Reliability of radiographic parameters in adenoid evaluation

The assessment of adenoids by x-ray imaging has been the topic of heated debate, but few studies have looked into the reliability of most existing radiographic parameters. Objective: This study aims to verify the intra-examiner and inter-examiner reproducibility of the adenoid radiographic assessment methods. Materials and Methods: This is a cross-sectional case series study. Forty children of both genders aged between 4 and 14 were enrolled. They were selected based on complaints of nasal obstruction or mouth breathing and suspicion of pharyngeal tonsil hypertrophy. Cavum x-rays and orthodontic teleradiographs were assessed by two examiners in quantitative and categorical terms. Results: All quantitative parameters in both x-ray modes showed excellent intra and inter-examiner reproducibility. Relatively better performance was observed in categorical parameters used in cavum x-ray assessment by C-Kurien, C-Wang, C-Fujioka, and C-Elwany over C-Cohen and C-Ysunza. As for orthodontic teleradiograph grading systems, C-McNamara has been proven to be more reliable than C-Holmberg. Conclusion: Most instruments showed adequate reproducibility levels. However, more research is needed to properly determine the accuracy and viability of each method.

A review and evaluation on constructive heuristics to optimise product mix based on the Theory of Constraints

In this paper, we address the problem of defining the product mix in order to maximise a system's throughput. This problem is well known for being NP-Complete and therefore, most contributions to the topic focus on developing heuristics that are able to obtain good solutions for the problem in a short CPU time. In particular, constructive heuristics are available for the problem such as that by Fredendall and Lea, and by Aryanezhad and Komijan. We propose a new constructive heuristic based on the Theory of Constraints and the Knapsack Problem. The computational results indicate that the proposed heuristic yields better results than the existing heuristic.