5,689 research outputs found

    Efficiency and converse reduction-consistency in collective choice

    Get PDF
    We consider the problem of selecting a subset of a feasible set over which each agent has a strict preference. We propose an invariance property, converse reduction-consistency, which is the converse of reduction-consistency introduced by Yeh (2006), and study its implications. Our results are two characterizations of the Pareto rule: (1) it is the only rule satisfying efficiency and converse reduction-consistency and (2) it is the only rule satisfying one-agent efficiency, converse reduction-consistency, and reduction-consistency.consistency converse consistency efficiency Pareto rule social choice correspondences.

    Peg

    Get PDF
    Yeh- it\u27s really the berries-some people\u27s names, I mean. I knew a girl once name of Nacy Longnecker..

    On the Upper Bound of Eigenvalues for Elliptic Equations with Higher Orders

    Get PDF
    AbstractLet Ω be a bounded domain in Rm with piecewise smooth boundary. We consider the upper bound of the (n+1)th eigenvalue λn+1 for the two problems [formula] and [formula] where l and r are positive integers with l>r, v is the unit outward normal to ∂Ω, and P(t)=al−rtl+al−r−1tl−1+ . . . +a1tr+1 with the constant coefficients al−r=1, ai≥0 for i=1, 2,..., l−r−1. The bounds of λn+1 are expressed in terms of the preceding eigenvalues. This generalizes the inequalities obtained by Payne, Polya, Weinberger, Protter, Hile, and Yeh

    Development Of Interaction Test Data Generation Strategy With Input-Output Mapping Supports

    Get PDF
    Uniform strength t-way testing (where t represents interaction strength) forms the basis of interaction testing. However, t is rarely uniform in real world as not all interaction faults are solely constituted by these fixed t-interactions. Consequently, a general solution has been introduced: input-output based relationship interaction testing. Although useful, most existing strategy implementations are lacking in terms of the automated input-output mapping support (to translate the symbolic outputs back into actual data form) and test suite generation flexibility. In order to address these aforementioned issues, a non-deterministic input-output based relationship interaction testing strategy, AURA, has been developed. AURA strategy also integrated with post-processing automated input-output mapping support and flexible iteration control capability to support test suite generation flexibility. Experimental results indicated that AURA strategy is generating competitive test suite size against existing strategies (Density, ParaOrder, Union, TVG, PICT, AETG, ACA, GA-N, IPO-N, IPO, Jenny, SA and ACS). Specifically, this strategy is capable to generate the test suite size as optimized as other strategies for certain inputs. Lastly, the post-processing automated input-output mapping support and flexible iteration control capability are evaluated with experiments
    corecore