BayesMortalityPlus: A package in R for Bayesian graduation of mortality modelling

The BayesMortalityPlus package provides a framework for modelling and predicting mortality data. The package includes tools for the construction of life tables based on Heligman-Pollard laws, and also on dynamic linear smoothers. Flexibility is available in terms of modelling so that the response variable may be modeled as Poisson, Binomial or Gaussian. If temporal data is available, the package provides a Bayesian implementation for the well-known Lee-Carter model that allows for estimation, projection of mortality over time, and assessment of uncertainty of any linear or nonlinear function of parameters such as life expectancy. Illustrations are considered to show the capability of the proposed package to model mortality data

Characterization of pool boiling heat transfer from porous-coating-enhanced surfaces

Development of techniques for enhancement and optimization of thermal management technologies has been a highly active area of research in recent decades in response to the rapid emergence of compact, high-power electronic systems. Immersion cooling by boiling is one of the preferred methods for high power density applications, due to its passive nature and high heat transfer coefficients obtained. Pool boiling heat transfer has been extensively studied in recent decades to understand the inherent mechanisms yielding the high heat transfer rates, as well as to further enhance the heat transfer by simple modifications or additions to existing approaches. This thesis aims to provide detailed fundamental analysis of heat transfer enhancement by surface-coating-based boiling enhancement methods and to quantitatively analyze the dependence of heat transfer performance on coating properties. For passive systems, which cannot afford active cooling due to either form factor or other application constraints, two-phase pool boiling heat transfer provides highly effective immersion cooling. Surface enhancement techniques, such as surface coatings, may further augment the cooling efficiency of such systems. The experimental study presented in this thesis analyzes the effects of variation of particle size on the pool boiling performance of FC-72 obtained by free-particle and sintered-coating enhancement techniques. In the free-particle technique, loose copper particles are placed on a heated copper surface, whereas in the sintered-coating technique, copper particles are sintered to the copper surface. The particle coatings provide additional vapor nucleation sites in the cavities formed at particle-surface and particle-particle contact points, thereby enhancing boiling performance over a polished surface. The boiling performance enhancement is studied for particle sizes varying from 45–1000 µm at a constant coating layer thickness-to-particle diameter ratio (δ/d) of approximately 4 for both techniques. High-speed flow visualizations are performed to understand the boiling patterns and bubble departure parameters that provide explanations for the trends observed in the boiling curves. The measured wall superheat is observed to be significantly lower with a sintered coating compared to the free-particle layer for any given particle size and heat flux. Performance trends with respect to particle size, however, are remarkably similar for both enhancement techniques, and an optimum particle size of ~100 µm is identified for both free particles and sintered coatings. The free-particle technique is shown to offer a straightforward method to screen the boiling enhancement trends expected from different particulate layer compositions that are intended to be subsequently fabricated by sintering. From the experimental investigation of pool boiling from coated surfaces, it was observed that for a given surface coating, several additional parameters might affect the heat transfer performance of the surface, and the coating porosity and particle morphology did not vary independent of each other. Hence, to further understand the effects of coating properties, pool boiling heat transfer of FC-72 is studied from coatings with independently varying coating porosities with two different particle morphologies. Surfaces are fabricated with same size particles (90–106 µm) having different morphologies, viz., spherical and irregular, at a constant coating layer thickness-to-particle diameter ratio (d/d) of approximately 4, with porosities varying over a wide range (∼40%–80%). The morphology and size of the particles affect the pore geometry, porosity, permeability, thermal conductivity, and other characteristics of the sintered coating. In turn, these characteristics impact the heat transfer coefficient and critical heat flux (CHF) during boiling. The porous structure formed by sintering is quantitatively characterized using image analysis and numerical simulation based on micro-computed tomography (µ-CT) scans to study the geometric and effective thermophysical properties of the coatings. Critical coating properties affecting the boiling performance metrics are identified, and regression analysis is employed to observe the dependence of these metrics on the coating properties. Coatings with irregular particles or lower porosity are observed to yield higher heat transfer coefficients than those with spherical particles or higher porosities. The relative strength of dependence of the heat transfer coefficient and CHF on the coating porosity, pore diameter distribution, particle diameter distribution, particle sphericity distribution, necking and interfacial areas, permeability, and thermal conductivity of the coatings are determined. The importance of high-fidelity coating characterization to understand the heat transfer behavior of coatings is demonstrated. Plans for future work are outlined based on the current findings. Proposed additional studies include investigation of the single bubble dynamics to further the understanding of bubble behavior that influences the heat transfer performance for free-particle and sintered-coating techniques. The quantitative regression analysis from µ-CT scans may be further extended to include a more rigorous model that employs codependence of critical inputs, to determine a predictive correlation for the boiling heat transfer performance based on coating properties

