Utilizing fuzzy compatibility of skill sets for team selection in multi-phase projects

In this paper, a model is developed for the selection of personnel for a multiple phase project which takes into account the match between the skills possessed by each individual, the skills needed for each phase, and rather flexible budget considerations. The algorithm uses the fuzzy construct of compatibility to measure the fit of a person’s skill set to the goal set for each project phase. Based on the individual fuzzy compatibility measures, the team is formed from combined levels of compatibility and acceptable levels of quality defined for the goal set. 1 and 2 present the background information necessary to an understanding of project management phases and compatibility of skills. The development of the model and subsequent algorithm in 3 and 4, respectively rely on fuzzy measures of compatibility. Finally, an application is presented in Section 4 with conclusions stated in Section 5.     

Implementation and evaluation of an HIV/STD intervention in Peru

This paper presents the lessons learned through a process evaluation (PE) after 1 year of implementation of a 2-year community intervention in Lima, Peru. The intervention consisted of training and motivating community popular opinion leaders (CPOLs) for three marginal population segments to disseminate prevention messages among their peers. PE data included: observations, qualitative interviews with CPOLS, conversations and messages delivered by CPOLs, training facilitators' perceptions about implementation, and a survey of CPOLs. The PE helped to document and enhance the intervention. CPOLs were motivated to talk to their peers. CPOLs perceived that their participation had an effect on their own risk behaviors and saw their role as beneficial to their community. The PE was helpful in examining training delivery and the feasibility and acceptability of the intervention in order to assess the elements related to program success necessary to replicate the CPOL model.     

Imputation in Data Fusion of Heterogeneous Data Sets A Model-Based Numerical Experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.     

A Comparative Exposure Assessment of Campylobacter in Ontario,Canada

To inform source attribution efforts, a comparative exposure assessment was developed to estimate the relative exposure to Campylobacter, the leading bacterial gastrointestinal disease in Canada, for 13 different transmission routes within Ontario, Canada, during the summer. Exposure was quantified with stochastic models at the population level, which incorporated measures of frequency, quantity ingested, prevalence, and concentration, using data from FoodNet Canada surveillance, the peer‐reviewed and gray literature, other Ontario data, and data that were specifically collected for this study. Models were run with @Risk software using Monte Carlo simulations. The mean number of cells of Campylobacter ingested per Ontarian per day during the summer, ranked from highest to lowest is as follows: household pets, chicken, living on a farm, raw milk, visiting a farm, recreational water, beef, drinking water, pork, vegetables, seafood, petting zoos, and fruits. The study results identify knowledge gaps for some transmission routes, and indicate that some transmission routes for Campylobacter are underestimated in the current literature, such as household pets and raw milk. Many data gaps were identified for future data collection consideration, especially for the concentration of Campylobacter in all transmission routes.     

The Interdependent Family‐Centric Career: Career Perspective of the Overseas Chinese in Indonesia

This theoretical article presents an interdisciplinary approach to extend the scope of current career theories and their application to the overseas Chinese (OC) in Indonesia. Using an ecological model to analyze culture and an emic perspective, the article discusses several factors that affect careers of OC Indonesians. Factors such as culture, discrimination, subjective careers, Confucian values, and family business structure are discussed as variables that create a bounded career perspective. This conceptual view is used as a foundation to discuss the needs for future research and the development of a cross‐cultural career model that is applicable in bounded career environments.     

Needed but Not Liked – The Impact of Labor Market Policies on Natives’ Opinions about Immigrants

This article builds on the notion that immigrants’ integration into the labor market benefits migrants and shapes natives’ opinions about immigrants. Using insights from the newest literature on labor immigration and drawing upon the literature on attitudes toward immigrants, the article explores in a multilevel design the impact that regulations in the EU member states concerning immigrants’ access to domestic labor markets have on threat perceptions and on opinions about immigrants’ economic role. It finds that labor market regulations have a positive effect on opinions about immigrants’ economic role and reduce the negative relationships between precarious labor market status and opinions about the economic role. However, a robust effect of labor market regulations on threat perceptions was not found. Our results imply that labor market incorporation rules need to be accompanied by other measures to close the gap between natives and immigrants.     

Constructing the digital patient: Patient organizations and the development of health websites

In order to understand the constraints and challenges of realizing the democratic potentials of the Internet, this paper focuses on the attempts of three Dutch patient organizations to develop health websites. The authors describe how these patient organizations had to overcome specific barriers to develop their digital services. All three organizations faced certain constraints that had negative consequences for the plans they wanted to realize. Lack of financial resources and manpower were the main reasons why these patient organizations could not develop interactive parts of their website or provide personal advice services. Other barriers the patient organizations had to overcome were getting access to digital expertise to build the websites. The paper shows that the development of a website is a very demanding task, even for patient organizations that have in-house expertise with computers and Internet. Moreover, the paper shows that patient organizations do not consider the involvement of patients as crucial for the design of health websites. This research thus confirms previous research findings that users, in this case patients, are largely absent from the design process of information and communication technologies Finally, the paper shows how patient organizations' websites contribute to a redefinition of the patient from being a passive actor towards one who is an active participant in his or her care.     

Strong invariance principles for triangular arrays of weakly dependent random variables

We establish a strong invariance principle for triangular arrays of a broad class of weakly dependent real random variables. We approximate the original array of dependent random variables by an array of rowwise independent standard normal variables. We demonstrate the functional central limit theorem and law of the iterated logarithm for the approximating array and thereby extend these results to the original array. Among several examples, we look at arrays used in describing the rate of convergence of estimators in regression analysis.