This chapter introduces emotional intelligence as an innovative variable in career decisionmaking processes. It also discusses recent empirical studies and outlines new research and intervention perspectives. In recent years, interest has grown in the significance of individual differences in career decision-making (Gati et al., 2010; Savickas, 2004). Awareness has also gradually increased that...

Reversible logic synthesis is important for the design of conventional logic systems such as adiabatic logic and also for quantum logic systems since all quantum logic gates are necessarily reversible in nature. A framework is presented that improves reversible logic synthesis by employing a dynamically determined variable order for quantum multiple-valued decision diagrams (QMDD). We demonstra...

Editor's Note: These short, critical reviews of recent papers in the Journal, written exclusively by graduate students or postdoctoral fellows, are intended to summarize the important findings of the paper and provide additional insight and commentary. For more information on the format and purpose of the Journal Club, please see Review of Selen et al. Many traditional information-processing mo...

sohrabi and nalchigar (2010) proposed a new data envelopment analysis (dea) model to identify the most efficient decision-making unit (dmu) in presence of imprecise data. in this paper, it is shown that the proposed model is not able to determine the most efficient dmu and is randomly introduced an efficient dmu. in addition, it is shown that this model determines the most efficient dmu in the ...

This paper proposes a kind of bi-level linear programming problem, in which there are two decision makers in a hierarchy and they have a common variable. To deal with this bi-level problem, we introduce a virtual decision maker, who controls the common variable to maximize the sum of the objective functions of the upper and lower level decision maker (the leader and follower). To illustrate the...

Finding the Value of Information About a State Variable in a Markov Decision Process Gilvan C. Souza The Robert H. Smith School of Business, The University of Maryland, College Park, MD, 20742 Phone: 301-405-0628; fax: 301-405-8655; email: [email protected] ABSTRACT In this paper we present a mixed–integer programming formulation that computes the optimal solution for a certain class of Markov dec...

Induction motors are mainly used for variable load applications and it is vital to have a condition monitoring system with capabilities to diagnose motor faults in variable load conditions. The environment noise varies has non-linear relation with motor load and it challenges the decision making capability of the condition monitoring system. This paper addresses the issue of reliable decision m...

An approach based on relative optimal membership degree is proposed to deal with multiple attribute decisionmaking (MADM) problems under risk with weight information unknown and attribute value as linguistic variable. Firstly, the operational laws of linguistic variable are introduced, and risk linguistic decision matrix is transformed into certain linguistic decision matrix by expectation valu...

In this article we discuss variable selection for decision making with focus on decisions regarding when to provide treatment and which treatment to provide. Current variable selection techniques were developed for use in a supervised learning setting where the goal is prediction of the response. These techniques often downplay the importance of interaction variables that have small predictive ...

In this paper, we propose a compact representation of logic functions using Multi-valued Decision Diagrams (MDDs) called heterogeneous MDDs. In a heterogeneous MDD, each variable may take a different domain. By partitioning binary input variables and representing each partition as a single multi-valued variable, we can produce a heterogeneous MDD with smaller memory size than a Reduced Ordered ...