What makes you win a chess tournament? You should be talented, but the choice of opponents will influence your final ranking as well. This article compares different ranking systems from mathematical point of view, such as the Swiss system and the elimination method and discusses how to handle tiebreaks. In order to judge which system is fair, a theoretical analysis by means of an appropriate e...

In this application paper we explore techniques to classify anomalous structures (defects) in data generated from Molecular Dynamics (MD) simulations of Silicon (Si) atom systems. These systems are studied to understand the processes behind the formation of various defects as they have a profound impact on the electrical and mechanical properties of Silicon. In our prior work [12, 13, 14] we pr...

Given the strong interdisciplinary character of Agent-Based Social Simulation (ABSS), and the difficulties related to ambiguous terminological and methodological assumptions, there is an increasing need to make more explicit the modelling paradigm underlying each research paper or project. In this paper we propose a classification of paradigmatic models in ABSS, which characterise different ont...

This research develops a novel data-integrated simulation to evaluate nurse-patient assignments (SIMNA) based on a real data set provided by a northeast Texas hospital. Tree-based models and kernel density estimation (KDE) were utilized to extract important knowledge from the data for the simulation. Classification and Regression Tree models, data mining tools for prediction and classification,...

A new class of discrete random fields designed for quick simulation and covariance inference under inhomogenous conditions is introduced and studied. Simulation of these correlated fields can be done in a single pass instead of relying on multi-pass convergent methods like the Gibbs Sampler or other Markov Chain Monte Carlo algorithms. The fields are constructed directly from an undirected grap...

The paper provides an overview and a comparison of several tools for visualization of physical simulations. We concentrate on new visualization tools a nd architectures that have been developed during last years (VRToolBox, VRML + Java, etc.). Classification of these approaches is presented together with practical examples including authors’ subjective opinion. This overview has been prepared w...

Covariance matrices have advantages to classify series for time classification. The is segmented into subsequences that its feature points are adopted as the vector. can capture pairwise correlation between vectors. After extraction, next step classification process. Our primary purpose evaluate covariance with kNN (Cov-kNN) under simulation pattern and UCR data sets by optimal neighborhood int...

This paper proposes a spe pattern classification problems using from human forearm muscles. For classification accuracy, a multi-referen class so that the classifier can cover obtained signals for training. The result accuracy through an off-line simulation validate the proposed concept.

The classes in classification tasks often have a natural ordering, and the training and testing examples are often incomplete. We propose a nonlinear ordinal model for classification into ordered classes. Predictive, simulation-based approaches are used to learn from past and classify future incomplete examples. These techniques are illustrated by making prognoses for patients who have suffered...

In this paper the Rank M-Type Radial Basis Function (RMRBF) neural network is used for the classification of Pap smear microscopic images. Simulation results indicate that the proposed neural network consistently outperforms the RBF network in terms of classification capabilities.