Input variable scaling is one of the most important steps in statistical modeling. However, it has not been actively investigated, and autoscaling is mostly used. This paper proposes two input variable scaling methods for improving the accuracy of soft sensors. One method statistically derives the input variable scaling factors; the other one uses spectroscopic data of a material whose content ...

Obesity prevention interventions through dietary and physical activity change have generally not been effective. Limitations on possible program effectiveness are herein identified at every step in the mediating variable model, a generic conceptual framework for understanding how interventions may promote behavior change. To minimize these problems, and thereby enhance likely intervention effec...

reducing test suite size without compromising the suite’s effectiveness in performing regression testing. This article presents a hybrid technique using the variable-based method that combines both selection and prioritization. It considers source code changes and coverage information with respect to each test case. Variables are the vital source of changes in the program, and this method captu...

A growing body of empirical literature supports key assertions of the resource-based view. However, most of this work examines the impact of firm-specific resources on the overall performance of a firm. In this paper it is argued that, in some circumstances, adopting the effectiveness of business processes as a dependent variable may be more appropriate than adopting overall firm performance as...