The Naive Bayesian Network (NBN) classifier is an optimal classifier (in the sense of minimal classification error rate) in the case of independent descriptors or variables. The presence of dependencies between variables generally reduce his efficiency. In this article, we are proposing a new classification method named Naive Bayesian Network in the Space of Discriminants Factors (NBNSDF) which is based on the use of the NBN in the space of discriminants factors issue from a discriminant analysis. The discriminants factors are not correlated letting very efficient the use of the NBN. We found on simulated data that the NBNSDF method better detects and isolates faults in multivariate processes than the NBN in the case of strongly correlated variables.
Customer complaints data are usually expressed as counts for a period of time and are governed by a Poisson process. This process is stationary when the number of complaints is constant, while a change in these numbers would indicate a potential change in the product performance. In this paper we describe an approach for establishing the maximum tolerance level for the number of complaints received within a month. Tolerance level is based on a relatively stable period of time when the Poisson process is stationary. A change-point analysis is performed to the complaints data that exhibit large changes to partition the relatively stable period from the problematic period. Examples that illustrate this approach are provided.
Customer satisfaction as the key element for success in business is a major concern for any industry. In this paper we propose a customer satisfaction index using principal component analysis for a software solution company. This index was used as an input to the marketing division to identify their potential customers from their past experience. Since this is a very common problem for any industry, the same approach can be used in similar situations.
The continued rapid worldwide diffusion of clinical hyperbaric facilities has substantially increased interest in clinical quality assessment and service improvement. This paper examines major issues, perspectives, and methods integral to the measurement and improvement of the quality of care provided to hyperbaric patients and their relevance and applicability across different societies. Special focus is directed toward the importance of quality assessment and improvement of clinical hyperbaric care, multiple stakeholder perspectives on improved clinical quality, measurement of clinical outcomes of hyperbaric care, importance of facility accreditation, process improvement methods, and the future importance of quality management in clinical hyperbaric facilities.
Peer Review is commonly applied during the final stage of a project and is used in the science community to determine the soundness of a conclusion and if the quality of information meets the standards of the scientific and technical community. Quality Assurance and Quality Control procedures are most effective when applied to planning, then during the process stage of a project, and during the review of a product. The gold standard for validating the quality of a study's results is comparison with a referenced data set, model, or result (Azouzi, 1999). However, costs can severely limits this approach for many applications. This article proposes an additional means for quality assessment using peer review as a quality assessment tool during the planning, process, and review of a project.
