BACKGROUND Data requirements by governments, donors and the international community to measure health and development achievements have increased in the last decade. Datasets produced in surveys conducted in several countries and years are often combined to analyse time trends and geographical patterns of demographic and health related indicators. However, since not all datasets have the same s...

BACKGROUND Studies of the effect of exposure to a risk factor measured in an entire cohort may be augmented by nested case-control subsets to investigate confounding or effect modification by additional factors not practically assessed on all cohort members. We compared three control-selection strategies-matching on exposure, counter matching on exposure, and random sampling-to determine which ...

BACKGROUND This study was carried out to use multiple imputation (MI) in order to correct for the potential nonresponse bias in measurements related to variable fasting blood glucose (FBS) in non-communicable disease risk factors survey conducted in Iran in 2007. METHODS Five multiple imputation methods as bootstrap expectation maximization, multivariate normal regression, univariate linear r...

The standard second-order matching algorithm by Huet may be expansive in matching a exible-rigid pair. On one hand, many fresh free variables may need to be introduced; on the other hand, attempts are made to match the heading free variable on the exible side with every \top layer" on the rigid side and every argument of the heading free variable with every subterm covered by the \top layer". W...

A palindrome is a string that reads the same forward and backward. We say that two strings of the same length are pal-equivalent if for each possible center they have the same length of the maximal palindrome. Given a text T of length n and a set of patterns P1, . . . , Pk, we study the online multiple palindrome pattern matching problem that finds all pairs of an index i and a pattern Pj such ...

We investigate the problem of deterministic pattern matching in multiple streams. In this model, one symbol arrives at a time and is associated with one of s streaming texts. The task at each time step is to report if there is a new match between a fixed pattern of length m and a newly updated stream. As is usual in the streaming context, the goal is to use as little space as possible while sti...

Permutations and matchings are core building blocks in a variety of latent variable models, as they allow us to align, canonicalize, and sort data. Learning in such models is difficult, however, because exact marginalization over these combinatorial objects is intractable. In response, this paper introduces a collection of new methods for end-to-end learning in such models that approximate disc...

We examine scheduling problems where we control not only the assignment of jobs to machines, but also the time used by the job on the machine. For instance, many tooling machines allow control of the speed at which a job is run. Increasing the speed incurs costs due to machine wear but also increases throughput. We discuss some fundamental scheduling problems in this environment and give algori...

With the advance in remote sensing, various machine learning techniques could be applied to study variable relationships. Although prediction models obtained by using machine learning techniques are suitable for predictions, they do not explicitly provide means for determining input-output variable relevance. The relevance information is often of interest to scientists since relationships among...

This paper describes the development of a Bayesian framework for multiple graph matching. The study is motivated by the plethora of multi-sensor fusion problems which can be abstracted as multiple graph matching tasks. The study uses as its starting point the Bayesian consistency measure recently developed by Wilson and Hancock. Hitherto , the consistency measure has been used exclusively in th...