Airport air traffic is one of the most important and hardest one among all the airport data forecasts. In this paper, the Markov Chain Monte Carlo (MCMC) method of applied theory of statistics has been introduced into the aviation sector, and the discussion on airport air traffic forecast has been conducted taking Shanghai airport as the application background. MCMC method is designed to solve ...

A robust and efficient face recognition system was developed and evaluated. The each individual face is characterized by 2D-DCT coefficients which follows a finite mixture of doubly truncated Gaussian distribution. In modelling the features vector of the face the number of components (in the mixture model) are determined by hierarchical clustering. The model parameters are estimated using EM al...

Discontinuous signals buried in noise cannot be recovered by linear filtering methods. This paper presents a new class of nonlinear filters in which sets of forward and backward linear predictors and smoothers compete with each other at each timestep. The winner of each competition is granted the right to produce the smoothed estimate at that timestep. This conceptually simple approach to nonli...

Abstract In this paper an approach is presented for robust shift detection of two given images. The new unifying idea is that we determine a shifted delta impulse using some well-known restoration techniques, e.g. the Wiener filtering, constraint restoration, entropy restoration, and Baysian restoration. The used restoration techniques imply the robustness of the presented method. Our approach ...

Epistasis that may explain a large portion of the phenotypic variation for complex economic traits of animals has been ignored in many genetic association studies. A Baysian method was introduced to draw inferences about multilocus genotypic effects based on their marginal posterior distributions by a Gibbs sampler. A simulation study was conducted to provide statistical powers under various un...

In this paper a novel and the new method for face recognition is developed and analyzed using doubly truncated multivariate Gaussian mixture model. The 2D DCT coefficients as the feature vector of the each individual face is modelled by k component mixture of doubly truncated multivariate Gaussian distribution. The number of components and initialization of the model parameter’s are obtained by...

Providing energy conservation services becomes a hot research topic because more and more people attach importance to environmental protection. This research proposes a framework that consists of four process models: appliance recognition, activity-appliances model, unattended appliances detection, and energy conservation service. Appliance recognition model can recognizes the operating states ...

The expression of motion verbs differs between languages. The path of motion, such as crossing or entering, is more prominently featured in path-based languages such as Spanish than in manner-based languages such as English. Here, we revisit the data from a study on manner and path biases in verb lexicalization (Havasi & Snedeker, 2004), and create a hierarchical Baysian computational model to ...

The credibility of politicians is crucial to their persuasiveness as election candidates. The paper applies a parameter-free Baysian source credibility model (integrating trustworthiness and epistemic authority) in a real-life test predicting participants’ posterior belief in the goodness of an unnamed policy after a named candidate has publically supported or attacked it. Two studies test mode...

The 3D body scan technology has recently innovated the way of measuring human bodies and generated a large volume measurements. However, one inherent issue that plagues use resultant database is missing data usually caused by using automatic extractions from scans. Tedious extra efforts have to be made manually fill for various applications. To tackle this problem, paper proposes machine learni...