background & aim: dental implants should be surrounded with at least 1mm bone. assessing ridge width is an important part to achieve this goal. the use of ridge mapping to assess bone levels available avoids some of the problems associated with ct-scanning. the aim of this study was to assess the accuracy of ridge-mapping compared to ct-scan in determination of bony ridge widths. methods & mate...

The QRAAT (”Quail Ridge Automated Animal Tracking”) system provides ecologists and animal biologists with high resolution animal tracking data. It is comprised of a network of radio receivers deployed across the Quail Ridge Reserve in Napa County, California, and uses radio telemetry to simultaneously track a variety of animals including small field mice, birds, and foxes. QRAAT improves the st...

In this paper we discuss the topic of modeling a moving object in a robot application considering as example the ball movement in a robot soccer environment. The paper focuses on the question of how to estimate the ball velocity reliably even if the ball collides with an obstacle or the observing robot is moving itself. We propose a new estimation algorithm based on a direct estimate using ridg...

CCA and Kernel-CCA are powerful statistical tools that have been successfully employed for feature extraction. However, when working in high-dimensional signal spaces, care has to be taken to avoid overfitting. This paper discusses the influence of ridge penalty regularization on kernel-CCA by relating it to multivariate linear regression(MLR) and partial least squares(PLS). Experimental result...

In this paper we study a dual version of the Ridge Regression procedure. It allows us to perform non-linear regression by constructing a linear regression function in a high dimensional feature space. The feature space representation can result in a large increase in the number of parameters used by the algorithm. In order to combat this \curse of dimensionality", the algorithm allows the use o...

This paper proposes a statistical model for fingerprint ridge orientations. The active fingerprint ridge orientation model (AFROM) iteratively deforms to fit the orientation field (OF) of a fingerprint. The OFs are constrained by the AFROM to vary only in ways according to a training set. The main application of the method is the OF estimation in noisy fingerprints as well as the interpolation ...

Regularized regression methods for linear regression have been developed the last few decades to overcome the flaws of ordinary least squares regression with regard to prediction accuracy. In this chapter, three of these methods (Ridge regression, the Lasso, and the Elastic Net) are incorporated into CATREG, an optimal scaling method for both linear and nonlinear transformation of variables in ...

A Bayesian approach is proposed for coefficient estimation in Tobit quantile regression model. The proposed approach is based on placing a g-prior distribution depends on the quantile level on the regression coefficients. The prior is generalized by introducing a ridge parameter to address important challenges that may arise with censored data, such as multicollinearity and overfitting problems...

In this paper, Coherence Enhancement Diffusion (CED) is boosted feeding external orientation using new robust orientation estimation. In CED, proper scale selection is very important as the gradient vector at that scale reflects the orientation of local ridge. For this purpose a new scheme is proposed in which pre calculated orientation, by using local and integration scales. From the experimen...