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This study sought to examine whether international master's recipients (IMRs) who graduated from U.S. institutions have different early career outcomes in major and job match, annual earnings, and career satisfaction from their counterpart domestic master's recipients (DMRs). By analyzing combined datasets of National Survey of Recent College Graduates, this study found that IMRs were 2 times more likely than DMRs to hold jobs that are related to their master's degree. On the other hand, IMRs faced an 8% earnings disadvantage as compared with DMRs. There was no statistically significant difference in job satisfaction between IMRs and DMRs. The policy implications for postsecondary institutions and the U.S. were discussed.

This paper mainly focuses on discrete‐time Markov jump linear stochastic systems (DMJLSSs) with external disturbances and multiplicative noise. Due to the multi‐player in the systems and multi‐objective cost function, the strategy design for these systems is more difficult than the traditional Markov jump stochastic systems. We combine H∞$$ {H}_{\infty } $$ theory with Pareto control and use the weighted sum method of the objective functional of each player to solve the problem of Pareto cooperative game. Four coupled difference matrix‐valued recursion equations (CDMREs) are derived by stochastic bounded real lemma (SBRL). Then, a sufficient and necessary condition for the existence of the Pareto optimal strategy is obtained, and the Pareto solution for every controller is derived under this strategy. A simulation example is given to verify the correctness of the theory. [ABSTRACT FROM AUTHOR]

This paper investigates the Pareto optimal strategy of discrete-time stochastic systems under H ∞ constraint, in which the weighting matrices of the weighted sum cost function can be indefinite. Combining the H ∞ control theory with the indefinite LQ control theory, the generalized difference Riccati equations (GDREs) are obtained. By means of the solution of the GDREs, the Pareto optimal strategy with H ∞ constraint is derived, and the necessary and sufficient conditions for the existence of the strategy are presented. Then the Pareto optimal solution under the worst-case disturbance is solved. Finally, the efficiency of the obtained results is illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

In this paper, the issues about weighted H ∞ performance analysis and H ∞ control for the stochastic switched nonlinear systems (SSNSs) with multiplicative noise are investigated. The mode-dependent average dwell time (MDADT) method is used to deal with the switching in different modes. Firstly, we get a sufficient condition to show that the considered system with all stable subsystems achieves the exponential stability in mean square sense and a specified weighted H ∞ performance, which is extended to the case that both stable and unstable subsystems coexist in terms of second-order Hamilton-Jacobi inequalities (HJIs). Then, by using Takagi-Sugeno (T-S) fuzzy approach, the H ∞ controller for SSNSs is designed via solving a set of linear matrix inequalities (LMIs). Finally, an example is supplied to illustrate the effectiveness of our results. [ABSTRACT FROM AUTHOR]