Sound exposure effects have been investigated by broadcasting a group of broilers with sound of Quran verses (Group B) whereas the other group is the control broilers (Group C). The growth rate comparisons in terms of weight and raw meat texture measured by shear force have been investigated. Twenty-seven broilers were randomly selected from each group on Day 24 and weight measurement was carri...

This article analyzes the interactions through which primary-care nurses and patients accomplish patient weighing. The analysis is based on videotaped nurse-adult patient interactions in clinics in the area of Southern California. Detailed examination of co-participants' naturally situated weighing conduct shows that parties recurrently deliver utterances that go beyond that required to accompl...

Introduction: Medical tourism is currently accepted as a developing industry. It describes the act of leaving home for treatment and care abroad. There are several factors that influence choice of destination for patients in medical tourism. Identification of these factors and prioritization according to importance weights could help international healthcare providers develop t...

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Importance sampling is an efficient strategy for reducing the variance of certain bootstrap estimates. It has found wide applications in bootstrap quantile estimation, proportional hazards regression, bootstrap confidence interval estimation, and other problems. Although estimation of the optimal sampling weights is a special case of convex programming, generic optimization methods are frustrat...

ATTRIBUTE IMPORTANCE WEIGHTS IN CONJOINT ANALYSIS: BIAS AND PRECISION Sanjay Mishra, Washington State University U. N. Umesh, Washington State University Donald E. Stem, Jr., Washington State University ABSTRACT Consumer researchers have used conjoint analysis to evaluate the importance of an attribute in forming preferences. Although past researchers have tested the validity and reliability of...

BACKGROUND Longitudinal data sources, such as electronic health records (EHRs), are very valuable for monitoring adverse drug events (ADEs). However, ADEs are heavily under-reported in EHRs. Using machine learning algorithms to automatically detect patients that should have had ADEs reported in their health records is an efficient and effective solution. One of the challenges to that end is how...

We propose a sample-efficient alternative for importance weighting for situations where one only has sample access to the probability distribution that generates the observations. Our new method, called Recurrence Weighting (RW), is described and analyzed in the context of online combinatorial optimization under semi-bandit feedback, where a learner sequentially selects its actions from a combi...