Ever since von Neumann and Morgenstern published the axiomisation of Expected Utility Theory, there have been a considerable amount of observations appeared in the literature violating the expected utility theory. To make decisions under uncertainty, people generally separate possible outcomes into gains and losses. They are risk averse for gains but risk seeking for losses with very large prob...

This paper provides preference foundations for parametric weighting functions under rank-dependent utility. This is achieved by decomposing the independence axiom of expected utility into separate meaningful properties. These conditions allow us to characterize rank-dependent utility with power and exponential weighting functions. Moreover, by allowing probabilistic risk attitudes to vary withi...

This paper presents an algorithm based on multi-objective approach for network reconfiguration. Multiple objectives are considered for reduction in the system power loss, deviations of the nodes voltage and transformers loading imbalance, while subject to a radial network structure in which all the loads must be energized and no branch current constraint is violated. These three objectives are ...

We present five different eight-point phase-shifting algorithms, each with a different window function. The window function plays a crucial role in determining the phase (wavefront) because it significantly influences phase error. We begin with a simple eight-point algorithm that uses a rectangular window function. We then present alternative algorithms with triangular and bell-shaped window fu...

PURPOSE In order to eventually develop an analytical algorithm with noise characteristics of an iterative algorithm, this technical note develops a window function for the filtered backprojection (FBP) algorithm in tomography that behaves as an iterative Landweber algorithm. METHODS Based on the formulation of the iterative Landweber algorithm, a frequency domain window function is derived fo...

The empirical mode decomposition (EMD) was recently proposed as a new time-frequency analysis tool for nonstationary and nonlinear signals. Although the EMD is able to find the intrinsic modes of a signal and is completely self-adaptive, it does not have any implication on reconstruction optimality. In some situations, when a specified optimality is desired for signal reconstruction, a more fle...