Modeling NO Emissions of an Off-road Diesel Engine Based on Emission Tests

Emissions values determined by the ISO 8178 emission certification tests do not necessarily represent emissions of a tractor in operation (Hansson et al., 2001). Rather than using ISO 8178 tests solely for certification, data collected during the tests may be suitable for predicting nitrogen oxide (NOx) emissions of an engine operating at constant loads and speeds. Linear multiple regression (LMR) and nonlinear polynomial network (NPN) models were developed with data collected from ISO 8178-4 (1996) test cycle B-type tests (ISO) and an expanded set of tests (EXP) to predict NOx emissions from a diesel engine. LMR using the ISO training data (R2 = 0.94) resulted in over-training of the model, as applied to the evaluation data (R2 = 0.51). LMR based on the expanded data (R2 = 0.60) was a better LMR model, when applied to the evaluation data (R2 = 0.73). NPN using the ISO training data (R2 = 0.99) resulted in a considerable improvement over the LMR models for the evaluation data (R2 = 0.81). NPN using the EXP training data (R2 = 0.96) resulted in the best model when applied to the evaluation data (R2 = 0.95). When applied to the evaluation data, the mean absolute error of the NPN EXP based model was significantly less than from the NPN ISO based model. The NPN model based on EXP data is recommended for predicting NOx. Data could be collected during ISO 8178-4 emission tests that included additional test modes and modeled with NPN to predict NOx emissions for a diesel engine operating at various constant speeds and loads

Analysis of the Factors that Impacting the MVA of Brazilian Public Companies: Does EVA® is more Value Relevant than the Traditional Performance Indicators?

This study aimed to analyze the explanatory power of EVA® and others traditional accounting indicators, assessing which of these measures is more related to the creation of shareholder wealth. Therefore, we analyzed 748 firms-years between 2005 and 2010. Through the use of pooled of ordinary least square regressions (POLS), we tested the informational content of EVA and traditional indicators, individually and together, as to the explanation of the market value added as a proxy for the generation of wealth for investors. Therefore, we used five univariate equations for the purpose of analyzing the explanatory power for each of the variables used in the study, whether accounting variables or EVA. After that, we used two multivariate models: one containing only the traditional accounting variables and the other with the addition of EVA, testing, through the Wald test, the hypothesis that EVA adds informative content to traditional accounting indicators. According to this methodology, it was observed that EVA is not more value Relevant than traditional indicators by univariate models, but add informative content to the set of indicators, in the joint analysis by multivariate models