EM procedures using mean field-like approximations for Markov model-based image segmentation

Image segmentation using Markov random fields involves parameter estimation in hidden Markov models for which the EM algorithm is widely used. In practice, difficulties arise due to the dependence structure in the models and approximations are required. Using ideas from the mean field approximation principle, we propose a class of EM-like algorithms in which the computation reduces to dealing with systems of independent variables. Within this class, the simulated field algorithm is a new stochastic algorithm which appears to be the most promising for its good performance and speed, on synthetic and real image experiments.     

Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners

Fingerprints are the oldest and most widely used biometrics for personal identification. Unfortunately, it is usually possible to deceive automatic fingerprint identification systems by presenting a well-duplicated synthetic or dismembered finger. This paper introduces one method to provide fingerprint vitality authentication in order to solve this problem. Detection of a perspiration pattern over the fingertip skin identifies the vitality of a fingerprint. Mapping the two-dimensional fingerprint images into one-dimensional signals, two ensembles of measures, namely static and dynamic measures, are derived for classification. Static patterns as well as temporal changes in dielectric mosaic structure of the skin, caused by perspiration, demonstrate themselves in these signals. Using these measures, this algorithm quantifies the sweating pattern and makes a final decision about vitality of the fingerprint by a neural network trained by examples.     

Directional features in online handwriting recognition

The selection of valuable features is crucial in pattern recognition. In this paper we deal with the issue that part of features originate from directional instead of common linear data. Both for directional and linear data a theory for a statistical modeling exists. However, none of these theories gives an integrated solution to problems, where linear and directional variables are to be combined in a single, multivariate probability density function. We describe a general approach for a unified statistical modeling, given the constraint that variances of the circular variables are small. The method is practically evaluated in the context of our online handwriting recognition system frog on hand and the so-called tangent slope angle feature. Recognition results are compared with two alternative modeling approaches. The proposed solution gives significant improvements in recognition accuracy, computational speed and memory requirements.     

Apollonius tenth problem via radius adjustment and Möbius transformations

The Apollonius Tenth Problem, as defined by Apollonius of Perga circa 200 B.C., has been useful for various applications in addition to its theoretical interest. Even though particular cases have been handled previously, a general framework for the problem has never been reported. Presented in this paper is a theory to handle the Apollonius Tenth Problem by characterizing the spatial relationship among given circles and the desired Apollonius circles. Hence, the given three circles in this paper do not make any assumption regarding on the sizes of circles and the intersection/inclusion relationship among them. The observations made provide an easy-to-code algorithm to compute any desired Apollonius circle which is computationally efficient and robust.     

Complete mobile email management

Years have lapsed since the inauguration of the first Wireless Application Protocol (WAP) application. One of the main reasons for the lukewarm response so far may be attributed to the lack of a “Killer” application. Many companies and developers have attempted to replicate email services (an Internet Killer appplication) within the WAP realm, but till now, no significant success has been reported. This paper will first discuss on the key functions which are lacking in the present WAP-email service, and which are arguably necessary if a much larger user base is to be attracted to these services. A new system will be proposed which can enable the user to send files residing in a remote personal computer (PC) as attachments to his emails using WAP-enabled mobile devices. The implementation of the system will be presented in details. Issue relating to the connection to various types of email servers and the security of the system will also be addressed in the paper.     

Adaptive boundary control for unstable parabolic PDEs—Part II: Estimation-based designs

The certainty equivalence approach to adaptive control is commonly used with two types of identifiers: passivity-based identifiers and swapping identifiers. The “passive” (also known as “observer-based”) approach is the prevalent identification technique in existing results on adaptive control for PDEs but has so far not been used in boundary control problems. The swapping approach, prevalent in finite-dimensional adaptive control is employed here for the first time in adaptive control of PDEs. For a class of unstable parabolic PDEs we prove a separation principle result for both the passive and swapping identifiers combined with the backstepping boundary controllers. The result is applicable in any dimension. For physical reasons we restrict our attention to dimensions no higher than three. The results of the paper are illustrated by simulations.     

On the relationships among latent variables and residuals in PLS path modeling: The formative-reflective scheme

A new approach for the estimation and the validation of a structural equation model with a formative-reflective scheme is presented. The basis of the paper is a proposal for overcoming a potential deficiency of PLS path modeling. In the PLS approach the reflective scheme assumed for the endogenous latent variables (LVs) is inverted; moreover, the model errors are not explicitly taken into account for the estimation of the endogenous LVs. The proposed approach utilizes all the relevant information in the formative manifest variables (MVs) providing solutions which respect the causal structure of the model. The estimation procedure is based on the optimization of the redundancy criterion. The new approach, entitled redundancy analysis approach to path modeling (RA-PM) is compared with both traditional PLS Path Modeling and LISREL methodology, on the basis of real and simulated data.