In this paper we address the problem of nding good viewpoints for three-dimensional straight-line graph drawings. We deene goodness in terms of preserving the relational structure of the graph, and develop two continuous measures of goodness. We develop Voronoi variants to nd the best viewpoints under these measures. We conclude by discussing future research and posing some open problems.

This study considers the goodness of fit test for a class of conditionally heteroscedastic location-scale time series models. For this task, we develop an entropy-type goodness of fit test based on residuals. To examine the asymptotic behavior of the test, we first investigate the asymptotic property of the residual empirical process and then derive the limiting null distribution of the entropy...

We consider the consistency of the Bayes factor in goodness of fit testing for a parametric family of densities against a nonparametric alternative. Sufficient conditions for consistency of the Bayes factor are determined and demonstrated with priors using certain mixtures of triangular densities. Running headline: Bayesian Goodness of Fit Testing

Listener bias is a well-documented phenomenon in linguistics and sociolinguistics research. Listeners have demonstrated bias in assigning personality traits such as intelligence, selfconfidence and likeability to speakers from different language backgrounds (Delamere, 1996). A study by Derwing and Munro (1997), demonstrated that intelligibility scores assigned to nonnative speech were better wh...

Recent research in distributed artificial intelligence (DAI) has shown that different organizational forms to which agents may organize themselves have beneficial and varying effects on the performance of multiagent systems (MAS) regarding scalability, agent drop-out safety and flexibility. This talk presents a concept to enlarge a spectrum of five organizational forms that has been specified w...

We present herein a fully distributed algorithm for group or coalition formation among autonomous agents. The algorithm is based on a distributed computation of maximal cliques (of up to pre-specified size) in the underlying graph that captures the interconnection topology of the agents. Hence, given the current configuration of the agents, the groups that are formed are characterized by a high...

The goodness-of-fit problem has recently attracted attention from the particle physics community. In modern particle experiments, one often performs an unbinned likelihood fit to data. The experimenter then needs to estimate how accurately the fit function approximates the observed distribution. A number of methods have been used to solve this problem in the past [1], and a number of methods ha...

Flood hydrograph simulation is affected by uncertainty in Rainfall – Runoff )RR( parameters. Uncertainty of RR parameters in Gharasoo catchment, part of the great Karkheh river basin, is evaluated by Monte–Carlo (MC) approach. A conceptual-distributed model, called ModClark, was used for basin simulation, in which the basin’s hydrograph was determined using the superposition of runoff generated...

This paper studies the problem of distributed consensus in the presence of spurious sensor information. We propose a new method, De-RANSAC, which allows a multi-agent system to detect outliers—erroneous measurements or incorrect hypotheses—when the sensed information is gathered in a distributed way. The method is an extension of the RANSAC (RANdom SAmple Consensus) algorithm, which leads to a ...