Learn More
The purpose of this study was to determine the intrarater and interrater reliability of a clinical evaluation system for scapular dysfunction. No commonly accepted terminology presently exists for describing the abnormal dynamic scapular movement patterns that are commonly associated with shoulder injury. A method of observation was devised for clinical(More)
A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of(More)
We present a method to tune software parameters using ideas from software testing and machine learning. The method is based on the key observation that for many classes of instances, the software shows improved performance if a few critical parameters have " good " values, although which parameters are critical depends on the class of instances. Our method(More)
− DeviceNet and ControlNet are two well-known idus-trial networks based on the CIP protocol (CIP = Control an Information Protocol). Both networks have been developed by Rockwell Automation, but are now owned and maintained by the two manufacturers organizations ODVA (Open DeviceNet Vendors Association, see http://www.odva.org) and ControlNet International(More)
An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and(More)
Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions. Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source: Abstract: An(More)
The support vector machine (SVM) is a flexible classification method that accommodates a kernel trick to learn nonlinear decision rules. The traditional formulation as an optimization problem is a quadratic program. In efforts to reduce computational complexity, some have proposed using an L1-norm regularization to create a linear program (LP). In other(More)
  • 1