This cross-sectional study examined accelerated second-degree (n = 117) and traditional (n = 71) baccalaureate nursing (BSN) graduates from a large, private, urban university in the mid-Atlantic United States regarding demographics, professional outcomes, and career satisfaction using an electronic survey. Results showed a statistically significant difference in two professional development var...

We address the coordination problem of individuals deciding to join an association that provides a public good and selective benefits to its members, when ability of the association to fulfill its purposes depends on membership size. In a global game formulation, we show that a unique equilibrium with non-trivial membership exists, and we perform meaningful comparative statics. A unique equilib...

Building high performance teams can be difficult, even under the best of conditions. Unstable membership poses an added challenge, and is often considered a valid explanation for the dysfunction or failure of any group that suffers from it. Having group members come and go during the team’s life makes it very difficult, some would say impossible, to foster teamwork. Yet certain task, personnel ...

Whilst there is an array of literature written about students’ skills development, a gap between development and what students can learn through membership professional accounting bodies. This study examines how being connected with body, the Association Chartered Certified Accountants (ACCA) from outset their degree helps awareness developing employability via belonging to profession. Using on...

Fuzzy mining approaches have recently been discussed for deriving fuzzy knowledge. Since items may have their own characteristics, different minimum supports and membership functions may be specified for different items. In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions. In that paper,...

This paper proposes a fusion model to reinforce fuzzy association rules, which contains two main procedures: (1) employing the cumulative probability distribution approach (CPDA) to partition the universe of discourse and build membership functions; and (2) using the AprioriTid mining algorithm to extract fuzzy association rules. The proposed model is more objective and reasonable in determinin...

Different studies have proposedmethods formining fuzzy association rules fromquantitative data, where themembership functions were assumed to be known in advance. However, it is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for mining fuzzy association rules. This paper thus presents a new fuzzy data-mining algorithm for extr...

Data mining is most commonly used in attempts to induce association rules from transaction data. Transactions in real-world applications, however, usually consist of quantitative values. This paper thus proposes a fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions. We present a GA-based framework for finding membership funct...