A robust empirical regularity in decision making is that the negative consequences of an option (i.e., losses) often have a stronger impact on people’s behavior than the positive consequences (i.e., gains). One common explanation for such a gain-loss asymmetry is loss aversion. To model loss aversion in risky decisions, prospect theory (Kahneman & Tversky, 1979) assumes a kinked value function ...

Figure 1 shows the comparison of a general normal based weighting function and the proposed weighting function. They are rendered with voxel cone tracing [Crassin et al. 2011] and spatio-temporal upsampling [Herzog et al. 2010]. The scene has a dynamic object (a galloping horse). In this experiment, the normal based weighting function has a Gaussian distribution [Yang et al. 2008] and its varia...

Input function noise contributes to model-predicted values and should be accounted for during parameter estimation. This problem has been examined in the context of PET data analysis using a noisy image-derived arterial input function. Huesman and Mazoyer (1987 Phys. Med. Biol 32 1569-79) incorporated the effect of error in the measured input function into the objective function and observed a ...

In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method,...

Conventionally, pathway-based analysis assumes that genes in a pathway equally contribute to a biological function, thus assigning uniform weight to genes. However, this assumption has been proved incorrect, and applying uniform weight in the pathway analysis may not be an appropriate approach for the tasks like molecular classification of diseases, as genes in a functional group may have diffe...

PURPOSE The goal of this paper is to extend our recently developed FBP (filtered backprojection) algorithm, which has the same characteristics of an iterative Landweber algorithm, to an FBP algorithm with the same characteristics of an iterative MAP (maximum a posteriori) algorithm. The newly developed FBP algorithm also works when the angular sampling interval is not uniform. The projection no...

Although the regularisation increased the popularity of inverse analysis due to its capability of deriving a stable solution, the significant problem is that the solution depends upon the regularisation parameters chosen. This paper presents a technique for deriving solutions without the use of the parameters, and further an optimisation method, which can work efficiently for problems of concer...

Application of the Metropolis algorithm for forest harvest scheduling is extended by automating the relative weighting of objective function components. Previous applications of the Metropolis algorithm require the user to specify these weights, which demands substantial trial and error in practice. This modification allows for general incorporation of objective function components that are eit...