Applying the Mahalanobis-Taguchi System to Vehicle Handling

The Mahalanobis-Taguchi system (MTS) is a diagnosis and forecasting method using multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and patterns that can be identified and analyzed with respect to a base or reference group. The MTS is of interest because of its reported accuracy in forecasting using small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This article presents the application of the MTS, its applicability in identifying a reduced set of useful variables in multidimensional systems, and a comparison of results with those obtained from a standard statistical approach to the problem

An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class

CD4 T Cell Immunity Is Critical for the Control of Simian Varicella Virus Infection in a Nonhuman Primate Model of VZV Infection

Primary infection with varicella zoster virus (VZV) results in varicella (more commonly known as chickenpox) after which VZV establishes latency in sensory ganglia. VZV can reactivate to cause herpes zoster (shingles), a debilitating disease that affects one million individuals in the US alone annually. Current vaccines against varicella (Varivax) and herpes zoster (Zostavax) are not 100% efficacious. Specifically, studies have shown that 1 dose of varivax can lead to breakthrough varicella, albeit rarely, in children and a 2-dose regimen is now recommended. Similarly, although Zostavax results in a 50% reduction in HZ cases, a significant number of recipients remain at risk. To design more efficacious vaccines, we need a better understanding of the immune response to VZV. Clinical observations suggest that T cell immunity plays a more critical role in the protection against VZV primary infection and reactivation. However, no studies to date have directly tested this hypothesis due to the scarcity of animal models that recapitulate the immune response to VZV. We have recently shown that SVV infection of rhesus macaques models the hallmarks of primary VZV infection in children. In this study, we used this model to experimentally determine the role of CD4, CD8 and B cell responses in the resolution of primary SVV infection in unvaccinated animals. Data presented in this manuscript show that while CD20 depletion leads to a significant delay and decrease in the antibody response to SVV, loss of B cells does not alter the severity of varicella or the kinetics/magnitude of the T cell response. Loss of CD8 T cells resulted in slightly higher viral loads and prolonged viremia. In contrast, CD4 depletion led to higher viral loads, prolonged viremia and disseminated varicella. CD4 depleted animals also had delayed and reduced antibody and CD8 T cell responses. These results are similar to clinical observations that children with agammaglobulinemia have uncomplicated varicella whereas children with T cell deficiencies are at increased risk of progressive varicella with significant complications. Moreover, our studies indicate that CD4 T cell responses to SVV play a more critical role than antibody or CD8 T cell responses in the control of primary SVV infection and suggest that one potential mechanism for enhancing the efficacy of VZV vaccines is by eliciting robust CD4 T cell responses

Identifying Useful Variables for Vehicle Braking Using the Adjoint Matrix Approach to the Mahalanobis-Taguchi System

The Mahalanobis Taguchi System (MTS) is a diagnosis and forecasting method for multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. MTS is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This paper presents the application of the Adjoint Matrix Approach to MTS for vehicle braking to identify a reduced set of useful variables in multidimensional systems

Applying the Mahalanobis-Taguchi System to Vehicle Ride

The Mahalanobis Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. The Mahalanobis-Taguchi System is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This paper presents the application of the Mahalanobis-Taguchi System and its application to identify a reduced set of useful variables in multidimensional systems

A Comparison of Techniques to Forecast Consumer Satisfaction for Vehicle Ride

This paper presents a comparison of methods for the identification of a reduced set of useful variables using a multidimensional system. The Mahalanobis-Taguchi System and a standard statistical technique are used to reduce the dimensionality of vehicle ride based on consumer satisfaction ratings. The Mahalanobis-Taguchi System and cluster analysis are applied to vehicle ride. The research considers 67 vehicle data sets for the 6 vehicle ride parameters. This paper applies the Mahalanobis-Taguchi System to forecast consumer satisfaction and provides a comparison of results with those obtained from a standard statistical approach to the problem

Quality Loss Function - a Common Methodology for Three Cases

The quality loss function developed by Genichi Taguchi considers three cases, nominal-thebest, smaller-the-better, and larger-the-better. The methodology used to deal with the larger-thebetter case is slightly different than the other two cases. This research employs a term called target-mean ratio to propose a common formula for all three cases to bring about similarity among them. The target-mean ratio can take different values representing all three cases to bring consistency and simplicity in the model. In addition, it eliminates the assumption of target performance at an infinite level and brings the model closer to reality. Characteristics such as efficiency, coefficient of performance, and percent non-defective are presently not larger-thebetter characteristics due to the assumption of target performance at infinity and the subsequent necessary derivation of the formulae. These characteristics can also be brought under the category of the larger-the-better characteristics. An example of the efficiency of prime movers is discussed to illustrate that the efficiency can also be considered as a larger-the-better characteristic. A second example is presented to suggest the subtle differences between both methodologies