A reference model for collaborative design in mould industry

The mould industry is an indispensable foundation for mass production by manufacturer and influences the time to market of new product. It is difficult to integrate the new product development processes and information systems among the mould companies which are mainly small and medium enterprises. The design chain operations reference-model (DCOR) provides a well-recognised methodology to standardise the management process for a product development project and enables the integration for mould industry. The DCOR focuses on a primary and preliminary product development process and is necessary to extend the detail templates for the industrial requirements. Hence, the purpose of this research is to develop an approach that extends the DCOR to the mould industry. The framework of the developed model, which is called the design chain operations reference-model for the mould industry, is adopted for a case mould company for a feasibility discussion.     

Approximation algorithms for connected facility location problems

We study Connected Facility Location problems. We are given a connected graph G=(V,E) with nonnegative edge cost c _e for each edge e∈E, a set of clients D⊆V such that each client j∈D has positive demand d _j and a set of facilities F⊆V each has nonnegative opening cost f _i and capacity to serve all client demands. The objective is to open a subset of facilities, say , to assign each client j∈D to exactly one open facility i(j) and to connect all open facilities by a Steiner tree T such that the cost is minimized for a given input parameter M≥1. We propose a LP-rounding based 8.29 approximation algorithm which improves the previous bound 8.55 (Swamy and Kumar in Algorithmica, 40:245–269, 2004). We also consider the problem when opening cost of all facilities are equal. In this case we give a 7.0 approximation algorithm.     

Simplified Maximum Likelihood Inference Based on the Likelihood Decomposition for Missing Data

In this paper, we propose an estimation method when sample data are incomplete. We decompose the likelihood according to missing patterns and combine the estimators based on each likelihood weighting by the Fisher information ratio. This approach provides a simple way of estimating parameters, especially for non‐monotone missing data. Numerical examples are presented to illustrate this method.     

Directional Dependence of Genes Using Survival Truncated FGM Type Modification Copulas

Ordinal data, such as student's grades or customer satisfaction surveys, are widely used in daily life. We can fit a probit or logistic regression model to the ordinal data using software such as SAS and get the estimates of regression parameters. However, it is hard to define residuals and detect outliers due to the fact that the estimated probabilities of an observation falling in every category form a vector instead of a scalar. With the help of latent variable and latent residuals, a Bayesian perspective of detecting outliers is explored and several methods were proposed in this article. Several figures are also given.     

Bayesian False Discovery Rate Wavelet Shrinkage: Theory and Applications

Statistical inference in the wavelet domain remains a vibrant area of contemporary statistical research because of desirable properties of wavelet representations and the need of scientific community to process, explore, and summarize massive data sets. Prime examples are biomedical, geophysical, and internet related data. We propose two new approaches to wavelet shrinkage/thresholding.

In the spirit of Efron and Tibshirani's recent work on local false discovery rate, we propose Bayesian Local False Discovery Rate (BLFDR), where the underlying model on wavelet coefficients does not assume known variances. This approach to wavelet shrinkage is shown to be connected with shrinkage based on Bayes factors. The second proposal, Bayesian False Discovery Rate (BaFDR), is based on ordering of posterior probabilities of hypotheses on true wavelets coefficients being null, in Bayesian testing of multiple hypotheses.

We demonstrate that both approaches result in competitive shrinkage methods by contrasting them to some popular shrinkage techniques.     

A Regression Model for the AUC of Clustered Ordinal Test Results and Working Independent Optimal Weights

We study a regression model on the area under the receiver operating characteristic curves (AUC) for clustered (or repeatedly measured) test results. To account for cluster information, we consider a weighted estimating equation for Dodd and Pepe (2003 Dodd , L. , Pepe , M. ( 2003 ). Semiparametric regression for the area under the receiver operating charateristic curve . Journal of the American Statistical Association 98 : 409 – 417 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar])'s regression model with working independence weights. We find the optimal weight in the given class of working independence weights to minimize the variance (or MSE) of regression estimators. We apply the proposed procedure to analyzing our recent experiment on diagnosing a liver disorder. In this experiment, we investigated MRI images of patients having symptoms of potential liver disorder to compare the performance of different MRI picturing methods in testing for liver disorders.     

Incorporating regulatory focus theory in product recall communications to increase compliance with a product recall

Product recall communications with consumers is an important yet under-researched area of crisis management. This study examines whether applying regulatory focus theory in product recall communications can help companies involved in a product recall. This study examines the issue with a product recall message related to laptop computers. We find that creating regulatory fit through the product recall message increases intentions to comply with a product recall request, however future purchase intentions are also adversely impacted. We believe that the benefits of increased compliance greatly outweigh the small decrease in future purchase intentions, and companies should seriously consider incorporating regulatory focus theory in their product recall communications.     

Work of Full‐Time Mothers: Putting Voice to the Relational Theory of Working

The purpose of this qualitative research was to explore the work experience of middle‐class, Korean full‐time mothers in their 50s. Interviews, observations, and photographs were collected from 11 Korean full‐time mothers to understand their work and career experiences. The data were analyzed by a case study qualitative method of inquiry. The themes that emerged from the data were paths to becoming full‐time mothers, multiple working roles from relationships, dialectical characteristics of work, meaning of full‐time mothering, and regrets and internalized biases for full‐time motherhood. The findings illustrate how full‐time mothers experience a sense of meaning and mattering from their work; how relationships and work are intertwined in their lives; and how gender, social class, and culture influence the work and relationships of full‐time mothers. Implications for counselors and researchers are discussed.     

Membership Benefits Matter

Professional associations have provided various benefits to their members to bolster member retention and recruitment. This study explored factors that could influence members’ behavioral intentions in professional membership associations by surveying 13,229 members from eighteen associations. More specifically, this analysis focused on the effects of members’ perceptions of the personal and professional benefits offered by associations with which they are affiliated and their satisfaction with those benefits. Our results suggested that members’ perceptions of personal and professional benefits positively correlated with their intentions to renew and recommend membership. If a member perceived a higher level of benefits, he or she would demonstrate a greater likelihood of satisfaction with the benefits and therefore be more likely to renew membership or recommend it to others. This study could advance understanding of the factors that influence members’ behavioral intentions while also providing professional associations with strategies for retaining existing members.