Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

How to make a greedy heuristic for the asymmetric traveling salesman problem competitive

It is widely confirmed by many computational experiments that a greedy type heuristics for the Traveling Salesman Problem (TSP) produces rather poor solutions except for the Euclidean TSP. The selection of arcs to be included by a greedy heuristic is usually done on the base of cost values. We propose to use upper tolerances of an optimal solution to one of the relaxed Asymmetric TSP (ATSP) to guide the selection of an arc to be included in the final greedy solution. Even though it needs time to calculate tolerances, our computational experiments for the wide range of ATSP instances show that tolerance based greedy heuristics is much more accurate an faster than previously reported greedy type algorithms

Bayesian Modeling of Latent Heterogeneity in Complex Survey Data and Electronic Health Records

In population health, the study of unobserved, or latent, heterogeneity in longitudinal data may help inform public health interventions. Growth mixture modeling is a flexible tool for modeling latent heterogeneity in longitudinal data. However, the application of growth mixture models to certain data types, namely, complex survey data and electronic health records, is underdeveloped. For valid statistical inferences in complex survey data, features of the sample design must be incorporated into statistical analysis. In electronic health records, the application of growth mixture modeling is challenged by high levels of missing values. In this dissertation, I have three goals: First, I propose a Bayesian growth mixture model for complex survey data in which I directly incorporate features of the complex sample design. Second, I extend a Bayesian growth mixture model of multiple longitudinal health outcomes collected in electronic health records to a shared parameter model that can account for dierent missing data assumptions. Third, I develop open-source software packages in R for each method that can be used for model tting, selection, and checking

Uniform color space analysis of LACIE image products

The author has identified the following significant results. Analysis and comparison of image products generated by different algorithms show that the scaling and biasing of data channels for control of PFC primaries lead to loss of information (in a probability-of misclassification sense) by two major processes. In order of importance they are: neglecting the input of one channel of data in any one image, and failing to provide sufficient color resolution of the data. The scaling and biasing approach tends to distort distance relationships in data space and provides less than desirable resolution when the data variation is typical of a developed, nonhazy agricultural scene

Competitive Markets with Endogenous Health Risks

We study a general equilibrium model where agents’ preferences, productivity and labor endowments depend on their health status, and occupational choices affect individual health distributions. Efficiency typically requires agents of the same type to obtain different expected utilities if assigned to di¤erent occupations. Under mild assumptions, workers with riskier jobs must get higher expected utilities if health a¤ects production capabilities. The same holds if health affects preferences and health enhancing consumption activities are sufficiently effective, so that income and health are substitutes. The converse obtains when health a¤ects preferences, but health enhancing consumption activities are not very effective, and hence income and health are complements. Competitive equilibria are first-best if lottery contracts are enforceable, but typically not if only assets with deterministic payoffs are traded. Compensating wage differentials which equalize the utilities of workers in different jobs are incompatible with ex-ante efficiency. Finally, absent asymmetric information, there exist deterministic cross-jobs transfers leading to ex-ante efficiency.compensating wage differentials, competitive markets, individual health risks, Pareto efficiency

Multi-Agent Goal Assignment with Finite-Time Path Planning

Minimising the longest travel distance for a group of mobile robots with interchangeable goals requires knowledge of the shortest length paths between all robots and goal destinations. Determining the exact length of the shortest paths in an environment with obstacles is challenging and cannot be guaranteed in a finite time. We propose an algorithm in which the accuracy of the path planning is iteratively increased. The approach provides a certificate when the uncertainties on estimates of the shortest paths become small enough to guarantee the optimality of the goal assignment. To this end, we apply results from assignment sensitivity assuming upper and lower bounds on the length of the shortest paths. We then provide polynomial-time methods to find such bounds by applying sampling-based path planning. The upper bounds are given by feasible paths, the lower bounds are obtained by expanding the sample set and leveraging knowledge of the sample dispersion. We demonstrate the application of the proposed method with a multi-robot path-planning case study

Rent, occupancy and performance : a case study of apartment management

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1987.Bibliography: leaves 67-68.by Dale Matthew Mumford and William Schein.M.S