Bayesian Classifiers Applied to the Tennessee Eastman Process

Fault diagnosis includes the main task of classification. Bayesian networks (BNs) present several advantages in the classification task, and previous works have suggested their use as classifiers. Because a classifier is often only one part of a larger decision process, this article proposes, for industrial process diagnosis, the use of a Bayesian method called dynamic Markov blanket classifier that has as its main goal the induction of accurate Bayesian classifiers having dependable probability estimates and revealing actual relationships among the most relevant variables. In addition, a new method, named variable ordering multiple offspring sampling capable of inducing a BN to be used as a classifier, is presented. The performance of these methods is assessed on the data of a benchmark problem known as the Tennessee Eastman process. The obtained results are compared with naive Bayes and tree augmented network classifiers, and confirm that both proposed algorithms can provide good classification accuracies as well as knowledge about relevant variables.     

Bayesian Treatment of Model Uncertainty for Partially Applicable Models

This article discusses how analyst's or expert's beliefs on the credibility and quality of models can be assessed and incorporated into the uncertainty assessment of an unknown of interest. The proposed methodology is a specialization of the Bayesian framework for the assessment of model uncertainty presented in an earlier paper. This formalism treats models as sources of information in assessing the uncertainty of an unknown, and it allows the use of predictions from multiple models as well as experimental validation data about the models’ performances. In this article, the methodology is extended to incorporate additional types of information about the model, namely, subjective information in terms of credibility of the model and its applicability when it is used outside its intended domain of application. An example in the context of fire risk modeling is also provided.     

Observed and parent‐reported conscience in childhood: Relations with bullying involvement in early primary school

This exploratory study aimed to examine which components of early childhood conscience predicted bullying involvement around school entry. In the population‐based Generation R Study, teacher reports of bullying involvement and parent reports of conscience were available for 3,244 children (M age = 6.7 years). Higher levels of overall conscience predicted lower bullying perpetration scores, independently of intelligence quotient, temperamental traits and sociodemographic characteristics. Particularly, the subscales guilt, confession, and internalized conduct, and to a lesser extent empathy, predicted bullying perpetration. Conscience was not related to victimization. Similar results were found using observations during so‐called ‘cheating games’ (subsample N = 450 children). Findings suggest that improving children's understanding of moral standards and norms may be a potential target for bullying intervention programs in early primary school.     

Introductory Statistics Textbooks and the GAISE Recommendations

The six recommendations made by the Guidelines for Assessment and Instruction in Statistics Education (GAISE) committee were first communicated in 2005 and more formally in 2010. In this article, 25 introductory statistics textbooks are examined to assess how well these textbooks have incorporated the three GAISE recommendations most relevant to implementation in textbooks (statistical literacy and thinking; use of real data; stress concepts over procedures). The implementation of another recommendation (using technology) is described but not assessed. In general, most textbooks appear to be adopting the GAISE recommendations reasonably well in both exposition and exercises. The textbooks are particularly adept at using real data, using real data well, and promoting statistical literacy. Textbooks are less adept—but still rated reasonably well, in general—at explaining concepts over procedures and promoting statistical thinking. In contrast, few textbooks have easy-usable glossaries of statistical terms to assist with understanding of statistical language and literacy development. Supplementary materials for this article are available online.     

Social network effects on academic achievement

How peer groups contribute to educational outcomes has long interested researchers. However, the possibility that peer groups dominated by either low- or high-achieving youth can have substantively different effects on achievement has been largely ignored. In this paper, we show that while being embedded in a high-achieving network of friends is not associated with increased own achievement, being embedded in a low-achieving network is associated with decreased own achievement. In additional analyses, we present evidence that these associations are at least in part due to influence, as opposed to only selection effects or shared environment. We also examine whether the structure of the network in which a student is embedded might affect their educational achievement. We show that achieving at higher levels positively predicts how centrally located a student is in their network, but being more centrally located does not predict concurrent achievement. This finding suggests that the behavior of individuals is affecting the formation of network structure and not the reverse.     

Restructuring of the Financial Industry: The Disappearance of Locally Owned Traditional Financial Services in Rural America

Restructuring in the financial services industry has altered the relationship between small business owners and capital. In the past small businesses have relied on relational, or soft data, lending from locally owned banks for capital. The proliferation of absentee‐owned local branch networks brought standardized practices, thus eliminating the autonomy of local loan officers to utilize soft data in loan decisions. In this article we examine the changes in the percentage of traditional financial services that are locally owned in three county types: metropolitan, micropolitan, and noncore. We utilize the Longitudinal Business Database at the U.S. Census Bureau Center for Economic Studies. We examine changes in local ownership of traditional financial services between 1976 and 2007. We find that the rate of decline of local ownership has been greatest in the noncore (most rural) counties. We also explore to what extent these patterns are related to the emergence of alternative financial services during the same period. We find that such alternative services are growing in all three county types, but at rates not significantly different than the population growth for these county types. We supplement our analysis with data from qualitative interviews with small business owners throughout rural Texas. We conclude with a discussion of implications and plans for future research.     

Impact of Gender Binarism on Hijras’ Life Course and Their Access to Fundamental Human Rights in Pakistan

This study adds to the growing body of knowledge on gender nonconformity aspects of heteronormativity by examining its impact on the life course of hijras and their access to fundamental human rights in Pakistan. Drawing on 50 semistructured interviews conducted in two sites, the findings suggest that the participants’ lived experiences associated with gender nonconformity significantly influenced the direction of their life course and their ability to have access to human rights. These experiences spanned from childhood to elderhood across a wide range of settings, such as family, school, guru dera (residence headed by a hijra guru), workplace, and interactions with authorities. The participants’ human rights were not recognized, resulting in abuse, social stigma, discrimination against them, and their exclusion from mainstream society. Finally, implications are drawn for public policy and future research on third gender concerns in Pakistan and elsewhere.     

A comparative study of social assistance systems in Macao and Hong Kong

This article compares social assistance systems in Macao and Hong Kong. It finds that Macao delivers a higher level of social assistance benefits, whereas Hong Kong has a larger group of social assistance beneficiaries. The Hong Kong Government spends a larger amount on social assistance provision and imposes tougher controls on the recipients, compared to Macao. The results of the comparison indicate that Macao and Hong Kong differ markedly in the type of productivist welfare regime they belong and challenge the assertion that the two welfare systems form a distinct welfare model.