Selecting the Right Improvement Projects

Selecting the Right Algorithm

Computer scientists always strive to find better and faster algorithms for any computational problem. It is usually true that programmers and/or users come across a plethora of different algorithms when looking to solve a particular problem efficiently. Each one of these algorithms might offer different guarantees and properties, but it is unlikely that a single one of them is the best (fastest...

Selecting the right medical student

Medical student selection is an important but difficult task. Three recent papers by McManus et al. in BMC Medicine have re-examined the role of tests of attainment of learning (A' levels, GCSEs, SQA) and of aptitude (AH5, UKCAT), but on a much larger scale than previously attempted. They conclude that A' levels are still the best predictor of future success at medical school and beyond. Howeve...

Reconcile sequence improvement projects

Introduction This document describes the strategies for reconciling a GEP sequence improvement project that has been improved by multiple students. The reconciliation process seeks to generate the most accurate sequence assembly possible by comparing the multiple assemblies. Discrepant regions among the different assemblies can help the reviewer identify problematic regions in the assembly that...

Selecting the right medical adhesive tape

Selecting the Right Heuristic Algorithm : Runtime Performance

It is obvious that, given a problem instance, some heuris-tic algorithms can perform vastly better than others; however, in most cases the existing literature provides little guidance for choosing the best heuristic algorithm. This paper describes how runtime performance pre-dictors can be used to identify a good algorithm for a particular problem instance. The approach is demonstrated on two f...