Measurement Error and the Black-White Wage Differential

This dissertation encompasses two papers. The first paper examines the impact of measurement errors in potential experience and reported education on Black-White wage differentials. I show that measurement error is not mean zero, is distributed differently for Black and White males and, for experience, is correlated with the value of the variable measured with error. Possible conditional distributions of the true values of education and experience, given reported values, are estimated using auxiliary data. This paper introduces a Maximum Likelihood method to deal with these errors, and evaluates this method as well as other methods currently used in the gender wage differential literature. The use of the Maximum Likelihood estimation method along with traditional Multi-Sample Two-Stage Least Squares reveals that a significant portion of the estimated Black-White wage differential in a classic Mincer-style regression is due to measurement error in reported educational attainment and (especially) potential experience. Use of predicted or probabilistic measures in lieu of reported education and potential experience reduce the estimated racial wage gap in the 2000 Census from 34 percent to less than 20 percent. In the second paper, I examine how the introduction of competition from Southwest Airlines affects airfares in a variety of market structures. While the consensus of the airline literature is that entry by Southwest results in substantially reduced fares on the entered and nearby routes (known as the Southwest Effect), little attention has been paid to the differing effects across routes. This paper fills this hole in the literature in two ways. First, I use difference-in-difference estimates to determine the causal effect of Southwest entry on fares using a natural experiment (the repeal of the Wright Amendment) that allowed for competition from Southwest on routes where such competition was previously illegal. I show that, consistent with the literature, the average effect on fares of competition from Southwest is substantial. However, the per-route effect varies substantially, from a fall in fares of roughly 40\% to a slight increase in fares. A fixed-effects regression centered around the repeal uncovers some of the factors behind this difference. Specifically, the presence of existing low-cost carriers and the presence of the ticketing airline in the origin and destination airports are the most important factors behind the ``Southwest Effect,\u27\u27 while the route Herfindahl and ticketing airline\u27s share of passengers on the route matter little. These results illustrate the hazards of using a small-scale case-study approach to estimating the fare effects of entry by Southwest, as well as a need for a deeper understanding behind the mechanics of the Southwest Effect

Video-aided model-based source separation in real reverberant rooms

Source separation algorithms that utilize only audio data can perform poorly if multiple sources or reverberation are present. In this paper we therefore propose a video-aided model-based source separation algorithm for a two-channel reverberant recording in which the sources are assumed static. By exploiting cues from video, we first localize individual speech sources in the enclosure and then estimate their directions. The interaural spatial cues, the interaural phase difference and the interaural level difference, as well as the mixing vectors are probabilistically modeled. The models make use of the source direction information and are evaluated at discrete timefrequency points. The model parameters are refined with the wellknown expectation-maximization (EM) algorithm. The algorithm outputs time-frequency masks that are used to reconstruct the individual sources. Simulation results show that by utilizing the visual modality the proposed algorithm can produce better timefrequency masks thereby giving improved source estimates. We provide experimental results to test the proposed algorithm in different scenarios and provide comparisons with both other audio-only and audio-visual algorithms and achieve improved performance both on synthetic and real data. We also include dereverberation based pre-processing in our algorithm in order to suppress the late reverberant components from the observed stereo mixture and further enhance the overall output of the algorithm. This advantage makes our algorithm a suitable candidate for use in under-determined highly reverberant settings where the performance of other audio-only and audio-visual methods is limited

Effects of Weather Conditions on Motorway Lane Flow Distributions

Several factors affect the lane choices made by motorway drivers. According to the driving rules, the nearside lane is the one that is primarily used. The main reasons for lane changes are overtaking, congestion, or restrictions on other lanes. The empirical research presented in this paper presents comprehensive traffic characteristics observed in different traffic lanes on four-lane motorways in Slovenia. The research was focused on the influence of adverse weather conditions on the lane flow distribution, and on the speed of vehicles in different lanes. The lane flow and speed distributions both directly affect road capacity and safety; therefore, estimating these characteristics could improve the reliability of active traffic control when traffic flow perturbation is detected. Field test results show that lane flow distributions and lane speed distributions at a particular site vary depending on weather conditions, namely, dry, wet (rain), low-visibility, and snow conditions.</p

The stochastic mortality modeling and the pricing of mortality/longevity linked derivatives

The Lee-Carter mortality model provides the very first model for modeling the mortality rate with stochastic time and age mortality dynamics. The model is constructed modeling the mortality rate to incorporate both an age effect and a period effect. The Lee-Carter model provides the fundamental set up currently used in most modern mortality modeling. Various extensions of the Lee-Carter model include either adding an extra term for a cohort effect or imposing a stochastic process for mortality dynamics. Although both of these extensions can provide good estimation results for the mortality rate, applying them for the pricing of the mortality/ longevity linked derivatives is not easy. While the current stochastic mortality models are too complicated to be explained and to be implemented, transforming the cohort effect into a stochastic process for the pricing purpose is very difficult. Furthermore, the cohort effect itself sometimes may not be significant. We propose using a new modified Lee-Carter model with a Normal Inverse Gaussian (NIG) Lévy process along with the Esscher transform for the pricing of mortality/ longevity linked derivatives. The modified Lee-Carter model, which applies the Lee-Carter model on the growth rate of mortality rates rather than the level of mortality rates themselves, performs better than the current mortality rate models shown in Mitchell et al (2013). We show that the modified Lee-Carter model also retains a similar stochastic structure to the Lee-Carter model, so it is easy to demonstrate the implication of the model. We proposed the additional NIG Lévy process with Esscher transform assumption that can improve the fit and prediction results by adapting the mortality improvement rate. The resulting mortality rate matches the observed pattern that the mortality rate has been improving due to the advancing development of technology and improvements in the medical care system. The resulting mortality rate is also developed under a martingale measure so it is ready for the direct application of pricing the mortality/longevity linked derivatives, such as q-forward, longevity bond, and mortality catastrophe bond. We also apply our proposed model along with an information theoretic optimization method to construct the pricing procedures for a life settlement. While our proposed model can improve the mortality rate estimation, the application of information theory allows us to incorporate the private health information of a specific policy holder and hence customize the distribution of the death year distribution for the policy holder so as to price the life settlement. The resulting risk premium is close to the practical understanding in the life settlement market.Information, Risk, and Operations Management (IROM