.g., the relationship between the United Nations General Assembly and the United Nations Security Council (UNSC). We develop a theoretical framework for analyzing democratic equitability in CVGs at both the country and region levels, and for different assumptions regarding preference correlation. We apply the framework to evaluate the equitability of the UNSC, and the claims of those who seek to reform it. We find that the individual permanent members are overrepresented by between 21.3 times (United Kingdom) and 3.8 times (China) from a country-level perspective, while from a region perspective Eastern Europe is the most heavily overrepresented region with more than twice its equitable representation, and Africa the most heavily underrepresented. Our equity measures do not preclude some UNSC members from exercising veto rights, however.